Explaining health and illness i

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519

British Journal of Health Psychology (2009), 14, 519–540 q 2009 The British Psychological Society

The British Psychological Society www.bpsjournals.co.uk

Lay perceptions of current and future health, the causes of illness, and the nature of recovery: Explaining health and illness in Malaysia Viren Swami1*, Adriane Arteche2, Tomas Chamorro-Premuzic2, Ismail Maakip3, Debbi Stanistreet4 and Adrian Furnham5 1

Department of Psychology, University of Westminster, London, UK Department of Psychology, Goldsmiths College, University of London, London, UK 3 School of Psychology and Social Work, University of Malaysia Sabah, Malaysia 4 Division of Public Health, University of Liverpool, Liverpool, UK 5 Department of Psychology, University College London, London, UK 2

This study examined beliefs about the causes and determinants of health, illness, and recovery in an opportunistic sample from Malaysia. In all, 371 women and 350 men completed the Health and Illness Scale, a 124-item scale that examined beliefs about current and future health, and beliefs about the causes of illness and recovery. Each of the four subscales of the Health Illness Scale were factor analysed to reveal the underlying structure. Results showed the emergence of a number of distinct factors in the case of each subscale, of which environmental, life-style, psychological, religious, and fate-related factors were fairly stable across subscales. Results also showed a number of differences in beliefs between religious groups, and that religiosity and sex were the strongest predictors of beliefs across the four subscales. The results are discussed in terms of the available cross-cultural literature on lay beliefs about health.

Lay beliefs of health and illness are conceptual models used by individuals or communities of individuals to explain health maintenance and reasons for ill-health (Helman, 1989; Kinsley, 1996). Research on lay perceptions of health and illness is well established, with work stretching back over three decades (e.g. Blaxter, 1983; Calnan, 1987; Cornwell, 1984; Crawford, 1984; Herzlich, 1973; Hughner & Kleine, 2004; Pill & Scott, 1982; Radley, 1993). This body of work has consistently shown that lay people view health and illness as something integrated into daily life, fuelling a shift away from wholly bio-medical frameworks towards more holistic understandings of health and illness (Conrad, 1990; Lawton, 2003).

* Correspondence should be addressed to Dr Viren Swami, Department of Psychology, University of Westminster, 309 Regent Street, London W1B 2UW, UK (e-mail: [email protected]). DOI:10.1348/135910708X370781


520 Viren Swami et al.

In the past several decades, research on the divergence between lay perceptions of health and illness on the one hand, and established medical orthodoxy on the other, has helped address contemporary health issues and inequalities (Popay & Williams, 1996; Popay, Williams, Thomas, & Gattrell, 1998; see also De Jong, 1980; Turner de Palma, Madey, Tillman, & Wheeler, 1999). Yet, despite the importance placed on understanding lay perceptions, relatively little work has examined how individuals relate to health and illness in different cultural contexts (but see Hughner & Kleine, 2004). This is important because, where cultures disagree about a pattern of symptoms of illness, it may lead to the development of conceptual models about health and the origin of illness that differ between cultural groups. In other words, cultural factors influence the perception, labelling, and explanation of illness (Stainton Rogers, 1991). Thus, for instance, Herzlich (1973) suggested that individuals in the West tend to seek explanations for illnesses much more than individuals in non-Western societies. Other corroborative evidence includes instances of folk understandings of illness, such as susto (or ‘fright sickness’) in South America (Goldman, Pebley, & Gragnolati, 2000) and amok (uncontrollable rage) in Southeast Asia (Kon, 1994). In addition, Eastern communities, particularly those from low socio-economic groups, appear to locate the origin of health and illness in the social (e.g. failure to observe social norms or perform essential rituals) or supernatural worlds (e.g. spirits and ghosts; Hillier & Jewell, 1983; Swami, Furnham, Kannan, & Sinniah, 2008), an occurrence quite uncommon in the West (Bra¨ndli, 1999). By contrast, Western conceptions of health and illness appear to more strongly emphasise biological concepts (e.g. genetics and heredity), particularly for mental health (Angermeyer & Matschinger, 2005; Read, Mosher, & Bentall, 2004). An additional reason why studies in different cultural settings are vital is because it may highlight instances in which poor understanding of health and illness remain dominant. For instance, general public-based studies have revealed that people do not often share the same opinions as health professionals about aspects of health and illness (e.g. effects of treatments; Link, Phelan, Bresnaham, Stueve, & Pescosolido, 1999; Priest, Vize, Roberts, Roberts, & Tylee, 1996), leading some to suggest that health and illness literacy is lacking in some circumstances. That is, some communities may explain poor health in manners that cannot be sustained by the available medical evidence, but which nevertheless exist because they form part of the conceptual knowledge of that community. Examples of poor health literacy are not difficult to come by. In one pertinent study, Jackson, Manan, Gani, and Carter (2004) showed that outpatients, medical students and staff in Kelantan, Malaysia, rationalized smoking by self-exempting beliefs. Specifically, some participants believed smoking could be made healthier by drinking water (because it cleaned or moistened the lungs and throat) or eating sour fruit (described as cleaning, and sometimes as ‘sharp,’ able to scrape out the essence of cigarettes). Such beliefs may be damaging for health, as has been described in the case of some African Americans refusing to apply pregnancy prevention methods, believing that birth control is a plot against Blacks (e.g. Bird & Bogart, 2003; Parsons, Simmons, Shinhoster, & Kilburn, 1999; Thorburn & Bogart, 2005). Clearly, then, there is a pressing need for further empirical research on lay perceptions of health and illness in different cultural contexts. To this end, the present study sought to examine lay perceptions about the causes and determinants of health, illness, and recovery based on a questionnaire developed by Stainton Rogers (1991), who used a Q-sort method to investigate what she termed ‘alternative accounts’ of health and illness. Although she reported eight distinct lay ‘theories’ of health and illness (e.g. health as a result of spiritual well-being, or the stress of modern life as a cause of disease), Furnham (1994) argued that the small sample size


