Assessing Physical Activity among Canadian Healthcare Professionals
Bibliographic record
Abstract
INTRODUCTION: Physical Activity is well known to keep illness at bay and promote healthy living among people. In today’s fast paced life, obesity is increasing amongst people and this can be eliminated through proper physical activity. AIM: To assess the physical activity among various Canadian healthcare professionals. MATERIALS AND METHOD: The present study was a multi-institution based observational study using a pre-tested, pre-validated questionnaire distributed among various colleges and privately practicing healthcare professionals in Canada using a close-ended questionnaire divided into five sections and containing 28 questions. Data analysis was done using SPPS version 19.0 and the independent samples t-test and multiple logistic regression was applied. Data was only considered significant when p was less than or equal to 0.05.RESULTS: Most males belonged to the “overweight” category (56.3%), while females belonged to the “normal” category (56.3%). A lesser number of females reported being obese (5.4%) as compared to their male counterparts; significant difference (p=0.05) was observed between males and females in the underweight category. Males were found to be insufficiently active (41.8%), while 44.8% females were found to be in the active category. Statistical differences were observed while comparing the physical activity levels between the males and females belonging to the Insufficiently Active category(p=0.02).CONCLUSION: Healthcare professionals should be reminded regarding their general health and the role of physical exercise in keeping them healthy.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".