The Intervention Effect of SMS Delivery on Chinese Adolescent’s Physical Activity
Bibliographic record
Abstract
To examine the effects of short messaging service (SMS) frequency and timing on the efficacy of an SMS-intervention for Hong Kong Chinese adolescents, sixty nine students aged between 12 and 16 (mean age 13.75 ± 0.90) were recruited from five schools in Hong Kong. Participants were randomly assigned into one of five groups: high-frequency + self-selected timing (HST), low-frequency + self-selected timing (LST), high-frequency + assigned timing (HAT), low-frequency + assigned timing (LAT) and the control group. The total duration of the intervention was four weeks. No significant intervention effects were detected in adolescent’s PA among the five groups (F = 1.14, p = 0.346). No significant differences were observed in the stage movement among the five groups (χ2 = 6.18, p = 0.627). No significant differences appeared in the exercise benefits, barriers and benefits/barriers differential scores. However, a growth trend in the exercise benefits score in the LST and HAT groups was found in contrast to the downswing in the control group. The exercise barriers score in the HST group showed the largest reduction after intervention. The benefits/barriers differential score in all the intervention groups increased, whereas it decreased in the control group. Although an increase is demonstrated in the high dosage SMS frequency and timing, no significant intervention effects were found among the five groups in PA behavior, stage of change and exercise benefits and barriers among Hong Kong Chinese 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".