Eligibility criteria

We included any type of study design, review or report of evidence, experience or evaluation of using the mhGAP-IG in LMICs. No papers were excluded based on language, and no relevant papers from high-income settings were identified.

Search strategy

We searched the following databases on 16–18 May 2017: Cochrane Library, CINAHL, EMBASE (1974 to May 2017), LILACS, Medline (1946 to May 2017), PsycINFO (1806 to May 2017), PubMed, SciELO, SCOPUS and Web of Science. Search terms were ‘mental health gap action programme’ OR ‘mental health gap action program’ OR ‘mhGAP’. Searches were conducted in English but studies written in other languages were eligible for inclusion. The term ‘intervention guide’ was not included, due to its variable use in literature and in the field. In addition to database searches, the reference lists of relevant excluded papers were searched for relevant studies. Grey literature, including book chapters, conference workshops and web-based resources, was identified by repeating the search on Google Scholar. Studies published in LMICs were additionally sought through hand-searching of non-Western online sources.

Study selection and data extraction

Figure 1 shows the flow of studies from identification to screening, eligibility and inclusion. The titles and abstracts of the 117 non-duplicated papers were screened by RCK, excluding 71, which did not review or report on the evidence, experience or evaluation of using the WHO mhGAP-IG. No papers were excluded which met inclusion criteria but came from a high-income setting. The remaining 46 full-text articles were assessed for eligibility by RCK, excluding a further 13 studies, which also did not review or report on the evidence, experience or evaluation of using the WHO mhGAP-IG. Data were extracted from the 33 papers eligible for inclusion, in the qualitative synthesis presented here, but the heterogeneity of mhGAP-IG uses, outcome measures and evaluations precluded meta-analysis. Data extracted included country involved, participants, sample size, nature of use, evaluation conducted and summary of findings. 

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Figure 1

Flow of studies from identification to screening. HIC, high income country; mhGAP-IG, Mental Health Gap Action Programme Intervention Guide.

Use in training

Of the 33 included papers, 15 reported mhGAP-IG use in training (see online Supplementary file 1). Studies were conducted in seven African or Middle Eastern countries and four Asian countries. Ten courses trained non-medical PHC staff, two trained doctors,9 10 one trained university student volunteers,11 one trained volunteer ‘champions’12 and another, school teachers.13 Sample sizes ranged from 12 in Sri Lanka to 1328 in the Philippines. Most studies reported experimental study designs, providing detail regarding participants, training and evaluation methods; three were more descriptive accounts, which did not include quantitative data.9 14 15

Only two studies explicitly stated that learners were trained using all modules of the mhGAP-IG,16 17 although some studies did not clarify this. Most included papers used a subset of mhGAP-IG modules, with depression, psychosis, drug and alcohol use disorders, epilepsy and suicide being the most common10 17–20; three focused on developmental and behavioural disorders.12 13 21

Course durations varied from 3 hours training for teachers about attention deficit hyperactivity disorder, followed by a 1.5-hour booster session,13 to 5 full days ‘base course’ followed by the mhGAP ‘standard course’16 or 40 hours child psychiatry training over 2 weeks.21 Most training lasted 2–3 days, combining didactic lecture teaching with videos, role plays, communication exercises and discussions. Only five studies provided supervision to participants after training.9 10 12 16 22

Ten included papers measured participant learning using pre and post-training knowledge assessments, the most common of which came from the WHO mhGAP monitoring and evaluation toolkit. Five studies reported the number of patients with priority MNS disorders diagnosed and treated following training10 16–19 but only three reported or measured learner feedback.9 21 22 One study provided detailed information about the subsequent career paths of learners on a 2-year child psychiatry MSc programme, and their contributions to local mental health services and research.21

Two studies were protocols, but were included for their rich descriptions of the planned training intervention and evaluation.10 19 One protocol’s final results paper was also included.20 The authors candidly outlined operational challenges arising during initial recruitment, which resulted in the ultimate published research differing significantly from the original protocol. They included a table comparing differences between what was planned and what was conducted, reflection on lessons learnt and listed challenges including lack of administrative support, lack of interest among PHC staff, difficulties with participant retention, unforeseen geopolitical eventualities, lack of locally tailored training resources and financial constraints. Another study reported local challenges, including the fact that training attendance was influenced by low per diem payments, which needed to cover accommodation and other expenses.16 They noted that master trainers (experienced senior psychiatrists) were expected to cascade training without specific preparation, and recommended a formal introduction to the mhGAP-IG and its training approach. Methodological challenges highlighted by authors included selection of course attendants for prior interest in, or commitment to, mental health work, rather than a representative sample of healthcare staff.10 18

One study developed avatar-assisted cascade training, a tablet-based tool.12 mhGAP-IG guidelines for developmental disorders were incorporated into animated, interactive narratives about three children and families, with training scenarios addressing psychoeducation, parent skills training, community participation, stigma and rights. ‘Champion’ volunteers delivered training to families of children with developmental disorders in their area. High initial costs of the system, which, once developed, provided an intervention at low cost, were addressed using a social franchise model. The authors summarise steps to replicate this public–private collaboration in other settings.

