quality of life and perception of aging in institutionalized and non-institutionalized elderly in...

Faculty of Health, Medicine and Life Sciences (FHML)

Master’s degree programme in Global Health

05.05.2014 – 31.08.2014

T.M. Kafczyk

[email protected]

Master’s thesis:

Quality of Life and Perception of Aging in Institutionalized and

Non-Institutionalized Elderly in the South Canara Region in India

I am truly grateful and humbled by the reliable and outstanding supervision, both in a

didactic and inter-personal way, of my first supervisor, Prof. Dr. G.I.J.M. Kempen,

Maastricht University, Dept. of Health Services Research. My thanks also go to my

second supervisor, Dr. J.S.M. Krumeich, Maastricht University, Dept. of Health, Ethics

and Society, who was especially at the beginning of the thesis project of priceless help in

pulling the strings to allow me to work on this important topic in Manipal, Karnataka

state, India. Another word of thanks which I absolutely want to express to my field

supervisor in Manipal, T. Andrews J, Manipal University, Dept. of Public Health, who was

of significant help, a source of great advice and field wisdom and who had always an

open ear for my problems.

Maastricht, August 26 2014

Note: this study was conducted in cooperation with the Dept. of Public Health, Manipal

University, Manipal 576 104, Karnataka, India. The placement took place from May 5 to

June 20 2014.

II

Abstract

Introduction

India will soon have the second largest population over 60 after China. Amplified by

globalization, older people face now a decline in traditional values that is reflected in a

breakdown of traditional family structures and a rise in the number of old age homes. In

light of these changes, a better understanding of how different living arrangements affect

quality of life and the self-perception of aging (SPA) is urgently warranted. This study

investigated if the living arrangement (community versus old age home) determined

differences in quality of life and if these differences are partly explained by the SPA

among older adults in India.

Methods

Purposive sampling was applied to collect data in India in the South Canara region in

Karnataka state in non-institutionalized and institutionalized older people ≥ 55 years old.

The mean age of the final sample of 139 participants was 69.75 (SD = 8.83) years.

Quality of life was assessed with the WHOQOL-BREF instrument, SPA was assessed with

the Attitudes Toward Own Aging subscale of the Lawton Philadelphia Geriatric Centre

Moral Scale. The statistical analysis was based on multiple regression analysis.

Results

Institutionalized elderly people showed lower quality of life scores in the domains physical

health, psychological health, social relationships and environment. The SPA did not vary

between the living arrangements and did not seem to explain the relationship between

living arrangement and quality of life. Instead, SPA changed the relationship between

living arrangement and quality of life. Possible explanations and implications are

discussed.

Conclusion

The results highlight the need to improve quality of life particularly in institutionalized

older people in the South Canara region. However, definite conclusions about whether

this should be done through the improvement of SPA cannot be drawn due to limitations

of the present study. A follow-up study is warranted in order to shed more light on this

important topic.

III

Table of contents

Abstract ............................................................................................................... II

Table of contents .................................................................................................. III

List of figures ........................................................................................................ V

List of tables ........................................................................................................ VI

List of abbreviations ............................................................................................. VII

1. Introduction ...................................................................................................... 1

1.1 Aging .......................................................................................................... 1

1.1.1 Demographic shift ................................................................................... 2

1.1.2 Health status .......................................................................................... 3

1.1.3 Perception of aging.................................................................................. 4

1.2 Caring structures .......................................................................................... 6

1.2.1 Impact of globalization ............................................................................ 6

1.2.2 Old age homes ....................................................................................... 7

1.2.3 Quality of life .......................................................................................... 8

1.3 Rationale and aim of the study ....................................................................... 9

1.4 Research question and hypotheses .................................................................10

1.4.1 Research question ..................................................................................10

1.4.2 Hypotheses ...........................................................................................10

2. Methods ..........................................................................................................12

2.1 Data collection .............................................................................................12

2.1.1 Sampling ..............................................................................................12

2.1.2 Procedure .............................................................................................15

2.2 Variables and measurement instruments ........................................................16

2.2.1 Independent variable: living arrangement .................................................16

2.2.2 Dependent variable: quality of life ............................................................16

2.2.3 Mediating variable: self-perception of aging ...............................................17

2.2.4 Covariates .............................................................................................18

2.2.5 Validity and reliability .............................................................................18

2.3 Statistical analysis .......................................................................................19

2.4 Ethical considerations ...................................................................................20

3. Results ............................................................................................................21

3.1 Descriptive statistics ....................................................................................21

3.2 Hypotheses .................................................................................................22

3.2.1 Hypothesis one: living arrangement and quality of life ................................22

IV

3.2.2 Hypothesis two: living arrangement and self-perception of aging .................24

3.2.3 Hypothesis three: self-perception of aging and quality of life .......................24

3.2.4 Hypothesis four: mediating role of self-perception of aging .........................26

4. Discussion and conclusion ..................................................................................29

4.1 Discussion ...................................................................................................29

4.2 Study limitations ..........................................................................................34

4.3 Future directions ..........................................................................................36

4.3.1 Research ...............................................................................................36

4.3.2 Policy implications ..................................................................................37

4.4 Conclusion ..................................................................................................39

References ..........................................................................................................40

Appendices ..........................................................................................................45

Appendix 1 Global AgeWatch domains and indicators .............................................45

Appendix 2 Demographics in Karnataka ...............................................................46

Appendix 3 Informed consent template ................................................................47

Appendix 4 WHOQOL-BREF and domain facets ......................................................51

Appendix 5 WHOQOL-BREF user agreement ..........................................................55

Appendix 6 Self-perception of aging questionnaire .................................................58

Appendix 7 Translation of the self-perception of aging questionnaire ........................59

Appendix 8 Ethical clearance certificate ................................................................64

Appendix 9 Correlations among study variables .....................................................66

Appendix 10 Study summary: statistical diagrams .................................................67

Appendix 11 Regression with interaction term .......................................................68

V

List of figures

Figure 1: Population pyramids in India for 1950, 2000 and 2050 ................................. 3

Figure 2: Conceptual diagram of the study model .....................................................11

Figure 3: Recruitment and data collection procedure .................................................16

Figure 4: Statistical diagram of the study model with effect terms ..............................19

Figure 5: Quality of life domains as a function of self-perception of aging per living

arrangement ........................................................................................................33

VI

List of tables

Table 1: Global AgeWatch health status domain ........................................................ 4

Table 2: Characteristics of old age homes ................................................................13

Table 3: Characteristics of study areas and participants per living arrangement ...........14

Table 4: Descriptive characteristics of the study sample ............................................22

Table 5: Regression results for living arrangement on quality of life controlling for

covariates ............................................................................................................23

Table 6: Regression results for living arrangement on self-perception of aging controlling

for covariates .......................................................................................................24

Table 7: Regression results for self-perception of aging on quality of life controlling for

covariates ............................................................................................................25

Table 8: Regression results for living arrangement on quality of life controlling for self-

perception of aging and covariates .........................................................................28

VII

List of abbreviations

BCa Bias-corrected and accelerated bootstrap

CI Confidence interval

DALYs Disability Adjusted Life-Years

GDP Gross domestic product

H1-4 Hypothesis 1-4

SPA Self-perception of aging

SPSS Statistical Package for the Social Sciences

Note: elderly people living in the community are described in the present study as “non-

institutionalized” and elderly people living in old age homes are described as

“institutionalized”. Both formulations (e.g. old age home and institution) are used

interchangeable.

Maastricht University | FHML | Tom Kafczyk | Master’s thesis | Chapter: 1. Introduction

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1. Introduction

In this first chapter, the background of the study is described. First, the topic “aging” is

introduced. Here, an emphasis is put on the demographic shift and the health status and

the self-perception of aging (SPA) of older people in India. Next, caring structures in

India are described, followed by the rationale and aim of the study. Finally, the research

question and hypotheses of the present study are stated.

1.1 Aging

“Population ageing is unprecedented, without parallel in human history—and the twenty-

first century will witness even more rapid ageing than did the century just past.” (United

Nations, 2001, second paragraph).

Aging is a normal phenomenon and means the effects of older age (Devi & Roopa, 2013;

Mahapatra, 2010). It is often associated with a decline in vitality (Sinclair & Guarente,

1997). More precise, aging has three aspects: biological, psychological and social

(Mahapatra, 2010). Age-related changes include a decline in physical and cognitive

abilities such as abilities in daily living activities or learning (Lockenhoff et al., 2009).

Research is undertaken to reverse or mitigate these biological changes and to increase

longevity (e.g. Baur et al., 2006; de Grey et al., 2004). However, the causes of aging, on

a molecular level, have yet to be determined (Sinclair & Guarente, 1997). Age-related

socio-emotional aspects of aging include wisdom, knowledge, received respect, life

satisfaction and family authority (Lockenhoff et al., 2009). Especially the perceived socio-

emotional characteristics of aging vary across cultures. The proportion of older persons in

the society or cultural aspects such as status differences, were found to affect societal

views on the socio-emotional aspects of aging. Basic biological age-related changes are

perceived to be similar across cultures (Lockenhoff et al., 2009).

Aging can lead to an increased vulnerability due to, for example, financial insecurity or

neglect in the society (Devi & Roopa, 2013; Mahapatra, 2010). In India, a non-universal

social pension scheme might contribute to financial insecurity (Pension watch, 2014).

Currently, about 19% of the population over 60 are covered by the pension scheme

(Pension watch, 2014). States as well as the children have a moral and legal obligation to


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care and provide security for older persons in India while the extent of this liability

varies; for instance, Hindu, Muslim or Christian common law describes different

obligations. The Code of Criminal Procedure 1973 governs all religions and communities.

It obliges children to care for their parents. Furthermore, the Maintenance and Welfare of

Parents and Senior Citizen Act 2007 obliges the family (including relatives) and the state

to care for the needs based maintenance and the welfare of elderly (National Human

Rights Commission, 2011). The Act has to be brought to action on a state level; not all

states notified the act (National Human Rights Commission, 2011).

1.1.1 Demographic shift

Population aging has become a major global demographic trend. Underlying population

aging is a reduction in mortality followed by a reduction in fertility along with a

lengthening of life expectancy (United Nations, 2001, 2013), whereas not all extra life

years are necessarily spend free of disabilities (Robine et al., 2005). The process is called

“demographic transition”. Developed countries have gone through the demographic

transition already. Developing countries such as India are presently in the transition

(United Nations, 2001); but developing countries are ageing now at faster speed than

more developed countries did (HelpAge International, 2000; United Nations, 2001).

Soon, there will be more older people than children in the world (World Health

Organization, 2014a). The major demographic shift has economic, social and political

consequences for societies. While developed countries faced the challenges of population

ageing earlier, developing countries are only starting to tackle some of the challenges

(e.g. housing or health facilities for older people). Due to its undeniable importance, the

World Health Organization devoted the World Health Day 2012 to the topic “ageing and

health” (World Health Organization, 2014a). Moreover, the Madrid International Strategic

Plan of Action on Aging, adopted during the World Assembly on Ageing in 2002,

emphasized the well-being of older persons as a priority for action (United Nations, 2002,

2013).

Demographic shift in India

In India, declining fertility and mortality rates, accompanied by decreasing child mortality

rates and an increasing life expectancy led to an increase in the number of elderly

persons (Lena, Ashok, Padma, Kamath, & Kamath, 2009). At the present point in time,

approximately 8% of the population are over 60 years old. The population in India aged

60 and older will double in the next 40 years to over 220 million in 2050 (Chatterji et al.,


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2008; Global AgeWatch, 2013; The Lancet, 2013). India will then have the second

largest population of people over 60 after China (Global AgeWatch, 2013). The societal

aging structure will change dramatically (see Figure 1), leading to major implications for

policy makers (Chatterji et al., 2008).

Figure 1: Population pyramids in India for 1950, 2000 and 2050

Note: from United Nations (2001, p. 271)

1.1.2 Health status

The Global AgeWatch report from 2013 compared 91 countries representing about 89%

of the world’s population aged 60 and older according to their economic and social well-

being; India ranked 73rd in total and Sweden ranked 1st showing the best results (Global

AgeWatch, 2013). Four domains were assessed, namely income security, health status,

employment and education and enabling societies and environment (see “Appendix 1

Global AgeWatch domains and indicators”). Table 1 summarizes the results for the health

status domain in comparison with Sweden. It shows, for example, that only 77.70% of

people in India over 50 years of age indicate that their life has meaning compared to

95.60% in Sweden (Global AgeWatch, 2013). This is similar to what Lena et al. (2009)

reported, who found that 48.00% of people aged 60 and older in South India were not

happy in life.


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Table 1: Global AgeWatch health status domain

Domain and indicators Description indicator India Total rank: 73

Sweden Total rank: 1

Health status Rank: 85 Rank: 7

Life expectancy at age 60

Average number of years a person aged 60 can expect to live

17.00 24.00

Healthy life expectancy at age 60

The average number of years a person aged 60 can expect to live in good health

12.60 18.20

Relative psychological/mental wellbeing

% of people over 50 who feel their life has meaning compared with people aged 35-49 who feel the same

77.70 95.60

Note: data from Global AgeWatch (2013), rank number 1 is the best rank and rank number 91 is the poorest

rank

Despite advancing technologies and increasing efforts by the government and non-

governmental organizations, elderly grow unhealthier (Chatterji et al., 2008). The

perceived health of the elderly in India has declined between 1995-96 and 2004 (Husain

& Ghosh, 2010). By 2030, over 45.76% of the Indian health burden measured in

Disability Adjusted Life-Years (DALYs) is projected to be caused by adults aged 45 and

older although this age group will account for only approximately 30% of the total

population. In 2004, 25.52% of DALYs were attributable to the age group 45 and older.

