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INTRODUCTION

In this topic, you will learn about the appropriate way to measure ones healthstatus. We will then discuss the various types of research design, and you will getto see the step by step flow of research. Next, we will discuss the issues ofreliability and validity in research. Lastly, we will discuss data analysis and datainterpretation.

MEASURING HEALTH STATUS

In Topic 1, we discussed the concept of health. Health is a multi-dimensionalconcept which emphasises four basic elements of your life:

(a) Physical:

(b) Psychological;

2.1

TTooppiicc

22 Research

Methods inHealthPsychology

LEARNING OUTCOMES

By the end of this topic, you should be able to:

1. Explain how to measure health status;

2. Describe various types of research design;

3. Describe various types of reliability; and

4. Describe various types of validity.

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TOPIC 2 RESEARCH METHODS IN HEALTH PSYCHOLOGY16

(c) Social; and

(d) Functional

As a health psychologist, you should understand how to measure the level ofhealth, not only for individual health status but also population health status.Even though there is no single standard to measure health status forindividuals or population groups, ideally all the elements in health mentionedabove should be measured.

2.1.1 Individual Health Status

The physical element of health is often measured by health professionals. A

doctor performs an examination and rates a persons health status by lookinginto his overall health, presence or absence of life-threatening illness, risk factorsfor premature death and severity of disease.

The psychological elements such as emotional well-being, pain or discomfort,overall perception of health and social functioning can be measured throughdirect interviews by mental health professionals, e.g. psychiatrists, psychologistsand counsellors, or by using questionnaires.

Below are a few examples of questionnaires that have been well-validated and

used cross-culturally in many countries:

(a) World Health Organization (WHO) Quality of Life: WHOQOL -100 orWHOQOL-BREF

(b) Medical Outcomes Study (MOS) 36 Item Short Form Health Survey: SF 36Health Survey

(c) Health-Related Quality of Life: HRQOL

*See references for more details on these questionnaires

2.1.2 Population Health Status

The health status of a country or community is determined by combining all theindividual health status. For example, Malaysias health status is a reflection ofthe status of all individual Malaysians. Data of each individuals status of healthis gathered through annual census and registry. Doctors are responsible for

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TOPIC 2 RESEARCH METHODS IN HEALTH PSYCHOLOGY 17

updating the census of their clinics, hospitals or other health facilities under theirauthority. Below are a few key measures of population health status used bymany countries including Malaysia:

(a)

Life expectancy;

(b) Morbidity and mortality rate; and

(c) Burden of Disease and Disability Adjusted Life Years (DALYs).

Lets now discuss these measures:

(a) Life ExpectancyLife expectancy is a prediction of how long a person is expected to live(assuming that present mortality patterns do not change and thatpremature death does not occur).

(b) Morbidity Rate and Mortality RateMorbidity raterefers to the rate of illness or disease in an individual and ina population. This data includes levels of disease, illness, disability andinjury. Two terms are often used:

(i) Incidence rate; and

(ii) Prevalence rate.

Incidence rate is the number of new cases of an illness or disease during a

given time.

Incidence rate =

Number of new cases of a disease occurring in the population

during a specified time period

umber of persons exposed to risk of developing the disease

during that period of time

Prevalence rate is the number or proportion of cases present in a populationat a given time or how many people currently have a particular disease at

that given time.

Prevalence rate

Number of cases of disease present in the population during a

specified time period

umber of persons at risk of having the disease at that specified

time

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Mortality raterefers to frequency of death in a population.

Mortality rate =

Number of deaths in the population during a specified time

period

umber of persons in the population during the specified

time period

The denominator is usually defined as the number of persons in thepopulation at the midpoint of the time period (usually 12 months). The rateis multiplied by 1,000 or 100,000 for ease of interpretation.

(c) Burden of Disease and Disability adjusted Life Year (DALY)

Burden of diseaserefers to the impact of a particular disease or condition inrelation to the amount of healthy lives lost due to premature death, illnessand/or disability. In other words, it indicates how much disease or illnessthere is in a country. Burden of disease is measured using DALY. It is a unitof measurement that has been developed to compare the impact of differentdiseases and injuries on an equal basis.

