Designing Culture-based Persuasive Technology to Promote Physical Activity among University Students
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Overweight and obesity are taking a huge toll on nations' financial and health resources annually. Student populations are at risk due to their sedentary lifestyles and the high demands of academic scholarship, leaving them with little or no time to exercise. Recently, persuasive technology, promoting physical activity, has been proposed. However, the traditional "one-size-fits-all" approach has not been effective among the student population. This calls for a newer and more effective approach, which leverages the available recreational and technological resources in the university at personal, social and cultural levels. In an effort to address students' sedentary behaviors, I aim to combine user behavior models, persuasive technology design and cultural strategies from Health Sciences for a more personalized and effective intervention. This paper presents the approach and the preliminary results of two user studies among 218 and 292 subjects from a Canadian and a Nigerian university respectively.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it