Journal Article
Brandon A Kohrt,
1Duke Global Health Institute, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA, 2Department of Psychology, Fordham University, New York, USA, 3Department of Anthropology, Department of Epidemiology, Emory University, Atlanta, GA, USA, 4Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA, 5Department of Psychology, Tribhuvan University, Kirtipur, Nepal, 6Butabika National Referral Mental and Teaching Hospital, Kampala, Uganda, 7AISSR, University of Amsterdam, The Netherlands and 8Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
*Corresponding author. Duke Global Health Institute, Trent Hall #213, 310 Trent Drive, Duke University, Durham, NC 27710, USA. E-mail:
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Andrew Rasmussen,1Duke Global Health Institute, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA, 2Department of Psychology, Fordham University, New York, USA, 3Department of Anthropology, Department of Epidemiology, Emory University, Atlanta, GA, USA, 4Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA, 5Department of Psychology, Tribhuvan University, Kirtipur, Nepal, 6Butabika National Referral Mental and Teaching Hospital, Kampala, Uganda, 7AISSR, University of Amsterdam, The Netherlands and 8Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Bonnie N Kaiser,1Duke Global Health Institute, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA, 2Department of Psychology, Fordham University, New York, USA, 3Department of Anthropology, Department of Epidemiology, Emory University, Atlanta, GA, USA, 4Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA, 5Department of Psychology, Tribhuvan University, Kirtipur, Nepal, 6Butabika National Referral Mental and Teaching Hospital, Kampala, Uganda, 7AISSR, University of Amsterdam, The Netherlands and 8Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Emily E Haroz,1Duke Global Health Institute, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA, 2Department of Psychology, Fordham University, New York, USA, 3Department of Anthropology, Department of Epidemiology, Emory University, Atlanta, GA, USA, 4Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA, 5Department of Psychology, Tribhuvan University, Kirtipur, Nepal, 6Butabika National Referral Mental and Teaching Hospital, Kampala, Uganda, 7AISSR, University of Amsterdam, The Netherlands and 8Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Sujen M Maharjan,1Duke Global Health Institute, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA, 2Department of Psychology, Fordham University, New York, USA, 3Department of Anthropology, Department of Epidemiology, Emory University, Atlanta, GA, USA, 4Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA, 5Department of Psychology, Tribhuvan University, Kirtipur, Nepal, 6Butabika National Referral Mental and Teaching Hospital, Kampala, Uganda, 7AISSR, University of Amsterdam, The Netherlands and 8Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Byamah B Mutamba,1Duke Global Health Institute, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA, 2Department of Psychology, Fordham University, New York, USA, 3Department of Anthropology, Department of Epidemiology, Emory University, Atlanta, GA, USA, 4Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA, 5Department of Psychology, Tribhuvan University, Kirtipur, Nepal, 6Butabika National Referral Mental and Teaching Hospital, Kampala, Uganda, 7AISSR, University of Amsterdam, The Netherlands and 8Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Joop TVM de Jong,1Duke Global Health Institute, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA, 2Department of Psychology, Fordham University, New York, USA, 3Department of Anthropology, Department of Epidemiology, Emory University, Atlanta, GA, USA, 4Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA, 5Department of Psychology, Tribhuvan University, Kirtipur, Nepal, 6Butabika National Referral Mental and Teaching Hospital, Kampala, Uganda, 7AISSR, University of Amsterdam, The Netherlands and 8Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Devon E Hinton1Duke Global Health Institute, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA, 2Department of Psychology, Fordham University, New York, USA, 3Department of Anthropology, Department of Epidemiology, Emory University, Atlanta, GA, USA, 4Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA, 5Department of Psychology, Tribhuvan University, Kirtipur, Nepal, 6Butabika National Referral Mental and Teaching Hospital, Kampala, Uganda, 7AISSR, University of Amsterdam, The Netherlands and 8Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Accepted:
04 October 2013
Published:
22 December 2013
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Brandon A Kohrt, Andrew Rasmussen, Bonnie N Kaiser, Emily E Haroz, Sujen M Maharjan, Byamah B Mutamba, Joop TVM de Jong, Devon E Hinton, Cultural concepts of distress and psychiatric disorders: literature review and research recommendations for global mental health epidemiology, International Journal of Epidemiology, Volume 43, Issue 2, April 2014, Pages 365–406, //doi.org/10.1093/ije/dyt227
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Abstract
Background Burgeoning global mental health endeavors have renewed debates about cultural applicability of psychiatric categories. This study’s goal is to review strengths and limitations of literature comparing psychiatric categories with cultural concepts of distress [CCD] such as cultural syndromes, culture-bound syndromes, and idioms of distress.
Methods The Systematic Assessment of Quality in Observational Research [SAQOR] was adapted based on cultural psychiatry principles to develop a Cultural Psychiatry Epidemiology version [SAQOR-CPE], which was used to rate quality of quantitative studies comparing CCD and psychiatric categories. A meta-analysis was performed for each psychiatric category.
Results Forty-five studies met inclusion criteria, with 18 782 unique participants. Primary objectives of the studies included comparing CCD and psychiatric disorders [51%], assessing risk factors for CCD [18%] and instrument validation [16%]. Only 27% of studies met SAQOR-CPE criteria for medium quality, with the remainder low or very low quality. Only 29% of studies employed representative samples, 53% used validated outcome measures, 44% included function assessments and 44% controlled for confounding. Meta-analyses for anxiety, depression, PTSD and somatization revealed high heterogeneity [I2 > 75%]. Only general psychological distress had low heterogeneity [I2 = 8%] with a summary effect odds ratio of 5.39 [95% CI 4.71-6.17]. Associations between CCD and psychiatric disorders were influenced by methodological issues, such as validation designs [β = 16.27, 95%CI 12.75-19.79] and use of CCD multi-item checklists [β = 6.10, 95%CI 1.89-10.31]. Higher quality studies demonstrated weaker associations of CCD and psychiatric disorders.
Conclusions Cultural concepts of distress are not inherently unamenable to epidemiological study. However, poor study quality impedes conceptual advancement and service application. With improved study design and reporting using guidelines such as the SAQOR-CPE, CCD research can enhance detection of mental health problems, reduce cultural biases in diagnostic criteria and increase cultural salience of intervention trial outcomes.
Introduction
In 1904 Emile Kraepelin initiated the field of comparative psychiatry [vergleichende Psychiatrie] through investigation of dementia praecox in Java, and he later documented psychiatric presentations among Native Americans, African Americans and Latin Americans.1 A century later, active debate continues regarding the role of culture in mental disorders and the cross-cultural applicability of biomedical psychiatric diagnoses.2 Methodological limitations in cross-cultural psychiatric epidemiology have been cited as a primary reason why cultural differences have not translated into re-evaluating psychiatric concepts and treatment practices.3,4 For example, cultural differences in schizophrenia outcomes, which have been identified in three successive studies,5–10 have done little to alter conceptualizations or treatment of the disorder, and this is in part due to methodological problems in the cross-national studies.3,11–13 These studies, along with World Health Organization [WHO] World Mental Health Surveys,14 are typified by application of Western culturally developed biomedical psychiatric diagnoses that lack inclusion of cultural concepts of distress [CCD]. To date there have not been large-scale cross-national global mental health epidemiology studies incorporating CCD. To address this gap in the research, a review of the literature on CCD was undertaken to examine the types of studies conducted, the methodological approaches and the association of CCD with psychiatric disorders. The goal is to identify best practices in cross-cultural psychiatric epidemiology to improve research on CCD and encourage application to mental health services.
