Evidence map›Paper›PMID 38172713›Full record

SynthesisBMC public health2024

The effectiveness of mental health interventions involving non-specialists and digital technology in low-and middle-income countries - a systematic review.

Kalpani Wijekoon Wijekoon Mudiyanselage, Karina Karolina De Santis, Frederike Jörg, Maham Saleem, Roy Stewart, Hajo Zeeb, Heide Busse

Abstract readSystematic Review
In one paragraph

Synthesis in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 3 pooled it
–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

34 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

7 authors.

Kalpani Wijekoon Wijekoon MudiyanselageFaculty 11 Human and Health Sciences, University of Bremen, Bremen, Germany. wijekoon@uni-bremen.de.
Karina Karolina De SantisDepartment of Prevention and Evaluation, Leibniz Institute for Prevention Research and Epidemiology- BIPS, Bremen, Germany.
Frederike JörgDepartment of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Maham SaleemDepartment of Prevention and Evaluation, Leibniz Institute for Prevention Research and Epidemiology- BIPS, Bremen, Germany.
Roy StewartDepartment of Health Sciences, Community & Occupational Medicine, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Hajo ZeebFaculty 11 Human and Health Sciences, University of Bremen, Bremen, Germany.
Heide BusseDepartment of Prevention and Evaluation, Leibniz Institute for Prevention Research and Epidemiology- BIPS, Bremen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCombining non-specialists and digital technologies in mental health interventions could decrease the mental healthcare gap in resource scarce countries. This systematic review examined different combinations of non-specialists and digital technologies in mental health interventions and their effectiveness in reducing the mental healthcare gap in low-and middle-income countries.

methodsLiterature searches were conducted in four databases (September 2023), three trial registries (January-February 2022), and using forward and backward citation searches (May-June 2022). The review included primary studies on mental health interventions combining non-specialists and digital technologies in low-and middle-income countries. The outcomes were: (1) the mental health of intervention receivers and (2) the competencies of non-specialists to deliver mental health interventions. Data were expressed as standardised effect sizes (Cohen's d) and narratively synthesised. Risk of bias assessment was conducted using the Cochrane risk-of-bias tools for individual and cluster randomised and non-randomised controlled trials.

resultsOf the 28 included studies (n = 32 interventions), digital technology was mainly used in non-specialist primary-delivery treatment models for common mental disorders or subthreshold symptoms. The competencies of non-specialists were improved with digital training (d ≤ 0.8 in 4/7 outcomes, n = 4 studies, 398 participants). The mental health of receivers improved through non-specialist-delivered interventions, in which digital technologies were used to support the delivery of the intervention (d > 0.8 in 24/40 outcomes, n = 11, 2469) or to supervise the non-specialists' work (d = 0.2-0.8 in 10/17 outcomes, n = 3, 3096). Additionally, the mental health of service receivers improved through digitally delivered mental health services with non-specialist involvement (d = 0.2-0.8 in 12/27 outcomes, n = 8, 2335). However, the overall certainty of the evidence was poor.

conclusionIncorporating digital technologies into non-specialist mental health interventions tended to enhance non-specialists' competencies and knowledge in intervention delivery, and had a positive influence on the severity of mental health problems, mental healthcare utilization, and psychosocial functioning outcomes of service recipients, primarily within primary-deliverer care models. More robust evidence is needed to compare the magnitude of effectiveness and identify the clinical relevance of specific digital functions. Future studies should also explore long-term and potential adverse effects and interventions targeting men and marginalised communities.

Indexed as

Mental DisordersMental HealthDelivery of Health CareDeveloping CountriesDigital TechnologyHumansDigital technologiesInterventionsLow-and middle-income countriesMental healthMental healthcareNon-specialistsSystematic reviewTask-sharing

Identifiers

PMID38172713
PMCPMC10763181

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.