Evidence map›Paper›PMID 42247677›Full record

ArticleJMIR mHealth and uHealth2026

Automated Physical Activity Support for Adults and Youth From Low-Income Communities: Single-Arm Pilot Study.

Jordan A Carlson, Frank Materia, Mallory Moon, Suryeon Ryu, Cory Yeager, Chelsea Steel, Kacee Shields, Harpreet Singh Gill, Jannette Berkley-Patton, Delwyn Catley

Registry-linked trialAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05110508 (Active KC), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05110508 nacompletednot on this map

Active KC: a Text Message Based Intervention for Physical Activity

TypeinterventionalSponsorChildren's Mercy Hospital Kansas CityRan2021 to 2022Enrolled210ConditionsPhysical Activity, Patient EngagementArmsText Based Behavioral Intervention for Physical Activity
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jordan A CarlsonCenter for Children's Healthy Lifestyles & Nutrition, Children's Mercy Hospital, Kansas City, MO, United States.ORCID 0000-0002-6008-7983
Frank MateriaDepartment of Otolaryngology-Head and Neck Surgery, University of Kansas Medical Center, Kansas City, KS, United States.ORCID 0000-0002-8015-1743
Mallory MoonCenter for Children's Healthy Lifestyles & Nutrition, Children's Mercy Hospital, Kansas City, MO, United States.ORCID 0009-0008-3332-7049
Suryeon RyuCenter for Children's Healthy Lifestyles & Nutrition, Children's Mercy Hospital, Kansas City, MO, United States.ORCID 0000-0002-8080-8821
Cory YeagerCenter for Children's Healthy Lifestyles & Nutrition, Children's Mercy Hospital, Kansas City, MO, United States.ORCID 0009-0005-9273-9519
Chelsea SteelCenter for Children's Healthy Lifestyles & Nutrition, Children's Mercy Hospital, Kansas City, MO, United States.ORCID 0000-0002-7119-5840
Kacee ShieldsCenter for Children's Healthy Lifestyles & Nutrition, Children's Mercy Hospital, Kansas City, MO, United States.ORCID 0009-0006-9302-3093
Harpreet Singh GillResearch Informatics, Children's Mercy Hospital, Kansas City, MO, United States.ORCID 0009-0001-9512-7615
Jannette Berkley-PattonDepartment of Biomedical and Health Informatics, School of Medicine, University of Missouri-Kansas City, Kansas City, MO, United States.ORCID 0000-0003-0235-7057
Delwyn CatleyDepartment of Psychology, San Diego State University, San Diego, CA, United States.ORCID 0000-0002-7270-8732

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile 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.

objectiveWe 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.

methodsParticipants 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.

resultsEnrollment 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).

conclusionsPersonalized 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 registrationClinicalTrials.gov NCT05110508; https://clinicaltrials.gov/ct2/show/NCT05110508.

Indexed as

ExercisePovertyAdolescentAdultDigital HealthFemaleHumansMaleMiddle AgedPilot ProjectsTelemedicineText MessagingWearable Electronic DevicesAfrican Americancommunity engagementmedically underservedtext messagingwearables

Identifiers

PMID42247677
PMCPMC13282599

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.