MASSAGE THERAPY VISITS BY THE AGED:

TESTING A MODIFIED ANDERSEN MODEL

By

Kevin Donald Willison

A thesis submitted in conformity with the requirements

for the degree of Doctor of Philosophy

Graduate Department of Public Health Sciences,

University of Toronto

© Copyright by Kevin D. Willison, 2009

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Massage Therapy Visits By The Aged: Testing A Modified Andersen Model. Kevin Willison, PhD, ,

Dept. of Public Health Sciences, University of Toronto, 2009

Abstract

Growing evidence suggests that chronic health conditions and disability act as reliable

predictors of complementary/ alternative medicine (CAM) use. Such use may have the potential

for some to increase independence and quality of life. Moreover, research indicates that older

people are significant consumers of CAM services. Yet, understanding profiles of older

individuals of these services continues to remain under researched. Here, a widely used type of

CAM was considered – massage therapy (MT).

Towards better understanding MT user profiles, this study tested a modified version of

the Andersen Health Behavior Model to help ascertain if it is useful towards understanding

factors associated with massage therapy (MT) utilization. Respondents represented an elderly

sample (aged 60+) that resided within a large urban city in Ontario Canada (Toronto). Eligible

respondents at the time of the study were non-institutionalized and self-reported having one of

more current chronic illness conditions which they have had for six months or more, and had

been diagnosed by a medical doctor.

Using a quantitative method, retrospective data were gathered using a pre-tested English-

only mail questionnaire, developed specifically for this study. Data were gathered over a period

of 6 months, between late 2000 to mid 2001. Bivariate analysis suggests that inequity exists

whereby the ability to access massage therapy varies according to one’s socioeconomic status.

This is further supported using backwards step-wise regression analysis, whereby one’s total

annual household income was a strong predictor of MT use status. One’s CAM-related health

and social network as well as having back problems also emerged as strong predictors of MT

use. Overall findings suggest that a modified Andersen model as used in this study does have

utility in relation to helping to identify potential factors associated with the utilization of massage

therapy.

Based on regression analysis, findings here suggest, for example, that those with higher

incomes are 1.5 times more likely to use MT. This provides support that there are existing

inequities regarding access to rehabilitation-oriented health care services. With population aging

and rising numbers of people needing restorative and rehabilitation services, study findings will

increasingly have important public health as well as health care policy related implications.

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Acknowledgements

I am deeply indebted to my thesis Committee: Dr. Michael Escobar, Dr. Michael

Goodstadt and my supervisor, Dr. Ted Myers (senior professors of the University of Toronto) for

their time and helpful advice. Moreover, Dr. Robert Mann from the Centre for Addiction and

Mental Health (CAMH - Toronto) also kindly assisted. Naturally, any errors in this document are

entirely my own.

I am particularly indebted to my wife (Qing Zhu, M.Eng., BSc., BEd.) for her patience

and encouragement. She has been my anchor throughout this entire process.

Moreover, I am thankful to former staff of ICT™ Kikkawa College – a massage therapy

teaching school located in Toronto (Canada). Faculty at this school provided valuable insights

regarding the wording of the mail questionnaire developed and used for this study.

I wish to also acknowledge Mr. Bruce Foster. a practicing physiotherapist in Belleville

Ontario. Serving as his summer assistant, Bruce introduced me to the field of rehabilitation, and

strongly encouraged me to learn more. Thank you.

Last but not least, I thank Dr. John Roder PhD. He is a senior investigator affiliated with

the University of Toronto and the Samuel Lunenfeld Research Institute (SLRI). Working with

him for almost three years Dr. Roder encouraged me to run the good race and fight the good

fight. As a friend, I have appreciated his advice and encouragement over the years.

Collectively, the individuals noted above have directly or indirectly encouraged me to

pursue my dream of obtaining a PhD. I am obliged to admit, however, that the more I learn the

more I come to understand how little I actually know. My wife can vouch for this.

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Study Index Page Introduction CHAPTER 1 1.1 The Use of CAM Health Services …………..…………………………….… 1 1.2 Why a Focus on Massage Therapy? ………………………………………. 2 1.3 Why a Focus on the Elderly in this Study? .………………………………. 4 1.4 Use of the Andersen Model in this Study …………………………………. 4 1.5 Purpose of this Study ………………………………………………………. 5 1.6 Methodology ………………………………..……………………………… 6 1.7 Research Questions …………………………………………………….… 6 1.8 Format of this Thesis ……. ………………………………………..……….. 6

Theory CHAPTER 2 2.1 Introduction …………………………………………………….…………. 8 2.2 The Andersen Model: Key Concepts …………………….…..…….……. 8 2.3 Origins of the Andersen Model ………………………………….………… 9 2.4 Uses of Andersen’s Behavioral Model Over Time ……………………… 11 2.5 Use of the Andersen Model to Study Equity Issues Related to Health Care Utilization ….………………….………………….…………………. 13 2.6 Applicability of the Andersen Model to Diverse Issues and Populations .. 15 2.7 The Present Study’s Use of a Modified Andersen Model…………………. 17 2.8 Summary…………..………………………………………………………… 19

Literature Review CHAPTER 3 3.1 Introduction ………………………………………………………………… 20 Part 1 - Contextual Characteristics: 3.2 Changing Demographics ………………………………………………… 21 3.3 The Focus on Cure as a Medical Community Value and Norm…………. 22 3.4 Increasing Use of Complementary and Alternative Medicine …..………. 24 3.5 Use of Health Care Providers ……………………………………………… 25 3.6 Population Morbidity Trends …………….……………………….……….. 26 Part 2 – Individual Characteristics: 3.7 Role of Beliefs and Values - Skepticism …………………….……………. 27 3.8 Satisfaction with Conventional Medicine and its Practitioners ………… 28 3.9 Belief in the Value and Potential of Massage Therapy ……………………. 29 3.10 Potential Role of Health and Social Networks Towards MT Use…….…. 32 3.11 Individual Illness and Morbidity Considerations…………………….…. 33 3.12 Use of CAM as a Self-Care Strategy …………………………………….. 33 3.13 Individual and Contextual Characteristics – Summary……………….. 36 3.14 Potential Limitations of Massage Therapy …………………………….. 36 3.15 Study Assumptions………………………………………………………. 37 Chapter 3 Endnotes …………………………………………………………… 39

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Study Index (continued) Page

Methodology CHAPTER 4 4.1 Research Design……. …………………………………………………. 43 4.2 Using a Mail Questionnaire ……………………………………………… 43 4.3 Research Setting…………………………………………………………… 44 4.4 Outcome Measure ……………….……………………………………….. 44 4.5 Using Human Respondents – Ethics Board Approval…………………… 45 4.6 Criteria for Sample Selection ……………………………………………` 45 4.7 Instrumentation – Development of the Mail Questionnaire……………… 46 4.8 Assessing the Questionnaire with a Pilot Test………………………………. 48 4.9 Independent Variables Used …………………………………………….. 48 4.10 Respondent Predisposing Characteristics ……………………………… 49 4.11 Respondent Enabling Characteristics ……………………………… 55 4.12 Respondent Need Characteristics ……………………………………… 57 4.13 Data Input Coding Procedure ………………………………………… 59 4.14 Developing a Codebook……………………………………………………. 59 4.15 Data Collection Time Period …………………………………………… 60 4.16 Respondent Recruitment Strategies ……………………………………….. 61 4.17 Data Collection Procedure………………………………………………….. 66 4.18 Measures Taken to Increase Questionnaire Response Rates…………. 66 4.19 Data Analysis …………………………………………………………….. 67 4.20 Data Editing and Cleaning Procedures………………………………… 68 4.21 Item Non-response/Missing Data ………………………………………. 69 4.22 Maintenance of Confidentiality – Storage of Collected Data……….. 69

Descriptive and Bivariate Results CHAPTER 5

5.1 Introduction ……………………………………………………………… 70 5.2 Response Rate……….. …………………………………………………. 70 5.3 Reliability of Scales Used……………………………………………………. 72 5.4 Study Demographics …………………………………………………….. 72

Predisposing Characteristics 5.5 Gender Differences between Groups………………………………………. 72 5.6 Marital Status………………………………….…………………………….. 73 5.7 Age Differences between Groups ………………………………………….. 73 5.8 Education of Respondents……..………………………………………. 74 5.9 Education of the Respondent’s Spouses……………………..………..……. 75 5.10 Occupational Background of Respondents ……………………………… 75 5.11 Skepticism …………………………………………………………………. 77 5.12 Satisfaction…………………………………………………………………. 79

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Study Index (continued) Page 5.13 Mastery …………………………………………………………………. 81 5.14 Self-Esteem…………………………………………………………………. 83 Enabling Characteristics: 5.15 Self-assessed Financial Situation………………………………………. 86 5.16 Money for Massage Therapy …………………………………………… 86 5.17 Payment Method for MassageTherapy …………………………………. 87 5.18 Respondent’s and their Spouses Employment Status…………………… 87 5.19 Respondent’s Employment Situation ……………………………………. 88 5.20 Spouse’s Employment Situation ………………………………………….. 88 5.21 Total Annual Household Income ………………………………………… 88 5.22 Added Health Insurance – Beyond OHIP ……………………………….. 89 5.23 Respondent’s Sources of Income…………………………………………… 89 5.24 Living Arrangement ……………………………………………………….. 90 5.25 Housing Arrangement ……………………………………………………… 91 5.26 Health Network Resources ………………………………………………… 91 5.27 Source of Referral to MT …………………………………………………. 93 5.28 Respondent’s Knowledge of Massage Therapy ………………………….. 94 5.29 CAM Knowledge Sources …………………………………………..… ….. 95 Need Characteristics: 5.30 Self-Perceived Health Status ……………………………………………….. 97 5.31 Morbidity …………………………………………………………………. 98 5.32 Chronic Condition Types ……………………………………………….. 99 5.33 ADL/IADL/Mobility ………………………………………………………. 100 5.34 Hospital Days ……………………………………………………………… 101 5.35 Correlation Findings ………………………………………………………. 103 Binary Logistic Regression Results CHAPTER 6 6.1 Introduction ……………………………………………………………… 108 6.2 Second Phase ……………………………………………………………… 111 6.3 Model Fit and Differences between Full Model & Parsimonious Model 114 6.4 Regarding Eliminated Variables …………………………………………… 116 6.5 Summary …………………………………………………………………….. 117 Discussion CHAPTER 7 7.1 Introduction ……………………………………………………………… 120 7.2 Utility of the Andersen Model in Understanding MT Utilization ……….. 121 7.3 Sample Predisposing Characteristics ……....……………………………… 122 7.4 Sample Enabling Characteristics………………………………………….. 124 7.5 Sample Need Characteristics……………………………………………….. 126 7.6 Overview of Regression Analysis Results…………………………………. 127 7.7 Inequity of Access to Massage Therapy: Relevance to Health Care Policy Development and to Health Care Practitioners…………………………….. 128

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Study Index (continued) Page 7.8 Study Relevance to the Aged………………………………………………. 130 7.9 Relevance of Study to Public Health …………………………………….. 131 7.10 Contributions of this Study ……………………………………………….. 134 7.11 Study Limitations………………………………………………………….. 136 7.12 Study Participant Recruitment Issues …………………………………….. 138 7.13 Suggestions for Future Research………………………………………….. 139 7.14 Conclusion ………………………………………………………………… 141 References ………………………………………..…………………………….. 143

Appendixes 1 - Pre-tested (Final) Questionnaire 2 - Study Area (Metropolitan Toronto Map) 3 - Ethics Approval (U. of T.) 4 - Participant Information Sheets 5 - Participant Consent Form

6 - Codebook

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Chapter 1

Introduction

1.1 The Use of CAM Health Services Increasingly, Canadians, both healthy and ill, are turning to complementary and

alternative medicine (CAM) therapies, practices and products (Health Canada, 2001). This

reflects changing health care behavior (Fouladbakhsh and Stommel, 2007) and will likely

continue. Though the notion of CAM remains difficult to define in its entirety, this dissertation

posits CAM as an additional treatment resource (Slee et al., 1996) that is often used in

conjunction with conventional (biomedically-oriented) health care services. This study does not

define CAM as a replacement to conventional medicine, though some individuals do, in fact, use

such as a complete replacement (Egede et al., 2002; Hollenberg, 1998; Kelner and Wellman,

1997; Millar, 2001, Yeh et al., 2002; York, 1999; Sirois and Gick, 2002).

Of the 350 different types of CAM (Chez et al., 1999), this study has chosen to focus on

massage therapy (MT). One of the more frequently used provider-based forms of CAM is MT

(Foster et al., 2000; Lindquist et al, 2003; Williamson et al., 2003, Sohn et al., 2002).

According to Reed’s estimation (1998) approximately three percent of the general

population seeks out registered massage therapy services in Ontario. Statistics Canada supports

this estimate in a report indicating massage therapy use in Ontario to be 4 percent (Health

Reports, 1999). Nationally, Ramsey et al., (1999) have indicated that between 17-24 percent of

Canadians use massage. The Fraser Institute supports this data, noting that the percentage of

Canadians who used massage at the time of their review was 23 % (Health Canada, 2001).

Eisenberg (1998) found that massage use in the United States increased by 62% from

1990 to 1997. In Canada, an Environics Research Group study (n=2,526) indicated MT use in

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1993 to be 4%. By 1999, its use rose to 10% (Berger, 1999). Together, this data supports Ernst’s

(2003) contention that massage therapy is currently experiencing a revival within health care

practice.

1.2 Why Focus on Massage Therapy?

Ontario Canada’s Massage Therapy Act (MTA – 1990, c.27, s.3) outlines massage

therapy’s scope of practice as follows:

“The practice of massage therapy is the assessment of the soft tissue and joints of

the body and the treatment and prevention of physical dysfunction and pain of the

soft tissues and joints, by manipulation to develop, maintain, rehabilitate or

augment physical function, or relieve pain.”

One definition posits massage as the hand motions practiced on the surface of the body

with a therapeutic goal (Boigy, 1950). Cook et al. (1997) define massage as the manipulation of

soft tissues of the body by a trained therapist as a component of a holistic therapeutic

intervention. This particular study considers 50-60 minute full body massage , (versus shorter

intervals, as often found in chair massage techniques). Swedish (“classic”) massage is the most

commonly practiced full body massage method in North America. The College of Massage

Therapists of Ontario (CMTO) sets all registration requirements as directed by the Massage

Therapy Act (1990), the Regulated Health Professions Act (1992) and Ontario’s Health

Professions Regulatory Advisory Council (HPRAC). A person cannot legally practice as a

massage therapist in Ontario unless he or she is registered under the CMTO. This study collected

data via assistance from Ontario registered (licensed) massage therapists only (chapter 4).

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As a manual healing method (Chez et al., 1999), massage therapy overlaps with more

recognized biomedical professions such as physical therapy (Kaptchuck et al., 2001). Currently

the only three provinces in Canada with licensing requirements to practice massage are: Ontario,

British Columbia and, Newfoundland.

Many massage therapy programs consists of a minimum of 2200 hours of training. In

addition, practicing massage therapy in Ontario demands that individuals pass a series of written

and practical examinations in order to obtain a Certificate of Registration from the CMTO.

Hippocrates, the revered father of medicine, was an early advocate of massage and

recommended its use on a continual basis to ease pain and prevent stiffness (Sergen, 1998).

Indeed, the art and science of massage has been used in all cultures throughout history (Vickers,

1993). However, despite its long history, research pertaining to massage is still in its infancy

(Ernst, 2003).

In an Ontario study comparing the opinions, attitudes and knowledge of final year

medical students, including nurses, physiotherapists and pharmacy students, massage therapy

received a high knowledge rating (Baugniet et al., 2000). While physicians generally

demonstrate poor general knowledge of CAM, they appear to be most familiar with such

practices as acupuncture and massage (Suter et al., 2004).

Nurses and other health care professionals have used massage therapy for centuries. As

the predominance of conventional medical practices in North America became established in the

early twentieth century, doctors reassigned time-intensive Semergent physiotherapists shifted

their interest from massage therapy to therapies that make use of high-tech equipment (Snyder

and Wieland, 2003).

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This study does not focus on the efficacy of massage. It is beyond the scope of this study

to do so. Chapter three does provide, however, a brief overview of example potential benefits as

well as limitations of massage therapy.

1.3 Why a Focus on the Elderly in this Study?

In developed countries, older individuals constitute the majority of people with chronic

health problems (Grundy and Sloggett, 2003). In addition, many older individuals suffer from

multiple ailments and find themselves susceptible to decreased balance, strength, endurance,

fitness and flexibility, as well as increased spasticity due to natural aging processes (Rimmer,

1999).

Adults with chronic health conditions are more likely to use CAM than those without

chronic conditions (Egede et al., 2002; Foote-Ardah, 2003; Votova, 2003; Junker et al., 2004;

Sirois and Gick, 2002; Wister et al., 2002). In fact, the projected demand for CAM services by

older individuals is expected to rise (Miller, 2001) since baby boomers are demonstrating a

greater interest in CAM than previous age groups, and the post-baby boomer cohort is following

suit (Lafferty et al,, 2006).

1.4 Use of the Andersen Model in this Study

Health care use models provide health care policy developers, health care practitioners

and community health researchers (etc.) with a better understanding of such facets as the

determinants of health care use. The Andersen model, also known as the Behavioral Model for

Health Services Utilization (Andersen, 1968, Andersen and Newman, 1973, Andersen, 1995,

5

Andersen and Davidson, 2007) – has now enjoyed over four decades of use. In the present study,

it is used as a theoretical and analytical guide.

According to the Andersen model, an individual’s health care use (in this case, MT)

depends on certain conditions that contribute to health care decisions and their resulting

behavior. Moreover, this model helps ascertain whether access opportunities to health care

services are equitable or inequitable by considering which predisposing, enabling or need

characteristics are dominant between users and non-users (this is further expounded in chapter

2). Overall, Andersen’s model helps to determine the impact socio-economic and other variables

have on the use and non-use of such health care services as MT (Sirois and Gick, 2002).

1.5 Purpose of this Study

The primary purpose of this study is to examine the utility of the Andersen model in

relation to distinguishing factors associated with the use of massage therapy. These factors will

be explored by considering profiles of users versus non-users. Currently, a lack of research exists

in relation to understanding profiles of older CAM users in general, and in particular, older users

of specific types of CAM (Cherniack et al., 2002; Foster et al., 2000; Andrews, 2002; Kelner and

Wellman, 2001; Wister et al., 2002; McKenzie and Keller, 2001).

Addressing profiles of CAM users can be helpful to health care and other professionals

wishing to improve their communication with their clients/patients concerning CAM usage

(Sohn et al., 2002). This may help said patients/clients make more informed choices (Boon et al.,

2000). This study is timely as an increasing need for such profiles exists since information and

service needs of older individuals is expected to increase and become more complex as the

population ages (Halton Report, 2007).

6

CAM user profile data could also elicit greater awareness of a patient/client’s perceived

needs, and methods used to help meet these needs. Furthermore, health policy makers could

incorporate such information in their development of relevant frameworks for future policy (Yeh

et al., 2002) as well as facilitating the development and implementation of improved health care

programs (Groft, 2001).

1.6 Methodology

Chapter four presents this study’s methodology, which denotes such information as the

development of a postal questionnaire for this study. Variables incorporated in this study were

guided by modified versions of the Andersen model, and uses Andersen’s constructs of

‘predisposing’, ‘enabling’ and ‘need’ characteristics. These key constructs are elaborated in

chapter two.

1.7 Research Questions

This study poises two research questions for consideration:

1.) Does the Andersen model provide a helpful tool for understanding factors associated

with massage therapy (MT) use?

2.) Does the study reveal inequity of access to MT, among the pre-selected predisposing,

enabling and need variables?

1.8 Format of this Thesis

This introduction is the first chapter of a seven chapter thesis. Chapter two - the theory

chapter – provides an overview and brief history of the Andersen model while chapter three

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provides examples of individual and contextual variables that may be found in modified versions

of the model. Chapter four provides the study’s methodology while chapter five provides the

descriptive results, including correlation data. Chapter six presents backwards step-wise logistic

regression analysis results of the study variables determined to be statistically significant to

massage therapy use status (the dependent variable). Finally, chapter seven offers a discussion of

the findings of this study in relation to the literature and above stated research questions. The

final chapter also provides recommendations and suggestions for further research. This is then

followed by a cited references section and relevant appendices.

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Chapter 2

Theory

2.1 Introduction

As introduced in chapter one, the primary purpose of this study is to examine the utility

of the Andersen model in relation to better understanding factors associated with the use of

massage therapy. In general, the Andersen model is used in this study because: (1) it is one of the

most influential models in the field of health care utilization over the past forty years (Fuller-

Thomson and Redmond, 2008); there is growing evidence that this model is even better suited to

predicting use of community-based discretionary services than to its original purpose of

predicting use of formal health services (Smith, 2003). This is of interest as massage therapy

service sites are usually community-based (versus hospital-based). (2) the Andersen model has

been used to explore a wide variety of issues involving a diverse array of populations. (3) The

Andersen model has been successfully used in exploring issues of equity.

2.2 The Andersen Model: Key Concepts

Andersen (1968) conceptualized health service utilization as behavior patterns influenced

by many co-occurring factors leading to service utilization (Barker and Himchack, 2006). The

Andersen model categorized its independent (i.e., predictor) variables as predisposing, enabling

or need characteristics. In the present study, a modified Andersen model is used to explore the

ways in which predisposing, enabling and need factors contribute to the prediction of massage

therapy use.

“Predisposing characteristics” include those variables that reflect the propensity to use

services, independent of personal circumstances and experiences that may trigger the need for

service use. Moreover they are individual factors present prior to the onset of illness (Wister et

9

al., 2002). In the present study, the predisposing component of the model includes three subsets

of factors: demographic factors such as age, gender, and marital status; attitudinal factors

reflecting values and beliefs that people have about health and health services; and social

structural characteristics such as education and occupation (Andersen, 1995).

“Enabling characteristics” are community and personal resources that facilitate an

individual’s use of health services (Mkanta et al., 2006). They affect an individual’s self-reported

ability to obtain (access) required health care (Baldwin et al., 2001; Chou and Chi, 2004; de

Boer, 1997). Income and health insurance, for example, are likely to enhance service use, while

help from informal support networks may either impede or facilitate use of formal services.

“Need characteristics,” refers to a person’s illness and morbidity traits, including

individual’s perceived needs related to their physical and behavioral health status. In studies

using the Andersen model, need-based factors often represent the most immediate determinants

of service utilization and are the strongest correlates of health care use (Andersen and Newman,

1973; Menec et al., 2001; Miralles et al., 1998; Wolinsky 1983).

In the present study, the outcome measure (i.e., dependent variable) relates to MT use

status. Here, service utilization is measured by respondent self-reports of actual MT service used,

not used, or formerly used.

2.3 Origins of the Andersen Model

While the Andersen model was originally developed to predict service use, it has also

been used successfully to predict unmet needs for services (Smith, 2003). In general, this focus

has been on defining and measuring equitable health care access in order to develop programs

and policies to promote optimal resource use (Mkanta, 2006). Andersen developed his

framework or model in response to his concern about large disparities in kinds and amounts of

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health care people received. In particular, he was concerned about why some people had good

access to care while others did not (Andersen, 2008). A key motivation underlying his initial

“Behavioral Model for Health Service Use” was to identify and measure the multiple

determinants of acute care health services use, and in particular, why families used health

services (Andersen 1968).

The Andersen model has its roots in his assessment of a 1964 survey (of which he was a

study director), which was the third in a series conducted at 5-year intervals by the Health

Information Foundation and the National Opinion Research Centre at the University of Chicago

(Aday and Awe, 1997). In 1964 Andersen developed and empirically tested his model in a

nationwide personal interview survey of 2367 families (Andersen, 1968). The family was

perceived as an appropriate unit of study because it is the primary earning, spending and

consuming unit in our society and is often the unit that makes care-seeking decision.

Andersen’s medical sociology perspective allowed him to clarify the policy implications

of his framework and analysis, in suggesting conditions that facilitate or impede utilization of

health services (Kelner and Wellman, 1997). While there is some question whether Andersen’s

model was meant to predict or explain health care use, Andersen has indicated that he (and his

colleagues) were concerned with both (Andersen, 1995). Throughout the past forty years, the

Andersen model has been subject to many modifications, depending on the focus of the research

and its applications (Andersen, 2008, Aday and Andersen, 1974, 1975, 1981; Andersen and

Aday, 1978; Andersen et al., 1983; Aday et al., 1984; Aday et al., 1980; Andersen 1968, 1995).

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2.4 Uses of Andersen’s Behavioral Model Over Time As cited in Porter (2000:26):

“The Andersen (1968) model was developed and refined (Andersen and Newman 1973) within a behaviorist research tradition. In early studies testing the model, references to “health utilization behavior” (Wan and Arling, 1983:415) were invoked in both theoretical frameworks and discussions of findings. However, when Aday and Andersen (1974) adapted the Andersen model to study access to care, they suggested an epidemiologic interpretation.”

The above citation provides a glimpse of the many modifications to the Andersen model over

time, to suit the purpose of a variety of researchers, including: psychologists, health economists,

medical sociologists and others to explain patterns of service utilization among diverse

populations (Pruchno and McMullen, 2004). Further, revisions and additions have occurred as a

result of emerging issues in health policy and health services delivery, as well as critiques of

earlier versions, and new developments in such areas as medical sociology and health services

research (Andersen, 2008).

In describing the “metamorphosis” of the Andersen model over time, (Gelberg et al.

2000) present three main phases, while more recent work suggest five phases (Andersen, 2008).

Phase 1 spanned in the 1960s when the model was used to assist in understanding why people

used health services (Andersen, 1968, 1995). It was suggested that use of hospital services is

primarily influenced by health needs and demographic characteristics, whereas other services

use, like dental care, were more likely to be explained by social structure, beliefs and enabling

factors (Prucho and McMullen, 2004). In general, the early use of the Andersen model suggested

that service use was a function of a predisposition by people to use health services, including

factors that enable or impede use, and people’s need for care (Andersen, 1968).

Phase 2 was characterized by work done in the 1970s, especially in association with

University of Chicago researchers (i.e., Lu Ann Aday et al.). In one of the Andersen model’s

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later prototypes, Andersen and Newman (1973) highlighted the importance of individual

behavior rather than that of the family (Porter, 2000). This is thought to have arisen from

difficulties in developing utilization measures at the family level (Mkanta et al., 2006). In Phase

2 saw greater elaboration of the measures of health services use specific to particular conditions

and episodes of illness, and greater emphasis on consumer satisfaction. Greater emphasis was

also placed on the health care system, in recognition of the importance of national health policies

and the resources and organization of the health care system in determining the population’s

health services use (Andersen, 2008).

Phase 3 occurred in 1980s to the 1990s. More scholars began to use the Andersen model

in examining clusters of services rather than individual services (Pruchno and McMullen, 2004).

This phase also saw greater focus on personal health care practices such as diet and exercise,

with an emphasis on the maintenance and improvement of health status. This was encouraged by

the recognition that health services should help maintain and improve health. Consequently,

during this period, health status was added as one of the model’s outcome measures (Andersen,

2008).

In Phase 4 (1990s), greater recognition was given to the Andersen model’s dynamic

nature represented by a dialectical interplay amongst the model’s predisposing, enabling and

need domains (Andersen 1995, Andersen et al. 2007). This is shown, for example, in seniors’

use of mobility and technical aids, with use predicted by both need and predisposing

characteristics (de Klerk et al., 1997).

Phase 4 also witnessed the introduction of feedback loops whereby outcomes are

considered to have an effect on subsequent predisposing, enabling and need characteristics of the

population and their use of health services. Here, the Andersen model assumes that a sequence of

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conditions contributes to the volume and type of health services a person uses (de Boer et al.,

1997), thereby adding complexity to the Andersen model. For example, Wellman and Kelner

(2001) indicate that once a person has used a CAM therapist, he or she may become more apt to

try other CAM therapies. This is supported by McClennon-Leong (1997) who found that it is not

uncommon for users of one CAM service to use other forms of CAM services concurrently.

Although the primary focus of the Andersen model has been to explain health services

utilization, within Phase 5 (i.e., the current phase), investigators have begun to expand the

conceptualization of service utilization to include unmet service needs as well as receipt of

services (Pruchno and McMullen, 2004). Moreover, emphasis is now placed on both the

contextual and individual determinants of health service use. Contextual characteristics consider,

for example, the nature of the health care system and how this may affect health care services

use.

2.5 Use of the Andersen Model to Study Equity Issues related to Health Care Utilization

As indicated earlier, the Andersen model has been used to explore issues of equity. For

Andersen and his colleagues, an individual’s access to health care services depends on access

opportunities that may be differentiated as being equitable or inequitable which, in turn, may be

captured using Andersen’s constructs of ‘predisposing’, ‘enabling’ and ‘need’ characteristics.

Equitable access to health care occurs when predisposing demographic and need variables

account for most of the variance in utilization. When there is equity, need characteristics are

considered as being the strongest predictors of utilization (Andersen, 1995). Inequitable access

occurs when enabling factors account for most of the variance. (Andersen, 2008; Fuller-

Thompson and Redmond, 2008). An example of inequitable access occurs when enabling

14

resources such as income determine health services distribution (Andersen, 1968; Chou and Chi,

2004).

Issues of ‘equity’ are relevant to the public health community. It is a topic receiving

increased attention in Canada. For example, in June, 2008, the annual report of Canada’s Chief

Public Health Officer drew attention to (in)equity in Canada (Kirkpatrick, 2009). Health

inequities have recently been defined as: “... the presence of disparities in health and in its key

demographic, social, economic and political determinants that are systematically associated with

social advantage /disadvantage.” (Ouellette-Kuntz et al., 2009: S9).

The current use of the term “inequalities” within public health sometimes includes the

additional element of inequity, or being unjust or unfair. For example, Whitehead (1990:10)

states that: “The term inequity has a moral and ethical dimension. It refers to differences which

are unnecessary and avoidable but, in addition, are also considered unfair and unjust... Our aim

is not to eliminate all health differences, for that would be impossible, but rather to reduce or

eliminate those that result from factors which are avoidable and unfair .... Equity in health

implies that ideally everyone should have a fair opportunity to attain their full health potential

and, more pragmatically, that no one should be disadvantaged from achieving this potential if it

can be avoided.”

Currently, a biomedical approach to health care is dominant in Canada. This orientation

tends to emphasize cure rather than providing equal attention to chronic (long-term, often non-

curable) conditions (see Chapter 3). As a consequence, those with chronic health conditions

might not attain their full health potential. Moreover, those with chronic health conditions

usually have the added burden to have to pay out-of-pocket for rehabilitative / restorative health

care services like massage therapy (and, in Ontario, physiotherapy). This can lead to inequitable

15

access to such regulated health services as massage, which for some could serve as a chronic

illness / chronic disease management resource.

2.6 Applicability of the Andersen Model to Diverse Issues and Populations

The Andersen model has also been broadly applied in predicting the utilization of home

care (Porter, 2000); support groups (Biegel et al., 2004); community-based services among the

homeless (Wong, 1999); ambulant social care by the elderly (Crets, 1996); publicly funded

health care services (Chou and Chi, 2004); children’s health services (Thind and Cruz, 2003);

psychiatric hospitals (Choi et al., 2009); community based services (Barker and Himchak, 2006);

formal and informal long-term care services (Bradley et al., 2004; Opoku et al., 2006), formal

support services as well as prescription and non-prescription drugs, mental health care and,

social services (Aday and Awe, 1998).