Years of Life Lost (YLL) refers to the loss of years of life as a result ofpremature death.

Years of Life Lost Due to Disability (YLD) refers to loss of a healthy life dueto non-fatal health condition e.g. disease or injuries.

Example of interpretation: One DALY: one year of health life lost due todisease or injury.

Disability adjusted Life Year (DALY) =

Year of Life Lost (YLL) + Years of Life Lost Due to Disability (YLD)

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Table 2.2: Leading Causes of Burden of Disease (DALYs) Worldwide in 2004

Disease or injury DALYs (millions) Per cent of total DALYs

World

1 Lower respiratory infections

94.5 6.2

2 Diarrhoeal diseases 72.8 4.83 Unipolar depressive disorders

65.5 4.3

4 Ischaemic heart disease 62.6 4.15 HIV/AIDS 58.5 3.86 Cerebrovascular disease 46.6 3.17 Prematurity and low birth weight 44.3 2.98 Birth asphyxia and birth trauma 41.7 2.79 Road traffic accidents 41.2 2.710 Neonatal infections and other 40.4 2.7

Source: World Health Organization (2004)

Refer to Table 2.1 to answer the following questions.Table 2.1: World Health Organization Key Measures of Health Status in Selected Countries

Health

Indicators

Malaysia Singapore Bangladesh Australia USA Japan

Life Expectancy

(Years old)

Male & Female

(2009)

71 76 79 84 64 66 80 84 76 81 80 86

Prevalence of

Tuberculosis

(Per 100 000

population)

(2009)

109 43 425 7.8 4.5 26

Infant MortalityRate

(Probability of

Dying at the age

of 1 per 1000

live birth) (2009)

6 2 41 4 7 2

Source: World Health Organization: World Health Statistics 2011http://www.who.int/gho/publications/world_health_statistics/EN_WHS2011_Full.pdf

ACTIVITY 2.1

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RESEARCH DESIGN

There are many ways to conduct research related to health psychology. Researchdesign can be classified in many ways. Let us read further.

2.2

1. Briefly explain the methods of measuring health.

2.

Define the key indicators of health below:

(a) Life expectancy;

(b) Mortality and morbidity rate; and

(c) Burden of disease.

SELF-CHECK 2.1

1. How long can a Malaysian man or woman expect to stay alive?

What about a Japanese or Australian man or woman?2. Using Life Expectancy as an indicator; which is the healthiest

country?

3. In 2009, how many cases of Tuberculosis were there in Malaysia?

4. Which country had the lowest number of Tuberculosis cases in2009?

5. Using prevalence of Tuberculosis as an indicator; which is thehealthiest country?

6.

What is the probability of your baby dying before the age of 1year old if you live in Japan? Malaysia? Bangladesh?

7. Using the infant mortality rate as an indicator; which is thehealthiest country?

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2.2.1 Classifying Research According to Examinationof Cause and Effect

Below are examples of research design classification based on the extent towhich the research measures association or cause and effect between certainphenomena.

(a) Experimental ResearchThis research examines the cause and effect relationship betweencertain phenomena or behaviour. There are factors that are manipulated(independent variables) and factors that are measured (dependentvariables). You should know four important concepts in experimental studydesign:

(i)

Pre-post test design

(ii) Treatment group and control group

(iii) Random assignment

(iv) Randomised controlled trial

Refer to Figure 2.1 for a better understanding of the flow of experimentalresearch.

Figure 2.1: The flow of experimental research

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(i) Pre-post Test DesignThis design is suitable for an interventional study. The studied variables aremeasured before (pre) and after (post) the intervention.

