The cumulative effects of consecutive days of prolonged, physical work or activity on heat strain and physical performance: a systematic review
Bibliographic record
Abstract
With climate warming, there is an urgent need to understand the health effects of occupational heat exposure. This systematic review examined the cumulative effects of consecutive days of prolonged physical work or activity on heat strain and physical performance. Electronic databases MEDLINE, SPORTDiscus, PsychInfo, and Academic Search Complete were searched until July 2024 with terms related to work, consecutive days, and heat. Studies were included if they involved ≥4 h of physical work/activity on ≥2 consecutive days, and included a measure of heat strain (e.g., core temperature) or physical performance (e.g., repetitions). After removing duplicates, 6030 studies were screened (title and abstract), 133 progressed to full-text screening, and 33 met the inclusion criteria with risk of bias assessed. However, only five studies used standardized environmental and work conditions across days. Synthesis of the cumulative effects (without meta-analysis) was therefore restricted to these studies. None observed a cumulative impact on heat strain, as indexed by a higher core temperature or heart rate compared to day 1. None reported a reduction in physical task performance across days. These findings indicate that the cumulative effects of occupational heat exposure on heat strain and physical task performance were minimal, although evidence supporting this conclusion is sparse. PROSPERO registration: CRD42023452936.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".