There is conclusive evidence indicating that India has an “elderly (health) problem”

resulting in various challenges such as the adaptation to the needs of the elderly (Global

AgeWatch, 2013; Raju, 2011). Nevertheless, there is a lack of studies exploring the

needs such as health needs of the elderly in India making it hard to precisely define them

(Boralingaiah, Bettappa, & Kashyap, 2012; Husain & Ghosh, 2010; Raju, 2011).

Contributing to the elderly (health) problem could be the share of the gross domestic

product (GDP) devoted to health. If India wants to deliver true universal health care to

its ageing population, the share of the GDP needs to be increased (The Lancet, 2013).

India spends currently about 2% of the GDP on health (The Lancet, 2013). The World

Bank listed in 2012 for India a total health expenditure of 4.00% and a public health

expenditure of 1.30% of the GDP (The World Bank, 2014); similar numbers are reported

by Spinaci, Currat, Shetty, Crowell, and Kehler (2006).

1.1.3 Perception of aging

SPA has been defined as a lens through which age-related changes are interpreted

(Sargent-Cox, Anstey, & Luszcz, 2014; Steverink, Westerhof, Bode, & Dittmann-Kohli,

2001). It is a dynamic concept (i.e. the perception of aging can change over time)


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(Sargent-Cox et al., 2014). In the context of aging, SPA is considered an important

concept because it affects future health, health behaviours and help-seeking behaviour

(Cheng, Yip, Jim, & Hui, 2012; Kleinspehn-Ammerlahn, Kotter-Gruhn, & Smith, 2008;

Sargent-Cox et al., 2014). For example, SPA is a significant predictor of mortality (Levy,

Slade, Kunkel, & Kasl, 2002; Uotinen, Rantanen, & Suutama, 2005). It has a greater

impact on survival than gender, socioeconomic status, functional health and loneliness

(Levy, Slade, Kunkel, et al., 2002) and can alternate the cardiovascular response to

stress and a wide array of other functions such as cognitive and behavioural outcomes,

handwriting, mathematical performance, physical performance, memory or views of

other older people (Levy, 1996, 2000, 2003; Levy, Hausdorff, Hencke, & Wei, 2000; Levy

& Myers, 2004; Levy, Slade, & Kasl, 2002; Levy, Slade, Kunkel, et al., 2002; Moser,

Spagnoli, & Santos-Eggimann, 2011). Moreover, SPA contributes to the interpretation of

illness and quality of life (Low, Molzahn, & Schopflocher, 2013).

SPA seems to develop by internalization and depends to some degree on common

stereotypes (Kotter-Gruhn & Hess, 2012; Levy, Slade, Kunkel, et al., 2002). In

accordance with this point are findings after which the frequency of contacts of younger

individuals with older people diminishes stereotypes (Lockenhoff et al., 2009). One

contributing factor to the SPA was described as the “societally sanctioned denigration of

the aged” (Levy, Slade, Kunkel, et al., 2002, p. 268). Stigmatized groups share the same

stereotypes that influence their self-perception (Levy, Slade, Kunkel, et al., 2002). This

could mean, for example, that the attitude of younger people towards old people living in

old age homes affects the perception of aging of older people (Dubey, Bhasin, Gupta, &

Sharma, 2011).

The aforementioned studies on SPA barely studied the variability across different settings

such as institutions, little attention has been paid to it (Kleinspehn-Ammerlahn et al.,

2008). Particularly in India, with changing caring structures and the breakdown of strong

traditional cultural systems after which the family needs to care for the elderly (see next

section “1.2 Caring structures”), the perception of aging has not been studied yet.

We may conclude that India is in a demographic transition with a growing older

population that will soon be the second largest in the world. Elderly people are compared

to younger people facing more problems such as health problems. Furthermore, SPA is

an important variable. It has shown to be a significant predictor of mortality and

contributes to quality of life. In light of societal changes in India (that are discussed in

the next subsection), a better understanding of the concept of SPA is needed.


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1.2 Caring structures

This section is subdivided into three subsections. First, aging in the context of

globalization and consequences for caring structures is discussed. Next, the rise of old

age homes in India is described. Lastly, quality of life in older people is elaborated.

1.2.1 Impact of globalization

Traditionally, older persons played an important role in the family and the community in

India, their opinions carried weight (Mahapatra, 2010). Informal support systems (e.g.

values, kinship) provided support to the elderly. According to Dubey et al. (2011) old age

has never been a problem for India, just since the disintegration of the joint family old

people face now a problem. “The older generation is caught between the decline in

traditional values on one hand and the absence of an adequate social security system on

the other hand thus, finding it difficult to adjust in the family.” (Dubey et al., 2011, p.

98). Nowadays in India, amplified by globalization due to economic development, a

gradual vanishing of the traditional societal structures and social and economic values

takes place. This trend is exemplified in the transition from joint families to nuclear

families. Informal support systems are breaking down leading to increasing economic

insecurity, social isolation and abuse and neglect of the elderly within the society (Dubey

et al., 2011; Ingle & Nath, 2008; Lena et al., 2009; Mahapatra, 2010; Raju, 2011).

There is evidence, that the modernization of societies is associated with unfavourable

attitudes towards aging and a lower status of elderly within the society (Bengtson, Dowd,

Smith, & Inkeles, 1975; Lockenhoff et al., 2009). As well, with rising proportions of

elderly, as expected for India (Chatterji et al., 2008), the views of the society of aging

become less favourable and authority within families depends less on age (Lockenhoff et

al., 2009). At present, India with a young population and high status differences was

found to have a favourable view on socio-emotional aspects of aging (Lockenhoff et al.,

2009). Westernization might play a role as well. Generally, Eastern cultures hold more

positive views of aging than western cultures (e.g. Italy or France). One reason might be

higher status differences in Eastern cultures (Lockenhoff et al., 2009). This holds true for

India that has shown more positive views on aging (Lockenhoff et al., 2009).

Nevertheless, “westernization” is progressing in India (Stigler et al., 2010), what could

affect the societal views on aging.

The aforementioned changes contributed to a change in the care for the elderly towards

institutionalized care (see next subsection). Mahapatra (2010, p. 116) wrote in this


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context: “The rapid increase in the elderly population, the changes in the family system,

the lifestyle of the younger generation have led to changes in the living arrangements of

elderly both in developed countries and developing ones.”

1.2.2 Old age homes

“India is at a crossroads and has to decide whether to go the family care way or the

institutional/ community care way.” (Raju, 2011, p. 13).

In order to give elderly people without social security system and without someone to

care for them a place where they get attention and care, old age homes were created

(Mahapatra, 2010). Depending on the context, old age homes are defined differently. The

National Centre for Health and Statistics defined it as “[…] a residence facility with three

or more beds that provided nursing and personal care to the aged who are chronically ill

or destitute or needy persons”.” (in Mahapatra, 2010, p. 120). Devi and Roopa (2013, p.

7) add, old age homes “are needed to take care of the lonely and forsaken elderly in the

evening of their lives”.

The demand for old age homes in India is increasing. An important reason is that less

adult children are caring for their parents in India (Liebig, 2003; Mahapatra, 2010). As a

result, old age homes “have sprung up” to meet the needs of the elderly that have not

been recognized earlier; consequently the population living in old age homes is rising

(Lena et al., 2009; Singh, Kumar, & Reddy, 2012).

Major reasons to shift to an old age home in India include the maladjustment of the

elderly in the family, poverty of the elderly and the migration of children in search of

employment opportunities (Devi & Roopa, 2013). In addition, Mahapatra (2010)

mentioned the following reasons: feeling of loneliness at home (e.g. no kids, loss of

husband/wife, loss of control), having no one to care for them (e.g. family might not be

willing to care for their older family members at home), decline of physical and mental

functioning or seeking a change from the urban hype.

The societal change towards nuclear families driven by factors associated with

globalization is reflected to some degree in the rising demand of old age homes. The new

form of institutionalized care for older family members in the Indian society has been

considered by Devi and Roopa (2013) as borrowed from the “West”. Since the idea of old

age homes in India is relatively new, the adjustment and well-being of residents in old

age homes is an important field of study. However, there is a scarcity of research


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investigating the results of these changes from non-institutional to institutional care in

the Indian context. “There is much research on the problem of the institutionalized old

people abroad but in India, very little organized information is available about the

problem of the aged living the families and in old age homes.” (Devi & Roopa, 2013, p.

7).

1.2.3 Quality of life

The World Health Organization defines quality of life as “an individual’s perception of

his/her position in life in the context of the culture and value systems in which he/she

lives, and in relation to his/her goals expectations, standards and concerns. It is a broad-

ranging concept, incorporating in a comparing way the person’s physical health,

psychological state, level of independence, social relationships, and their relationship to

salient features of their environment.” (in Devi & Roopa, 2013, p. 8).1

Mathew, George, and Paniyadi (2009) reported that institutionalized older people in

Kerala, India, have more stress and report lower quality of life than their non-

institutionalized counterparts. Dongre and Deshmukh (2012) identified factors that could

explain why elderly in India in old age homes have a lower quality of life. They identified

the working status, not being neglected, involvement in social activities and the

relationship with family as factors that determine quality of life. These factors can be

expected to be lower in residents in old age homes and could therefore explain why

Mathew et al. (2009) found a lower quality of life. This is in line with Raju (2011, p. 8)

who stated that non-institutionalized elderly people are better adjusted because of the

“deep rooted” tradition in the Indian society that it is the duty of the family to “look after

the elderly”. The family is perceived to be the main provider of elderly care and the

better environment (Dongre & Deshmukh, 2012). Dubey et al. (2011) bring in another

factor that could partly explain why institutionalized elderly people demonstrate lower

quality of life. They reported that women in the state Jammu and Kashmir, India, living

with their families in contrast to institutionalized older people had a more positive

perception of aging while the attitude of younger people towards old people living in old

age homes was unsatisfactorily (see subsection “1.1.3 Perception of aging”). Antonelli,

Rubini, and Fassone (2000) reported results for elderly in Italy that are similar to what

1 Leventhal and Colman (2007, p. 756) add: “Quality may be better in one domain (e.g., social relationships) than another (e.g., ambulatory ability), but whatever and wherever it differs, the judgment of quality is a product of both the individual’s assessment of his or her personal experience within a variety of domains (i.e., data) and the integration of these observations into an overall judgment using a decision rule yet unspecified.”


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Dubey et al. (2011) found in India: institutionalized elderly people compared to their

non-institutionalized counterparts had a more negative self-concept. Contrary to what

has been mentioned above, Devi and Roopa (2013) reported lower quality of life in non-

institutionalized elderly in Karnataka in the age group 65-70 compared to elderly that are

71-76 years old. However, Devi and Roopa (2013) did not offer an explanation.

Ultimately, there is a lack of studies in quality of life research in this respect, making it

hard define the needs of the elderly and consequently to enable the conditions or

circumstances in which successive elderly cohorts grow older with more quality in their

life.

To summarize what has been mentioned so far, India’s population is growing and aging.

Due to processes associated with globalization, older people face now a decline in

traditional values that is leading to a breakdown of family structures and a rise in the

number of old age homes. Not the family but institutions look now more and more after

the elderly. Non-institutionalized older people living among their family might be better

adjusted and hence show a higher quality of life. The perception of aging could be one

factor that explains this relationship. In light of the societal changes in India, a better

understanding of different living arrangements and hence caring structures and their

impact on quality of life could be beneficial. Interesting is furthermore, if or how the SPA

is involved in this relationship.

1.3 Rationale and aim of the study

The present study assumes that processes associated with globalization such as

modernization changed traditional family dynamics. With fewer children caring for their

parents and a breakdown in traditional norms, more and more elderly have to move to

an old age home. Accordingly, old age homes reflect changing caring-structures in India

towards institutionalization. India will soon have the second largest population of older

people in the world and yet, the impact of this change from traditional caring structures

within the family to institutions is not well understood. This holds particularly true for the

impact on quality of life. Spending the last years in an old age home and not as

traditionally dominant among the family in the community may negatively affect quality

of life (Mathew et al., 2009). Moreover, the SPA could mediate this relationship as the

experience associated with moving to an old age home could affect the SPA (Dubey et

al., 2011). The SPA can explain why the external event of living in an old age home leads


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to differences in quality of life. In light of the ever growing population in India over 60

(Global AgeWatch, 2013), factors affecting quality of life is an urgent issue (Low et al.,

2013) and should have priority in research.

The aim of the present study is to shed light on potential differences in quality of life of

elderly people in India living in the community versus living in old age homes; and to

shed light on the SPA of elderly people as a possible concept that partly explains the

difference. This understanding could help policy-makers to design better strategies to

enhance the quality of life of older persons in late life.

1.4 Research question and hypotheses

In this section, the research question and stipulated hypotheses are introduced followed

by a conceptual diagram of the study model.

1.4.1 Research question

The research question is: Does living arrangement (community versus old age home)

determines differences in quality of life and is this difference partly explained by the

perception of aging among older adults over 55? As sex, age and health may influence

living arrangement, the perception of aging and quality of life, the influence of these

variables will be taken into account.

1.4.2 Hypotheses

Hypothesis 1 (H1): Older people in old age homes have a more negative quality of life

compared to older people living in the community.

Hypothesis 2 (H2): Older people in old age homes have a more negative SPA compared

to older people living in the community.

Hypothesis 3 (H3): Older people with a more negative SPA report a more negative

quality of life compared to older people with a more positive SPA.

From these three hypotheses, a final fourth hypothesis can be formulated:

Hypothesis 4 (H4): The association between living arrangement and quality of life is

partly explained by SPA.


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A summary of the proposed model is depicted in Figure 2 below.

