The Relationship Between Physical Activity and Quality of Life During the Confinement Induced by COVID-19 Outbreak: A Pilot Study in Tunisia
Bibliographic record
Abstract
The present study aimed to determine the relationship between physical activity (PA) and quality of life (QoL) during the confinement caused by the COVID-19 outbreak. A total of 216 participants (men: n = 112, women: n = 114) were included in the present study. They were divided into three groups [i.e., inactive group (IG): less than 600 metabolic equivalent of tasks (METs), n = 131; minimally active group (MAG): from 600 to 2,999 METs, n = 49; and health-enhancing PA group (HEPAG): 3,000 + METs, n = 36] based on their habitual PA level in the period of confinement. WHO Quality of Life Instrument-Short Form (WHOQOL-BREF) and International Physical Activity Questionnaire-BREF (IPAQ-BREF) questionnaires were used to assess QoL and PA intensities. The main findings of the present study showed that MAG and HEPAG have better total PA, physical, psychological, social, and environmental QoL domains scores than IG (all, p < 0.01). Small to large correlations (r ranging from 0.14 to 0.72) were also observed between total PA, total walking activity, total moderate-intensity PA, total vigorous-intensity PA, and QoL domains (all, p < 0.01). PA with light-, moderate-, and vigorous-intensities can be well recommended to decrease the negative psychosocial effect of confinement. However, longitudinal studies are needed to draw causal inferences and underpin more robust and evidence-based and informed recommendations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".