Abstract summary 

Unhealthy alcohol use (UAU) is a major public health challenge, particularly in low- and middle-income countries. Mozambique is the fourth poorest country in the world where half of the population lives below the poverty line. UAU is frequent among drinkers in Mozambique; however, resources and infrastructure to treat UAU are very limited. This paper examines how task-shifting and a provider-facing mobile health application are being used to improve access to care. In this paper, the feasibility, acceptability and appropriateness of a provider-facing mobile health application being used under a task-shifting model to identify UAU and provide a four-session brief motivational interviewing intervention are described.The study used a sequential exploratory mixed-methods design with a QUAL → quan structure. First, 15 psychiatric technicians and primary care providers in Mozambique's Nampula Province participated in semi-structured interviews. These interviews were recorded and transcribed. Then, 45 providers completed a 12-item quantitative survey on tablets. Quantitative analysis used descriptive statistic calculation and qualitative analysis used thematic analysis.Nonspecialized providers found the mobile health app to be acceptable, appropriate, and feasible when delivering a 4-session brief motivational intervention under a task-shifting model. Central benefits of the technology were enhanced standardization and efficiency of sessions as well as feelings of legitimacy when interacting with patients. Main concerns were feasibility of implementing the intervention due to time constraints of workload and internet connectivity issues.Provider-facing technology shows promise in supporting task-shifting models that can expand alcohol intervention services and increase access to care in low- and middle-income countries. Providers without specialized training in behavioral health interventions can provide critical services to patients with UAU and provider-facing mobile health applications may help bring such models to scale.

Authors & Co-authors:  O'Grady Megan A MA Mootz Jennifer J Suleman Antonio A Sweetland Annika A Teodoro Eugénia E Anube Anibal A Feliciano Paulino P Bezuidenhout Charl C Dos Santos Palmira Fortunato PF Fumo Wilza W Gouveia Lidia L Pinsky Ilana I Mello Milena M Kann Bianca B Wainberg Milton L ML

Study Outcome 

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