Unit for Social and Community Psychiatry, Barts and the London School of Medicine, London
Correspondence: Rosemarie McCabe, Unit for Social and Community Psychiatry, Barts and the London School of Medicine, Newham Centre for Mental Health, London E13 8SP, UK. Tel: +44 (0)20 7540 2296; Fax: +44 (0)20 7540 2976; e-mail: r.mccabe{at}qmul.ac.uk
Declaration of interest None. Funding detailed in Acknowledgements.
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ABSTRACT |
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Aims To compare explanatory models among people with schizophrenia from four cultural backgrounds and explore their relationship with clinical and psychological characteristics.
Method Explanatory models, insight, treatment compliance, health locus of control, quality of life, treatment satisfaction, therapeutic relationships and symptomatology were assessed in UK Whites and Bangladeshis, AfricanCaribbeans and West Africans.
Results When biological and supernatural causes of illness were compared, Whites cited biological causes more frequently than the three non-White groups, who cited supernatural causes more frequently. When biological and social causes were compared, Whites cited biological causes more frequently than AfricanCaribbeans and Bangladeshis, who cited social causes more frequently. A biological explanatory model was related to enhanced treatment satisfaction and therapeutic relationships but not treatment compliance.
Conclusions Explanatory models of illness contribute to patient satisfaction with treatment and relationships with clinicians.
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INTRODUCTION |
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METHOD |
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The four groups were of AfricanCaribbean, Bangladeshi, West African and UK White origin. Second-generation patients were selected because: there are consistent differences in service use and outcome among this group; the findings would be less confounded by individual histories of migration and schooling because all interviewees have grown up in the same educational system and background culture; all interviews could be conducted in English because this is most relevant for clinical practice; and the material could be elicited in English and analysed without considering specific connotations in different languages. The inclusion criteria were selected to reduce the heterogeneity of the groups and increase the possibility of detecting specific differences despite relatively small sample sizes for each ethnic group.
Sample
The sample consisted of four groups of out-patients from four distinct
cultural backgrounds aged between 18 and 48 years who met DSMIV
(American Psychiatric Association,
1994) criteria for a diagnosis of schizophrenia, were in the care
of a community mental health team, had no known organic impairment and had no
significant formal thought disorder as assessed on the Brief Psychiatric
Rating Scale (BPRS; Overall & Gorham,
1962). The four groups were recruited in East London and the three
groups of non-UK origin were all second-generation immigrants. Patients were
identified as second generation if they were either born in the UK with both
parents of the specified origin or moved to the UK before the age of 12 years.
Participants were included when clinical and self-report of ethnicity were in
full agreement. In accordance with the central limit theorem, 30 participants
per group were recruited so that the mean could be approximated closely by the
normal distribution (Mukhopadhyay,
2000). Samples A, B and C comprised individuals of
second-generation AfricanCaribbean, Bangladeshi and West African (from
Nigeria or Ghana) ethnic origin. Sample D consisted of White English
participants, all born in the UK.
Participants were recruited from secondary mental health services (i.e. four community mental health teams, a day hospital and a psychology service). Service managers, psychiatrists and support workers were consulted to identify those clients meeting the inclusion criteria. Diagnosis was clinical rather than derived from case notes. On clinicians recommendations, patients were contacted by letter, telephone or in person at clinics according to the individual patients preferences and circumstances. All participants provided written informed consent to take part in the study.
Measures
A modified version of the Short Explanatory Model Interview (SEMI;
Lloyd et al, 1998)
enabled a qualitative assessment of patients conceptualisations of
their illness within a structured framework that allowed for eventual
quantification of data. Questions originally developed for use in primary care
that were not relevant for people with chronic illness were omitted from the
scale. The modified version was divided into three sections on the nature of
the problem and its consequences, aetiology and treatment. Each patient
interview was audio-recorded and transcribed.
Psychopathology was observer rated using the 24-item version of the BPRS (Overall & Gorham, 1962). Patient insight into their illness was observer rated using the Schedule for Assessment of Insight into Psychosis (SAI; David et al, 1992), which has three sub-scales: treatment compliance, awareness of illness and relabelling of symptoms. Ratings were based on information from the patient and additional information from the keyworker. Quality of life was self-rated with the Manchester Short Assessment of Quality of Life (MANSA; Priebe et al, 1999). A modified version of the Helping Alliance Scale (HAS; Priebe & Gruyters, 1993) was self-rated by the patient who assessed their primary therapeutic relationship, typically with their keyworker. Treatment satisfaction was self-rated using the Patient Care Satisfaction Questionnaire (PCSQ; Barker et al, 1996). Finally, health locus of control was self-rated with the Health Locus of Control scale (HLC; Wallston et al, 1976), which has three sub-scales: external locus of control, internal locus of control and powerful others. Unless otherwise stated, mean scores for each measure are reported and were used in data analyses. For all of the scales, a higher score indicates greater presence of the construct, with the exception of the PCSQ where a higher score indicates greater treatment dissatisfaction.
