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Introduction: Governance, the least studied health system component, comprises a system of rules and processes, and is a key determinant for effective decision making for health care planning. This study aims to identify institutional, legal and policy factors which are either barriers or facilitators for the implementation of integrated mental health in primary care in the India. Methods: Semi-structured interviews were conducted with 33 key informants at the district and national levels with policy makers, state level health care planners and district planners and managers in India. The data were analysed using thematic analysis using the qualitative software NViVO 10. Findings: Participants stated that a conducive environment for mental health service delivery is necessary at the legislative, policy and planning levels, to facilitate integration of mental health into primary care. Amongst other factors, the need for active involvement of civil society and service user organisations, strengthening mental health information systems, and building the non-technical skills of the mental health workforce, were identified as particularly necessary to deliver adequate mental health services.Conclusion: Amidst the favourable policy context supporting collaborative and integrated care in India, this study identified low resourcing, weak collaborations and inadequate information to be crucial for integrated mental health in India at present.

Background There is a large “treatment gap” for depression worldwide. This study aimed to better understand the treatment gap in rural India by describing health care use and treatment-seeking for depression. Methods Data were analysed from a two round cross-sectional community survey conducted in rural Madhya Pradesh between May 2013 and December 2016. We examined the proportion of individuals who screened positive for depression (≥10) on the Patient Health Questionnaire (PHQ-9) who sought treatment in different sectors, for depression symptoms and for any reason, and compared the latter with health service use by screen-negative individuals. We analysed the frequency with which barriers to healthcare utilisation were reported by screen-positive adults. We also analysed the association between seeking treatment for depression and various predisposing, enabling and need factors using univariable regression. Results 86% of screen-positive adults reported seeking no depression treatment. However, 66% had used health services for any reason in the past 3 months, compared to 46% of screen-negative individuals (p Conclusions These findings suggest that the majority of adults who screen positive for depression seek healthcare, although not primarily for depression symptoms, indicating the need to improve detection of depression during consultations about other complaints. Private providers may need to be considered in programmes to improve depression treatment in this setting. Further research should test the hypotheses generated in this descriptive study, such as the potential role of marriage in facilitating treatment-seeking.

Aims Research from high-income countries has implicated travel distance to mental health services as an important factor influencing treatment-seeking for mental disorders. This study aimed to test the extent to which travel distance to the nearest depression treatment provider is associated with treatment-seeking for depression in rural India. Methods We used data from a population-based survey of adults with probable depression (n = 568), and calculated travel distance from households to the nearest public depression treatment provider with network analysis using Geographic Information Systems (GIS). We tested the association between travel distance to the nearest public depression treatment provider and 12 month self-reported use of services for depression. Results We found no association between travel distance and the probability of seeking treatment for depression (OR 1.00, 95% CI 0.98–1.02, p = 0.78). Those living in the immediate vicinity of public depression treatment providers were just as unlikely to seek treatment as those living 20 km or more away by road. There was evidence of interaction effects by caste, employment status and perceived need for health care, but these effect sizes were generally small. Conclusions Geographic accessibility – as measured by travel distance – is not the primary barrier to seeking treatment for depression in rural India. Reducing travel distance to public mental health services will not of itself reduce the depression treatment gap for depression, at least in this setting, and decisions about the best platform to deliver mental health services should not be made on this basis.

Background There is a large treatment gap for common mental disorders (CMD), with wide variation by world region. This review identifies factors associated with formal health service utilisation for CMD in the general adult population, and compares evidence from high-income countries (HIC) with that from low-and-middle-income countries (LMIC). Methods We searched MEDLINE, PsycINFO, EMBASE and Scopus in May 2016. Eligibility criteria were: published in English, in peer-reviewed journals; using population-based samples; employing standardised CMD measures; measuring use of formal health services for mental health reasons by people with CMD; testing the association between this outcome and any other factor(s). Risk of bias was assessed using the adapted Mixed Methods Appraisal Tool. We synthesised the results using “best fit framework synthesis”, with reference to the Andersen socio-behavioural model. Results Fifty two studies met inclusion criteria. 46 (88%) were from HIC. Predisposing factors: There was evidence linking increased likelihood of service use with female gender; Caucasian ethnicity; higher education levels; and being unmarried; although this was not consistent across all studies. Need factors: There was consistent evidence of an association between service utilisation and self-evaluated health status; duration of symptoms; disability; comorbidity; and panic symptoms. Associations with symptom severity were frequently but less consistently reported. Enabling factors: The evidence did not support an association with income or rural residence. Inconsistent evidence was found for associations between unemployment or having health insurance and use of services. There was a lack of research from LMIC and on contextual level factors. Conclusion In HIC, failure to seek treatment for CMD is associated with less disabling symptoms and lack of perceived need for healthcare, consistent with suggestions that “treatment gap” statistics over-estimate unmet need for care as perceived by the target population. Economic factors and urban/rural residence appear to have little effect on treatment-seeking rates. Strategies to address potential healthcare inequities for men, ethnic minorities, the young and the elderly in HIC require further evaluation. The generalisability of these findings beyond HIC is limited. Future research should examine factors associated with health service utilisation for CMD in LMIC, and the effect of health systems and neighbourhood factors. Trial registration PROSPERO registration number: 42016046551. Electronic supplementary material The online version of this article (10.1186/s12888-018-1837-1) contains supplementary material, which is available to authorized users.

