Texting to Increase Adolescent Physical Activity: Feasibility Assessment
Bibliographic record
Abstract
OBJECTIVE: Feasibility trials assess whether a behavior change program warrants a definite trial evaluation. This paper reports the feasibility of an intervention consisting of Self Determination Theory-informed text messages, pedometers, and goal prompts to increase adolescent physical activity. METHODS: A 4-group randomized design with baseline and immediate post-study assessments was used. Groups (pedometer; pedometer + goal prompt; pedometer + goal prompt + theory-informed texts; no-treatment control) were systematically varied to assess the additive effect of intervention components on objectively measured physical activity (ie, ActiGraph). The primary outcome of the 12-week intervention was program feasibility. Changes in average daily step counts and minutes of moderate-to-vigorous physical activity also were examined. Post-intervention research with a subset of participants examined program reactions. RESULTS: Participants (N = 160) were evenly split by sex, mostly 14-15 years old, and of diverse race/ethnicity. Feasibility criteria were met. The attrition rate was less than 2%. Modest increases in average daily step counts and moderate-to-vigorous physical activity were observed in all groups except the control group. Participants reported positive reactions to the intervention. CONCLUSIONS: An intervention consisting of pedometers, theory-informed texts, and goal prompts, is a feasible and acceptable method for promoting physical activity to adolescents.
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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 | 0.037 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".