Lay perceptions

521

and non-parametric methodology limited the study by Stainton Rogers (1991). In his own study with British respondents, Furnham (1994) reported similar factors emerging in relation to current and future health, the causes of illness and the nature of recovery. These included psychological or emotional well-being, the work-home interface, and life-style behaviours. Furnham (1994), therefore, argued that it was possible to reduce lay beliefs about the causes of health, illness and recovery to certain factors that mirrored the health information available to the public in the form of popular media. Continuing along the cultural vein described above, the present study sought to examine the structure of lays beliefs about the causes and determinants of health, illness and recovery in a multi-religious sample of Malaysians. Specifically, we examined these perceptions among Muslims (the majority religious group in Malaysia), Buddhists and Catholics. In general, the available evidence would suggest that, despite significant changes to the Malaysian health care system1 (e.g. Jamaiyah, 2000), many Malaysians still hold religious or superstitious beliefs about health (e.g. Jackson et al., 2004; Razali, Khan, & Hasanah, 1996). More than this, there exists some research to suggest that core differences between various religious beliefs may figure prominently in the perception of illness and recovery, as well as the methods that people use to cope with illness (e.g. Cole & Pargament, 1999; Pargament, 1997; Pargament, Smith, Koenig, & Perez, 1998). As reviewed by Miller and Thoresen (2003), however, research attempting to relate religious beliefs to various psychological phenomena has tended to be piecemeal, and where specific hypotheses about religious beliefs have been formulated, experimental designs suffer from a lack of variation in religious groups (in the West, for example, religiosity is typically conceived narrowly in terms of Protestant Christianity; Larson, Swyers, & McCullough, 1998). In the present study, therefore, the inclusion of different religious groups living within the same cultural or national context offers a significant contribution to the literature on perceptions of health, illness and recovery. Given the lack of previous research on religious differences in health beliefs, this part of the study was primarily exploratory.

Method Participants The sample comprised 721 participants (371 women, 350 men) recruited from the city of Kota Kinabalu in East Malaysia. Participants were recruited from two campus settings and reflected a mix of students and members of staff. Participant age ranged from 21 to 37 years (M ¼ 28.86, SD ¼ 2.59). Of the total sample, 69.9% were educated to a postsecondary level, and 29.0% had a university degree. Half of the sample (53.0%) were Muslims, while 18.0% was Buddhist, 15.0% Catholic, 8.3% Hindu and 4.4% Protestant. Measures Health and illness scale (Furnham, 1994; Stainton Rogers, 1991) This was a 124-item questionnaire designed to investigate explanations of responsibility and blame in health and illness. Respondents were asked to rate each item on a 7-point 1

The health care system in Malaysia is similar to that in Britain, with a government-funded public sector and a private system. Western-style medicine is dominant in both the private and public sectors, but it is still possible to visit practitioners of traditional medicine (e.g. bomohs or faith-healers), particularly in more rural localities.



scale (1 ¼ Strongly disagree, 7 ¼ Strongly agree). The questions are divided into four subscales: (1) perceptions of current state of health (27 items); (2) perceptions of ability to achieve better health in the future (31 items); (3) perceptions of whether participants will become ill or not (31 items) and; (4) perceptions of the speed and likelihood of recovery when participants are ill (35 items). The questionnaire was translated into Bahasa Malaysia (Malay) by the first author and a back-translation by an independent translator certified its validity. Demographics Participants provided their demographic details, including age, sex (1 ¼ Male, 2 ¼ Female), highest educational qualification, and religion. In addition, on a 7-point scale (1 ¼ Very religious, 7 ¼ Not at all religious), participants considered themselves quite religious (M ¼ 2.54, SD ¼ 1.62) and on a 5-point scale (1 ¼ Very health, 5 ¼ Very unhealthy) they considered themselves relatively healthy (M ¼ 2.45, SD ¼ 1.06; henceforth referred to as global health). Procedure All participants were recruited opportunistically by the authors of this study. In practice, this meant approaching participants on campus sites and soliciting voluntary participation. Recruitment of participants continued until the experimenters deemed the sample to be of sufficiently large size. All participants took part on a voluntary basis and were not remunerated for participation. Participants completed the questionnaires in view of the experimenters and returned the questionnaire after completion. Completion of the questionnaire took approximately 20 min and participants were debriefed following the experiment. Analyses Factor analysis and descriptive statistics were initially computed for each of the four subscales. Correlational and regression analyses were then carried out to assess the extent to which demographic variables predicted scores on each subscale. Finally, analyses of variance (ANOVAs) were run in order to test subscale means among different religious groups.

