The integration of idioms of distress into mental health assessments and interventions: a systematic review

Cork, Cliodhna; Kaiser, Bonnie N.; White, Ross

doi:10.1017/gmh.2019.5

Cited by 42 publications

(36 citation statements)

References 51 publications

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“…The study demonstrated change in a locally meaningful outcome: “heart–mind problems”. Few prior studies have included locally salient outcomes [ 52 ], which are important to promote engagement, adherence, and scale-up, as well as minimize stigma [ 16 , 53 ]. The intervention and associated implementation materials also underwent a rigorous cultural adaptation process to assure validity of the concepts and strategies for Nepali language and culture [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

Effectiveness of Group Problem Management Plus, a brief psychological intervention for adults affected by humanitarian disasters in Nepal: A cluster randomized controlled trial

et al. 2021

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Background Globally, 235 million people are impacted by humanitarian emergencies worldwide, presenting increased risk of experiencing a mental disorder. Our objective was to test the effectiveness of a brief group psychological treatment delivered by trained facilitators without prior professional mental health training in a disaster-prone setting. Methods and findings We conducted a cluster randomized controlled trial (cRCT) from November 25, 2018 through September 30, 2019. Participants in both arms were assessed at baseline, midline (7 weeks post-baseline, which was approximately 1 week after treatment in the experimental arm), and endline (20 weeks post-baseline, which was approximately 3 months posttreatment). The intervention was Group Problem Management Plus (PM+), a psychological treatment of 5 weekly sessions, which was compared with enhanced usual care (EUC) consisting of a family psychoeducation meeting with a referral option to primary care providers trained in mental healthcare. The setting was 72 wards (geographic unit of clustering) in eastern Nepal, with 1 PM+ group per ward in the treatment arm. Wards were eligible if they were in disaster-prone regions and residents spoke Nepali. Wards were assigned to study arms based on covariate constrained randomization. Eligible participants were adult women and men 18 years of age and older who met screening criteria for psychological distress and functional impairment. Outcomes were measured at the participant level, with assessors blinded to group assignment. The primary outcome was psychological distress assessed with the General Health Questionnaire (GHQ-12). Secondary outcomes included depression symptoms, posttraumatic stress disorder (PTSD) symptoms, “heart–mind” problems, social support, somatic symptoms, and functional impairment. The hypothesized mediator was skill use aligned with the treatment’s mechanisms of action. A total of 324 participants were enrolled in the control arm (36 wards) and 319 in the Group PM+ arm (36 wards). The overall sample (N = 611) had a median age of 45 years (range 18–91 years), 82% of participants were female, 50% had recently experienced a natural disaster, and 31% had a chronic physical illness. Endline assessments were completed by 302 participants in the control arm (36 wards) and 303 participants in the Group PM+ arm (36 wards). At the midline assessment (immediately after Group PM+ in the experimental arm), mean GHQ-12 total score was 2.7 units lower in Group PM+ compared to control (95% CI: 1.7, 3.7, p < 0.001), with standardized mean difference (SMD) of −0.4 (95% CI: −0.5, −0.2). At 3 months posttreatment (primary endpoint), mean GHQ-12 total score was 1.4 units lower in Group PM+ compared to control (95% CI: 0.3, 2.5, p = 0.014), with SMD of −0.2 (95% CI: −0.4, 0.0). Among the secondary outcomes, Group PM+ was associated with endline with a larger proportion attaining more than 50% reduction in depression symptoms (29.9% of Group PM+ arm versus 17.3% of control arm, risk ratio = 1.7, 95% CI: 1.2, 2.4, p = 0.002). Fewer participants in the Group PM+ arm continued to have “heart–mind” problems at endline (58.8%) compared to the control arm (69.4%), risk ratio = 0.8 (95% CI, 0.7, 1.0, p = 0.042). Group PM+ was not associated with lower PTSD symptoms or functional impairment. Use of psychosocial skills at midline was estimated to explain 31% of the PM+ effect on endline GHQ-12 scores. Adverse events in the control arm included 1 suicide death and 1 reportable incidence of domestic violence; in the Group PM+ arm, there was 1 death due to physical illness. Study limitations include lack of power to evaluate gender-specific effects, lack of long-term outcomes (e.g., 12 months posttreatment), and lack of cost-effectiveness information. Conclusions In this study, we found that a 5-session group psychological treatment delivered by nonspecialists modestly reduced psychological distress and depression symptoms in a setting prone to humanitarian emergencies. Benefits were partly explained by the degree of psychosocial skill use in daily life. To improve the treatment benefit, future implementation should focus on approaches to enhance skill use by PM+ participants. Trial registration ClinicalTrials.gov NCT03747055.