The term ‘cultural concept of distress’ is a new addition to the Diagnostic and Statistical Manual of Mental Disorders [DSM] series with the publication of DSM-5: ‘Cultural Concepts of Distress refers to ways that cultural groups experience, understand, and communicate suffering, behavioral problems, or troubling thoughts and emotions’.15 The term is a recent advance in the history of attempts to categorize psychological distress with demonstrable cultural influence that lacks one-to-one unity with biomedical psychiatric diagnoses [see Box 1 for exemplar CCD.] The attempt to label CCD dates back to Pow Meng Yap’s research in Hong Kong in the 1950–60s.16 Yap employed the term ‘culture-bound depersonalization syndrome’ to describe koro, a ‘state of acute anxiety with partial depersonalization’ associated with fear of the penis retracting into the body. The term ‘culture-bound syndrome’ has been used in cross-cultural psychiatry since and was included in the DSM-IV.17
Box 1. Examples of Cultural Concepts of Distress [CCD]
Nervios-related conditions—In the Americas, nervios [nerves]-related conditions among Latino populations are the most commonly described CCD.126 Nervios starts with ‘a persistent idea that ‘is stuck to one's mind’ [‘idea pegada a la mente’], and these ‘particular idea[s] … invade the mind and accumulate … Affected individuals think so much about the ideas that the ideas ‘get stuck' to the brain’.94 Among Mexicans with nervios, 40% endorsed having an idea stuck to their mind. In nervios, feelings of humiliation lead to the slow deterioration of one’s mind, nerves and spirit and ‘may even cause death, if adequate help is not timely received’.127 The spectrum of nervios follows a gradient of behavioural control.80 One end of the spectrum begins with socially acceptable nervousness: ser una persona nerviosa [being a nervous person]. Padecer de los nervios [suffering from nerves] is more serious. Ataques de nervios [attacks of nerves] have greater severity and are characterized by social stressors triggering loss of behavioural control, dissociation, violent acts toward oneself or others, anger and somatic distress.128 Severe nerve illness can lead to loco [madness]. Nervios [nerves], padecer de nervios [suffering from nerves] and ataques de nervios [nerve attacks] have been studied in clinical samples in large-scale Latino representative community studies in Puerto Rico and the USA.70,71 Ataques de nervios overlap with some symptoms of panic attacks and panic disorder. However, they are distinct from panic attacks because of the centrality of interpersonal disputes in triggering episodes, dissociative features and an experience of relief among some individuals after an ataque.80,132 These nervios-related conditions are associated with unexplained neurological complaints, physical health problems and functional impairment independent of association with psychiatric disorders.
Dhat—Dhat syndrome has been studied in South Asia and is rooted in Ayurvedic traditions about bodily production of semen as representing an end-product of energy demanding metabolism: 40 meals create 1 drop of blood, 40 drops of blood create 1 drop of semen.43 Dhat is recognized by a whitish discharge in urine assumed to be semen. Although sexually transmitted infections may be a source of such discharge, dhat sufferers do not appear to have greater frequency of STIs.69 Dhat sufferers do appear to have high rates of psychosexual dysfunction including premature ejaculation and erectile dysfunction: 42% of men with dhat had premature ejaculation in one study in India.64 Young males appear to be the most frequent demographic group presenting with dhat. Dhat has corollaries in Chinese medicine and European and American history with accounts of weakness, physical illness and mental illness related to the loss of semen.43,77
Koro—Koro was one of the first cultural concepts discussed in transcultural psychiatry literature.16 Koro epidemics have been reported in South Asia, and case reports have been reported throughout the world. Fear of the penis retracting into the body among men and retraction of breasts among women is a central feature. The majority of reported cases are among men.
Brain fag—Brain fag has been studied for a half-century in Western Africa. The condition is characterized by distress from thinking too much, with students being a vulnerable population.86 The experience includes headaches and an experience of a worm crawling in the head. This is similar to the Nigerian cultural concept of distress, ode ori:84 the disorder ode ori [hunter in the head] affects the brain under the anterior fontanelle where the iye [senses] control mental functions through okun [strings] that project throughout the body and provide direct linkages among the brain, eyes, ears and heart.
Khyal attacks and ‘wind’-related illnesses—The substance qi, [cf chi, chi’i, khí, khii, rlung, khyal] is associated with wind flow and wind balance. Wind-related illnesses are commonly described in East Asian populations including Tibetans, Cambodians, Vietnamese, Chinese and Mongolians.73,77,78,129,130 Shenjing shuairuo [neurological weakness, neurasthenia], studied by Kleinman in the 1970s and 80s, is associated with weakness, fatigue and social distress mediated by an alteration in qi.77 Yadargaa, a nervous fatigue described in Mongolia, is similarly viewed as an alteration in khii flow and balance.78 In the Vietnamese CCD ‘hit by wind’, shifts in ambient temperature, especially gusts of cold air, are associated with a range of physical complaints, traumatic memories, thinking too much, epilepsy and stroke.73 Similarly, in China, nerve weakness is associated with a fear of cold because it worsens nerve weakness.77 Among Cambodians, the wind-like substance khyal can be experienced as an attack associated with palpitations, asphyxia and dizziness.130 Khyal attacks can lead to rupture of blood vessels in the neck and spinning of the brain.
Kufungisisa—The experience of thinking too much [Shona: kufungisisa] is associated with general psychological distress and common mental disorders in Zimbabwe. Thinking too much is considered both a symptom of distress and a cause of other physical and psychological health problems: thinking too much can cause pain and feelings of physical pressure on the heart.54
Hwa-Byung—Heat and fire are important elements in East Asian ethnopsychology. The condition hwa-byung [fire illness resulting from chronic accumulated anger] in Korea occurs when haan [a mixture of sorrow, regret, hatred, revenge and perseverance] builds up to create a pushing sensation in the chest, resulting in the inability to appropriately control one’s anger.85 Hwa-byung affects middle-aged women in Korea who have experienced years of interpersonal conflict, typically in the context of an abusive marital relationship.
However, the term culture-bound syndrome has been associated with numerous limitations: findings of similar patterns of distress in disparate cultural settings, lack of cohesive symptom presentation characterizing a syndrome, and wide diversity in aetiological attributions, vulnerability groups and symptoms that influence cultural labels.18–22 Moreover, the combination of medical anthropology research, which documents the social construction of psychiatric disorders,23 with innovations in gene-by-environment and social neuroscience research, which illustrate that culture and biology are not neatly divisible categories,24–28 demonstrates that all psychological distress is culture bound. To acknowledge this, the DSM-5 includes text that ‘all forms of distress are locally shaped, including the DSM disorders’.15 Due to dissatisfaction with the term culture-bound syndrome, researchers have proposed other labels such as ‘idioms of distress’, ‘popular category of distress’, ‘cultural syndrome’ and ‘explanatory model’.29–33 The term ‘cultural concept of distress’ is an attempt to aggregate these different concepts without implying cultural exclusivity.
There has been a tension in cultural psychiatry about comparing CCD with psychiatric disorders. Because CCD often incorporate culturally salient aetiological models, vulnerability expectations, wide-ranging associated symptoms and a mixture of lay and local professional attributions systems, comparison with psychiatric diagnoses has been criticized as forcing homogeneity onto CCD and losing key aspects of aetiology and vulnerability that are not incorporated in most psychiatric diagnoses.20,21,34 However, there is a growing body of epidemiology literature comparing CCD with psychiatric disorders for a variety of goals, such as validating psychiatric disorders against CCD, identifying vulnerable groups based on CCD status and identifying forms of distress and impairment not captured by psychiatric disorders.
