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Record W7036985229

A Cross-sectional Study on Lower Back Pain amongst Medical Students and Foundation Doctors in Malta

2025· article· en· W7036985229 on OpenAlexaff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Taxonomy and Phylogenetics
Canadian institutionsWestern University
Fundersnot available
KeywordsFoundation (evidence)Back painLow back painHuman factors and ergonomicsHealth careSample (material)PopulationQuality (philosophy)Occupational safety and health
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: Lower back pain (LBP) is one of the most common health problems and a significant global burden on both an individual and economic level. It is especially prevalent amongst healthcare workers and students, partly due to working conditions. This study aimed to investigate the prevalence and common risk factors of LBP amongst medical students and foundation doctors in Malta. METHODS: A mixed-methods cross-sectional, online questionnaire based on the Nordic Musculoskeletal Questionnaire was distributed to medical students and foundation doctors in Malta. Quantitative data was analyzed by means of Chi-squared test followed by multivariate analysis, whilst qualitative data was organized into broad themes. RESULTS: A total of 319 individuals participated in the questionnaire. The 12-month and 7-day prevalence of lower back pain in the sample population overall is 78.14% and 28.71% respectively. Females and students who worked during medical school were more likely to have LBP (p < 0.001 and p= 0.040 respectively). Long working/studying hours and awkward sitting/standing postures were identified as contributors to LBP by participants. CONCLUSIONS: Lower back pain is a highly prevalent issue amongst medical students and foundation doctors in Malta. If unaddressed, it will continue to contribute to disability, decreased quality of life and reduced career longevity. An approach based on Human Factors and Ergonomics principles focusing on ergonomic design and ergonomics training in medical school can lead to improved staff wellbeing and increase patient safety and efficiency.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.210
GPT teacher head0.514
Teacher spread0.304 · 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; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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