Factors associated with headache and neck pain among telecommuters – a five days follow-up
Bibliographic record
Abstract
BACKGROUND: The current sanitary crisis brought on by the COVID-19 recently forced a large proportion of workers to adopt telecommuting with limited time to plan transition. Given that several work-related risk factors are associated with headache and neck pain, it seems important to determine those associated with headache and neck pain in telecommuters. The main objective of this study was to identify which telecommuting and individual associated factors are related with headache and neck pain occurrence in telecommuters over a five days follow-up. The second objective was to evaluate the impact of wearing a headset on headache and neck pain intensity in telecommuters. METHODS: One hundred and sixty-two participants in telecommuting situation were recruited. Baseline assessment included sociodemographic data, headache and neck pain-related disability (6-item Headache Impact Test (HIT-6) and Neck Bournemouth Questionnaire (NBQ)), headache and neck pain frequency and intensity as well as questions about the wearing of a headset (headset wearing, headset type and headset wearing hours). A prospective data collection of headache, neck pain and headset wearing was conducted using daily e-mail over a 5-day follow-up. A stepwise multivariate regression model was performed to determine associated factors of headache or neck pain occurrence during the follow-up. A t-test was conducted to assess the impact of headset wearing on headache and neck pain intensity during the follow-up. RESULTS: = 0.182; p < 0.001). T-test showed no difference between participants that wore a headset and participant that did not wore a headset on mean headache (p = 0.94) and neck pain (p = 0.56) intensity during the five days follow-up. CONCLUSION: Although several work-related risk factors are associated with headache and neck pain in workers, telecommuting did not present the same risks. Working set-up did not have a significant impact on headache and neck pain as headache-related disability was the only associated factor of future headache episodes and neck-pain related disability was the only associated factor of future neck pain episodes. Also, wearing a headset had no impact on headache and neck pain in telecommuters.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".