Data analysis
The qualitative data collected using the SMI were content analysed and
coded into categories a posteriori. Responses to the question
What do you think has caused your problem were initially coded
into ten categories derived from the content analysis: do not know;
drugs/alcohol/medication; interpersonal problems; supernatural causes; mental
illness; physical illness/trauma; personality; stress; negative childhood
events; and other. Given the small cell counts, these categories were then
collapsed to form four categories: biological (physical illness/substance
misuse); social (interpersonal problems/stress/negative childhood
events/personality); supernatural (supernatural); and non-specific (do not
know/mental illness/other). Although the heterogeneity of responses in the
non-specific category renders it clinically meaningless, it is retained for
the sake of completeness of the data. A power calculation in detecting
differences between the groups of explanatory models and treatment preferences
in categorical analyses indicated that: a large effect size (i.e. a difference
in proportions when translated into a fourfold product moment r
ranges between 0.37 and 0.39) would be detected with 87% power on a two-tailed
significance test where P=0.05; a medium effect size (when translated
r=0.25) would be detected with 49% power; and a small effect size
(when translated r=0.10) with only 12% power
(Cohen, 1988). Interrater
agreement in classifying the raw data into categories was calculated using the
statistic. The four causal categories were compared on
socio-demographic, clinical and psychological variables. The therapeutic
relationship scores were recorded into a score below or above the midpoint on
the scale, indicating a generally positive v. a generally negative
therapeutic relationship. Differences between the groups according to
explanatory model and ethnicity were analysed using analysis of variance and
2 or Fishers exact test. Where multiple tests were
conducted, the Bonferroni-adjusted significance levels are reported.
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RESULTS |
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Thirty AfricanCaribbeans, Bangladeshis and UK Whites and 29 West Africans were interviewed. Their socio-demographic and clinical history characteristics are presented in Table 1. Bangladeshis were younger and had a shorter duration of illness than AfricanCaribbeans and UK Whites. They were also less likely to live alone than West Africans.
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The four ethnic groups were also compared on clinical and psychological characteristics and there were no significant differences between the groups on any of these variables (data available on request).
Explanatory models
Responses to the SEMI questions concerning concept, severity, course,
aetiology and treatment from the sample as a whole were content analysed and
are presented in Table 2.
Although an individual may have cited more than one response, particularly
with respect to aetiology and treatment preferences, the first response
provided by each participant was coded for the purpose of this analysis. Four
raters independently coded the raw data from the transcripts into categories.
The chance-corrected proportional interrater agreement between the four raters
was very good: =0.87 (Altman,
1991).
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Approximately 20% of the sample called their problem schizophrenia/psychosis and 18.5% called it depression/manic depression. Almost two-thirds said that their illness was either moderately or very severe. Approximately half stated that their illness had a long course and almost one-third said that it had a short course.
There was substantial variation in the primary causes of illness cited: 21.4% said they did not know; 16.2% cited interpersonal factors (e.g. break-up of relationship, emotional baggage); 15.4%, supernatural factors (e.g. someone did magic to me when I was a little boy, evil forces); 9.4%, stress mostly arising from training or employment (stress from work, working very hard); 8.5%, personality factors (e.g. myself for not being wiser, lack of knowledge of when I was becoming stressed); 7.7%, drugs/alcohol (e.g. heavy drinking, took crack); 7.7%, negative childhood events (e.g. physical and mental abuse in childhood, influence in life when I was young); 5.1%, mental illness (e.g. depression at a young age, breakdown); and 5.1%, physical illness or injury (e.g. heart disease, run over by a car and was in a coma).
With respect to participants first treatment preference, 19.7% thought that they should receive medication; 18.8% wanted counselling, including help understanding the illness; 12.5% wanted something to make them get better but did not specify what; 5.4% wanted natural remedies (e.g. natural herbal remedies, alternative herbal treatment instead of medication); 5.4% wanted practical help (e.g. help with accommodation, help with housing problems and around the house); 4.5% wanted social/occupational activities (e.g. occupational therapy, something to do like a club); 2.7% said they were getting the right treatment; and 15.2% mentioned specific treatments that did not fit into the general categories (e.g. equal opportunities as the system hates Black people, X-ray).