Results Preliminary analysis Data reduction was carried out via Principal Component Analyses (PCA) followed by Promax rotation. The aim was to test the underlying structure of each of the four subscales of the Health and Illness Scale (see Tables 1–4). Scree plot tests and Eigenvalues were used to identify the relevant components, and the communality cutoff point for inclusion of an item was 0.30. Although there are no objective criteria for determining the cut-off point of the factor loadings in factor analyses, it is common practice in psychological research to interpret values of 0.30 or larger as relevant. However, the importance of factor loadings is largely determined by the sample size (Stevens, 1992 widely adopted table of critical values recommends a cut-off point of 0.30 for samples over more than 300 people). Items with cross-loadings . 0.30 were used to compute only the factor that was deemed theoretically relevant.

Work-Home Interface The circumstances of my home life My working environment My home environment The current circumstances at work

Societal Factors

The society in which we live in Malaysia The culture within which I live My relationship with friends and family

Lifestyle

My overall lifestyle Everyday behaviour (e.g. getting enough sleep; eating regularly) Taking good care of myself Whether or not I’m actively taking action to be healthy

Whether I feel ‘on the top’ of my life, or pressured by it

Emotional well-being

Inner forces of my psyche My emotions My state of mind

Environment

Whether or not I am being exposed to certain substances Whether or not I have been exposed to infectious organisms The weather God or some other supernatural power

(1) 23 22 21 24

(2)

13 14 16

(3)

8 7 9 10

6

(4)

5 4 3

(5)

26 20 15 19

Eigenvalue 2.47 [1.57]




Eigenvalue 3.50 [4.70]a

.72 .70 .64 .42

Variance 5.82

.75 .73 .68 [.35 on factor 7]

Variance 6.19

.79 .77 .67 .46 [.39 on factor 8]c .42 [.36 on factor 4] [.32 on factor 6]

Variance 7.24

.78 .66 .66

Variance 9.93

Varianceb 17.40% .84 .83 .77 .73

5.04(1.00)

4.76(1.05)

5.64(0.78)

4.21(1.15)

4.56(1.14)

M(SD)

Table 1. Means, standard deviations, and factor loadings of the items related to the question, ‘My current state of health is due to’

.51

.69

.67

.69

.81

Cronbach’s alpha (a)

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Lay perceptions 523

Whether there is somebody ill wishing me or not Good or bad luck Particular events in my life at this time Simple probability

Constitution

My age The constitution with which I was born My body’s natural defences

Medical care The care of medical professionals

18 11 25 12

(7)

27 1 2

(8) 17




Variance 4.37 .80

.72 .66 .48 [.53 on factor 4]

Variance 4.65

.79 .56 .40 .35 [.46 on factor 2]

Variance 5.34

4.40(1.53)

4.33(1.00)

3.58(0.94)

M(SD)

.39

.51


Notes. a Values in brackets represent eigenvalues for the unrotated matrix; b Explained variance for the unrotated matrix; c Values in brackets show cross-loadings.

Fate

(6)

Table 1. (Continued)




Environmental Factors Improvements in my circumstances at home Improvements in the circumstances in which I work Improvements in my working environment Improvements in my home environment

Medical Treatment

Getting advice from my doctor or health visitor Getting advice from a practitioner of alternative medicine Getting medical treatment Seeking out preventive medical services My age

Social Support

Getting advice from friends and family Getting advice from books or leaflets Improvements in my relationships with family and friends

Being Positive

Promoting a positive attitude Actively seeking out things that make me happy Actively changing to a healthier life style

Constitution

My current state of health Marshalling my body’s own strengths The constitution with which I was born

(1) 54 55 53 52

(2)

45 46 47 44 48

(3)

42 43 41

(4)

31 32 36

(5)

29 30 28






.80 .79 .61

Variance 5.23%

.81 .80 .34 [.50 on factor 9]c [ 2 .30 on factor 11]

Variance 6.01%

.85 .84 .59

Variance 7.06%

.97 .90 .61 .48 .41

Variance 8.52%

Varianceb 19.64% .91 .85 .82 .72

4.46(0.98)

5.83(0.85)

5.09(1.03)

5.38(0.90)

4.70(1.23)

M(SD)

.55

.66

.75

.74

.86


Table 2. Means, standard deviations and factor loadings of items related to the question ‘My capacity to become healthier in the future is due to’



Lay perceptions 525

Whether or not I am exposed to certain substances Whether or not I am exposed to infectious organisms Particular events – what happens in the future

Psychological factors

Taking charge of, and responsibility for, my own life Tackling any unresolved inner conflicts

Fate

Good or bad luck Simple probability

Self-medication

Changing my day to day behaviour Giving up unhealthy habits Takings vitamins or a tonic

Religious Factors

God’s power of influence Any other supernatural influence

Weather The weather

57 51 56

(7)

34 33

(8)

39 40

(9)

35 37 58

(10)

49 50

(11) 38







Variance 3.24% .92

.95 .42

Variance 3.36%

.89 .47 .44 [.41 on factor 6]

Variance 3.77%

.94 .81

Variance 3.94%

.86 .81

Variance 4.42%

.85 .71 .42

Variance 4.59%

4.90(1.53)

4.29(1.39)

5.50(0.92)

3.53(1.18)

5.03(1.05)

5.01(1.10)

M(SD)

.34

.43

.62

.74

.55


Notes. a Values in brackets represent eigenvalues for the unrotated matrix; b Explained variance for the unrotated matrix; cValues in brackets show cross-loadings.