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Section: Discussionmentioning

confidence: 99%

Effectiveness of Group Problem Management Plus, a brief psychological intervention for adults affected by humanitarian disasters in Nepal: A cluster randomized controlled trial

et al. 2021

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“…For developers that adopt a lexical approach, dictionaries that pay particular attention to culturally different expressions of mental health will be beneficial. Kohrt et al provide a systematic review of transcultural psychiatry and the different cultural idioms of distress that warrant greater attention [ 33 ]. Integrating such vocabulary into the dictionaries of lexical models could mitigate the negative impact of unequal cultural representation in existing psychiatric literature.…”

Section: 0 Discussionmentioning

confidence: 99%

“…Desai and Chaturvedi describe how "idioms of distress" differ between cultural communities and detail how the psychological symptoms in traditional cultures may not fit within existing western psychiatric frameworks [31]. Non-western expressions of mental illness are often not captured in the mental health literature and will therefore be missed by NLP models that are based on our existing medical assessments [31][32][33][34][35][36].…”

Section: Expression Of Datamentioning

confidence: 99%

Artificial Intelligence in mental health and the biases of language based models

Straw

Callison-Burch

2020

PLoS ONE

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Background The rapid integration of Artificial Intelligence (AI) into the healthcare field has occurred with little communication between computer scientists and doctors. The impact of AI on health outcomes and inequalities calls for health professionals and data scientists to make a collaborative effort to ensure historic health disparities are not encoded into the future. We present a study that evaluates bias in existing Natural Language Processing (NLP) models used in psychiatry and discuss how these biases may widen health inequalities. Our approach systematically evaluates each stage of model development to explore how biases arise from a clinical, data science and linguistic perspective. Design/Methods A literature review of the uses of NLP in mental health was carried out across multiple disciplinary databases with defined Mesh terms and keywords. Our primary analysis evaluated biases within ‘GloVe’ and ‘Word2Vec’ word embeddings. Euclidean distances were measured to assess relationships between psychiatric terms and demographic labels, and vector similarity functions were used to solve analogy questions relating to mental health. Results Our primary analysis of mental health terminology in GloVe and Word2Vec embeddings demonstrated significant biases with respect to religion, race, gender, nationality, sexuality and age. Our literature review returned 52 papers, of which none addressed all the areas of possible bias that we identify in model development. In addition, only one article existed on more than one research database, demonstrating the isolation of research within disciplinary silos and inhibiting cross-disciplinary collaboration or communication. Conclusion Our findings are relevant to professionals who wish to minimize the health inequalities that may arise as a result of AI and data-driven algorithms. We offer primary research identifying biases within these technologies and provide recommendations for avoiding these harms in the future.

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“…Piloting of the translated items prior to study implementation and qualitative research exploring perceptions of depression and how it relates to interpersonal issues (a domain that was not represented in our reduced scale) and positive affect in this context could also shed light on why items in these two domains performed so poorly and serve as a starting point for generation of a new pool of items to be piloted as part of the scale in this setting. Evidence from other developing countries suggests that the generation of new items with local idioms, either for a new scale or to replace poorly performing items in an existing scale, can generate a more precise measure of depression [43].…”

Section: Public Health Significance and Recommendationsmentioning

confidence: 99%

Challenges in measuring depression among Ugandan fisherfolk: a psychometric assessment of the Luganda version of the Center for Epidemiologic Studies Depression Scale (CES-D)

Miller

Kintu²,

Kiene

2020

BMC Psychiatry

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Background: Depression is a prevalent and serious mood disorder and a major source of disability adjusted life years (DALY) in Uganda. Furthermore, evidence from Uganda and other countries throughout sub-Saharan Africa suggests that nearly a third of persons living with human immunodeficiency virus (HIV) suffer from depression and it adversely affects healthcare seeking behavior. The high burden of disease attributable to depression makes data on the prevalence of depression in Uganda, a country with a generalized HIV epidemic, a public health priority. This paper describes the psychometric properties of the Center for Epidemiologic Studies-Depression (CES-D) measure when administered to men and women residing in three fishing communities along the shore of Lake Victoria. Methods: We applied methods based on item response theory and classical test theory approaches to assess individual item characteristics, conducted exploratory factor analysis and assessed internal reliability, and construct and content validity of the measure. All analyses were performed in R Studio. Results: The study sample consisted of 300 residents of fishing communities in Wakiso District, Uganda. Fifty-six percent of the sample was female and 19.7% reported being HIV positive. Seven items of the measure that did not perform well, either because they could not differentiate between levels of the latent trait or because they did not map onto the primary factor, were removed from the scale. A single factor structure best fit our final set of 13items and we found an overall coefficient alpha of 0.89, indicating high internal consistency in this population. Conclusions: Based on our findings, we recommend that future use of the CES-D in this population utilize our revised scale with the final set of 13-items. The addition of other measures that can improve the rigor of CES-D validation efforts, such as inclusion of a clinical depression measure and administration in both a clinical and a general population sample in this setting are needed.

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The integration of idioms of distress into mental health assessments and interventions: a systematic review

Cited by 42 publications

References 51 publications

Effectiveness of Group Problem Management Plus, a brief psychological intervention for adults affected by humanitarian disasters in Nepal: A cluster randomized controlled trial

Effectiveness of Group Problem Management Plus, a brief psychological intervention for adults affected by humanitarian disasters in Nepal: A cluster randomized controlled trial

Artificial Intelligence in mental health and the biases of language based models

Challenges in measuring depression among Ugandan fisherfolk: a psychometric assessment of the Luganda version of the Center for Epidemiologic Studies Depression Scale (CES-D)

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