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Record W2157470677 · doi:10.1080/02699050701311075

Psychological adjustment and marital satisfaction following head injury. Which critical personal characteristics should both partners develop?

2007· article· en· W2157470677 on OpenAlexaff
Marie Claude Blais, Jean-Marie Boisvert

Bibliographic record

VenueBrain Injury · 2007
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité LavalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPsychologyClinical psychologyHead injuryLife satisfactionPhysical medicine and rehabilitationMedicinePsychiatrySocial psychology

Abstract

fetched live from OpenAlex

UNLABELLED: PRIMARY OBJECTIVE AND RESEARCH DESIGN: Using a correlational design, this study verifies the relationships between personal characteristics of individuals with TBI and their spouses and their level of psychological and marital adjustment. METHODS AND PROCEDURE: Seventy individuals with TBI and their spouses in the post-acute rehabilitation phase completed self-report questionnaires assessing the predictive variables (coping and social problem-solving strategies; perceived communication skills) and the criteria variables of psychological and marital adjustment. MAIN OUTCOMES AND RESULTS: In the target group, the characteristics most strongly related to adjustment variables were an effective attitude towards problems, infrequent use of avoidance coping strategies, and a positive perception of one's spouse's communication skills. Individuals with TBI and their spouses report significantly lower scores on some of these personal characteristics, compared to those of a matched control group of 70 couples from the general population. CONCLUSIONS: Specific personal characteristics are critical for psychological and marital adjustment following TBI. This knowledge may be of relevance for detecting couples at risk for developing difficulties in the post-acute rehabilitation phase. Rehabilitation interventions targeting the personal characteristics identified as critical for the adjustment process could help to prevent these difficulties.

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)0.001
metaresearch head score (Gemma)0.008
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.116
GPT teacher head0.445
Teacher spread0.329 · 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

Citations37
Published2007
Admission routes1
Has abstractyes

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