Evidence map›Paper›PMID 42559019›Full record

ArticleFrontiers in digital health2026

Culturally sensitive approaches in digital mental health research: lessons learned from co-developing the core mental health dataset.

Heidi Tranter, Madeleine France Ratcliffe, Thomas Price, Auden Edwardes, Pauline Whelan, Kathryn M Abel

Abstract read
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Heidi TranterGM.Digital Research Unit, Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom.
Madeleine France RatcliffeDepartment of Sport and Exercise Science, Manchester Metropolitan University, Manchester, United Kingdom.
Thomas PriceGM.Digital Research Unit, Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom.
Auden EdwardesGM.Digital Research Unit, Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom.
Pauline WhelanGM.Digital Research Unit, Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom.
Kathryn M AbelGM.Digital Research Unit, Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cultural sensitivity is central to ethical and valid mental health research, yet we observed it is often insufficiently embedded in digital research tools. Drawing on qualitative work conducted during the co-development of the Core Mental Health Dataset (CMHDS), this commentary reflects on the practical challenges we encountered and the considerations which shaped our approach to culturally sensitive data collection in digital mental health research. We synthesise insights from a lived experience advisory group, recognising how our interpretations were informed through dialogue with participants, focusing on mental health terminology, perceptions of mental health and ethical considerations in research. This paper shares lessons learned from co-developing the CMHDS and advocates for culturally sensitive digital approaches to improve acceptability, inclusivity, and data quality. We emphasises the requirement of sustained co-production and ongoing reflexive design practices in addressing cultural sensitivity in digital mental health research.

Indexed as

co-developmentcultural sensitivitymental healthmental health dataPPIE

Identifiers

PMID42559019
PMCPMC13438297

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.