As has already been indicated, the Andersen model has been employed in studying a

wide variety of issues, and with a range of vulnerable populations (Gelberg et al., 2000),

including the chronically-ill elderly. The Andersen model has been used as a theoretical and

empirically analytical guide to better understand health access issues for such vulnerable

populations as: individuals with AIDS (Anthony et al., 2007; Mkanta and Uphold, 2006), the

impoverished (Fuller-Thomson and Redmond, 2008), the homeless (Gelberg et al., 2000), those

suffering from severe depression (Choi et al., 2006), and those with a wide range of health

conditions such as respiratory illness (Thind and Andersen, 2003).

The Andersen model has also been employed with varying degrees of explanatory

success in several early studies using surveys of large national samples (Andersen, 1968;

Andersen and Anderson, 1979; Andersen, Kravits and Anderson, 1975; Dutton, 1978). In 1995,

16

Wolinsky (et al) showed constructs from the model to be associated with hospital and physician

use by older adults. Potvin et al (1995) used the Andersen model to predict mammography use,

while Evans and Stoddart (1990) used the Andersen model in showing that personal health

practices such as diet and exercise interact with use of formal health services to influence

outcome.

Of particular relevance to the present study, the Andersen model has also been widely

applied in research on use of services by the elderly (Aday and Awe, 1997; Bradley et al., 2004;

Barker and Himchak, 2006; Cheung et al., 2007; Bass et al., 1992; Bazargan et al., 1998;

Benjamins and Brown, 2004; Borrayo et al., 2002; Chou and Chi, 2004; Kelner and Wellman,

1997; Wister et al., 2002; Wolinsky, 1994; Wolinsky et al., 1995). These studies have found that

service utilization is influenced by such factors as: education, gender, marital status and living

arrangements (as predisposing characteristics); family income, contact with community agencies

and availability of transportation (as enabling factors); plus, need factors like activities of daily

living (ADL) ability and, having chronic health conditions (Chou et al., 2008).

The large diversity of study populations that has been explored to date using the

Andersen model speaks well of the model’s flexibility. Specifically, it grants researchers the

discretion to modify the model in accordance with the characteristics of the population being

studied, therefore allowing researchers to include or exclude variables within its broad

framework (Fouladbakhsh and Stommel, 2007).

Modifications to the model have allowed investigators to examine the use of health

services, as well as other contributing factors influencing access, availability and barriers to

services (Barker and Himchak, 2006). Andersen notes that these revisions have mainly resulted

in additions to the model and, have not changed its fundamental components or their

17

relationships (Andersen, 2008). Consistent within this framework, for example, has been use of

the notions of individual ‘predisposing’, ‘enabling’ and ‘need’ factors.

Since its inception in 1968, the Andersen model has tended to focus on the utilization of

biomedically-oriented health care services. The present study expands the use of the model by

considering massage therapy use as an outcome variable. In Ontario (Canada) massage therapy is

a regulated health care service (under the Regulated Health Practitioners Act) placing it outside

the biomedical realm. In Canada, massage is labeled by the medical establishment as “non-

medically necessary” (therefore, not publicly fundable), as well as an “alternative” type of health

care.

2.7 The Present Study’s use of a Modified Andersen Model

Modifications of the Andersen model occur when researchers use the model to study

unique outcomes. In the present study, a modified Andersen model (see Table 2.1) was used to

expand on the limited previous research regarding use of massage therapy services by older

adults, who have one or more self-reported chronic health conditions. These modifications

include: First, it was recognized that “occupation” is complex variable, wherein no single

measure of this construct is adequate. Secondly, enabling characteristics were expanded to

include the construct of “family network” wherein health and social network questions were

added. This acknowledges lessons learned from the Network-Episode Model of Utilization

(NEM). The NEM stresses the importance of social networks on health care utilization

(Pescosolido, 1991; Pescosolido 1998a, 1998b). Further, this is in response to critiques of the

Andersen model (e.g., Strain, 1990) that it lacks an emphasis on social support and social

networks.

18

Table 2.1 Summary of Study-Related Variables Guided by the Andersen Model Construct Original

Andersen Model Previous Modified Andersen Models

Current Modified Model

PREDISPOSING

Age Gender Education Occupation Marital Status Skepticism

Mastery Self-esteem Satisfaction

Last occupation Usual occupation Self-employed

Construct Original

Andersen Model Previous Modified Andersen Models

Current Modified Model

ENABLING

Insurance Income

Current money meets needs Number of people in household Family network

Subsidized housing Health and social network (F1-F3)

Construct Original Andersen

Model Previous Modified Andersen Models

Current Modified Model

NEED

Morbidity (chronic condition types) Number of chronic conditions

Health status (population and cohort compared) ADL/IADL

Number of hospital days

19

Thirdly, based on a review of the literature there is a strong indication that socioeconomic status

(SES) can impact CAM utilization. Therefore, I included the following SES related measure:

‘subsidized housing.’ My hypothesis at the time of inclusion of this variable was that individuals

living in subsidized housing likely had less disposable income and, therefore, were more likely to

not use non-publicly funded types of health care, like massage. Fourthly, the modified Andersen

model’s “need characteristics” included ‘”number of hospital days” as a further measure of

health status. Fifth and last, the present study includes psychosocial variables which may impact

MT service use. These include: self-esteem, skepticism, satisfaction and, mastery. This is in

response to criticisms (e.g., Bradley et al., 2002) that, although the Andersen model includes

“beliefs” as a predisposing characteristic, which include attitudes toward health services

(Andersen and Newman, 1973), limited attention has been given to psychosocial factors.

2.8 Summary

As far as I am aware this study is the first of its kind in Canada (and possibly in North

America) that explores factors associated with massage therapy (MT) use by the aged, from the

perspective of an expanded Andersen model. Despite limitations of this model this study

provides a contribution to knowledge in a previously neglected area of study. Moreover, the

model used is the most thorough and advanced of its kind to be used for this study.

We now turn our attention to a further review of the literature as it relates to the Andersen

model, as we briefly consider the potential selected individual and contextual variables may have

upon MT utilization.

20

Chapter 3

Literature Review

3.1 Introduction

This chapter investigates how the Andersen model furthers our understanding of potential

factors associated with massage therapy utilization. Specifically, the chapter considers both

individual and contextual determinants. Whether one investigates individual or contextual

determinants separately or together, the Andersen model ultimately aims to understand health

behavior of individuals (Andersen and Davidson, 2007).

We will begin by considering potential contextual factors. In this case, ‘context’ includes

health organization and provider-related factors, as well as community characteristics. Whereas

the major components of contextual characteristics operate in a similar way to individual

characteristics – which enable us to use Andersen’s constructs of predisposing, enabling and

need indicators, contextual characteristics function at a community and/or societal level. For

instance, when dealing with predisposing contextual characteristics, societal norms and values,

related specifically to health care are of interest. The ‘enabling’ contextual characteristics

considered in this dissertation relate to the use of health care providers in general, while ‘need’

contextual characteristics consider such aspects as population health characteristics, including

morbidity trends.

Bausell et al., (2001) note that the decision to use CAM1 represents a complex and

multidimensional choice. Issues of aging associated with seniors’ use of CAM occur in social,

political, economic and environmental contexts. Determining the types of contexts and their

1 For numbers 1-6 inserted in the text, refer to this chapter’s endnotes.

21

potential impact on health care utilization has been a primary interest in research undertaken by

Andersen and his colleagues for over thirty years.

This chapter aims to present a cross-sectional overview of the literature on selected

topics and issues that impact CAM use, on an individual as well as contextual level. We begin by

considering an example with predisposing contextual characteristics, which could potentially

impact massage therapy utilization.

Part 1 – Example Contextual Characteristics

Predisposing Contextual Characteristics 3.2 Changing Demographics

The prevalence of chronic illnesses increases with age (Schultz and Kopec, 2003). Since

complementary and alternative medicine users (henceforth CAM) typically report having one or

more chronic conditions (Ramsey et al., 2001), the future demand for CAM by older people has

the potential to increase significantly (Millar, 2001).

The Canadian population, like many populations around the world, is aging. In particular,

people over the age of 80 in Canada have become the fastest growing segment of the population,

a segment that has grown a remarkable 41 percent since the past decade. In 2001, one Canadian

in eight was aged 65 years or over and research has projected that by the year 2026, this number

will change to one Canadian in five (Abelsohn, 2002). Thomas et al (2007) document that the

population aged 65 or older is projected to represent 18.4 percent of Canada by 2021 (compared

with 14.1 percent reported in 2001).

In 2001, Statistics Canada recorded the median age to be 36.7, an increase of 2.3 years

from 35.3 in 1996 (Statistics Canada, 2001). However, the numbers differ according to

geographic communities; for example, Brampton’s (Ontario) median age was 28, while Owen

22

Sound’s (Ontario) was 46 (Statistics Canada, 2001). In Toronto (Canada), where this study took

place, the median age was noted at 36 and climbing (Toronto, 2002). Andersen and Davidson

(2007) argue that community demographics can impact the mix of available health care services.

To that end, older communities should have health services and facilities that differ from

younger communities. Overall, a consideration of local and regional demographics facilitates our

understanding of potential changes in utilization of health care services such as CAM and

enables us to improve health care planning and expenditures.

3.3 The Focus on Cure as a Medical Community Value and Norm

In North America, calls for improving health care services for the aged – with a

special focus on meeting older individuals’ rehabilitation needs – have been muffled by

existing health care policies and practices that purport a predominantly cure-focused

approach. As a consequence, dominant Western (orthodox) medical practices are

considered to be largely ineffective and inappropriate in addressing the care needs of

those with long-term, incurable health problems (Cohen et al., 2007; Rimmer, 1999;

Whitehouse, 1999; Foote-Ardah, 2003; Seymour, 1991; Liaschenko et al., 1991;

Mechanic, 1993; Mitzdorf et al., 1999). Indeed, critics argue that conventional

(biomedical/ allopathic) medicine offers an overly reductionistic, organ specific,

mechanistic and depersonalized approach to patients (Chez et al., 1999).

On a macro level, convincing evidence exists that a growing number of people are

turning to CAM practices such as massage therapy, because of discontent with the current health

care system. Chronic disease problems now account for more than fifty percent of the global

burden of diseases, but in spite of such an increasing and often greater proportion of community

23

health problems that are chronically (non-cure) oriented, world-wide health care systems and

their corresponding infrastructures remain dominantly cure oriented (Epping-Jordan 2005).

One model of care cannot provide all of the expertise needed to rehabilitate a given

individual. However, the dominance of biomedically driven health care systems remains ill-

equipped to meet population needs for comprehensive health care for chronic conditions

(Epping-Jordan 2005). To complicate matters, current funding mechanisms and established

health care policies perpetuate this short-coming (Dwyer 2004). One potential consequence is a

reduced emphasis and availability of rehabilitation oriented health care services and resources for

individuals with chronic conditions.

According to Lorig et al., (2001), while major advances have been made in surgical and

medical care for chronic conditions (e.g. hip replacements), little has been done to enable

individuals to manage on-going chronic conditions over the long term. A significant proportion

of the conventional health care system may actually be inefficient and ineffective (Evans et al.,

1994). In a system designed for acute rather than chronic care, the urgent need to bring chronic

illness under optimal management is often neglected (Bodenheimer et al., 2002). Lomas et al.,

(1994) argued that it is becoming increasingly obvious that high inputs towards medical care

(e.g. money and health care resources) do not equal improved health status, decreased morbidity

and improved quality of life. Previous research also supports this stance; for instance, in his

extension of the work of Rene Dubos, McKeown (1979) argued that progress in longevity are

due to improved environmental conditions such as better housing, safer food, enhanced nutrition

and the development of sewers and access to clean water rather than the outcome of improved

medical treatments (McKeown, 1979; also cited in Torrance, 1987). McKinlay et al (1977;

1989), have also noted the questionable contributions of medical measures indicating, for

24

instance, that morbidity has increased for certain subgroups. On the whole researchers have

stressed that a more critical look at our health care system is required to ascertain and improve its

current strengths, assumptions and, weaknesses.

3.4 Increasing Use of Complementary and Alternative Medicine

Though health care systems remain out of step with contemporary health care needs of

aging citizens (CHSRF, 2006), the general public is ushering in a form of emancipation, which

proactively pursues alternative forms of self-care. The rise in CAM use is explained in part as the

result of dissatisfaction or disappointment with allopathic medical treatment (Shmueli and

Shuval 2006). 2

Discontent with mainstream medicine is further exacerbated by long waiting lists for

elective surgeries and less personalised care. A poll conducted by the National Post (November

2001) found that 62% of those surveyed felt that health-care services, including hospitals, have

been getting worse over the last couple of years. Researchers such as Mitzdorf et al., (1999)

suggest that negative experiences with conventional medicine and perceived positive aspects of

CAM act as key reasons for people to seek out CAM treatments. Dissatisfaction with an

increasingly technical approach to medicine, a fragmentation of care due to specialization, and a

loss of bedside skills, contribute largely to the increased popularity of CAM therapies (Downer

et al., 1994).

Having one or more chronic diseases is significantly and independently related to the use

of complementary and alternative medicine (Blais et al. 1997, Burgmann et al. 2004, Chez et al.

1999, Egede et al. 2002, Furnham et al. 2000, Junker et al. 2004, McKenzie and Keller 2001,

Kelner and Wellman 1997, McClennon-Leong 1997, Sirois and Gick 2002, Wellman et al. 2001,

25

Wister et al. 2002). Demand for CAM services is expected to grow as a result of population

aging and will likely increase substantially among people who will experience one or more

chronic health problems (Cawley 1997, Dossey 1997, Millar 2001, Newman et al., 2004; Hoey

1998). Researchers such as Eisenberg et al. (1998) support this projection in their report that

massage therapy use increased from 62% from 1990 to 1997 in the United States. A further study

conducted by the Environics Research Group (n = 2,526) found that massage therapy (MT) use

in Canada rose six percent between 1993 and 1999 (Berger, 1999).3 On the whole, a growing

number of people are turning to CAM, including the elderly (Andrews, 2002; McKenzie and

Keller, 2001).

Enabling Contextual Characteristics 3.5 Use of Health Care Providers

According to Lorig et al., (2001), a chronic health condition is a principal cause for

seeking health care. The presence of a chronic health condition represents a risk factor for such

outcomes as institutionalization as well as a higher risk for superimposed events including

injuries and illnesses (German, 1989). Consequently, the chronically ill and disabled constitute a

vulnerable population (Shi, 2001).

Though studies demonstrate that the number of physician consultations and procedures

tend to grow with age (Saunders et al., 2001), Roos et al., (1992) report that the elderly are not

necessarily high users of health-care services. Despite their poor health status, elderly rates of

physician contact is similar to that of younger groups, and their rates of referral to specialists are

even lower. Furthermore, evidence exists to disprove the claims that the ill elderly in Canada use

a larger than average amount of health care services compared with the well elderly. Healthy

26

seniors are the ones who have driven the most significant increases in healthcare use (CHSRF,

2001).

Baugniet and Boon (2000) emphasizes the basic ethical responsibility of physicians and

other health care workers not be biased either for or against CAM; rather, they should be

prepared to evaluate each CAM approach based on the current scientific literature. 4 Further he

urges that it is incumbent upon physicians and others to be able to distinguish among

complementary, alternative and fringe approaches and to advise consumers of CAM accordingly.

For some patients, this could include insisting upon professional certification. Bussing et al.

(2006) address the concern that since self-care strategies (including MT use) are commonly

employed and appear to co-exist with (other) professional treatment, healthcare providers need to

actively explore individual use of such strategies to ensure that they not interfere with prescribed

treatments. However, it remains difficult to ascertaining exactly who is using CAM, since CAM

users often choose not to disclose their use (Chez et al. 1999).

Need Contextual Characteristics 3.6 Population Morbidity Trends

Older individuals now constitute the majority of those with health problems in developed

countries (Grundy and Sloggett, 2003). While the majority of seniors in Canada are healthy and

independent, they are nevertheless susceptible to chronic health disorders (Williams 1990;

Morawsky, 1995; Turpie et al., 1997). Most non-institutionalized elders have at least one chronic

medical condition; many have multiple ailments (Morawski and Davis, 1998; Eliopoulos, 1991;

Wallace et al. 1992; Knottnerus et al. 1992; Cassel et al., 1991). Sherbourne et al (1992) report

27

that the number of elderly individuals who are functionally impaired due to chronic disease

increases from 41% for those aged 54-74 years to over 60% for those 85 years and older.

The overall rise in use of regulated forms of CAM may be attributed in part to increased

life expectancy, population aging and the growing number of individuals who choose to self-

manage their chronic condition. In spite of this projection, little research has been undertaken to

examine the characteristics of elderly individuals who use CAM practices (Cherniack et al.,

2001; Foster et al., 2000; Thorne et al., 2002). Only recently have studies focused serious

attention on reasons for CAM-related use (Schuster et al., 2004). According to Health Canada,

greater, more in-depth analysis of user characteristics of complementary and alternative health

care services “would be a valuable area for further study” (Health Canada, 2003:13).

Part 2 – Example Individual Characteristics

Determining the influence of contextual determinants on access to care has presented

many analytic challenges (Andersen, 2007). As a result, many empirical studies on service

utilization (Bradley et al., 2002; Mkanta et al., 2006) have focused on individual factors. This

thesis continues this trend and considers individual factors such as a person’s unique beliefs and

values as well as one’s opinion on such topics as self-care and health promoting behavior.

Predisposing Individual Characteristics

3.7 Role of Beliefs and Values - Skepticism

Individuals who exhibit greater levels of skepticism towards conventional medicine, or a

lack of satisfaction with conventional therapeutic methods, often try CAM (Moser et al., 1996).

28

Heavy users of CAM health practitioners have been found to be the most critical of physicians

(Health Canada, 2001). According to King (1985:549), the growth of CAM is based on a

continuing human search for well-being and meaning. In some areas this search is turning away

from science and expressing disillusionment with science’s potential unhealthy outcomes, such

as iatrogenesis.

Verhoef et al., (1990) have reported that fewer CAM users (54%) than nonusers (85%)

expressed satisfaction with conventional medicine (p < 0.01) and a greater number of CAM users

(49%) than nonusers were very skeptical of conventional medicine (p < 0.01). A further survey

of 65 patients who attended a CAM clinic reported that their attendance was due to the failure of

conventional medicine (Vincent et al., 1996). Furnham and Bhagrath (1993) revealed similar

findings. Clawson et al. (2001) added to the skepticism surrounding the health care system by

reporting that conventional (main-stream) medical practitioners were often poorly prepared, if

prepared at all, to treat musculoskeletal conditions effectively. Yet, musculoskeletal dysfunctions

remain one of the most prevalent clusters of chronic conditions amongst populations such as the

elderly (Westert et al., 2001). The literature suggests that certain people are turning to CAM

because of their disenchantment with the care they receive from their traditional physicians.

3.8 Satisfaction with Conventional Medicine and its Practitioners

However, Downer (1994) found that most of the patients in her study who used CAM

were satisfied with conventional treatment. Similarly, Donnelly et al., (1985) found no support to

indicate that those who used CAM did so because they were disgruntled with conventional

medicine. Further, there is support for the contention that most CAM users not only have

29

received prior conventional treatment (Richardson et al., 2001) but also continue to use

conventional medicine (Health Canada, 2001; Verhoef et al., 1994; York, 1999).

Statistics Canada reports that Canadians continue to rely on mainstream (conventional)

health care while increasingly turning to CAM (Millar, 2001). In fact, the increased use of CAM

services appear in conjunction with conventional medical services (Downer et al., 1994; Egede et

al., 2002; Kelner and Wellman 1997a and 1997b; Cassileth et al., 1984; Verhoef et al., 1994;

Vincent et al., 1996; Yeh et al., 2002; York, 1999). Eisenberg et al. (1993) estimated that one in

five individuals who consults a medical doctor for a principal condition also sees a CAM

therapist. Recently, the same researchers re-estimated the number to be one in three (Eisenberg et

al., 1998). Furnham and Bhagrath (1993) suggest this may occur since patients (clients) ‘hedge

their bets’ by staying with conventional practitioners while also using CAM.

3.9 Belief in the Value and Potential of Massage Therapy

Many believe in the usefulness of massage for a variety of health conditions (Bausell et

al., 2001). While “CAM” remains difficult to define 4 an overall positive belief in the methods of

CAM is a reason for its use (Kelner and Wellman, 1997a; Risberg et al., 1997; Vincent et al.,

1994). Such beliefs could include: (a) an all encompassing theory or philosophy which views

“health” as a balance of forces within the body and healing as the restoration of balance, (b) a

holistic approach and (c) an emphasis on each individual’s own responsibility for health (Ernst

1994; Kelner and Wellman 1997). Vincent and Furnham (1996) add the following: (1) a belief in

the positive value of alternative health care; (2) concern about the adverse side-effects of medical

care; (3) previous experience of conventional medicine as ineffective; and, (4) poor

communication between patients and conventional medical practitioners. In short, much of the

30

literature suggests that an individual’s perception of the benefits and limitations of CAM

severely impacts its use.

Massage is noted for its potential to alleviate chronic tension headaches (Quinn et al.,

2002), mobilize stiff joints, subdue muscle tension and chronic pain in general, reduce swelling

and inflammation and, lessen stress (Segen, 1998). It is one of the most common therapies for

treating rheumatic disease in industrialized countries (Kolasinski, 2001). In addition, the general

population is resorting to massage therapy with increasing frequency to treat pain and burnout. In

recent randomized controlled trials, massage therapy has been shown to be effective in reducing

a variety of negative mood states including anxiety, confusion, fatigue and depression (Katz et

al., 1999). This is an important finding given that the chronically ill are often susceptible to

somatic and depressive symptoms including social withdrawal (Roy, 1992).

Further, massage use helps promote relaxation, improve blood flow, improve co-

ordination and flexibility, increase energy, elevate a sense of well-being and mood, and finally,

to deepen and lengthen sleep. Massage also aids in decreasing risk of injury from falls, which is

one example of preventative strategies that are unique to the elderly (German, 1989). Among the

senior population, falls are reported to be responsible for 64 percent of injuries reported in 1990

and 84 percent of injury-related hospital admissions (Abelsohn, 2002a).

According to members of Standford University’s School of Medicine

(http://camps.stanford.edu/), complementary and alternative medicine (CAM) therapies, such as

massage, have the potential to enhance successful ageing, reduce frailty, and increase

independence and quality of life in older persons, especially those therapies that may decrease

the impact of cardiovascular and musculoskeletal diseases. Doing so also has the potential to

alleviate the strain on health care systems.

31

Along with acupuncture, chiropractic, and homeopathy, massage therapy is one of the

more frequently used provider-based CAM practices currently used in North America (Sirois and

Gick, 2002; Eisenburg et al., 1998; Mulkins et al., 2002; Palinkas et al., 2000; Sohn et al., 2002).

In fact, older adults are among the growing number of users of CAM in general (McKenzie and

Keller, 2001). There is also an indication that awareness of CAM therapies among the older

population is high (Aus, 1993).

The Canadian Medical Association notes that, while most seniors are not sick, they

continue to live independently in their community with help from support services from time to

time (CMA, 1987). For example, the use of massage shows promise to help seniors remain

independent with their home and/or community (Falvo et al., 1990). Used alongside

conventional medicine, it remains possible that massage serves as a preventative measure to help

avoid further injury or illness (Mayo, 2005). The prevention or delay of acute hospital and

nursing home care has a double potential benefit to help reduce health care costs and to enhance

the quality of life of its users (German, 1989). Moreover, as most unconventional therapies tend

to involve fewer drugs and less technology, the cost of CAM is touted as being considerably less

than standard medical treatment (Goldstein et al., 1988), though greater research is needed to

substantiate this.

CAM practices such as massage therapy are perceived to be being patient-centered, since

they expend considerable attention and time on the needs and feelings of the patient (Eisenberg,

2002; Goldstein et al., 1988). As a holistic approach, CAM tends to focus on the entire person

instead of a set of symptoms and is reputed to be gentler than conventional medicine (Sorgen,

1998). King (1985) notes that the content and style of CAM practice is often immensely

reassuring, involving close attention to even “trivial” symptoms and signs, and offering

32

procedures which allow close, personal contact between the therapist and the client. CAM

practitioners often have long consultation sessions with their patients, which would be difficult to

match in a busy clinic (Smart et al., 1986).

On the whole, when dealing with chronic, debilitating conditions an increasing

number of people perceive CAM therapies, such as massage, as more effective than a

solely conventional (orthodox) medical care approach (Eisenberg et al., 2001). In

addition, growing public interest in complimentary therapies has resulted in a resurgence

of interest in the therapeutic value of such modalities as massage (Smith et al., 2002).

An Enabling Individual Characteristic

3.10 Potential Role of Health and Social Networks Towards MT Use Montbriand (2000), as cited in Murray et al., (2006:45), notes that engagement with what

is classified as alternative therapies are frequently initiated or prescribed by self, family, one’s

network of friends, or an alternative health care practitioner. In particular, family relationships

represent an important type of social network. According to Gallegos-Carrillo et al. (2009), this

becomes increasingly true as the population gets older and more individuals have been out of the

workforce (a significant source of peer relationships), for longer periods of time.

In general, social and family networks are important to the elderly, as they contribute to

elderly individuals’ sense of well-being and acceptance. Familial and social relations frequently

also have direct health benefits, including reduced institutionalization (Tulchinsky and

Varavikova, 2000). Furthermore, such networks serve as a source of information and/or referral

to health care services. While research on the role of social networks on health care utilization is

not new, the impact of such networks on CAM utilization needs further investigation.

33

Need Individual Characteristics 3.11 Individual Illness and Morbidity Considerations

Limitations in major activities such as work, housekeeping and independent living

accompany chronic conditions and are particularly common among older persons (Becker et al.,

2004). Those with chronic health conditions frequently battle muscular skeletal disorders, pain,

disability and/or other dysfunctions. Theirs is a world in which activities of daily living such as

bathing, shopping, dressing and eating are inhibited. While the concept of chronic conditions or

chronic disease is difficult to define, McKenna et al. (1998) capture its complexity well.

According to their definition, chronic conditions are generally characterized by: uncertain

aetiology, non-contagious origin, multiple risk factors, a long latency period, a prolonged course

of illness, functional impairment or disability, and incurability. Given the dominant emphasis on

cure, there is significant demand for new and/or improved “bridges” to better join the cure –

chronic care divide.

3.12 Use of CAM as a Self-Care Strategy

Older people are a very diverse group (Cassell and Neugarten, 1991), and as a diverse

group, many use a variety of self-management strategies to address their chronic health care

needs (Sorgen, 1998), including use of complementary and alternative medicine (Williamson et

al., 2003; Wister et al., 2002). 5 In addition, many individuals with chronic diseases seek out and

use CAM therapies for support and self care as they may be concerned with the side effects of

conventional (mainstream) medicine and, generally agree on the safety of CAM therapies.

Self-care is broadly defined as “the range of health and illness behaviour undertaken by

individuals on behalf of their own health” (Dean, 1992:34) and/or “the activities individuals,

34

families and communities undertake with the intention of enhancing health, preventing disease,

limiting illness and restoring health” (Health Education, 1983:181). Self-care practices could

include the use of licensed CAM therapists, which are often pursued on a self-referred basis

(ACOG, 2000). An increasing number of health care providers are accepting and referring their

clients to certain forms of CAM (Palinkas and Kabongo, 2000). Self-care implies seeing out the

services of trained (registered) CAM professionals in hopes of improving one’s health, whether

this is a realistic goal or not.

Arguably, successful management of chronic conditions depends on adequate self-care

(Bayliss et al., 2003). However, self-management by individuals with a chronic condition is not

an option (Bodenheimer et al., 2002). Effective management of chronic conditions is complex

and requires significant participation by patients as well as their families (Bayliss et al., 2003).

Indeed, individuals with long-term chronic conditions such as cancer must become partners in

their own care, since is they are the one with the disease or condition, and have the primary

responsibility of managing that disease or condition on a day-to-day basis, in collaboration with

their physician (College, 2003). As clinicians may only be present for a fraction of a patient’s

life, nearly all outcomes are mediated through patient behaviour (Glasgow et al., 2003). Korff et

al. (1997) further address the notion of collaboration and note medical care for chronic

conditions is rarely effective in the absence of adequate self-care and that, furthermore, disease

control and outcomes depend significantly on the effectiveness of self-management.

Increasingly, research is recognizing self-management for people with chronic disease as a

necessary part of treatment (Dongbo et al., 2003).

Self-care and health promotion share underlying themes: both entail the involvement and

empowerment of people in promoting and caring for their own health (Bhuyan, 2004), both aim

35

to sustain and/or maximize health as best as possible, and to prevent illness (Haber, 2003; Epp,

1986; Lalonde, 1974; Ottawa Charter, 1996). The concept of “empowerment” signifies that

individuals accept responsibility to manage their own conditions and are encouraged to solve

their own problems with information, rather than rely solely on professionals for managing their

actions (Bodenheimer et al., 2002). To support this, Marshall and McPherson (1994) stress that

people generally want to be independent for as long as possible. Those who criticize this

approach link such emphasis as a display of hostility towards physical decline (Hepworth 1995),

or as a way to place full responsibility for health squarely on its user (Daykin and Naidoo, 1995).

Though important considerations, such a way of thinking should not hinder progress in

developing and implementing programs and alternatives best suited for those with chronic

dysfunctions who are actively seeking options. Hill (2003) suggests that health promoters

committed to individual empowerment and community action appear most likely to support

some form of involvement with complementary and alternative medicine.

While self-care use of CAM is an important adjunct to chronic illness management and

an example of a health promotion strategy, its full potential is often limited to those who can

regularly use such services and afford to do so, since most CAM services are paid out-of-pocket

or through private insurance. This reality poses more of a problem for women than for men,

since health care availability depends primarily on national insurance contributions, direct fees

for services or private insurance; women more than men are often penalized because of their

generally lower incomes, the breaks they make in work-related contributions and their insurance

status (WHO, 2001). Further reflections on the importance of self-care is noted in chapter 7.

36

3.13 Individual and Contextual Characteristics- Summary

Using the Andersen model as a guide, this chapter has briefly considered individual and

contextual characteristics/factors which may directly or indirectly affect the utilization of

restorative / rehabilitative health care practices, such as massage therapy. Distinguishing between

individual and contextual factors is not straight forward, since these variables often interact

dialectically. Nevertheless, Andersen’s framework helps organize a large amount of data

effectively, while openly highlighting and elucidating the importance of the wide range of issues

and considerations that need to be made with regards to explaining or understanding health care

utilization.

3.14 Potential Limitations of Massage Therapy

Research to date provides varying levels of evidence for the benefits of massage therapy

for different chronic pain conditions. For Cohen et al. (2007), the inclusion of CAM therapies in

any medical subspecialty is not in and of itself clinically inadvisable or legally risky. However, it

remains advisable to exercise caution in order to avoid over-reliance on such services to the

exclusion of conventional (biomedical) care. Indeed, all modes of intervention have limitations

and MT is no exception.

Although massage rarely has any side effects (Ernst, 2003b), there are nevertheless

potential contraindications. It is therefore essential that the person applying massage techniques

be trained and competent in evaluating soft tissue restrictions, and have the ability to recognize

general contraindications. For instance, massage should not be used when there is compromised

or insufficient peripheral circulation (thrombus, embolus), acute infection or inflamation

(rheumatoid arthritis), injured vessels (acute phlebitis, bleeding), irritating skin conditions

37

(impetigo, poison ivy), and metastatic cancers (melanoma, bony metastasis) (Speer, 2005). In

addition, massage should be avoided by those who have a fever or have such health conditions as

lymphangitis. Finally, the treatment could be detrimental over over stents or other prosthetic

devices, since displacement can occur (Kerr, 1997).