(ii) Treatment Group and Control GroupThe effectiveness of intervention is measured by comparing the sample ortreatment group and the control group. The treatment group is a group ofparticipants who receive the intervention, while the control group is agroup of participants who do not receive the intervention (placebo). Youcan also compare the treatment group with participants who receive othertypes of intervention. Ideally, at the beginning of a study, both groupsshould have a baseline background which is statistically the same. Youmust also consult your statistician for a suitable number of sample cases

and control cases, which often has to be more than 30.

(iii) Random AssignmentParticipants in the study are randomly assigned to ensure that anydifference between the treatment group and the control group is due tochance alone, and not due to a selection bias. If you have a pool ofparticipants from your population and randomly allocate them to either thetreatment group or the control group, this technique is called RandomisedControlled Trial (RCT).

RCT is a study in which people are allocated at random (by chance alone) toreceive one of several clinical interventions. One of these interventions isthe standard of comparison or control. The control may be a standardpractice, a placebo (sugar pill), or no intervention at all. Someone whotakes part in a randomised controlled trial (RCT) is called a participant orsubject. RCTs seek to measure and compare the outcomes after theparticipants receive the interventions. Because the outcomes are measured,RCTs are quantitative studies.

In conclusion, RCTs are quantitative, comparative, controlled experimentsin which investigators study two or more interventions in a series ofindividuals who receive them in random order. The RCT is one of thesimplest and most powerful tools in clinical research.

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(iv) Double Blind Randomised Controlled TrialsThe best way to reduce selection bias is by conducting Double BlindRandomised Controlled Trials. In this technique, both the people who

deliver the intervention (e.g. therapist or doctor) and the participants arenot aware of their grouping. In other words, both the researcher and thesubjects do not know whether they are in the treatment group or the controlgroup.

In a randomised double-blind, placebo-controlled trial of a medicaltreatment, some of the participants are given the treatment, others are givenfake treatment (placebo), and neither the researchers nor the participantsknow which is which until the study ends (they are thus both blind). Theassignment of participants to treatment or placebo is done randomly,

perhaps by flipping a coin (randomised).

(b) Descriptive ResearchThis type of research does not examine the cause and effect relationshipbetween certain phenomena. It only involves observation, recording orinterviewing and description of a phenomenon. For example; you collectthe demographic data of patients and data on the prevalence of certaindiseases.

(c) Correlational ResearchThis research does not examine the cause and effect relationshipbetweencertain phenomenon but it examines how strong the association orrelationship between one variable (e.g. age) is with other variables (e.g.effectiveness of medication).

(d) The Intervention StudyIn a controlled observational cohort study, two groups of subjects areselected from two populations that differ in only one characteristic at thestart. The groups of subjects are studied for a specific period and contrastedat the end of the study period. For instance, smokers and non-smokers arestudied for a period of 10 years, and at the end, the proportions of smokersand non-smokers that died during that period are compared. On theother hand, in an intervention study, the subjects are selected from onepopulation with a particular characteristic present; then, immediately after

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baseline, the total study group is split up into a group that receives theintervention and a group that does not receive that intervention (controlgroup). The comparison of the outcomes of the two groups at the end of the

study period is an evaluation of the intervention. For instance, smokers canbe divided into those who will be subjected to a smoking-cessationprogram and those who will not be motivated to stop smoking.Interventions have the intention to improve the condition of an individualor a group of individuals.

2.2.2 Classifying Research According to Time andDuration

Research design can also be classified according to the time and duration of thestudy. The two major types of research are Longitudinal Research and Cross-

sectional Research.

(a) Cross-sectional ResearchThis type of research involves a study in which data is gathered at only onepoint or during a specific duration of time and no follow up is required(refer to Figure 2.2). No randomisation is needed. It can be done relativelyquickly because data is all gathered at the same point in time. This type of

1. Briefly discuss the types of research according to the level ofmeasuring the cause and effect relationship between twovariables.

2.

What is experimental research? Explain the main issues in thistype of research.

SELF-CHECK 2.2

With your classmates; debate the topic below:

Should you allow the use of placebos in double blind randomisedcontrolled trials of patients with heart disease?

