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Toward an Explanatory Model of Social Participation for Adults With Traumatic Brain Injury

2004· article· en· W2066649759 on OpenAlexaff
Claire Dumont, Marie Gervais, Patrick Fougeyrollas, Raphael Bertrand

Bibliographic record

VenueJournal of Head Trauma Rehabilitation · 2004
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité LavalQuebec Automobile Insurance Corporation
Fundersnot available
KeywordsDynamismPsychologyTraumatic brain injuryExploratory researchPopulationClinical psychologyIntervention (counseling)MedicinePsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify resiliency factors that could improve social participation for adults with traumatic brain injury. DESIGN: Cross-sectional single measurement, correlational and exploratory study, including quantitative and qualitative data. PARTICIPANTS: Fifty-three community-dwelling people with sequelae of traumatic brain injury, individually interviewed, which included filling out questionnaires and answering open-ended questions. MAIN MEASURES: Social participation, self-efficacy, and positive mental states. RESULTS: Dynamism, self-efficacy, and will account for 51% of the variance in social participation and are the main resiliency factors. Fatigue is one of the sequelae that pose the greatest challenge to self-efficacy and limit social participation. CONCLUSION: Resiliency factors constitute a target for research and intervention for this population.

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)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.115
GPT teacher head0.409
Teacher spread0.294 · 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 designTheoretical or conceptual
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

Citations59
Published2004
Admission routes1
Has abstractyes

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