• PLoS medicine · Dec 2022

    Review

    Understanding ethnic inequalities in mental healthcare in the UK: A meta-ethnography.

    • Narinder Bansal, Saffron Karlsen, Sashi P Sashidharan, Rachel Cohen, Carolyn A Chew-Graham, and Alice Malpass.
    • Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
    • PLoS Med. 2022 Dec 1; 19 (12): e1004139e1004139.

    BackgroundEvidence regarding the presence and persistence of ethnic inequalities in mental healthcare is well established. The reasons for these inequalities and lack of progress in diminishing them are less understood. This meta-ethnography aims to provide a new conceptual understanding of how ethnic inequalities are created and sustained; this is essential to develop effective interventions. Specifically, we sought to understand why people from ethnic minority groups are underrepresented in primary care mental health service provision and overrepresented in crisis pathways and detention.Methods And FindingsFollowing eMERGe guidelines for meta-ethnographies, we searched OpenGrey, Kings Fund, CINAHL, Medline, PsycINFO, and Social Care Online databases for qualitative articles published from database inception until October 2, 2022, using broad categories of search terms relating to "ethnicity AND (mental illness/mental health/emotional distress) AND (help-seeking/service utilisation/experience/perception/view)." We included all conceptually rich articles that used qualitative methods of data collection and analysis and excluded non-UK studies and those that focused solely on causation of mental illness. Our patient, public, and practitioner lived experience advisory group provided feedback and input on key stages of the project including search terms, research questions, data analysis, and dissemination. A total of 14,142 articles were identified; 66 met the inclusion criteria. We used reciprocal, refutational, and line of argument analytical approaches to identify convergence and divergence between studies. The synthesis showed that current models of statutory mental healthcare are experienced as a major barrier to the delivery of person-centred care to those in ethnic minority groups due to the perceived dominance of monocultural and reductionist frameworks of assessment and treatment (described as "medical" and "Eurocentric") and direct experiences of racist practice. The lack of socially oriented and holistic frameworks of knowledge and understanding in medical training and services is experienced as epistemic injustice, particularly among those who attribute their mental illness to experiences of migration, systemic racism, and complex trauma. Fear of harm, concerns about treatment suitability, and negative experiences with health providers such as racist care and medical neglect/injury contribute to avoidance of, and disengagement from, mainstream healthcare. The lack of progress in tackling ethnic inequalities is attributed to failures in coproduction and insufficient adoption of existing recommendations within services. Study limitations include insufficient recording of participant characteristics relating to generational status and social class in primary studies, which prevented exploration of these intersections.ConclusionsIn this study, we found that the delivery of safe and equitable person-centred care requires a model of mental health that is responsive to the lived experiences of people in ethnic minority groups. For the people considered in this review, this requires better alignment of mental health services with social and anti-racist models of care. Our findings suggest that intersections related to experiences of racism, migration, religion, and complex trauma might be more relevant than crude ethnic group classifications. Strategies to tackle ethnic inequalities in mental healthcare require an evaluation of individual, systemic, and structural obstacles to authentic and meaningful coproduction and implementation of existing community recommendations in services.Copyright: © 2022 Bansal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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