Exposure to Organisms

(6)





Living in a poor environment Stressful, nasty or unsettling events in my life

Stress If my state of mind becomes negative Feeling unhappy Inner conflicts in my psyche making themselves felt

Lifestyle Adopting a life style that is unhealthy Behaving in stupid ways If my body’s own natural defences become weakened or break down Exposure to harmful chemicals

Fate Bad luck Simple probability Other supernatural influence A curse or ill-wishing

Something at home or work that I can avoid being ill

Poor treatment The ill-effects of poor medical treatment Lack of proper medical care Uncaring or unsympathetic treatment

78 82

(2) 61 62 63

(3) 65 64 60

(4) 66 67 74 75

76

(5) 71 70 72

84

Environment Stressful conditions at home Stressful conditions at work Working in a poor environment

(1) 80 81 79






Variance 5.16% .95 .92 .59

Variance 5.28% .90 .77 .69 .60 [2 .31 on factor 3] .34

Variance 8.33% .96 .92 .44 [2 .36 on factor 6] .32 [.35 on factor 9]

Variance 11.23% .91 .85 .69

Varianceb 20.23% .99 .93 .62 [.31 on factor 7]c .44 .43

4.74(0.98)

3.48(1.02)

5.59(0.99)

4.73(1.17)

4.83(1.09)

M(SD)

Table 3. Means, standard deviations and factor loadings of the items related to the question ‘Whether or not I become ill is due to’

.61

.70

.71

.82

.78




Lay perceptions 527

Conflicts Rows or conflicts with family or friends Rows with people at work

Exposure The weather The constitution with which I was born

The virulence of infective organisms Whether or not I have been exposed to infectious organisms

Life Events Other people’s stupid actions Major pleasant life changes

Uncontrollable Events God’s will My age

(6) 68 69

(7) 88 59

87 77

(8) 85 83

(9) 73 89

Eigenvalue 1.58 1.04]




Variance 3.36% .79 .43 [.57 on factor 7] [.31 on factor 8]

Variance 3.81% .86 .58

Variance 4.09% .90 .79 [.34 on factor 8] .61 .31

.31 [.37 on factor 8] [2 .42 on factor 6] Variance 4.23% .91 .80

4.79(1.45)

3.92(1.42)

4.92(0.92)

3.55(1.37)

M(SD)

.45

.53

.57

.87



In built weakness or susceptibility to particular diseases

86





Psychological Factors Finding ways to make myself feel happier. Finding ways to resolve any inner conflicts. Taking responsibility for myself, and doing all I can to get better. Thinking positively and seeing the illness as challenge. Getting ‘back to normal’ as soon as possible. Looking after myself and taking things easy.

Lifestyle Actively taking steps to make my lifestyle healthier. Giving up unhealthy habits. Being careful about my day-to-day behaviour. An environment, which is conductive to recovery.

Recovery Factors Taking drugs or medicines that are effective. My body’s own natural defenses. Treatments (e.g. surgery, radiotherapy) that are effective. My body’s own natural defenses. Particular events in my life at time. The constitution with which I was born.

Fate Good luck. A curse of ill-wishing.

Simple probability.

118 90 94

(2) 96 97 95 110

(3) 113 117 114 117 112 116

(4) 98 104

99

(1) 91 92 93





Variance 5.16% .84 .63 [.55 on factor 9] .68

Variance 6.79% .71 .70 .69 .70 .59 .47 [2 .41 on factor 5] [.30 on factor 7]

Variance 10.09% .90 .77 .60 .33 [.62 on factor 6]c

.62 .50 .36

Varianceb 18.26% .96 .92 .54

3.44(1.13)

5.00(0.85)

5.65(0.95)

5.29(0.81)

M(SD)

.63

.62

.67

.77


Table 4. Means, standard deviations, and factor loadings of the items related to the question ‘When I am ill, how quickly and effectively I recover is due to’



Lay perceptions 529

Seeking medical advice soon enough – not waiting until the illness becomes too serious before I go to the doctor. ‘Alternative’ therapies, if I sought them out.

Conventional Treatment The quality of any conventional medical treatment. Circumstances which are conductive to recovery. The sympathy and understanding of my nurse/doctor.

Care received The care I got from my family and friends. The quality of medical treatment I got.

Religious Factors Prayers said to me. God’s will.

Supernatural Power The virulence of the disease itself. Some other supernatural power. The intervention of a spiritual healer or healers.

Understanding Just the chance to talk things over with the doctor without any treatment.