In spite of an increasing number of textbooks devoted to massage, lack of supporting

evidence exists for making many of the decisions related to its contraindications. As well,

sources may list anywhere from 3 to 86 contraindications and precautions for massage (Batavia,

2004).

It remains unclear whether the effects of massage in general relate in an understandable

and systematic way to clinical improvement. In some cases, MT is only an effective short term

solution. In general, massage works best for mild to moderate chronic health problems and is not

particularly effective as a treatment for severe chronic pain (Bratman, 1999). Nevertheless, there

is an increasing demand for CAM practices such as MT.

According to Cohen (2006), including CAM therapies such as massage in any medical

subspecialty is not clinically inadvisable or legally risky; rather, that the danger stems from an

over-reliance on one or more CAM therapies to the exclusion of conventional (biomedical) care,

which could become imminently necessary in certain cases. All therapies, be they CAM or

conventionally, more bio-medically oriented, have limitations and their use or non-use require

careful scrutiny. 6

3.15 Study Assumptions

MT utilization is a type of behavior (Badger et al., 2000) which can be explained

and/or anticipated by using the Andersen model, which employs such concepts as

38

“predisposing”, “enabling” and “need” characteristics (see chapter 2). This study

considers inequity of access to MT as a social problem, which is modifiable through

legislation. In particular, enabling characteristics appear to be the most mutable, which

can be easily affected by changes in public policy, while need (illness/morbidity)

characteristics are often considered to be less mutable (Borrayo et al., 2002).

Research has demonstrated that independent living and active involvement in community

life is a desirable state for many people, including the chronically ill (Kozyrskyj et al., 2003); in

other words, individuals want to maximize their well-being and functional independence. While

meeting the needs of vulnerable individuals is difficult in the best of circumstances (Popejoy,

2005), this thesis argues that, in certain cases, regulated massage therapy has the potential to

enhance an older individual’s well-being and functional independence.

The next chapter examines this study’s methodology.

39

Chapter Three Endnotes [1] Problematically, it is a challenge to definitively define what CAM is, as its scope of practice is broad, encompassing more than 1,800 therapies and systems of care (Snyder and Lindquist, 2002). The acronym “CAM” is often used to include both “complementary” and “alternative” medicine terms (Furnham et al., 1999). It is ‘complementary’ when used alongside more legitimated biomedically-oriented (“orthodox” or “allopathic”) forms of health care, and ‘alternative’ when not used along-side orthodox forms of care. Often both terms are used interchangeably, without the distinctions noted above. “CAM” is a residual category composed of heterogeneous healing methods (Kaptchuk et al., 2001a). CAM encompasses a broad spectrum of beliefs and practices (Eisenberg et al., 1993) that varies considerably from one movement or tradition to another (Gevitz, 1988) and, each has different histories, philosophies and methods (Furnham et al., 1999) with distinct indigenous and non-indigenous origins (Nigenda et al., 2001). Problematically, there are no set guidelines for what falls under such headings as “complementary”, “unconventional”, “alternative”, “integrative”, or “adjunctive” medicine (Sorgen, 1998).

Moreover, defining CAM is said to be a linguistic minefield as there is no agreement on terminology (Harris et al., 2000; Kaptchuk et al., 2001a; Kelner & Wellman, 2000). To specifically define CAM by what it is, does not work (Kaptchuk et al., 2001b) as there over 350 modalities that can be listed under the broad category of complementary/alternative medicine (Chez et al., 1999; Eng et al., 2001). However, as an overall guide, most commentators agree that approximately 12 core CAM disciplines exist, these being acupuncture, homeopathy, hypnotherapy, manual therapies (e.g. massage), healing, herbalism, chiropractic, creative and sensory therapies, reflexology, naturopathy and osteopathy (Andrews, 2002; Zollman and Vickers, 1999). One of the most comprehensive definitions of CAM arose out of the 1997 National Institutes of Health Panel on “Definition and Description”. This panel has defined CAM as a broad domain of healing resources that encompasses all heath modalities, systems, and practices and their accompanying beliefs and theories, other than those intrinsic to the politically dominant health system of a particular culture or society in a given historical period. CAM includes all such practices and ideas self-defined by their users as preventing or treating illness or promoting health and well-being. Boundaries within CAM and between the CAM domain and the domain of the dominant system are not always sharp or fixed.

The Office of Alternative Medicine (OAM), predecessor to the Center for Complementary and Alternative Medicine based in the United States, define alternative (complementary) practices by three criteria: (1) the treatments are not generally taught in US medical schools; (2) the treatments lack sufficient documentation in the United States for safety and effectiveness against specific conditions and diseases; and (3) the treatments are not generally reimbursable by health insurance providers (Wainapel et al., 1998). CAM has also been referred to as: (a) medical practices that are not in conformity with the standards of the medical community; and (b) therapies that are medical interventions but not taught widely at medical schools nor generally available at hospitals (Millar, 2001; Eisenberg et al., 1993; Eisenberg et al., 1998). Ernst (1994) considers CAM as “those branches of the art and science of health care that are not in accordance with current medical thought, scientific knowledge or university teaching” (page 121).As a clear indication that the definition of CAM is in flux, a growing number of medical schools in Canada and the U.S. now offer courses and programs on

40

CAM (Health Canada, 2001; Kolasinski, 2001; Maizes et al., 2002). Moreover, in the United States, postgraduate CAM conferences are offered by such universities as Harvard, Stanford and Columbia and, for the past two years, the National Institutes of Health (NIH) has offered institutions five-year grants to develop curricula in CAM (Brokaw et al., 2002). In Canada, most medical schools as far back as 1998 have reported that they include CAM in their curricula, usually as part of a required course (Ruedy et al., 1999; Verhoef et al., 2002). In a study conducted by Kaufman and MacLeod (1999), 13 of 16 medical schools surveyed in Canada (81%) offer CAM education while the other three indicated they were planning on it. Currently, Humber College in Toronto (Canada), which is developing close ties with the University of Guelph, began offering CAM courses in their palliative care program (Vale, 2002). In general there is indication that CAM has become a serious subject in medical schools (Kaptchuk et al., 2001a).

Overall, a common thread which links the varied definitions of CAM is that they differ significantly from a biomedical science approach to health care. It involves ideas about the body or health or treatment which are not found in conventional medicine. It is an approach that includes a wide range of diagnostic systems and therapeutic practices that stands separate from, or in some cases opposed to, conventionally based medicine (Vincent and Furnham, 1997). This follows the thinking of Chez et al., (1999:33) who functionally define CAM in a residual manner as “that subset of medical and health care practices which is not an integral part of conventional (Western) medicine” or in other words, that which lies for the most part outside the mainstream of conventional medicine (Downer et al., 1994; Gevitz, 1988; King, 1985).

Despite challenges in defining CAM, as noted above, CAM is defined in this study as a therapy that is used as an additional treatment resource (Slee et al., 1996), in conjunction with or as a supplement to conventional (biomedically-driven) medicine (Cassileth 1998), not as a replacement (Sirois and Gick, 2002) (although some may use CAM as a replacement to conventional medicine). This takes into consideration Vickers’ (1994) caution of not using the term “complementary” as a polarized comparison with orthodox (conventional) medicine, since complementary medicine is increasingly being integrated within orthodox practice. [2] By 2021, older individuals are projected to form 18% of Canada’s population, compared to 12.5% in 2000 (National Advisory Council, 2005). As a result of decreasing fertility rates and increasing life expectancy, the proportion of the population over 65 years of age is expanding in most modern societies (Chou and Chi, 2004; McPherson, 1994). The median age within many parts of Canada, including Toronto, Ontario, is increasing (Statistics Canada, 1990; Statistics Canada, 2000; Toronto Star, A1/A8: 2002). In 2001, one Canadian in eight was aged 65 years or over and, it is projected by the year 2026, this will change to one Canadian in five (Abelsohn, 2002a). The expectation is that demographic shifts and socioeconomic trends in the US as well as Canada will result in vulnerable populations, such as the study population, to become the majority within the twenty-first century (Shi, 2001).

[3] Reported percentages of the Canadian population who use a CAM practitioner vary considerably between studies, depending on the target population chosen (York, 1999). Moreover, differences in study hypothesis across studies, over-sampling of certain populations, the methodology used to gain access to the sample (e.g. household interviews versus telephone interviews; and the manner in which CAM is defined (what modality of CAM is included or

41

excluded), can all influence how estimates of CAM use are derived (York, 1999; Egede et al., 2002). As examples, Eng et al., (2001) note that, within a Canadian survey, 44% of cancer patients were found to be using CAM. Among breast cancer survivors for instance, studies have found high usage of CAM services (Cheng et al. 2003; Boon et al., 2000). [4] There is a growing interest in CAM in general within the health professions (Vincent and Furnham, 1996). More and more mainstream healthcare providers are integrating complementary treatments into their traditional practices (Sorgen 1998; Gordon et al. 1998) plus, there is a growing number of physicians who are willing to refer patients to alternative practitioners (Phillips, 1999). Anderson and Anderson (1987, also cited in Furnham et al. 1999:102) studied 222 UK general practitioners and found a high level of interest in, referral, and knowledge of, complementary medicine. This is further reported by Vincent and Furnham (1994).

The medical establishment appears to be gradually becoming more open-minded about CAM (Ernst 1994). Gorden (1996 as cited in Drivdahl et al. 1998) predicts that in less than a generation the techniques and approach currently called “alternative” will be an integral part of the practice of all family physicians.

Today’s medical students appear to be more receptive and sympathetic to complementary medicine than previous generations (Phillips, 1999; Furnham et al., 1999). Reilly (1983 as cited in Furnham et al. 1999:102), examined the attitudes of general practitioners trainees to complementary medicine and found them overall rather positive. A study conducted by Gordon et al. (1998) found that younger primary care physicians and obstetrics-gynecology clinicians (aged 55 or younger) were more likely interested in CAM related use than similar specialists older than 55 years. The primary factor found in their study of what motivated these clinicians to be interest in CAM was their self-reported belief that not all problems can be treated effectively by conventional treatment alone.

A Canadian study, conducted by Montbriand (2000), indicates that health care professionals (namely nurses, physicians and pharmacists) would be willing to become resource persons for patients seeking out CAM if succinct and evidence-based information were made available on such therapies. Her study also found that nurses were about twice as likely as other professionals to use CAM themselves but half as likely to suggest such services or related products to their patients.

[5] As the population ages (Mirowsky 1998; Statistics Canada 1990), enduring chronic illness tends to replace the briefer acute illness episodes of youth (Hickey et al., 1992). Further, due to natural aging processes, older individuals are particularly susceptible to acquiring serious illness (Stewart, 2004), and/or a range of chronic health conditions (Marshall et al., 1995), requiring in turn greater health care attention (Andrews, 2002). Indeed, older individuals are prone to having several chronic conditions (co-morbidity) that must be managed simultaneously (Eliopoulos 1987; Wallace et al., 1992; Knottnerus et al., 1992; Cassel et al., 1991; de Boer et al., 1997; Health Reports 1999; Ontario Health Survey 1990; Falvo and Holland, 1990; Westert et al., 2001). It is a key reason why old people are disproportionately heavy users of healthcare services (Chou and Chi, 2004). [6] Complementary and alternative medicine in general, though increasingly popular, is not without its critics. Critics of CAM point out that its related therapies are often rejected by

42

established medicine as being unproven, ineffective and out-right fraudulent (Cassileth et al. 1984). Barrett and Jarvis (1993) are those of many who are particularly vocal in sharing the belief that CAM is simply a lot of hocus-pocus and that such terms as “alternative medicine” act only as slogans with no credibility behind it. According to Gevitz (1988), many regular physicians view all forms of unorthodoxy as quackery. The values purported by CAM experts are said to be not only different but deviant hence controversial as they involve ideas which diverge from conventional scientific understanding (Vickers, 1993). There are those within conventional medicine who write off CAM related therapies as being examples of a placebo effect – defined as an inactive substance or procedure given to satisfy a patient’s need for treatment (Furnham and Forey, 1994). Many CAM related treatments are still thought of as snake oil and dangerous by some orthodox health care professionals (Bratman 1999). Others suggest that the use of CAM services represents a ‘flight from science’ or credulous faith in occult or paranormal phenomena (Baum, 1989; Cornell, 1984 as cited in Donnelly et al. 1985:540). Some even say that CAM practitioners are menaces to society as they keep patients away from responsible treatments. “They are fools at best and crooks at worst, always ready to swatch insulin syringes from the hands of diabetic youngsters in favor of chamomile tea.” (Bratmen 1999:40). A standard argument from the practitioners of conventional medicine is that these quacks exploit the misery of illness and pose a threat to the patient’s health (Furnham et al. 1994). Such paranoid fantasies, according to Bratman (1999) is the equivalence in reverse of what many alternative proponents think about the conventional medicine profession. Objectively, both complementary and conventional medicine have their disadvantages as well as their advantages; neither can solve all health problems, each may well be more appropriate in certain circumstances (Vickers, 1993).

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Chapter 4

Methods

4.1 Research Design

In order to gain further information about factors related to the use of massage therapy

by an older population, I developed a mail questionnaire for this cross-sectional study. The

questionnaire relied primarily on multi-stage and convenience sampling approaches. The

Anderson model served as a guide for the order of logistic regression analysis and the variables

of interest, in keeping with this study’s goal: to test whether a modified version of the Andersen

model is a useful / productive tool toward a greater understanding massage therapy use

(Andersen, 1968, Andersen and Newman, 1973).

4.2 Using a Mail Questionnaire

According to McCarthy et al., (1997), mail questionnaires are widely used in health

research since they offer a relatively inexpensive form of data collection (Edwards et al., 2002).

In addition, a mail questionnaire is well suited to the Andersen model, which relies on

information easily gathered on surveys – predisposing, enabling and need population

characteristics (Andersen and Newman, 1973, Fouladbakhsh and Stommel, 2007).

However, each methodological tradition and study design comes with its own set of

potential problems (Broom et al., 2004). For instance, though self-reported instruments such as

mail questionnaires require relatively little time to complete, they frequently neglect to address

and explain sensitive/unpleasant/ difficult terms (Turpie et al., 1997). In order to limit this

potential hazard, this study asked licensed massage therapists from a Toronto massage therapy

44

school (i.e. ICT Kikkawa College) to review the survey’s wording, clarity and content validity

(see Appendix 1 – final questionnaire).

4.3 Research Setting

Since CAM therapies are usually practiced on an out-patient rather than in-patient basis

(Lewith and Davies, 1996), and since the Andersen model is well suited for community-based

research, this study focused on community-dwelling (non-institutionalized) respondents

currently residing in Toronto, a large Canadian metropolitan city that includes Etobicoke, York,

North York, Scarborough and the Borough of East York (see map - Appendix 2). At the time of

this study this geographic area comprised a quarter of Ontario’s elderly population (Hayward,

2001).

4.4 Outcome Measure

The present study made use of a single outcome measure – massage therapy (MT) use status.

For the purposes of descriptive and bivariate analysis, MT use status refers to an individual’s

use, non-use or former use of MT. This study defines a massage therapy “Former User” of as one

who reported having used massage therapy at least four months prior to the data collection

period. A MT “User” of MT is an individual either in the process of undergoing massage therapy

or had done so less than four months before completing the questionnaire. A “Non-User” of MT

is an individual who reported never having used massage therapy.

The present stage of analysis links non-users and former users, since logistic regression

analysis requires a binary outcome – in this case, MT use or non-use.

45

Sample

4.5 Using Human Respondents – Ethics Board Approval

The Research Ethics Board (University of Toronto) approved the present study

(Appendix 3). Each respondent received full disclosure concerning the nature of the study, the

respondent’s right to refuse participation, the researcher’s responsibilities, and the likely risks

and benefits (Polit et al., 1995). Furthermore, the study informed respondents of their

confidentiality rights (namely, that identifiers such as their name would not to be disclosed), the

possibility to withdraw from the study at any time, and that they were free to ignore any question

they wished. In addition, the study assured potential respondents that their decision to participate

in the study would in no way affect their future health care. To facilitate a participant’s

understanding of the investigation’s nuances, each respondent received a two-page information

sheet (Appendix 4) and was requested to sign a Questionnaire (Participant) Consent Form

(Appendix 5).

4.6 Criteria for Sample Selection

In order to be selected for the study, respondents had to conform to the following criteria

at the time of data collection:

(a) At least sixty years of age

(b) Toronto resident

(c) Non-institutionalized (community-dwelling).

46

(d) Currently experiencing one or more chronic health conditions (i.e., the individual

reports to have an on-going health condition which has exceeded 6 months and was

diagnosed by a medical doctor).

(e) Able to understand English, and

(f) Be willing to complete a timed 15-20 minute self-administered mail questionnaire.

In order to ensure that the respondents met all of the above criteria, the questionnaire

included the following questions: (a) when were you born? (day, month, year); (b) what city do

you live in and, what is your home postal code?; (c) How many people live in your household?;

(d) How many chronic on-going health problems would you say you now have that have lasted

for 6 or more months that has been diagnosed by a medical doctor? The questionnaire was only

available in English.

How the Questionnaire Developed

4.7 Instrumentation – Development of the Mail Questionnaire

Faculty and administrative staff members of ICT™ Kikkawa College – a private massage

therapy teaching school based in Toronto – critiqued the questionnaire and enhanced its validity.

Mr. Douglas Aboud, a registered massage therapist from Toronto, also provided valuable

insights concerning the presentation and specific wording of the questionnaire. The Seniors

Secretariat website, “Communicating in Print With/About Seniors” (http://www. hc-

sc.gc.ca/seniors-aines/pubs/communicating/ commse n.html) provided essential guidelines for

communicating with our target population and included such helpful suggestions as increasing

font size for greater legibility.

47

The principal investigator further refined the 15-page mail questionnaire. After receiving

ethical approval from the University of Toronto in August of 2000, the principal investigator

administered the questionnaire to a pilot study sample of n=32 respondents over a three month

period, from September to November 2000. Data collection stopped entirely during the month of

December 2000, when results may have been skewed due to the holiday season. The mail

questionnaire was used over a six-month period, from January to June 2001.

The questionnaires contained nine sections (A-I) and, according to the pilot study,

required between 10 and 25 minutes to complete. Questions were either dichotomous (yes/no)

and closed-ended in nature or laid out according to a Likert Scale format. Likert Scaling is

commonly used in the development of attitudinal measures and draws on summated scores

(Miralles and Kimberlin, 1998).

The sequence of questions underwent careful consideration to ensure that the order and

logical progression of questions would have minimal effect on respondents’ subsequent answers

(Jary and Jary, 1991). Each section began with a brief set of instructions. Section “A” addressed

demographics. Section “B” sought information about the respondent’s use and non-use of

massage therapy, as well as their satisfaction with orthodox mainstream medicine in general.

Section “C” focused on questions related to the respondent’s self-reported health status; their

ADL, IADL and mobility concerns; their time spent in a hospital over the last 12 months; and

what specific type of chronic [on-going] health condition they were undergoing. Section “D”

attempted to ascertain the respondent’s sense of mastery, while section “E” considered the

respondent’s level of self-esteem. Section “F” proceeded to address the individual’s established

health network while section “G” requested data on their use of selected mainstream and CAM

(complementary/ alternative medicine) practitioners. This section also had a question regarding

48

one’s perceived, overall rating of the benefits of CAM. Section “H” then proceeded to address

the respondent’s level of skepticism towards orthodox mainstream practitioners. Finally, section

“I” aimed to compile the respondent’s overall socioeconomic profile.

4.8 Assessing the Questionnaire with a Pilot Test

The pilot test questionnaires n=32 included a one-page evaluation form which asked

respondents how long they had spent on the test and whether they had any suggestions for

improvement. Pilot test results called for a replacement of the social support index, which had

revealed little variability among the responses, with a health network index. The test also

revealed a need for larger font size and simpler wording in the questions. None of the pilot test

questionnaires are incorporated in the final analysis, due to the fact that pilot test respondents

resided mainly outside of Toronto and the fact that the questionnaire underwent multiple

changes.

In an effort to increase response rates, the final questionnaire was designed to be as

simple as possible, and fully accessible to individuals of any socioeconomic background. In

order to further enhance the reliability of the instrument (in other words, its content validity), the

questionnaire integrated previously validated scales.

4.9 Independent Variables Used

Drawing on the Andersen model as a guide, the present study employed twenty-one

explanatory/exploratory measures (Andersen and Newman, 1973; Andersen 1995). As presented

49

in Chapter 2, this theoretical framework emphasizes potential health utilization determinants

(population characteristics) and represents them with predisposing, enabling or need variables.

4.10 Respondent Predisposing Characteristics

Demographic

Gender

The questionnaire coded gender as a dichotomous variable (coded [1] for females and [0] for

males).

Age

Currently, many countries define “elderly” as 60 years of age and older (Miralles and

Kimberlin, 1998). In this study, age operates as a continuous variable. The questionnaire coded

respondents’ ages according to their date of birth (day, month and year) at the time of data

collection.

Marital Status

The questionnaire distinguished between three marital status categories: legally married

(and not separated), or, legally married (but separated) individuals were coded as [1]; divorced or

widowed were coded as [2], and single (never-married) individuals were coded as [3].

50

Figure 4.2 Variables Used and their Corresponding Location in the Questionnaire

Predisposing Characteristics

Demographic Beliefs & Attitudes - Age [A2] - Mastery [D1-D7] - Gender [A3] - Skepticism [H1-H4] - Marital status [A4] - Self-esteem [E1-E6] - Satisfaction [B21-B26] Social Structure - Education [A6] - Family size (total people in household) [I14] - Occupation: - Last occupation [I8] - Self-employed [I2] - Employment situation [I1]

↕ Enabling Characteristics

Family Community (Health Network) - Health insurance (added) [I7] - Lay and professional health - Total annual household income [I8] network [F1 & F2] - Number of people in household [I4] - Lay and professional CAM network [F3] Financial Situation - Subsidized housing [I6] - Current money meets needs [I2]

↕

Need Characteristics (Illness Level) General State of Health: - Morbidity (number of chronic conditions) [C13] - Hospital days (</= 12 months) [C12] Disability: - Ability to walk up/down stairs [C7] Symptoms: - High blood pressure [C14-hbp] - Back problem(s) [C14-back] - Muscular-skeletal [C14-musc]

↓

Study Outcome Variable – Utilization of MT

* Use of Massage Therapy (MT) * Non-use of MT

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Social Structure

Education

Formal education frequently affords different access to social and economic rewards and

is usually associated with larger incomes in retirement (McDonald et al., 2000). The

questionnaire divided respondents’ education levels in two dichotomous variables: some high

school and high school graduation were collapsed and coded as [1] while some college or

university education was coded as [2] and, college or university graduation was coded as [3].

Caveat: Education remains only one of several variables that determines socioeconomic status

(SES). Occupation and economic resources, for instance, also function as important components.

Unfortunately, such variables do not represent the entire domain of SES and are imperfect

markers. For example, similarities in education levels between users and non-users of massage

do not imply equal educational experiences, because the quality of schooling often also

correlates with other facets of SES (McCracken et al., 2001).

Occupational Background

Since occupation is a categorical variable, this study collected data indicating the

respondent’s usual (principal) occupation and, if applicable, the spouse’s usual (principal)

occupation. The study employs the Pineo-Porter-McRoberts scale of 16 occupational classes.,

much like the NPHS (1995), which were collapsed into three categories according to Goel et al.

(1996 as used and cited in Hall and Coyte, 2001:178). The first category (classes 1-6), coded [1],

includes the self-employed, professionals, managers, semi-professionals and technicians. The

second category (classes 7-11), coded [2], consists of supervisors, foremen/women, trades people

and skilled clerical, sales and service personnel. The third and final category (classes 12-16),

coded [3], comprises semi and unskilled clerical, sales and service personnel, and manual

52

workers. Often a ranking of occupational classes reveals a fairly reliable indication of one’s

standing in industrial society (Deonandan et al., 2000).

Self-employed Respondents

Respondents had a choice of 7 different answers to the question “are currently self

employed?” Question I1 (Appendix 1) outlines these responses.

Employment Situation of Respondents

The answer to “what is your current employment situation?” became a collapsed variable:

a code of [1] indicated a homemaker, [2] signaled the person was retired (not working) and [7]

signified “other” (e.g. in paid employment, self employed, etc.).

Family Size

Factors such as household size have become indicators of financial resources and social

support (McDonald and Donahue, 2000). The study determined this variable by simply asking

the respondent, “how many people live in your household?” The responses were coded as “1” for

1-2 people, and “2” for three or more.

Skepticism

This study incorporates skepticism since the Andersen-Newman (1973) model accounts

for attitudes toward health services. To that end, four items defined skepticism in this study

(questions H1-H4: Appendix 1). Using a Likert-type scale, response indicators range from

strongly agree (coded 1) to strongly disagree (coded 5). The lower the score, the higher the

skepticism. Respondents chose four statements that people could potentially use to describe

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themselves: (H1) I can overcome illness without help from a medically trained professional;

(H2) Home remedies are often better than drugs prescribed by a doctor; (H3) If I get sick, it is

my own behavior that determines how soon I will get well; (H4) I understand my health better

than most doctors do.

Mastery

This study integrates concepts of “mastery” and “self-esteem” (as “model two” – see

Chapter 6) since Andersen (1995) and others suggest a need to expand the original concept of

“beliefs” from the Andersen and Newman (1973) model, by incorporating psycho-social related

variables in order to enhance comprehensiveness (Bradley et al., 2002). Based on the work of

Pearlin and Schooler (1978), seven items define mastery in this study (questions D1-D7:

Appendix 1), which reflects a highly respected and commonly used scale (Schieman and Turner,

1998). Respondents commented on seven different statements that people frequently use to

describe themselves: (D1) You have little control over the things that happen to you; (D2) There

is really no way you can solve some of the problems you have; (D3) There is little you can do to

change many of the important things in your life; (D4) You often feel helpless in dealing with

problems in life; (D5) What happens to you in the future mostly depends on you; (D6)

Sometimes, you feel that you are being pushed around in life; and, (D7) You can do just about

anything you really set your mind to do. The questionnaire asked respondents to respond to each

statement by selecting one of the following Likert Scale responses: “strongly disagree” (coded

5), “disagree” (coded 4), neither agree nor disagree” (coded 3), “agree” (coded 2) or “strongly

agree” (coded 1). The higher the score, the greater the sense of mastery, with the exception of

questions five and seven, which were reverse coded.

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Self-esteem

The study defined self-esteem according to six items on the test (questions E1-E7:

Appendix 1), developed by Rosenberg (1979). The self-esteem index reflects positive self-

attributions that an individual holds about her/himself (Cairney, 2000) and refers to an

individual’s sense of self-respect or self-worth. Those with low self-esteem are said to lack self-

respect while those with high self-esteem have it (Singleton et al., 1993). The test assesses self-

esteem by adding responses using a five-point Likert scale: “strongly disagree” (coded 5),

“mildly disagree” (coded 4), neither agree nor disagree” (coded 3), “mildly agree” (coded 2) or

“strongly agree” (coded 1). Respondents described their feelings about the six items, which

included: (1) You feel that you have a number of good qualities. (2) You feel that you are a

person of worth at least equal to others. (3) You are able to do things as well as most other

people of your age. (4) You take a positive attitude toward yourself. (5) On the whole, you are

satisfied with yourself. (6) All in all, you are inclined to feel that you are a failure (reverse

coded). Unlike mastery, the lower the score the higher the self-esteem. Statistics Canada (via the

NPHS, 1995) has determined 17 to be the cut-off score per respondent. This study revealed that a

total score (per respondent) of the six items equaling or greater than 17 was considered an

indicator of low self-esteem (≥ 17 = low self-esteem: an average score per item of more than 3).

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4.11 Respondent Enabling Characteristics

Family

Annual Household Income

Previous research demonstrated that questions that require participants to fill in

exact sums of money frequently lead to high levels of non-response (Kempen et al.,

1991). To that end, the present study incorporated eight income categories before

collapsing and entering them as an ordinal variable with three categories, the lowest

income coded [1]: 0-$29,999, $30,000-$59,999 – coded [2], and $60,000 + coded [3].

Caveat: Household income is a better SES indicator for younger adults than for the

elderly. For many adults over 65, the transition from work to retirement moves them into

a lower income bracket. However, though many seniors have lower incomes, they

compensate for the loss by collecting assets such as a mortgage-free home (Roberge et

al., 1995). In order to account for these discrepancies, this study incorporates a range of

income sources.

Health Insurance (Beyond OHIP)

Since all of the respondents were eligible for the Ontario Hospital Insurance Plan (OHIP), this

study measured any other form of health insurance as the presence (coded 1) or absence (coded

2) of supplemental insurance.

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Employment Status of the Respondents

A respondent’s employment status is coded as a collapsed dichotomous variable, where

[1] indicates homemaker, [2] is a retired individual, and [7] refers to a category called “other”

(for instance, involved in paid employment, self employed, etc.).

Community

Questionnaire sections F1 to F3 relate best to Andersen and Newman’s (1973) concept of

“community” as a predisposing characteristic, and consider a respondent’s health network. The

primary investigator added these sections to the model in response to criticism for not having

considered a respondent’s social network as indicated the Andersen-Newman model. Each

section allows the respondent to choose a yes/no answer to questions whether they sought out or

talked to a doctor, family and/or friends, a hospital specialist, an alternative practitioner, or

nobody. The questionnaire also provided a string coded, “other” response option.

Section F1 asked respondents: “who among the following can you confide in or talk to

when you have problems with your health?” F2 inquires: “who among the following can you

really count on to give you information about health in general?” Finally, section F3 solicits an

answer to the following question: “who, if anyone, gives you information about complementary/

alternative medicine?”

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4.12 Respondent Need Characteristics

General state of Health

Morbidity (number of chronic conditions)

In keeping with Millar’s model (1997), this study also counted chronic conditions

(question C13) and determined four chronic disease categories: no chronic disease, one chronic

disease, two chronic diseases, and three or more chronic diseases. The question required

respondents to have one or more self-reported chronic heath condition(s) diagnosed by a medical

doctor that has been ongoing for six or more months. The study automatically eliminated

individuals who reported no chronic health conditions.

A continuous variable measured the total number of self-reported chronic health

conditions: less than two were coded as [1], while three or more were collapsed and coded as [2].

Functional Status Indicators

This study considered ADL, IADL and mobility scale indicators (Atchley and Scala,

1998) in order to measure an individual’s functional status. Developed by Katz et al. (1963), the

Activities of Daily Living (ADL) index (Hunt et al., 1986) is considered to be one of the best-

known scales of disability and provided this study with ADL measures. In this case, disability

specifically refers to task performance dysfunction, which translates into an inability to perform

a complex set of functions combining strength, timing, coordination, skill and flexibility (Kemp,

1997). The study employed an ordinal variable to measure the degree to which the participants’

self-reported their activities as limited: No difficulty / A little difficulty – was coded [1], A lot of

difficulty / Unable – was coded [2]. Afterwards, the sum of scores provided a single total and

reflected the following: the higher the score, the greater the functional limitation. The study

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included Activities of daily living (ADL) such as dressing and washing/bathing; three

Instrumental Activities of Daily Living (IADL) such as managing one’s own money, preparing

meals and using the phone, drawing on the work of Lawton and Brody (1969); finally, three

mobility factors such as getting out of the house as often as one would like, walking up and

down the stairs and using public transportation. After extensive testing of the variables, the only

indicator to appear in the final logistic regression model was “able to walk up and down stairs” –

(coded as c7).

