Evaluation of diversity characteristics in a large mental healthcare data platform and their use in research publications: a cross-sectional review.

چکیده اصلی

BACKGROUND: Reporting diversity characteristics is required for more inclusive, equitable and policy-relevant research. OBJECTIVES: To evaluate the reporting of diversity characteristics in publications using a large mental healthcare electronic health record (EHR)-derived research data resource, and to compare reporting of these characteristics in publications with their availabilities in the underlying dataset. DESIGN: Cross-sectional review of Clinical Record Interactive Search (CRIS)-derived publications and assessment of diversity characteristic availability within the underlying EHR-derived database. SETTING: The South London and Maudsley (SLaM) National Health Service (NHS) Foundation Trust Biomedical Research Centre Case Register, accessed via the CRIS platform, representing secondary mental healthcare delivered to a geographic catchment area covering four boroughs in south London. METHODS AND ANALYSIS: All CRIS-derived publications were reviewed to ascertain reporting of protected characteristics, as defined in the UK Equality Act 2010, alongside additional diversity-related characteristics. The availability of each characteristic within CRIS was assessed from records available up to 15 April 2026. Descriptive statistics were used to summarise reporting and data availability. RESULTS: A total of 362 publications were evaluated. The mean number of diversity characteristics reported per publication was 4.0, and no publication reported more than 10 characteristics. Age (89.3%), sex (87.3%) and ethnicity (80.4%) were the most frequently reported characteristics. Socioeconomic status was reported in 42.5% of publications, while marriage and civil partnership (35.0%) and disability (27.0%) were reported in a smaller proportion of studies. All remaining characteristics were reported in less than 10% of publications.Data availability within CRIS was highest for sex (99.9%) and age (99.8%), followed by socioeconomic status, geographic location and homelessness (all 97.5%) and ethnicity (86.5%). However, several characteristics were reported far less frequently than they were available in the dataset, particularly geographic location (6.6% reported despite 97.5% availability) and homelessness (5.8% reported despite 97.5% availability). CONCLUSIONS: Reporting of diversity characteristics in this case study for EHR-based mental health research was uneven and did not fully reflect availability in the source data. While age, sex and ethnicity are commonly reported, several other protected and diversity-related characteristics are rarely used by researchers despite their availability, and other characteristics remain challenging to capture. As routine EHR-derived datasets increasingly inform mental health research and policy, greater attention to recording, accessibility and reporting of diversity characteristics is required to support more inclusive and representative research.

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