Explanatory models and ethnicity
Concept of illness, or the name patients used to describe their problem,
did not differ significantly between the four groups (2=18.9,
P=0.09), nor did perceived severity of illness
(
2=16.02, P=0.18). Cause of illness, coded into four
categories broken down by ethnic group is displayed in
Table 3 and
Fig. 1.
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Cause of illness differed significantly according to ethnicity (see
Fig. 1) in a 4x4 analysis
(2=28.7, d.f.=9, P<0.001). Because the 4x4
analysis does not show which groups differed on which measures, the effect was
broken down into a series of focused 2x2 comparisons using
2 and Fishers exact test in the case of low cell
counts.
The sources of the overall effect were somewhat localised. Overall, there were no differences between AfricanCaribbeans, Bangladeshis and West Africans except when social causes were compared with supernatural causes; AfricanCaribbeans were more likely (P=0.053) to cite social causes than West Africans.
By contrast, Whites were distinguished from the other groups in four cases. First, when biological causes were compared with supernatural causes, Whites cited biological causes more frequently than AfricanCaribbeans (P=0.022), Bangladeshis (P<0.001) and West Africans (P=0.001). Second, when biological causes were compared with social causes, Whites cited biological causes more frequently than AfricanCaribbeans (P=0.05) and Bangladeshis (P=0.003). Given the statistical power of the study, a trend (P=0.072) for the same pattern when Whites were compared with West Africans is worth noting. Third, when biological causes were compared with non-specific causes, Whites cited biological causes more frequently than Bangladeshis (P=0.014). Finally, when supernatural causes were compared with social and non-specific causes, both Bangladeshis (cf. social P=0.016, cf. non-specific P=0.013) and West Africans (cf. social P=0.024, cf. non-specific P=0.004) cited supernatural causes more frequently than Whites.
Treatment preference also differed according to ethnicity
(2=24.7, P=0.054). Bangladeshis were less likely to
want treatment of any kind than Whites (P=0.019) and
AfricanCaribbeans (P=0.049). Both Whites and
AfricanCaribbeans were more likely to want counselling and,
additionally, Whites were more likely to want medication (P=0.051) or
to be unsure about what they wanted (P=0.029). Bangladeshis were also
more likely to want non-conventional forms of treatment, including natural
remedies and spiritual activities, than Whites (P=0.008), who were
more likely to be unsure about what they wanted.
Cause of illness and clinical and psychological characteristics
Because there was substantial variation within ethnic groups, explanatory
models (independent of ethnicity) were analysed with respect to the clinical
and psychological characteristics assessed. With respect to concept of
illness, patients who called their problem a specific or non-specific
psychiatric illness or breakdown were more likely to accept that they had a
mental illness than those who named it differently (P=0.05). For
severity of illness, patients who perceived their illness to be very severe
had a lower external health locus of control than those who thought that their
illness was moderately severe (P=0.05).
Cause of illness cited by patients was significantly related to treatment satisfaction, therapeutic relationships and acceptance of mental illness (see Table 4). People who cited biological causes were more likely to say that they were receiving the right treatment for them (P=0.021), were more satisfied with treatment (P=0.041) and had better therapeutic relationships (P=0.006) than those who cited social causes. They were also more satisfied with treatment (P=0.012) and had better therapeutic relationships (P=0.044) than those who cited non-specific causes. People who cited social causes were most likely to accept that they had a mental illness, significantly more so than those who cited supernatural causes (P=0.044), but had worse therapeutic relationships than the latter (P=0.046). Cause of illness cited was not associated with treatment compliance (F=1.3, P=0.28). Hence, having a biological explanatory model was not associated with better treatment compliance.
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With respect to treatment, those who wanted practical help had higher levels of symptomatology than those who wanted medication (P=0.005) or no treatment (P=0.038). Those who wanted medication were more likely to be compliant with treatment (P=0.041). Finally, those who wanted medication were more likely to accept that they had a mental illness (P=0.001).
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DISCUSSION |
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Explanatory models, ethnicity and treatment
Bangladeshis, who cited supernatural causes more frequently, either wanted
alternative forms of treatment such as religious activities or no treatment at
all. Conversely, Whites, who cited biological and social causes more
frequently, preferred medication and counselling. Type of explanatory model,
independent of ethnicity, was related to satisfaction with treatment,
suggesting that what people believe about their illness influences their
experience of and benefit from mental health services (cf.
Dein, 2002). There was a
marked difference between a biological or social explanatory model and
corresponding perceptions of treatment. People with a biological
explanatory model more often said that they were receiving the right treatment
for them, were more satisfied with the treatment and had better therapeutic
relationships than those with a social explanatory model.