121

(6) 103 111 102

(7) 100 101

(8) 106 107

(9) 109 108 105

(10) 122







Variance 3.24% .97

Variance 3.44% .82 .52 .55 [.33 on factor 4]

Variance 3.63% .81 .78

Variance 4.02% .87 .69 [.49 on factor 6]

.39 [.34 on factor 3] Variance 4.38% .73 .62 .55

.81 [2.40 on factor 7] .59

Variance 4.85% .83

3.16(1.71)

3.48(1.20)

5.13(1.66)

5.37(1.03)

4.92(0.99)

5.12(1.01)

M(SD)

.57

.70

.66

.56

.56



115

120

Seek Medical treatment Following ‘doctor’s orders’ – complying properly with the treatment I am given. Letting nature take its course.

(5) 119






Lay perceptions

531

For the Perceptions of current state of health subscale, eight factors emerged and accounted for 60.97% of the variance. The first three factors (named Work–Home Interface; Societal Factors, and Lifestyle) accounted for most of the variance (34.6%). Item 17 (‘The care of medical professionals’) was kept as a single item in the last factor once its correlation with the other factors was confirmed as being very low. Except for Fate-Lifestyle and for Constitution–Environment, all other components were significantly correlated (ranging from r ¼ .07, p , .05, to r ¼ .33, p , .001). Analysis of the Perceptions of future state of health subscale showed that 11 factors emerged from the factor analysis, which together explained 69.8% of the variance. Again, one item (Item 38, ‘The weather’) was kept alone in the last factor. Significant intercorrelations were observed among the majority of the factors and ranged between r ¼ .07 ( p , .05) and r ¼ .38 ( p , .001). Fate was the weakest correlated component, being only significantly associated with Psychological Factors (r ¼ .07, p , .05). Regarding the Perceptions of whether one becomes ill or not subscale, exploratory factor analysis showed a nine-factor underlying structure, which explained 65.70% of the variance. The factors were clearly identified and the first component to emerge was related to Environmental items (accounting for 20% of the variance). Apart from FateLifestyle and Conflicts-Lifestyle, all components were significantly correlated (r ¼ 2.08, p , .05, to r ¼ .42, p , .001). Finally, results of the Perceptions of the speed and likelihood of recovery subscale showed 10 emerged factors (with one item kept alone in the last factor), which accounted for 63.09% of the variance. The components were significantly correlated between r ¼ 2.07 ( p , .05) and r ¼ .45 ( p , .001); (except for Supernatural-Psychological Factors and Care Received-Fate which were not significantly associated). Means, standard deviations and internal consistency (Cronbach’s alpha) were computed for each subscale see Tables 1–4). Given its low correlations with the other items, the three single-item factors were excluded from further analysis.

Explanations of illness and health and demographic variables A series of bivariate correlations were performed in order to investigate the relationship between lay perceptions and demographic variables (sex, age, education, global health, and religiosity). Religiosity was significantly associated with 18 of total of 35 tested factors, sex and health were significantly correlated with 12 factors, education was a significant correlate of 8 factors and age was a significant correlate of 6 factors (see Table 5). Based on the correlational table, a series of multiple hierarchical regressions were then performed, regressing significant demographic variable correlates (i.e. age, sex, education, religiosity, and global health) on to each factor. A significance level of p , .01 was applied in order to control for Type 1 errors. Religiosity was a major predictor, being significant for 13 factors. Sex was an important predictor on 8 factors, while global health was a significant predictor of 5 factors (see Table 6). The majority of the tested models (24 out of 30) were significant; however, the low explained variance (ranging from 1 to 8%) suggests that the present variables were not strong predictors of beliefs about health, illness and recovery.

Explanations of illness and health, and religion Factor scores were computed by taking the mean of items related to each factor. ANOVAs were then performed in order to test for differences in beliefs about the causes and determinants of illness and recovery between different religious groups.


532 Viren Swami et al. Table 5. Correlations between subscales and demographic variables Sex A. My current state of health is 1. Work- home interface 2. Societal factors 3. Lifestyle 4. Emotional well-being 5. Environment 6. Fate 7. Constitution

due to: : : 2 .01 .17** 2 .06 .01 2 .01 2 .07* 2 .02

Age

.08* 2.01 2.05 .17** 2.01 .04 .05

Education

.15** 2 .01 2 .01 .13* .04 .01 2 .05

Health

Religiosity

.09* .02 2 .15** 2 .08* .02 .02 2 .16**

.15** 2.08* 2.00 2.04 2.17** 2.07 2.03

.05 .01 2 .02 2 .03 2 .05 .06 .02 2 .06 .03 2 .09*

.06 .01 2.05 2.07 .00 .09* 2.11** 2.05 .11** 2.23**

2 .00 .10** .10** .01 .05 .02 .05 2 .03 2 .03

.05 .02 2 .04 2 .06 .17** .07* .04 2 .10** 2 .04

.13** 2.01 .13** 2.05 2.01 .01 .14** 2.08** 2.11**

D. When I’m ill, how quickly and effectively I recover is due to: : : 1. Psychological factors 2 .05 .05 2 .09* 2. Lifestyle .13** 2.01 .05 3. Recovery factors 2 .03 2.07 2 .01 4. Fate 2 .02 .03 .03 5. Seek medical treat. .14** 2.05 .01 6. Conventional treat. 2 .04 2.06 .08* 7. Care received .09* 2.06 .04 8. Religious factors .03 .05 .08* 9. Supernatural power 2 .05 .04 .10**