Figure 2: Conceptual diagram of the study model

H= Hypothesis

Maastricht University | FHML | Tom Kafczyk | Master’s thesis | Chapter: 2. Methods

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2. Methods

In this second chapter the proposed methods of the present study will be described.

First, the data collection is elaborated. Next, the variables that are used are introduced.

Finally, the statistical analysis of the data is described followed by ethical considerations.

2.1 Data collection

In this section, first, the sampling is described with details about the inclusion- and

exclusion criteria, the recruitment procedure, the sampling area and the sample size.

Second, the data collection procedure in the field is outlined.

The data collection took place from May 24 to June 10 2014.

2.1.1 Sampling

Inclusion criteria

Three inclusion criteria for the present study were defined: (1) participants were ≥ 55

years old, (2) participants gave an informed consent and (3) the participants lived either

in the community or in an old age home at the time of data collection.

Worldwide, there is no standard numerical criterion to define an older person (World

Health Organization, 2014b). Often the pension age of ≥ 60 is used (e.g. Mathew et al.,

2009; World Health Organization, 2014b); in other contexts, for example Africa, the age

of ≥ 50 is considered as old (World Health Organization, 2014b). The present study has

adopted the age of ≥ 55 to define an older person for three reasons. First, to account for

a lower life expectancy in India; life expectancy at age 60 is 17-18 years in India (Global

AgeWatch, 2013; Jeyalakshmi, Chakrabarti, & Gupta, 2011) compared to approximately

23 in more developed regions such as Europe and as high as 26 in Japan (Global

AgeWatch, 2013; United Nations, 2013). Second, most Indians seem to consider

themselves as old before the age of 60 (Dubey et al., 2011). And lastly, in view of

practical issues such as resource constraints in the present study, the age of ≥ 55

enabled to collect more data in an easy way. Indirectly through more data more

statistical power was achieved.


13

Exclusion criteria

Two exclusion criteria were defined: (1) the participant was unable to communicate

intended answers (e.g. participant is unable to speak or give answers otherwise) and (2)

the participant did not understand instructions (written and verbally) (e.g. due to severe

dementia, visual and hearing impairment). Eventually, the exclusion of participants was

subject to the researchers’ interpretation in a case to case manner in consultation with

the translator (see below) and employees (e.g. manager) within the old age homes or

relatives in the community.

Two different sampling methods were employed for the different living arrangements and

are described in the following.

Recruitment: old age home

There is no record of old age homes in Karnataka state hence, a convenient sample had

to be deployed to recruit participants from institutions (T. Andrews, personal

communication, March 12, 2014). Participants were recruited from six old age homes

(see Table 2 for a description of the old age homes). Table 3 lists the number of

participants that were sampled from each old age home.

Table 2: Characteristics of old age homes

OAH Religious affiliation

Residents in total (Female/male)

Payment (Free vs. for-pay home)

Bedrooms (Single vs. shared bedroom)

OAH1 Hindu 7 (5/2) For-pay home (approx. 7000Rps/mo)

Shared bedrooms (≤ 5 people)

OAH2 Christian 34 (25/9) For-pay home (approx. 2000Rps/mo)

Single bedrooms and shared bedrooms (≤ 5 people)

OAH3 Hindu 35 (23/12) Free-home or for-pay homea

Shared bedrooms (≤ 4 people)

OAH4 Hindu 10 (6/4) Free-home Shared bedrooms (≤ 3 people)

OAH5 Hindu 12 (12/0) Free-home Single shared bedroom (12 people)

OAH6 Christian 180 (138/42) Free-homeb Shared bedrooms (≤ 25 people)

Note: information was obtained from old age home (OAH) managers, Rps= Indian Rupees (1000 Rupees are

approximately 12.50 Euro), adepending on the economic status residents pay approximately 6000Rps/mo, bsome residents do pay a little bit if they economically can

Recruitment: community

A purposive sampling procedure was applied to recruit elderly from the community.

Community participants were recruited (with a door-to-door survey) within the same

area (i.e. the same town) of the old age home. This had two reasons. First, to sample


14

participants from the same area reduces extraneous variables such as access to

transport or noise pollution and in this way the influence of other (not controlled)

environmental variables on the study outcome was kept as minimal as possible; and

second, to collect data in the same town was practically more feasible with regards to the

time- and resource constraints of the present study work.

Sampling area

Data was collected in the South Canara region in Karnataka state, India, in the Dakshina

Kannada and Udupi district; both districts bound to the west with the Arabian Sea. From

1.2 billion people in India, 61.1 million lives in the state of Karnataka. Within Karnataka,

about 2.1 million lives in Dakshina Kannada district and about 1.2 million lives in Udupi

district (see “Appendix 2 Demographics in Karnataka”). Kannada is the official language

and most widely spoken in Karnataka. The vast majority is Hindu, with fewer Muslims

and Christians (Ministry of Home Affairs, 2014a). The percentage of urban population in

Karnataka has increased from 34.00% in 2001 to 38.67% in 2011. In Dakshina Kannada

district 47.67% lived in urban areas in 2011 and in Udupi 28.37% (Indian Census, 2011).

Urbanization in Karnataka and South Canara is rapidly increasing.

In Dakshina Kannada district, data was collected in the city Mangalore. In Udupi district,

data was collected in the village Thekatte, the city Udupi and the towns Brahmavar,

Kundapura, Santhekatte and Manipal. Table 3 shows how many participants were

sampled from each settlement area per living arrangement.

Table 3: Characteristics of study areas and participants per living arrangement

Living arrangement

Area Non-Institutionalized

Institutionalized

Settlementc Urban vs. rural

Income Participants (Female/male)

OAH Participants (Female/male)

Total

Manipal and Udupia

Urban Middle to lower-

income

15 (10/5) OAH1 6 (4/2)

21

Santhekattea Rural Middle-income

12 (7/5) OAH2 12 (8/4)

24

Kundapuraa, + Urban Middle-income

7 (5/2) OAH3 10 (6/4)

17

Thekattea Rural Lower-income

10 (5/5) OAH4 7 (4/3)

17

Brahmavara Rural Middle-income

9 (5/4) OAH5 12 (12/0)

21

Mangaloreb Urban Middle-income

24 (16/8) OAH6 25 (18/7)

49

Total 77 (48/29) 72 (52/20) 149 Note: information about areas was obtained from community residents, OAH= old age home, aUdupi district,

bDakshina Kannada district, cSetttlement refers to either a city, town or village


15

Target sample size

The general rule of thumb was applied, that at least 10 participants per variable are

needed in order to obtain adequate statistical results. The target sample size was set at a

minimum of approximately 120 participants, i.e. six (variables) multiplied with 10

(participants) multiplied by two (living arrangements).

2.1.2 Procedure

Each participant was invited to take part in the study individually. The study details were

explained and the possibility to ask questions was given. A subject information sheet was

handed over to the participant along with contact addresses in case of any further

questions, doubts or requests. If the participant agreed to participate, an informed

consent had to be signed stating for instance that the participation is voluntary and

confidential. If the participant was not able to sign, an oral consent was obtained and

confirmed by the signature of a witness (see “Appendix 3 Informed consent template”).

If the participant had no further questions, the questionnaires were filled in. Because

some elderly were not able to do the paper and pencil task or did not want to self-

administer the questionnaires, assistance in filling in the questionnaires was provided.

Reasons for assistance included illiteracy2, visual impairments or writing limitations. Each

participant was asked if she or he could or wants to fill in the questionnaire by her- or

himself. Two modes of questionnaire administration were hence used: (1) interview-style

(interviewer reads the questions and writes down the answers) and (2) questionnaire-

form (self-administered). English and Kannada version questionnaires were employed. If

the participant was bilingual in both languages, the participant was asked which language

she or he preferred. The procedure is summarized in Figure 3 (along with the frequency

of the language and interview-form).

Translator

Because the principal investigator was not fluent in Kannada, a translator was employed

for this study. The translator was a Master of Science student at Manipal University,

fluent in Kannada (native) and English.

2 In 2011, Dakshina Kannada district had a literacy rate of 88.57%, Udupi district of 86.24% (Indian Census, 2011).


16

Figure 3: Recruitment and data collection procedure

anumber in total, bnumber non-institutionalized, cnumber institutionalized

2.2 Variables and measurement instruments

In the following subsections, the variables used in this study are introduced. Hereafter,

the validity and reliability of the methods is elaborated.

2.2.1 Independent variable: living arrangement

Living arrangement is the independent variable. It is a dichotomous variable (1=

community, 2= old age home).

2.2.2 Dependent variable: quality of life

Quality of life is the dependent variable. The WHOQOL-BREF was used to collect data

(WHOQOL Group, 1998). It consists of 26 items and measures the domains physical

health (7 items), psychological health (6 items), social relationships (3 items) and

environment (8 items). For each domain, up to 20% of missing items were tolerated.

Missing items were substituted with the mean scores of the other items in the domain of


17

the respective participant. Two general items measure health satisfaction and overall

quality of life. Answers were given on a 5-point Likert scale in relation to the last two

weeks (see “Appendix 4 WHOQOL-BREF and domain facets”). The domain scores ranged

on a scale from 0 to 100, higher scores indicate a “better” quality of life.3 Some items

had to be recoded. A translated version in Kannada was available from the World Health

Organization (Chandra, Deepthivarma, Jairam, & Thomas, 2003). Skevington, Lotfy, and

O'Connell (2004) found a Cronbach’s alpha in a field trial in India (Delhi) of 0.76 for the

physical domain, 0.80 for the psychological domain, 0.63 for the social domain and 0.84

for the environmental domain. Hwang, Liang, Chiu, and Lin (2003) confirmed these

results for older people but found a higher Cronbach’s alpha for the social domain with

0.73. In the present study, the Cronbach’s alpha for the physical domain was 0.80, for

the psychological domain 0.62, for the social domain 0.75 and for the environmental

domain 0.76. Permission to use the English and Kannada version of the WHOQOL-BREF

for the purpose of this study was obtained prior the study start (see “Appendix 5

WHOQOL-BREF user agreement”).

2.2.3 Mediating variable: self-perception of aging

Self-perception of aging (SPA) is considered the mediating variable. SPA was measured

with the Attitudes Toward Own Aging subscale from the Lawton Philadelphia Geriatric

Centre Morale Scale (Lawton, 1975). The scale has been used in different studies (e.g.

Jang, Poon, Kim, & Shin, 2004; Levy, Slade, & Kasl, 2002; Sargent-Cox et al., 2014) and

consists of five items. Respondents answered in a yes/no or better/worse format for each

item (see “Appendix 6 Self-perception of aging questionnaire”). Two items had to be re-

coded. The score in sum ranges theoretically from 0 to 5. For each high morale response

a “1” was given, each low morale response received a “0”. For example, if “Do things

keep getting worse as you get older?” was answered with a “yes” then a “0” was given.

Higher scores indicate a more positive SPA. A translated version into Kannada language

was not found in the literature. The English version was hence translated in Kannada

following the validated two-phase translation procedure from Sperber (2004). The reader

is referred to “Appendix 7 Translation of the self-perception of aging questionnaire” for a

detailed description of the procedure. Jang, Poon, Kim, and Shin (2004) established a of

Cronbach’s alpha of 0.71. In the present study, a Cronbach’s alpha of 0.70 was found.

Permission to use the scale is granted (Lawton, 2003).

3 At first, a sum score for each of the domains was calculated. The scores range theoretically from 7 to 35 for the physical domain, 6 to 30 for the psychological domain, from 3 to 15 for the social relationships domain and from 8 to 40 for the environmental domain. These raw scores were then converted to a 0-100 scale.


18

2.2.4 Covariates

Covariates were obtained to statistically control for variables that could confound the

outcome. For practical reasons and reasons of feasibility it has been decided to control

for three variables. These are sex (0= female, 1= male), age (numerical in years) and

health (1= very dissatisfied, 2= dissatisfied, 3= neither satisfied nor dissatisfied, 4=

satisfied, 5= very dissatisfied). For the latter, the question “How satisfied are you with

your health?” was asked, one general question from the WHOQOL-BREF questionnaire

(WHOQOL Group, 1998). Age and health have been shown to influence quality of life

(Dongre & Deshmukh, 2012; Kumar, Majumdar, & G, 2014). A less consistent finding in

the literature is that the sex of elderly people influences quality of life (Barua, Mangesh,

Kumar, & Saajan, 2005; Devi & Roopa, 2013). As well, age and health have been shown

to affect the perception of aging (Jang et al., 2004; Kleinspehn-Ammerlahn et al., 2008).

2.2.5 Validity and reliability

Validity and reliability has been ensured by using already existing and validated

measurement instruments that are frequently used in the literature. The internal

consistency of the instruments (in English) was found to be acceptable to good in

previous studies what has been confirmed by the internal consistency measures obtained

in this study. The translated versions of the instruments (in Kannada language) were

either validated by the World Health Organization (WHOQOL-BREF) or were translated in

the present study with a strict and validated translation procedure (SPA scale, see

“Appendix 7 Translation of the self-perception of aging questionnaire”). Furthermore, to

reduce the influence of extraneous variables on the study outcome, a purposive sampling

was applied to sample elderly from both the community and institutions from the same

area. The principal investigator was moreover aware of potential biases due to his own

role in the study and tried to minimize these biases (e.g. interviewer bias4) as much as

possible.

4 The interviewer bias means that the interviewer influences the respondents’ answer; the interviewer is not

completely neutral (Bowling, 2005).


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2.3 Statistical analysis

The Statistical Package for the Social Sciences (SPSS, v. 20) was used to analyze the

data. In order to avoid data entry errors to SPSS, a double entry verification method was

used using the update syntax of SPSS to identify mismatches.

