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Record W4414853152 · doi:10.1186/s12913-025-13438-6

Qualitative evaluation of the perceived impacts of a task-sharing mental health intervention

2025· article· en· W4414853152 on OpenAlexafffund
Marilyn N. Ahun, Chanelle N. Lawson-Lartego, Jesse Blakor, Nutifafa Eugene Yaw Dey, Angela Ofori-Atta

Bibliographic record

VenueBMC Health Services Research · 2025
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersFondation de l'Hôpital de Montréal pour enfantsChildren's Hospital FoundationMcGill University
KeywordsMental healthThematic analysisCLARITYFocus groupPublic healthHealth informaticsQualitative researchIntervention (counseling)

Abstract

fetched live from OpenAlex

BACKGROUND: Mental health is a global public good essential for human development. Yet there exist vast inequities in the distribution of and access to mental health resources within and between countries. To address these inequities, a non-governmental organization in Ghana, Psych Corps Ghana (PCG), leveraged the country’s National Service program to train psychology graduates to provide psychological first-aid. The objective of this study was to qualitatively evaluate the experiences of different stakeholders involved in PCG’s task-sharing intervention. METHODS: We conducted a qualitative study in Accra, Ghana. Convenience sampling was used to recruit a diverse sample of adults involved with the intervention: Psych Corps members (recent psychology graduates who delivered the intervention during their National Service placement), mental health professionals (supervisors and co-workers of Psych Corps members), community members, and PCG leadership. Data were collected through in-person and virtual in-depth interviews and focus group discussions. Reflexive thematic analysis was used. RESULTS: Forty individuals were interviewed (20 Psych Corps members, 10 mental health professionals, 5 community members, 5 PCG leaders). Most were female (67.5%), living/working in the Greater Accra region (80%), and had completed secondary school (97.5%). Participants had an overwhelmingly positive perception of the intervention, highlighting its usefulness in supporting clinicians and addressing the dearth of mental health professionals. They also emphasized its role in increasing community awareness of mental health services and helping to reduce mental health stigma. Important weaknesses were the lack of clarity on the specific tasks Psych Corps members were equipped to engage in and a lack of continued supervision and support from PCG leadership during their placements. Recommendations for improvement included (1) better integration into Ghana’s mental healthcare system (2), strengthening communication between PCG leadership and the mental health professionals with whom Psych Corps members worked during their placements, and (3) ensuring structured, consistent support of Psych Corps members during their placement. CONCLUSIONS: PCG’s task-sharing intervention leverages an existing platform to provide an innovative solution to the shortage of mental health professionals in Ghana. Further evidence on its implementation and effectiveness are needed to inform its potential scale-up to address Ghana’s mental healthcare needs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.031
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.006
Scholarly communication0.0030.002
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.247
GPT teacher head0.640
Teacher spread0.394 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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