ACTIVITY 2.2

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Figure 2.3: The flow of longitudinal research

2.2.3 Classifying Research According to MainMethodology

Research design also can be classified according to the methodology of theresearch, i.e., Quantitative Researchand Qualitative Research. Refer to Table 2.1

below to see the differences between both types of studies.

1. Briefly discuss the types of research, classified according to timeand duration.

2. Discuss the differences between cross-sectional research andlongitudinal research.

SELF-CHECK 2.3

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Table 2.1: Differences between Qualitative Research and Quantitative Research

Qualitative Research Research Aspect Quantitative Research

Discover Ideas, withGeneral Research Objects

Common Purpose Test Hypotheses or SpecificResearch Questions

Observe and Interpret Approach Measure and Test

Unstructured. Fee Form Data Collection Approach Structured ResponseCategories Provided

Research is intimatelyinvolved. Results aresubjective

Researcher Independence Researcher uninvolvedObserver. Results areObjective

Small samples Often in

Natural setting

Samples Large Samples to Produce

Generalisable Results

(a) Qualitative ResearchThis type of study involves an in-depth exploration of subjectivevariables, e.g., attitudes, behaviours, value systems, concerns, motivations,aspirations, culture or lifestyles.

Unlike quantitative research, which tests a hypothesis, this type of researchdiscovers new ideas or creates new hypotheses itself. The data is collectedwithout structured measures. The conclusion is only valid for the studied

population and cannot be generalised to the population. Some examples ofqualitative research are phenomenology, narrative inquiry, groundedtheory and ethnography.

(b) Quantitative ResearchThis study examines objective and numerical data, for example, age, weightand height, blood concentration and amount of substance. At the beginningof your research, you have to create a hypothesis. The purpose of yourstudy is to test the significance of your hypothesis. Data is gathered in astructured manner. The number of samples has to be calculated

appropriately in order for your research to be significant enough torepresent the actual scenario that is happening in the studied population.

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ISSUES OF RELIABILITY AND VALIDITY

There are two important issues that you have to consider when selecting tools touse when conducting research in health psychology. The issues are:

(a) Reliability

(b) Validity

We will discuss these issues in the following section.

2.3.1 Reliability

Reliability is the consistency of your measurement, or the degree to which an

instrument generates the same measurement when used on the samerespondents, under the same conditions. A measure is considered reliable if therespondents score similarly on the same test given twice.

There are a few types of reliability (Refer to Figure 2.4):

Figure 2.4: Types of reliability

2.3

1. State the types of research according to general methodology.

2. Discuss the differences between quantitative research andqualitative research.

SELF-CHECK 2.4

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Lets now discuss the four types of reliability.

(a) Test Retest Reliability

Test Retest Reliability measures the reliability of the tools over time. Thetools used in your study, e.g., questionnaires or interviews, should give thesame results even if your participants do not take it at the same time. Thiscan be measured using a statistical method called Correlation Coefficient.

(b) Internal ConsistencyInternal consistency is the reliability of the tools that you use in your studyin terms of assessing the same construct at the same dimension. It showsthe correlation between each individual item score in your questionnaire,and the total score. It is measured using a statistical method called

Cronbachs alpha. The generally acceptable value for Cronbachs alpha isfrom 0.70 to 0.90.

Refer to Activity 2.3, where the construct that you have to study isdepression. If you have a questionnaire with a Cronbachs alpha of 0.98;this indicates that the questionnaire has too many items that measuredepression. On the other hand, if the value is too low, e.g. 0.48, thequestionnaire only has a few items that measure depression. In both cases,you may have to choose another questionnaire.

(c) Inter-rater ReliabilityLet us say that your study requires more than one interviewer to gatherdata from the samples. All interviewers should have standard proceduresto rate the data. The agreement between the interviewers is called inter-rater reliability. It is measured using a statistical method called CohensKappa Coefficient. The values of Kappa, according to Fleiss (1981), can beinterpreted as follows: 0.75 excellent.

