Examining the initial usability, acceptability and feasibility of a digital mental health intervention for college students in India
Generalised anxiety disorder (GAD) is prevalent among college students in India; however, barriers like stigma, treatment accessibility and cost prevent engagement in treatment. Web‐ and mobile‐based, or digital, mental health interventions have been proposed as a potential solution to increasing tr...
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Veröffentlicht in: | International journal of psychology 2020-08, Vol.55 (4), p.657-673 |
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Sprache: | eng |
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Zusammenfassung: | Generalised anxiety disorder (GAD) is prevalent among college students in India; however, barriers like stigma, treatment accessibility and cost prevent engagement in treatment. Web‐ and mobile‐based, or digital, mental health interventions have been proposed as a potential solution to increasing treatment access. With the ultimate goal of developing an engaging digital mental health intervention for university students in India, the current study sought to understand students' reactions to a culturally and digitally adapted evidence‐based cognitive behavioural therapy (CBT) for GAD intervention. Specifically, through theatre testing and focus groups with a non‐clinical sample of 15 college students in India, the present study examined initial usability, acceptability and feasibility of the “Mana Maali Digital Anxiety Program.” Secondary objectives comprised identifying students' perceived barriers to using the program and eliciting recommendations. Results indicated high usability, with the average usability rating ranking in the top 10% of general usability scores. Participants offered actionable changes to improve usability and perceived acceptability among peers struggling with mental health issues. Findings highlight the benefits of offering digital resources that circumvent barriers associated with accessing traditional services. Results build on existing evidence that digital interventions can be a viable means of delivering mental healthcare to large, defined populations. |
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ISSN: | 0020-7594 1464-066X |
DOI: | 10.1002/ijop.12640 |