Although the clinicians explanatory model was not assessed in this
study, it seems reasonable to suggest that because the predominant treatment
model is medication-based it is primarily biological. This finding seems to
support Callan & Littlewood
(1998), who found that
satisfaction is higher when there is concordance between the patients
and psychiatrists explanatory models.
Although cause of illness stated by patients was related to their treatment preferences and perceived benefit from and satisfaction with treatment, it was not associated with treatment compliance. A similar finding was also reported by Holzinger et al (2002), who investigated subjective illness theory and compliance with atypical antipsychotics among people with schizophrenia.
People who cited supernatural causes of illness were less insightful (i.e. less likely to accept that they had a mental illness) but were not less compliant with treatment. Goldberg et al (2001) found that ethnic minorities were more likely to be rated as having poor insight. It may be that insight is narrowly assessed as a difference between the perspective of the rater and the person being rated in how mental illness is conceptualised, without taking account of differences in social cultural attributions. The fact that type of explanatory model was not related to treatment compliance may highlight the lack of explanatory power of insight if assessed in this way (cf. McCabe et al, 2000; McCabe & Quayle, 2002). Indeed, other sociocultural factors, such as varying degrees of social deference, may mediate readiness to comply with treatment.
Methodological issues
In this study, individual accounts of cause of illness were not fixed but
fluid and often people did not cite a single, but multiple causes. Williams
& Healy (2001) suggested
that exploratory map rather than model might
reflect more accurately how people construct narratives about illness. This
may be particularly relevant among people of different ethnic origin in the
UK, who will vary in degree of acculturation and so may draw on multiple
social and linguistic resources in narratives about illness. The fluidity of
accounts of illness during the course of a single interview is compounded when
testretest reliability is considered. The stability of explanatory
models over time appears to be low (McCabe
& Priebe, 2004), thus limiting their value in predicting
long-term outcome.
The current study used an operationalised method to assess explanatory models, as suggested by Bhui & Bhugra (2002). It highlighted the limitations as well as the potential benefits of such methods (cf. Canino et al, 1997). There was a tension in reducing explanatory models to single categories to link them with quantitative outcomes. A necessarily reductionistic approach in condensing complex accounts of illness to fixed simple categories resulted in the loss of rich contextual information, underlining the tension between the anthropological framework within which the concept of explanatory model of illness was originally developed and a reductionistic approach for quantification (McCabe & Priebe, 2004). Moreover, the categories derived from the qualitative analysis appear to be more sensitive in discriminating White from non-White groups and less sensitive in discriminating between the three non-White groups. It is possible that the analysts categories are less finely tuned than those members themselves (i.e. in this case the different cultural groups) use to order the social world.
The low statistical power of the small sample sizes precluded the identification of small effect sizes. Consequently, negative findings, such as the failure to detect a significant association between explanatory model and treatment compliance, must be interpreted cautiously. Also, although post hoc testing between groups for specific results was Bonferroni adjusted, there was no adjustment for multiple testing across all tested associations. This approach is justified, however, in an exploratory study investigating a number of independent research questions (Perneger, 1998).
Although it is a strength of the study that all groups were assessed with standardised instruments and that the groups were comparable in their socio-economic conditions, there may have been a selection bias. Those who did not agree to participate or were not in contact with services are likely to be less satisfied with treatment and may differ more in their explanatory models. Further research is required to shed light on the influence of explanatory models in the early phases of illness on contact with services and benefit from treatment. A related issue is that it remains unclear whether and, if so, how contact with clinicians affected patients explanatory models.
Although various methodological issues remain unresolved, this study is a step forward because it successfully linked qualitative data elicited in semi-structured interviews with conventional quantitative outcomes and yielded statistically significant associations that are clinically relevant and may guide further research. The differences in explanatory models between ethnic groups may be considered reliable because Fishers exact test is a conservative statistical test (Rosenthal & Rosnow, 1991) and so is unlikely to lead to Type I errors.
In conclusion, this study suggests that explanatory models differ reliably according to cultural background and are associated with treatment preferences and satisfaction but not with treatment compliance. Although Whites are more likely to have a biological explanatory model, AfricanCaribbeans, West Africans and Bangladeshis are more likely to have a social or supernatural explanatory model. Moreover, having a biological explanatory model, especially compared with a social explanatory model, is linked with greater treatment satisfaction and better therapeutic relationships.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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Received for publication July 30, 2003. Revision received January 14, 2004. Accepted for publication January 24, 2004.
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