The model, terms and relation to hypotheses

Before the analytical strategy is introduced a few general terms and abbreviations are

described that will be used in this study. Figure 4 shows the paths (a, b, c, c’) and effects

that are tested here. The paths are equivalent to the tested hypotheses. “X” refers to the

predictor variable, “Y” to the outcome variable and “M” to the proposed intermediate

variable. The total effect (X on Y) is equivalent to H1. The total effect can be portioned in

a direct and indirect effect. The direct effect is the effect of X on Y when M is in the

model. The indirect effect is the amount of mediation or path a plus b (X M Y). The

indirect effect is equivalent to H4. Path a and b are equivalent to H2 and H3.

Figure 4: Statistical diagram of the study model with effect terms

e=error term, SPA= self-perception of aging, a, b, c, c’= paths

Analytical strategy

At first, descriptive statistics are reported accompanied by bivariate statistics to test for

differences between the living arrangements. Hereafter, each stipulated hypothesis is

tested with a regression-based approach, controlling for the covariates (see Figure 4).

Covariates were entered to partial out their association with the main variables of

interest (Hayes, 2013). The statistical analysis follows in general the four steps (i.e. the


20

four hypotheses) of the mediation analysis described by Baron and Kenny (1986).

However, the procedure from Baron and Kenny (1986) seems to be in some aspects

outdated and restrictive (e.g. Hayes, 2009, 2013; Rucker, Preacher, Tormala, & Petty,

2011; Shrout & Bolger, 2002). For example, the procedure by Baron and Kenny (1986)

was shown to have less power in detecting mediation effects than newer methods (e.g.

Hayes, 2009; Shrout & Bolger, 2002). In addition, the four step approach requires that

each path in the model is significant. Although one path is not significant, the indirect

effect should always be tested (Hayes, 2013). To test hypothesis four, consequently, a

bootstrapping procedure was performed that is the recommended method to test the

indirect effects (Hayes, 2009, 2013; Preacher & Hayes, 2004; Shrout & Bolger, 2002).5

Supplementary, a Sobel test, i.e. a normal theory test for the indirect effect, was

performed. Assumptions to run the statistical tests were tested.6 There were no extreme

violations. Outliers of greater than three standard deviations of the residuals from the

mean were removed if their influence on the test outcome was of serious concern.

Statistical significance was set at an alpha level of 0.05. In addition, to account for

multiple comparisons, a Bonferroni correction was applied (e.g. Zhang, Quan, Ng, &

Stepanavage, 1997). The alpha of 0.05 was divided by the number of comparisons (i.e.

four WHOQOL-BREF domains). Hence, an alpha of 0.0125 was considered as significant

each time quality of life was the outcome variable (in H1, H3 and H4). To take into

account multiple comparison for the bootstrapping procedure in H4, a 99% confidence

interval (CI) was used to infer significance. The 95% CI is reported nevertheless, for

reasons of familiarity, completeness and to increase replicability.7

2.4 Ethical considerations

This study was reviewed by the Institutional Ethics Committee, Kasturba Hospital,

Manipal, India. The study protocol received approval May 13 2014 (no. IEC 300/2014)

(see “Appendix 8 Ethical clearance certificate”).

5 Bootstrapping estimates the indirect effect by resampling the original sample with replacement (here 10000 bootstrap samples were used). It generates a representation of the sampling distribution of the indirect effect to compute a confidence interval (CI). If the CI for the indirect effect does not include zero, it suggests a significance of the indirect effect (i.e. mediation) (Hayes, 2013). 6 For bivariate statistics, the assumptions normality and homogeneity of variance were tested. For multiple regression, the assumptions independence of residuals, linear relationship, homoscedasticity, multicolinearity and normal distribution of residuals were tested. 7 In the following text, two asterisks highlight a Bonferonni corrected significance (**p < 0.0124), one asterisk highlights a non-corrected significance (*p < 0.05).

Maastricht University | FHML | Tom Kafczyk | Master’s thesis | Chapter: 3. Results

21

3. Results

In this third chapter, first descriptive statistics are reported. Secondly, results are

presented to test each stipulated hypothesis. Additionally, from “Appendix 9 Correlations

among study variables” correlations between the study variables can be obtained.

From 149 initially conducted interviews, 10 were excluded from the data analysis to not

affect the trustworthiness of the data. During the data collection, while the interviews

were conducted, it became clear that three participants from the community and four

from old age homes did not understand the instructions. As well, during two interviews in

the community relatives influenced or answered in the name of the participants. The

participants answered therefore not entirely independent. One participant’s age in an old

age home turned out to be under 55 years of age. These participants were excluded from

the analysis. The analysis is therefore based on a sample of 139 participants.

3.1 Descriptive statistics

From the final sample of 139 participants, 72 were from the community and 67 from old

age homes. The majority (67%) of the sample was female and there were more females

(73%) in institutions compared to the community (61%). However, the difference was

not significant. Participants in institutions were with a mean age of 71.64 (SD = 9.40)

significantly older than participants in the community with a mean age of 68.04 (SD =

8.00). The self-perception of aging (SPA) did not differ significantly between participants

in the community (M = 3.24, SD = 1.60) and institutions (M = 2.88, SD = 1.65).

Significant differences in quality of life between elderly people in the community and old

age homes were found. Elderly people in old age homes reported significantly lower

scores in all quality of life domains compared to elderly people in the community (see

Table 4).


22

Table 4: Descriptive characteristics of the study sample

Living arrangement

Characteristic Non-institutionalized (N= 72)

Institutionalized (N= 67)

Total (N= 139)

Statistical comparison

Sex Female (N (%)) Male (N (%))

44 (61.11%) 28 (38.89%)

49 (73.13%) 18 (26.87%)

93 (66.91%) 46 (33.09%)

X2 (1, N= 139)= 2.27, p= 0.152

Age (Mean ± SD) 68.04 ± 8.00 71.64 ± 9.40 69.65 ± 8.83 t(137) = -2.26, p = 0.025*

Health (Mean ± SD) 3.26 ± 1.05 3.34 ± 0.96 3.30 ± 1.00 t(137) = -0.46, p = 0.643

SPA (Mean ± SD) 3.24 ± 1.60 2.88 ± 1.65 3.06 ± 1.63 t(137) = 1.29, p = 0.199

Domains of QOL (Mean ± SD)

Physical 61.86 ± 18.61 51.60 ± 16.78 56.88 ± 18.42 t(136) = 3.40, p = 0.001** Psychological 61.20 ± 14.78 54.49 ± 14.36 57.97 ± 14.91 t(135) = 2.69, p = 0.008** Social relations 67.38 ± 20.30 51.77 ± 22.00 59.80 ± 22.47 t(134) = 4.30, p < 0.001** Environment 60.13 ± 15.83 50.12 ± 13.78 55.31 ± 15.65 t(137) = 3.96, p < 0.001** *p < 0.05, **p < 0.0125, X2 = Chi-Square test, t = Student’s t-test, SD= standard deviation, SPA= self-

perception of aging, QOL= quality of life

3.2 Hypotheses

Below are the outcomes of the regression analysis to test the stipulated hypotheses as

described in “1.4.2 Hypotheses”. Additionally, from “Appendix 10 Study summary:

statistical diagrams” a graphical summary of the findings can be obtained.

3.2.1 Hypothesis one: living arrangement and quality of life

Multiple regression analysis was used to test H1 that older people in old age homes have

a lower quality of life compared to older people living in the community controlling for

sex, age and health. Living arrangement was the predictor. Each quality of life domain

was tested separately. The results are summarized in Table 5.

Living arrangement significantly predicted physical health, psychological health, social

relationships and the environment domain, independent of the covariates sex, age and

health. Living in an old age home was associated with a decrease on average in physical

health of 10.07 points, in psychological health of 7.19 points, in social relationships of

16.02 and in the environment domain score of 10.05. The model explained a significant

proportion of variance of 39.62% in physical health, 25.91% in psychological health,

17.95% in social relationships and 20.06% in the environment domain score.


23

Based on the regression results and t-test mentioned in Table 4 above, H1 for the quality

of life domains physical health, psychological health, social relationships and environment

was accepted.

Table 5: Regression results for living arrangement on quality of life controlling for

covariates

Unstandardized

coefficients

Predictor β SE t p Model summary

Dependent variable: quality of life physical healtha

Constant 58.82 11.65 5.05 < 0.001**

R2 = 0.396 F(4, 133) = 21.82, p < 0.001**

LA -10.07 2.55 -3.96 < 0.001**

Sex 2.99 2.68 1.11 0.267

Age -0.20 0.15 -1.40 0.163

Health 9.78 1.24 7.86 < 0.001**

Dependent variable: quality of life psychological healtha

Constant 49.65 10.41 4.77 < 0.001**

R2 = 0.259 F(4, 132) = 11.54, p < 0.001**

LA -7.19 2.29 -3.14 0.002**

Sex -4.37 2.41 -1.81 0.072

Age -0.14 0.13 -1.09 0.279

Health 6.50 1.11 5.83 < 0.001**

Dependent variable: quality of life social relationshipsa

Constant 76.63 16.75 4.57 < 0.001**

R2 = 0.179

F(4, 131) = 7.17, p < 0.001**

LA -16.02 3.66 -4.38 < 0.001**

Sex -6.85 3.84 -1.78 0.077

Age -0.26 0.21 -1.25 0.213

Health 4.14 1.80 2.30 0.023

Dependent variable: quality of life environment domaina

Constant 64.39 11.34 5.68 < 0.001**

R2 = 0.201 F(4, 134) = 8.41, p < 0.001**

LA -10.05 2.48 -4.06 < 0.001**

Sex -2.82 2.60 -1.08 0.282

Age -0.20 0.14 -1.39 0.165

Health 4.46 1.21 3.67 < 0.001**

**p < 0.0125, a= higher values indicate higher quality of life domain scores, SE= standard error, t = Student’s

t-test, F= F-test, OAH= old age home, LA= living arrangement [1= community, 2= OAH], sex [0= female, 1=

male]


24

3.2.2 Hypothesis two: living arrangement and self-perception of aging

Multiple regression analysis was used to test H2 that older people in old age homes have

a lower SPA compared to older people living in the community adjusting for sex, age and

health. Living arrangement was the predictor. The results are reported in Table 6.

Living arrangement did not significantly predict the SPA score. Living in an old age home

was associated with a non-significant decrease in SPA of 0.39 points. The model

explained a significant proportion of variance of 18.56% in the SPA score.

Based on the regression analysis and t-test results (see Table 4) H2 is rejected.

Table 6: Regression results for living arrangement on self-perception of aging controlling

for covariates

Unstandardized coefficients


Constant 1.78 1.19 1.50 0.137

R2 = 0.186 F(4, 134) = 7.63, p < 0.001*

LA -0.39 0.26 -1.49 0.139

Sex 0.15 0.27 0.55 0.581

Age 0.00 0.01 -0.07 0.943

Health 0.66 0.13 5.20 < 0.001* Dependent variable: self-perception of aging (SPA), *p < 0.05, higher values indicate a higher SPA score, SE=

standard error, t = Student’s t-test, F= F-test, OAH= old age home, LA= living arrangement [1= community,

2= OAH], sex [0= female, 1= male]

3.2.3 Hypothesis three: self-perception of aging and quality of life

Multiple regression analysis was also used to test H3 that older people with a more

negative perception of aging report lower quality of life compared to older people with a

more positive perception of aging controlling for sex, age and health. SPA was the

predictor. The results of the regression analysis are reported in Table 7.

After controlling for the covariates, SPA predicted physical health and psychological

health significantly. SPA did not significantly predict the environment and social

relationships domain.

One unit increase in the SPA score was associated with a significant increase on average

in physical health of 3.04 points and in psychological health of 3.14 points. The increase


25

in the environment domain score of 2.10 points and in social relationships of 0.79 points

was not significant.

The model of SPA as a predictor and the covariates explained a significant proportion of

38.64% in physical health, 29.98% in psychological health and 14.17% in the

environment domain score. The model explained a non-significant proportion of 6.19% in

the social relationships domain.

Based on the regression analysis, H3 seems to be true for the physical health domain

and the psychological health domain. H3 for the environment and social relationships

domain seems to be not true.

Table 7: Regression results for self-perception of aging on quality of life controlling for

covariates




Constant 50.52 11.75 4.30 < 0.001**

R2 = 0.386 F(4, 133) = 20.94, p < 0.001**

SPA 3.04 0.85 3.55 0.001**

Sex 3.43 2.68 1.28 0.203

Age -0.31 0.14 -2.11 0.029

Health 7.48 1.37 5.47 < 0.001**


Constant 41.42 10.20 4.06 < 0.001**

R2 = 0.300

F(4, 132) = 14.13, p < 0.001**

SPA 3.14 0.73 4.27 0.001**

Sex -4.12 2.33 -1.77 0.079

Age -0.20 0.12 -1.63 0.105

Health 4.27 1.19 3.60 < 0.001**


Constant 68.74 17.87 3.85 < 0.001**

R2 = 0.062 F(4, 131) = 2.16, p = 0.077

SPA 0.79 1.30 0.62 0.538

Sex -4.68 4.08 -1.15 0.253

Age -0.42 0.22 -1.94 0.054

Health 3.07 2.08 1.48 0.142


Constant 56.46 11.77 4.80 < 0.001**

R2 = 0.142 F(4, 134) = 5.53, p < 0.001**

SPA 2.10 0.85 2.48 0.014

Sex -1.99 2.69 -0.74 0.459

Age -0.29 0.14 -2.02 0.045

Health 2.78 1.37 2.03 0.045


t-test, F= F-test, SPA= Self-perception of aging, sex [0= female, 1= male]


26

3.2.4 Hypothesis four: mediating role of self-perception of aging

According to Baron and Kenny (1986), H4 that the association between living

arrangement and quality of life is partly explained by SPA cannot be true because one

path of the model (path a, see subsection “3.2.2 Hypothesis two: living arrangement and

self-perception of aging”) was not significant. Furthermore, the significant relationship

between living arrangement and the quality of life domains still persist after entering SPA

into the model (see Table 8). Following Baron and Kenny (1986), if the relationship

between living arrangement and quality of life would have been (partly) explained by

SPA, then the β coefficients of living arrangement should not be significant anymore.

