Dataset Information

Continuum beliefs and stigmatising beliefs about mental illness: results from an Asian community survey.

ABSTRACT:

Objectives

To establish the prevalence and correlates of continuum beliefs for five mental illnesses in a multiethnic population and to explore its association with stigma.

Design

A community-based, cross-sectional study.

Setting

A national study in a multiethnic Asian country.

Participants

A comprehensive study of 3006 Singapore residents (Singapore citizens and permanent residents) aged 18-65 years who were living in Singapore at the time of the survey.

Outcome measures

Parameters assessed included belief in a continuum of symptom experience, stigma dimensions and causal beliefs in mental illness. Statistical analyses included descriptive statistics and multiple linear regression (MLR).

Results

About half of the population indicated agreement with a continuum of symptoms for depression (57.9%) and dementia (46.8%), whereas only about one in three respondents agreed with it for alcohol abuse (35.6%), schizophrenia (32.7%) and obsessive-compulsive disorder (OCD) (36.8%). MLR analyses revealed that students (β=0.28; 95% CI 0.05 to 0.50; p=0.018) and those who were unemployed (β=0.60; 95% CI 0.26 to 0.95; p=0.001) (vs employed) as well as those who had previous contact with people with mental illness (β = 0.31; 95% CI 0.18 to 0.45; p<0.001) and believed stress, family arguments, difficulties at work or financial difficulties to be a cause for mental illness (β=0.43; 95% CI 0.13 to 0.73; p=0.005) were associated with a higher belief in a continuum of symptom experience. Continuum beliefs were related to lower desire for social distance in alcohol abuse, OCD and schizophrenia; however, they were associated with higher scores on 'weak-not-sick' stigma dimension in dementia and schizophrenia.

Conclusions

Perceiving that a person with a mental illness is similar to themselves may reduce social distancing by the public. Thus, the approach may lend itself well to public education aimed at reducing stigma.

SUBMITTER: Subramaniam M

PROVIDER: S-EPMC5594210 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Continuum beliefs and stigmatising beliefs about mental illness: results from an Asian community survey.

Subramaniam Mythily M Abdin Edimansyah E Picco Louisa L Shahwan Shazana S Jeyagurunathan Anitha A Vaingankar Janhavi Ajit JA Chong Siow Ann SA

BMJ open 20170405 4

<h4>Objectives</h4>To establish the prevalence and correlates of continuum beliefs for five mental illnesses in a multiethnic population and to explore its association with stigma.<h4>Design</h4>A community-based, cross-sectional study.<h4>Setting</h4>A national study in a multiethnic Asian country.<h4>Participants</h4>A comprehensive study of 3006 Singapore residents (Singapore citizens and permanent residents) aged 18-65 years who were living in Singapore at the time of the survey.<h4>Outcome ...[more]

PMID: 28381420

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Project description:AimsTo identify the common causal beliefs of mental illness in a multi-ethnic Southeast Asian community and describe the sociodemographic associations to said beliefs. The factor structure to the causal beliefs scale is explored. The causal beliefs relating to five different mental illnesses (alcohol abuse, depression, obsessive-compulsive disorder (OCD), dementia and schizophrenia) and desire for social distance are also investigated.MethodsData from 3006 participants from a nationwide vignette-based study on mental health literacy were analysed using factor analysis and multiple logistic regression to address the aims. Participants answered questions related to sociodemographic information, causal beliefs of mental illness and their desire for social distance towards those with mental illness.ResultsPhysical causes, psychosocial causes and personality causes were endorsed by the sample. Sociodemographic differences including ethnic, gender and age differences in causal beliefs were found in the sample. Differences in causal beliefs were shown across different mental illness vignettes though psychosocial causes was the most highly attributed cause across vignettes (endorsed by 97.9% of respondents), followed by personality causes (83.5%) and last, physical causes (37%). Physical causes were more likely to be endorsed for OCD, depression and schizophrenia. Psychosocial causes were less often endorsed for OCD. Personality causes were less endorsed for dementia but more associated with depression.ConclusionsThe factor structure of the causal beliefs scale is not entirely the same as that found in previous research. Further research on the causal beliefs endorsed by Southeast Asian communities should be conducted to investigate other potential causes such as biogenetic factors and spiritual/supernatural causes. Mental health awareness campaigns should address causes of mental illness as a topic. Lay beliefs in the different causes must be acknowledged and it would be beneficial for the public to be informed of the causes of some of the most common mental illnesses in order to encourage help-seeking and treatment compliance.

Project description:The full range of biopsychosocial complexity is mind-boggling, spanning a vast range of spatiotemporal scales with complicated vertical, horizontal, and diagonal feedback interactions between contributing systems. It is unlikely that such complexity can be dealt with by a single model. One approach is to focus on a narrower range of phenomena which involve fewer systems but still cover the range of spatiotemporal scales. The suggestion is to focus on the relationship between temperament in healthy individuals and mental illness, which have been conjectured to lie along a continuum of neurobehavioral regulation involving neurochemical regulatory systems (e.g., monoamine and acetylcholine, opiate receptors, neuropeptides, oxytocin), and cortical regulatory systems (e.g., prefrontal, limbic). Temperament and mental illness are quintessentially dynamical phenomena, and need to be addressed in dynamical terms. A meteorological metaphor suggests similarities between temperament and chronic mental illness and climate, between individual behaviors and weather, and acute mental illness and frontal weather events. The transition from normative temperament to chronic mental illness is analogous to climate change. This leads to the conjecture that temperament and chronic mental illness describe distinct, high level, dynamical phases. This suggests approaching biopsychosocial complexity through the study of dynamical phases, their order and control parameters, and their phase transitions. Unlike transitions in physical systems, these biopsychosocial phase transitions involve information and semiotics. The application of complex adaptive dynamical systems theory has led to a host of markers including geometrical markers (periodicity, intermittency, recurrence, chaos) and analytical markers such as fluctuation spectroscopy, scaling, entropy, recurrence time. Clinically accessible biomarkers, in particular heart rate variability and activity markers have been suggested to distinguish these dynamical phases and to signal the presence of transitional states. A particular formal model of these dynamical phases will be presented based upon the process algebra, which has been used to model information flow in complex systems. In particular it describes the dual influences of energy and information on the dynamics of complex systems. The process algebra model is well-suited for dealing with the particular dynamical features of the continuum, which include transience, contextuality, and emergence. These dynamical phases will be described using the process algebra model and implications for clinical practice will be discussed.

Dataset Information

Continuum beliefs and stigmatising beliefs about mental illness: results from an Asian community survey.

Objectives

Design

Setting

Participants

Outcome measures

Results

Conclusions

Publications

Continuum beliefs and stigmatising beliefs about mental illness: results from an Asian community survey.

Similar Datasets

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