Hospital days

A continuous variable measured the number of days an individual spent in hospital

over the past 12 months. Zero days in hospital, indicated by “none” was coded as [1], a

week or less was coded as [2], less than a month was coded as [3], one month was coded as [4],

2-3 months was coded as [5] and, 4 or more months was coded as [6].

Chronic Condition Types

A respondent’s self-reported, medically diagnosed chronic health conditions (lasting six

or more months) were measured with a continuous variable. The present study focused on the

common chronic health conditions (Abelsohn, 2002a) and frequently studied chronic diseases

(de Boer et al., 1997). To that end, the study adapted a symptom list from the NPHS (1995) for

its questionnaire, which included: Arthritis or Rheumatism – coded [1]; Osteoporosis – coded

[2]; High Blood Pressure – coded [3]; Kidney Condition – coded [4]; Diabetes – coded [5]; Back

Problems – coded [6]; Headaches – coded [7]; Muscular-Skeletal Pain – coded [8]; Heart

Condition – coded [9]; Bowel and/or Digestive Condition – coded [10]; Lung Condition – coded

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[11]; and, Other (requested to specify). – coded [99]. After thoroughly testing the variables, three

of the above indicators made the final logistic regression model – back problems, muscular-

skeletal problems and high blood pressure.

Caveat: As the work of Cooper and Kohlmann (2001) reminds us, self-reported diagnosis always

contains potential for error, in spite of the fact that the question specified a condition “diagnosed

by a medical doctor.”

4.13 Data Input Coding Procedure

The questionnaire pre-coded all of the indicators in order to facilitate the process

of inputting data for analysis. The final consideration in the development of recodes was

category size. Where necessary, the questionnaire collapsed certain variables into fewer

categories (deVaus, 1986). Ultimately, the recoding process sought to develop internally

consistent and diverse categories, while retaining analytical interest and large enough

numbers to assure stable estimates of variations (Cox and Cohen, 1985; Turner and

Marino, 1994). Deciding where to collapse categories was based on initial exploratory

data analyses of 129 returned questionnaires.

4.14 Developing a Codebook

This study developed a codebook in order to facilitate the data input accumulated

from the completed mail questionnaires (Appendix 6). In addition to listing and

numbering all of the variables, the codebook also labeled the variables and suggested

which values were legitimate (Salant et al., 1994).

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4.15 Data Collection Time Period

The principal investigator of this study recruited eligible respondents and collected their

corresponding data collected, over a period of six months, from late November 2000 to early

April 2001. As this chapter demonstrates, the process of recruiting a sufficient sample size

required extensive efforts.

Table 2 Sample Instruments Used In The Final Questionnaire

Instrument or source(s) Measured Variable

• Katz et al. (1963)1

• Lawton & Brody (1969)2

• Bierman et al., (1999)3

ADL

IADL

Health Status

• Pearlin & Schooler (1978)4 Mastery

• Rosenberg (1979)5 Self-esteem

• Vincent & Furnham 19966 Satisfaction with orthodox medicine.

• CHAS/NORC 19707 Skepticisim towards orthodox medical practitioners.

1 Katz, S., Ford, A.B., Moskwitz, R.W., Jacobson, B.A., and Jaffe, M.W. (1963). The Index of ADL: A Standardized Measure of Biological and Psuchological Function. JAMA 186:914-919. 2 Lawton, M.P., Brody, E. (1969). Assessment of older people: self-maintaining and instrumental activities of daily living. The Gerontologist, 9: 179-186. 3 Bierman A.S., Bubolz T.A., Fisher E.S., Wasson J.H. (1999). “How Well Does a Single Question about Health Predict the Financial Health of Medicare Managed Care Plans?” Original Article, Effective Clinical Practice, 2 (2), March/April, 56-62. Article reprint provided by the U.S. Department of Health and Human Services, HCPR. 4 Pearlin L.I., Schooler C. (1978). “The Structure of Coping.” Journal of Health and Social Behavior, 19 (1), March, 2-21. 5 Rosenberg M. (1979). Conceiving the self. New York: Basic Books. – Self-esteem Scale - 6 Vincint C., Furnham A. (1996). :Why do patients turn to complementary medicine? An empirical study.” British Journal of Clinical Psychology, 35, February, 37-48. 7 CHAS/NORC – Centre for Health Administration Study/National Opinion Research Centre. As cited in Fiscella et al. (1998) Medical Care, 36 (2), February, 180-189.

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4.16 Respondent Recruitment Strategies

Users of Massage Therapy The present study set up a multistage sampling technique in order to identify, select and

contact massage therapy practitioners. Once the practitioners were selected, the study proceeded

to seek out MT clients who met the inclusion criteria. The process employed the following six

sequential steps:

Step 1: The primary investigator identified Toronto-area massage therapists by resorting to a

registry of all registered massage therapists in the province of Ontario listed in a (public domain)

directory produced by the College of Massage Therapists of Ontario (CMTO, 2001).

Step 2: Following this step, the primary investigator installed a random sampling technique (with

replacement) in order to recruit Toronto area massage therapists (MT’s). The study intentionally

excluded MT’s who worked in spas, massage therapy teaching schools, and private clubs as well

as MT’s listed under their own name, who had neither business nor clinic. The investigator then

assigned a number to each of the remaining 247 clinics/businesses. Of this list, 16 MT

clinics/businesses were initially chosen at random, with the help of a table of random numbers.

As a final step, the primary investigator contacted the registered massage therapist to request his

or her participation.

Massage Therapist Inclusion Criteria

In order to be recruited, the study required that the Toronto-area registered massage

therapist:

(1) Be registered (included in the CMTO Directory).

(2) Practice in Toronto, Ontario.

(3) Treat individuals aged 60 and over who had one or more chronic continuous health

conditions.

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(4) Speak/communicate in English and,

(5) Practice 1-hour body (Swedish) massage (not chair massage).

Caveat: The process of selecting massage therapists revealed that using the 2001 CMTO

Directory imposed certain limitations. For instance, numerous MT’s were listed under business

addresses where they no longer practiced. When this occurred, the study employed a table of

random numbers to reselect another therapist.

Step 3 After being located and screened, the primary investigator of this study contacted the

massage therapist by telephone in order to inform them of the nature of the study, and to assess

their willingness to participate. In order to eliminate all possible therapists who did not fit the

criteria, the investigator asked, point blank, whether they “treat clients who are sixty years of age

and over and have at least one chronic health condition?” In the event that the MT practitioner

replied with a “no,” they were automatically excluded from the study. In such cases, and on the

rare occasion that the MT practitioner contacted stated he or she was too busy or not interested in

the study, further random sampling helped select other potential MT participants.

Step 4 If a selected and qualified MT expressed interest in the study and was treating the target

population at the time of the recruitment phase, he/she received a sample study package in the

mail at their practice site. In order to better acquaint Toronto-area massage therapists with the

study, they received: (1) a 15-page postal questionnaire, (2) a two-page study summary, (3) a

questionnaire consent form, and, (4) a stamped return envelope. This last point, according to

Edwards et al. (2002), increased response rates. Included in the package was an invitation letter,

written by Douglas Aboud, a practicing (registered) Toronto-area massage therapist, to further

help solicit the therapists. Edwards et al. (2002) also report that personalized letters increase

response rates.

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Salant and Dillman (1994) argue that a public announcement of a survey of questionnaire

often legitimates it. To that end, the present study placed a quarter-page ad summarizing the

study in the Ontario Massage Therapist Association (OMTA) Newsletter (October/November

2000 issue).

Caveat: Not all registered massage therapists are members of the OMTA. Many OMTA member

MT’s admitted to rarely reading the newsletter.

When possible, study packages were hand delivered to MT’s; this expedited the process

of providing data to interested MT’s and also personalized the study by acquainting MT and

researcher, thus encouraging participation. In three cases, when contacted by phone, MT’s

enthusiastically ordered “x” number of study packages to give their clients who met the inclusion

criteria.

Caveat: However, this sort of enthusiasm frequently proved to be short lived, since delivered

study packages were not always used.

Caveat: The study revealed yet another limitation of the CMTO Directory: many listed MT

addresses and postal codes were not accurate. As a result, some of the study packages mailed to

MT’s were returned to this researcher, which slowed down the process and required verbal

verification of the MT’s exact address.

Step 5 Upon receiving a sample study package, the MT had two weeks to decide whether he/she

would assist with the study, at which point the primary investigator contacted them by phone.

Drawing on the work of Kelner and Wellman (1997), the primary investigator asked each

participating MT to enlist the help of their clients, in order to maximize recruitment and give due

respect to the relationship between the MT practitioner and their clients. Twenty-nine randomly

contacted MTs/MT clinics chose not to help with the study; these individuals were thanked and

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removed from the study. The vast majority (~95%) of such MT’s indicated they did treat clients

aged sixty and over, at which point another MT was chosen to take their place (via

randomization). Massage therapists who agreed to voluntarily help were requested to: (1)

identify eligible respondents from their client records based on the study inclusion criteria, (2)

contact such client(s) to determine whether they wished to voluntarily participate, and, if they

expressed interest, (3) to provide the primary investigator with an approximate number of how

many study packages to drop off or mail to the identified MT practice site. The process enabled

each participating MT to provide one study package to a qualified client at their next scheduled

appointment. In an effort to reduce attrition rates and the additional time and expenses of printing

and postage, MT’s were requested to ensure that their client was not only qualified, but also was

genuinely interested in the study.

The study provided MT’s with a one-page flyer for clients to facilitate communication.

Individual respondents received instructions along with study packages; the instructions spelled

out the need to sign and mail a consent form directly to the principal investigator at a University

of Toronto postal address. According to Edwards et al. (2002), questionnaires originating from

universities are more likely to be returned than questionnaires sent from other sources, such as

commercial organizations. All of these techniques – University of Toronto logos, colored ink,

massage therapy practitioner endorsement – operated as efforts to increase response rates and

reassure respondents of the legitimacy of the study.

Step 6 Once the study population was established, the primary investigator of this study kept in

contact with the MT to remind him or her of the study in order to encourage their recruitment

efforts. Over a six-month data collection period, massage therapists received study packages on a

need basis.

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Recruitment of Former Users and Non-Users of Massage Therapy

In order to glean information from as many non-users and former users of massage

therapy as possible, the present study employed a wide range of recruitment strategies. These

groups then served as a basis of comparison with users of MT.

Recruitment techniques varied widely. One technique involved using Rogers television’s

Community Bulletin Board. For two weeks, a notice regarding the study was televised along

with other events, free of charge. Another technique required obtaining permission by the

Marketing and Communications office of the Toronto Public Library to post flyers concerning

the study in 94+ branches throughout Toronto. In addition, flyers were posted on church bulletin

boards as well as Community Centres, senior apartment residences, and hospital bulletin boards

(e.g. at Mt. Sinai Hospital). Willowdale Baptist Church, in North York (Toronto), included an

insert about the study in its church bulletin. The study also turned to internet web sites geared

toward seniors, such as: www. doublenickels.com; http://www.Wiredseniors.com;

Exclusivelyseniors.com, and www.seniorwomen.com and the Canadian Arthritis Association

http ://www2.arthritis.ca/living/wwwboard/wwwboard.cgi. Several individuals voluntarily acted

as referral sources: many of these participated in the study and told a friend or neighbor, who

then contacted the primary investigator of this study. Another important recruitment step

involved contacting seniors/health-oriented Toronto-area community agencies either by

telephone, e-mail and/or a personal visit to request their help. Many organizations generously

agreed to help, including: SPRINT (Seniors People’s Resources in North Toronto Inc.), Seniors

Link, Senior Adults Services Sunshine Centres for Seniors, Promised Care Centre, University

Women’s Club, York Fairbank Centre for Seniors, and the Etobicoke DCVS Services for

Seniors. Each organization received general recruitment posters in order to facilitate their efforts.

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Finally, two oral presentations to senior audiences at the Hope Residence and the Franklin

Horner Community Centre (Toronto) helped recruit even more respondents.

4.17 Data Collection Procedure

This thesis draws on quantitative data by using self-administered mail questionnaires.

Mail surveys contain a cover letter and/or fact sheet(s) that explain the study goals and also

enable the respondents to answer calmly, without being pressured by time.

4.18 Measures Taken To Increase Questionnaire Response Rates

This study encouraged respondents to return the contents of their study packages in

several specific ways. In particular, the primary investigator relied did not underestimate the

importance of the visual impact of the study package and its contents, drawing on the research

by Salant and Dillman (1994).

University of Toronto logos on the questionnaire projected a serious, professional image.

Laser printing further ensured the survey’s readability. The questionnaire’s first page included a

return address was included in the event that the respondent lost their stamped-addressed return

envelope. Postage stamps were favored over postal machine meters on return envelopes in order

to ensure a more personal touch. Most of the return envelopes had instructions on the back as a

reminder for the participant(s) to enclose their signed and dated consent form and completed

questionnaire; the back of the envelope also thanked them for their participation. Finally,

individuals could learn more about the study by consulting a tailor-made website, also indicated

on the first page of the questionnaire.

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4.19 Data Analysis

The data were processed and analyzed using the “Statistical Package for the Social

Sciences” (SPSS-versions 15.0 and 16.1 for Windows). Licensees for these were purchased from

the University of Toronto’s licensure office. Bryman and Cramer (2001), Foster (1998) and Pett

(1997), as well as training sessions at the Toronto General hospital, guided this study’s use of

SPSS. Finally, I obtained invaluable advice from statistical consulting services (via the

University of Toronto) and my dissertation committee.

Given the relatively small study sample size due to cost and geographic constraints, this

study opted for non-parametric statistics (DePoy and Gitlin, 1998; Pett, 1997). Standard

deviation, as well as the Cox and Snell and Nagelkerke R2 determined measures of variability in

this study.

Descriptive statistics such as frequency distributions depicted characteristics of the study

sample. The study employed Chi-square tests to detect statistically significant proportions of

people who did not use, had used or formerly used massage therapy, in relation to other

independent variables. As well correlation and regression analysis were conducted, the later of

which obtained such statistics such as the odds ratio. Odds ratios (OR) provided the likelihood

(factor change) of using practitioner-based MT (compared to not using MT) for one-unit change

in an explanatory variable, while statistically controlling for all others (Votova, 2007; Frank et

al., 1997).

Logistic regression analysis is a statistical technique of choice to perform analysis for a

dichotomous outcome (in this case, “use” or “non-use” of massage therapy), with various

degrees of skewing (DeMaris, 1995). This method carries fewer assumptions than discriminant

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analysis, which requires neither multivariate normality nor homogeneity of variance-covariance

matrices (Kinnear and Gray, 2009).

MT use status served as the dependent variable in this study. Drawing on the Andersen

model as a guide for independent variables, they were classified as either ‘predisposing’,

‘enabling’ or ‘need’ variables (Andersen and Newman 1973; Andersen 1995). Simultaneous

logistic regression enabled me to first to consider each predisposing, need and enabling variable

individually in order to ascertain their independent link to MT use status. A second step involved

using step-wise logistic regression. Backward logistic regression determined the degree of

statistical association to MT use status. The study presents estimates with 95% confidence

intervals.

4.20 Data Editing and Cleaning Procedures

Editing reduces missing data and ensures that the information on a questionnaire or

interview schedule is ready to be transferred to a computer for analysis. “Ready” implies that the

data are as complete, error-free and as readable as possible. This process is carried out during

and after the process of data collection, and much of it occurs simultaneously with coding

(Singleton et al., 1993). In this study, opportunities to edit questionnaires occurred when a

community agency (e.g. SPRINT) provided a list of names and telephone numbers of interested

candidates and a code (e.g. A10) was written on the outside of their return envelope for potential

follow-up. Codes that matched a unique identifier – a respondent’s name, address and telephone

number – were recorded in a logbook. Occasionally, respondents wrote their return address on

the provided stamped envelope, although the information was only used in the event there was a

problem with the respondent’s questionnaire. The majority of returned mail questionnaires did

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not include the respondent’s contact information. Two returned questionnaires had significant

missing data that could not be followed up and were subsequently eliminated from the study.

Upon completion of data coding and entering into a computer with SPSS, meticulous

attention was required to ensure the accuracy of these inputs – a process referred to as “cleaning

the data” (DePoy and Gitlin, 1998; Singleton et al., 1993). This study included the following data

cleaning techniques: (1) Each questionnaire was inputted twice for comparative purposes; and

(2) valid range checks corrected erroneous codes outside a pre-selected range. Finally, (3) the

study carried out consistency checks to ensure that responses flowed logically (deVaus, 1986).

4.21 Item Non-response/Missing Data

In cases where completed questionnaires contained missing data and could not be edited,

cells were left blank. SPSS automatically considers blank cells to be missing data. Falling back

on the advice of Salant and Dillman (1994), this study carefully distinguished blank cells from

categories that indicated “don’t know” or “unsure” responses (which were coded appropriately).

Variables excluded from further analysis were ones that contained significant missing data or

ones that reduced the number of cases analyzed according to logistic regression.

4.22 Maintenance of Confidentiality - Storage of Collected Data

To ensure confidentiality, all collected information pertinent to this study, including the

returned mail questionnaires, is currently stored in a secure place in the principal investigator’s

home. This material will be properly destroyed upon full completion of this thesis.

Two separate chapters present the results. Chapter 5 provides the descriptive and

bivariate results, while chapter 6 imparts the logistic regression results.

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Chapter 5

Descriptive and Bivariate Analysis Results

5.1 Introduction

As noted in chapter 4 the variables used in this study were guided by Andersen’s

Behavioural Model. Here, the primary purpose and importance of conducting bivariate analysis,

using such statistics as chi-square, is to set the stage to conduct step-wise regression analysis. In

other words, by determining which variable s considered in this study were statistically

significant to the outcome (massage therapy [MT] use status) these then are further investigated

using binary logistic regression.

Throughout this chapter, descriptive and bivariate results are presented using constructs

from the Andersen model, under the key headings of either ‘predisposing’, ‘enabling’ or ‘need’

characteristics. Before doing so, a summary descriptive table is presented, as well as in brief the

following: response rate, reliability of the scales used and, study demographics.

5.2 Response Rate Of 226 postal questionnaires distributed, n=157 (69%) were returned and n=141 (62%)

were sufficiently completed and met the study inclusion criteria. This number was considered

sufficient to allow for the identification of trends, to assess the relevance of the study instrument

plus, to undertake the analysis needed to adequately address the research question.

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Table 1 Sample Descriptive Statistics

Variable (coded) M (SD) n (%) Age 3.8 (1.43) 85+ (6) 7 (5) 80-84 (5) 24 (17) 75-79 (4) 27 (19) 70-74 (3) 30 (21)

65-69 (2) 35 (24.8)

60-64 (1) 18 (12.8)

Marital Status 2 (.22)

Married (1) 49 (34.8)

Divorced/Widowed (2) 75 (53.2)

Never Married (3) 17 (12.1)

Income b 2 (1)

0-29,000 (1) 66 (46.8)

30-59,999 (2) 42 (29.8)

60K+ (3) 21 (14.9)

Education 2.6 (1.2)

Less than high Sch. (1) 42 (29.8)

High School Grad (2) 22 (15.6)

Some post-secondary (3) 30 (21.3)

Post-secondary Grad (4) 46 (32.6)

Last Occupation 2 (1)

Blue Collar (1) 49 (34.8)

White Collar (2) 41 (29.1)

Professional (3) 48 (34) Massage Therapy Status Users (1) 79 (56) Non-Users (0) 62 (44)

--------------------------------------------------------------------------------------------------- Where SD = standard deviation, M = Mean, n = sample size, b = missing data for 12 participants (n=129)

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5.3 Reliability of Scales Used

Previously validated scales incorporated in the study postal questionnaire – used to

measure: self-esteem, satisfaction, mastery and skepticism - had an alpha coefficient range of

.6022 to .8723. This indicates moderate to high internal reliability.

5.4 Study Demographics

The qualified sample included 78% (n=110) females and 22% (n= 31) males. The age

range is 60-94 with a mean of 73. The majority of the sample (n=58 at 41%) were aged 75 or

over. Of the 141 qualified respondents, 44% (n=62) were Users of (registered) massage therapy,

15% (n=21) were Former Users and 41% (n=58) were Non-users of MT. The majority indicated

they were separated, widowed or divorced (57%). Approximately one third indicated that they

were married (31%) while a small minority stated that they had never married (12%).

Predisposing Characteristics

Predisposing characteristics considered were guided by the Behavioral Model. These

included the respondent’s: age, gender, marital status, education, usual occupation, as well as

measures of beliefs and attitudes (mastery, satisfaction, skepticism and self-esteem). We begin

our comparisons, between the three study groups, by considering gender.

5.5 Gender Differences Between Groups

Within each study group, the majority of respondents were female. Non-users of massage

therapy (MT) in particular had a higher percentage of females than males, while Users of MT

had a higher percentage of males, relative to the other two groups, although there were no

statistically significant differences among the groups. Within table one, and throughout this

chapter, valid percentages are provided which are based on the actual number of respondents.

73

Table 2 Gender Characteristics using Chi-square

Gender Characteristics of Respondents - in Percent n = 141 χ2 = 5.085, p = .079 Users Former Users Non-Users Sample Total (%)

Female 69 81 86 78 Male 31 19 14 22 Column Total (%): 100 100 100 100 5.6 Marital Status

Table 3 provides the marital status breakdown of the study sample. The majority of Users were

married. The majority of the Non-User and Former User groups were found to be in the

separated, widowed or divorced category, each having a mode of 4 (widowed). Using chi-square

(cross-tabulation), marital status was found to be statistically significant to MT Use status (χ2 =

20.295, df=8, p = .009), although the strength of this association was found to be weak at .268,

using Cramer's V.

Table 3 Marital Status

Variables Users

% Non-

Users % Former Users %

Row Total %

Marital Status

Married Separated/Widowed/Divorced Single/Never Married Column Totals - %:

N = 62 38 45 16 99

N = 58 24 69 07 100

N = 21 24 62 14 100

N = 141 30 57 12 99

Where N= is based on number of respondents. 5.7 Age Differences between Groups The majority of respondents within each group were found to be aged 75 or over (see table 4).

74

Table 4

Age Characteristics using Spearman's Rho Age Characteristics - % n=141 p = .106 (1-tailed) Users Former Users Non-Users (n = 62) (n = 21) (n = 58) Sample Total % % % Age (years) % 60 - 64 13 13 19 11 65 - 69 25 31 14 22 70 - 74 21 24 19 19 75 + 41 32 48 48 Column Totals: 100 100 100 100 ________________________________________________________________________ Age Range: 61-92 60-84 60-94 Standard Deviation: 7.25 7.63 7.50 Mode: 69 79 67 Median: 71 74 74 Except for rounding error, column percentages sum to 100%.

5.8 Education of Respondents

Participants in each group were found to range in education from less than or some high school

to college or university graduation. Of 140 respondents, the respondent's education was found to

be statistically significant (χ2 = 18.131, df=6, p = .006) although the strength of association was

not found to be strong (Cramér's V = .254). Users of massage therapy (MT) were found to have

more education (3.02 ± 1.12) (mean ± standard deviation) when compared to Former Users (2.33

± 1.97, mode = 1), and Non-users (2.19 ± 1.22, mode = 1).

Using frequency analysis (%), Non-Users were found to have fewer formal years of

education than Users and Former Users. Further, the spouse’s of the User and Former-user

groups were found to have more formal education than the spouse’s within the Non-User group

(see table 5).

75

Table 5 Respondents and their Spouse’s Education - %

Valid percents used.

5.9 Education of the Respondent's Spouses

Pertaining to the respondent's spouse's education, no statistical significance to MT use status was

found using chi-square (where χ2 = 9.369, df=6, p = .154).

5.10 Occupational Background of Respondents

Table 6 provides a summary table of the frequency distributions of the respondents, and their

spouses, occupational positions.

Variables & Categories Users Former

Users Non-Users

Row Totals

Respondent’s Education

1. Less than or some high school education 2. High School Graduate 3. Some college/university 4. College/university Grad Column totals:

Respondent’s Spouse Education

1. Less than or some high school education 2. High School Graduate 3. Some college/university 4. College/university Grad Column totals:

(N=61) 15 16 21 48 100

(N=46) 15 20 24 41 100

(N=21) 38 10 33 19 100

(N=17) 29 24 29 18 100

(N=58) 43 17 17 23 100

(N=45) 36 24 11 29 100

(N=140) 30 16 21 33 100

(N=108) 26 22 20 32 100

76

Table 6 Respondent's and their Spouse's Occupational Background

Column valid percentages (per variable) are rounded to 100%.

Users of MT, and their spouse, had much higher occupational prestige (category 1) positions

than the Non-User and Former User groups. Non-Users had more category 3 (lower class)

positions than Former Users and Users, followed by Former Users who had more category 3

(lower class) positions than Users.

Table 7 provides a summary table of the associations found between the respondent's

(and their spouse's) occupational position and their MT use status.

Variables & Categories

Users

%

Non-Users

%

Former Users

%

Row %

Respondent’s Last Occupation Category 1: Professionals/Managers/Semi-Prof./Tech. Category 2: Supervisors/Trades/Skilled Clerical/Sales Category 3: Semi and unskilled clerical/Man. Workers Column totals:

Respondent’s Usual Occupation Category 1: Professionals/Managers/Semi-Prof./Tech. Category 2: Supervisors/Trades/Skilled Clerical/Sales Category 3: Semi and unskilled clerical/Man. Workers Column totals:

Respondent’s Spouse - Last Occupation

Category 1: Professionals/Managers/Semi-Prof./Tech. Category 2: Supervisors/Trades/Skilled Clerical/Sales Category 3: Semi and unskilled clerical/Man. Workers Column totals:

Respondent’s Spouse - Usual Occupation

Category 1: Professionals/Managers/Semi-Prof./Tech. Category 2: Supervisors/Trades/Skilled Clerical/Sales Category 3: Semi and unskilled clerical/Man. Workers Column totals:

N = 60

47 30 23 100

N = 58

38 22 40 100

N = 35

54 20 26 100

N = 33 52 33 15 100

N = 58

28 24 48 100

N = 54

28 20 52 100

N = 40

22 43 35 100

N = 38 23 45 32 100

N = 20

20 45 35 100

N = 16

19 31 50 100

N = 12

17 58 25 100

N = 13 15 62 23 100

N = 138

35 30 35 100

N = 128

31 23 46 100

N = 87

34 36 30 100

N = 84 33 43 24 100

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Table 7 Association between Occupational Status and MT Use Status Occupational

Status N χ2 df p Cramér's V Respondent's Last Occup. Respondent's Usual Occup. Spouse's Last Occupation Spouse's Usual Occup.

138

128

87

84

11.907

3.447

12.066

9.384

4 4 4 4

.018

n/s

.017

n/s

.208

n/a

.263

n/a

Where n/s = statistically not significant and n/a = non-applicable df = degrees of freedom.

Based on table 7, there are no statistically significant findings with the respondent's and

spouse's usual occupational background in relation to the outcome variable. As for the

respondents and their spouse's last occupation, these variables were found to be statistically

significant.

5.11 Skepticism

Table 8 provides an overview of the responses given (using percentages) pertaining to

skepticism. The scale used for this variable ranged from 1-5 (where 1 = strongly agree, 5 =

strongly disagree).

78

Table 8 Skepticism towards Orthodox Medical Practitioners Scale Measure

n

Strongly

Agree

%

Agree

%

Neither Agree nor

Disagree %

Disagree

%

Strongly Disagree

%

1. I can overcome most illness without help from a medically trained professional. 2. Home remedies are often better than drugs prescribed by a doctor. 3. If I get sick, it is my own behaviour that determines how soon I get well. 4. I understand my health better than most doctors do.

U = 62 N = 56 F = 21

U = 62 N = 58 F = 20

U = 62 N = 58 F = 20

U = 62 N = 57 F = 21

03 07 05

06 07 00

10 10 10

05 04 05

14.5 13 24

24 17 35

40 43 45

27 30 29

14.5 14 24

36 38 30

37 19 30

37 24 24

47 55 43

23 26 25

10 22 15

21 28 29

21 11 05

11 12 10

03 05 00

10 14 14

Where U = Users, N = Non-users and F = Former Users of massage therapy (MT). Except for rounding error, rows equal 100%. n = Number of respondents per group, per scale measure.

Highlights of the differences between the three study groups regarding skepticism, now

follows. Of the responses provided for question 1 (Q1), each group indicated a high tendency

(i.e. each with a mode of 4) to want to seek help from a medically trained professional when ill.

Upon comparing the mean and median scores between the groups it is evident from Q1 that

Users and Non-Users were very similar while Former Users differed by having a lower score.

This indicates that Former Users were inclined to state that they agreed with the notion that they

79

could overcome most illness without help from a medically trained professional, more so than

the other two groups (Table 8). For Q2, all three groups were similar in terms of their mean and

median values, although percentage wise, Former Users were more inclined to agree with the

idea that home remedies were often better than drugs prescribed by a doctor (Table 8).

Responses for Q3 show a similar pattern between the Non-Users and Former Users in terms of

their median and mean values, while Users tended to lean more towards stating that they neither

agreed nor disagreed. Further to Q3, overall the study groups sided with the notion that it was

their own behavior that determined how soon they would get well (Table 8). For Q4, differences

between the study groups are found when one compares their mode, however the median values

for this category are all the same, as are their ranges. Overall, pertaining to the respondents’

feedback on this measure, differences between the groups regarding skepticism appear minor.

This is evident when one totals the responses for each group where Users = 12.35 ± 3.06 (mean ±

SD), Non-Users = 12.40 ± 3.02 and Former Users = 11.7 ± 2.55.

5.12 Satisfaction

Table 9 provides summary descriptive statistics regarding "satisfaction". Non-Users of

MT were asked to skip this section of the questionnaire, as these questions were used to further

probe possible reasons for using massage therapy. Highlights of the differences between the two

study groups used on this section, based on the tables noted above, follows. For Q1 (question 1),

Users were more apt to strongly agree than Former Users, while the later were more apt to

moderately agree. For Q2 the mean and median scores were very similar, although Former Users

were more inclined to moderately disagree while Users strongly disagreed. For Q3, both groups

strongly disagreed and their mean and median scores were very similar. For Q4, Former Users

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were more prone to moderately agree (showing a maximum value of 2) while Users were apt to

moderately disagree (showing a maximum value of 4).

Table 9

Predisposing Characteristics – Satisfaction with the Orthodox Health Care System

Possible Reasons for Using Massage Therapy

Scale Measure

N

Strongly Agree

%

Mod. Agree

%

Mod. Disagree

%

Strongly Disagree

%

1. Because traditional treatment was not effective for your particular problem. 2. Because the traditional treatment you received had unpleasant side effects. 3. Because you found it difficult to talk to your doctor. 4. Because you value the emphasis on treating the whole person. 5. Because you believe that complementary medicine such as massage enables you to take a more active part in maintaining your health. 6. Because you believe complementary therapy will be more effective for your problem than traditional medicine.

