Evidence map›Paper›PMID 41029657›Full record

ArticleBMC health services research2025

Enhancing mental health outcomes through a theory of change: supporting open-source data science platforms to promote FAIR data and evidence-based decisions.

Bylhah Mugotitsa, Pauline Andeso, Henry Owoko, Reinpeter Momanyi, Dorothy Mailosi, Joshua Ssebunnya, Benjamin Tsofa, Jay Greenfield, Agnes Kiragga, Jim Todd and 1 more

Abstract read
In one paragraph

Article in BMC health services research, 2025. 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
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0citing papers in PubMed
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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

11 authors.

Bylhah MugotitsaAfrican Population and Health Research Center (APHRC), Nairobi, Kenya. bylhah.mugotitsa@strathmore.edu.
Pauline AndesoAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Henry OwokoAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Reinpeter MomanyiAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Dorothy MailosiCODATA-Committee on Data of the International Science Council, Paris, France.
Joshua SsebunnyaInfectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda.
Benjamin TsofaKEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
Jay GreenfieldCODATA-Committee on Data of the International Science Council, Paris, France.
Agnes KiraggaAfrican Population and Health Research Center (APHRC), Nairobi, Kenya.
Jim ToddDepartment of Epidemiology, Catholic University for Health and Allied Sciences, Mwanza, Tanzania.
INSPIRE network

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMental health disorders remain a significant public health challenge in low- and middle-income countries (LMICs) such as Kenya and Uganda due to limited resources, stigma, and inadequate service integration. The INSPIRE Mental Health (MH) Project aims to address these challenges by developing an open-source data science platform that aligns with FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. A Theory of Change (ToC) was developed to guide project implementation.

methodsA participatory approach was employed, involving targeted intrest holder engagements through workshops, focus group discussions, and key informant interviews with policymakers, healthcare providers, Village Health Team (VHT) members, data managers, researchers, and community representatives. All participants provided informed consent be- fore inclusion in the study. Collected data was transcribed, cleaned, and analyzed using Atlas.ti, employing thematic analysis to identify emerging themes. The insights gained in- formed the development of the ToC, which visually maps causal linkages between project activities, assumptions, and anticipated outcomes.

findingsInterest-holders identified key challenges in mental health service delivery, including fragmented services, inadequate funding, and limited data management capacity. The findings were categorized into five themes: (1) mental health program design, (2) bur- den assessment, (3) screening and assessment tools, (4) data reporting and utilization, (5) prospects for longitudinal studies. Participants emphasized the need for standardized data collection, improved reporting systems, and capacity building in data science techniques to support evidence-based decision-making.

conclusionThe ToC framework offers a strategic roadmap to enhance mental health service delivery and data utilization, fostering collaboration and sustainability. By promoting FAIR data principles and interest holder engagement, the project aims to support informed mental health interventions in Kenya and Uganda.

Indexed as

Data ScienceMental DisordersMental Health ServicesDeveloping CountriesEvidence-Based PracticeFocus GroupsHumansKenyaUgandaData scienceFAIR principlesInterest holder engagementInterventionsKenyaMental healthTheory of changeUganda

Identifiers

PMID41029657
PMCPMC12481834

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.