Persuading Students to Exercise: What Is the Best Way to Frame Messages for Normal-Weight Versus Overweight/Obese University Students?
Bibliographic record
Abstract
OBJECTIVE: The authors investigated the effect of gain-framed (GF) compared with loss-framed (LF) messages on exercise behaviors in normal weight and among overweight/class I obese. The authors also examined which groups would have significantly improved exercise behaviors over time. PARTICIPANTS: Sixty-four undergraduates were randomized to the 4 groups by message type and weight category from September 2008 to December 2011. METHODS: After screening, students received messages and attended an exercise instruction session. RESULTS: There were no significant differences between GF or LF message groups among normal weight or overweight/obese on the primary outcomes at posttest. After receiving the GF messages, the overweight/obese group was the only group to have a significant increase on all 3 primary outcomes: fitness center attendance (p = .038), combined moderate- and vigorous-intensity activity (p = .005), and strength training (p = .037). CONCLUSIONS: The exercise behaviors of undergraduate students who are overweight or obese can benefit from GF messages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".