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Record W4401485770 · doi:10.1002/msc.1920

Does COVID‐19 Related Lockdown Restrictions Impact People With Musculoskeletal Disorders? A Systematic Review

2024· review· en· W4401485770 on OpenAlexaboutno aff
Francis Fatoye, C. Fatoye, Joyceline Lawoe, Chidozie Emmanuel Mbada, Tadesse Gebrye

Bibliographic record

VenueMusculoskeletal Care · 2024
Typereview
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnxietyDepression (economics)Coronavirus disease 2019 (COVID-19)Quality of life (healthcare)MEDLINESystematic reviewInclusion (mineral)Family medicineDiseasePsychiatryPsychologyNursingPathology

Abstract

fetched live from OpenAlex

BACKGROUND: As a result of coronavirus disease 2019 (COVID-19) related lockdown restrictions, people with musculoskeletal (MSK) disorders could be at increased risk of physical and psychological disabilities. This review aimed to summarise the impact of COVID-19 related lockdown restrictions on people with MSK disorders. METHODS: Six electronic databases were searched for studies in the English language published until June 10, 2024. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to identify, select, and critically appraise relevant research. Two reviewers independently abstracted data from the included studies. Data were summarised using narrative synthesis, and the Newcastle-Ottawa Scale was used for quality assessment. RESULTS: The search strategy identified 637 articles, 129 of which were removed as duplicates. Fifteen studies that met the inclusion criteria were analysed. The sample size the studies reviewed ranged from 40 to 1800. Having MSK disorders during COVID-19 related lockdown restrictions led to increased risk of pain, stress, depression, anxiety, MSK related injuries, decreased quality of life and increased use of emergency department. CONCLUSIONS: This is the first study to report that COVID-19 related lockdown restrictions led to increased risk of pain, MSK injuries and healthcare resource utilisation as well as decreased quality of life among patients with MSK disorders. These results may help inform policy and management strategies in future for people with MSK disorders to mitigate the negative impact of pandemic.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.205
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.009
Bibliometrics0.0010.005
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.011
GPT teacher head0.346
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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