Applying Meaning and Self-Determination Theory to the Development of a Web-Based mHealth Physical Activity Intervention: Proof-of-Concept Pilot Study
Bibliographic record
Abstract
BACKGROUND: Meaning in life is positively associated with health, well-being, and longevity, which may be partially explained by engagement in healthier behaviors, including physical activity (PA). However, promoting awareness of meaning is a behavior change strategy that has not been tested in previous PA interventions. OBJECTIVE: This study aims to develop, refine, and pilot-test the Meaningful Activity Program (MAP; MAP to Health), a web-based mobile health PA intervention, theoretically grounded in meaning and self-determination theory, for insufficiently active middle-aged adults. METHODS: Following an iterative user-testing and refinement phase, we used a single-arm double baseline proof-of-concept pilot trial design. Participants included 35 insufficiently active adults in midlife (aged 40-64 years) interested in increasing their PA. After a 4-week baseline period, participants engaged in MAP to Health for 8 weeks. MAP to Health used a web-based assessment and just-in-time SMS text messaging to individualize the intervention; promote meaning salience; support the basic psychological needs of autonomy, competence, and relatedness; and increase PA. Participants completed measures of the hypothesized mechanisms of behavior change, including meaning salience, needs satisfaction, and autonomous motivation at pretest (-4 weeks), baseline (0 weeks), midpoint (4 weeks), and posttest (8 weeks) time points, and wore accelerometers for the study duration. At the end of the intervention, participants completed a qualitative interview. Mixed models compared changes in behavioral mechanisms during the intervention to changes before the intervention. Framework matrix analyses were used to analyze qualitative data. RESULTS: Participants were aged 50.8 (SD 8.2) years on average; predominantly female (27/35, 77%); and 20% (7/35) Asian, 9% (3/35) Black or African American, 66% (23/35) White, and 6% (2/35) other race. Most (32/35, 91%) used MAP to Health for ≥5 of 8 weeks. Participants rated the intervention as easy to use (mean 4.3, SD 0.8 [out of 5.0]) and useful (mean 4.3, SD 0.6). None of the hypothesized mechanisms changed significantly during the preintervention phase (Cohen d values <0.15). However, autonomy (P<.001; Cohen d=0.76), competence (P<.001; Cohen d=0.65), relatedness (P=.004; Cohen d=0.46), autonomous motivation (P<.001; Cohen d=0.37), and meaning salience (P<.001; Cohen d=0.40) increased significantly during the intervention. Comparison of slopes before the intervention versus during the intervention revealed that increases during the intervention were significantly greater for autonomy (P=.002), competence (P<.001), and meaning salience (P=.001); however, slopes were not significantly different for relatedness (P=.10) and autonomous motivation (P=.17). Qualitative themes offered suggestions for improvement. CONCLUSIONS: MAP to Health was acceptable to participants, feasible to deliver, and associated with increases in the target mechanisms of behavior change. This is the first intervention to use meaning as a behavior change strategy in a PA intervention. Future research will test the efficacy of the intervention in increasing PA compared to a control condition.
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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 | 0.022 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".