Background The incidence, presentation, and course of psychotic disorders are highly variable across populations. A recent review noted a lack of evidence from low- and middle-income countries in the global South, where around 85% of the world’s population lives. Robust population-based data from these contexts are needed to better understand the sources of variation in psychotic disorders. INTREPID II is a multi-country programme comprising incidence, case-control, and follow-up studies of psychotic disorders in three diverse catchment areas with populations at risk of ~ 500,000 in Tamil Nadu (India), Oyo state (Nigeria), and northern Trinidad. Here, using baseline data from the initial 15 months, we present findings on variations in incidence and clinical presentation. Methods Baseline recruitment and assessment is ongoing. In each site individuals with an untreated psychotic disorder are identified through a comprehensive case detection system that includes professional, folk, and popular sectors. Inclusion criteria are age of 18–64, resident in catchment area, presence of a ICD-10 psychotic disorder, and no more than one continuous month of treatment with antipsychotic medication prior to the start of case identification. At baseline, detailed data on demographic and clinical characteristics and putative risk factors are collected using established tools. Results In the first 15 months, we identified 614 cases (199 in India, 92 in Nigeria, and 264 in Trinidad). There was wide variation in where cases were identified: In India, 9% via professional services and 91% via the popular sector (i.e., in the community); In Nigeria, 33% via professional services and 63% via the folk sector (traditional and religious service providers); In Trinidad, 98% via professional services. Further, there were notable variations in incidence and sociodemographic and clinical characteristics. Age-adjusted rates were highest in Trinidad (men: 47.1, 95% CI 39.8–55.4; women: 38.7, 95% CI 32.0–46.3) compared with India (men: 23.0, 95% CI 18.4–28.4; women: 30.2, 95% CI 24.9–36.4) and Nigeria (men: 13.0, 95% CI 9.5–17.2; women: 12.4, 95% CI 9.0–16.6). The proportion with age of onset before 29 years was higher in Trinidad (74%) compared to Nigeria (45%) and India (36%). Among those on whom full data are currently available (n, 327), more in Nigeria were assigned a diagnosis of schizophrenia (63%) than in India (46%) and Trinidad (42%). Median duration of untreated psychosis was was longer in India (5.1 years, IQR 1.9–13.6) than in Nigeria (1.5 years, IQR 0.1–4.1) and Trinidad (2.6 years, IQR 0.3–15.2). However, an insidious onset (i.e., gradual emergence of symptoms over several months) was more common in Trinidad (50% of cases) than in India (28%) and Nigeria (14%). Education levels were lower in India (31% completed secondary education or higher) than in Nigeria (74%) or Trinidad (68%). However, the proportion of cases who were married or in a steady relationship was similar in all sites (India: 42%, Nigeria: 38%, Trinidad: 38%), as was the proportion who were unemployed (India: 48%, Nigeria: 55%, Trinidad: 51%). Discussion In initial analyses, we found evidence that the incidence and presentation of psychoses varied by site, findings that both further highlight the heterogeneity of psychoses across contexts and challenge assumptions about the basic epidemiology based on findings from the global North. For example, the data from our India site suggest higher rates among women and a later age of onset than commonly supposed. Our findings also show that many people with psychotic disorders in these settings are untreated for long periods, indicating an urgent need to develop more accessible services.

ObjectivesTo estimate the proportion of adult primary care outpatients who are clinically detected and initiate treatment for depression and alcohol use disorder (AUD) in low-income and middle-income country (LMIC) settings.DesignFive cross-sectional studies.SettingAdult outpatient services in 36 primary healthcare facilities in Sodo District, Ethiopia (9 facilities); Sehore District, India (3); Chitwan District, Nepal (8); Dr Kenneth Kaunda District, South Africa (3); and Kamuli District, Uganda (13).ParticipantsBetween 760 and 1893 adults were screened in each district. Across five districts, between 4.2% and 20.1% screened positive for depression and between 1.2% and 16.4% screened positive for AUD. 96% of screen-positive participants provided details about their clinical consultations that day.Primary outcomesDetection of depression, treatment initiation for depression, detection of AUD and treatment initiation for AUD.ResultsAmong depression screen-positive participants, clinical detection of depression ranged from 0% in India to 11.7% in Nepal. Small proportions of screen-positive participants received treatment (0% in Ethiopia, India and South Africa to 4.2% in Uganda). Among AUD screen-positive participants, clinical detection of AUD ranged from 0% in Ethiopia and India to 7.8% in Nepal. Treatment was 0% in all countries aside Nepal, where it was 2.2%.ConclusionsThe findings of this study suggest large detection and treatment gaps for adult primary care patients, which are likely contributors to the population-level mental health treatment gap in LMIC. Primary care facilities remain unfulfilled intervention points for reducing the population-level burden of disease in LMIC.