The goal of this review is to explore the methodological approaches of these epidemiological studies of CCD and psychiatric disorders, to identify limitations in the approaches and best practices for future work. We sought to develop specific criteria for evaluating epidemiological studies based on cultural psychiatry principles. With the expansion of global mental health research and scaling up of services,35–38 it is an ideal time to evaluate if and how CCD can be incorporated into community and clinical epidemiology to reduce suffering. Our review is divided into the following sections: identification of studies comparing CCD and psychiatric disorders; description of study objectives and methods including ranking epidemiological quality of these studies; examining summary effect sizes and sources of heterogeneity when comparing CCD and psychiatric disorders; and concluding with recommendations for incorporating CCD in global mental health research and services.
Methods
Informational sources
To identify literature on CCD we searched MEDLINE/PubMed, applying the following keywords: ‘culture-bound’ or ‘culture bound’ or ‘idiom of distress’ or ‘idioms of distress’. To assure inclusion of popularly studied CCD, we combined the above search with a search of CCD listed in the DSM-5 glossary: ‘nervios’ or ‘dhat’ or ‘khyal’ or ‘kufungisisa’ or ‘maladi moun’ or ‘shenjing shuairou’ or ‘susto’ or ‘taijin kyofusho’]. We limited psychiatric outcomes to common mental disorders [operationalized here as depression, anxiety-related conditions including posttraumatic stress disorder [PTSD] and panic disorder, and somatization-related conditions] because of their significant burden of disease, the breadth of research on CCD and common mental disorders, and feasibility of assessing common mental disorders through self-report. In contrast, psychosis-related conditions have shown poor reliability and low detection through self-report cross-culturally.39,40 In our preliminary searches for substance use disorders, eating disorders and developmental disorders, we identified a limited number of studies precluding synthesis of findings. The psychiatric disorder search terms thus included the following: ‘depression’ or ‘depression, postpartum’ or ‘PTSD’ or ‘stress disorders, post-traumatic’ or ‘fatigue syndrome, chronic’ or ‘fatigue’ or ‘anxiety disorders’ or ‘anxiety’ or ‘panic disorder’ or ‘panic attack’ or ‘somatoform disorders’ or ‘somatic complaints’. Searches were limited to English-language peer-reviewed journal publications. In addition, reference sections of previous reviews on culture-bound syndromes were searched,41–48 and reference sections of articles identified in the search were used to locate additional articles. The initial searches was performed in November 2012 and repeated for new references in March 2013 and September 2013.
Data collection
To extract relevant data, all studies identified through searches were read and evaluated for inclusion by the first author. Inclusion criteria comprised English language, prevalence data for a psychiatric category, prevalence data for a CCD, odds ratios with 95% confidence intervals for association of CCD and psychiatric category or data presented in a manner enabling construction of a two-by-two comparison of psychiatric classification and CCD. Exclusion criteria were case studies and articles lacking original quantitative data. Extracted data included world region, country, study population [including current country of residence for refugee and immigrant populations], researcher label for CCD [e.g. idiom of distress, culture-bound syndrome, cultural syndrome, cultural somatic symptom], language of term, English translation of term, research objective of the study, sample size, sample description, sample origin [clinical, community or school], age group of sample, representative vs convenience or other sample, inclusion and description of control or comparison group, symptom/syndrome description, assessment method for CCD [self-labelling with single-item term, labelling based on a multi-item self-report instrument score, labelling by healthcare provider including traditional healers and clinical providers, labelling from key informant in community], symptom severity assessment, type of symptoms [subjective self-report, externally observable or mixed], CCD prevalence [lifetime, current or unclear], age of onset, duration of current episode, psychiatric diagnostic instrument, administration format of psychiatric instrument [e.g. clinician administered, researcher administered, self-report], validation of instrument in study population, assessment of functioning and impairment, aetiology/perceived cause of CCD, vulnerability factors and risk group for CCD, protective factors against CCD, inclusion of follow-up assessment, percentage lost to follow-up, reasons lost to follow-up, current or prior treatment status, description of study treatment, assessment of psychiatric comorbidities, assessment of biological comorbidities and potential confounds.
Quality assessment
To assess quality, we chose the Systematic Assessment of Quality in Observational Research [SAQOR], which has been developed for assessing quality in observational studies49 and has been used to rate global mental health research conducted across cultural settings.50 SAQOR includes six domains: Sample, Control/Comparison Group, Quality of Exposure/Outcome Measurements, Follow-Up, Distorting Influences and Reporting Data. Each domain contains multiple criteria. For this study, the results section describes modification of SAQOR to develop a version for Cultural Psychiatry Epidemiology [SAQOR-CPE].
Meta-analyses
Odds ratios were extracted or calculated from quantitative studies to determine the likelihood of a specific psychiatric category given the presence of a specific CCD. Two-by-two tables were constructed for all quantitative papers that included data for categorical outcomes of CCD [yes vs no] and psychiatric categories [yes vs no]. If studies only included mean scores on symptom scales without providing information on categorical cut-offs, these studies were not included in the meta-analysis. In the two-by-two tables, CCD were considered the independent variable and psychiatric categories were considered the dependent variable.
Odds ratios [OR], 95% confidence intervals, sensitivity, specificity, positive predictive value [PPV] and negative predictive value [NPV] were calculated for all studies in the meta-analysis. If a study contained an empty field in the two-by-two table, then individual study outcomes [OR, sensitivity, specificity, PPV and NPV] were not calculated; however, the participants were included in the meta-analysis summary calculations. Sensitivity was calculated as the proportion of persons positive for both the CCD and the psychiatric category, among all persons with CCD. Specificity was calculated as the proportion of persons negative for the CCD and negative for the psychiatric category, among all persons negative for the CCD. Positive predictive value was calculated as the proportion of participants positive for both the CCD and psychiatric category, among all participants positive for the psychiatric category. Negative predictive value was calculated as the proportion of participants negative for both the CCD and the psychiatric category, among all persons negative for the psychiatric category.
Heterogeneity for summary effect sizes was calculated with the Q statistic. The statistic was calculated by summing the squared deviations of each study’s effect estimated from the overall effect estimate; each study was weighted by its inverse variance.51,I2 is another measure of heterogeneity calculated by dividing the difference of the Q statistic and its degrees of freedom by the Q statistic and multiplying this by 100.51 Low values [e.g. 75% suggests high heterogeneity with study characteristics and methods influencing the associations.