2 .13** 2 .03 .01 2 .20** .10** .01 .11** .05 2 .07

2.03 .01 .09* 2.22** .13** .03 .14** 2.27** 2.08*

B. My capacity to become healthier in the future is due to: : : 1. Environmental factors .00 .07 .07 2. Medical treatment .01 2.04 2 .01 3. Social support .13** .05 .04 4. Being positive .04 .06 .05 5. Constitution .06 2.00 .00 6. Exposure to organism 2 .01 .11** .03 7. Psychological factors .00 2.02 2 .03 8. Fate 2 .03 2.01 2 .03 9. Self-medication .11** .01 .02 10. Religious factors 2 .02 .07 .01 C. Whether or not I become ill 1. Environment 2. Stress 3. Lifestyle 4. Fate 5. Poor treatment 6. Conflicts 7. Exposure 8. Life events 9. Uncontrollable events

is due to: : : .06 .02 .10** 2 .07* 2 .16** 2 .14** .02 2 .00 2 .09*

.03 .11** .10** .01 .03 2.06 .09* 2.04 .07

Note. N ¼ 721; *p , .05; ** p , .01.

Participants were divided in three groups: Muslims, Buddhists and Catholics. Other religions were not included in the analysis, as the number of participants was small. Significant differences ( p , .01) were observed on 17 factors (see Table 7). There were few significant differences between religious groups on the Perceptions of current health subscale, with only two factors showing significant differences (Muslims had the highest scores on Environment and the lowest scores on Work-Home Interface).

B(SD)

C. Whether or not I become ill is due to: : : EN –– –– ST –– .03(.02) LS .20(.07) .10* .02(.01) FA 2 .15(.07) 2 .07 –– PT 2 .31(.07) 2 .16* –– CF 2 .37(.10) 2 .13* –– EX –– .03(.01) LE –– –– UN 2 .29(.10) 2 .10* ––

.08

–– .14(.11) .14(.09) –– –– –– –– –– ––

.13(.09) –– ––

.13*

.07 .05

.33(.10) ––

.01

.05 .06

.06

.13*

b

2 .11(.05)

.15(.03) .09(.04)

2 .11(.02) 2 .08(.03)

.03(.04)

B(SD)

2 .04(.04)

b

––

––

–– –– –– ––

–– –– –– ––

–– ––

––

Health

B. My capacity to become healthier in the future is due to: : : SS .27(.07) .13* –– –– EX –– .04(.01) .10* –– PSY –– –– –– SM .21(.06) .11* –– –– REL –– –– ––

B(SD)

Education

2 .15(.03)

b

Age

A. My current state of health is due to: : : WH –– .01(.01) SF .40(.08) .17* –– LS –– –– EWB –– .05(.01) EN –– –– FA 2 .14(.07) 2 .07 –– CS –– ––

B(SD)

Sex

2 .09

.16* .07

2 .03

2 .16*

2 .15* 2 .08

.03

b B(SD)

Religiosity

.08(.02) –– .08(.02) –– –– –– .07(.02) 2.04(.03) 2.10(.03)

–– .06(.02) 2.07(.02) .06(.02) 2.19(.03)

.09(.02) 2.05(.02) –– 2.01(.02) 2.10(.02) –– ––

Table 6. Regression of demographic and psychological factors on to subscales of the Health and Illness Scale

.13* 2 .05 2 .11**

.13*

.12*

.08* 2 .11* .11* 2 .22*

2 .02 2 .17*

.13* 2 .07

b

12.21* 5.28 7.75* 4.09 20.53* 8.96* 9.58* 4.80 8.48*

12.94* 7.14* 9.10* 9.63* 20.59*

8.16* 14.13* 16.66* 7.35* 21.73* 4.01 20.18*

F

.12 .12 .20 .07 .23 .15 .16 .11 .15

.13 .14 .11 .16 .23

.20 .19 .15 .19 .17 .07 .16

R

.01 .01 .03 .01 .05 .02 .02 .01 .02

.01 .01 .01 .02 .05

.03 .03 .02 .03 .02 .01 .02

DR2



Lay perceptions 533

b

B(SD)

Age

b B(SD)

b

.07(.03)

2 .16(.04) .07(.03)

2 .09(.02)

B(SD)

–– ––

––

–– ––

Health

.07

2.15* .07

2.12*

b –– –– .04(.02) 2 .12(.02) .07(.02) –– .08(.02) 2 .28(.03) 2 .06(.02)

B(SD)

Religiosity

.12* 2 .27* 2 .08

.08 2 .17* .11*

b 8.37* 11.75* 5.37 26.13* 10.19* 4.16 8.77* 32.47* 6.57*

F .15 .12 .08 .26 .20 .07 .18 .28 .13

R .02 .01 .01 .06 .03 .01 .03 .08 .01

DR2

Note. *p , .01. The dashed lines indicate variables that were not included in the model due to its non-significant correlation with the target factor. Abbreviations. WH ¼ Work-home interface; SF ¼ Social factors; LS ¼ Life style; EWB ¼ Emotional well-being; EN ¼ Environment; FA ¼ Fate; CS ¼ Constitution; SS ¼ Social support; EX ¼ Exposure; Psy ¼ Psychological factors; SM ¼ Self medicine; Rel ¼ Religious factors; ST ¼ Stress; PT ¼ Poor treatment; CF ¼ Conflict; LE ¼ Life events; UN ¼ Uncontrollable events; RE ¼ Recovery; SM ¼ Seek medical treatment; CT ¼ Conventional treatment; CR ¼ Care received; SN ¼ Supernatural.

