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Low back pain among doctors in a tertiary institution in Southern Nigeria

2023· article· en· W4321134073 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGSC Advanced Research and Reviews · 2023
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLow back painOverweightBack painLogistic regressionOdds ratioUnivariate analysisSpecialtyPhysical therapyStatistical significanceFamily medicineObesityInternal medicineMultivariate analysisAlternative medicine

Abstract

fetched live from OpenAlex

Introduction: Low back pain is common in health workers with deleterious effects on their work and quality of life. Aims: This study aimed to identify work related disabilities and risk factors for low back pain amongst doctors in Nigeria. Methodology: One hundred and fifty-four doctors were recruited and a structured proforma was administered using the Aberdeen low back pain scale, revised Oswestry and Quebec pain scales as guides. Data was analysed using Statistical Package for the Social sciences version 25. Univariate and multivariable logistic regression were used to calculate the odds ratios for the independent risk factors for LBP. Level of significance was determined at p < 0.05. Results: The male to female ratio was 1.8:1 and 70(45.50%) doctors were in the age range of 31-40years. Half (50%) of the respondents were obese while 21.9% were overweight. The duration of an episode of back pain was less than a week in 130 (84.40%) persons. A few doctors- 22(14.29%) reported that low back pain had prevented them from coming into work, of these, 12 had been absent for a day, four for 2-7 days and six for 1 to 4 weeks. Anesthetists were ten times more likely to develop low back pain than any other medical specialty (OR=10.99, 95%CI=1.336-90.545, p=0.026) and increasing age and BMI were also identified as predictors of low back pain. Conclusion: Low back pain is associated with poor productivity among doctors and can impact health care delivery.

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.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.382
Teacher spread0.340 · 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