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Record W2060983755 · doi:10.3109/02699052.2012.743177

Evaluation of the<i>Patient Generated Index</i>as a measure of quality-of-life in people with severe traumatic brain injury

2013· article· en· W2060983755 on OpenAlexaff
Mark Hogan, Niamh Nangle, Todd G. Morrison, Brian E. McGuire

Bibliographic record

VenueBrain Injury · 2013
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsQuality of life (healthcare)DistressAcquired brain injuryCommunity integrationRehabilitationTraumatic brain injuryClinical psychologyPsychologyConstruct validityLife satisfactionDepression (economics)PsychiatryPhysical therapyPsychometricsMedicineSocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVES: Quality-of-life (QoL) measures may be useful in quantifying the personal impact of an acquired brain injury and as an indicator of the effectiveness of service provision. This study investigated the validity of the patient generated index (PGI) as a measure of QoL with a sample of adults who had sustained a severe traumatic brain injury. METHOD: Fifty-five participants with an acquired brain injury were selected from four regional rehabilitation centres. Each participant completed validated questionnaires measuring subjective satisfaction with life, community integration, emotional distress, socially desirable responding and the patient generated index. RESULTS: The criterion-related validity of the PGI was demonstrated through a statistically significant positive correlation with life satisfaction. Evidence of construct validity was observed through significant correlations with measures of emotional distress and community integration. Depression had a strong negative association with QoL. Social desirability correlated significantly with both indices of QoL, suggesting that this variable may be treated as a covariate. CONCLUSION: The results offer some preliminary evidence for the validity of the PGI as a measure of QoL in people with severe brain injury.

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)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.107
GPT teacher head0.373
Teacher spread0.267 · 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 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
Published2013
Admission routes1
Has abstractyes

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