U = 58 F = 19

U = 53 F = 18

U = 57 F = 18

U = 58 F = 19

U = 61 F = 20

U = 60 F = 20

43 16

09 11

04 06

05 04

82 65

38 20

31 58

19 22

09 11

27 30

16 30

38 65

19 16

34 50

21 22

37 24

02 05

23 15

07 10

38 17

66 61

21 28

00 00

00 00

Questions found in section B21-B26 of Appendix 01. Mod. = Moderately Where U = Users and F = Former Users of massage therapy (MT). Except for rounding error, rows equal 100%. n = Number of respondents per group, per scale measure.

81

Further to Table 9, by comparing the mean values in Q5, Users more so than Former Users

tended to strongly agree. In Q6, the User and Former User groups tended to moderately agree,

while showing very similar means and medians. Overall, pertaining to the responder's feedback

on this measure, differences between the User and Former User groups, regarding satisfaction,

appear minor. This is further evident when one totals the responses for each group and compares

them wherein Users = 12.23 ± 3.37 (mean ± SD), with a median value of 12, versus Former

Users at 12.74 ± 2.56, with a median value of 13.

5.13 Mastery

Table 10 provides frequency analysis (using valid percents) for questions poised to the

respondents regarding indicators of Mastery. Responses were gathered using a 5-point scale,

where 1 = strongly agree and 5 = strongly disagreed. Questions 5 and 7 were reverse coded.

Overall, respondents from the three groups did not differ remarkably when it came to

self-reporting their mastery. By calculating the total scores and comparing each of the study

groups, Users were found to have a median value of 27 and an overall mean of 26.24, with a

standard deviation of 5.08. This compares with Non-Users at 25.74 ± 4.46 (median = 27) and

Former Users at 25.24 ± 5.65 (median = 25). Based on these results, where the larger the score

the lower the mastery, Former Users were found to have slightly higher (more) mastery than the

Non-User and Former User groups (the latter two being almost tied).

82

Table 10 Mastery

Scale Measure

n

Strongly Agree

%

Agree

%

Neither Agree nor Disagree

%

Disagree

%

Strongly Disagree

%

1. You have little control over the things that happen to you. 2. There is really no way you can solve some of the problems you have. 3. There is little you can do to change many of the important things in your life. 4. You often feel helpless in dealing with problems in life. 5. What happens to you in the future mostly depends on you. 6. Sometimes, you feel that you are being pushed around in life. 7. You can do just about anything you really set your mind to do.

U = 62 N = 57 F = 21

U = 61 N = 58 F = 21

U = 61 N = 58 F = 21

U = 62 N = 58 F = 21

U = 62 N = 57 F =21

U = 62 N = 58 F = 21

U = 62 N = 58 F = 21

5 2 0 5 7 5 7 2 9 3 2 0

32 26 33 3 5 0

32 19 29

14 9 19

18 17 28

16 13 24

10 10 29

40 47 43

13 12 24

42 41 29

18 21 19

18 19 09

10 21 19

15 19 14

16 18 19

12 17 24

16 19 24

44 44 38

38 38 29

44 43 24

45 45 19

10 05 05

32 43 28

08 16 14

19 24 24

21 19 29

23 21 24

27 27 38

02 04 00

40 22 24

02 05 05

Questions found in section D1-D7 of Appendix 01. Where U = Users, N = Non-users and F = Former Users of massage therapy (MT). Except for rounding error, rows equal 100% (valid percent). n = based on actual number of respondents.

83

5.14 Self-Esteem

Table 11 provides frequency analysis (valid percents) for questions poised to the

respondents regarding indicators of their self-esteem. Responses were gathered using a 5-point

scale, where 1 = strongly agree and 5 = strongly disagreed. Except for question 6 (Table 11), the

lower the score the greater the degree of self-esteem. For question 6, the higher the score the less

the degree of self-esteem. Within question 1 of the self-esteem scale (Table 11), each group were

found to have a similar mode. Former Users were found to have a slightly higher mean and

median value. For question 2, all three groups had a similar mode and median value. This also

was true for Questions 3 and 4. For Question 5, all of the study groups had a similar mode but

their median values differed. Here, Former Users had a higher median value (higher self-esteem)

than Non-Users and Non-Users had a higher median (higher self-esteem) value than Users.

Finally, for question 6, all of the study groups had a similar mode and median values.

Overall, respondents from the three groups did not differ remarkably when it came to

self-reporting their self-esteem. By calculating the total scores and comparing each of the study

groups, Users were found to have a median self-esteem value of 8 and an overall mean of 8.33,

with a standard deviation of 2.79. This compares with the self-esteem of Non-Users at 9.41 ±

3.53 (median = 9) and Former Users at 10 ± 4.39 (median = 10). Based on these results, where

the lower the score the higher the self-esteem, Users were found to have slightly higher (more)

self-esteem than Non-Users, and Non-Users were found to have slightly higher (more) self-

esteem than Former-Users.

84

Table 11 Self-Esteem

Scale Measure

n

Strongly Agree

%

Mildly Agree

%

Neither Agree nor Disagree

%

Mildly Disagree

%

Strongly Disagree

%

1. You feel that you have a number of good qualities. 2. You feel that you are a person of worth at least equal to others. 3. You are able to do things as well as most other people of your age. 4. You take a positive attitude toward yourself. 5. On the whole, you are satisfied with yourself. 6. All in all, you are inclined to feel that you are a failure.

U = 61 N = 58 F = 21

U = 61 N = 58 F = 21

U = 61 N = 58 F = 21

U = 61 N = 58 F = 21

U = 61 N = 58 F = 20

U = 61 N = 58 F = 21

67 69 47

74 69 57

69 55 52

62 62 57

52 50 45

00 05 05

31 27 43

24 29 33

24 31 33

34 31 29

36 36 35

00 05 09

00 02 05

02 00 10

05 02 10

02 03 09

05 07 10

07 09 09

02 02 05

00 02 00

02 10 00

02 03 05

07 05 10

08 21 10

00 00 00

00 00 00

00 02 05

00 00 00

00 02 00

85 60 67

Questions found in section E1-E6 of Appendix 01. Where U = Users, N = Non-users and F = Former Users of massage therapy (MT). Except for rounding error, rows equal 100% (valid percent). n = actual number of respondents per group.

Having presented descriptive statistics of the predisposing characteristics of the sample, I

turn now my attention to present similar statistics for the enabling characteristics.

Enabling Characteristics

Overall, enabling characteristics influence one’s ability to secure services (de Boer,

1997). A condition which permits a person to satisfy a need regarding health services utilization,

85

Table 12 Financial Resources - Group Differences

Variables and Categories Users

% Non-

Users % Former Users %

Row Total %

Self-Assessed Financial Situation

Money meets most current needs - Yes

N=61

89

N=58 79

N=21 86

N=140 84

Money for Massage Therapy (MT) 1

Money to use MT when needed - Yes

N =62 60

n/a n/a

N =21 29

N=83 52

Payment Method Used for MT 1

Paid by Out of Pocket Paid by Private Insurance Other Column Total:

N=60 75 18 07 100

n/a n/a n/a n/a n/a

N=20 75 05 20 100

N=80 75 15 05 100

Respondent - Self Employed

Yes

N = 60 10

N = 58 02

N = 21 19

N=139 08

Respondent’s Employment Situation

Retired – no paid employment Homemaker Other Paid for 30 hrs./week Column Total:

N=62 73 05 04 08 100

N=57 86 12 00 02 100

N=21 76 10 14 00 100

N=140 78 09 09 04 100

Respondent's Spouse Self-Employed

Yes

N = 56 14

N = 55 04

N = 21 00

N=132 08

Total Annual Household Income < 29,999 30K – 59,999 60K + Column Total:

N=53 32 38 30 100

N=57 58 35 07 100

N=19 84 11 05 100

N=129 51 33 16 100

Health Insurance beyond OHIP 2

Yes

N=61 67

N=57 42

N=21 24

N=139 50

The number of User, Non-User and Former User respondents varied per variable, as indicated above 1 = Where Non-Users of MT are excluded. 2 = OHIP : Ontario Health Insurance Plan (Government subsidized).

86

for example, may be considered an enabling factor. Factors considered in the present study under

the umbrella of "Enabling Characteristics" include data on the respondent's financial resources,

psycho-social and family resources, as well as the respondent's health network.

Table 12 considers pre-selected factors associated with the respondent's financial

resources. These are considered individually using descriptive statistics, for the purpose of

comparing differences between the study groups.

5.15 Self-assessed Financial Situation

Respondents were asked, via a pre-tested postal questionnaire, if the money they have

meets their current needs (I15, Appendix 1). Of interest was that all three study groups were

inclined to indicate "yes" (Table 11). Using a scale of 1-2, where 1=yes and 2=no, the mode as

well as median values for all three groups was equal to 1. The mean ± standard deviations for the

three groups, pertaining to this variable were: 1.11± .321 for the Users, 1.21± .409 for the Non-

Users and 1.14 ± .359 for the Former Users of massage therapy (MT). Based on the descriptive

data obtained, it was found that the three study groups self-reported minor to no differences

regarding their self-assessed financial situation.

5.16 Money for Massage Therapy

Users and Former Users of massage therapy (MT) were asked if they felt they had

enough money to use massage therapy when they needed to (B10, Appendix 1). Non-Users were

excluded, as this question was deemed at the time to be unrelated to their particular situation.

Overall, it was found that Users were more inclined to say yes than Former Users (Table 12).

Using a 1-3 scale, where 1 = Yes, 2 = No and 3 = unsure, Users had a mode and median of 1

87

while Former Users had a mode and median value of 2. Further, Users indicated a mean ± SD

value of 1.55 ±.739 while Former Users showed a value of 1.95 ±. 740. Overall, Users self-

reported more so than Former Users as having money for MT when needed, although both

groups had a high number of individuals (i.e. n=25, 40% - of the User group and n= 15, 71% of

the Former Users) who said no.

5.17 Payment Method for Massage Therapy

Former Users and Users of MT were asked what their payment method for MT was (I16,

Appendix 1). The majority in both groups paid for MT out of pocket, although Users also had

used extra private insurance (beyond the Ontario Hospital Insurance Plan - OHIP), more so than

the Former User group (Table 12). Former Users were more inclined to indicate than Users that

they had paid for their MT treatment using other forms of payment (e.g. paid by spouse).

Overall, Users and Former Users varied little in the manner they paid for their MT treatment(s).

5.18 Respondent's and their Spouse's Self-Employment Status

Respondents were asked if they and/or their spouse (if applicable), were self employed

(I2 and I4, Appendix 1). Proportionately more of the Users followed by the Former Users and

then the Non-Users were inclined to indicate they were self-employed (Table 11). As for their

spouses, the User group had more spouses self-employed than the Non-Users while the Former

User group found this to be non-applicable (Table 11).

88

5.19 Respondent's Employment Situation

Based on the responses to section I1 of Appendix 1, it was found that the mode and

median category for all three study groups was being retired and no longer in paid employment.

Proportionately, this was particular evident amongst the Non-Users (Table 12). The

"homemaker" and "other" categories tied and were both subsequently ranked second, while being

"paid for 30 hours per week" ranked third. Fewer Users than the other two groups indicated

being a homemaker. Former Users were inclined to be placed in the '"other" category, more so

than the Users and, much more than the Non Users of MT (Table 12).

5.20 Spouse's Employment Situation

From the responses provided to section I3 of Appendix 1, it was found that, while many

of the respondent's spouses were classified in the "other" category, Non-User's spouses in

particular fitted into this category. The "retired and not in paid employment" category ranked

second for all study groups spouses, although Former User's spouses were more represented

(Table 12). Spouses from the User and Former User groups were tied in the third ranked

category of homemaker, while this was non-applicable for the Non User's spouses (Table 12).

5.21 Total Annual Household Income

As further denoted in Table 12, the respondent's total annual household income also was

considered (I18, Appendix 1). Proportionately, more Former Users than Non-Users, and more

Non Users than Users of MT earned an annual household income of less than $29,999 (coded 1).

Secondly, more Users than Non-Users, and more Non-Users than Former Users earned an annual

household income of $30,000 - 59,999 (coded 2). And, more Users than Non-Users, and more

89

Non-Users than Former Users earned an annual household income of $60,000 or more (coded 3).

Using the codes noted as a reference to income level, Users were found to have a mean and

standard deviation of 1.98± .796 (with a median and mode of 2) followed by Non-Users at 1.49±

.630 (with a median and mode of 1), and Former Users at 1.21± .535 (also with a median and

mode of 1). In summary, through the use of descriptive statistics, Users are found to have better

incomes than Non-Users while Non-Users are found to have better incomes than Former Users.

5.22 Added Health Insurance - Beyond OHIP

To ascertain if the respondents had health insurance beyond the Ontario Hospital

Insurance Plan (OHIP), a dichotomous variable (yes/no) was used (I7, Appendix 1). Users more

than Non-Users, and Non-Users more than Former Users were found to have added health

insurance (Table 11). Of interest was that of the 139 respondents to this question, half had added

health insurance (Table 11).

5.23 Respondent's Sources of Income

Table 13 indicates the varied sources of income within and between the respondent

groups. The majority within all three groups (users, non-users and former users of MT) received

the Canada Pension Plan (CPP) as well as Old Age Security (OAS), although, fewer Users of

MT than the other two groups indicated they were receiving OAS. As well, Users, more so than

Non Users, and a great deal more than Former Users, indicated they received a work/company

pension. Of interest was that savings and interest ranked higher as a source of income than

obtaining a work/company pension. Further, non-RRSP investments were found to be more

90

common among Users, followed by Non-Users. Much fewer Former Users had this as a source

of income.

Sample responses for the "Other" category, as sources of income, included such

responses as: royalties, estate, Quebec Pension, US Social Security, disability, and family. More

Users than Non Users and more Non Users than Former Users indicated having more "Other"

sources of income.

Table 13 Ranked Sources of Income - %

Sources of Income (varied)

Canada Pension Plan Old Age Security Savings & Interest Work/Company Pension Other Non-RRSP Investments

Users N=62

85 69 53 53 40 32

Non-Users N=57

89 84 33 46 32 30

Former Users N=21

90 86 57 19 29 10

Row Total N = 140

88 78 46 45 35 28

Multiple sources - columns and rows do not add to 100%.

5.24 Living Arrangement

Regarding the living arrangement of the respondents, (section I5 of Appendix 1) a code

of 1 = lived alone, a code of 2 = with spouse or partner, code 3 = lived with daughter or son and

a code of 4 = other. The majority of Former Users (1.4 ± .746) (mean ± SD) and Non-Users (1.4

± .662) lived alone (both with a median of 1) while the majority of the Users (1.7 ± .893) did not

(with a median of 2). Users and Former Users were found to have a range of 1-4 while the Non-

Users had a range of 1-3. As a nominal variable, chi-square (cross-tabulation) was used. The

respondent's living arrangement was not found to be statistically significant to MT Use status (χ2

= 9.523, df=6, p = .146).

91

5.25 Housing Arrangement

Table 14 also indicates the housing arrangement of the respondent, during the time of the

data collection. It was found that the majority of respondents (n=109 of 141) did not live in rent

subsidized or public housing (1.7 ± .420), where 1 = yes and 2 = no. Interestingly, Former Users

of MT were more apt to live in rent subsidized or public housing than Non-Users. Non-Users

were more apt to do so than Users (Table 14).

The respondent's housing arrangement was found to be statistically significant to MT Use

status (χ2 = 6.190, df=2, p = .045), although the strength of this association was found to be weak

at .210, using Cramer's V.

Table 14 Living Arrangement

Variables and Categories Users

% Non-

Users % Former Users %

Row Total %

Living Arrangement

Lives Alone Other Column Totals - %:

Lives in Rent Subsidized and/or Public Housing

Yes No Column Totals - %:

N = 61

48 52 100

N = 62

13 87 100

N = 58

66 34 100

N = 58

29 71 100

N = 21

67 33 100

N = 21

33 67 100

N = 140

58 42 100

N = 141

23 77 100

Where N= is based on number of respondents. See text for chi-square values. 5.26 Health Network Resources

A consideration of the respondent's lay and professional health network was considered

(chiefly, who the respondent confides in on matters pertaining to their health and where they

usually seek to obtain health information). Table 15 denotes the results.

92

Table 15 Health Network Resources

Scale Measure

Users %

Non-Users %

Former Users %

Row Total %

1) Person to confide

in and talk to

regarding problems

with health.

Doctor Family and Friends Alternative Practitioner Hospital Specialist Other No One

(2) Person counted on

to provide general

health information

Doctor Family and Friends Alternative Practitioner Hospital Specialist Other No One

N = 62

89 84 79 34 11 00

N = 62

90 57 65 37 15 02

N = 58

90 86 10 36 05 00

N = 58

95 50 14 33 10 02

N = 21

91 71 52 20 14 05

N = 21

86 38 43 10 19 05

N = 141

89 83a 47 33b 09 01

N = 141

91 51 40 31 13 02c

Columns do not equal 100% (varied sources). Related to sections F1/F2 of Study questionnaire In a, b, and c: row percentages are adjusted. As shown in Table 15, the scale categories (doctor - no one) are ranked from the most common

to least common sources sought for information. The following highlights were found within

question one (i.e. seeking out a doctor to confide in and talk to regarding health) - all three

groups sought the advice of a doctor; Former Users were less inclined than the other two groups

to seek out friends and family; Non-users were much less inclined than Former Users and even

more less inclined than Users to seek out an alternative practitioner; and, Former Users were less

inclined to seek out a hospital specialist than the other two groups.

93

Non-Users were found to have fewer "other" sources to pursue when compared with the

other study groups. Only one respondent from the study sample, a Former User, indicated having

no one to confide in. Those in the "other" category noted by the respondents in the pre-tested

postal questionnaire included a: chiropractor, dentist, the Internet, a lung specialist, a

rheumatologist, psychiatrist and, a physiotherapist.

Further to Table 15, as to a person counted on to provide general health information, the

following highlights were found within question two: all three groups were inclined to count on

their doctor; Former Users less than Non-Users and Non-Users less than Users counted on their

family and friends; Non-Users were much less willing than the Former User and User groups to

count on an alternative practitioner; Users more so than Non-users and Non-Users more so than

Former Users counted on a hospital specialist; Non-Users had fewer "other" sources to confide in

than the other study groups. Finally, only 1 respondent for each study group indicated they had

no one to count on. Among those indicated in the "other" category included a: pharmacist,

naturopath, chiropractor, dentist, the Internet, medical books, medical friends, a psychiatrist,

physiotherapist, CARP (Canadian Association of Retired Persons), and, a public health nurse.

Users were more inclined to specify an alternative practitioner than the other study groups.

5.27 Source of Referral to MT

Non-Users of MT were excluded, as this category was not applicable to their situation. As

indicated in Table 16, the most common source of referral to MT for both groups, but more so

for the Former User group, was a friend. The next ranked response for this category was "no

one." Potential alternative sources for information on MT may have been derived from their

CAM knowledge sources, soon to be discussed. Another common source of referral to MT,

94

particularly for the Former Users, was the family doctor (Table 16). Following this, an added

common source, noted only be the User group, was that of a chiropractor. No specifics as to what

the other sources of referral to MT were was gathered. Overall, both Users and Former Users had

a variety of sources of referral to MT provided to them.

As a nominal-level variable, a chi-square test for k independent samples was used. This

indicated that the source of referral to MT was not statistically significant in relation to its'

association to that of the outcome variable (χ2 = 16.980, df = 12, p = .150).

5.28 Respondent's Knowledge of Massage Therapy (MT)

Respondent's ranked their knowledge about MT using a 4-point scale from 1=expert to 4

= very little or nothing. Non-Users more than Former Users, and Former Users more than Users

indicated they knew little or nothing about MT. When percentages are used, Former Users vary

very little compared to Non-Users (Table 16). More significant differences transpire when the

mean ranks of the study groups are compared. Here, Users of MT were found to have a mean

rank (MR) of 43.97, which compares significantly to the Non-Users mean rank of 101.18 and the

Former Users mean rank value of 67.45. As an ordinal-level measure, a Kruskal-Wallace chi-

square for k independent samples statistic was used, which revealed a highly statistically

significant association between the respondent's knowledge of MT and their MT use status (K-W

χ2 = 69.192, df = 2, p = .000). Post-hoc analysis using Mann-Whitney U tests indicate that all

three groups have a highly statistically significant association to the outcome variable (p = .000

to p = .002).

95

Table 16 MT Knowledge and Referral

Variables & Categories

Users

%

Non-Users

%

Former Users

%

Row Total

%

P

Source of Referral to MT

A Friend No One Other Family Doctor Chiropractor Column total:

Resp. Knowledge of MT

Little/Nothing A Lot/Expert Column total:

CAM Knowledge Sources1

Alternative Practitioner Family and Friends Doctor No One Hospital Specialist Other

N = 59

25 25 21 12 17 100

N = 62

65 35 100

N = 61 77 57 41 08 17 11

= 0 n/a n/a n/a n/a n/a n/a

N = 58

98 02 100

N = 58 12 33 31 41 07 03

N = 19

32 26 21 21 00 100

N = 21

95 05 100

N = 21 48 33 29 25 05 14

N = 78

27 26 20 14 13 100

N = 141

83 17 100

N = 140 46 44 35 24 11 09

p = .150

(χ2)

p = .000 (K-W)

p = .000 (χ2)

Where 1 = varied sources, therefore column does not equal 100%.

5.29 CAM Knowledge Sources

Table 16 provides a breakdown of the most common CAM knowledge sources revealed

by the study respondents. While such sources vary by group, the most common source for CAM

knowledge came from alternative (CAM) practitioners, followed by family and friends, one's

family doctor, "no one" and then hospital specialists. The least common was under the category

of "other" which was reported by the respondents as including: the Internet, the media,

pharmacists, physiotherapists, a public health nurse, health stores, a psychiatrist and, a close

relative (i.e. daughter).

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Not surprisingly, Users indicated much more than Non Users as consulting a CAM

practitioner. Moreover, Users were found to rely on family and friends and their doctor for CAM

knowledge more so than the other two study groups. Non-Users on the other hand were much

more apt than the other groups to indicate they had no one as a source of CAM information.

Further, Users were more than twice likely than Non-Users and more than three times as likely

than Former Users to obtain CAM information from hospital specialists. Former Users reported

more than Users, and Users reported more than Non-Users to use "other" sources for their CAM

knowledge (Table 16).

CAM knowledge sources was found to be highly statistically significant to that of the

outcome variable. As a nominal-level variable, a chi-square test for k independent samples was

used with the following results: χ2 = 40.953, df = 10, p = .000). The strength of this association

at .382 was found to be strong (i.e. greater than .3).

Having presented descriptive statistics of the enabling characteristics of the sample, I turn

now my attention to present similar statistics for the need characteristics, for purposes of

comparing the results within and between the study groups.

Need Characteristics

"Need" refers to the illness and/or morbidity characteristics of the study respondents. Pre-

selected need characteristics of the present study include the respondent's self-reported

information on: their morbidity (i.e. number of chronic conditions), chronic condition types,

ADL (activities of daily living) / IADL (instrumental activities of daily living) and, number of

hospital days within a 12 month time period.

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5.30 Self-Perceived Health Status

Table 17 provides frequency distributions of the respondent's self-perceived health status.

Table 17 Perceived Health Status and Benefits of CAM and MT

1 Frequency distributions based on total number of responses provided. 2 Of this measure only, Non-Users of MT are excluded (where n/a = non-applicable).

Table 17 provides a break down of the respondent's health status (population and cohort

compared) which was self-rated from 1-5 (excellent to poor). The respondent's self-perceived

benefits of complementary/alternative medicine (CAM) and massage therapy (MT) also was

rated, from 1-6 (excellent to unsure).

These findings indicate that the Former Users were more inclined than the other two

study groups to indicate that their health was good to excellent, when population compared,

Variables and Categories Users

% Non-

Users % Former Users %

Total %

Health Status –Population Compared Good/Very Good/Excellent Fair/Poor Column totals: Health Status-Cohort Compared Good/Very Good/Excellent Fair/Poor Column totals: Self-Perceived Benefits of CAM Very Good/Excellent Good Fair/Poor/Unsure Column totals: Self-Perceived Benefits of Massage Therapy2 Very Good/Excellent Good Fair/Poor/Unsure Column totals:

N = 62

73 27 100

N= 62

89 11 100

N = 62

61 23 16 100

N = 62

89 08 03 100

N = 58

71 29 100

N =57

79 21 100

N = 55

07 18 75 100

n/a n/a n/a n/a n/a

N = 21

81 19 100

N = 21

81 19 100

N =20

40 30 30 100

N = 20

65 20 15 100

N = 141

73 27 100

N = 140

84 16 100

N = 137

36 22 42 100

N = 82

83 11 06 100

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whereas in the cohort compared category, Users of MT were more apt than the other groups to

indicate that their health status was good to excellent. Non-Users were more inclined to rate their

health as fair or poor when cohort compared.

Within the population compared category, Users are found to be more optimistic about

their health showing a mean score of 2.79 and a standard deviation of 1.01 (mode =2), which

compared with the Former Users at 2.90 ± .830, with a mode of 3, followed by Non-Users at

2.98 ±.888 with a mode of 3. The median for all three groups was 3. A slightly different pattern

emerges with respect to the respondent's self-reported health status when cohort compared. Here,

Users are found, again, to be more optimistic about their health than the other groups showing a

mean score of 2.40 and a standard deviation of .949 (mode =2), only this time Non-Users are

found to be more optimistic about their health at 2.58 ±1.07 (mode =3) relative to Non-Users at

2.67 ±.913 (mode =3). Users had a median score of 2 whereas the Non-User and Former User

groups had a median score of three. The ranges are almost identical in the population and cohort

comparisons. Overall, findings indicate that the three study groups show little difference when it

comes to their self-perceived health status.

5.31 Morbidity

Respondents were asked how many chronic (on-going) health problems they had at the

time of the data collection period, lasting for six or more months (section C13 of Appendix 1).

Respondents must have had at least one chronic condition in order to have participated in the

study. A scale from 1 to 6 was used where 1 = none, 2 = one, 3 = two, 4 = three, 5 = four or more

and 6 = unsure. Comparisons to other responses in the questionnaire (e.g. question C14

Appendix 1) were made for those who responded either as "none" or "unsure" to further

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determine their eligibility. Following such screening it was found that, relative to the number of

chronic conditions they had, Users (n= 59) and Non-Users (n = 58) of MT had a mode of 3 while

Former Users (n = 21) had a mode of 2. All three study groups were found to have a median

value of 3.

Proportionately, based on the number of respondents: more Former Users (14%) than

Non-Users (12%) and Users (9%), self-reported having four or more chronic conditions; more

Non-Users (20%) than Users (19%) and Former Users (10%) had three chronic conditions; more

Users (39%) than Non-Users (35%) and Former Users (33%) had two chronic conditions; while

more Former Users (33%) than Non-Users (29%) and Users (25%) self-reported having only one

chronic health condition.

As the measure of morbidity used here is a continuous variable, Spearman's rho was used

to determine association. No statistically significant association between the number of chronic

conditions a respondent has had, and their MT use status, was found (r = .037; p = .663 two-

tailed; p = .332 one-tailed).

5.32 Chronic Condition Types

Respondents were asked to choose from a pre-selected list of on-going health conditions

(indicators derived from the Canadian National Population Health Survey) to which they self-

reported currently having for six months or more, and diagnosed by a medical doctor (section

C14, Appendix 1). Table 18 ranks these conditions as per the responses provided.

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Table 18 Respondent's Self-Reported Chronicity - %

Percentages per column based on respondent participation (valid percents). Based on section C14 of Appendix 1. n/s = not found statistically significant to MT use status.

Arthritis/Rheumatism followed by back problems and high blood pressure were among the

conditions cited most by the study respondents, while such conditions as diabetes, headaches,

lung and kidney conditions ranked the lowest (Table 18). Two example differences between the

groups are as follows: Non-Users more than Users, and Users more than Former Users reported

having arthritis/rheumatism. Non-Users more than Former Users, and Former Users more than

Users self-reported having high blood pressure (Table 18).

5.33 ADL/IADL/Mobility

Table 19 provides frequency data comparisons between the three study groups in relation to their

self-reported ADL/IADL and mobility characteristics. Data suggests that Users reported more

than the other two groups as having "no difficulty" with the ADL/IADL and mobility measures

provided.

Chronic Condition Type(s) Users

% Non-

Users % Former Users %

Row Totals %

χ2 p

Arthritis/Rheumatism Back Problems High Blood Pressure Other Muscular-Skeletal Pain Osteoporosis Bowel/Digestive Condition Heart Condition Diabetes Headaches Lung Condition Kidney Condition

57 58 26 39 39 18 18 19 11 10 08 03

62 24 45 22 19 29 17 22 14 10 07 07

52 43 38 24 14 24 29 05 10 10 14 05

58 42 35 30 27 23 19 18 12 10 09 05

n/s .001 n/s ---- .019 n/s n/s n/s n/s n/s n/s n/s

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With the exception of "preparing meals" and "bathing", Former Users had lower mean

scores than the Non-Users for the remainder of the categories. While generally speaking it may

be said that the Users had higher functional status than the Former Users, and Former Users had

higher functional status than the Non-users, within most of the categories used for this measure

all three groups had similar median and mode values (indicating very little differences between

the groups). The exception to this is Non-Users having a higher median and mode value than the

Users in being able to go up and down stairs. Former Users had the same median as the Non-

Users in this regard, but a lower mode value.

Overall, all three groups showed little difference pertaining to their mobility and ADL

and IADL indicators used (Table 19).

5.34 Hospital Days

The final need characteristic considered is with reference to section C12 (Appendix 1) which

asked the respondents to report how many days they had spent in the hospital in the last 12

months (from the time of data collection). The scale used was 1= none to 4 or more months = 6.

Results indicate that most of the study respondents spent no days in hospital within the time

frame suggested. Only 1 Former User self-reported having spent 1 week or less in the hospital

while Non-Users (21% of N=58) more than Users of MT (13% of N =62) reported being in the

hospital for the same period. One User (2%) and two Non-Users (3.4%) indicated they spent less

than one month in the hospital. Further, one Non-User (2%) indicated having spent 2-3 months

in the hospital while one User stated having spent 4 or more months.

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Table 19 Need Characteristics – ADL/IADL/Mobility % N=141

Scale Measure Study Group

No Difficult

y

%

A Little Difficulty

%

A Lot of Difficulty

%

Unable

%

Dress (ADL) Bathe (ADL) Use Phone (IADL) Manage Money (IADL) Prepare Meals (IADL) Get out of Home (IADL) Go Up and Down Stairs (Mobility) Use Public Transport (Mobility)

U = N = F =

U = N = F =

U = N = F =

U = N = F =

U = N = F =

U = N = F =

U = N = F =

U = N = F =

86 74 81

81 72 71

92 95 95

100 88 95

87 81 81

81 71 81

53 31 48

74 57 67

13 26 14

18 24 19

08 03 05 0 12 05

11 17 10

16 22 9.5

36 52 33

14 28 19

01 0 05

01 03 10 0 02 0 0 0 0

02 02 09

03 07 9.5

11 17 19

07 10 09

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

05 05 05

Questions found in section C3-C10 of Appendix 01. Based on number of responses. Where U = Users (n=62), N = Non-users (n=58) and F = Former Users (n=21) of massage therapy (MT). Except for rounding error, rows equal 100%.

