The impact of COVID-19 related lockdown restrictions on musculoskeletal health: a systematic review
Bibliographic record
Abstract
There is limited empirical evidence on whether Coronavirus disease 2019 (COVID-19) related lockdown restrictions precipitate or perpetuate musculoskeletal (MSK) disorders. This study was aimed to synthesis literature that assessed the impact of COVID-19 related lockdown restrictions on MSK health. A literature search was conducted using MEDLINE, CINAHL, PsycINFO, Allied and Complementary Medicine Database (AMED), Web of Science, and Scopus databases. Studies meeting the following criteria were included in the review: the condition being considered was MSK health, the intervention was COVID-19 related lockdown restrictions, cross sectional studies, cohort studies, case controlled, prospective studies and retrospective studies. Data were extracted by 2 independent researchers. Risk of bias was assessed by the Newcastle-Ottawa quality assessment scale. Evidence from included studies was summarised using narrative synthesis. Fourteen studies comprising 22,471 participants of the general population from Turkey (n = 5), Italy (n = 1), Poland (n = 1), Australia (n = 2), Jordan (n = 1), Bangladesh (n = 1), Estonia (n = 1), the Netherlands (n = 1) and Saudi Arabia (n = 1) have met the inclusion criteria. The sample size of populations studied ranged from 91 to 1054. The included studies used questionnaire, visual analogic scale, or growth mixture modelling. Except for one study, all the included studies reported increased prevalence and incidence of MSK disorders due to COVID-19 related lockdown restrictions. The findings suggest that COVID-19 related lockdown restriction led to increased MSK disorders. Home-based strategies such as physical activity programmes and ergonomic workspace could potentially guide public health authorities to avoid MSK health problem.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".