A personalized mobile app for physical activity: An experimental mixed-methods study

被引:5
|
作者
Tong, Huong Ly [1 ]
Quiroz, Juan C. [2 ]
Kocaballi, Ahmet Baki [3 ]
Ijaz, Kiran [4 ]
Coiera, Enrico [4 ]
Chow, Clara K. [1 ]
Laranjo, Liliana [1 ]
机构
[1] Univ Sydney, Fac Med & Hlth, Westmead Appl Res Ctr, Sydney, NSW, Australia
[2] Univ New South Wales, Ctr Big Data Res Hlth, Sydney, NSW, Australia
[3] Univ Technol Sydney, Sch Comp Sci, Sydney, NSW, Australia
[4] Macquarie Univ, Ctr Hlth Informat, Australian Inst Hlth Innovat, Sydney, NSW, Australia
来源
DIGITAL HEALTH | 2022年 / 8卷
关键词
Mobile applications [MeSH; exercise [MeSH; physical activity; health behavior [MeSH; personalization; tailoring; digital technology [MeSH; BEHAVIOR; HEALTH; INTERVENTIONS; TECHNOLOGY; CANCER; DESIGN;
D O I
10.1177/20552076221115017
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Objectives To investigate the feasibility of the be.well app and its personalization approach which regularly considers users' preferences, amongst university students. Methods We conducted a mixed-methods, pre-post experiment, where participants used the app for 2 months. Eligibility criteria included: age 18-34 years; owning an iPhone with Internet access; and fluency in English. Usability was assessed by a validated questionnaire; engagement metrics were reported. Changes in physical activity were assessed by comparing the difference in daily step count between baseline and 2 months. Interviews were conducted to assess acceptability; thematic analysis was conducted. Results Twenty-three participants were enrolled in the study (mean age = 21.9 years, 71.4% women). The mean usability score was 5.6 +/- 0.8 out of 7. The median daily engagement time was 2 minutes. Eighteen out of 23 participants used the app in the last month of the study. Qualitative data revealed that people liked the personalized activity suggestion feature as it was actionable and promoted user autonomy. Some users also expressed privacy concerns if they had to provide a lot of personal data to receive highly personalized features. Daily step count increased after 2 months of the intervention (median difference = 1953 steps/day, p-value <.001, 95% CI 782 to 3112). Conclusions Incorporating users' preferences in personalized advice provided by a physical activity app was considered feasible and acceptable, with preliminary support for its positive effects on daily step count. Future randomized studies with longer follow up are warranted to determine the effectiveness of personalized mobile apps in promoting physical activity.
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页数:13
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