Effect of pretesting on intentions and behaviour: A pedometer and walking intervention
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
This study addressed the influence of pedometers and a pretest on walking intentions and behaviour. Using a Solomon four-group design, 63 female university students were randomly assigned to one of four conditions: pedometer and pretest (n = 16), pedometer and no pretest (n = 16), no pedometer and pretest (n = 15), no pedometer and no pretest (n = 16). The pretest conditions included questions on walking, intentions to walk 12,500 steps per day, and self-efficacy for walking 12,500 steps per day. In the pedometer conditions a Yamax Digi-Walker SW-650 pedometer was worn for one week. All participants completed posttest questions. While significant pretest x pedometer interactions would have indicated the presence of pretest sensitisation, no such interactions were observed for either intention or self-reported walking. Wearing pedometers reduced intentions for future walking and coping self-efficacy. However, after controlling for pretest self-reported walking, pedometer use resulted in more self-reported walking. We conclude that wearing a pedometer increased self-reported walking behaviour but that a pretest did not differentially influence walking intentions, behaviour, or self-efficacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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