MétaCan
Menu
Back to cohort
Record W2068935982 · doi:10.1093/occmed/kqu191

Health-care barriers for workers with HAVS in Ontario, Canada

2015· article· en· W2068935982 on OpenAlexaffabout
Thomas Bodley, Sabrina Nurmohamed, D. Linn Holness, R. House, Aaron Thompson

Bibliographic record

VenueOccupational Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsPublic Health OntarioUniversity of TorontoToronto Public HealthSt. Michael's Hospital
Fundersnot available
KeywordsMedicineSeriousnessHealth careFamily medicineOccupational medicineEnvironmental healthOccupational exposure

Abstract

fetched live from OpenAlex

BACKGROUND: Hand-arm vibration syndrome (HAVS) becomes irreversible unless it is identified early and progression prevented. AIMS: To describe the health-care-seeking behaviours of workers with HAVS and barriers to health care. METHODS: We invited all patients assessed for HAVS between 15 January and 27 March 2013 at a hospital-based occupational health clinic (OHC) in Ontario, Canada, to complete a questionnaire asking why and from whom they sought health care, reasons they waited to seek care and barriers they encountered in accessing care. We analysed the data using descriptive statistics. RESULTS: Forty-one (82%) patients agreed to participate. Thirty-seven had confirmed HAVS; 30 (84%) were Stockholm workshop vascular stage 2 or greater and 35 (97%) were sensorineural stage 1 or greater. The commonest employment sectors were construction [21 (57%)] and mining [6 (17%)]. The main reasons for seeking treatment were pain [11 (30%)], finger numbness [8 (22%)] and functional limitations [5 (14%)]. The commonest initial point of health care was the family physician [23 (66%)]. The mean wait between symptom onset and seeking treatment was 3.4 years, while the mean time between onset and OHC assessment was 9 years. Reasons for delay in seeking care were ignorance of the seriousness and irreversibility of HAVS and ability to continue to work. Family physicians suspected HAVS in 17% of cases and recommended job modification in 34%. CONCLUSIONS: Workers with HAVS in Ontario delay seeking health care. Primary care physicians often fail to recognize HAVS. Barriers to health care include ignorance of HAVS and of the importance of prevention.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.215
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.036
GPT teacher head0.339
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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueOccupational MedicineSame topicEffects of Vibration on HealthFrench-language works237,207