.09* .10*

.07

2.08

Education

D. When I’m ill, how quickly and effectively I recover is due to: : : PSY –– –– 2 .14(.06) LS .24(.07) .12* –– –– RE –– –– –– FA –– –– –– SM .28(.07) .14* –– –– CT –– –– .15(.07) CR .18(.07) .09 –– –– REL –– –– .32(.12) SN –– –– .26(.09)

B(SD)

Sex






Lay perceptions

535

Table 7. ANOVAs comparing health and illness beliefs between religious groups Religion Muslim n ¼ 387 M(SD) A. My current state of health is due to: : : Work-Home 4.45 Environment 5.21

Catholic n ¼ 112 M(SD)

4.61 4.87

Buddhist n ¼ 130 M(SD)

ANOVA df (2, 627) F

4.80 4.73

4.82* 13.76*

B. My capacity to become healthier in the future is due to: : : Environment 4.52 4.87 Social Support 5.04 5.37 Psychological Factors 5.07 5.30 Religious 4.59 4.38

5.04 4.86 4.72 3.29

10.91* 7.95* 10.39* 49.32*

C. Whether or not I become ill is due to: : : Environment 4.64 Stress 4.56 Fate 3.50 Conflicts 3.45 Exposure 4.98 Life Events 3.75 Uncontrollable 5.07

5.08 4.93 3.30 3.33 5.00 3.80 3.91

11.59* 7.74* 4.27* 8.15* 4.86* 9.53* 35.37*

5.12 3.16 3.68 3.17

7.51* 5.12* 75.42* 6.93*

5.07 4.94 3.67 3.97 4.68 4.41 4.60

D. When I’m ill, how quickly and effectively I recover is due to: : : Psychological Factors 5.30 5.52 Fate 3.51 3.34 Religious 5.56 4.92 Supernatural 3.59 3.67 Note. *p , .01

More religious differences were observed on the Perceptions of future state of health subscale and on the Perceptions of the speed and likelihood of recovery subscale. On the former, Buddhists had the highest means on Environment and the lowest means on Religious, whilst Catholic participants had the highest means on Social Support and Psychological Factors. On the latter, Catholics had the highest scores on Psychological Factors and Supernatural Events, while Muslims had the highest scores on Fate and Religious. Finally, the largest religious difference was observed on the Perceptions of whether one becomes ill subscale, with significant differences being observed on seven factors. Muslims had the lowest scores in Environment, Stress and Life Events, but had the highest means in Uncontrollable Events.

Discussion This is the first study to systematically investigate the structure of lay beliefs among Malaysians about current and future health, the causes of illness and the nature of recovery. The first important finding of this study is that, although the four subscales of the Health and Illness Scale measured distinct aspects of health beliefs, there were nevertheless similarities in the four factor structures that emerged. Specifically, a



number of factors were common across subscales, particularly environmental and exposure factors, life-style factors, psychological factors and positive emotion, and, importantly, fate and religious factors. This would seem to suggest that the perceptions about the causes and determinants of health, illness and recovery examined in the present study are both related and multidimensional (Furnham, 1994). In general terms, the factors observed in the present study were similar to those reported by Furnham (1994) in his study with a British sample. That is, like their Malaysian counterparts, Britons appear to believe that the causes of health, illness and recovery are related to specific factors, such as psychological temperament, the quality and quantity of medical treatment, work and home environments, societal and cultural factors, and fate and religious aspects. These findings are consistent with similar studies that have examined the lay perceptions of health in the West (e.g. Furnham & Smith, 1988; Helman, 1989). Although direct comparisons should be applied with caution, given the lack of a suitable comparison group in the present study, our results nevertheless suggest that the overall structure of lay beliefs about the causes of health, illness and recovery may be similar among Malaysians and their counterparts in the West. It is possible to argue, therefore, that in Malaysia, as in the West, individuals hold quite robust beliefs about health that may transfer across domains. That is, regardless of whether beliefs about health, illness, or recovery are considered, it would appear that a similar explanatory framework is sufficient to understand such beliefs. Put differently, the present results suggest a degree of generalisability in the structure of health beliefs, both across domains as well as between studies. Of course, it should also be noted that the relative similarity in factor structures in Malaysia and the West may stem from the fact that the present sample were relatively well-educated members of Malaysian society. They may have, therefore, been exposed to, and assimilated common knowledge structures about health and well-being. Even so, it is important to note that, although the overall structure of beliefs in the present study may have been similar to that reported by Furnham (1994), there were notable differences in the importance placed on each factor. Of particular interest, social and environmental factors appeared to explain the greatest amount of variance in the present study for perceptions of the causes of current and future health, respectively. Overall, these results corroborate previous studies suggesting that Eastern communities tend to perceive the social world as being an important cause of health and illness (e.g. Hillier & Jewell, 1983; Swami et al., 2008). Moreover, for beliefs about the causes of illness, it can be seen from Table 1 that medical care explained the least amount of variance, which contrasts with perceptions of health and illness in the West that emphasise biological concepts and medical treatment (e.g. Furnham, 1994; Read et al., 2004). It is also important to note the model of causes of illness reported here and elsewhere (Furnham, 1994; Stainton Rogers, 1991) may not be entirely consistent with other theoretical frameworks that have considered lay representations of illness. For example, some work based on the Self Regulatory Model suggests that cognitive illness representations are organized around five dimensions, namely identity (symptoms associated with the illness), time line (beliefs about the duration of the illness), consequences (beliefs about the effects), control and cure (beliefs about controllability and recover) and cause (perceived causes of an illness) (Leventhal et al., 1997; see also Moss-Morris et al., 2002; Weinman, Petrie, Moss-Morris, & Horne, 1996). Of course, these variations may reflect different emphases between scales (e.g. compared with the