Generalized estimating equations [GEE] were used to assess the influence of study design on effect sizes. GEE is one method that can account for the clustering of multiple comparisons within a single study.52 The odds ratio for each study was used as the dependent variable. Independent variables included world region [Americas, Africa, Asia], researcher label [‘culture-bound …’, ‘idiom …’, ‘popular …’, other ‘… syndrome’ and other label], study objective [compare CCD and psychiatric disorder, instrument validation study, assessment of risk factors for psychological distress, and other], sample size [75%]
| Depression | Coraje, dhat, hwa-byung, jham-jham, koro, shenjing shuairuo, nervios-related labels, ode ori, phiền não tâm thần, susto, yadargaa, yo’kwekyawa | 20 | 9032 | 7.55 | 6.69—8.52 | 6.15 [>75%] | 0.61 | 0.78 | 0.41 | 0.88 |
| General anxiety | Dhat, fright idioms, hwa-byung, jham-jham, koro, lo âu sợ hãi, shenjing shuairuo, nervios-related labels, ode-ori, worry attacks, yadargaa | 16 | 8211 | 5.06 | 4.48—5.70 | 8.70 [>75%] | 0.58 | 0.88 | 0.48 | 0.85 |
| Panic | Dhat, nervios-related labels, trúng gió | 9 | 6158 | 4.48 | 3.77—5.32 | 2.43 [>75%] | 0.30 | 0.91 | 0.37 | 0.89 |
| PTSD | Fright idioms, nervios-related labels, trúng gió, worry attacks | 4 | 1246 | 10.10 | 7.51—13.57 | 0.10 [>75%] | 0.58 | 0.88 | 0.64 | 0.85 |
| All anxiety | Dhat, fright idioms, hwa-byung, jham-jham, koro, lo âu sợ hãi, shenjing shuairuo, nervios-related labels, ode-ori, worry attacks, taein kong po, taijin kyofu sho, trúng gió, yadargaa | 22 | 9731 | 6.12 | 5.49—6.83 | 13.75 [>75%] | 0.50 | 0.86 | 0.53 | 0.85 |
| General psychological distress | Dhat, jham-jham, kufungisisa, kusuwisia, mental problem, nervios-related labels, spiritual problems, tension | 9 | 6658 | 5.39 | 4.71—6.17 | 7.41 [8%] | 0.50 | 0.88 | 0.54 | 0.87 |
| Somatoform disorders | Dhat, shenjing shuairuo, nervios-related labels, xáo trộn tâm thần và thế xác, yadargaa | 7 | 3268 | 2.68 | 2.18—3.28 | 0.67 [>75%] | 0.37 | 0.82 | 0.28 | 0.87 |
Table 4
Meta-analysis for odds of meeting criteria for a psychiatric category among persons endorsing a cultural concept of distress
| Depression | Coraje, dhat, hwa-byung, jham-jham, koro, shenjing shuairuo, nervios-related labels, ode ori, phiền não tâm thần, susto, yadargaa, yo’kwekyawa | 20 | 9032 | 7.55 | 6.69—8.52 | 6.15 [>75%] | 0.61 | 0.78 | 0.41 | 0.88 |
| General anxiety | Dhat, fright idioms, hwa-byung, jham-jham, koro, lo âu sợ hãi, shenjing shuairuo, nervios-related labels, ode-ori, worry attacks, yadargaa | 16 | 8211 | 5.06 | 4.48—5.70 | 8.70 [>75%] | 0.58 | 0.88 | 0.48 | 0.85 |
| Panic | Dhat, nervios-related labels, trúng gió | 9 | 6158 | 4.48 | 3.77—5.32 | 2.43 [>75%] | 0.30 | 0.91 | 0.37 | 0.89 |
| PTSD | Fright idioms, nervios-related labels, trúng gió, worry attacks | 4 | 1246 | 10.10 | 7.51—13.57 | 0.10 [>75%] | 0.58 | 0.88 | 0.64 | 0.85 |
| All anxiety | Dhat, fright idioms, hwa-byung, jham-jham, koro, lo âu sợ hãi, shenjing shuairuo, nervios-related labels, ode-ori, worry attacks, taein kong po, taijin kyofu sho, trúng gió, yadargaa | 22 | 9731 | 6.12 | 5.49—6.83 | 13.75 [>75%] | 0.50 | 0.86 | 0.53 | 0.85 |
| General psychological distress | Dhat, jham-jham, kufungisisa, kusuwisia, mental problem, nervios-related labels, spiritual problems, tension | 9 | 6658 | 5.39 | 4.71—6.17 | 7.41 [8%] | 0.50 | 0.88 | 0.54 | 0.87 |
| Somatoform disorders | Dhat, shenjing shuairuo, nervios-related labels, xáo trộn tâm thần và thế xác, yadargaa | 7 | 3268 | 2.68 | 2.18—3.28 | 0.67 [>75%] | 0.37 | 0.82 | 0.28 | 0.87 |
| Depression | Coraje, dhat, hwa-byung, jham-jham, koro, shenjing shuairuo, nervios-related labels, ode ori, phiền não tâm thần, susto, yadargaa, yo’kwekyawa | 20 | 9032 | 7.55 | 6.69—8.52 | 6.15 [>75%] | 0.61 | 0.78 | 0.41 | 0.88 |
| General anxiety | Dhat, fright idioms, hwa-byung, jham-jham, koro, lo âu sợ hãi, shenjing shuairuo, nervios-related labels, ode-ori, worry attacks, yadargaa | 16 | 8211 | 5.06 | 4.48—5.70 | 8.70 [>75%] | 0.58 | 0.88 | 0.48 | 0.85 |
| Panic | Dhat, nervios-related labels, trúng gió | 9 | 6158 | 4.48 | 3.77—5.32 | 2.43 [>75%] | 0.30 | 0.91 | 0.37 | 0.89 |
| PTSD | Fright idioms, nervios-related labels, trúng gió, worry attacks | 4 | 1246 | 10.10 | 7.51—13.57 | 0.10 [>75%] | 0.58 | 0.88 | 0.64 | 0.85 |
| All anxiety | Dhat, fright idioms, hwa-byung, jham-jham, koro, lo âu sợ hãi, shenjing shuairuo, nervios-related labels, ode-ori, worry attacks, taein kong po, taijin kyofu sho, trúng gió, yadargaa | 22 | 9731 | 6.12 | 5.49—6.83 | 13.75 [>75%] | 0.50 | 0.86 | 0.53 | 0.85 |
| General psychological distress | Dhat, jham-jham, kufungisisa, kusuwisia, mental problem, nervios-related labels, spiritual problems, tension | 9 | 6658 | 5.39 | 4.71—6.17 | 7.41 [8%] | 0.50 | 0.88 | 0.54 | 0.87 |
| Somatoform disorders | Dhat, shenjing shuairuo, nervios-related labels, xáo trộn tâm thần và thế xác, yadargaa | 7 | 3268 | 2.68 | 2.18—3.28 | 0.67 [>75%] | 0.37 | 0.82 | 0.28 | 0.87 |
Potential sources of between-study variation in association of cultural concepts of distress with psychiatric categories
Given the high heterogeneity among the studies, we used generalized estimating equations [GEE] to determine the association of study design with strength of odd ratios between CCD and psychiatric categories [see Table 5]. We conducted 13 bivariate analyses of study characteristics with strengths of odds ratios between CCD and psychiatric disorders. Variables significant in bivariate analyses were entered into the multivariable analysis. In the multivariable analysis, studies conducted in the Americas had greater ORs than those conducted in Africa or Asia; studies labelled as ‘culture-bound’ had greater ORs than any of the other labels; validation studies had ORs 16 points greater than studies in which the objective was to compare CCD with psychiatric disorders; greater sample sizes were associated with greater ORs; self-report multi-item checklists had 6 points greater ORs than dichotomous categorical self-report scores, and medium quality SAQOR-CPE rankings were 7 points below ORs of very low quality studies.
