Initial prototype testing of Ray's Night Out: A new mobile app targeting risky drinking in young people
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Hides, L
Zelenko, O
Quek, LH
Stoyanov, S
Tulloch, K
Johnson, D
Tjondronegoro, D
Kavanagh, DJ
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Abstract
Background Risky single occasion drinking (RSOD; ≥4 drinks in <6 h) more than doubles the risk of injury in young people (15–25 years). The potential role of smartphone apps in reducing RSOD in young people is yet to be explored. Objective To describe the initial prototype testing of ‘Ray's Night Out’, a new iPhone app targeting RSOD in young people. Method Quantitative and qualitative methods were used to evaluate the quality, perceived utility, and acceptability of the app among nine young people (19–23 years). Results Participants reported Ray's Night Out had good to excellent levels of functionality and visual appeal, acceptable to good levels of entertainment, interest and information, and acceptable levels of customization and interactivity. Young people thought the app had high levels of youth appeal, would prompt users to think about their alcohol use limits, but was unlikely to motivate a change in alcohol use in its current form. Qualitative data provided several suggestions for improving the app. Conclusion Following revision, Ray's Night Out could provide an effective intervention for RSOD in non help-seeking young people. A randomized controlled trial is currently underway to test the final prototype of the app.
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Computers in Human Behavior
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54
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© 2016 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
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Psychology
Cognitive and computational psychology
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Pocuca, N; Hides, L; Zelenko, O; Quek, LH; Stoyanov, S; Tulloch, K; Johnson, D; Tjondronegoro, D; Kavanagh, DJ, Initial prototype testing of Ray's Night Out: A new mobile app targeting risky drinking in young people, Computers in Human Behavior, 2016, 54, pp. 207-214