Lay perceptions

537

Health and Illness Scale, the Illness Perception Questionnaire used to examine Leventhal et al.’s five dimensions more directly measures the cognitive component of health beliefs), but it nevertheless highlights issues relating to the nature and structure of health beliefs as uncovered by different research groups. In our regression analyses, there were a number of consistent predictors of lay beliefs about the causes of health, illness and recovery. For instance, stronger religious beliefs were related with stronger fatalistic and religious health related-beliefs, but weaker belief in the environment and life-style as a cause of illness. Similarly, women showed stronger beliefs that social factors and social support were causes of current and future health, which may mirror prescriptive gendered norms for women in Malaysia. That is, ‘emphasized femininity’ (Connell & Messerschmidt, 2005) within the Malaysian context may lead to a set of beliefs about the causes of health and illness, which in turn may be related to women’s health behaviour. By contrast, our results also revealed that some variables rarely significantly predicted health beliefs. This included education and age, which may reflect the rather constricted nature of our sample (see limitations below). In the present study, we were also able to examine differences in health perceptions between different religious groups. The results of this analysis suggested that there were a number of significant differences between Muslims, Catholics, and Buddhists, although there did not appear to be any clear pattern in the direction of these differences (see Table 7). For example, compared with Buddhists and Catholics, Muslims were more likely to believe that their current was caused by environmental factors, but least likely to believe that environmental factors affected their future health. What could explain this seemingly ambiguous pattern of results? The most likely possibility is that, to the extent that religious differences in health beliefs do exist, they appear to be quite small. Indeed, in the present study, it might be suggested that the significant differences by religion were a result of an artifact of the statistical design or large sample size. However, this is unlikely to be a complete explanation of the present results. For one thing, it can be seen from Table 7 that Muslim participants consistently have the highest scores to religious factors and fate. Muslims were also more likely than Buddhists or Catholics to believe that their likelihood of becoming ill was uncontrollable and the recovery was partly caused by supernatural agents. Such beliefs, if they truly are systematic, may have a detrimental effect on health behaviours. For instance, religious beliefs may prevent participants who believe that illnesses are uncontrollable from seeking or complying with medical treatment, or may encourage them to rely on faith or traditional medicine rather than modern medical care (for a review, see Koenig, McCullough, & Larson, 2000). For the moment, these conjectures remain speculative, and it would be useful for future studies to examine in more detail possible ethnic or religious differences in lay perceptions of health. In terms of limitations, it should be noted that, despite the relatively large sample size of the present study, the participants were recruited opportunistically and, therefore, cannot be considered representative of Malaysians more generally. For instance, our opportunistic sample may over represent well-educated and young participants, and of course our participants were all recruited from a campus setting. It would be useful, therefore, to replicate this study in other settings in Malaysia, such as among Malaysians of low socio-economic status or from rural backgrounds. In such contexts, the importance of religious factors and fate may be more pronounced than in the present study. An additional limitation was the present study’s reliance on the Health and Illness



Scale, which was developed by Stainton Rogers (1991) almost two decades ago. Certainly, the study of lay beliefs around health appears to be limited by a lack of validated and reliable scales (but see Moss-Morris et al., 2002; Weinman et al., 1996) and this study was no exception to this limitation. In future work, it would be useful to develop scales that are more adept at exploring local beliefs, in conjunction with the collection of other relevant demographics such as socio-economic status. The latter could be measured based on such items as annual income, which would allow for a more direct test of socio-economic differences health belief (as opposed to using proxies of socio-economic status such as education). Finally, future work could also improve on the present design by examining cross-cultural differences in health beliefs more systematically. This could be achieved, for instance, by replicating the present study on two representative and comparable cross-cultural samples (e.g. Easterners vs. Westerners), as this would provide for a better understanding of cultural differences in beliefs about health, illness, and recovery. These limitations aside, the present study documents evidence for fairly robust beliefs about current and future health, and causes of illness and recovery, among a sample of Malaysians. The present findings may prove useful for understanding the way in which different cultural groups understand and assimilate the growing body of knowledge relating to health. Certainly, much work remains to be done in this area, but this study provides a useful point of departure for future work examining lay perceptions of health in different cultures.

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