Evaluation of the impacts of a district-level mental health care plan on contact coverage, detection and individual outcomes in rural Uganda: a mixed methods approach

Nakku, Juliet; Rathod, Sujit D; Garman, Emily; Ssebunnya, Joshua; Kangere, S.; Silva, M. De; Patel, Vikram; Lund, Crick; Kigozi, Fred

doi:10.1186/s13033-019-0319-2

Cited by 13 publications

(19 citation statements)

References 33 publications

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“…Both diagnostic and screening tools were used to assess depression among different populations in Uganda ( Table 1 ). The tools used included: (i) Depression sub-section of the Hopkins Symptom Checklist (DHSCL) ( n = 34, 26.8%) [ 35 , 55 , 61 , 63 , 65 – 68 , 71 , 73 , 74 , 79 – 82 , 84 , 92 , 100 , 108 , 110 , 111 , 113 , 125 , 135 , 136 , 138 , 140 , 141 , 144 , 147 , 151 , 155 , 166 ], (ii) Patient Health Questionnaire (PHQ) ( n = 33, 26.0%) [ 16 , 21 , 32 , 34 , 36 , 37 , 52 , 86 , 88 – 90 , 93 , 98 , 99 , 101 , 102 , 112 , 116 – 118 , 120 – 123 , 126 – 128 , …”

Section: Resultsmentioning

confidence: 99%

Prevalence of depression in Uganda: A systematic review and meta-analysis

Kaggwa

Najjuka²,

Bongomin³

et al. 2022

PLoS ONE

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Background Depression is one of the most studied mental health disorders, with varying prevalence rates reported across study populations in Uganda. A systematic review and meta-analysis was carried out to determine the pooled prevalence of depression and the prevalence of depression across different study populations in the country. Methods Papers for the review were retrieved from PubMed, Scopus, PsycINFO, African Journal OnLine, and Google Scholar databases. All included papers were observational studies regarding depression prevalence in Uganda, published before September 2021. The Joanna Briggs Institute Checklist for Prevalence Studies was used to evaluate the risk of bias and quality of the included papers, and depression pooled prevalence was determined using a random-effects meta-analysis. Results A total of 127 studies comprising 123,859 individuals were identified. Most studies were conducted among individuals living with HIV (n = 43; 33.9%), and the most frequently used instrument for assessing depression was the Depression sub-section of the Hopkins Symptom Checklist (n = 34). The pooled prevalence of depression was 30.2% (95% confidence interval [CI]: 26.7–34.1, I2 = 99.80, p<0.001). The prevalence of depression was higher during the COVID-19 pandemic than during the pre-pandemic period (48.1% vs. 29.3%, p = 0.021). Refugees had the highest prevalence of depression (67.6%; eight studies), followed by war victims (36.0%; 12 studies), individuals living with HIV (28.2%; 43 studies), postpartum or pregnant mothers (26.9%; seven studies), university students (26.9%; four studies), children and adolescents (23.6%; 10 studies), and caregivers of patients (18.5%; six studies). Limitation Significantly high levels of heterogeneity among the studies included. Conclusion Almost one in three individuals in Uganda has depression, with the refugee population being disproportionately affected. Targeted models for depression screening and management across various populations across the country are recommended. Trial registration Protocol registered with PROSPERO (CRD42022310122).

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Section: Resultsmentioning

confidence: 99%

Prevalence of depression in Uganda: A systematic review and meta-analysis

Kaggwa

Najjuka²,

Bongomin³

et al. 2022

PLoS ONE

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“…An application of that can be found in the Program for Improving Mental Health Care (PRIME), which evaluated the integration of mental health into primary health care (Lund et al ., 2012 ; Jordans et al ., 2019 b ). The programme demonstrated that population-level change in contact coverage was not achieved in some of the settings– even after significant efforts to make services available (Nakku et al ., 2019 ; Shidhaye et al ., 2019 ). Besides such supply-side approach, demand-side drivers will therefore need to be addressed in order to actually achieve significant changes in contact coverage.…”

Section: Roadmap To Impactmentioning

confidence: 99%

Scaling up mental health care and psychosocial support in low-resource settings: a roadmap to impact

