Texting to Increase Physical Activity Among Teenagers (TXT Me!): Rationale, Design, and Methods Proposal
Bibliographic record
Abstract
BACKGROUND: Physical activity decreases from childhood through adulthood. Among youth, teenagers (teens) achieve the lowest levels of physical activity, and high school age youth are particularly at risk of inactivity. Effective methods are needed to increase youth physical activity in a way that can be maintained through adulthood. Because teens text a great deal, text messages promoting walking, a low cost physical activity, may be an effective method for promoting sustainable physical activity. OBJECTIVE: The objective of our study was to determine the effect of pedometers, self selected step goals, and texts grounded in the self-determination theory (SDT) on physical activity among the teens. METHODS: "TXT Me!" was a 12 week intervention that texted 14-17 year olds to increase their daily physical activity by increasing the number of steps they take each day. The intervention was grounded in the SDT. Formative research with the teens helped construct the intervention and develop the texts. A total of 84 texts were developed (12 to set a step goal, and 72 promoting autonomy, competence, and relatedness). The pilot evaluation used a four group, randomized design (n=160). After baseline data collection, the participants were randomized to one of four conditions (no treatment control, pedometer only, pedometer + weekly prompts, pedometer + weekly prompts + SDT grounded texts). Data were collected at baseline and immediately upon completion of the study. The primary outcome was physical activity, measured by 7 days of accelerometry. Basic psychological needs, physical activity motivation, process evaluation, and program satisfaction data were also collected. RESULTS: To our knowledge, this is one of the first studies to explore the use of stand alone, SDT grounded texts, supported by pedometers and prompts to set a self selected step goal, as a method for increasing physical activity among teens. CONCLUSIONS: This pilot study will contribute valuable information regarding whether theoretically grounded text messages show promise as an effective method to increase physical activity among teens. TRIAL REGISTRATION: Clinicaltrials.gov NCT01482234; http://clinicaltrials.gov/ct2/show/NCT01482234 (Archived by WebCite at http://www.webcitation.org/6NYvRMOoq).
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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 | 0.027 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".