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Record W3159196716 · doi:10.1097/htr.0000000000000687

Vocational Outcomes After Traumatic Brain Injury; Prevalence and Risk Factors After 1 Year in a Multivariable Model

2021· article· en· W3159196716 on OpenAlexaff
Rajiv Singh, Jeremy Dawson, Subhashis Basu, Thomas J. Humphries, Suzanne Mason, Fiona Lecky

Bibliographic record

VenueJournal of Head Trauma Rehabilitation · 2021
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsDawson College
FundersNational Institute for Health and Care Research
KeywordsMedicineTraumatic brain injuryDepression (economics)PopulationInjury preventionCohortPoison controlPediatricsDemographyEmergency medicinePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the prevalence of employment status (ES) or full-time study after traumatic brain injury (TBI) in a representative population and its predictive factors. DESIGN: Prospective cohort study. SETTING: Regional Major Trauma Centre. Participants: In total, 1734 consecutive individuals of working age, admitted with TBI to a Regional Trauma Centre, were recruited and followed up at 8 weeks and 1 year with face-to-face interview. Median age was 37.2 years (17.5-58.2); 51% had mild TBI, and 36.8% had a normal computed tomographic (CT) scan. MAIN OUTCOME MEASURE: Complete or partial/modified return to employment or study as an ordinal variable. RESULTS: At 1 year, only 44.9% returned to full-time work/study status, 28.7% had a partial or modified return, and 26.4% had no return at all. In comparison with status at 6 weeks, 9.9% had lower or reduced work status. Lower ES was associated with greater injury severity, more CT scan abnormality, older age, mechanism of assault, and presence of depression, alcohol intoxication, or a psychiatric history. The multivariable model was highly significant (P < .001) and had a Nagelkerke R2 of 0.353 (35.3%). CONCLUSIONS: Employment at 1 year is poor and changes in work status are frequent, occurring in both directions. While associations with certain features may allow targeting of vulnerable individuals in future, the majority of model variance remains unexplained and requires further investigation.

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)0.004
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 score0.039
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.363
Teacher spread0.321 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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