Use in clinical practice

Nine included papers described uses of the mhGAP-IG in clinical practice (See online supplementary table 2). Studies were conducted in three African, one Asian and one South American country. Although most also included mhGAP-IG use in training, they were distinguished from the previous section for focusing on clinical outcomes of mhGAP-IG use by staff, following training. Five studies used the mhGAP-IG to address a set of priority MNS disorders23–27 and four addressed a single diagnosis, namely depression,28–30 or alcohol use disorder.31 Six studies measured rates of case identification,23 24 26–29 three measured rates of follow-up24 26 29 and three, clinical outcomes.25 29 31

Of the included clinical papers, seven worked with healthcare staff in a biomedical model and two from the same research group worked with traditional health practitioners (THPs; traditional and faith healers) in Kenya.29 30 These studies showed that the mhGAP-IG depression module can be effectively used by THPs as well as more biomedical PHC workers, with depression diagnostic accuracy measures showing 86% specificity and 46% sensitivity.

Patient sample sizes varied from 6524 in Haiti, to 1664 in Kenya,28 and staff sample sizes from 1126 in Nepal, to 360 in Ethiopia.23 Two studies described clinical applications of the mhGAP-IG using a mobile phone-operated ‘app.’ In Afghanistan,27 an android-based mobile application using the mhGAP-IG, developed by a private enterprise, had been pretested for functionality and acceptability at Aga Khan Health Services in Pakistan and Afghanistan. Smartphones provided by the study were used by about 125 PHC staff in community and facility-based roles. The app featured capability for patient registration, blended learning, interactive mhGAP-IG use for screening and management decision making, store and forward, and teleconsultation. In Kenya,28 a simple mhGAP-IG app was used for depression screening. Focus group discussions and key informant interviews supported its acceptability and feasibility.

Several studies reported a range of implementation factors. One listed context-related strengths and challenges,23 such as political commitment, healthcare infrastructure, supervision and medication supply. Others conducted detailed evaluation of service user and health worker views and experiences.25 26

Local adaptation

Three papers reported local adaptations of the mhGAP-IG for their setting in Africa, the Middle East and Asia (see online supplementary table 3). One study32 provided a detailed account of six steps taken to contextualise the mhGAP-IG in Nigeria, from situational analysis and stakeholder focus group discussions, to national consultation, pilot training and evaluation. It had a wider scope than the training (see online supplementary table 1) and clinical (see online supplementary table 2) studies, but involved a smaller sample size and was only conducted in one state. The other two studies were more descriptive in nature. One described the use of the mhGAP-IG in the Eastern Mediterranean, in new community mental health services in Gaza and the West Bank, without presenting any evaluations, or details of how the mhGAP-IG was tailored to the setting.33 Another study described the adaptation of the mhGAP-IG dementia module for the Nepalese context, alongside cognitive assessment tools, postdiagnostic carer support and treatment protocols.34 The authors expressed the intention to evaluate its acceptability, suitability and impact, but did not report any evaluation data or details on how contextualisation took place.

Economic modelling

Three included papers used the mhGAP-IG to conduct economic modelling (see online supplementary table 4). One paper used the mhGAP-IG epilepsy module to calculate the costs of full implementation and maintenance of recommended treatments in Zambia, as less than $25.00 per patient, per year.35 The other two studies both used similar approaches (and had a researcher in common), with the first being an abstract describing economic modelling for India,36 and the second a full publication of modelling for five LMICs participating in the PRIME (PRogramme for Improving Mental health carE) consortium: Ethiopia, India, Nepal, South Africa and Uganda.37 This study used a dedicated tool to derive estimated total and incremental costs of scaled-up mental health service provision, broken down by mhGAP-IG diagnosis, type of expenditure and year of scale-up. Using identical methods for economic modelling in five diverse LMICs enabled the authors to calculate differences in costs of training, supervision and management, hospital-based services and inflation in different settings. They found that additional costs per year to reach target service coverage were less than $0.10 per head of population, in each country.

Other uses

Two papers used the mhGAP-IG as a control intervention for comparison in randomised controlled trials,38 39 and one used its training model to pilot and develop a new rating scale, of therapist competence in global mental health (see online supplementary table 5). The first two studies, based in India and Pakistan,38 and Zimbabwe,39 are examples of next steps taken in the field to conduct robust, randomised controlled trials of the low-intensity psychosocial interventions advocated by the mhGAP-IG alongside consideration of pharmacotherapy. The use of the mhGAP-IG for controlled implementation of ‘enhanced treatment as usual’ represents a valuable opportunity to acquire rigorous evidence of its utility in a range of LMICs. The development of the ENACT (ENhancing Assessment of Common Therapeutic factors) rating scale40 is a further important step in the growth of evidence-based practice and high-quality implementation science in the field of global mental health.