Effectiveness of a Mobile Technology Intervention for the Treatment of Depression

Epidemiologic research has clearly established the significant public health importance of mental disorders in low- and middle-income countries (LMIC) and their chronic nature. Among mental disorders, depression has become a major problem as a single condition and, more often, as part of complex clinical pictures in which multiple conditions and risk factors are combined. There is substantial co-morbidity between depression and chronic physical conditions, and outcome of both conditions is impaired when there is this co-morbidity. Most of the disease burden in LA is now explained by chronic diseases, including depression, cardio-vascular diseases -mostly hypertension related- and diabetes. Despite the public health impact of depression, it often goes unrecognized and untreated. One factor for this treatment gap is the lack of financial and human resources. The limited mental health resources available in LMIC are often not optimally distributed either. Funds and trained personnel are typically allocated in tertiary health care services, such as psychiatric hospitals. Therefore, any short- and medium-term efforts to develop, evaluate, and disseminate effective mental health interventions in LMIC must adapt to these severe workforce, resource limitations, and inequities. The mental health field needs to consider developing self-help automated interventions that can reach people where there are no health care providers. This can be partially addressed through two strategies: 1) increasing effective self-management; and 2) through task-shifting roles to less specialized but appropriately trained health workers. We are conducting a community cluster randomized trial with individuals with chronic diseases (hypertension and/or diabetes) and symptoms of depression, attending primary care clinics in São Paulo, Brazil. Participating clinics (20) will be randomly allocated to have their nurse assistants trainned and supervised to monitor an intervention based on behavior activation (experimental group) delivered by an applicative for smartphones (CONEMO) or to receive routine care (control group). The focus of this project is on patients helping themselves through the use of resources that provide continuous advice, support, and motivation. However, studies suggest that depressed patients left alone with their own devices fail to make good use of self-help interventions. Nurse assistants will assist participants by a web-based automated interface connected to the smartphone application (CONEMO) and will receive supervision in this task once a week. Method: CONEMO is a cluster randomized controlled trial conducted with 880 chronic patients who present diabetes and/ or hypertension and with depression, receiving health care in 20 Primary Care Units with Family Health Program in Sao Paulo, Brazil. Of these, half (10) will deliver the intervention CONEMO and half (10) will deliver usual care. The intervention, based in behavior activation, is delivered by a smartphone and monitored by health professionals (nurse assistants) working at the primary care unit responsible for the care of the patient. The CONEMO intervention is based on behavior activation and is delivered by an applicative for smartphones 3 times a week during 6 weeks, with a total of 18 sessions. A nurse assistant mediates this intervention, motivating the patient and monitoring his/her performance. Intensity of depressive symptoms and suicidal ideation is assessed by research assistants using the PHQ-9 and standardized protocols for suicidal risk at baseline, 3- and 6-month follow-ups. The primary outcome is remission of depressive symptoms 3 months after inclusion in the study. Secondary outcomes include remission of depressive symptoms at 6 months after inclusion, social support, quality of life, compliance to medication, suicidal ideation and activities performed. The effectiveness and cost-effectiveness of the intervention will be assessed with intention-to-treat analysis, using the clinical outcome and the assessment of quality of life (EQ-5D) 3 and 6 months after inclusion in the trial and the use of health services. Primary Outcome Measures: Patient Health Questionnaire (PHQ-9) score 3 months after inclusion in the study. A 50% reduction in the PHQ-9 score from baseline will be considered success. Secondary Outcome Measures: Depression - Patient Health Questionnaire (PHQ-9), Quality of life-EQD5, Adherence to medication-Morisky; Social functioning- WHODAS, Daily activities (BADS). Time Frame: 6 months after inclusion in the study. A 50% reduction on the PHQ-9 score from baseline will be considered success. Cost effectiveness measures (3 and 6 months). Use of health services and medication. General Quality of life (EQ-5D). Process evaluation: Data collected in the interviews with participants and Nurse Assistants about CONEMO system.