Living arrangement still significantly predicted the quality of life domains. However, in

addition to the approach suggested by Baron and Kenny (1986), a more recent approach

was adopted in the present study (Hayes, 2009, 2013; Preacher & Hayes, 2004; Rucker

et al., 2011; Shrout & Bolger, 2002): bootstrapping and the Sobel test were used to

estimate the indirect effect (i.e. H4). The results are reported below.8 The β coefficient of

living arrangement from the final model (see Table 8) provides an estimation of the

direct effect on quality of life and is reported here as well (although this is not crucial to

answer the hypothesis but it will provide the reader with further information).

Quality of life domain: physical health

The direct effect of living arrangement on the quality of life domain physical health was

significant. A bootstrapped confidence interval (CI) for the indirect effect of living

arrangement on physical health through SPA was significant at the 95% CI, β = -1.14,

95% bias-corrected and accelerated bootstrap (BCa) CI [-3.21, -0.05], because the

range does not include zero. To adjust for multiple comparisons, however, the 99% CI

was calculated as well. The effect vanished at the 99% CI, β = -1.10, 99% BCa CI [-

3.81, 0.38]; the CI now includes zero thus indicating a non-significant result. The Sobel

test supports the non-significance of the indirect effect (z = -1.44, p = 0.150).

Based on the bootstrapped indirect effect estimation, the Sobel test and the Baron and

Kenny (1986) procedure, H4 for the physical health domain seems to be not true.

8 Note: bootstrapping and the Sobel test were calculated with PROCESS (v. 2.11) for SPSS (more information on PROCESS in Hayes, 2013).


27

Quality of life domain: psychological health

This direct effect of living arrangement on the quality of life domain psychological health

was significant. A bootstrapped CI for the indirect effect of living arrangement on

psychological health through SPA was not significant, β = -1.09, 95% BCa CI [-2.99,

0.25], because the range does include zero. The Sobel test supports this finding (z = -

1.33, p = 0.183).


Kenny (1986) procedure, H4 for the psychological domain is rejected.

Quality of life domain: social relationships

The direct effect of living arrangement on the quality of life domain social relationships

was significant. A bootstrapped CI for the indirect effect of living arrangement on social

relationships through SPA was not significant, β = 0.00, 95% BCa CI [-1.27, 1.27]. The

Sobel test indicates a similar result (z = 0.00, p = 0.999).


Kenny (1986) procedure, H4 for the social relationships domain is rejected.

Quality of life domain: environment

The direct effect of living arrangement on the quality of life domain environment was

significant. A bootstrapped CI for the indirect effect of living arrangement on the

environment score through SPA was not significant, β = -0.66, 95% BCa CI [-2.40,

0.08]. The Sobel test supports this finding (z = -1.13, p = 0.258).


Kenny (1986) procedure, H4 for the environment domain is rejected.


28

Table 8: Regression results for living arrangement on quality of life controlling for self-

perception of aging and covariates




Constant 55.17 11.33 4.87 < 0.001**

R2 = 0.441 F(5, 132) = 20.85, p < 0.001**

LA -8.91 2.47 -3.60 < 0.001**

SPA 2.67 0.82 3.27 0.001**

Sex 2.40 2.58 0.93 0.354

Age -0.25 0.14 -1.62 0.107

Health 8.01 1.32 6.07 < 0.001**


Constant 44.64 10.01 4.46 < 0.001**

R2 = 0.340

F(5, 131) = 13.49, p < 0.001**

LA -6.16 2.18 -2.82 0.006**

SPA 2.88 0.72 4.00 0.001**

Sex -4.83 2.28 -2.12 0.036

Age -0.14 0.12 -1.14 0.257

Health 4.64 1.16 3.98 < 0.001**


Constant 76.98 16.90 4.55 < 0.001**

R2 = 0.178 F(5, 130) = 5.62, p < 0.001**

LA -15.79 3.69 -4.28 < 0.001**

SPA 0.13 1.22 0.11 0.916

Sex -6.49 3.85 -1.68 0.095

Age -0.26 0.21 -1.26 0.209

Health 4.00 1.97 2.03 0.044


Constant 61.36 11.29 5.43 < 0.001**

R2 = 0.226 F(5, 133) = 7.77, p < 0.001**

LA -9.39 2.46 -3.81 < 0.001**

SPA 1.71 0.81 2.10 0.038

Sex -3.07 2.57 -1.19 0.235

Age -0.19 0.14 -1.40 0.164

Health 3.33 1.31 2.53 0.013


t-test, F= F-test, SPA= Self-perception of aging, OAH= old age home, LA= living arrangement [1= community,

2= OAH], sex [0= female, 1= male]

Maastricht University | FHML | Tom Kafczyk | Master’s thesis | Chapter: 4. Discussion and conclusion

29

4. Discussion and conclusion

This last chapter discusses first the results within the context of the hypotheses that

were formulated. Next, some study limitations that threaten the internal and external

validity are presented. Based on the study findings and limitations, several

recommendations for future research and policies are elaborated. Finally, a conclusion is

formulated.

4.1 Discussion

Quality of life and SPA in older persons is barely studied in the Indian context in different

living arrangements. The present study shed further light on these important concepts

and their interplay. It might have been the first study that used a quantitative approach

to examine the role of SPA in differences in quality of life among non-institutionalized and

institutionalized Indian elderly.

Hypothesis one: living arrangement and quality of life

As hypothesized, institutionalized elderly had a significantly lower quality of life in the

domains physical health, psychological health, social relationships and environment. The

mean difference between the living arrangements in the domain scores was 10.26 for

physical health, 6.71 for psychological health, 15.61 for social relationships and 10.01 for

the environment domain (see Table 4).

Particularly, differences in social relationships have been found. This means that older

persons in old age homes are on average less satisfied with, for example, their personal

relationships and social support. This is what has been expected. Dongre and Deshmukh

(2012) stated that social activities and the relationship to the family are factors that

determine quality of life. Such factors can be expected to be less or lower respectively in

old age homes in India, although empirical data is missing. Furthermore, the social

capital could be lower because residents might not be part of a wider social network and

have less social commitments. Social capital has been defined by Putnam (1995, p. 77)

as the “[...] features of social organization such as networks, norms, and social trust that

facilitate coordination and cooperation for mutual benefit.” The social capital was found to

be an associated factor with well-being and health of older adults in the community

outside of India (e.g. Cramm, van Dijk, & Nieboer, 2013; Momtaz, Haron, Ibrahim, &


30

Hamid, 2014; Norstrand & Chan, 2014). However, what role social capital plays in India

specifically in old age homes needs to be investigated empirically.

That the physical and psychological health domain scores are lower is not surprising as

well. This means, for example, that older persons in old age homes report to have less

mobility and have more negative feelings. Mahapatra (2010) mentioned physical and

mental decline as well as the feeling of loneliness as reasons to move to an institution.

Following this reasoning, participants had already a lower quality of life when they shifted

to the institution. Alternatively, it can also be argued that the sense of purpose in the old

age home is lower and therefore led to differences observed in psychological health.

Participants in the community (M = 3.43, SD = 0.90) stated that their life is to a greater

extend meaningful compared to those in old age homes (M = 3.11, SD = 0.87), t(135) =

2.13, p = 0.035.9 However, due to the cross-sectional design of the present study causal

inferences can not be made.

The environment domain as an aspect of quality of life was lower as well in

institutionalized elderly. This means that elderly people living in old age homes are on

average less satisfied with, for example, their financial resources, their freedom, the

accessibility and quality of health and social care, the old age home environment, the

opportunity to acquire new skills or the opportunity for leisure activities compared to

elderly in the community. For instance, elderly people in the community (M = 2.58, SD =

1.18) experienced on average more to have enough money to meet their needs

compared to those in old age homes (M = 1.96, SD = 1.16), t(137) = 3.16, p = 0.002.10

This was expected; poverty was mentioned as one of the main reasons to shift to an old

age home (Devi & Roopa, 2013). The pension coverage could contribute to the

difference. However, the coverage in old age homes is not established (Pension watch,

2014). It seems that old age homes cannot provide the same quality of life in the aspect

environment that is given in the community. One reason might be that old age homes

have not the resources (financial-wise, space-wise etc.). For instance, all old age homes

in this study had shared bedrooms with up to 25 older people sleeping in one room (see

Table 2). Residents in shared bedrooms might feel a lack of freedom/privacy what

negatively affects quality of life.

9 The results are from the question from the psychological health domain of the WHOQOL-BREF: “To what extent do you feel your life to be meaningful?” (see “Appendix 4 WHOQOL-BREF and domain facets”). The question was rated on a scale from 1 (= not at all) to 5 (= an extreme amount). 10 The results are from the question from the environment domain of the WHOQOL-BREF: “Have you enough money to meet your needs?” (see “Appendix 4 WHOQOL-BREF and domain facets”). The question was rated on a scale from 1 (= not at all) to 5 (= completely).


31

The results of H1 support researchers from India stating that the family is the better

environment for elderly people (Dongre & Deshmukh, 2012) and that non-

institutionalized older people are better adjusted because of the tradition in the Indian

society that it is the duty of the family to care for the elderly (Raju, 2011).

The difference in quality of life is in accordance with an outcome of a study by Mathew et

al. (2009). In contrast, results from Devi and Roopa (2013) indicated that older people in

the community have a lower quality of life compared to older people living in old age

homes. However, our study and studies of Mathew et al. (2009) and Devi and Roopa

(2013) are only partially comparable. The studies had different inclusion criteria and were

conducted in different settings. The results, nevertheless, are highly relevant given the

rapid increase of the older population in India (Global AgeWatch, 2013; United Nations,

2001) and the accompanying rise of the number of old age homes (Liebig, 2003;

Mahapatra, 2010). From a human rights perspective (United Nations, 2014), the findings

highlight the need to ensure a standard of living in which elderly people can grow older

with more quality in their lives.

Hypothesis two: living arrangement and self-perception of aging

Contrary to what has been hypothesized, living in an old age home compared to living in

the community was not associated with significant differences in self-perception of aging

(SPA). This means that the living arrangement is not associated with the SPA. The results

contradict findings of a study by Dubey et al. (2011). An explanation would be that SPA

stronger depends on common stereotypes of aging present in society than on differences

between living arrangements (Kotter-Gruhn & Hess, 2012; Levy, Slade, Kunkel, et al.,

2002). Possible is also that moving to an old age home initially affects the SPA but that

due to adaptation processes an adjustment in a positive direction occurs. This is similar

to what Gilbert, Pinel, Wilson, Blumberg, and Wheatley (1998) described as the

psychological immune system. Likely is furthermore that moving to an old age home

could have been an improvement for some elderly that were “lonely and forsaken” before

(Devi & Roopa, 2013, p. 7). Individuals in old age homes could contrast their perception

of aging to other more negative (life) events in the past compared to community elderly

who had more positive experiences. This is known as a contrast effect (Amundson,

2010). Mahapatra (2010, p. 120) described this point as follows: “For many older people

who have no one to support them, old age homes serve as a safe heaven.” Another

possible explanation is that participants in institutions compared their aging to that of

other residents and not to something as the “general population” leading to a response

shift (Amundson, 2010).


32

Hypothesis three: self-perception of aging and quality of life

In accordance with what has been hypothesized, SPA did significantly predict differences

in quality of life in the domains physical health and psychological health. It did not

predict the environment and social relationships domain. This means that a low SPA

score predicts a low quality of life score (see Figure 5). This is in line with a previous

study of Low et al. (2013).

Hypothesis four: mediating role of self-perception of aging

One might argue that the above discussed differences in quality of life are partly

explained by SPA, but there was no evidence that SPA functions as an intermediate

variable. An explanation could be that SPA is not influenced by living arrangement (as

discussed above) what affects the likelihood of a significant indirect effect through the

variables X M Y. Alternatively, SPA could change the relationship between living

arrangement and quality of life. This latter assumption was tested with a regression

analysis (see “Appendix 11 Regression with interaction term”). An interaction term of

living arrangement by SPA was added to the model reported in Table 8. The results

indicate that SPA was a moderator in the relationship between living arrangement and

physical health, β = -5.58, t(131) = -3.63, p < 0.001, social relationships, β = -1.88,

t(129) = -1.37, p = 0.002, and environment, β = -4.04, t(132) = -2.91, p = 0.004. SPA

did not function as a significant moderator between living arrangement and the quality of

life domain psychological health, β = -1.88, t(130) = -1.37, p = 0.173. The results

suggest that with an increasing SPA score elderly in the community report significantly

higher quality of life scores (see Figure 5). When the SPA score is low, no significant

relationship between living arrangement and quality of life can be observed (see also

“Appendix 11 Regression with interaction term”).


33

Figure 5: Quality of life domains as a function of self-perception of aging per living

arrangement

(a)

(b)

(c)

(d)

SPA= self-perception of aging, (a) WHOQOL-BREF domain physical health, (b) psychological health, (c) social

relationships and (d) environment

Furthermore, the SPA score and quality of life domain scores are correlated stronger for

older people living in the community. For these elderly, there was a significant positive

correlation between physical health and SPA, r(71) = 0.69, p < 0.001, psychological

health and SPA, r(71) = 0.55, p < 0.001, social relationships and SPA, r(70) = 0.36, p =

0.002, and the environment domain and SPA, r(72) = 0.46, p < 0.001. In elderly in

institutions, the relationship between living arrangement and quality of life was weaker.

