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Published on: May 31, 2021
User engagement in a digital health intervention designed for young people who have experienced technology-assisted
Sandra Bucci1,2, Xiaolong Zhang1, Kaja Dabrowska1
1Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biological, Medical and Health Sciences, Manchester Academic Health Science, University of Manchester, Manchester, United Kingdom.
Background:
Technology-assisted sexual abuse (TASA) mostly involves the production and non-consensual sharing of sexual images; however, evidence-based support for young people (YP) who have experienced TASA is scant. Digital Health Interventions (DHIs) have the potential to increase access to support and provide timely therapeutic input in a familiar format to YP. However, studies describing engagement with DHIs is nascent. Our objective is to describe engagement patterns for YP people who used the i-Minds app.
Methods:
The i-Minds app is a co-designed mentalisation-based DHI for YP who have experienced TASA. Usage data was collected during the 6-week intervention window using Matomo analytics software and analysed according to the AMUsED framework.
Results:
Forty-one participants were onboarded to the app. Of these, 95 % completed the introductory mandatory module, and nearly half completed the remaining three modules. Median duration of app engagement was 33 days. Most participants used the app on weekdays in the afternoon. Demographic variables, namely gender not matching with sex assigned at birth/prefer not to disclose and higher baseline clinical severity were associated with higher app engagement.
Conclusions:
Participants showed high module completeness and engagement duration, suggesting the potential for real-world use. Potential participant-level predictors of engagement, such as gender identity and severity of TASA related traumatic stress and emotional distress, were identified. Achieving satisfactory engagement in DHIs is challenging yet necessary for delivering effective interventions. Future studies should explore participant-level predictors of engagement to inform real-world use of DHIs with a diverse sample.
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