Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Oct 17, 2018
Open Peer Review Period: Oct 25, 2018 - Dec 20, 2018
Date Accepted: Apr 11, 2019
(closed for review but you can still tweet)
Characteristics of adopters of an online social networking physical activity smartphone app: a cluster analysis
ABSTRACT
Background:
To date, many online health behaviour programs developed by researchers have not been translated at scale. To inform translational efforts, health researchers must work with marketing experts to design cost-effective marketing campaigns. It is important to understand the characteristics of end-users of a given health promotion program, and identifying key market segments.
Objective:
This study aimed to describe the characteristics of the adopters of Active Team, a gamified online social networking physical activity app, and identify potential market segments, to inform future research translation efforts.
Methods:
Participants (n=545) were Australian adults aged 18-65 years who responded to general advertisements to join a randomized controlled trial (RCT) evaluating the Active Team app. At baseline they provided demographic (age, sex, education, marital status, BMI, location of residence and country of birth), behavioural (sleep, assessed by the Pittsburgh Quality Sleep Index (PSQI) and physical activity, assessed by the Active Australia Survey), psychographic information (health and wellbeing, assessed by the PERMA Profile, depression, anxiety and stress, assessed by the Depression and Anxiety Scale (DASS-21) and quality of life, assessed by the SF-12 Health Survey). Descriptive analyses and a k-medoids cluster analysis were performed using the software R 3.3.0 to identify key characteristics of the sample.
Results:
Cluster analyses revealed four clusters: (1) younger inactive women with poor well-being (n=218), characterised by a higher score on the Depression and Anxiety Stress Scale (DASS-21), low mental component summary score on the SF-12 Health Survey and relatively young age; (2) older, active women (n=153), characterized by a lower score on DASS-21, a higher overall score on the SF-12 Health Survey and relatively older age; (3) young, active but stressed men (n=58) with a higher score on DASS-21 and higher activity levels; and (4) older, low active and obese men (n=30), characterised by a high body mass index (BMI) and lower activity levels.
Conclusions:
Understanding the characteristics of population segments attracted to a health promotion program will guide the development of cost-effective research translation campaigns.
Citation
Per the author's request the PDF is not available.
Copyright
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