Table 5
Generalized estimating equation for association of study design variables with magnitude of odds ratio between psychiatric category and cultural concept of distress
| World region | Americas | 44 [55.7%] | Ref. | Ref. |
| Africa | 7 [8.9%] | -4.14 [−5.91, −2.36]*** | −8.23 [−13.38, −3.18]** | |
| Asia | 28 [35.4%] | 2.17 [−5.97, 10.31] | −5.44 [−10.26, −0.62]* | |
| Researcher label | ‘Culture-bound … ’ | 15 [19.0%] | Ref. | Ref. |
| ‘Idiom … ’ | 21 [26.6%] | 7.85 [−1.30, 17.01] | −4.67 [−7.63, −1.70]** | |
| ‘Popular … ’ | 9 [11.4%] | 2.08 [−1.00, 5.17] | −3.44 [−6.86, −0.01]* | |
| Other ‘ … syndrome’ | 13 [16.5%] | 3.25 [1.23, 5.27]** | −4.59 [−8.76, −0.41]* | |
| Other label | 21 [26.6%] | 0.37 [−2.01, 2.74] | −4.54 [−7.86, −1.23]** | |
| Study objective | Compare CCD and psychiatric disorder | 47 [59.5%] | Ref. | Ref. |
| Validation | 7 [8.9%] | 17.65 [9.11, 26.18]*** | 16.27 [12.75, 19.79]*** | |
| Assess risk factors | 17 [21.5%] | 2.26 [−0.24, 4.75] | −1.62 [−3.57, 0.33] | |
| Other | 8 [10.1%] | −1.67 [−3.72, 0.38] | −5.08 [−8.61, −1.55]** | |
| Sample size | 1-99 | 20 [25.3%] | Ref. | Ref. |
| 100-499 | 34 [43.0%] | 3.42 [−3.55, 10.39] | −2.13 [−4.68, 0.42] | |
| ≥ 500 | 25 [31.6%] | 3.03 [1.42, 4.64]*** | 6.92 [2.66, 11.17]** | |
| Recruitment site | Clinical | 48 [60.8%] | Ref. | |
| Community | 29 [36.7%] | −0.12 [−5.68, 5.44] | ||
| School | 2 [2.5%] | −2.72 [−9.01, 3.58] | ||
| Representative | No | 50 [63.3%] | Ref. | |
| Yes | 29 [36.7%] | 0.40 [−4.70, 5.51] | ||
| Cultural concept of distress category | Nervios-related labels | 40 [50.6%] | Ref. | Ref. |
| Dhat | 10 [12.7%] | −2.99 [−4.84, −1.15] | −0.15 [−7.72, 7.42] | |
| Hwa-byung | 2 [2.5%] | −3.52 [−5.26, −1.78]*** | 8.02 [−0.04, 16.10] | |
| Other labels | 27 [34.2%] | 3.86 [−4.26, 11.98]** | 3.58 [−2.73, 9.89] | |
| CCD self-eport | No | 19 [24.1%] | Ref. | |
| Yes | 60 [75.9%] | 2.29 [−2.44, 7.03] | ||
| Assessment method for cultural concept of distress | Single-item sel- report | 40 [50.6%] | Ref. | Ref. |
| Self-report multi-item scale score | 18 [22.8%] | 7.51 [−4.69, 19.70] | 6.10 [1.89, 10.31]** | |
| Clinician diagnosis | 8 [10.1%] | −2.28 [−3.82, −0.73]++ | 0.48 [−1.93, 2.89] | |
| Other labelled [parent, key informant] | 13 [16.5%] | 1.59 [−1.21, 4.39] | −2.81 [−5.90, 0.28] | |
| Prevalence | Lifetime | 30 [38.0%] | Ref. | Ref. |
| Current | 33 [41.8%] | 1.68 [−5.34, 8.70] | 6.65 [−0.87, 14.17] | |
| Unclear | 16 [20.3%] | −3.78 [−5.20. −2.36]*** | −6.31 [−13.00, 0.37] | |
| Psychiatric category | General psychological distress | 13 [16.5%] | Ref. | |
| Anxiety disorders | 30 [38.0%] | 2.76 [−1.87, 7.38] | ||
| Mood disorders | 21 [26.6%] | 2.18 [−2.69, 7.05] | ||
| Somatic disorders | 8 [10.1%] | 4.65 [−2.44, 11.74] | ||
| Psychotic and other disorders | 7 [8.9%] | −1.87 [−4.14, 0.39] | ||
| Controlled for comorbidity | Not controlled | 27 [34.2%] | Ref. | |
| Controlled | 52 [65.8%] | −4.56 [−13.06, 3.93] | ||
| SAQOR-CPE ranking | Very Low | 5 [6.3%] | Ref. | Ref. |
| Low | 48 [60.8%] | 2.28 [0.22, 4.33]* | −5.04 [−10.14, 0.06] | |
| Medium | 26 [32.9%] | 6.35 [−1.69, 14.40] | −7.47 [−12.63, −2.30]** |
| World region | Americas | 44 [55.7%] | Ref. | Ref. |
| Africa | 7 [8.9%] | -4.14 [−5.91, −2.36]*** | −8.23 [−13.38, −3.18]** | |
| Asia | 28 [35.4%] | 2.17 [−5.97, 10.31] | −5.44 [−10.26, −0.62]* | |
| Researcher label | ‘Culture-bound … ’ | 15 [19.0%] | Ref. | Ref. |
| ‘Idiom … ’ | 21 [26.6%] | 7.85 [−1.30, 17.01] | −4.67 [−7.63, −1.70]** | |
| ‘Popular … ’ | 9 [11.4%] | 2.08 [−1.00, 5.17] | −3.44 [−6.86, −0.01]* | |
| Other ‘ … syndrome’ | 13 [16.5%] | 3.25 [1.23, 5.27]** | −4.59 [−8.76, −0.41]* | |
| Other label | 21 [26.6%] | 0.37 [−2.01, 2.74] | −4.54 [−7.86, −1.23]** | |
| Study objective | Compare CCD and psychiatric disorder | 47 [59.5%] | Ref. | Ref. |
| Validation | 7 [8.9%] | 17.65 [9.11, 26.18]*** | 16.27 [12.75, 19.79]*** | |
| Assess risk factors | 17 [21.5%] | 2.26 [−0.24, 4.75] | −1.62 [−3.57, 0.33] | |
| Other | 8 [10.1%] | −1.67 [−3.72, 0.38] | −5.08 [−8.61, −1.55]** | |
| Sample size | 1-99 | 20 [25.3%] | Ref. | Ref. |
| 100-499 | 34 [43.0%] | 3.42 [−3.55, 10.39] | −2.13 [−4.68, 0.42] | |
| ≥ 500 | 25 [31.6%] | 3.03 [1.42, 4.64]*** | 6.92 [2.66, 11.17]** | |
| Recruitment site | Clinical | 48 [60.8%] | Ref. | |
| Community | 29 [36.7%] | −0.12 [−5.68, 5.44] | ||
| School | 2 [2.5%] | −2.72 [−9.01, 3.58] | ||
| Representative | No | 50 [63.3%] | Ref. | |
| Yes | 29 [36.7%] | 0.40 [−4.70, 5.51] | ||
| Cultural concept of distress category | Nervios-related labels | 40 [50.6%] | Ref. | Ref. |
| Dhat | 10 [12.7%] | −2.99 [−4.84, −1.15] | −0.15 [−7.72, 7.42] | |
| Hwa-byung | 2 [2.5%] | −3.52 [−5.26, −1.78]*** | 8.02 [−0.04, 16.10] | |
| Other labels | 27 [34.2%] | 3.86 [−4.26, 11.98]** | 3.58 [−2.73, 9.89] | |
| CCD self-eport | No | 19 [24.1%] | Ref. | |
| Yes | 60 [75.9%] | 2.29 [−2.44, 7.03] | ||
| Assessment method for cultural concept of distress | Single-item sel- report | 40 [50.6%] | Ref. | Ref. |
| Self-report multi-item scale score | 18 [22.8%] | 7.51 [−4.69, 19.70] | 6.10 [1.89, 10.31]** | |
| Clinician diagnosis | 8 [10.1%] | −2.28 [−3.82, −0.73]++ | 0.48 [−1.93, 2.89] | |
| Other labelled [parent, key informant] | 13 [16.5%] | 1.59 [−1.21, 4.39] | −2.81 [−5.90, 0.28] | |
| Prevalence | Lifetime | 30 [38.0%] | Ref. | Ref. |
| Current | 33 [41.8%] | 1.68 [−5.34, 8.70] | 6.65 [−0.87, 14.17] | |
| Unclear | 16 [20.3%] | −3.78 [−5.20. −2.36]*** | −6.31 [−13.00, 0.37] | |
| Psychiatric category | General psychological distress | 13 [16.5%] | Ref. | |
| Anxiety disorders | 30 [38.0%] | 2.76 [−1.87, 7.38] | ||
| Mood disorders | 21 [26.6%] | 2.18 [−2.69, 7.05] | ||
| Somatic disorders | 8 [10.1%] | 4.65 [−2.44, 11.74] | ||
| Psychotic and other disorders | 7 [8.9%] | −1.87 [−4.14, 0.39] | ||
| Controlled for comorbidity | Not controlled | 27 [34.2%] | Ref. | |
| Controlled | 52 [65.8%] | −4.56 [−13.06, 3.93] | ||
| SAQOR-CPE ranking | Very Low | 5 [6.3%] | Ref. | Ref. |
| Low | 48 [60.8%] | 2.28 [0.22, 4.33]* | −5.04 [−10.14, 0.06] | |
| Medium | 26 [32.9%] | 6.35 [−1.69, 14.40] | −7.47 [−12.63, −2.30]** |
N = 79 comparisons; number of studies 26. Only items with significant bivariate associations were included in the multivariable model.
