Testing different engagement strategies, language and content style in an early prototype of a mental health screening smartphone application

None listed

Our research team has recently been awarded an Australian Mental Health Award by Beyondblue and the Movember Foundation, that will fund a program of research aimed at developing and evaluating a range of new e-health interventions for working men, termed ‘Men@Work’. One of the first parts of this program is the development of a new smart-phone application that will allow men to screen themselves for both symptoms and risk factors for common mental health problems. The working title for this new smartphone application is ‘Mindgauge’. This registration covers one part of the development process; the testing of the relative appeal of different feedback texts, language, measurement tools, and content style with an early prototype of the ‘Mindguage’ application. The testing of different features and content styles within an early prototype or minimum viable product (MVP) is considered a usual early stage in the development of complex new smartphone applications. The specific questions that this research project (and registration application) will aim to answer are: a) What feedback texts are most persuasive for convincing participants to follow links to recommended interventions? b) What mood widget measurement is most appropriate? And does it map onto other standardised tools? c) Are app notifications acceptable to users? d) How interested are people in finding out about their risk? Does it impact engagement? Data collection Participants will complete quizzes pertaining to: Mood and anxiety symptoms (K6 questionnaire) and Wellbeing (WHO 5 Well-being Index) and sliding scales measuring alcohol use quantity; hours slept; perceived stress; physical and social activity. Participants who are deemed at-risk of mental health problems on the quizzes will be randomly allocated to receiving one of the following feedback types: normative positive, normative negative, theory-driven, humour-driven. The outcome measure is number of clicks to external interventions. They will be reassured that techniques are available to help improve these factors and immediately following their feedback will be provided information and a link to a variety of online self help or information sites. Participants then use the app to monitor mood and alcohol quantity, sleep quality, stress, and physical and social activity. They have the option of finding out their current risk of mental health problems. In a subsequent randomisation participants will receive one of five different mood measurement gauges, outcomes will include engagement (quantity and frequency of check-ins with app) and Signal quality (correlation of signal to weekly k6 scores and accuracy of a baseline linear classifier trained to predict k6 score from mood signal.