Refer to Activity 2.3; you should select a few respondents to calculate theKappa value. You and the other interviewers in your study shouldadminister the same questionnaire to the same respondents separately.Then, compare your results with those of the other interviewers bycalculating the Kappa value. The Kappa value would indicate theagreement (inter-rater reliability) between you and the other team membersin your research, in terms of conducting interviews with the respondents.

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(d) Parallel Form ReliabilityThis kind of reliability is applicable to situations in which a research tool

being used can be administered in many different forms, despite measuring

the same construct, e.g., computerised questionnaires and writtenquestionnaires. Both forms of your tools should give equivalent results toone other. This is called parallel form reliability.

2.3.2 Validity

Validity is the degree to which a test measures what it claims to measure. Forexample; if your research is on depression, you should use tools that measurecomprehensively manifestation of depression.

Your tools should also be culturally friendly in order for you to get an accurateresponse. For example, if you administered a questionnaire in English torespondents who do not understand English; would your questionnaire measure

what it claims to measure? Or, in other words, is it valid? There are many typesof validity, as shown in Figure 2.5.

Figure 2.4: Various types of reliability and validity

Briefly discuss the issue of reliability. Give appropriate examples foryour discussion.

SELF-CHECK 2.5

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(a) Construct ValidityConstruct validity refers to how well a tool or questionnaire measures whatit claims to measure, and whether it reflects the true theoretical meaning of

a concept. Refer again to Activity 2.3; the questionnaire you choose shouldmeasure the construct, i.e. depression, and not other symptoms, e.g.,anxiety, or obsession.

(b) Content ValidityContent validity refers to the level of ability of a tool to measure the fullcontent of a concept that is studied. For example; your questionnaire thatmeasures level of depression has good content validity if it measures allconcepts of depression, e.g., somatic symptoms, cognitive symptoms,melancholic symptoms, atypical symptoms and other symptoms of

depression.

(c) Criterion ValidityCriterion validity is how a tool measures the intended data when comparedto a gold standard tool. This kind of validity can be divided into two:

(i) Concurrent validity

(ii) Predictive validity

(d) Concurrent ValidityConcurrent validity refers to the level of correlation between new studytools with previously validated tools in measuring a same construct. Forexample, your new questionnaire that measures level of depression hasgood concurrent validity if it measures depression with good correlationcompared to an existing validated questionnaire, e.g., the HamiltonDepression Rating Scale.

(e) Predictive ValidityPredictive validity is the level to which the tools predict the association

between the construct you are measuring and something else.

(f)

Face Validity

Face validity refers to superficial evaluation of the tool that indicates itseems to measure what it is supposed to measure. Refer to Activity 2.3.You may create your own questionnaire and ask a professional (e.g.,a psychiatrist or psychologist) to give his opinion on whether yourquestionnaire seems to measure depression.

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(g) Discriminant ValidityDiscriminant validity refers to the extent to which a tool does not measurewhat it should not measure. Refer to Activity 2.3; if you are developing a

new questionnaire for your study to measure depression, you may want toassess the discriminant validity of your questionnaire by comparing it witha questionnaire measuring anxiety.

DATA ANALYSIS AND DATA

INTERPRETATION

If you are doing quantitative research, you might want to store your data andanalyse your data systematically in a computer. You can use widely availablesoftware such as SPSS, STATA, or Excel, to do this. Before analysing your data,you should know which statistical test to choose. This is determined by the datathat you have gathered. This data can be divided into parametric and non-parametric data.

Parametric data is data that is normally distributed. If the data is parametric data,we should use a parametric test to analyse it. Non-parametric data is the datawhich is not normally distributed or skewed. If the data is non-parametric data,we should use a non-parametric test to analyse it. Table 2.2 shows someexamples of statistical tests for parametric or non-parametric.

2.4

Briefly discuss the issue of validity. Give appropriate examples foryour discussion.

SELF-CHECK 2.6

With your classmates; debate the topic below:Should you allow the use of placebos in double blind randomisedcontrolled trials of patients with heart disease?