There was a non-significant correlation between physical health and SPA, r(67) = 0.17, p

= 0.180, a significant positive but weak correlation between psychological health and

SPA, r(66) = 0.33, p = 0.007, a non-significant correlation between social relationships

and SPA, r(66) = -0.19, p = 0.118, and a non-significant correlation between the

environment domain and SPA, r(67) = 0.06, p = 0.625. In non-institutionalized elderly

SPA correlates therefore positive with the quality of life domains while in institutionalized

elderly SPA only correlates positive with psychological health.


34

The results indicate that quality of life and the perception of aging have different

relationships depending on the living situation. This has practical implications. While in

community elderly strategies to enhance the SPA are more indicated, in elderly in

institutions strategies targeting directly the quality of life aspects might be more

promising. The following quote derived from Jang et al. (2004, p. 486) who refer to a

paper of Levy, Slade, Kunkel, et al. (2002) may be partially relevant for community-

living elderly people in India: “Enhancement of positive self-perception has important

practical implications because it is strongly connected with better adjustment to changes

in old age and it leads to a higher quality of life regardless of objective life circumstances

[...].”

Covariates

The covariates sex and health did not vary significantly between the groups. The

covariate age differed significantly between the living arrangements. Older persons in

this study living in old age homes were on average older (approximately 3.60 years).

This difference is not surprising since people are more likely to move to an old age home

with progressing age. Age, however, did not influence the study outcome: after the effect

of age on quality of life was removed from the effect of living arrangement on quality of

life, the main effects for all quality of life domains were still highly significant.

Research question

To answer the research question if living arrangement (community versus old age home)

determines differences in quality of life and if this difference is partly explained by the

perception of aging among older adults over 55, the answer is two-fold. The living

arrangement determines differences in quality of life but SPA did not partly explain this

relationship. Instead, SPA seems to be a moderator indicating that the association

between living arrangement and quality of life depends on the perception of aging. If the

SPA is low, no significant differences between the living arrangements in quality of life

can be observed. On the other hand, if the SPA is high, significant differences were

observed.

4.2 Study limitations

Some study limitations are important to mention here. First, some of the effects

observed in this study could be attributable to unmodeled effects within the old age


35

homes or within the different areas and neighbourhoods. Bhushanam, Sreedevi, and

Kameshwaran (2013), for instance, suggested differences in the nutritional status of

residents in paid and unpaid old age homes. To test these “clusters” or organizational

units need to be part of a follow-up study. Multilevel modelling could be used assuming

an appropriate sample size (Hayes, 2013).

Second, due to practical constraints only three covariates and in total six variables were

examined in this study. This was necessary to not jeopardize the statistical power;

however, six variables can barely reflect the complex reality. Other not assessed

variables could have influenced or explained some of the observed variation in the

dependent variable. On an individual level, these are variables such as marital status,

feeling of personal control, social network, objective health status, income, education or

the participation in daily life (Barua et al., 2005; Cantor & Sanderson, 1999; Peterson,

1999; Pinquart & Sorensen, 2000; Thiyagarajan J, Prince, & Webber, 2014). On the level

of the old age home and household respectively, these are variables such as living in a

shared bedroom (more relevant in old age homes) or hygienic conditions. On the level of

the town, these are variables such as age-friendly transportation, availability of geriatric

health facilities or the availability and accessibility of recreational facilities. The covariate

“health” was measured here with only one question. There are problems with one-

question variables that methodologically need to be clarified in the future (Schwarz &

Strack, 1999). Participants might have had a different interpretation of the concept

“health” and thus a different interpretation of “How satisfied are you with your health?”.

One can also argue that objectively participants in old age homes have had a lower

health status but subjectively the participants reported the same health satisfaction

(Frederick & Loewenstein, 1999).

Third, another weakness of the study is that with the cross-sectional data collected here,

it is hard to make any causal claims. Longitudinal data has certainly advantages to

disentangle causal associations. Similarly, the direction of the effects is unclear. While

the relationship X M Y was modelled, it could as well have been X Y M (Hayes,

2013).

Lastly, another limitation is that different data collection methods (interview-form and

questionnaire-form). The majority of the data was collected in interview-form. While this

was necessary because most people did not want to or could not self-administer the

questionnaires, it is unclear whether the collection method biased the results. It is known

that differences in the mode of questionnaire administration can have effects on the

quality and accuracy of the data (Bowling, 2005). Both methods applied here are


36

associated with different biases such as recall bias, social desirability bias or interviewer

bias (Bowling, 2005).11 Likewise, the different languages (Kannada and English) might

have biased the outcome. The meanings of the questionnaires in both languages might

have been the same, but the interpretation could have been different. In “Appendix 7

Translation of the self-perception of aging questionnaire” a discussion of the limitations of

the translation of the SPA scale is presented. In addition, the settings and places where

data was collected (e.g. a kitchen or common room) varied resulting in differences in the

amount of privacy. The interaction of mode of administration, language and data

collection setting on the data quality is unclear.

Inferences based on the present results should therefore be done with caution. The data

could behave differently if the data would have been analyzed in its respective

organizational units or clusters. Furthermore, the time, location, principal investigator

and translator are further restrictions to the generalizability of the results. Likewise, the

selected participants itself could be a limitation to the generalizability. Older persons

unwilling to participate are not reflected in the data. As well, other groups of elderly,

such as homeless elderly, have not been studied. It is moreover worth pointing out, that

inferences are only possible within the boundaries of the operational definitions and

methods chosen for the present study.

4.3 Future directions

In this section, future directions for research and implications for policies based on the

study results are discussed.

4.3.1 Research

Further research is warranted in order to build on the present findings and shed more

light on the important topic examined here - a follow-up study is recommended. Future

research should try to minimize the study limitations mentioned above.

Multilevel-analysis and multiple comparisons need to be employed to test for differences

within the organizational units and clusters; these methods could yield to new insights

11 The recall bias means that different cognitive processes are necessary to recall information in an interview-style (oral information) compared to a self-administrated form (visual information) what could bias the results (Bowling, 2005). The social desirability bias is the tendency of participants to present themselves in the best possible way (Bowling, 2005). The interviewer bias was introduced above (see footnote 4).


37

into factors at the different levels responsible for the observed variation in quality of life.

Mixed methods including qualitative research could yield to more information as well.

Qualitative research can provide in-depth information about “the how and why”. For

example, ethnography can be employed to answer the question: “Which specific aspects

in an old age home characterize the life of an older person and how do these aspects

relate to the interpretation of quality of life and SPA?” Another question answerable with

qualitative methods that derived from the present study is: “Why does quality of life

depends less on SPA in institutionalized elderly compared to non-institutionalized?”

Future research should also place more emphasis on the role of SPA as a moderator;

more complex models (e.g. mediated moderation, multiple moderators) could be

considered (Jang et al., 2004). Moreover, because differences in age- and sex-sub-

groups in quality of life have been reported in India (Barua et al., 2005; Devi & Roopa,

2013), sub-group analysis by sex and age could be considered. Other variables not

considered here such as education need to be collected and assessed (see section “4.2

Study limitations”). Health as a covariate could be measured more rigorous and

methodologically sound. Longitudinal data would have an advantage in terms of causal

attributions of study effects; for example, the direction of the effect could be tested in

this way (e.g. X Y M versus X M Y). Furthermore, the effect of the interaction

of mode of questionnaire administration, language and data collection setting on the

quality of the data needs to be tested.

The discussion above brought up some topics that could be investigated in future

research in order to increase the understanding of the findings presented here. For

example, the role of stereotypes of aging, adaptation processes or contrast effects on

SPA (see section “4.1 Discussion”). Moreover, the role of social capital and pension

coverage in India specifically in institutions could be an interesting field of study in the

context of quality of life.

4.3.2 Policy implications

The present study provides evidence for the need to improve the quality of life

particularly in institutionalized elderly in the geographical study area. Especially the

improvement of social relationships could increase quality of life.

On the local level, within old age homes, an environment has to be created that is

adequate for the health and well-being of the residents. This includes meaningful

activities. To offer more (social) leisure activities might be an option for old age homes to


38

improve the quality of life domain environment and social relationships (Ra, An, & Rhee,

2013). To improve physical and psychological health, regular services are an option, such

as psychological counselling (Hepple, 2004), physiotherapy (Harada, Chiu, Fowler, Lee, &

Reuben, 1995) or occupational therapy (Steultjens et al., 2004). However, there is no

clear-cut evidence for a single measure. Instead, a holistic approach including multiple

measures on various levels should be considered.

The present work suggests the development of community strategies to enhance the

perception of aging in order to improve quality of life. An example would be programmes

for older adults that build on the principles of lifelong learning and active aging. Such

programmes have shown to be effective in enhancing the SPA in older adults in Spain,

Mexico, Chile and Cuba (Fernández-Ballesteros et al., 2013).

To indirectly benefit the local situation, on the national level, an increase of the share of

the gross domestic product that is devoted to health is an option. In this way, universal

health care for the aged population is more likely. As well, efforts to increase the pension

scheme coverage could be considered (Pension watch, 2014); this might lead to an

enhancement of financial security and consequently the domain environment of quality of

life. Another option is the development of a national monitoring and evaluation system of

the living situation of elderly in institutions. With such a system, the quality of care and

quality of life of residents in old age homes nationwide could be assessed and evaluated

regularly. This could lead to informed decision- and policy making.

On the global level, high income countries that have gone through the demographic

transition earlier and are experienced in institutionalized care for older people might play

an advisory role for India and be involved in other forms of development assistance to

improve institutionalized care.

The recommendations, however, are only partially valid. First, further research is

required obtaining high quality data. In addition, the process of policy-making should

involve older persons as well (participatory policy making). Second, implications might

vary depending on the old age home and geographical area. And lastly, financial aspects

and financial responsibilities have to be clarified. Who will pay for better facilities and

more services? Policies in India only encourage the construction and maintenance of old

age homes (Dongre & Deshmukh, 2012).


39

4.4 Conclusion

In conclusion, the present study used cross-sectional data from elderly in the community

and old age homes to assess differences in quality of life and the role of the perception of

aging as a mediator. While the results highlight lower quality of life scores in the domains

physical health, psychological health, social relationships and environment among people

living in an old age homes compared to those living in the community, the perception of

aging did not vary between the different living settings. SPA did predict physical health

and psychological health, but evidence that it partly explains differences in quality of life

was not found. Instead, SPA was identified as a moderator. The results suggest that the

relationship between living arrangement and physical, psychological and environmental

quality of life changed as a function of SPA. Strategies should be implemented to

enhance the quality of life of older persons particularly in institutionalized elderly.

Definite conclusions about whether this should be done through SPA cannot be drawn

based on the present study. A larger longitudinal follow-up study is recommended.

Maastricht University | FHML | Tom Kafczyk | Master’s thesis | Chapter: References

40

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Maastricht University | FHML | Tom Kafczyk | Master’s thesis | Chapter: Appendices

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Appendices

Appendix 1 Global AgeWatch domains and indicators

Global AgeWatch domains and indicators for India and Sweden

Domains and indicators Description indicator India Total rank: 73

Sweden Total rank: 1

Income security Rank: 54 Rank: 8

Pension coverage % people over 65 receiving a pension (percentage > 100 indicates that pension

coverage starts before the age of 65)

54.40 116.10

Old age poverty rate % of people aged 60+ with an income of less than half the country's median

income

5.60% 9.30%

Relative welfare

Average income/consumption of people aged 60+ as a % of average income/consumption of the rest of the population

102.70 89.00

GDP per capita This is a proxy for standard of living of people within a country, it aims to provide comparison across countries

US$ 3,073.20 US$ 4,125.40

Health status Rank: 85 Rank: 7

Life expectancy at age 60

Average number of years a person aged 60 can expect to live

17.00 24.00

Healthy life expectancy

at age 60

The average number of years a person

aged 60 can expect to live in good health 12.60 18.20

Relative psychological/mental wellbeing

% of people over 50 who feel their life has meaning compared with people aged 35-49 who feel the same

77.00 95.60

Employment and education Rank: 73 Rank: 5

Employment of older people

% of the population aged 55-64 that are employed

56.40% 70.50

Educational attainment % of population aged 60+ with secondary or higher education

20.30% 70.50

Enabling societies and environment Rank: 72 Rank: 5

Social connections % of people over 50 who have relatives or friends they can count on when in trouble

51.00% 88.00%

Physical safety % of people over 50 who feel safe walking alone at night in the city or area where they live

61.00% 77.00%

Civic freedom % of people over 50 who are satisfied with the freedom of choice in their life

54.00% 96.00%

Access to public transport

% of people over 50 who are satisfied with the local public transportation systems

59.00% 74.00%

Note: data from Global AgeWatch (2013), rank number 1 is the best rank and rank number 91 is the poorest

rank, GDP= gross domestic product


46

Appendix 2 Demographics in Karnataka

Demographics in India, Karnataka State, Dakshina Kannada and Udupi district

Population

Decadal growth rate population

(in %)

Sex ratioa

Population density (per sq. km)

Persons Females Males 2001-11 2011 2011

India AN 1210193422 586469174 623724248

17.64 940 382 RN 100.0% 48.46% 51.54%

Karnataka State

AN 61130704 30072962 30072962 15.67 968 319

RN 100.0% 49.19% 50.81%

Dakshina

Kannada

AN 2083625 1051048 1032577 9.80 1018 457

RN 100% 50.44% 49.56%

Udupi AN 1177908 615012 562896

5.90 1093 304 RN 100.0% 52.21% 47.79%

Note: data from Ministry of Home Affairs (2014b), decadal growth rate= growth of the population in 10 years,

AN= absolute number, RN= relative number, a Sex ratio= females per 1000 males

For demographics separated by age groups please refer to the following domain:

http://censusindia.gov.in/Census_Data_2001/Census_Data_Online/Social_and_cultural/Age_Groups.aspx

http://censusindia.gov.in/Census_Data_2001/Census_Data_Online/Social_and_cultural/Age_Groups.aspx


47

Appendix 3 Informed consent template

Note: the informed consent here is only a template; the format used in the study was

more “age-friendly” (i.e. bigger font size).

