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Record W2083032416 · doi:10.1097/bcr.0000000000000041

Returning to Work After Electrical Injuries

2014· article· en· W2083032416 on OpenAlexafffundabout
Mary Stergiou‐Kita, Elizabeth Mansfield, Mark Bayley, J. David Cassidy, Angela Colantonio, Manuel Gómez, Marc G. Jeschke, Bonnie Kirsh, Vicki L. Kristman, Joel Moody, Oshin Vartanian

Bibliographic record

VenueJournal of Burn Care & Research · 2014
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsLakehead UniversityInstitute for Work & HealthHealth Sciences CentreSunnybrook HospitalInstitute for Clinical Evaluative SciencesDefence Research and Development CanadaUniversity of TorontoUniversity Health NetworkPublic Health OntarioSunnybrook Health Science CentreToronto Rehabilitation Institute
FundersCanadian Institutes of Health Research
KeywordsMedicineWork (physics)Medical emergencyElectrical InjuriesPoison controlInjury prevention

Abstract

fetched live from OpenAlex

The objective of this study was to gain an understanding of workers' experiences with returning to work, the challenges they experienced, and the supports they found most beneficial when returning to work after a workplace electrical injury. Thirteen semistructured qualitative telephone interviews were conducted with individuals who experienced an electrical injury at the workplace. Participants were recruited from specialized burns rehabilitation programs in Ontario, Canada. Interviews were transcribed verbatim and thematic analysis used to analyze the qualitative interviews. Data regarding workers' demographics, injury events, and occupational categories were also gathered to characterize the sample.Participants identified three distinct categories of challenges: 1) physical, cognitive, and psychosocial impairments and their effects on their work performance; 2) feelings of guilt, blame, and responsibility for the injury; and 3) having to return to the workplace or worksite where the injury took place. The most beneficial supports identified by the injured workers included: 1) support from family, friends, and coworkers; and 2) the receipt of rehabilitation services specialized in electrical injury. The most common advice to others after electrical injuries included: 1) avoiding electrical injury; 2) feeling ready to return to work; 3) filing a Workplace Safety and Insurance Board injury/claims report;4) proactive self-advocacy; and 5) garnering the assistance of individuals who understood electrical injuries to advocate on their behalf. Immediate and persistent physical, cognitive, psychosocial, and support factors can affect individuals' abilities to successfully return to work after an electrical injury. Specialized services and advocacy were viewed as beneficial to successful return to work.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.094
GPT teacher head0.538
Teacher spread0.444 · 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 source (direct Gemma or distilled Codex), 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

Citations21
Published2014
Admission routes3
Has abstractyes

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