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. 2025 Jun 16:13:e51707.
doi: 10.2196/51707.

College Community-Based Physical Activity Support at a Public University During the COVID-19 Pandemic: Retrospective Longitudinal Analysis of Intra- Versus Interpersonal Components for Uptake and Outcome Association

Garrett I Ash #  1   2   3 , Selene S Mak #  4 , Adrian D Haughton  5 , Madilyn Augustine  6 , Phillip O Bodurtha  5 , Robert S Axtell  5 , Beatrice Borsari  1   2 , Jason J Liu  1   2 , Shaoke Lou  2 , Xin Xin  7   8 , Lisa M Fucito  6   9   10 , Sangchoon Jeon  11 , Matthew Stults-Kolehmainen  12   13 , Mark B Gerstein  1   2   14   15   16
Affiliations

College Community-Based Physical Activity Support at a Public University During the COVID-19 Pandemic: Retrospective Longitudinal Analysis of Intra- Versus Interpersonal Components for Uptake and Outcome Association

Garrett I Ash et al. JMIR Mhealth Uhealth. .

Abstract

Background: College students are vulnerable to setting long-term trajectories of low physical activity (PA) but are reachable via mobile health fitness tracking (eg, mobile health step counting) and interpersonal support tailored to the college community. However, no studies have statistically isolated the appeal and influence of these intra- and interpersonal components in college-based PA interventions.

Objective: This study retrospectively examined a college-based PA promotion program at a northeast US public university during the COVID-19 pandemic to (1) test the impact of student status on the use of intervention components and (2) determine whether such use was associated with successful retention and goal achievement in the program.

Methods: The university used a commercial platform for a 30-day PA promotion program during April 2021 with intrapersonal (step-tracker syncing, education, self-monitoring, and motivational messaging) and interpersonal (friend interactions and team games) components. App use was operationalized as intrapersonal (frequency of opening app, education, and self-monitoring) and interpersonal (friends made in-app and team affiliation and size).

Results: Campus-wide emails elicited sign-up by 156 undergraduate students, 57 graduate students, and 126 faculty and staff members. Objective 1 yielded the following results: undergraduates used the app less frequently (median 0.8, IQR 0.4-1.7 times per day) than other groups (graduate students: median 1.4, IQR 0.7-2.7 times per day; P=.01; faculty: median 1.3, IQR 0.7-2.7 times per day, H2=14.5; P=.001) but made the same number of friends (median 1-2) and teammates (median 8-9; P=.77 for friends and P=.93 for teammates). Objective 2 yielded the following results: most participants (313/335, 93.4%; 95% CI 90%-96%) were retained for the first 7 days, but by 30 days, retention dropped, most notably for undergraduate students (82/154, 53.2%; 95% CI 45%-61%), followed by graduate students (39/56, 70%; 95% CI 56%-81%) and faculty and staff (93/125, 74.4%; 95% CI 66%-82%; χ22=12.6; P<.001). Retention was associated with app engagement frequency (model hazard ratio 0.56, 95% CI 0.43-0.72; P<.001) and affiliation with a team having high median app engagement and a large size (intracluster correlation coefficient 0.064, 95% CI 0.001-0.164, P=.05). Meeting a daily step goal was associated with app engagement frequency (β=.72, SE=0.21; P=.001), number of friends (β=.40, SE 0.20; P=.04), and an initial motive of maintaining or increasing (rather than starting) PA (β=.99, SE=0.21; P<.001).

Conclusions: College students, compared with faculty and staff, used the app less frequently, used the app for a shorter duration before abandonment, and met the step goal on fewer days. Engagement with the program was associated with longer retention and better PA outcomes, which were critically modified by the interpersonal engagement. These findings suggest that college students using virtual PA support during times of physical isolation could benefit from more tailored implementation strategies (eg, timed prompts and team reassignments).

Keywords: education; faculty; goals; mobile apps; social networks; students; universities.

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Conflict of interest statement

Conflicts of Interest: GIA receives professional service fees from Calm.com [61] (nominal fee), Labfront (full fee), and GlucoseZone (full fee). LMF and GIA have a provisional patent filed for a digital system for lifestyle medicine (047162-5346-P1US) outside the submitted work. SSM, ADH, MA, POB, RSA, BB, JJL, SL, XX, SJ, MS-K, and MBG declare no potential conflicts of interest. The authors attest that Calm.com [61], Labfront, GlucoseZone, and a digital system for lifestyle medicine had no influence on the design of this study or its outcomes.

Figures

Figure 1
Figure 1
Retention survival curve according to engagements per day, which was the only predictor of retention retained in the parsimonious final model.
Figure 2
Figure 2
Retention (ie, duration of app use before abandonment) was clustered by team affiliation (intracluster correlation coefficient 0.064, 95% CI 0.001-0.164; P=.05). Therefore, we plotted average retention among team members in relation to team characteristics, including team size (bubble size) and median app engagements per day among team members (x-axis). It is visually apparent that the longer-retained individuals were those on teams with a larger size and higher median rate of app engagement. The dotted curve is for visual purposes and approximates retention days as 2.29 × ln(median engagement of team) + 24.29.
Figure 3
Figure 3
Temporal trends in steps per day relative to the cutoffs for the prize drawings (purple).
See this image and copyright information in PMC

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