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Record W4400737157 · doi:10.1080/02699052.2024.2373919

Pre-injury psychiatric history, subacute symptoms and personality traits predict social reintegration at 3-month post-mild traumatic brain injury

2024· article· en· W4400737157 on OpenAlexaff
Catherine Gagnon, Laurence Trépanier, Stéphany Denault, Maude Laguë-Beauvais, Rajeet Singh Saluja, Jennifer Massad, Michel Abouassaly, Élaine de Guise

Bibliographic record

VenueBrain Injury · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsMcGill UniversityMcGill University Health CentreUniversité de MontréalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsTraumatic brain injuryPsychologyPsychiatryClinical psychologyPersonalityBig Five personality traitsPersonality changesMedicine

Abstract

fetched live from OpenAlex

Background The purpose of the study was to identify whether the presence of a pre-injury psychiatric history, subacute post-concussive symptoms (PCS) and personality traits were predictive of less favorable social reintegration for 3 months following a mild traumatic brain injury (mTBI).Method A total of 76 patients with mTBI were included, and the presence of a pre-injury psychiatric history was identified from the medical chart. One-month post-accident, these patients completed the Millon Multiaxial Clinical Inventory, 3rd Edition assessing personality traits and the Rivermead Post-Concussion Symptoms Questionnaire to measure subacute PCS. Social reintegration was measured using the Mayo-Portland Adaptability Inventory, 4th Edition at 3-month post-accident.Results The presence of pre-injury psychiatric history, high levels of subacute PCS and Cluster B personality traits such as histrionic and borderline features were significant predictors of social reintegration quality at 3-month post injury.Conclusion This study provides new insights on cluster B personality traits and its influence on recovery and social reintegration at 3-month post mTBI.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.343
Teacher spread0.297 · 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.

Study designNot applicable
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

Citations1
Published2024
Admission routes1
Has abstractyes

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