Invitation letter

To: Older persons living in the community or old age homes in Udupi district who are

invited to participate in the “Quality of Life and Perception of Aging Project”

This invitation letter is part of the informed consent that consists of two parts:

Part A: Subject Information Sheet

Part B: Informed Consent Form

Dear respected participant,

I am Tom Kafczyk, a final year master student of Global Health from Maastricht

University. I am now undertaking a thesis-project for the partial fulfilment of the course

in collaboration with Manipal University. The project is about quality of life and perception

of aging. I am going to give you information (Part A) and invite you to be part of this

project. You do not have to decide right now whether or not you will participate in the

research.

If you accept to participate I will ask you to sign an informed consent (Part B)/give oral

consent and to fill out questionnaires. It should not take longer than 20 minutes. You

may answer the questionnaire yourself, or it can be read out to you and the answer you

chose will be written down for you. If you do not want to answer any of the questions,

you may just want to skip them and move on to the next questions. You do not have to

give us any reason for not answering a question.

Thank you very much. Do you have any questions?

Yours sincerely

Tom Kafczyk

Maastricht and Manipal University

Mobile: [anonymized]


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Part A: SUBJECT INFORMATION SHEET

Protocol title: Quality of Life and Perception of Aging in Institutionalized and Non-

Institutionalized Elderly in Karnataka State

Language: English and Kannada

Principal Investigator: Tom Kafczyk

Designation: PG student in Global Health (Maastricht/Manipal University)

Contact number: [anonymized]

Please read this form carefully. If you don’t understand the language or any information

in this document, please discuss with the principal investigator.

Introduction to the research study

India will soon have the second largest population over 60 after China. Amplified by

globalization, older people face now a decline in traditional values that is reflected in a

breakdown of family structures and a rise in the number of old age homes. Not family

but institutional care for the elderly is on the rise. In light of these changes, a better

understanding of how different living arrangements affect quality of life and the

perception of aging is needed. This quantitative study aims to contribute to a better

understanding of the interplay of living arrangement, perception of aging and quality of

life in elderly in Karnataka.

Purpose of the study

The purpose of the present study is to shed light on potential differences in quality of life

of elderly people living in the community versus living in old age homes and how the

perception of aging of the elderly may explain at least partly this difference. The study

will thus help to identify the need to enhance quality of life and the perception of aging

and might assist policy-makers in identifying appropriate strategies.

Who can take part

Elderly persons within old age homes and within the community in Udupi and Dakshina

Kannada district will be asked to participate. Inclusion criteria are ≥ 55 years and giving

informed consent.

Information about the study

It is a comparative cross-sectional study. The data will be collected in approximately two

month. The target population size is 120 (60 in old age homes and 60 in communities).

Two questionnaires are used: the WHOQOL-BREF and the Attitude Toward Own Aging

subscale of the Lawton Philadelphia Geriatric Centre Morale Scale. It should not take


49

longer than 20 minutes. None of the questions are sensitive or embarrassing. The study

does not involve any kind of physical examination of the participants.

Your role in the study

You are invited for participation to provide with your valuable responses.

What are the risks?

There is no potential risk in the study. The information provided by the participants will

be treated as confidential. This proposal has been reviewed and approved by the

Institutional Review Committee, Kasturba Hospital, Manipal that is a committee whose

task it is to make sure that research participants are protected from harm.

What are the potential benefits of participating in the study?

This study may provide new insights into the quality of life and perception of aging

research. These evidences can have policy implications and might thus indirectly benefit

the participants. Participants will not receive any incentives.

Confidentiality of information

The information provided will be treated as confidential and anonymous and no one else

except the principal investigator will have access to the provided information.

Voluntary participation

Whether or not you take part in the study is your choice. If you do not wish to

participate, you do not have to give a reason. You have the right to access information

collected as part of the study.

Whom to contact in case of any questions

If you have any questions about this form or any study related issues, you may contact

the following person.

Name: Dr. Lena Ashok

Address: Assistant Professor

Dept. of Public Health

Manipal University

Telephone No.: [anonymized]


50

Part B: Informed consent Form

I have read the Subject Information Sheet and its contents were explained. I had the

opportunity to ask questions and received satisfactorily answers.

I understand that my participation in the study is voluntary and that I have the right to

withdraw at any time without giving any reason, without my medical care or legal rights

being affected.

I agree to take part in the above study I confirm that I have received a copy of the

subject information sheet along with this signed and dated informed consent form.

______________________________________ __________

Name & Signature of the research subject Date

______________________________________ __________

Name & signature of the witness Date

______________________________________ __________

Name & signature of the person explaining the consent Date


51

Appendix 4 WHOQOL-BREF and domain facets

The following four domains were assessed with the WHOQOL-BREF questionnaire

(WHOQOL Group, 1998): (1) physical health, (2) psychological health, (3) social

relationships and (4) environment. Please note that a Kannada version was used as well

(not shown here). As well, note that the WHOQOL-BREF versions used in the field were

used in their original formats provided by the World Health Organization.12

WHOQOL-BREF questionnaire

This assessment asks how you feel about your quality of life, health, or other areas of your life.

Please answer all the questions. If you are unsure about which response to give to a question,

please choose the one that appears most appropriate. This can often be your first response. Please

keep in mind your standards, hopes, pleasures and concerns. We ask that you think about your life

in the last two weeks

Very poor Poor Neither poor

nor good Good Very good

1

How would you rate

your quality of life? 1 2 3 4 5

Very

dissatisfied

Dissatisfied Neither

satisfied nor

dissatisfied

satisfied Very satisfied

2

How satisfied are

you with your

health?

1 2 3 4 5

The following questions ask about how much you have experienced certain things in the last two

weeks.

Not at all A little A moderate

amount Very much

An extreme

amount

3

To what extent do

you feel that

physical pain

prevents you from

doing what you need

to do?

1 2 3 4 5

4

How much do you

need any medical

treatment to

function in your

daily life?

1 2 3 4 5

12 An original format of the BREF questionnaire in English can be accessed under the following link: http://www.who.int/substance_abuse/research_tools/en/english_whoqol.pdf.

http://www.who.int/substance_abuse/research_tools/en/english_whoqol.pdf


52

5 How much do you

enjoy life? 1 2 3 4 5

6

To what extent do

you feel your life to

be meaningful?

1 2 3 4 5

Not at all A little A moderate

amount Very much Extremely

7 How well are you

able to concentrate? 1 2 3 4 5

8 How safe do you feel

in your daily life? 1 2 3 4 5

9

How healthy is your

physical

environment?

1 2 3 4 5

The following questions ask about how completely you experience or were able to do certain things in

the last two weeks.

Not at all A little Moderately Mostly Completely

10

Do you have enough

energy for everyday

life?

1 2 3 4 5

11

Are you able to

accept your bodily

appearance?

1 2 3 4 5

12

Have you enough

money to meet your

needs?

1 2 3 4 5

13

How available to you

is the information

that you need in

your day-to-day life?

1 2 3 4 5

14

To what extent do

you have the

opportunity for

leisure activities?

1 2 3 4 5

Very poor Poor Neither poor

nor good Good Very good

15 How well are you

able to get around? 1 2 3 4 5

The following questions ask you to say how good or satisfied you have felt about various aspects of

your life over the last two weeks.

Very

dissatisfied Dissatisfied

Neither

satisfied nor

dissatisfied

Satisfied Very satisfied

16 How satisfied are

you with your sleep? 1 2 3 4 5


53

17

How satisfied are

you with your ability

to perform your

daily living

activities?

1 2 3 4 5

18

How satisfied are

you with your

capacity for work?

1 2 3 4 5

19 How satisfied are

you with yourself? 1 2 3 4 5

20

How satisfied are

you with your

personal

relationships?

1 2 3 4 5

21

How satisfied are

you with your sex

life?

1 2 3 4 5

22

How satisfied are

you with the support

you get from your

friends?

1 2 3 4 5

23

How satisfied are

you with the

conditions of your

living place?

1 2 3 4 5

24

How satisfied are

you with your access

to health services?

1 2 3 4 5

25

How satisfied are

you with your

transport?

1 2 3 4 5

The following question refers to how often you have felt or experienced certain things in the last two

weeks.

Never Seldom Quite often Very often Always

How often do you

have negative

feelings such as blue

mood, despair,

anxiety, depression?

1 2 3 4 5

Did someone help you to fill out this form? O Yes O No


54

WHOQOL-BREF domains and the incorporated facets

The following table lists in column two the facets that are incorporated into the WHOQOL-

BREF domains.

WHOQOL-BREF domains and incorporated facets

Note: information from WHOQOL Group (1998, p. 552)

Domain Facets incorporated into the domains

1. Physical health

(7 items)

- Activities of daily living - Dependence on medicinal substances and medical aids - Energy and fatigue - Mobility - Pain and discomfort - Sleep and rest - Work capacity

2. Psychological health (6 items)

- Bodily image and appearance

- Negative feelings - Positive feelings - Self-esteem - Spirituality/religion/personal beliefs - Thinking, learning, memory and concentration

3. Social relationships

(3 items)

- Personal relationships - Social support - Sexual activity

4. Environment (8 items)

- Financial resources

- Freedom, physical safety and security - Health and social care: accessibility and quality - Home environment - Opportunities for acquiring new information and skills - Participation in and opportunities for recreation/leisure activities - Physical environment (pollution/noise/traffic/climate) - Transport


55

Appendix 5 WHOQOL-BREF user agreement


56


57


58

Appendix 6 Self-perception of aging questionnaire

The following self-perception of aging questionnaire was used (Lawton, 1975). Please

note that the version in Kannada language is not shown here; see the next Appendix for

a detailed description of the translation procedure. As well, note that the format used in

the study was more “age-friendly” (i.e. bigger font size).

Self-perception of aging questionnaire

I would like to ask you a few questions. You can just answer yes or no to most of them.

Please answer the questions by circling the correct answer.

1 Do things keep getting worse as you get older? Yes No

2 Do you have as much pep as you had last year? Yes No

3 Do you feel that as you get older you are less useful? Yes No

4 As you get older, are things (better/worse) than you

thought they would be? Better Worse

5 Are you as happy now as you were when you were

younger? Yes No


59

Appendix 7 Translation of the self-perception of aging

questionnaire

Introduction

The original version of the Attitude Toward Own Aging subscale of the Philadelphia

Geriatric Center Morale Scale was used to measure self-perception of aging (see

“Appendix 6 Self-perception of aging questionnaire”). The scale has not been used in

Kannada language elsewhere. Because the target group in the present study of elderly in

Karnataka speaks primarily Kannada language a translation was obligatory (see

subsection “2.1.1 Sampling”).

Methods

To translate the scale, the two-phase validated translation procedure of Sperber (2004)

was applied (see figure below). Taking into account time and resource constraints of the

present study, this procedure seemed to be the most appropriate.

Flow diagram of the two-phase validated translation

procedure

Note: from Sperber (2004, p. 126)

In the first phase, the original Attitude Toward Own Aging scale in English (A) was

translated to Kannada language (B). In a next step, the Kannada version was back-


60

translated to English language (C). Research assistants in the Dept. of Public Health at

Manipal University, Karnataka, India, fluent in English and Kannada, independently

translated and back-translated the two versions.

In the second phase, the original version in English (A) and the back-translated version

(C) were formerly compared using a rating sheet as described in Sperber (2004) to

identify problems in the translation. The items (Q1-Q5) in (A) and (B) were compared by

up to 31 raters (see table below) according to two criteria. First, according to

comparability of language on a Likert scale from 1 (= extremely comparable) to 7 (= not

at all comparable); and second, according to similarity in language on a Likert scale from

1 (= extremely similar) to 7 (= not at all similar).

Raters were recruited in the Kasturba Medical College Central Library (mostly students),

Manipal University, and asked to rate the items according to the two criteria. All raters

were independent of the principal investigator and did not include the translators. Refer

to the Table below for a description of the raters.

Because the first formal comparison yielded to unacceptable results phase one and two

were repeated once (the two cycles are hereafter referred to as: first round and second

round).

Characteristics of raters of the first and second validation round

First round (N= 19)

Second round (N= 31)


Age (Mean ± SD) 29.47 ± 10.93 23.55 ± 2.26 t(44) = 2.10, p = 0.056

Sex (Female/male) 9/10 18/13 X2 (1, N= 50)= 0.54, p= 0.560

Students (in %) 70.60% 96.80% X2 (1, N= 48)= 6.88, p= 0.020*

Native English speakers (in %)

18.20% 53.30% X2 (1, N= 48)= 4.04, p= 0.070

Note: only 19 participants were recruited in the first round because a preliminary analysis yielded to

unacceptable results, *p < 0.05, X2 = Chi-Square, t = Student’s t-test, SD= standard deviation

Results

The results of phase two of the first translation round are given in the Table below.13 No

mean score was within the acceptable range of 1-2.5 as defined by Sperber (2004). With

the exception of the interpretation of Q2 (M = 2.79, SD = 1.51) and the comparability of

13 Round one, phase one, the back translated version: Q1. As age progress things are becoming worst? Q2. Are you equally energetic as that of last year? Q3. As age progress do you feel less and less useful? Q4. As you are becoming older things are becoming good/bad than expected? Q5. Are you as happier even now, as you were during younger?


