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Objective Integration of mental health and chronic disease services in primary care could reduce the mental health treatment gap and improve associated health outcomes in low-resource settings. Low rates of nurse identification and referral of patients with depression limit the effectiveness of integrated mental health care; the barriers to and facilitators of identification and referral in South Africa and comparable settings remain undefined. This study explored barriers to and facilitators of nurse identification and referral of patients with depressive symptoms as part of integrated mental health service delivery in KwaZulu-Natal, South Africa. Design Triangulation mixed methods study incorporating qualitative and quantitative data. Methods Data collection, analysis, and interpretation were guided by the Consolidated Framework for Implementation Research (CFIR). Participants were professional nurses at ten primary health care facilities in Amajuba, KwaZulu-Natal, South Africa. Qualitative data collection involved semi-structured interviews targeting specific CFIR constructs with high- and low-referring nurses. Deductive and inductive coding were used to derive primary themes related to barriers and facilitators. Quantitative data collection involved a structured questionnaire assessing determinants explored in the interviews. Qualitative comparative analysis was used to identify the necessary or sufficient conditions for high and low nurse referral. Results Twenty-two nurses were interviewed. Primary themes related to insufficient training, supervision, and competency; emotional burden; limited human and physical resources; perceived patient need for integrated services; and intervention acceptability. Sixty-eight nurses completed questionnaires. Quantitative results confirmed and expanded upon the qualitative findings. Low self-assessed competency was a consistent barrier to appropriate service delivery. Conclusions To promote the success of integrated care in a context of severe staff shortages and over-burdened providers, implementation strategies including direct training, structured supervision, and routine behavioral health screening tools are warranted. Interventions to improve mental health literacy of patients as well as emotional support for nurses are also needed.

Background: People with chronic general medical conditions who have comorbid depression experience poorer health outcomes. This problem has received scant attention in low- and middle-income countries. The aim of the ongoing study reported here is to refine and promote the scale-up of an evidence-based task-sharing collaborative care model, the Mental Health Integration (MhINT) program, to treat patients with comorbid depression and chronic disease in primary health care settings in South Africa. Methods: Adopting a learning-health-systems approach, this study uses an onsite, iterative observational implementation science design. Stage 1 comprises assessment of the original MhINT model under real-world conditions in an urban subdistrict in KwaZulu-Natal, South Africa, to inform refinement of the model and its implementation strategies. Stage 2 comprises assessment of the refined model across urban, semiurban, and rural contexts. In both stages, population-level effects are assessed by using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) evaluation framework with various sources of data, including secondary data collection and a patient cohort study (N=550). The Consolidated Framework for Implementation Research is used to understand contextual determinants of implementation success involving quantitative and qualitative interviews (stage 1, N=78; stage 2, N=282). Results: The study results will help refine intervention components and implementation strategies to enable scale-up of the MhINT model for depression in South Africa. Next steps: Next steps include strengthening ongoing engagements with policy makers and managers, providing technical support for implementation, and building the capacity of policy makers and managers in implementation science to promote wider dissemination and sustainment of the intervention.

Against the backdrop of mounting calls for the global scaling-up of mental health services – including quality care and prevention services – there is very little guidance internationally on strategies for scaling-up such services. Drawing on lessons from scale-up attempts in six low- and middle-income countries, and using exemplars from the front-lines in South Africa, we illustrate how health reforms towards people-centred chronic disease management provide enabling policy window opportunities for embedding mental health scale-up strategies into these reforms. Rather than going down the oft-trodden road of vertical funding for scale-up of mental health services, we suggest using the policy window that stresses global policy shifts towards strengthening of comprehensive integrated primary health care systems that are responsive to multimorbid chronic conditions. This is indeed a substantial opportunity to firmly locate mental health within these horizontal health systems strengthening funding agendas. Although this approach will promote systems more enabling of scaling-up of mental health services, implications for donor funders and researchers alike is the need for increased time commitments, resources and investment in local control.

