Effectiveness of a Hybrid Community-Based Heart-Healthy Lifestyle Intervention: Three-Arm Randomized Controlled Trial Integrating mHealth and Motivational Interviewing
Bibliographic record
Abstract
BACKGROUND: Limited empirical evidence exists on the effectiveness of a hybrid approach to heart-healthy lifestyle interventions that integrates mobile health (mHealth) technology with face-to-face counseling. Moreover, its superiority over exclusive mHealth use in promoting heart-healthy behavioral outcomes within a community setting remains unclear. OBJECTIVE: This study aims to evaluate the effectiveness of a hybrid community-based approach to heart-healthy lifestyle intervention incorporating a mobile app and motivational interviewing among community-dwelling adults without a history of cardiovascular disease. METHODS: We conducted a 3-arm, parallel-group, randomized controlled trial with assessments at baseline and after 12 weeks. A total of 75 participants, each presenting at least 1 component of metabolic syndrome and no history of cardiovascular disease, were randomly assigned to 1 of 3 groups: hybrid (n=25), mobile (n=25), or control (n=25). Participants were recruited through an online platform. The hybrid group underwent a 12-week hybrid intervention combining a mobile app (ie, "My HeartHELP") and face-to-face motivational interviewing led by a nursing researcher. The mobile group used only the mobile app, while the control group received written material on general heart health. The intervention was facilitated by 3 trained nursing researchers. The primary outcome was a composite score of "heart-healthy behaviors," while secondary outcomes included scores for heart-healthy "information," "self-efficacy," "motivation," and cardiovascular parameters. The trial was conducted in 2 rounds from October 2022 to May 2023. An intention-to-treat analysis was performed. RESULTS: =3.90, P=.03) following the 12-week intervention. Particularly, the hybrid group-unlike the mobile group-showed significantly greater improvement in dietary behavior, a subscale of heart-healthy behavior, compared with the control group, and demonstrated significantly greater improvements in interest or enjoyment, a core subscale of intrinsic motivation, than the mobile and control groups. CONCLUSIONS: The hybrid community-based heart-healthy lifestyle intervention-integrating a mobile app and motivational interviewing-demonstrated overall effectiveness comparable to the mobile app alone, while yielding greater improvements in dietary behavior and core intrinsic motivation. These findings highlight the potential of mHealth apps as practical, stand-alone tools to promote cardiovascular health, particularly in community settings with limited access to in-person professional support. However, incorporating motivational interviewing may further enhance internalized motivation and complex behavior changes over time. Health professionals can therefore adopt mHealth either independently or in combination with motivational interviewing. Future studies should optimize integration strategies to enhance effectiveness and evaluate the long-term sustainability of such hybrid approaches. TRIAL REGISTRATION: ISRCTN Registry ISRCTN83643383; https://www.isrctn.com/ISRCTN83643383. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1161/circ.147.suppl_1.P147.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".