Jordans

Kohrt

2020

Epidemiol Psychiatr Sci

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Aims Despite recent global attention to mental health and psychosocial support services and a growing body of evidence-support interventions, few mental health services have been established at a regional or national scale in low- and middle-income countries (LMIC). There are myriad challenges and barriers ranging from testing interventions that do not target priority needs of populations or policymakers to interventions that cannot achieve adequate coverage to decrease the treatment gap in LMIC. Method We propose a ‘roadmap to impact’ process that guides planning for interventions to move from the research space to the implementation space. Results We establish four criteria and nine associated indicators that can be evaluated in low-resource settings to foster the greatest likelihood of successfully scaling mental health and psychosocial interventions. The criteria are relevance (indicators: population need, cultural and contextual fit), effectiveness (change in mental health outcome, change in hypothesised mechanism of action), quality (adherence, competence, attendance) and feasibility (coverage, cost). In the research space, relevance and effectiveness need to be established before moving into the implementation space. In the implementation space, ongoing monitoring of quality and feasibility is required to achieve and maintain a positive public health impact. Ultimately, a database or repository needs to be developed with these criteria and indicators to help researchers establish and monitor minimum benchmarks for the indicators, and for policymakers and practitioners to be able to select what interventions will be most likely to succeed in their settings. Conclusion A practicable roadmap with a sequence of measurable indicators is an important step to delivering interventions at scale and reducing the mental health treatment gap around the world.

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“…This type of intervention was diverse in terms of who developed the intervention, its content, and duration of implementation (Table 5). Some examples of this type of intervention included implementation of evidence-based guideline on the identification of depressive symptoms [76], the World Health Organization's International Classification of Diseases 10th version (WHO ICD-10) PHC guideline [77,84], Behavioral health Screening, Brief Intervention, and Referral to Treatment (SBIRT) program [78], Mental Healthcare Plan (MHCP) [79]; adaptation and implementation of the WHO mhGAP [80]; implementation of a chronic diseases management approach [83], and organized, multifaced collaborative approach to quality improvement [82,85]. The guidelines/care packages/quality improvement programs were either locally developed by the research team or adapted from international guidelines/care packages/quality improvement programs.…”

Section: Interventions To Improve Detection Of Depression In Primary ...mentioning

confidence: 99%

Interventions to improve the detection of depression in primary healthcare: systematic review

et al. 2023

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Background Several studies have been conducted on the effect of interventions on the detection of depression in primary healthcare (PHC). Systematic reviews have also been done on the effectiveness of separate interventions. However, systematic reviews are not done on the comparative effectiveness of several interventions. This study, therefore, aimed at synthesizing the global evidence on the effectiveness of interventions to improve the detection of depression in PHC. Methods We searched PubMed, Embase, PsycINFO, Web of Science, Cochrane Database of Systematic Reviews, Global Index Medicus, African Index Medicus, and African Journals Online, from the inception of the databases to until the 4th week of April 2020. We also searched references of the included articles. We included randomized trials, cluster randomized trials, or quasi-experimental studies, which evaluated the effectiveness of an intervention to improve detection of depression in the PHC setting. Two of the review authors independently extracted data from the included studies. The methodological quality of the included studies was assessed using the Assessment Tool for Quantitative Studies developed by the Effective Public Health Practice Project. The protocol for the review was registered on PROSPERO (CRD42020166291). Results Of 23,305 records identified, we included 58 articles in the review. Diverse types of interventions were evaluated to improve clinician diagnosis of depression in the PHC setting. Interventions related to implementation of guidelines, screening with feedback, educational interventions which incorporated active learning and clinical practice, and disclosure of screening results were found to be mostly effective. Interventions which combined education, screening, and feedback were particularly more effective. Most of the included studies were weak or moderate in their methodological quality. Conclusions Our review indicates that implementation of a single type of intervention does not improve the detection of depression in PHC. Combining aspects of each type of intervention which are more effective may be useful. Education and training interventions which include more simulation and role playing are found to be effective over time. Most of the studies conducted in the area are from high-income countries and are weak in their methodological quality. There is need to conduct more number of studies in low-income settings.

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Evaluation of the impacts of a district-level mental health care plan on contact coverage, detection and individual outcomes in rural Uganda: a mixed methods approach

Cited by 13 publications

References 33 publications

Prevalence of depression in Uganda: A systematic review and meta-analysis

Prevalence of depression in Uganda: A systematic review and meta-analysis

Scaling up mental health care and psychosocial support in low-resource settings: a roadmap to impact

Interventions to improve the detection of depression in primary healthcare: systematic review

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