103

Overall, the three groups differed very little regarding the number of hospital days they

had spent over the past 12 months. All groups have the same mode and median value of 1. The

mean and standard deviation for the Users with this measure was 1.24 ± .739, for the Former

Users it was 1.05 ± .218 and, for the Non-Users it was 1.34 ± .715. As hospital days is a

continuous variable, Spearman's rho was used to ascertain association. No statistically significant

association was found between the respondents’ number of hospital days and MT use status (r =

-.015, p = .430 one-tailed, p = .860 two-tailed).

Further results of the data will now be presented using correlational analysis.

5.35 Correlation Findings Individual variable s determined to be statistically significant to the outcome are now

examined using a correlation matrix (via Spearman’s rho). Readers are directed to the summary

correlation tables denoted at the end of this chapter (Tables 20-22). Table twenty provides a

summary of all variables used in this study, and their correlation to the outcome, while Table 21

indicates only those variables determined to be statistically significant. Table 22 then provides a

correlation matrix of these variables (as denoted in Table 21). An elaboration of sample findings

from Table 22 is denoted below.

In reviewing some of the correlation coefficients we see that Table 22 indicates that

gender is determined to be correlated only with income (.215, at the .05 level). Education on the

other hand is found to be correlated with all 13 variables considered, with the exception of

having back problems and ability to walk up and down stairs. For example at the .01 level of

significance, education was determined to be correlated with the respondent’s last occupation

(.581), health and social network (where N1 is equal to .424, N2, .392 and N3 at .409), income

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(.503), added insurance (.274) and, self-reported muscular-skeletal conditions (.235). At the .05

level of significance, education appears correlated with the respondent’s employment situation

(.201).

As further examples denoted in Table 22, the variable ‘total annual household income’

was also found to be statistically significant at the .01 level, with not only the outcome variable

but also to the following: respondent’s last occupation (.478), health and social network (where

N1 is equal to .314, N2, .433 and N3 at .439), added insurance (.324), subsidized housing (-.407)

and, ability to climb up and down stairs (.270) – Table 22. Further, the variable ‘added

insurance’ was found to be statistically significant at the .01 level to the following: respondent’s

education (.274), last occupation (.220), health and social network (where N1 is equal to .288,

N2, .266 and N3 at .385), subsidized housing (-.243), and, income (.324). Also, at the .05 level of

significance, education (.201) and last occupation (.208) where determined to be associated with

employment situation. And so forth. In summary, what Table 22 conveys, and as further

elaborated in the next chapter, is that dialectical interplay that exists among the study variables,

be they predisposing, enabling and/or need characteristics.

Following this chapter’s endnotes, which provide data relevant to Tables 20-22, this

study will then turn its attention to using the statistically significant variables in a step-wise

regression analysis so as to help pinpoint this study’s strongest variables associated with MT use.

By doing so, key differences in profiles between users and non-users of MT within this study

may then be disclosed.

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Table 20 Summary of All Variables Used and their Correlation to the Outcome

PREDISPOSING CHARACTERISTICS

Socio-demographic Background Beliefs and Attitudes - Age [cc = -.115, p = .173] - Mastery [cc = -.067, p = .431] - Gender [cc = .185*, p = .028] - Satisfaction [cc = .-.064, p = .575] - Marital Status [cc = .130, p = .125] - Self-esteem [cc = .157, p = .064] - Education [cc = .328**, p < .001] - Skepticism [cc = -.007, p = .930] - Current Employment Situation [cc = .237**, p = .005] - Last occupation [cc = .252**, p = .003] - Usual occupation [cc = -.136, p = .124] - Self-employed [cc = .067, p = .431]

↕ ENABLING CHARACTERISTICS

Financial Situation

- Subsidized Housing [cc = -.207*, p = .014] - Health Insurance (beyond OHIP) [cc = .298**, p < .001]

- Current money meets needs [cc = -.102, p = .229] - Number of people in household [cc = .095, p = .268]

- Total Annual Household Income [cc = .362**, p < .001]

Health and Social Network - (F1) [cc = .329**, p < .001] - (F2) [cc = .350**, p < .001]

- (F3) [cc = .475**, p < .001]

↕ - NEED CHARACTERISTICS -

Health Status - Population compared [cc = -.104, p = .218]

- Cohort compared [cc = -.105, p = .219] - Number of chronic conditions [cc = .045, p = .600]

- Hospital days [cc = .052, p = .544]

Chronic Condition Type(s) - Muscular-skeletal condition(s) [cc = .235**, p = .005]

- Back problem(s) [cc = .291**, p < .001]

ADL/IADL/Mobility Abilities - Walk up/down stairs [cc = .176*, p = .037]

Where: cc = correlation coefficient / p = significance (* at .05. ** at .01)

106

107

Table 22 Summary of 13 Variables Considered For Logistic Regression Analysis

PREDISPOSING CHARACTERISTICS

Socio-demographic Background - Gender [cc = .185*, p = .028]

- Education [cc = .328**, p < .001] - Current Employment Situation [cc = .237**, p = .005]

- Last occupation [cc = .252**, p = .003] ↕

ENABLING CHARACTERISTICS

Financial Situation - Subsidized Housing [cc = -.207*, p = .014]

- Health Insurance (beyond OHIP) [cc = .298**, p < .001] - Total Annual Household Income [cc = .362**, p < .001]

Health and Social Network

- (F1) [cc = .329**, p < .001] - (F2) [cc = .350**, p< .001]

- (F3) [cc = .475**, p < .001]

↕ NEED CHARACTERISTICS

Chronic Condition Type(s)

- Muscular-skeletal condition(s) [cc = .235**, p = .005] - Back problem(s) [cc = .291**, p < .001]

ADL/IADL/Mobility Abilities

- Walk up/down stairs [cc = .176*, p = .037]

Where: cc = correlation coefficient / p = significance (* at .05. ** at .01)

108

Chapter 6

Binary Logistic Regression Analysis Results 6.1 Introduction

Relevant results from the previous chapter serve as a bridge for this chapter. Specifically,

the thirteen study variables determined to be statistically significant via correlation analysis – as

denoted in chapter 5 - are now further considered. Each are individually considered in Table 6.1.

Table 6.1 Individually Entered Variables using Binary Logistic Analysis - MT Utilization Variable OR Wald β 95% CI S.E. p Predisposing Characteristics Gender (ref. - female) (n=141) 2.47 4.68 .903 1.09-5.59 .417 .030 Education (n= 140) 1.75 13.46 .557 1.29-2.35 .152 .000 Last occupation (n=138) --- 6.57 ---- ------- ----- .012block Last occupation-1 .286 8.45 -1.25 .123-.665 .431 .004 Last occupation-2 .559 1.83 -.582 .241-1.29 .430 .176 Employment situation* (n=140) --- 6.57 ---- ----- ----- .023block Homemaker (1) --- ---- -22.3 ----- 8420.9 ---- Retired (2) --- ---- -21.6 ----- 8420.9 ---- 30+ hrs work --- ---- -19.6 ----- 8420.9 ---- <30 hrs work --- ---- -20.5 ----- 8420.9 ---- Looking for work --- ---- ---- ----- 8420.9 ---- Enabling Characteristics Annual household income (n=129) 1.55 17.35 .435 1.26-1.89 .105 .000 Added health insurance (n=139) 3.46 11.94 1.24 1.71-7.01 .360 .001 Health and Social Network:

F1 (total) (n=141) 2.08 12.81 .734 1.39-3.12 .205 .000 F2 (total) (n=141) 2.12 14.32 .753 1.44-3.14 .199 .000 F3 (total) (n=140) 3.56 21.46 1.27 2.08-6.09 .274 .000 Subsidized Housing (n=141) .340 5.74 -1.08 .140-.822 .451 .017 Need Characteristics Chronic condition type(s): Back problem(s) (n=141) 3.37 11.58 1.22 1.67-6.79 .357 .001 Muscular-skeletal problem (n=141) 2.93 7.47 1.08 1.36-6.34 .393 .006 ADL/IADL/Mobility: Up/down stairs (ref. – yes) (n=141) 1.69 4.43 .529 1.04-2.78 .251 .035 Dependent variable: MT use status. Here: OR = Odds ratio, β = Beta, CI = confidence interval, n = number of respondents, S.E. = standard error; p = significance of the Wald statistic at the 0.05 level. F1-F3 refer to health and social network; ref. = reference category; * indicates that this variable had very low frequencies, therefore, proper estimation of parameters could not be conducted.

109

Category variables ‘last occupation’ and ‘employment situation’ denoted a corresponding

block chi-square value of p = .012 and p = .023 (table 6.1). The probability for stepwise was set

at p = .05 at entry and p = .10 for removal. In table 6.1, each variable was entered individually

and compared to the outcome (MT use status) using binary logistic regression (via SPSS version

15.1). This was coded so that an increase of the variable corresponded to an increase in odds of

MT utilization. Variables that required re-coding included: gender, last occupation, having added

insurance, as well as back and muscular-skeletal conditions. Reasons why logistic regression is

the statistical model of choice are denoted in chapter 4.

Results denoted in table 6.1 indicate that those variables with a high Wald statistic

included such variables as: education; back problems, F1-F3 – total (health and social network);

and, income. The Wald test is particularly useful to help determine the importance of an

individual coefficient (Katz, 1999).

Table 6.2 shows how categorical variables were handled in the analysis. For this study,

the first category served as the reference category for each of the categorical variables. For

example, for the variable “Last Occupation” two coefficients were obtained – one comparing

category 2 to category 1 and secondly comparing category 3 to category 1. For all binary

variables, the “yes” category was compared to the “no” (reference) category. Therefore, the

regression coefficients relate to having some quality versus not having it.

110

Table 6.2 Predictor Category Frequency (N=125) Current Employment Homemaker 12

Situation. Retired 95 Paid 30hrs/week 06

Unemployed 01 Collecting welfare 02

Last Occupation Unskilled/clerical 46 Sales/skilled clerical 38 Professional/Managerial 41 Walk up/down No difficulty 20 stairs. A little difficulty 54 A lot of difficulty 51 Back Problem(s) No 74 Yes 51

Muscular-Skeletal No 94 Problem(s) Yes 31 Subsidized Housing No 95 Yes 30

Added Health Insurance No 62 Gender Female 99 Male 26

The variable “employment situation” required elimination. Here, most people in this

dataset were retired and other categories had very low frequencies (see Table 6.2). Therefore,

proper estimation of parameters for this variable could not be conducted. It is noted that, if this

variable was not removed at this point, it would have been eventually during the step-wise

process at step 4. Moreover, by dropping this variable we gained another respondent (from an

n=125 to an n= 126.

111

6.2 Second Phase

In the next phase of the analysis, towards the process of establishing the final logistic

regression model, I used an SPSS syntax command to request from SPSS a logistic regression

analysis with backward stepwise elimination of the remaining 12 variables of interest. This

analysis transpired in ten steps, meaning that most variables used at this stage were eliminated

one by one.

The logic of using step-wise regression is that the final model is parsimonious as it

contains variables that have little correlation with each other. Indeed, an important goal in

regression analysis is to arrive at adequate descriptions of observed phenomena. This allows a

researcher to isolate the most important variables (Chatterjee et al., 2000). Moreover, this allows

us to see the odds ratio when adjusted for other variables in the model. Overall, of the original

dataset of n=141, 126 cases were included in the analysis. This included n=75 non-users and

n=51 users. Users of MT were coded as “1” and non-users were coded as “0.”

Table 6.3 is a summary table denoting, for example, when the elimination of variables

took place (at which step “S”), using step-wise regression. We see here that all of the

predisposing characteristics entered into the logistic regression equation were eliminated by step

5 (of 10), with gender, for example, eliminated at step four and, education at step five.

112

Table 6.3 Full Model - All Variables Included in the Logistic Regression Variable β p OR SE S CI

PREDISPOSING

Gender 0.284 0.644 1.33 0.61 4 .398-4.43 Education 0.126 0.557 1.13 0.21 5 .746-1.72

Last Occupation ----- .921 ----- ---- 1 -------- Last Occupation – 1 -0.018 0.98 0.98 0.71 1 .246-3.92 Last Occupation – 2 0.240 0.71 0.79 0.64 1 .222-2.78

ENABLING

Ann. House Income .379 .002 1.46 .121 10 1.15-1.85 Added H. Insur. .330 .505 1.39 .494 8 .528-3.66

Subsidized Housing -.201 .755 .818 .645 3 .231-2.89 F1 – Network .221 .460 1.25 .299 6 .694-2.24 F2 – Network -.040 .912 .961 .360 2 .474-1.95 F3- Network .949 .001 2.58 .294 10 1.45-4.59

NEED

Up and down stairs ---- .381 ---- ---- 7 -------- Up and down stairs-1 -.766 .308 .465 .751 7 .107-2.03 Up and down stairs-2 -.697 .200 .498 .544 7 .171-1.45

Back problem(s) 1.23 .007 3.43 .460 10 1.39-8.45 Muscular problem(s) .723 .169 2.06 .525 9 .736-5.77

Where: β = Beta score; p = significance; OR = odds ratio, SE= standard error; S = step; CI = confidence interval for full model; Added H. Insur. = added health insurance; Ann. House Income = Total annual household income; Employment Sit = current employment situation. The above statistics are for the full model, where all variables are collectively considered. Variables noted in (S) step 10 were not eliminated in the final model.

The variable with the largest p-value is eliminated at each step. Note that 9 variables that

were dropped were not significant in the full model (where all variables are included). None of

the effects of the dropped variables are significant when all 12 variables are added to the model.

Table 6.4 is the final model, which contains only three variables – two enabling and one

need characteristic. The two enabling characteristics included health and social network (p =

.001) and, total annual household income (p = .002). The need characteristic included back

problem(s) (p = .007). Individually, in relation to the outcome variable, each of these three

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variables were determined to have statistically significant (strong) correlation coefficients (at the

.01 level, 2-tailed) as depicted in figure 6.1.

Table 6.4 Step-wise Logistic Regression Summary (n=126)

Predictor Beta S.E. Wald p Odds Ratio 95% CI

Enabling Total household income Health and social network (F3) Need Back problem(s)

.379

.949

1.23

.121

.294

.460

9.83

10.40

7.16

.002

.001

.007

1.46

2.58

3.43

(1.15 – 1.85)

(1.45 – 4.59 )

( 1.39 - 8.45 )

Where CI = confidence interval, S.E. = standard error. p = significance.

The regression coefficients for all three variables are found to be positive. This means

that people with back problems, people with more extensive health and social networks in terms

of who they consult with concerning CAM, and people with higher income are more likely to be

MT users. Specifically, people with back problems are 3.4 times more likely to use MT than

people with no back problems. Also, the difference in one type of social network (friends,

family, etc.) makes people 2.6 times more likely to use MT. Lastly, those being in a higher

income category makes people 1.5 times more likely to use MT.

Now we will discuss where the variables were eliminated and data surrounding the

goodness of fit of the model.

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6.3 Model Fit and Differences Between the Full Model and Parsimonious Model

In conducting logistic regression, it is critical to examine the appropriateness of the

model in terms of its fit, or, how well the model describes the observed data (Hosmer et al.,

1991). Table 6.5 provides model summaries as it relates to changes to such measures as the -2

log likelihood and Nagelkerke R-square. Specific variables eliminated at each step are also

noted. Step 10 is the exception wherein three variables are kept in the model (namely, ‘back

problems’, ‘income’ and ‘F3-Network’).

Table 6.5 When Variables Eliminated (via Step-wise Logistic Regression)

Step -2 Log Cox and Snell Nagelkerke Likelihood R-Square R-Square Variable Eliminated

------------------------------------------------------------------------------------------------------ 1 109.365 .338 .457 Last Occupation 2 109.393 .338 .456 F2 - Health & Social Network 3 109.405 .338 .456 Subsidized Housing 4 109.449 .337 .455 Gender 5 118.466 .336 .453 Education 6 118.502 .334 .451 F1-Health & Social Network 7 118.589 .331 .447 Walk up/down Stairs 8 119.060 .321 .433 Added Health Insurance 9 121.154 .318 .430 Muscular-skeletal Problem(s) 10 121.632 .308 .416 * Back problem(s) * F3 - CAM Network * Annual household income

--------------------------------------------------------------------------------------------------------- * All variables in step 10 are kept in the final regression model.

Table 6.5 provides information similar to R2 in multiple regression. However, these

pseudo R2 coefficients cannot be interpreted as the amount of variance explained. These

coefficients can vary between 0 and 1 and the closer they are to 1.0 the better the model. As one

can see, the first Nagelkerke coefficient equalled .457 and the final model had a coefficient of

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.416. The difference between the first and the last model is only .041, which justified elimination

of most of the variables from the model.

The Nagelkerke R-square statistic is a pseudo-R square used in logistic regression to

estimate the percentage of variance in the outcome variable explained by variables in the model

(Nagelkerke, 1991). With further reference to table 6.5, the variance in MT use accounted for

was moderate, with a Nagelkerke R2 = .42 (final step). At step ten there was a -2 log likelihood

of 121.63, and a .308 Cox and Snell R2 value.

Table 6.6 provides the results of the Hosmer and Lemeshow tests on the ten regression

blocks that were run, which is another test of goodness of fit (Hosmer and Lemeshow 1989;

Lemeshow and Hosmer 1982). Non-significant values for this test tell us that that a given model

is not significantly different from the maximal model (model with all variables). From table 6.6

we can see that elimination of the variables did not result in the loss of model fit.

The proportion of correct assignments when the regression model was applied to the data

(derived from the classification table), was 77 percent. Moreover, a Hosmer-Lemeshow test at

step ten reveals a chi-square value of 9.62 (df = 8, p = .293).

Table 6.6 Hosmer and Lemeshow Test Results Step Chi-square df Sig. CT (%) -----------------------------------------------------------------------------------------

1 12.41 8 .134 73.8 2 9.51 8 .301 73.8 3 8.77 8 .362 73.8 4 5.96 8 .651 73.0 5 4.08 8 .849 74.6 6 15.72 8 .047 74.6 7 10.88 8 .208 75.4 8 10.41 8 .238 77.8 9 9.11 7 .245 77.0 10 9.62 8 .293 77.0

-------------------------------------------------------------------------------------------- Legend: df = degrees of freedom; Sig = significance; CT = Classification Table (overall percentage of number of respondents correctly classified).

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The results of the SPSS classification table (CT) for each model provides the overall

percentage of people who were correctly classified by each model if we were using it for

prediction of Users/Non-users. As we can see from table 6.6, the model at step 1 correctly

classifies 74 percent of people, while the model at step ten correctly classifies 77 percent of

people. Therefore, elimination of the variables from the model actually gradually increased the

number of observations in the sample that the model is classifying correctly (by 3.2%). A 77

percent correct classification generally indicates that the logistic regression model used in this

study works well (with a cut-off at p = .05).

The final step in the step-wise regression analysis yielded a model (and block) chi-square

of 46.41 with 3 degrees of freedom (p = .000), indicating that the set of variables reliably

distinguished between users and non-users of MT.

6.4 Regarding Eliminated Variables

Although predisposing characteristics used in this study were not found in the final

logistic regression model (using step-wise regression), such variables should not be considered

as having little to no influence on the general makeup or resulting profiles of MT users. We can

see a summary of their possible interactions with other variables using data from the correlation

matrix found in the previous chapter. We can also reflect on such interactions in this chapter

using Figure 6.1. Through such a representation of the data we can better visualize a dialectical

interplay between the predisposing, enabling and need study variables.

The variable “education,” for example (fig. 6.1), although not in the final regression

model, does have a statistically significant correlation coefficient of .328 (at the .01 level – 2-

tailed) to that of the outcome variable. Moreover, ‘education’ as a variable revealed statistically

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significant correlation coefficients to that of other variables such as the respondent’s last

occupation (.581 at the .01 level); current employment situation (.201 at the .05 level) and,

income (.478 at the .01 level).

Overall, while many other variables examined in this study were not in the final logistic

regression model, several of these nevertheless were significantly related to MT use in individual

regression, and were correlated to the variables in the final logistic model.

6.5 Summary

To briefly re-visit what has been done, we first considered each of the variables one by

one that were noted in the previous chapter as being statistically significant to the outcome. This

yielded a good sense of the odds ratios and if rather or not some variables required re-coding.

Moreover, at this stage of the analysis the variable ‘employment situation’ was removed.

Upon further analysis, a full logistic model was then used wherein all twelve remaining

statistically significant variables were run simultaneously, using step-wise regression. This led to

the best parsimonious model possible to which only three statistically significant variables

remained. Model fit diagnostics completed demonstrated a model chi-square (at 46.41) that is

statistically significant (df =3, p = .000) and a Hosmer and Lemeshow test at p = .293 (df= 8, chi-

square = 9.62).

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Figure 6.1

.328** .013 .252**

.581** .475** .237** .291** .478** .362**

.201* .208* .439** .298**

.220* .172* .134 -.046 .324** .385** .111 Where: E = Enabling; N = Need and P = Predisposing characteristics. For illustrative purposes only (not intended as a path diagram). Where (**) is significant at the .01 level (2-tailed) and (*) at the .05 level (2-tailed).

[P] Education

[E] Total Annual Household Income

Outcome: MT Use Status

[P] Last Occupation

Selected Correlation Coefficients

[E] Health and Social Network - 3

[P] Current Employment Situation

[E] Added Health Insurance

[N] Back Problem(s)

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To summarize these findings and the bivariate results further is considered in the next

chapter. Moreover, the messages this specific study brings to public health practitioners and

policy makers, the contributions to knowledge this study provides, suggestions for further

research, and limitations of the present study are also now considered in the next and final

chapter.

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Chapter 7

Discussion

7.1 Study Overview

Complementary/alternative medicine (CAM) use may provide important benefits for

people, such as increased independence and improved quality of life. Understanding of the

utilization of CAM is limited, and the general goal of this thesis was to increase knowledge of

factors that affect CAM use. The Andersen model, used as a guide for this study, has been used

extensively in North America and internationally to study health care utilization by a variety of

populations, including the aged (Ashton, 2008). The model provided this study with key

constructs, including ‘predisposing’, ‘enabling’ and ‘need’ characteristics (see Chapters 2 and 3),

which in turn, offered a conceptual framework for choosing variables associated with MT

utilization. With Andersen’s model as a guide, this study asked two research questions: 1) Does

the Andersen model provide a helpful tool for understanding factors associated with massage

therapy (MT) use? 2) Does the study reveal inequity of access to MT, among the pre-selected

predisposing, enabling and need variables? This study devotes particular attention to individual-

level determinants of MT use and aims to identify characteristics of aging chronically-ill

individuals that affect whether or not they have access to MT.

This thesis reports the results of a study of volunteer respondents, ranging from 60 to 94

years of age, designed to address these two questions. The sample included 78% (n=110) females

and 22% (n= 31) males. The majority of the sample (n=58 at 41%) were aged 75 or over. As

well, the majority indicated they were separated, widowed or divorced (57%). For purposes of

conducting regression analysis, the study grouped the non-institutionalized, community-dwelling

respondents into two categories: users or non-users of registered massage therapy. All of the

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respondents resided in a large urban city in Ontario, Canada and self-reported having one or

more chronic health care conditions that had been diagnosed by a medical doctor, lasting at least

six months. The data presented in this study come from a pre-tested mail questionnaire,

specifically developed for this thesis.

7.2 Utility of the Andersen Model in Understanding MT Utilization

Bivariate analysis found four ‘predisposing’, six ‘enabling’ and three ‘need’

characteristics to be statistically significant correlates of outcome (MT use). Table 7.1

summarizes the characteristics; a detailed version of this table is found in Chapter 5 (Table 21).

Table 7.1 Correlation Coefficients of Variables Associated with MT Use Status (Bivariate)

Construct Variable Correlation Coefficient (2-tailed)

Predisposing

Enabling

Need

Gender

Education

Last Occupation

Employment Situation

Health & Social Network (F1)

Health & Social Network (F2)

CAM Network (F3)

Subsidized Housing

Health Insurance

Annual Household Income

Muscular-skeletal conditions

Back problem(s)

Walk up/down stairs

.185*

.328**

.252**

.237**

.329*

.350**

.475**

-.207*

.298**

.362**

.235**

.291**

.176*

* - p < .05; ** - p < .01

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Table 7.1 illustrates how key constructs from the Andersen model are associated with MT

utilization, which supports the model’s utility. Andersen’s framework allows for a particularly

productive way to consider a broad array of factors related to health care use.

Many of the variables noted in Table 7.1 were eliminated during step-wise (backwards)

regression. However, many were also correlated with the variables found in the final logistic

model, and therefore may play an important role in MT utilization. Those variables found to be

significantly associated with MT use, including those retained in the final model, are reviewed

below.

7.3 Sample Predisposing Characteristics

Education

Bivariate analysis revealed that, compared to users, non-users of MT were more likely to

report less than or some high school education; furthermore, education is significantly associated

with MT use (p < .05). The literature suggests that CAM users typically have higher levels of

formal education than non-users (Egede et al., 2002; Health Canada, 2001; Shmueli and Shuval,

2006; Schofield, 2000). Of interest, Burgmann et al. (2004) note that greater awareness of CAM

practices like MT could actually indicate that a person’s formal education level attained may not

play as great a role as it once did. This may be due to the rise of informal learning practices, such

as seeking out health information on the internet.

Education correlated significantly with all of the variables noted in Table 7.1, with the

exception of back problems and ability to walk up and down stairs. Education was also found to

be closely associated with income (p < .001). This may account for why education was

eliminated during step-wise regression.

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Psychosocial Variables

Few studies have addressed the relationships between dispositional psychological factors

and the use of CAM (Honda and Jacobson, 2005). Related factors considered in this study (i.e.,

mastery, self-esteem, satisfaction and skepticism) had no statistically significant relationship

with the outcome. Some previous research suggested self-care for health problems (e.g., use of

CAM services) as an indicator of mastery (Punamaki and Aschan, 1994). However, similar to

Parslow and Jorm (2004), this study found no statistically significant differences between users

and non-users of MT in terms of such indicators as mastery.

Of interest, mastery was found to be correlated with education (p < .001), as well as the

respondent’s last occupation (p = .007). Skepticism was found to be associated with back

problems (p = .007) and self-esteem was associated with mastery (p < .001), income (p = .023),

and health and social network (F1, p = .010, F2, p = .001, and F3, p = .013).

Occupation

Forty-seven percent of the users of MT compared with 28% of the non-users and 20% of

the former users formally held professional, managerial and semi-professional occupations. An

individual’s occupation is closely linked to income and education, which may explain why

higher occupational status enhances one’s opportunities to access CAM-related health care

services.

Though considerable variation exists among CAM users in terms of occupational

background, education, age, and health status (Astin, 2000), people identified as most likely to

consult and/or use CAM practitioners are well educated individuals with a high occupational

status (Sharma, 1995; Kelner and Wellman, 1997a). It is to say that, generally, CAM is more

often used by those with high socioeconomic status. SES is most often associated with three

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related dimensions: (last) occupation, education and income (McCracken et al., 2001). Each of

these indicators in this study were correlated with MT use (p =.003, p = .001 and p < .001

respectively – Chapter 5, Table 20).

Of interest, last occupation was found to be associated with MT use status (p = .003); age

(p = .004); education (p < .001); mastery (p = .007); income (p < .001); and having supplemental

health insurance (p = .010).

7.4 Sample Enabling Characteristics

Income

Users of massage therapy more than non-users self-reported obtaining a total annual

household income of $60,000 or more. Also, more non-users than users of MT indicated

obtaining a total annual household income of less than $29,999. Overall, respondents in this

study with higher incomes were 1.5 times more likely to use MT than those with lower incomes

(odds ratio = 1.46). This is consistent with literature showing that CAM use in general rises with

income (Sibbald, 2005). Similar results are suggested in this study.

Income relates directly to being able to pay for out-of-pocket expenses, such as

rehabilitation and/or restorative health care services. This is particularly relevant to the aged as

the National Advisory Council on Aging (NACA, 2005) indicates that a substantial number of

seniors in Canada continue to live under very difficult economic conditions. Moreover, this

council indicates that older women in particular are vulnerable, as they tend to have lower

incomes largely as a result of inferior wages when employed.

The NACA further indicate that as women live longer, they are at greater risk of using up

their savings as time goes by. Further, women who are divorced or separated often have much

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lower retirement incomes than do single women and widows. This is relevant to this study in

that marital status was found to be associated with income (p = .001, with a correlation

coefficient of .295 at the .01 level, 2-tailed).

Supplemental Health Insurance

In this study, 67% of the users of MT, compared with 42% of the non-users and 24% of

the former users indicated they had supplemental health insurance. This study suggests that

having supplemental health insurance beyond OHIP (the Ontario Health Insurance Plan), may

provide a means for individuals to use MT. Here, having supplemental health insurance was

statistically associated with MT use status (p < .001, with a correlation coefficient of .298 at the

.01 level, 2-tailed). However, this variable was not included in the final step of the regression

analysis.

In this study, bivariate analysis indicates supplemental health insurance to be associated

with: education (p = .001); last occupation (p = .010); mastery (p = .021); income (p < .001); F1

(p < .001); F2 (p = .002); and the respondent’s CAM-related health and social network (F3, p <

001).

Health and Social Network

As noted earlier, F1 refers to the question: “Who can you confide in or talk to when you

have problems with your health?”; F2 – “Who can you really count on to give you information

about health in general?” and F3: “Who, if anyone, gives you information about complementary/

alternative health care therapies?” With reference to the respondent’s CAM-related health

network (F3), non-users of MT were much more inclined (41%) than users (8%) and former

users (24%) to indicate that they had no one as a CAM knowledge source. Moreover, this

variable was found to be statistically significant both in the bivarate analysis as well as the final

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step of the regression model (p < .001). In the bivariate analysis, this variable was found to be

significantly associated with: education (p < .001); last occupation. (p < .001); income (p <

.001); supplemental health insurance (p < .001); F1 (p < .001) and F2,. (p < .001).

Variables F1 and F2 (which also reflect the respondent’s health and social network) were

also found to be significantly associated with MT use (both at p < .001). These variables

reflected people that respondents could talk to about health problems (F1) and sources of

information about health in general (F2). These were not included in the final step of the

regression analysis. However, both were significantly correlated with income (p < .001 for both).

Consideration of an individual’s network is important because social relationships can serve as

an enabling resource to facilitate or impede health services’ use (Andersen, 1995).

7.5 Sample Need Characteristics

Back Problem(s)

Back problems, such as back pain, are a common condition managed in primary care and

one of the commonest causes of disability in North America (Little et al., 2008). In a review of

the literature by the Cochrane collaboration, massage was found to be of particular benefit for

those with low back pain, especially if combined with exercise and delivered by a licensed

therapist (Furlan et al., 2002).

Bivariate analysis clearly revealed back problems as being a factor associated with MT

use status (p < .001 with a correlation coefficient (cc) of .291 at the .01 level, 2-tailed). The

variable also was found to be associated with the respondent’s CAM-related health network – F3

(p < .042, cc = .172 at the .05 level, 2-tailed), and self-reported muscular-skeletal problems (p =

.050, cc = .165, 2-tailed).

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Regression analysis found back problems to be a factor strongly associated with MT use

status. Specifically, in this study respondents with back problems were found to be 3.4 times

more likely to use MT than people without back problems.

Health Status

Study groups reported few health problems and there were no statistically significant

differences in their perceived health status. This finding supports McPherson’s (1994) claim that

high positive ratings of one’s health could reflect reality or could, alternatively, be a

methodological or sampling artifact. He suggests the possibility that older adults overestimate

their reported health status to emphasize that they are capable of independent living. It could also

be the case that health expectations diminish in one’s later years, and simply surviving to an

older age is evidence of at least good, if not very good health (Shields and Shooshtari, 2001).