ACTIVITY 2.3

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Table 2.2: Statistical Tests for Parametric and Non-Parametric Data

Parametric Test Non-parametric Analogue

One-sample t-test Nothing quite comparablePaired sample t-test Wilcoxon T Test

Independent samples t-test Mann-Whitney U Test

Pearsons correlation Spearmans correlation

If you are doing qualitative research, statistical analysis is generally not required.The discussion is often presented in a descriptive manner. You can use NViVO orAtlas.ti. to manage your data.

Measuring health status can be divided into measuring individual healthstatus and population health status. Both should measure all the fourimportant elements of health: physical, psychological, social and functional.

A few examples of questionnaires for the measurement of psychological andsocial functioning aspects of health are: World Health Organization (WHO)Quality of Life: WHOQOL 100 or WHOQOL-BREF, Medical Outcomes

Study (MOS) 36 Item Short Form Health Survey: SF 36 Health Survey andHealth-Related Quality of Life: HRQOL.

Population health status is measured using health indicators such as lifeexpectancy, morbidity and mortality rate, burden of disease and Disability-adjusted Life Years (DALYs).

There are various types of research design such as experimental research,descriptive research, correlational research, cross-sectional research,longitudinal research, quantitative research and qualitative research.

1. State the difference between processing and analysing data forquantitative versus qualitative research.

2. Give some examples of tests for parametric data and non-parametric data.

SELF-CHECK 2.7

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Reliability is the consistency of your measurement, or the degree to which aninstrument measures in the same respondents, the same way each time it isused and under the same conditions. Examples of reliability measures are:

test retest reliability, internal consistency, inter-rater reliability and parallelform reliability.

Validity is the degree to which a test measures what it claims to measure.

There are many types of validity: construct validity, content validity, criterionvalidity, concurrent validity, predictive validity, face validity anddiscriminant validity.

Data analysis is different between qualitative research and quantitativeresearch. In quantitative research, statistical tests are done according to type

of data, i.e. parametric and non parametric data. Qualitative research requiresno statistical analysis and is presented in a descriptive manner.

Burden of disease

Concurrent validity

Construct validity

Content validity

Correlational research

Criterion validity

Cross-sectional research

Data analysis

Descriptive research

Disability-adjusted Life Years (DALYs).

Discriminant validityExperimental research

Face validity

Health-Related Quality of Life: HRQOL

Individual health status

Internal consistency

Inter-rater reliability

Life expectancy

Longitudinal research

Morbidity and mortality rate,

Parallel form reliability

parametric and non parametricdata

Population health status.

Predictive validity

Qualitative research

Quantitative research

ReliabilitySF 36 Health Survey

Test Retest reliability,

Validity

World Health Organization (WHO)Quality of Life

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Australian Health Outcome Collaboration; Instrument Review: SF 36 HealthSurvey. Retrieved from:http://ahsri.uow.edu.au/ahoc/documents/sf36review.pdf

De Vet, Henrica, C. W.; Terwee, Caroline, B., Mokkink, Lidwine, B.; & Knol, Dirk,L. (2011). Measurement in Medicine: A Practical Guide. Cambridge:Cambridge University Press.

Health Related Quality of Life (HRQOL): CDC Center of Disease Control; Health-Related Quality of Life. Retrieved from:

http://www.cdc.gov/hrqol/methods.htm

World Health Organization Division of Mental health and Prevention ofSubstance (1999) Abuse Programme on Mental Health Measuring Qualityof Life WHOQOL; Retrieved from:http://www.who.int/mental_health/media/68.pdf

World health organization: the global burden of disease: 2004 update: retrievedfrom:http://www.who.int/healthinfo/global_burden_disease/gbd_report_2004

update_full.pdf

World health organization: world health statistics 2011. Retrieved from:http://www.who.int/gho/publications/world_health_statistics/en_whs2011_fu

ll.pdf)

06 abpg2103 topic 2

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