*P < .05; **P < .01; ***P < .001.
Table 5
Generalized estimating equation for association of study design variables with magnitude of odds ratio between psychiatric category and cultural concept of distress
| World region | Americas | 44 [55.7%] | Ref. | Ref. |
| Africa | 7 [8.9%] | -4.14 [−5.91, −2.36]*** | −8.23 [−13.38, −3.18]** | |
| Asia | 28 [35.4%] | 2.17 [−5.97, 10.31] | −5.44 [−10.26, −0.62]* | |
| Researcher label | ‘Culture-bound … ’ | 15 [19.0%] | Ref. | Ref. |
| ‘Idiom … ’ | 21 [26.6%] | 7.85 [−1.30, 17.01] | −4.67 [−7.63, −1.70]** | |
| ‘Popular … ’ | 9 [11.4%] | 2.08 [−1.00, 5.17] | −3.44 [−6.86, −0.01]* | |
| Other ‘ … syndrome’ | 13 [16.5%] | 3.25 [1.23, 5.27]** | −4.59 [−8.76, −0.41]* | |
| Other label | 21 [26.6%] | 0.37 [−2.01, 2.74] | −4.54 [−7.86, −1.23]** | |
| Study objective | Compare CCD and psychiatric disorder | 47 [59.5%] | Ref. | Ref. |
| Validation | 7 [8.9%] | 17.65 [9.11, 26.18]*** | 16.27 [12.75, 19.79]*** | |
| Assess risk factors | 17 [21.5%] | 2.26 [−0.24, 4.75] | −1.62 [−3.57, 0.33] | |
| Other | 8 [10.1%] | −1.67 [−3.72, 0.38] | −5.08 [−8.61, −1.55]** | |
| Sample size | 1-99 | 20 [25.3%] | Ref. | Ref. |
| 100-499 | 34 [43.0%] | 3.42 [−3.55, 10.39] | −2.13 [−4.68, 0.42] | |
| ≥ 500 | 25 [31.6%] | 3.03 [1.42, 4.64]*** | 6.92 [2.66, 11.17]** | |
| Recruitment site | Clinical | 48 [60.8%] | Ref. | |
| Community | 29 [36.7%] | −0.12 [−5.68, 5.44] | ||
| School | 2 [2.5%] | −2.72 [−9.01, 3.58] | ||
| Representative | No | 50 [63.3%] | Ref. | |
| Yes | 29 [36.7%] | 0.40 [−4.70, 5.51] | ||
| Cultural concept of distress category | Nervios-related labels | 40 [50.6%] | Ref. | Ref. |
| Dhat | 10 [12.7%] | −2.99 [−4.84, −1.15] | −0.15 [−7.72, 7.42] | |
| Hwa-byung | 2 [2.5%] | −3.52 [−5.26, −1.78]*** | 8.02 [−0.04, 16.10] | |
| Other labels | 27 [34.2%] | 3.86 [−4.26, 11.98]** | 3.58 [−2.73, 9.89] | |
| CCD self-eport | No | 19 [24.1%] | Ref. | |
| Yes | 60 [75.9%] | 2.29 [−2.44, 7.03] | ||
| Assessment method for cultural concept of distress | Single-item sel- report | 40 [50.6%] | Ref. | Ref. |
| Self-report multi-item scale score | 18 [22.8%] | 7.51 [−4.69, 19.70] | 6.10 [1.89, 10.31]** | |
| Clinician diagnosis | 8 [10.1%] | −2.28 [−3.82, −0.73]++ | 0.48 [−1.93, 2.89] | |
| Other labelled [parent, key informant] | 13 [16.5%] | 1.59 [−1.21, 4.39] | −2.81 [−5.90, 0.28] | |
| Prevalence | Lifetime | 30 [38.0%] | Ref. | Ref. |
| Current | 33 [41.8%] | 1.68 [−5.34, 8.70] | 6.65 [−0.87, 14.17] | |
| Unclear | 16 [20.3%] | −3.78 [−5.20. −2.36]*** | −6.31 [−13.00, 0.37] | |
| Psychiatric category | General psychological distress | 13 [16.5%] | Ref. | |
| Anxiety disorders | 30 [38.0%] | 2.76 [−1.87, 7.38] | ||
| Mood disorders | 21 [26.6%] | 2.18 [−2.69, 7.05] | ||
| Somatic disorders | 8 [10.1%] | 4.65 [−2.44, 11.74] | ||
| Psychotic and other disorders | 7 [8.9%] | −1.87 [−4.14, 0.39] | ||
| Controlled for comorbidity | Not controlled | 27 [34.2%] | Ref. | |
| Controlled | 52 [65.8%] | −4.56 [−13.06, 3.93] | ||
| SAQOR-CPE ranking | Very Low | 5 [6.3%] | Ref. | Ref. |
| Low | 48 [60.8%] | 2.28 [0.22, 4.33]* | −5.04 [−10.14, 0.06] | |
| Medium | 26 [32.9%] | 6.35 [−1.69, 14.40] | −7.47 [−12.63, −2.30]** |
| World region | Americas | 44 [55.7%] | Ref. | Ref. |
| Africa | 7 [8.9%] | -4.14 [−5.91, −2.36]*** | −8.23 [−13.38, −3.18]** | |
| Asia | 28 [35.4%] | 2.17 [−5.97, 10.31] | −5.44 [−10.26, −0.62]* | |
| Researcher label | ‘Culture-bound … ’ | 15 [19.0%] | Ref. | Ref. |
| ‘Idiom … ’ | 21 [26.6%] | 7.85 [−1.30, 17.01] | −4.67 [−7.63, −1.70]** | |
| ‘Popular … ’ | 9 [11.4%] | 2.08 [−1.00, 5.17] | −3.44 [−6.86, −0.01]* | |
| Other ‘ … syndrome’ | 13 [16.5%] | 3.25 [1.23, 5.27]** | −4.59 [−8.76, −0.41]* | |
| Other label | 21 [26.6%] | 0.37 [−2.01, 2.74] | −4.54 [−7.86, −1.23]** | |
| Study objective | Compare CCD and psychiatric disorder | 47 [59.5%] | Ref. | Ref. |
| Validation | 7 [8.9%] | 17.65 [9.11, 26.18]*** | 16.27 [12.75, 19.79]*** | |
| Assess risk factors | 17 [21.5%] | 2.26 [−0.24, 4.75] | −1.62 [−3.57, 0.33] | |
| Other | 8 [10.1%] | −1.67 [−3.72, 0.38] | −5.08 [−8.61, −1.55]** | |
| Sample size | 1-99 | 20 [25.3%] | Ref. | Ref. |
| 100-499 | 34 [43.0%] | 3.42 [−3.55, 10.39] | −2.13 [−4.68, 0.42] | |
| ≥ 500 | 25 [31.6%] | 3.03 [1.42, 4.64]*** | 6.92 [2.66, 11.17]** | |
| Recruitment site | Clinical | 48 [60.8%] | Ref. | |
| Community | 29 [36.7%] | −0.12 [−5.68, 5.44] | ||
| School | 2 [2.5%] | −2.72 [−9.01, 3.58] | ||
| Representative | No | 50 [63.3%] | Ref. | |
| Yes | 29 [36.7%] | 0.40 [−4.70, 5.51] | ||
| Cultural concept of distress category | Nervios-related labels | 40 [50.6%] | Ref. | Ref. |
| Dhat | 10 [12.7%] | −2.99 [−4.84, −1.15] | −0.15 [−7.72, 7.42] | |
| Hwa-byung | 2 [2.5%] | −3.52 [−5.26, −1.78]*** | 8.02 [−0.04, 16.10] | |
| Other labels | 27 [34.2%] | 3.86 [−4.26, 11.98]** | 3.58 [−2.73, 9.89] | |