Background Integration of depression treatment into primary care could improve patient outcomes in low-resource settings. Losses along the depression care cascade limit integrated service effectiveness. This study identified patient-level factors that predicted detection of depressive symptoms by nurses, referral for depression treatment, and uptake of counseling, as part of integrated care in KwaZulu-Natal, South Africa. Methods This was an analysis of baseline data from a prospective cohort. Participants were adult patients with at least moderate depressive symptoms at primary care facilities in Amajuba, KwaZulu-Natal, South Africa. Participants were screened for depressive symptoms prior to routine assessment by a nurse. Generalized linear mixed-effects models were used to estimate associations between patient characteristics and service delivery outcomes. Results Data from 412 participants were analyzed. Nurses successfully detected depressive symptoms in 208 [50.5%, 95% confidence interval (CI) 38.9–62.0] participants; of these, they referred 76 (36.5%, 95% CI 20.3–56.5) for depression treatment; of these, 18 (23.7%, 95% CI 10.7–44.6) attended at least one session of depression counseling. Depressive symptom severity, alcohol use severity, and perceived stress were associated with detection. Similar factors did not drive referral or counseling uptake. Conclusions Nurses detected patients with depressive symptoms at rates comparable to primary care providers in high-resource settings, though gaps in referral and uptake persist. Nurses were more likely to detect symptoms among patients in more severe mental distress. Implementation strategies for integrated mental health care in low-resource settings should target improved rates of detection, referral, and uptake.

Background Low demand for mental health services in sub-Saharan Africa is driven by poor mental health literacy, stigma, and poor service availability. Objective To develop a Community Mental Health Education and Detection (CMED) Tool for adults for use by community health teams in South Africa aligned with their roles of health promotion, screening and linkage to care. Methods Formative evaluation methods involving four processes: (1) Ongoing engagement with the KwaZulu-Natal Department of Health (KZN DoH) to ensure co-creation of the CMED tool and alignment with routine community health team activities; (2) Adaptation of the CMED tool from the Community Informant Detection Tool (CIDT), used to promote help-seeking of people with mental health problems in Nepal; (3) Review of the CMED vignettes and illustrations by a panel of local and international mental health care experts to establish accuracy and contextual and cultural relevance; (4) Process mapping and focus group discussions (FGDs) with community health teams in one district to establish cultural and contextual appropriateness as well as coherence and compatibility with existing community-based services. Results The resulting CMED tool consists of five case vignettes and related illustrations to facilitate psychoeducation and the detection of possible depression, anxiety, psychosis, harmful alcohol use, and drug use by community health teams. Based on prototype matching, it includes two structured questions to guide the community health teams in the detection and referral process. The tool was acceptable, culturally and contextually appropriate, and helpful for the services provided by community health teams. Challenges of working in households and the importance of self-care were highlighted as important considerations when developing training content and piloting the tool. Conclusion Extensive consultation with the KZN DoH, community health teams, and the expert mental health panel resulted in developing a tool that was perceived to be culturally sensitive and relevant to the community package of services.

Background. Integrating care for common mental disorders (CMDs) such as depression, anxiety and alcohol abuse into primary healthcare (PHC) should assist in reducing South Africa (SA)’s quadruple burden of disease. CMDs compromise treatment adherence, health behaviour change and self-management of illnesses. Appropriate identification of mental disorders in primary care can be facilitated by brief, easy-to-administer screening that promotes high specificity. Objectives. To establish the criterion-based validity of a seven-item Brief Mental Health (BMH) screening tool for assessing positive symptoms of CMDs in primary care patients. Methods . A total of 1 214 participants were recruited from all patients aged ≥18 years visiting 10 clinics as part of routine care in the Newcastle subdistrict of Amajuba District in KwaZulu-Natal Province, SA, over a period of 2 weeks. Consenting patients provided basic biographical information prior to screening with the BMH tool. PHC nurses remained blind to this assessment. PHC nurse-initiated assessment using the Adult Primary Care (APC) guidelines was the gold standard against which the performance of the BMH tool was compared. A specificity standard of 80% was used to establish cut-points. Specificity was favoured over sensitivity to ensure that those who did not have CMD symptoms were excluded, as well as to reduce over-referrals. Results. Of the participants, 72% were female. The AUD-C (alcohol abuse) performed well (area under the curve (AUC) 0.91 (95% confidence interval (CI) 0.88 - 0.95), cut-point ≥4, Cronbach alpha 0.87); PHQ-2 (depression) performed reasonably well (AUC 0.72 (95% CI 0.65 - 0.78), cut-point ≥3, alpha 0.71); and GAD-2 (anxiety) performance was acceptable (AUC 0.69 (95% CI 0.58 - 0.80), cut-point ≥3, alpha 0.62). Using the higher cut-off scores, patients who truly did not have CMD symptoms had negative predictive values (NPVs) of >90%. Overall, 26% of patients had CMD positive symptoms relative to 8% using the APC guidelines. Conclusions. Using a higher specificity index, the positive predictive value and NPV show that at higher cut-point values the BMH not only helps identify individuals with alcohol misuse, depression and anxiety symptoms but also identifies a majority of those who do not have symptoms (true negatives), thus not overburdening nurses with false positives needing assessment. Research is needed to assess whether use of such a short and valid screening tool is generalisable to other clinic contexts as well as how mental health screening should best be introduced into routine clinic functioning and practice.