However, as in any cross-sectional study, there may have been contextual and other factors

affecting self-reported health over time which could not be revealed here (Wilson et al., 2007).

7.6 Overview of Regression Analysis Results

Only three of the variables from Table 7.1 appeared in the final step of the logistic

regression model, indicating strong association to the outcome. These variables included one

need characteristic (back problems) and two enabling characteristics (CAM-related health and

social network and their total annual household income). Similar to other studies (e.g., Mkanta

and Uphold, 2006), the final model contained no predisposing characteristics.

The regression coefficients of the three variables remaining in the model were found to

be positive in direction. These results indicate that individuals with back problems, those with

more extensive CAM-related health and social networks, and people with a higher income are

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more likely to be MT users. As noted previously, people with back problems are 3.4 times more

likely to use MT than people without back problems. Also, those who had someone to turn to for

advice pertaining to CAM were 2.6 times more likely to use MT. Finally, individuals in a higher

income category were 1.5 times more likely to use MT (see Chapter 6).

Final results of a step-wise regression analysis yielded a good model fit, where the model

chi-square (at 46.41) was statistically significant (p < .001). Furthermore, a Hosmer and

Lemeshow test yielded a p value of .293 (chi-square = 9.62). These findings indicate that the

Andersen model helps distinguish determinants for MT use that are statistically significant.

In summary, in response to the first research question, the results of the bivariate and

regression analysis show that the modified Andersen model used in this study does show utility

by facilitating our understanding of factors associated with MT utilization.

7.7 Inequity of Access to Massage Therapy: Relevance to Health Care Policy Development

and to Health Care Practitioners

The second research question in this study inquired if inequity of access to MT might be

reflected among the pre-selected predisposing, enabling and need variables. The short answer is

“yes”, and what follows will support this contention.

According to Andersen and his colleagues, equitable versus inequitable access to health

service depends on which categories of predictors for service utilization are dominant (Chou and

Chi, 2004). More specifically, equitable access to health care occurs when predisposing,

demographic and need variables account for most of the variance in utilization. Inequitable

access occurs when enabling factors account for the greater part of the variance (Andersen, 2008;

Fuller-Thompson and Redmond, 2008). Since this study’s results indicate that enabling resources

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such as income determine health services utilization, the results suggest that there is inequitable

access to MT. This finding has implications for policy makers, health care practitioners and for

future research.

First and foremost, this study suggests that poorer individuals in Ontario, Canada have

reduced or limited access to restorative and rehabilitation-oriented health care services (in this

case, access to MT), due to income level. The high cost associated with restorative types of

services, including physiotherapy in Ontario, are a particular burden to the poor and chronically

ill (Ruger and Kim, 2007), since individuals using alternative modalities must pay out of pocket

(Ruger and Kim, 2007). The fact that many chronically-ill elderly have the added burden of out-

of-pocket health care expenses in order to attend to their chronic condition(s) may be said to be

unfair, and therefore, a type of inequity. One’s (in)ability to pay likely makes the difference

between having or not having the chance to prevent physical dysfunction and to develop,

maintain, rehabilitate or augment one’s physical function or relieve pain (the scope of practice

for massage therapy). Factors such as an individual’s socioeconomic status, though not directly

related to health care, discourage or deny regulated CAM service use.

The equity and efficiency of health care systems remain an important policy issue (Ruger

and Kim, 2007). Canada has spent an estimated 172 billion dollars on health care in 2008

(Canada Health Council, 2009). However, the greater part of this expenditure has traditionally

gone toward acute, life saving care, while long-term care, rehabilitation care, and mental health

have been considered grossly under-funded (Breslin et al., 2005).

In order to improve and strengthen public delivery of healthcare, more effort is needed to

identify which factors are associated with better performance (Mills, 2005). An example of poor

performance is the increasing number of older individuals in Canada who have unmet health care

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needs. Though they require rehabilitation-oriented health care services, they lack the means to

afford such services. As Ontario’s population is aging and the number of individuals with

chronic health care disorders is projected to rise, the question of equitable health care service

access, particularly for the aged, is an increasingly important public health care issue.

7.8 Study Relevance to the Aged

This study suggests that due to cost, there is reduced or limited access to restorative and

rehabilitation-oriented health care services, such as MT, for the aged. The poor are not able to

access the health care system as effectively as those of higher socioeconomic status (Poland et

al., 1998). Overwhelming support exists in the literature that the rich lead longer, healthier lives

than the poor (Coburn, 2004). The impact of socioeconomic factors on the health of older

populations is well documented and reveals a consistent inverse relationship between

socioeconomic status and mortality, morbidity, and disability (Von dem et al., 2003; Liang et al.,

2000; Kabir et al., 2003). Low SES negatively impacts older individuals’ ability to effectively

engage in self-care.

CAM in general is increasingly accepted in North America both as treatment for illness

and self-care to promote health and well-being (Honda and Jacobson, 2005). As noted in Chapter

3, self-care may be broadly defined as “the range of health and illness behavior undertaken by

individuals on behalf of their own health” (Dean, 1992:34) and/or “the activities individuals,

families and communities undertake with the intention of enhancing health, preventing disease,

limiting illness and restoring health” (Health Education, 1983:181). Arguably, successful

management of chronic conditions depends on adequate self-care (Bayliss et al., 2003).

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Conventional medicine offers palliative treatments for chronic illness symptoms, but such

treatments frequently have minimal success and adverse effects (Haynes et al., 2003). In

response to the limitations of conventional/allopathic medicine, many older adults are turning to

non-conventional therapies, such as MT. To older adults, conventional medicine often lacks an

emphasis on health promotion and rehabilitation (i.e., an emphasis on maximizing health).

Anomalies inherent in a dominant biomedical approach speak of the need for change, to keep

pace with society’s changing health care needs, which is shifting from an acute care focus to a

greater chronic care focus. Although the need for change has been acknowledged for some time

(Epp, 1986; Ottawa Charter, 1986), our health care system continues to overemphasize a

biomedical science approach to care, which is often not appropriate for the care of the aged.

7.9 Relevance of Study to Public Health

This study suggests that variables such as income, education and supplemental health

insurance have varying levels of relationship to the outcome of interest. These findings support

the assertion that the most significant determinants of health are social and economic factors, not

those more linked to such factors as personal choices (Barr et al., 2003). Therefore, a

comprehensive approach to care and prevention is needed which reaches beyond individual

behavior-change interventions and tackles the social determinants of health and empowers

communities to improve their own well-being (Kreindler, 2009; Willson, 2009). Such a

challenge is inherent in the mission and overall objectives of public health.

Public health aims to inform, educate and empower people about health issues,

investigate new insights and innovative solutions to health problems, and link people to needed

health services. Public health also assures the provision of health care when otherwise not

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available, develops policies and plans that support individual and community health efforts, and

evaluates effectiveness, accessibility and quality of personal and population-based health

services (Tooker, 2004). To help meet such a broad mandate, those who work in public health

need to consider the potential contributions of regulated CAM practices such as MT, and, at the

very least, periodically review which individuals and groups have access to these practices.

Increasingly, public health is addressing issues related to complementary and alternative

health care use (Weze et al., 2005). However, links between the domains of public health and

such CAM practices as massage therapy are currently in their infancy. Unfortunately, barriers

exist in facilitating a dialogue between CAM professionals and leaders in public health. One

such hindrance lies in the misperception that public health is focused solely on infectious disease

control (Frieden, 2004). The fact that the current organization and delivery of public health

services in many countries are fragmented (Healy et al., 2002) and resources dedicated to public

health worldwide are lacking (Beaglehole, 2004) present yet more barriers. Though public health

favors innovative ideas such as enhancing chronic illness management programs and/or

strategies, such ideas can only become a reality if governments make public health a greater

priority.

In addition, more research and directed funding are required to examine the potential

synergy between such domains as primary health care, public health and complementary and

alternative medicine practices, particularly as they relate to developing more effective and novel

strategies for chronic illness management, and improving population health as a whole. One of

public health’s established priorities lies in understanding factors which improve population

health.

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“The new public health” movement emphasizes health promotion and disease prevention

(Tulchinsky and Varavikova, 2000). While public health textbooks typically only briefly touch

on the topic of CAM (e.g., Shah, 2003), scholars such as Mulkins et al. (2002) emphasize that

CAM is congruent with health promotion and disease prevention.

Further, public health practitioners often address issues related to inequity of access to

health care services. They know all too well that the poor are more likely to experience inequity.

They acknowledge that inequalities and inequities affect individuals and sectors of communities

profoundly, making some more vulnerable than others in terms of, for example, access to care.

To reduce inequalities, public health officials have recommended universal access to

comprehensive care (Tulchinsky and Varavikova, 2000).

As CAM use continues to increase among chronic care patients, the role of public health

as a guide and monitor will inevitably shift toward integrative health care that enables combined

use of CAM practices with orthodox/allopathic health care. Such a shift is crucial. Public

health’s legitimacy for this role rests in its present and future capacity to encompass a wide

variety of overlapping and interlinking initiatives, such as health protection, preventative

medicine, and health education.

According to Beaglehole (2004), public health practitioners have an important role in

helping to strengthen health systems and respond to the full range of health problems faced by

communities, including chronic disease management issues. Chronic disease surveillance,

prevention, and control ought to be a clear mandate for public health. Perhaps less obvious but

equally important is that public health could help community-based researchers and others forge

improved collaborations and community partnerships. With public health coordinating such

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community efforts, the potential would exist to reduce wasteful redundancies, create cost-saving

synergies, and target limited resources where they are most needed.

Public health needs to strengthen its mandate of safeguarding and improving population

health. In the broad field of CAM, further testing is needed to determine the efficacy of certain

modalities. Those in public health could help spearhead such testing. However, improved

funding and resources are required to accomplish such an initiative. In addition, public health

could have an enhanced monitoring function, consistent with its role as an agent for assessment,

policy development, and quality assurance.

Whether or not one agrees with the use of regulated CAM practices like MT, one cannot

ignore the fact that a growing number of people of all ages are using such practices to address

their chronic health care needs. An improved dialogue between CAM therapists and

professionals in public health has now become essential. Such a dialogue would improve

interdisciplinary collaborations to investigate ways of meeting the health care needs of such

vulnerable and growing populations as the chronically ill. This is needed to better address the

unique needs of our aging population (Moore et al., 2005).

7.10 Contributions of this Study

This study represents the first of its kind in Ontario (and possibly in Canada) that

considers diverse factors associated with MT utilization by a sample of chronically ill older

individuals, using a modified (expanded) version of the Andersen model. As such, the findings

presented, as they relate to MT use by the study population, are new. Moreover, through this

study, we now have an improved understanding of seniors’ use of massage, and also of the value

of the modified Andersen model in understanding factors that may affect use of this health care

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service. Access to MT is a complex health policy issue, which can be explored in

multidimensional terms using concepts from the Andersen model (Andersen, 1995).

This study is also useful in that it helps to conceptualize and measure access to MT. This

is done through the use of the Andersen model, which provides a framework to understand and

make health policy (Andersen et al., 2007). This is made possible by this thesis in three ways.

First, this study ascertains characteristics of MT users, thereby helping to predict use of MT.

Second, this study promotes social justice given its focus on equity of access. And third, this

study promotes the improvement and efficiency of health care delivery by calling for a more

balanced health care system that takes into greater account chronic health care needs.

This study represents a contribution in other ways as well. From a health care policy and

public health perspective it is of benefit to know who may or may not have access to MT as this

type of care could, for some, enhance an individual’s health-related quality of life, plus enhance

the opportunity to remain independent in one’s home.

Currently, there are relatively little data to date concerning people’s complementary

therapy’s information seeking behavior (Verhoef et al., 2009). This study provides a contribution

by showing the positive association one’s health and social network, and in particular, one’s

CAM-related health and social network has with MT utilization.

Moreover this study is unique in exploring equity of access to MT by using the Andersen

model. This has been scantly considered to date in the CAM literature. Information of this sort is

critical for improving equity of access and in developing and implementing comprehensive

approaches to advance health care intervention (as well as health education) for patients and/or

or clients (Shreffler-Grant et al., 2007). This thesis therefore makes a substantive contribution to

a previously neglected area of study.

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7.11 Study Limitations

This study has a number of limitations, as listed below:

[1] The sample was predominately female (78%, n = 110), which limits insights on male

utilization of MT. Women use CAM-related health care services more than men (Shmueli

and Shuval, 2006). In general, studies reveal that women may be more health-conscious

than men and choose to invest more of their time and resources on health-related

activities (Shreffler-Grant et al., 2007).

[2] Similar to Ni et al. (2002), this study is limited in its exclusion of those unable to

speak and/or understand English. Generally, CAM use may relate to one’s cultural

background and traditional beliefs (Ho et al., 2009). A large survey would be required to

determine the spectrum of utilization of CAM by our increasingly culturally diverse

population(s) (Ni et al., 2002).

[3] Similar to Chou et al (2008), this study’s sample is drawn from just one city. As a

result, the findings cannot be generalized to the rest of Ontario’s population. Participants

in this study were recruited using convenience sampling through massage therapy site

referrals and voluntary participation. Consequently, the study sample may be very

different from the general population, which further reduces its generalizability (Cohen et

al., 2002; Cherniack and Pan, 2002). While using a convenience sampling is inexpensive

and can increase accessibility (Burns et al., 1997), this technique also has potential for

selection bias, e.g. volunteer bias. For instance, individuals who choose to participate in a

given study may possess characteristics distinct from non-respondents, thereby limiting

the external validity or generalizability of the findings. However, the present study

attempted to offset this limitation by using participant inclusion and exclusion criteria.

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[4] This study is cross-sectional in design. The majority of CAM therapy studies have

relied on non-random cross-sectional sampling, which can potentially limit

generalizability of the study findings (Cohen et al., 2002; Cherniack and Pan, 2002). In

this study, it was seen that some eligible and willing clients only attend a massage

therapy treatment session once every 4, 8 or 12 weeks (or even longer). As a cross-

sectional study, it is thus possible that some clients were missed. Longitudinal studies

could have better determined the relationships between the variables, including casual

relationships, and detected changes in the patterns of service use over time (Chou and

Chi, 2004).

[5] Data gathered for this study were obtained from a mail questionnaire and relied on

self-reported answers, which are subject to recall and reporting bias (Thind and Cruz,

2003). Inaccuracies and omissions are frequently associated with this method of data

collection (Parslow and Jorm, 2004).

[6] Self-reported income is often prone to error (Ruger and Kim, 2007). Reported

incomes may, for example, be artificially inflated.

[7] Though widely used, the Andersen model has limitations (as evaluated in chapter 2),

which in turn impact this study. For instance, the Andersen model typically explains the

use of a single service. Choi et al. (2006) suggest the benefit of studying service use

patterns in order to better assess the full range and number of services used by an

individual.

[8] Lastly, since this study did not consider all the sub-components or related factors of

the original Andersen model, it cannot be considered to have included all aspects of

Andersen’s model.

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Overall, the modified model used in this study served its intended purpose well. Despite the

noted limitations, this study provides a useful contribution to the literature and can play a part in

informing health care policy development.

7.12 Study Participant Recruitment Issues

Most of the randomly selected MT sites in the study turned out not to treat the target

population. Of those that did, only 1-3 individuals per site met the study inclusion criteria. In

turn, a lower than expected number of seniors were recruited from each participating massage

therapy treatment site. As a result, I extended the data collection time period from 4 to 6 months

to recruit more eligible respondents from additional randomized MT practice sites. Part of the

difficulty in locating older users and non-users of MT may have been because a larger proportion

of users of MT are younger than the target population. Generally, it is reported that MT use is

more common among people aged 35 to 49 (Haynes et al., 2003; Millar 1997).

Furthermore, MT practitioners identified potential respondents on their own and no one

was available to ensure they followed the protocol on how to choose eligible respondents to

participate in the study. Consequently, returns from sixteen respondents were disqualified

because they did not meet the inclusion criteria.

A number of therapists expressed reservation about helping to recruit former clients,

fearing that the individuals would comment negatively on the services they received. Other MT’s

stated that they had not obtained prior permission from their client to re-contact them for such

purposes as a research project, and therefore were reluctant to do so. As a result, no former users

of MT in this study were recruited with the help of massage therapists.

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Gotay (1996) indicates that there are certain conditions that may interfere with one’s

ability to complete questionnaires, including problems with vision, literacy or language. Since

such conditions are particularly common among an aged population, this study attempted to

overcome these potential problems by using a 14 point font size and grade 8 level English in the

questionnaire.

7.13 Suggestions for Future Research

Future research could build upon the findings of this study. Specifically, the following

areas would benefit from further research:

[1] Though CAM is becoming the focus of social scientific research (Foote-Ardah, 2003),

little information exists regarding individual sub-groups of CAM users. In addition, data

concerning anticipated health services consumption habits of the upcoming cohorts of

seniors remains scarce. Further research on CAM therapies offers an opportunity to

reflect on what we believe will help a particular patient and why; such reflections should

be brought to all therapies.

[2] Future research could address the following questions. Is CAM use by older

populations evidence of a health promotion strategy? Why are people paying for CAM

out of pocket when they have free conventional health services available? What impact

does insurance coverage for CAM have on use? Do CAM modalities contribute to cost

savings by preventing and/or ameliorating illness?

[3] Incorporating qualitative data would further enhance our understanding of the

respondent’s perspective. By doing so, one method’s limitations (i.e., quantitative) could

help offset those of another method (i.e., qualitative).

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[4] Future studies intending to test components of the Andersen model for vulnerable

populations require sufficiently large sample sizes. Larger samples help ensure adequate

power.

[5] Future research could consider the burden of out-of-pocket spending for CAM among

low income and chronically ill groups in particular (Ruger and Kim, 2007).

[6] Health sociologists, researchers, public health practitioners, and policy developers

ought to consider how health is embedded in the larger social, political and economic

context and which broader forces shape access to health care, including access to CAM

(Saltus, 2007). The CAM research field requires further investigation to explore these

contextual characteristics, which could also benefit by using the Andersen model (see

Chapter 3).

[7] Whether health care availability depends on national insurance contributions, direct

fees for services or private insurance, women are often penalized more than men because

of their generally lower incomes and the interruptions they experience in work-related

health support (WHO, 2001). Consideration of such topics as gender disparity and ageism

in relation to CAM utilization would be of interest.

[8] Researchers may also wish to study service use patterns as opposed to considering use

of a single service. Choi et al. (2006) have recommended coupling the Andersen model

with the Network Episode Model (NEM) for this specific purpose. The NEM postulates

that patients / clients go through different care paths ranging from formal medical

professionals to alternative healers, non-medical professionals, and lay advisors

(Pescosolido and Boyer, 1999).

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[9] To further explain where socioeconomic differences are located, with reference to

CAM related health care utilization, future work also needs to explore socio-economic

differences in referral patterns, and the reasons for those differences. For example, it is

important to know if socioeconomic differences in referral to CAM specialists such as

massage therapists reflect a general practitioner’s decisions, or the effectiveness of a

patient’s negotiation with the general practitioner to see a CAM specialist.

[10] To date, evaluation tools to determine the effectiveness of interprofessional

education programs are limited, particularly when it comes to programs that integrate

both the social and medical sciences. Considering that the Andersen model has evolved

by drawing on a wide range of disciplines, potential exists for such a model to be adapted

for this very purpose.

To elaborate on the last point, further research may also consider the importance of integrative

health care strategies to enhance care provision to the chronically ill elderly. Berwick Stewart

has stated that: “Every system is perfectly designed to produce the results it gets” (Ockenden and

Cheema, 2004:3). Health care systems in industrialized countries remain inadequately designed

to attend to the unique health care needs of chronically ill individuals.

7.14 Conclusion

This study applied a modified version of Andersen’s original Behavioral Model

(Andersen, 1968) to aid in understanding MT use among chronically-ill aged individuals. Here,

the strongest variables statistically associated with MT utilization include: total annual household

income; the respondent’s CAM-related health and social network (enabling characteristics), and

back problem(s) (one need characteristic).

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The conceptualization of massage therapy use in terms of predisposing, enabling and

need factors adopted from the Andersen model has significant policy and program implications.

In particular, this study suggests that inequity of access to massage points to further need for

program and policy development. Attaining more equitable distribution of services requires

minimizing the influence of predisposing factors, such as education, and enabling factors, such

as income, on service use. Further, greater attention should be devoted to need factors such as

muscular-skeletal and back problems (Andersen and Newman, 1973). Thus, services would

target those most in need and alter the organizational practices that typically favor one group

(often those with acute disorders) over another group (frequently individuals suffering from non-

acute chronic conditions).

Lingering questions such as “will social inequality in Canada increase in the twenty-first

century?” (Kendall, 2004:201) require on-going reflection, research, and action. If improved

equity of access to regulated types of complementary and alternative medicine holds potential to

assist individuals to preserve and enhance health (Epp, 1986), then the onus is on health care

researchers, policy makers and others to investigate the issues raised in this thesis further.

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APPENDIX 1

15-20 Minute Health Questionnaire

Instructions: The following asks about your general health and possible use of health services (such as massage therapy). A massage treatment usually last about one hour and involves a trained therapist who presses upon soft tissues and joints as a form of treatment. Please complete this even if you have never used massage therapy. Each question is important, but remember – there are no right or wrong answers. The entire questionnaire should take you about 15-20 minutes. Your answers are strictly confidential. Please answer every question. For most, use a check-mark for your response (for example: _√_ ). Thank you for your assistance. Section A: YOUR DEMOGRAPHIC BACKGROUND I would like to start by asking you questions regarding your background:

A1 In which city do you live?

_______________________

A2

When were you born?

Day_____ Month _____ Year______

A3 Are you male or female?

Male _______ (0) Female _______ (1)

Institute for Human Development, Life Course and Ag ing

University of Toronto

CASE#____ DATED:___/___/___

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A4

What is your current marital status?

Legally married (and not separated) _____ (1) Legally married and separated…….. _____ (2) Divorced ……………….. ………… _____ (3) Widowed…………………………... _____ (4) Single (never married).. …………... _____ (5)

A5

What is your home postal code?

_______________________

A6

What is your highest level of education?

Less than or some high school ____ (1) High school graduation ____ (2) Some college or university ____ (3) College or University graduation ____ (4)

A7

What is or was your spouses (or partner’s) highest level of education? •••• ____ I do not have a spouse or partner.

Less than or some high school ____ (1) High school graduation ____ (2) Some college or university ____ (3) College or University graduation ____ (4)

Section B: USE OF REGISTERED MASSAGE THERAPY Now, I am going to ask you questions regarding your use of massage:

♦♦♦♦ If you have never used massage therapy, please go to question B11 (PG. 4) to continue.

B1

Have you used registered massage therapy in the past 4 months or less?

Yes _____ (1)

No _____ (2)

Who first referred you No One…………………………….. ____ (1)

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B2

to a registered massage therapist? * Check only ONE .

A Friend …………………………… ____ (2)

Chiropractor………………………… ____ (3)

Advertisement…………………………____ (4)

A Physical or Occupational Therapist…____(5)

Spouse/Family/Relative……………… ____(6)

Family Doctor……………..…………. ____ (7)

Other – Please indicate:______________ (0)

B3

Have you completely stopped using massage therapy?

Yes ____ - If yes, please briefly explain why:

_____________________________

No ____ (2) Unsure _____ (0)

B4

During your massage therapy treatments, were you also seeing a medical doctor?

Yes…… ____ (1)

No …… ____ (2)

B5

Does your medical doctor know that you have used massage therapy?

Yes…… ____ (1)

No……. ____ (2)

Unsure.. ____ (0)

B6

Within the past month, how many times have you used registered massage therapy?

_____ times

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B7

Please indicate each month you have used registered massage therapy. * Please check off all that apply to you.

NONE _____ (1)

December 2000 _____ (2) January 2001 _____ (3) February 2001 _____ (4) March 2001 _____ (5) April 2001 _____ (6) May 2001 ______ (7) June 2001 _____ (8)

Any other time in the year 2000?

Yes ____ (1) No _____ (2)

B8

Overall, how would you rate the benefits of registered massage therapy?

Excellent …. ____ (1)

Very Good…____ (2)

Good……… ____ (3)

Fair ……….. ____ (4)

Poor……….. ____ (5)

B9

If it was covered by OHIP, would you use registered massage therapy more?

Yes…….____ (1)

No……. ____ (2)

Unsure…____ (0)

B10 Do you feel that you have enough money to use registered massage therapy when you need to? YES ____ NO____ Unsure ____ (1) (2) (3)

B 11

Do you plan to use registered massage therapy in the future? (Check only one)

NO ……………………………. ___ (1)

Yes. Soon, in about 2 months or less ___ (2)

Yes, in more than 2 months but less than 3 months__

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(3)

Yes, but not for more than 3 months ___ (4)

Unsure……………………………………… ___ (5)

B 12

How much do you know about registered massage therapy?

I consider myself to be an expert…... ____ (1)

A lot ………………………………... ____ (2) A little ………………………………. ____ (3) Very little or nothing ………………. ____ (4)

REASONS FOR NOT HAVING MASSAGE THERAPY Please complete this section if you have stopped using or have never used massage therapy. Why do you not use massage therapy?

Strongly Agree

Agree

Neither Agree nor Disagree

Disagree

Strongly Disagree

B13. I no longer need to use Registered Massage Therapy.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

B14. I use other forms of complementary health care instead.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

B15. Massage therapy is too expensive.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

B16. Massage therapy is too painful for me to use.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

B17. I’ve never thought of using massage.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

B18. I do not like to undress for a massage.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

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B19. Massage therapy is not helpful to me.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

B20. Please indicate any other reason(s) below why you do not or no longer use registered massage therapy : __________________________________________

REASONS FOR HAVING MASSAGE THERAPY

Have never used massage therapy? Please go to question C1 (next page).

Please indicate the extent of your agreement or disagreement with each of the following statements. (Please check (√ ) one answer per item).

You have used massage therapy………….. B21. Because traditional treatment was not effective for your particular problem. ____ ____ ____ ____ Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4) B22. Because the traditional treatment you received had unpleasant side effects. ____ ____ ____ ____ Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4) B23. Because you found it difficult to talk to your doctor. ____ ____ ____ ____ Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4) B24. Because you value the emphasis on treating the whole person. ____ ____ ____ ____ Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4)

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B25. Because you believe that complementary medicine such as massage enables you to take a more active part in maintaining your health. ____ ____ ____ ____ Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4) B26. Because you believe complementary therapy will be more effective for your problem than traditional medicine. ____ ____ ____ ____ Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4) Section C: HEALTH STATUS For this section, I would like to ask you questions about your health: C1 Have you had a chronic (on-going) health problem for 6 months or more, and diagnosed by a medical doctor? Yes _______ (1) No _______ (2) C2. Compared with the overall population, would you say your health is:

Excellent ____ Very Good____ Good_____ Fair _____ Poor ______

(1) (2) (3) (4) (5)

Do you have difficulty with ………… C3. Using the phone? No Difficulty____ A Little Difficulty____ A Lot of Difficulty___ Unable___ (1) (2) (3) (4) C4. Getting out of your home as often as you would like? No Difficulty____ A Little Difficulty____ A L ot of Difficulty___ Unable___ (1) (2) (3) (4) C5. Dressing?

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No Difficulty____ A Little Difficulty____ A L ot of Difficulty___ Unable___ (1) (2) (3) (4) C6. Washing and bathing? No Difficulty____ A Little Difficulty____ A L ot of Difficulty___ Unable___ (1) (2) (3) (4) C7. Walking up and down the stairs? No Difficulty____ A Little Difficulty____ A Lot of Difficulty___ Unable___ (1) (2) (3) (4) C8. Using public transportation such as a bus? No Difficulty____ A Little Difficulty____ A L ot of Difficulty___ Unable___ (1) (2) (3) (4) C9. Managing your own money? No Difficulty____ A Little Difficulty____ A Lot of Difficulty___ Unable___ (1) (2) (3) (4) C10. Preparing meals? No Difficulty____ A Little Difficulty____ A L ot of Difficulty___ Unable___ (1) (2) (3) (4) C11. In general, compared with others your age, would you say your health is:

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Excellent ____ Very Good____ Good_____ Fair _____ Poor ______

(1) (2) (3) (4) (5) C12. How many days have you had to spend in the hospital in the last 12 months? None _____ (1) A week or less _____ (2) Less than 1 month ____ (3) One month ____ (4) 2-3 months ____ (5) 4 or more months ____ (6) C13. How many chronic (on-going health problems) would you say you now have that have lasted for 6 or more months? None ____ One ____ Two ____ Three ____ Four or more ____ Unsure ____ (a) (b) (c) (d) (e) (f) C14. Have you had any of the below conditions on an on-going basis for six or more months and diagnosed by a medical doctor? Please check off all that apply to you and/or indicate below. Arthritis or Rheumatism ____ (1) Osteoporosis ____ (2) High Blood Pressure ____ (3) Kidney Condition ____ (4) Diabetes ____ (5) Back Problems ____ (6) Headaches ____ (7) Muscular-Skeletal Pain ____ (8) Heart Condition ____ (9) Bowel and/or Digestive Condition _____ (10) Lung Condition _____ (11) Do you have any other on-going medical problem(s)? Please indicate bellow: ____________________________ ________________________________

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Section D: PERSONAL HEALTH The purpose of this section is to know a little about your thoughts and feelings about your health. There are no right or wrong answers. Thinking about your health, to what extent do you currently agree or disagree with each of the following statements? (Please check (√ ) one answer per item).

Strongly Agree

Agree

Neither Agree nor Disagree

Disagree

Strongly Disagree

D1. You have little control over the things that happen to you.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

D2. There is really no way you can solve some of the problems you have.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

D3. There is little you can do to change many of the important things in your life.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

D4. You often feel helpless in dealing with problems in life.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

D5. What happens to you in the future mostly depends on you.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

D6. Sometimes, you feel that you are being pushed around in life.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

D7. You can do just about anything you really set your mind to do.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

205

Section E: THOUGHTS ABOUT YOURSELF Now, I will ask you briefly what you think about yourself. (Please check (√√√√ ) one answer per item).

Strongly Agree

Mildly Agree

Neither Agree nor Disagree

Mildly Disagree

Strongly Disagree

E1. You feel that you have a number of good qualities.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

E2. You feel that you are a person of worth at least equal to others.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

E3. You are able to do things as well as most other people of your age.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

E4. You take a positive attitude toward yourself.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

E5. On the whole, you are satisfied with yourself.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

E6. All in all, you are inclined to feel that you are a failure.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

206

SECTION F: HEALTH NETWORK Now, a few questions about your contact with people regarding your health. (Please check (√√√√ ) all that apply to you). F1. Who among the following can you confide in or talk to when you have problems with your health? Your doctor (GP) Family and Friends Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) Hospital specialist Alternative practitioner e.g. massage therapist Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) No One Other Yes ___ (1) No ___ (2) Please specify: __________________ F2. Who among the following can you really count on to give you information about health in general? Your doctor (GP) Family and Friends Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) Hospital specialist Alternative practitioner e.g. massage therapist Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) No One Other Yes ___ (1) No ___ (2) Please specify: __________________

F3. Who, if anyone, gives you information about complementary/ alternative health care therapies? Your doctor (GP) Family and Friends Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) Hospital specialist Alternative practitioner e.g. massage therapist Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) No One Other Yes ___ (1) No ___ (2) Please specify: __________________

207

Section G: YOUR HEALTH CARE SERVICE USE This next section asks you questions about how you are currently using health care services: G1. In the past 12 months, have you talked to or visited any of the following health care professionals regarding your health?

a) Family doctor or general practitioner YES ____(1) NO ____(2)

b) Eye specialist (e.g. optometrist) YES ____(1) NO ____(2)

c) A nurse YES ____(1) NO ____(2)

d) Dentist or orthodontist YES ____(1) NO ____(2)

e) Chiropractor YES ____(1) NO ____(2)

f) Physiotherapist YES ____(1) NO ____(2)

g) Speech, hearing or occupational therapist YES ____(1) NO ____(2)

Other – please indicate: ___________ (0)

G2

Overall, how do you rate the benefits of non-traditional (alternative /complementary) medicine?