| CCD self-eport | No | 19 [24.1%] | Ref. | |
| Yes | 60 [75.9%] | 2.29 [−2.44, 7.03] | ||
| Assessment method for cultural concept of distress | Single-item sel- report | 40 [50.6%] | Ref. | Ref. |
| Self-report multi-item scale score | 18 [22.8%] | 7.51 [−4.69, 19.70] | 6.10 [1.89, 10.31]** | |
| Clinician diagnosis | 8 [10.1%] | −2.28 [−3.82, −0.73]++ | 0.48 [−1.93, 2.89] | |
| Other labelled [parent, key informant] | 13 [16.5%] | 1.59 [−1.21, 4.39] | −2.81 [−5.90, 0.28] | |
| Prevalence | Lifetime | 30 [38.0%] | Ref. | Ref. |
| Current | 33 [41.8%] | 1.68 [−5.34, 8.70] | 6.65 [−0.87, 14.17] | |
| Unclear | 16 [20.3%] | −3.78 [−5.20. −2.36]*** | −6.31 [−13.00, 0.37] | |
| Psychiatric category | General psychological distress | 13 [16.5%] | Ref. | |
| Anxiety disorders | 30 [38.0%] | 2.76 [−1.87, 7.38] | ||
| Mood disorders | 21 [26.6%] | 2.18 [−2.69, 7.05] | ||
| Somatic disorders | 8 [10.1%] | 4.65 [−2.44, 11.74] | ||
| Psychotic and other disorders | 7 [8.9%] | −1.87 [−4.14, 0.39] | ||
| Controlled for comorbidity | Not controlled | 27 [34.2%] | Ref. | |
| Controlled | 52 [65.8%] | −4.56 [−13.06, 3.93] | ||
| SAQOR-CPE ranking | Very Low | 5 [6.3%] | Ref. | Ref. |
| Low | 48 [60.8%] | 2.28 [0.22, 4.33]* | −5.04 [−10.14, 0.06] | |
| Medium | 26 [32.9%] | 6.35 [−1.69, 14.40] | −7.47 [−12.63, −2.30]** |
N = 79 comparisons; number of studies 26. Only items with significant bivariate associations were included in the multivariable model.
*P < .05; **P < .01; ***P < .001.
Discussion
Within the growing body of literature comparing cultural concepts of distress [CCD] and psychiatric disorders, there is a wide range of quality and epidemiological rigor. Twelve [27%] of the studies had medium quality based on the Systematic Assessment of Quality in Observational Research–Cultural Psychiatry Epidemiology [SAQOR-CPE] ranking system. The remainder were of low or very low quality. Studies lack both basic criteria for epidemiological reporting [e.g. representative samples, prevalence parameters, missing data frequency and management, and controlling for potential confounds] and key aspects of CCD reporting [e.g. differentiation among symptoms, syndromes, and aetiological models; operationalization of cultural and ethnic groups to generalize findings; assessment of confounders; and severity and course of distress].
Making generalizations based on summary effects from meta-analysis is impeded by the high degree of heterogeneity in all but one of the analyses. The high degree of heterogeneity is not surprising given the wide range of quality and methodological approaches among the studies. Studies conducted in the Americas were more likely to show an association of CCD with psychiatric disorders. This may represent acculturation issues among the populations studied because most of the participants were immigrants in the USA. Phan and colleagues suggested that CCD were strongly associated with psychiatric disorders among Vietnamese immigrants in Australia because of acculturation effects that reframe understandings of mental health and disorder.92
We were surprised to find that studies in which the researcher referred to the CCD as ‘culture-bound’ had stronger associations between the CCD and psychiatric disorders than all other labels. This was counter-intuitive given that ‘culture-bound’ implies a distinction from psychiatric nosology. However, we found that labels such as ‘culture-bound’ or ‘idioms of distress’ were not applied systematically. The same CCD, e.g. ataques de nervios, was described as a culture-bound syndrome, idiom of distress, and popular category by different researchers. Moreover, the category labels for CCD change between studies even within single research teams. Therefore, we do not suggest that comparing studies based on the label used is an informative lens and may lead to potentially spurious associations.
The finding that validation studies were most likely to show an association between CCD and psychiatric disorders is expected, given that in validation studies researchers likely try to identify the CCD that are most similar to a psychiatric category. Furthermore, there is high likelihood of a publication bias in validation studies with negative findings less likely to be published [it is rare to read a published negative validation study]. The same publication bias may not hold for studies comparing CCD and psychiatric disorders that have negative findings, as this would still be theoretically significant for culture-bound suppositions. Multi-item checklists for CCD assessment were associated with stronger associations between CCD and psychiatric disorders. This is consistent with checklists operating more similarly to psychiatric diagnostic criteria. Studies in which single items are used for CCD endorsement likely enable greater diversity of manifestations and framings.
