Healthy Campus 2010: Physical Activity Trends and the Role Information Provision
Bibliographic record
Abstract
BACKGROUND: The primary purpose of this investigation was to examine the frequency and type of self-reported physical activity behavior in postsecondary students with reference to Healthy Campus 2010 objectives. The secondary purpose was to explore the role of information provision in terms of promoting physical activity behavior in postsecondary students. METHODS: Postsecondary students were assessed (N = 127360). Employing a trend survey design, the frequency and type of physical activity behavior was assessed along with physical activity/fitness information provision across a five year period between 2000 to 2004. RESULTS: In 2004, respondents meeting Healthy Campus 2010 objectives for self-reported moderate and vigorous physical activity (MVPA) was 42.20% (95% CI = 41.75 to 42.65) and 48.60% (95% CI = 48.14 to 49.06) for strength (STRENGTH) training behavior. Progress quotients demonstrated that 12.93% and 7.87% of target objective for MVPA and STRENGTH respectively had been achieved from baseline. Those who received information reported engaging in more frequent physical activity behavior compared with those who did not (P < .001). CONCLUSIONS: Results suggest the need for continued commitment to increasing physical activity behavior. The provision of physical activity/fitness information may be one mechanism through which this can be achieved.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".