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Record W2754005147 · doi:10.3233/wor-172597

Cognition and return to work after mild/moderate traumatic brain injury: A systematic review

2017· review· en· W2754005147 on OpenAlexaff
Karthik Mani, Bryan Cater, Akshay N. Hudlikar

Bibliographic record

VenueWork · 2017
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsCommunity Sector Council Newfoundland and Labrador
Fundersnot available
KeywordsTraumatic brain injuryCognitionRehabilitationCognitive rehabilitation therapyClinical psychologyPopulationMedicinePhysical medicine and rehabilitationPsychologyPhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Approximately two percent of the United States population are traumatic brain injury (TBI) survivors. The unemployment rate among them is substantial. Cognitive skills are essential to perform any job. OBJECTIVE: We analyzed the literature on cognitive rehabilitation (CR) related to mild/moderate TBI to learn the influence of cognition on return to work (RTW) post TBI. METHODS: We conducted a systematic review of the studies on CR related to RTW post TBI that were published between 2000 and 2015. RESULTS: We critically reviewed 30 studies that met the inclusion criteria. Ten studies highlighted cognition as a predictor variable, seven studies demonstrated support for cognitive testing in RTW assessments, and 13 studies showed the efficacy of CR in facilitating RTW post TBI. CONCLUSION: Cognition plays a significant role in predicting and facilitating RTW in patients with TBI.

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)0.003
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.218
GPT teacher head0.445
Teacher spread0.227 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations93
Published2017
Admission routes1
Has abstractyes

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