The final noteworthy finding of our review is that medium quality studies had weaker associations between CCD and psychiatric disorders than very low quality studies [no high quality studies were identified in this review]. This raises a crucial issue: we do not hypothesize that greater epidemiological rigor will foster stronger associations between CCD and psychiatric disorders. The converse is equally likely: more rigorous and culturally appropriate studies [as recognized by higher SAQOR-CPE rankings] may represent studies that describe CCD more accurately and thus capture the uniqueness from psychiatric categories. For example, studies than controlled for psychiatric and physical health comorbidities had weaker associations than those not controlling for comorbidity. One of the most important quality issues was better documentation of CCD course and timing in association with psychiatric disorders. Future studies that closely document course and use longitudinal designs in well-contextualized community settings will shed new light on the experience and meaning of CCD and their association psychiatric pathological categories. Emulating the work of pioneers in psychiatric epidemiology, such as Alexander Leighton who followed a rural population in Canada over decades to understand life trajectories of mental illness, can help inform future studies.28,117,118
Limitations
The objective of this review was to provide an overview of the quality of epidemiological studies comparing CCD and psychiatric disorders. Whereas the issues highlighted here and the recommendations provided can be used to strengthen the epidemiological rigor of CCD studies, we caution against generalizing the findings beyond the literature identified here. We limited our initial search of the literature to PubMed/MEDLINE and English-language publications. All of studies were coded by the first author; future reviews should include multiple coders with inter-rater reliability metrics. Future research also should incorporate databases such as PsycInfo, which may include more rigorous psychological studies, and Web of Science, which will capture social science and medical anthropological journals not indexed in PubMed. Inclusion of books and book chapters would also bolster the social science representation. Ultimately, to make broad claims about the association of CCD and psychiatric disorders, access to investigators’ original data would be most helpful because many of the shortcomings reported here may reflect what is reported rather than what is collected. We hope that the adaptation of the SAQOR-CPE can be applied to broader searches and to the design of future cultural psychiatric epidemiology studies.
Applications to global mental health
The DSM-5 and other publications have provided recommendations for the application of CCD to improve clinical care.15,119 CCD also can be applied to improve research and public health interventions in global mental health, with special attention to low resource settings:
CCD can be used to enhance screening and detection of mental health problems. – The CCD literature demonstrates an overlap with psychiatric disorders as well as identification of populations with emotional, behavioral, or cognitive problems with significant impairment that may not be captured by psychiatric diagnoses. The single summary effect with low heterogeneity in our analyses was the comparison of CCD and general psychological distress: persons with any CCD have five-fold greater odds of having general psychological distress than persons not endorsing CCD. Furthermore, in order for global mental health not to be limited to treating only disorders recognized by Western biomedical psychiatry, it will be crucial to consider how scaling up services can also address CCD. CCD feasibly can be incorporated into psychiatric screeners such as the PHQ-9 through the addition of a limited number of questions. Among Latinas, the addition of CCD identifies distress not captured by standard PHQ-9 implementation.61 In Zimbabwe, the Shona Symptom Questionnaire adequately captures common mental disorders including postpartum distress and has the benefit of including idioms that represent key concerns of both local patient populations and traditional healers.89,120
CCD are key to assessing treatments and interventions in global mental health. – One of the major shortcomings of the current literature was the lack of CCD in treatment studies. If interventions reduce psychiatric symptoms but do not impact CCD, then individuals will be likely to continue treatment seeking and report functional impairment. In order for interventions to be used and sustained they will need to demonstrate that local concerns and CCD also are improved. Cultural adaptation of psychotherapy is a promising area to address CCD as well as psychiatric problems. Culturally adapted CBT has positive outcomes for ataque de nervios and a number of Southeast Asian CCD75,106,121-124 as did treatment with SSRIs.135 Whereas psychotherapy as practiced in hospital settings in India does not appear culturally compelling for treatment of dhat,59,67,69 clinical trials of SSRIs would be ideal because they can improve not only psychological distress but also reduce premature ejaculation and other complaints associated with dhat.
CCD can highlight vulnerable populations for public health measures and secondary prevention initiatives. – Despite variable associations of CCD with psychiatric disorders, they are consistently associated with identifying vulnerable populations. CCD are a marker of risk groups and may indicate a prodrome to psychiatric disorders. Public health and non-clinical psychosocial interventions should be investigated with CCD-endorsing populations as a possible avenue of mental health promotion and disorder prevention.
Cross-cultural comparison studies of CCD can help illuminate biases and limitations in psychiatric categories. – One study in our review demonstrated that offense-avoidance symptoms are common among Americans with social phobia similar to Koreans with TKS.65 This draws attention to therapeutic needs to address offense-avoidance in American social phobia patients, as well as the need to potentially add these to DSM criteria as symptoms of interest [current TKS features are limited to ‘culture-related diagnostic issues’ in DSM-5, p.20515]. Similarly, cross-cultural comparisons of ataque de nervios demonstrate that interpersonal-distress induced anxiety and loss of control are also observable among European Americans and are not synonymous with panic disorder.76 Therefore, the therapeutic need to address aspects of ataques in non-Latino populations could be considered. A number of studies demonstrated that some symptom requirements in psychiatric disorders may lead to exclusion of treatment for distressed persons from other cultural groups. For example, requiring that panic attacks be unprovoked would exclude Cambodian patients for whom catastrophic cognitions related to orthostatic hypotension and ethnophysiological expectations of khyal trigger attacks.125 Ultimately, cross-national studies that include a range of CCD features as well as psychiatric diagnoses are needed to reduce cultural bias in psychiatric nosology and help address unmet needs in both high-income and low- and middle-income settings.
Conclusions
Despite claims that cultural concepts of distress are not amenable to epidemiological study, our literature review demonstrated a range of important contributions of CCD epidemiological studies to detection of mental health problems, evaluation of interventions, identification of vulnerable groups, and identification of cultural biases in psychiatric diagnostic criteria. The literature, however, suffers from a lack of epidemiological rigor and lack of comprehensive data collection about key issues in CCD. Tools such as the SAQOR-CPE are needed to systematically evaluate this literature and establish guidelines for research design and reporting for global mental health studies. Ultimately, combining the strengths of psychiatric epidemiology and cultural psychiatry will foster equitable, feasible, and effective global mental health services.
Funding
This work was supported by the National Institute of Mental Health [U19 MH095687-01S1, South Asian Hub for Advocacy, Research & Education on Mental Health [SHARE], Principal Investigators: Vikram Patel and Atif Rahman] supplement for continuity of research experience during clinical training provided to the first author [BAK]. Author BNK is supported by the National Science Foundation Graduate Research Fellowship [Grant No. 0234618].
Conflict of interest: None declared.
Epidemiology studies of cultural concepts of distress can improve global mental health services through improved detection of psychological distress, identification of risk groups and assessment of culturally salient intervention outcomes.
The literature on cultural concepts of distress and psychiatric disorders is characterized by low epidemiological rigor [e.g. unclear prevalence reporting, use of non-validated instruments and lack of control for confounding] and lack of reporting key facets of explanatory models [e.g. aetiological attributions, course and severity of distress, and association with impaired functioning].
Treatment and intervention studies including both psychiatric disorders and cultural concepts of distress demonstrate independent changes in these outcomes. Future global mental health intervention research should include both psychiatric outcomes and cultural concepts of distress to assure that culturally salient indicators of distress also resolve in treatment trials.
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Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2013; all rights reserved.
Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2013; all rights reserved.
Topic:
- epidemiology
- heterogeneity
- mental disorders
- mental health
- psychiatry
- post-traumatic stress disorder
- diagnosis
- culture-bound syndromes
- cultural psychiatry
- cultural concepts of distress