Excellent …. ____ (1)

Very Good…____ (2)

Good……… ____ (3)

Fair ……….. ____ (4)

Poor……….. ____ (5)

Unsure …… ____ (6)

208

G3

In the past 12 months, have you talked to or visited any of the following?

a) Acupuncturist YES ____ (1) NO ____ (2)

b) Homeopath YES ____ (1) NO ____ (2) c) Biofeedback Teacher YES ____ (1) NO ____ (2) d) Shiatsu Therapist YES ____ (1) NO ____ (2) e) Herbalist YES ____ (1) NO ____ (2) f) Naturopath YES ___ (1) NO ____ (2) g) Other – please indicate: __________ (0)

Section H: Thoughts About Health Care Now, in general, what are your attitudes toward health care?

Strongly Agree

Agree

Neither Agree nor Disagree

Disagree

Strongly Disagree

H1. I can overcome most illness without help from a medically trained professional.

(1)

___

(2)

___

(3)

___

(4)

___

(5)

___

H2.Home remedies are often better than drugs prescribed by a doctor.

(1)

___

(2)

___

(3)

___

(4)

___

(5)

___

H3. If I get sick, it is my own behavior that determines how soon I get well.

(1)

___

(2)

___

(3)

___

(4)

___

(5)

___

209

H4. I understand my health better than most doctors do.

(1)

___

(2)

___

(3)

___

(4)

___

(5)

___

Section I

And finally, a few more questions. Please remember that all your answers are strictly confidential. The source will not be disclosed to anyone.

I1

What is your current employment situation?

I am a home-maker ……………………… ___ (1)

I am retired and no longer in paid employment ___ (2) I am paid for 30+ hours work per week …….. ___ (3)

I am paid for less than 30 hrs work per wk… ___ (4)

I am currently unemployed/looking for work . .___ (5)

I am collecting welfare………………………...___ (6)

Other – Please indicate:

___________________ (7)

I2 Are you currently self-

employed?

Yes _____ (1)

No _____ (2)

I3

What is your spouses’ (or partner’s) present employment situation? •••• ____ I do not have a spouse or partner.

She/he is a home-maker ………………………. ___(1)

He/She is retired and not in paid employment ___(2) She/He is paid for 30+ hours work per week ___(3)

He/She is paid for less than 30 hrs work per wk ___(4)

She/He is unemployed/looking for work……… ___(5) He/She receives welfare ………………………. ___(6)

Other – Please indicate: __________________ ___(7)

I4

Is your spouse or partner now self-employed?

Yes ____ (1)

No ____ (2)

I have NO Spouse or Partner ____ (3)

210

I5

What is your current living arrangement?

I live alone ___ (1) I live with my spouse or partner ___ (2) I live with my daughter or son ___ (3) Other – Please indicate: _______________ (4)

I6

Do you live in rent subsidized or public housing?

Yes ___ (1) No ___ (2)

I 7

Do you have added health insurance (beyond OHIP)?

Yes ___ (1) No ___ (2)

I 8

I 9

What is or was your last held or current occupation? How many years were you / have you been in this occupation?

Please give full description (e.g. home maker, office clerk, factory worker, forestry technician):

____________________________

For ______________ years

I 10

What is or was your USUAL occupation most of your life?

Please give full description (e.g. home maker, office clerk, factory worker, forestry technician): ___________________

For ______________ years

I 11

I 12

What is or was your spouses last held or present occupation? How many years was/ has he or she been in this occupation?

Please give full description (e.g. home maker, office clerk, factory worker, forestry technician):

____________________________

For ______________ years

211

I 13

What is or has been your spouses USUAL occupation most of his or her life?

Please give full description (e.g. home maker, office clerk, factory worker, forestry technician): ___________________

For ______________ years

I 14

How many people live in your household?

1 or 2 ___ 3 or 4 ___ 5 or more ___

(a) (b) (c)

I 15

Does the money you have meet most of your current needs?

Yes ….. ____ (1)

No …… ____ (2)

I 16

If you use massage therapy, how do you usually pay for it?

I do not use massage therapy ………… ____ (9)

Private Insurance ……………………… ____ (1)

Workers Compensation ………………. ____ (2)

Out of Pocket (Self-pay) ……………… ____ (3)

Social Services/Welfare Assistance……. ____ (4)

Paid for by a Friend ……………………. ____ (5) Paid for by Spouse …………………… ____ (6)

Paid for by a Family Member / Relative .. ____(7)

Other - Please indicate: __________________ (0)

I 17

What are your current sources of income? * Please indicate all sources of income

Salary/wage income………………. ____ (1)

Canada Pension Plan ………………____ (2)

Work or Company Pension ……….____ (3)

Savings and/or interest …………… ____ (4)

212

applicable to you. Guaranteed Income Supplement …. ____ (5)

Old Age Security ………………… ____ (6)

Non-RRSP Investments………….. ____ (7)

Other Government Transfers ……. ____ (8)

Welfare …………………………... ____ (9)

Other – Please indicate: _______________ (0)

I 18

What is your total household annual income from all sources (before taxes)? * Check one only.

Under 10,000…….____ (1) 10,000 to 14,999…____ (2) 15,000 to 19,999…____ (3) 20,000 to 29,999…____ (4) 30,000 to 39,999…____ (5) 40,000 to 59,999…____ (6) 60,000 to 79,999…____ (7) 80,000 or more …____ (8)

THANK YOU FOR YOUR PARTICIPATION!!

* Questions? Please call Kevin at 416-586-8246

Please mail as soon as possible your completed questionnaire and signed consent form using the stamped addressed envelope provided. If the envelope is lost, please mail to the address noted on top of page one.

213

APPENDIX 2

214

215

APPENDIX 4

PARTICIPANT’S INFORMATION SHEET

Title of Study: “Factors Associated with Current, Drop-out and Non-Usage Of Massage Therapy by Non-Institutionalized Chronic Elderly in Toronto (Canada)”

Principal Investigator : Kevin Willison - (416) 586-8246

Introduction Many people sixty years of age and over are using complementary health care services such as massage therapy. This study seeks to understand who and why. The information collected in this study will help increase our understanding about the use, non-use or past use of registered massage therapy by individuals who are 60 years of age or over, who have a chronic illness and, who are living in the Toronto community. I would very much like to invite you now to participate in this study.

Your Involvement

From the materials provided to you in the study package, you are asked to complete the consent form and fill in the questionnaire as best as you can. The questionnaire addresses such key areas as your current health status and your possible use of health care services (such as registered massage therapy). Please fill these in even if you do not use massage therapy. This may take you 15 to 20 minutes in total. Please return your completed forms as soon as possible to me. I, Kevin Willison, who is the principal investigator of this study, am a student at the University of Toronto (Graduate Department of Community Health). I am conducting this research to complete my graduate degree. Your assistance is crucial and would be tremendously appreciated!

Risks and Expected Benefits

You will not directly benefit from participating in this study. The information gathered in this study would be very useful, however, towards understanding health care services use by individuals aged 60 and over. Findings of this study would also supply updated and useful information for health care decision makers and others involved in health care. It is possible that you may feel some discomfort about answering some questions. If you do not wish to answer any question on the questionnaire, you are free to do so.

216

[Appendix 4 – continued]

Confidentiality

No information that would identify you in any reports, presentations, or publications, as a result of the study, will be made known. Your name will not appear on any reports or other material. Only statistics will be used to indicate findings. At the end of the study, questionnaires will be shredded.

Feedback

Your questions or concerns about this study can be answered by calling Kevin Willison (the Principal Investigator) at (416) 586-8246. Please leave a brief message, including your phone number, and I will call you back promptly. You may also e-mail me at: willison@mshri.on.ca. Please feel free to contact me with any questions you may have. Your time is valued and greatly appreciated. A summary of the results of the study will be made available to all participants upon request. To receive a copy of these results, please contact Kevin Willison.

Thank you in advance for your time.

217

APPENDIX 5 - PARTICIPANT CONSENT FORM

Name of Study: “Factors Associated with Current, Drop-out and Non-Usage Of Massage Therapy by Non-Institutionalized Chronic Elderly in Toronto (Canada).” Principal Investigator: Kevin Willison - (416) 329-8530 or (416) 586-8246 • I am aware that during the study, all questionnaires will remain with Kevin Willison. Once the study is completed, all questionnaires will be shredded. • I have read and understand the study information sheet and requests. • Only I and Kevin Willison will know if I completed the questionnaire. The source of the information provided is confidential and my identity will not be published in any report. • My participation is completely voluntary and I may withdraw from the study at any time. I have the right to refuse to answer any question(s). • My participation or withdrawal from the study will in no way affect any future health care I may receive. • I know that Kevin Willison is a graduate student from the University of Toronto and that this study will assist towards the completion of his degree.

[Please print and sign your name below. Please also indicate the date]:

___________________________________ _____________________________

Your Name in Block Letters Your Signature

______________________________ _____________________________

Kevin Willison Signature of Principal Investigator

____________________Date

* PLEASE RETURN YOUR COMPLETED QUESTIONNIARE AND TH IS CONSENT FORM AS SOON AS POSSIBLE – THANK YOU ! -

218

Questionnaire Codebook – Appendix 6 (1) = coded 1 and so forth using SPSS version 10.1

Section A: DEMOGRAPHIC BACKGROUND Code Name A1

In which city do you live?

String Coded

a1_city SCREEN

Reject if not

Toronto

A2

When were you born?

Day_____ Month _____ Year______

Coded: dd/mm/yy

a2_dob INTERVAL

Reject if not aged

60 or over

A3

Are you male or female?

Male _______ (0) Female _____

(1)

a3_sex NOMINAL

A4

What is your current marital status?

Legally married (and not separated) _ (1) Legally married and separated…….. _ (2) Divorced ……………….. ………… _ (3) Widowed…………………………... _ (4) Single (never married).. …………... _ (5)

a4_ms NOMINAL

Collapse

1 & 2 3 & 4 5 = 5

A5

What is your home postal code?

String Coded

a5_post SCREEN

Reject if not

Toronto

A6

What is your highest level of education?

Less than or some high school ____ (1) High school graduation ____ (2) Some college or university ____ (3) College or University graduation ____ (4)

a6_educ ORDINAL

A7

What is or was your spouses (or partner’s) highest level of education?

Less than or some high school ____ (1) High school graduation ____ (2) Some college or university ____ (3) College or University graduation ____ (4)

a7_ed_sp ORDINAL

Collapse

1 & 2 3 & 4

219

•••• ____ I do not have a spouse or partner.

Code as

“77”

Section B: USE OF REGISTERED MASSAGE THERAPY In code book spreadsheet, user =(1), Non-user =(2) Former user=(3)

♦♦♦♦ Respondent requested to go to question B11 if non-user.

B1

Have you used registered massage therapy in the past 4 months or less?

Yes _____ (1)

No _____ (2)

Code Name b1 SCREEN

B2

Who first referred you to a registered massage therapist? * Check only ONE

No One………….. ____ (1)

A Friend ……… ____ (2)

Chiropractor……… ____ (3)

Advertisement………____ (4)

Physical or Occup. Therapist ____(5)

Spouse/Family/Relative … ____(6)

Family Doctor……………. ____ (7)

Other:______________ (0)

b2

NOMINAL

Collapse 3/4/5/6/0 (as “other”) 1 = 1 2 = 2 7 = 7

B3

Have you completely stopped using massage therapy?

1 = Yes

2 = No

0 = Unsure

Reason (if provided) = string coded

b3

NOMINAL

b3_reas

B4

During your massage therapy treatments, were you also seeing a medical doctor?

Yes…… ____ (1)

No …… ____ (2)

b4 NOMINAL

220

B5

Does your medical doctor know that you have used massage therapy?

Yes…… ____ (1)

No……. ____ (2)

Unsure.. ____ (0)

b5 NOMINAL

Collapse

2 & 0 (as “no”) 1 = 1

B6

Within the past month, how many times have you used registered massage therapy?

_____ times [numeric code]

b6 RATIO

B7

Please indicate each month you have used registered massage therapy. * Please check off all that apply to you.

NONE _ 1=yes / 2 = no

December 2000 __ 1=yes / 2 = no

January 2001 __ 1=yes / 2 = no

February 2001 __ 1=yes / 2 = no

March 2001 __ 1=yes / 2 = no

April 2001 __ 1=yes / 2 = no

May 2001 ___ 1=yes / 2 = no

June 2001 __ 1=yes / 2 = no

Any other time in the year 2000? Yes ____ (1) No _____ (2)

Code Name

b7_none

b7_dec b7_jan b7_feb b7_mar b7_apr b7_may b7_jun b7_2000

NOMINAL

Determine frequency

Of variables

B8

Overall, how would you rate the benefits of registered massage

Excellent …. ____ (1)

Very Good…____ (2)

Good……… ____ (3)

Fair ……….. ____ (4)

b8

ORDINAL

Collapse

1 & 2

3 = 3

221

therapy? Poor……….. ____ (5) 4 & 5

25

If it was covered by OHIP, would you use registered massage therapy more?

Yes…….____ (1)

No……. ____ (2)

Unsure…____ (0)

b9

NOMINAL

Collapse

1=1

2 & 0

B10

Do you feel that you have enough money to use registered massage therapy when you need to?

YES ___ (1) NO____ (2) Unsure ___ (3)

b10

NOMINAL

Collapse 1 = 1 2 & 3 (as “no”)

B11

Do you plan to use registered massage therapy in the future? (Check only one)

NO ……………………. ___ (1)

Yes. Soon, in about 2 months or less (2)

Yes, in more than 2 months but less than 3 months__ (3) Yes, but > 3 months __ (4) Unsure…………………… ___ (5)

b11

NOMINAL

Collapse 1 = 1 2/3/4 (as “yes”) 5 = 5

B12

How much do you know about registered massage therapy?

I consider myself to be an expert __

(1)

A lot…... ____ (2) A little ………. ____ (3) Very little or nothing ……_ (4)

Code

Name

b12

ORDINAL

Collapse

1 & 2

3 & 4

REASONS FOR NOT HAVING MASSAGE THERAPY If stopped using or have never used massage therapy. Why do you not use massage therapy?

Strongly Agree

Agree

Neither Agree nor Disagree

Disagree

Strongly Disagree

INTERVAL

B13. I no longer need to use MT.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

Add up Numbers

Lower score = ↑

agreement

222

B14. I use other forms of CAM instead.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

As above

B15. MT too expensive.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

As above

B16. MT is too painful to use.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

As above

B17. I’ve never thought of using massage.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

As above

B18. I do not like to undress for a massage.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

As above

B19. MT not helpful to me.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

As above

B20. Other reason(s) for no longer using registered massage therapy : __________________________________ STRING Code (Nominal) SATISFACTION WITH HEALTH CARE SYSTEM

• Note: Respondent requested to skip to C1 (Q. 43) if never used MT.

You have used massage therapy………….. INTERVAL

B21. Because traditional treatment was not effective for your particular problem. Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4)

Add up Numbers

Lower score = ↑

agreement

B22. Because the traditional treatment you received had unpleasant side effects. Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4)

As above

223

B23. Because you found it difficult to talk to your doctor. Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4)

As above

B24. Because you value the emphasis on treating the whole person. Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4)

As above

B25. Because you believe that complementary medicine such as massage enables you to take a more active part in maintaining your health. Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4)

As above

B26. Because you believe complementary therapy will be more effective for your problem than traditional medicine. Strongly Agree Moderately Agree Moderately Disagree Strongly Disagree (1) (2) (3) (4)

As above

Section C: SELF-REPORTED HEALTH STATUS

C1. Have you had a chronic (on-going) health problem for 6 months or more, and diagnosed by a medical doctor? NOMINAL & SCREEN Yes ___ (1) No ___ (2)

Reject

questionnaire if no

C2. Compared with the overall population, would you say your health is:

Excellent __ Very Good__ Good___ Fai r ___ Poor ____ (1) (2) (3) (4) (5)

∗∗∗∗ORDINAL

Add score ↓ score =

more positive health

assessment

ADL / IADL / Mobility = Functional Status - ∗INTERVAL

C3. IADL Using the phone No Difficulty_ A Little Difficulty___ A Lot of Difficulty___

Add up score

Higher score = lower functional

224

Unable___ (1) (2) (3) (4)

status

C4. Mobility Getting out of your home as often as you would like No Difficulty___ A Little Difficulty____ A Lo t of Difficulty__ Unable _ (1) (2) (3) (4)

As above

C5. ADL Dressing No Difficulty___ A Little Difficulty____ A Lo t of Difficulty__ Unable _ (1) (2) (3) (4)

As above

C6. ADL Washing and bathing No Difficulty___ A Little Difficulty____ A Lo t of Difficulty__ Unable _ (1) (2) (3) (4)

As above

C7. Mobility Walking up and down the stairs No Difficulty___ A Little Difficulty____ A Lo t of Difficulty__ Unable _ (1) (2) (3) (4)

As above

C8. Mobility Using public transportation such as a bus No Difficulty___ A Little Difficulty____ A Lo t of Difficulty__ Unable _ (1) (2) (3) (4)

As above

C9. 51 IADL Managing your own money No Difficulty___ A Little Difficulty____ A Lo t of Difficulty__ Unable _ (1) (2) (3) (4)

As above

C10. 52 IADL Preparing meals No Difficulty___ A Little Difficulty____ A Lo t of Difficulty__ Unable _ (1) (2) (3) (4)

As above

C11. 53 In general, compared with others your age, would you say your health is:

Excellent __ Very Good__ Good___ Fair ___ Poor ____ (1) (2) (3) (4) (5)

Add score

↓ score = more positive

health assessment

225

ORDINAL C12. 54 How many days have you had to spend in the hospital in the last 12 months? None _____ (1) A week or less _____ (2) Less than 1 month __ (3) One month __ (4) 2-3 months __ (5) 4 or more months __ (6) RATIO

Collapse 1 = 1 2/3/4/5/6 (as “1 wk. or more”)

C13. 55 How many chronic (on-going health problems) would you say you now have that have lasted for 6 or more months? None ___ One __ Two __ Three _ Four or more _ Unsure (1) (2) (3) (4) (5) (6) RATIO Collapse: 1 =1 6 = 6 2 & 3 4 & 5

Compare with C14. If C14 empty and R

indicates “none”- reject Questionnaire

C14. Have you had any of the below conditions on an on-going basis for six or more months and diagnosed by a medical doctor? Please check off all that apply to you and/or indicate below. Coded 56 Arthritis or Rheumatism ____ (1) c14_arth where 1=yes / 2 = no 57 Osteoporosis ____ (2) c14_ost where 1=yes / 2 = no 58 High Blood Pressure ____ (3) c14_hbp where 1=yes / 2 = no 59 Kidney Condition ____ (4) c14_kc where 1=yes / 2 = no 60 Diabetes ____ (5) c14_diab where 1=yes / 2 = no 61 Back Problems ____ (6) c14_back where 1=yes / 2 = no 62 Headaches ____ (7) c14_head where 1=yes / 2 = no 63 Muscular-Skeletal Pain ____ (8) c14_musc where 1=yes / 2 = no 64 Heart Condition ____ (9) c14_hrt where 1=yes / 2 = no 65 Bowel and/or Digestive Condition __ (10) c14_bow where 1=yes / 2 = no 66 Lung Condition _____ (11) c14_lung where 1=yes / 2 = no 67 Do you have any other on-going medical problem(s)? Please indicate bellow: c14_ot [String coded]

NOMINAL

Determine frequency of

“yes” and “no” variables

per category

Section D: MASTERY

Note: Higher (↑) score = greater (↑) sense of mastery.

226

(Exceptions: D5 and D7 ���� Reverse Coded). INTERVAL

Strongly Agree

Agree

Neither Agree nor Disagree

Disagree

Strongly Disagree

CODED

D1. 68 You have little control over the things that happen to you.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

ADD

SCORE

D2. 69 There is really no way you can solve some of the problems you have.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

ADD

SCORE

D3. 70 There is little you can do to change many of the important things in your life.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

ADD

SCORE

D4. 71 You often feel helpless in dealing with problems in life.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

ADD

SCORE

D5. 72 What happens to you in the future mostly depends on you.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

Reverse

Code (Add score)

D6. 73 Sometimes, you feel that you are being pushed around in life.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

ADD

SCORE

D7. 74 You can do just about anything you really set your mind to do.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

Reverse

Code (Add score)

227

Section E: SELF-ESTEEM Note: Lower (↓) score = greater (↑) self-esteem Exception: E6 ���� Reverse Coded INTERVAL

Strongly Agree

Mildly Agree

Neither Agree nor Disagree

Mildly Disagree

Strongly Disagree

CODED

E1. 75 You feel that you have a number of good qualities.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

Add Score

E2. 76 You feel that you are a person of worth at least equal to others.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

Add Score

E3. 77 You are able to do things as well as most other people of your age.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

Add Score

E4. 78 You take a positive attitude toward yourself.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

Add Score

E5. 79 On the whole, you are satisfied with yourself.

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

Add Score

E6. 80 All in all, you are inclined to feel that you

(1) ___

(2) ___

(3) ___

(4) ___

(5) ___

Add Score

Reverse Coded

228

are a failure.

SECTION F: HEALTH NETWORK Respondent asked: F1. Who among the following can you confide in or talk to when you have problems with your health?

* CODED AS INDICATED BELOW * Determine SCORE per category Confident score: Yes=1, 2=No [Added] - INTERVAL Your doctor (GP) f1_dr [code name(s)] Family and Friends f1_fam Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) [81] [84] Hospital specialist f1_spec Alternative practitioner f1_alt Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) [82] [85] No One f1_none Other Yes ___ (1) No ___ (2) Please specify: [String coded] [83] [86] f1_0th F2. Who among the following can you really count on to give you information about health in general? Your doctor (GP) f2_dr [code name(s)] Family and Friends f2_fam Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) [87] [90] Hospital specialist f2_spec Alternative practitioner f2_alt Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) [88] [91] No One f2_none Other Yes ___ (1) No ___ (2) Please specify: [String coded] [89] [92] f2_0th F3. Who, if anyone, gives you information about complementary/ alternative health care therapies? Your doctor (GP) f3_dr [code name(s)] Family and Friends f3_fam

229

Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) [93] [96] Hospital specialist f3_spec Alternative practitioner f3_alt Yes ___ (1) No ___ (2) Yes ___ (1) No ___ (2) [94] [97] No One f3_none Other Yes ___ (1) No ___ (2) Please specify: [String coded] [95] [98] f3_0th Section G: MAIN STREAM PRACTITIONER UTILIZATION Respondent asked: G1. In the past 12 months, have you talked to or visited any of the following health care professionals regarding your health?

INTERVAL

[Scores Added]

d) [99] Family doctor or general practitioner YES ____(1) NO ____(2)

e) [100] Eye specialist (e.g. optometrist) YES ____(1) NO ____(2)

f) [101] A nurse YES ____(1) NO ____(2)

d) [102] Dentist or orthodontist YES ____(1) NO ____(2)

e) [103] Chiropractor YES ____(1) NO ____(2)

h) [104] Physiotherapist YES ____(1) NO ____(2)

i) [105] Speech, hearing or occupational therapist

YES ____(1) NO ____(2)

[106] Other – please indicate: [String coded]

Code Name

g1a g1b g1c g1d g1e g1f g1g g1_oth

230

G2

[107] Overall, how do you rate the benefits of non-traditional (alternative /complementary) medicine?

Excellent …. ____ (1)

Very Good…____ (2)

Good……… ____ (3)

Fair ……….. ____ (4)

Poor……….. ____ (5)

Unsure …… ____ (6)

Collapse 1 & 2 3 = 3 4 & 5 & 6

ORDINAL

G3

INTERVAL

[Scores Added] In the past 12 months, have you talked to or visited any of the following?

g) Acupuncturist [108] YES ____ (1) NO ____ (2)

h) Homeopath [109] YES ____ (1) NO ____ (2)

i) Biofeedback Teacher [110]

YES ____ (1) NO ____ (2) j) Shiatsu Therapist [111]

YES ____ (1) NO ____ (2) k) Herbalist [112]

YES ____ (1) NO ____ (2) l) Naturopath [113]

YES ___ (1) NO ____ (2) m) Other – please indicate: [114]

[String Coded] * Add “yes” variables per category.

Code Name

g3a

g3b

g3c

g3d

g3e

g3f

g3g_oth

Section H: SKEPTICISM SCALE INTERVAL

Strongly Agree

Agree

Neither Agree nor Disagree

Disagree

Strongly Disagree

H1. [115] I can overcome most

(1)

(2)

(3)

(4)

(5)

Add score Lower

231

illness without help from a medically trained professional.

___

___

___

___

___

score =

↑ skep

H2. [116] Home remedies are often better than drugs prescribed by a doctor.

(1)

___

(2)

___

(3)

___

(4)

___

(5)

___

As above

H3. [117] If I get sick, it is my own behavior that determines how soon I get well.

(1)

___

(2)

___

(3)

___

(4)

___

(5)

___

As above

H4. [118] I understand my health better than most doctors do.

(1)

___

(2)

___

(3)

___

(4)

___

(5)

___

As above

Section I Socio-economic Status (SES)

I1

[119] What is your current employment situation?

I am a home-maker ………………… (1)

Retired and no longer in paid employment (2)

I am paid for 30+ hours work per week … (3)

I am paid for < 30 hrs work per wk… (4)

I am currently unemployed/looking for

work (5)

I am collecting welfare…………… …….. (6)

Other – Please indicate: _______________

(7)

Collapse

1 = 1 2 = 2 3/4/5/6/7 (as “other”) NOMINAL

I2 [120]

Are you

currently self-

employed?

Yes _____ (1)

No _____ (2)

NOMINAL

232

I3

[121] What is your spouses’ (or partner’s) present employment situation? •••• ____ I do not have a spouse or partner.

She/he is a home-maker ……………. ___(1)

He/She is retired and not in paid employment(2)

She/He is paid for 30+ hours work per week_(3)

He/She is paid < 30 hrs work per wk (4)

She/He is unemployed/looking for

work__(5)

He/She receives welfare ………… . ___(6)

Other – Please indicate: __________ ___(7)

Collapse

1 = 1 2 = 2 3/4/5/6/7 (as “other”) NOMINAL Code: “77”

I4

[122] Is your spouse or partner now self-employed?

Yes ____ (1)

No ____ (2)

I have NO Spouse or Partner ____ (3)

NOMINAL

I5

[123] What is your current living arrangement?

I live alone ___ (1) NOMINAL I live with my spouse or partner ___ (2) I live with my daughter or son ___ (3) Other : ___ (4)

Collapse 1 = 1 2/3/4 (code as “other”) If R indicates nursing home, reject.

I6

[124] Rent subsidized or public housing?

Yes ___ (1) No ___ (2)

NOMINAL

I 7

[125] Do you have added health insurance (beyond OHIP)?

Yes ___ (1) No ___ (2)

NOMINAL

I 8

I 9

[126] What is or was your Last held or current occupation? [127] How many years were you / have you been in this occupation?

Please give full description (e.g. home maker, office clerk, factory worker, forestry technician):

_____ [String code]

For ____ years [Numeric code]

NOMINAL

RATIO

233

Note: Re. Coding Occupation(s) Re. For questions 126 / 128 / 130 and 132 Re. Pineo-Porter-McRoberts scale. Category 1, coded [1] includes the self-employed, professionals, managers, semi-professionals and technicians. Examples: Accountant, Social Worker, Teacher, Store Owner and Executive. Category 2, coded [2] includes the supervisors, foreman/women, trades people and skilled clerical, sales and service personnel. Examples: carpenter, social service worker, medical secretary and truck driver. Category 3, coded [3] includes semi and unskilled clerical, sales and service personnel, and, manual workers. Examples: home maker, factory worker, sales clerk, laundry worker and data entry clerk. I 10

[128] What is or was your USUAL occupation most of your life? [129]

Please give full description (e.g. home maker, office clerk, factory worker, forestry technician): ________ [String code]

For _____years [Numeric code]

NOMINAL

RATIO I 11

I 12

[130] What is or was your spouses last held or present occupation? How many years was/ has he or she been in this occupation?

Please give full description (e.g. home maker, office clerk, factory worker, forestry technician):

_______ [String code] [131]

For ______________ years [Numeric code]

NOMINAL

RATIO

I 13

[132] What is or has been your spouses USUAL occupation most of his or her life?

Please give full description (e.g. home maker, office clerk, factory worker, forestry technician): _________[String code]

[133]

For ______________ years [Numeric code]

NOMINAL

RATIO

I 14

[134] How many people live in your household?

1 or 2 ___ 3 or 4 ___ 5 or more ___

(1) (2) (3)

Collapse

1 = 1 2 & 3 (as “3 or more”)

234

I 15

[135] Does the money you have meet most of your current needs?

Yes ….. ____ (1)

No …… ____ (2)

NOMINAL

I 16

[136] If you use massage therapy, how do you usually pay for it?

I do not use massage therapy ………… __ (9)

Private Insurance ……………………… __ (1)

Workers Compensation ………………. __ (2)

Out of Pocket (Self-pay) ……………… __ (3)

Social Services/Welfare Assistance……. __ (4)

Paid for by a Friend ……………………. __ (5)

Paid for by Spouse …………………… __ (6)

Paid for by a Family Member / Relative . __(7)

Other - ……………………………………. (0)

Collapse

1 = 1 3 = 3 9 = 9 2/4/5/6/7/0 (as “other”) NOMINAL

I 17

What are your current sources of income? * Please indicate all sources of income applicable to you.

Salary/wage income [137] 1 = yes / 2 = no (1) Canada Pension Plan

[138] 1 = yes / 2 = no (2)

Work or Company Pension

[139] 1 = yes / 2 = no (3) Savings and/or interest

[140] 1 = yes / 2 = no (4)

Guaranteed Income Supplement

[141] 1 = yes / 2 = no (5) Old Age Security

[142] 1 = yes / 2 = no (6)

Non-RRSP Investments

[143] 1 = yes / 2 = no (7) Other Government Transfers [144] 1 = yes / 2 = no (8) Welfare [145] 1 = yes / 2 = no (9) Other [146] [String Code] (0)

Code Name i17_sal i17_cpp i17_wcp i17_sav i17_gis i17_oas i17_nrsp i17_ogov i17_wel i17_oth

Collapse

2 = 2

3 = 3

4 = 4

6 = 6

7 = 7

1/5/8/9/0

(as “other”)

NOMINAL

235

I 18

[147] What is your total household annual income from all sources (before taxes)?

Under 10,000…….____ (1) 10,000 to 14,999…____ (2) 15,000 to 19,999…____ (3) 20,000 to 29,999…____ (4) 30,000 to 39,999…____ (5) 40,000 to 59,999…____ (6) 60,000 to 79,999…____ (7) 80,000 or more …____ (8)

ORDINAL Collapse٭

1/2/3/4 (as 0-29,999) 5/6 (as 30K-59,999) 7/8 (as 60K+”)