61

language of Q4 (M = 2.72, SD = 1.81), all scores had a mean of equal or above 3

indicating the necessity of a formal review of the translation.

Q2 differed with 0.63 points between the comparability of language and the

interpretation. The word “pep” was translated to “energetic” in the target language.

Despite being different in language, the interpretation seems to be similar. Because the

mean values were significantly over 3, phase one and two were repeated after only 19

participants. All items in the second round were assessed and revised thoroughly in

phase one and compared again in phase two as described below.

The revision of the translation in the second round revealed that the word “energetic” in

Q2 has to be maintained because there is no word in Kannada for “pep”. “Energetic”

most closely represents the original wording of “pep”. In order to guarantee consistency

and validity of the versions in English and Kannada, Q2 in English was revised as well.

The item was changed to “Do you have as much pep/energy as you had last year?”. The

revised version of the Kannada translation (B) was back-translated to English.

The results for round one and round two of the validation procedure are given in the

Table below.

Mean comparison first and second round

Round one (Mean ± SD)

N Round two (Mean ± SD)

N Difference = µround 1 –

µround 2


Q1_Comp 3.47 ± 1.39 19 2.97 ± 1.11 31 0.50 t(48) = 1.4, p = 0.160

Q1_Interp 3.53 ± 1.50 19 3.10 ± 1.45 31 0.43 t(48) = 1.0, p = 0.320 Q2_Comp 3.42 ± 1.46 19 2.81 ± 1.11 31 0.62 t(48) = 1.68, p = 0.100 Q2_Interp 2.79 ± 1.51 19 2.58 ± 1.43 31 0.21 t(48) = 0.49, p = 0.626 Q3_Comp 4.26 ± 1.48 19 3.03 ± 1.52 30 1.23 t(47) = 2.78, p = 0.008*

Q3_Interp 3.68 ± 1.60 19 2.90 ± 1.49 31 0.78 t(48) = 1.75, p = 0.090 Q4_Comp 2.72 ± 1.81 18 2.55 ± 0.99 31 0.17 t(47) = 0.43, p = 0.710 Q4_Interp 3.12 ± 1.27 17 2.71 ± 1.27 31 0.41 t(46) = 1.06, p = 0.290

Q5_Comp 3.00 ± 1.75 18 3.07 ± 1.51 30 -0.07 t(46) = -0.14, p = 0.89

Q5_Interp 3.24 ± 1.60 17 2.71 ± 1.10 31 0.53 t(46) = 1.34, p = 0.190 *p < 0.05, SD= standard deviation, Comp= comparison, Interp= interpretation, µ= mean

The mean scores for all items improved in the second round14 except for the

comparability of language of Q5 (-0.07). The comparability of Q3 improved the most with

1.23 points. Nevertheless, none of the items is within the acceptable range of 1-2.5. Q2

14 Round two, phase one, the back translated version: Q1. Do you think that as you grow older things are going worse for you? Q2. Do you feel you are as energetic as you were last year? Q3. Do you think as you are growing older you are becoming less useful? Q4. Do you think that as you are growing older things are becoming better/worse than you thought? Q5. Are you as happy now as in your youth age?


62

and Q4 are within the 2.5-3.0 range indicating the need for possible corrections. After a

review of Q2 and Q4 no need for possible corrections was identified. Q1, Q3 and Q5 are

only slightly over the 3.0 value arguably a formal review of the translation is not

necessary and after reviewing item Q1, Q3 and Q5 only Q5 seems to lack in

comparability of language and interpretability requiring some corrections. In Q5 the

translation from “when you were younger” to “as in your youth age” needs correction

because “younger” is a much broader term and “youth age” does specify a certain time

period that does not include adulthood. The answer responses could change because the

meaning of the question is altered. After reviewing the item, however, it turned out that

the translation back to English (C) was not correct. “Youth” should have been “younger”.

Nevertheless, the target language, Kannada, does not have a word for “younger”. In

Kannada “younger” is translated to what would most closely represent “younger age”.

After a careful review of the translation, it has been decided that the questions in round

two are properly translated, i.e. the meaning is the same. No further correction is

needed.

Discussion and Conclusion

Due to time- and resource-constraints, the two-phase validated translation procedure

from Sperber (2004) has been preferred over more labor-intensive and time-consuming

procedures (e.g. Acquadro, Conway, Hareendran, & Aaronson, 2008) to translate the

Attitute Towards Own Aging scale. In total 50 raters formally compared the original

version and the back-translated version of the scale eventually indicating a valid

translation.

Certain limitations are associated with this procedure that should be mentioned. First,

only one person translated the original version to Kannada and only one person

(independent of the first person) back-translated the version. Two translators could have

translated (and back-translated) the questionnaire followed by a step to synthesize the

best possible translation by the two translators. Second, there was no review of the

translation by other professionals and no pretesting of the translation. Lastly, it is unclear

whether the items of the scale in Kannada language are equivalent to its original version.

Are the items in English behaving in the same way and loading on the same factor

(perception of aging) as the version translated to Kannada? For example, the subject-

specific ability to speak Kannada could lead to differential effects. Differential item

functioning has not been conducted here (Teresi, Ramirez, Lai, & Silver, 2008).

Furthermore, confirmatory factor analysis and reliability analysis has not been conducted.

These advanced statistical procedures to confirm the validity and reliability of the

translation are not part of the two-phase translation procedure from Sperber (2004) and


63

were not feasible for the purpose of this study. However, future larger research projects

using the translation to Kannada language of the Attitude Toward Own Aging scale should

consider advanced statistical procedures to confirm the validity and reliability of the

scale.

Conclusion

Despite limitations of the validated translation procedure used to translate the Attitude

Toward Own Aging scale, evidence for the validity of the translation has been provided.

Within the constraints of the used procedure from Sperber (2004), after a careful review

of the translated items, it is concluded that no further improvements of the translated

version into Kannada language was feasible.


64

Appendix 8 Ethical clearance certificate


65


66

Appendix 9 Correlations among study variables

Pearson correlations among study variables

Quality of life domains

LA Sex Age Health SPA Physical Psychological Social relations Environment

LA Corr - 0.128 0.190 0.040 -0.110 -0.280 -0.225 -0.349 -0.321 p 0.134 0.025* 0.642 0.199 0.001** 0.008** 0.000** 0.000**

N 139 139 139 139 138 137 136 139

Sex Corr 0.128 - 0.101 -0.108 -0.104 -0.175 0.052 0.061 0.002 p 0.134 0.237 0.204 0.223 0.040* 0.549 0.482 0.984

N 139 139 139 139 138 137 136 139

Age Corr 0.190 0.101 - -0.057 -0.056 -0.198 -0.142 -0.167 -0.179 p 0.025* 0.237 0.507 0.507 0.020 0.098 0.053 0.035 N 139 139 139 139 138 137 136 139

Health Corr 0.040 -0.108 -0.057 - 0.410 0.537 0.421 0.160 0.270 p 0.643 0.204 0.507 0.000* 0.000** 0.000** 0.063 0.001** N 139 139 139 139 138 137 136 139

SPA Corr -0.110 -0.104 -0.056 0.410 - 0.454 0.453 0.113 0.294

p 0.199 0.233 0.513 0.000* 0.000** 0.000** 0.191 0.000** N 139 139 139 139 138 137 136 139

Physical Corr -0.280 -0.175 -0.198 0.537 0.454 - 0.652 0.276 0.525 p 0.001** 0.040 0.020 0.000** 0.000** 0.000** 0.001** 0.000** N 138 138 138 138 138 136 135 138

Psychological Corr -0.225 0.052 -0.142 0.421 0.453 0.652 - 0.429 0.659

p 0.008** 0.549 0.098 0.000** 0.000** 0.000** 0.000** 0.000** N 137 137 137 137 137 136 134 137

Social relations Corr -0.349 0.061 -0.167 0.160 0.113 0.276 0.429 - 0.624 p 0.000** 0.482 0.053 0.063 0.191 0.001** 0.000** 0.000** N 136 136 136 136 136 135 134 136

Environment Corr -0.321 0.002 -0.179 0.270 0.294 0.525 0.659 0.624 -

p 0.000** 0.984 0.035 0.001** 0.000** 0.000** 0.000** 0.000** N 139 139 139 139 139 138 137 136 *p < 0.05, **p < 0.0125, Corr= correlation, LA= living arrangement, SPA= self-perception of aging


67

Appendix 10 Study summary: statistical diagrams

Statistical diagrams of living arrangement on quality of life (for each domain) mediated

through self-perception of aging

(a)

(b)

(c)

(d)

Note: the indirect effect values were calculated with PROCESS (v. 2.11) for SPSS, the CI (= confidence interval)

for the indirect effect is a bootstrapped CI based on 10000 samples, the β coefficients are unstandardized, (a)

WHOQOL-BREF domain physical health, (b) psychological health, (c) social relationships and (d) environment,

the significance of the 95% CI in (a) does not persist at the 99% CI that is trusted in the present study to

adjust for multiple comparisons (see subsection “3.2.4 Hypothesis four: mediating role of self-perception of

aging”)


68

Appendix 11 Regression with interaction term

Results regression with interaction term controlling for the covariates




Constant 56.81 11.25 5.05 < 0.001**

R2 = 0.494 F(6, 131) = 29.05, p < 0.001**

LA -8.54 2.45 -3.48 < 0.001**

SPA 2.93 0.85 3.45 < 0.001**

Sex 1.74 2.64 0.66 0.512

Age -0.31 0.15 -2.09 0.039

Health 7.23 1.30 5.55 < 0.001**

Int_LA*SPA -5.58 1.54 -3.63 < 0.001**


Constant 46.37 9.93 4.67 < 0.001**

R2 = 0.347 F(6, 130) = 9.87, p < 0.001**

LA -6.01 2.24 -2.68 0.008**

SPA 2.94 0.72 4.08 0.001**

Sex -4.83 2.34 -2.07 0.041

Age -0.16 0.13 -1.21 0.228

Health 4.36 1.18 3.70 < 0.001**

Int_LA*SPA -1.88 1.37 -1.37 0.173


Constant 61.87 16.67 3.71 < 0.001**

R2 = 0.247 F(6, 129) = 7.80, p < 0.001**

LA -15.59 3.70 -4.21 < 0.001**

SPA 0.34 1.25 0.27 0.788

Sex -7.14 3.68 -1.94 0.055

Age -0.36 0.20 -1.80 0.074

Health 3.23 1.95 1.65 0.101

Int_LA*SPA -7.42 2.37 -3.14 0.002**


Constant 57.17 10.14 5.64 < 0.001**

R2 = 0.268

F(6, 132) = 9.70, p < 0.001**

LA -9.20 2.39 -3.85 < 0.001**

SPA -1.90 -0.78 -2.42 0.017

Sex -3.42 2.45 -1.39 0.166

Age -0.25 0.13 -1.90 0.059

Health 2.83 1.28 2.22 0.028

Int_LA*SPA -4.04 1.39 -2.91 0.004**

Note: the statistic was calculated with PROCESS (v. 2.11) for SPSS, **p < 0.0125, a= higher values indicate

higher quality of life domain scores, SE= standard error, t = Student’s t-test, F= F-test, SPA= Self-perception

of aging, OAH= old age home, Int= Interaction, LA= living arrangement [1= community, 2= OAH], sex [0=

female, 1= male]


69

Slopes of regression of living arrangement on quality of life at three levels of self-

perception of aging

WHOQOL-BREF domain SPA score slope results

(a)

When the SPA score is low, there is a non-significant relationship

between living arrangement and the quality of life domain physical

health, β = 0.50, 95% CI [-6.37, 7.38], t(131) = 0.14, p = 0.886.

At middle level of SPA, there is a significant relationship between living

arrangement and physical health, β = -8.54, 95% CI [-13.39, -3.69],

t(131) = -3.49, p < 0.001**.

When SPA high, there is a significant relationship between living

arrangement and physical health, β = -8.54, 95% CI [-13.39, -3.69],

t(131) = -3.49, p < 0.001**.

(b)


between living arrangement and the quality of life domain

psychological health, β = -2.95, 95% CI [-9.37, 3.47], t(130) = -0.91,

p = 0.365.


arrangement and psychological health, β = -6.01, 95% CI [-10.43, -

1.58], t(130) = -2.68 p = 0.008**.


arrangement and psychological health, β = -9.06, 95% CI [-15.13, -

3.00.], t(130) = -2.95, p = 0.004**.

(c)


between living arrangement and the quality of life domain social

relationships, β = -3.56, 95% CI [-14.14, 7.01], t(129) = -0.67, p =

0.506.


arrangement and social relationships, β = -15.59, 95% CI [-22.91, -

8.27], t(129) = -4.21, p < 0.001**.


arrangement and social relationships, β = -27.62, 95% CI [-38.13, -

17.11], t(129) = -5.20, p < 0.001**.

(d)


between living arrangement and the quality of life domain

environment, β = -2.64, 95% CI [-9.04, 3.77], t(132) = -0.82, p =

0.417.


arrangement and environment, β = -9.20, 95% CI [-13.92, -4.47],

t(132) = -3.85 p < 0.001**.

When SPA is high, there is a significant relationship between living

arrangement and environment, β = -15.76, 95% CI [-22.35, -9.16],

t(132) = -4.73, p < 0.001**.

Note: the statistic was calculated with PROCESS (v. 2.11) for SPSS, **p < 0.0125, CI= confidence interval, t=

Student’s t-test, SPA= self-perception of aging, (a) WHOQOL-BREF domain physical health, (b) psychological

health, (c) social relationships and (d) environment

quality of life and perception of aging in institutionalized and non-institutionalized elderly in...

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