Document Type
Article
Publication Date
6-5-2026
Identifier
DOI: 10.2196/76991
Abstract
BACKGROUND: Mobile health (mHealth) interventions are growing in popularity, but less research has focused on low-income families, particularly interventions integrating wearable devices with automated personalized messages.
OBJECTIVE: We tested a preliminary wearable-integrated mHealth intervention with initial personalization elements among adults and youth from low-income urban communities, focusing on feasibility, acceptability, and preliminary evidence of physical activity behavior.
METHODS: Participants were 83 adults and 31 youth recruited through community health events held in low-income urban communities. Using a single-arm pre-post design, participants were enrolled into a 7-week beta-version mHealth intervention that integrated a Garmin activity monitor with automated text messages. Messages were sent 4 days/week and focused on increasing step counts using theory-based behavior change techniques related to goal setting, self-monitoring, reinforcement, contextual factors, and self-efficacy. Most messages were personalized by including calculations based on the step-count and step-goal data, using branching logic, and using 2-way question-and-response messages. Feasibility measures included enrollment, retention, fidelity of message delivery, and adherence to wearing the Garmin device. Acceptability measures included survey items and engagement with responding to 2-way messages. Changes in daily steps were explored using mixed-effects linear regression.
RESULTS: Enrollment and eligibility rates were 64% (84/132, adults) and 63% (31/49, youth), retention for physical activity measures was 84% (70/83) and 77% (24/31), and 99% (3910/3955) of the intended messages were delivered. Adults and youth adhered to wearing the Garmin on 82% (45/56) and 79% (44/56) of the study days, respectively. Overall acceptability ratings were 83% to 100%, with 97% (75/77) of adults and 100% (27/27) of youth indicating they would recommend the program. Adults and youth replied to a mean of 2.6 (SD 2.2) and 3.2 (SD 2.7) of the 7 text messages that asked for a reply, with higher engagement among adults who participated with their child. Pre-post changes in daily steps were β=240 (95% CI -387 to 866) for adults and β=413 (95% CI -877 to 1703) among youth, with larger changes observed among those in the highest tertile of engagement (adults: β=584, 95% CI -784 to 1952; n=19; youth: β=941, 95% CI -827 to 2709; n=11) and those who were meeting less than two-thirds of the physical activity guideline at baseline (adults: β=609, 95% CI -30 to 1247; n=47; youth: β=1406, 95% CI -94 to 2907; n=22).
CONCLUSIONS: Personalized mHealth physical activity interventions integrating wearable step trackers with automated text messaging appear to be feasible and acceptable among adults and youth from low-income communities. Step-count findings show promise for the intervention's ability to support individuals who are further from meeting physical activity guidelines and warrant more research among parent-child dyads. Overall, findings support additional research to optimize and evaluate similar interventions within this population group using fully powered randomized controlled trials.
TRIAL REGISTRATION: ClinicalTrials.gov NCT05110508; https://clinicaltrials.gov/ct2/show/NCT05110508.
Journal Title
JMIR Mhealth Uhealth
Volume
14
First Page
76991
Last Page
76991
PubMed ID
42247677
Keywords
African American; community engagement; medically underserved; text messaging; wearables.
Recommended Citation
Carlson JA, Materia F, Moon M, et al. Automated Physical Activity Support for Adults and Youth From Low-Income Communities: Single-Arm Pilot Study. JMIR Mhealth Uhealth. 2026;14:e76991. Published 2026 Jun 5. doi:10.2196/76991


Comments
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included.
Publisher's Link: https://mhealth.jmir.org/2026/1/e76991