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Record W2039244160 · doi:10.3109/02699052.2014.989905

Does what we measure matter? Quality-of-life defined by adolescents with brain injury

2015· article· en· W2039244160 on OpenAlexafffund
Ashley Di Battista, Celia Godfrey, Cheryl Soo, Cathy Catroppa, Vicki Anderson

Bibliographic record

VenueBrain Injury · 2015
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchState Government of Victoria
KeywordsQuality of life (healthcare)PsychologyPsychology of selfClinical psychologyCognitionTraumatic brain injuryDevelopmental psychologyPsychiatryPsychotherapistSocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine if domains included in popular measurement systems (e.g. the Peds QL™) reflect the adolescent survivor of a brain injury's sense of QoL and explore this relationship in reference to an emerging model of wellbeing in the adolescent with TBI. METHODS: Mixed methods; adolescent QoL assessed using the PedsQL™ self-report and a semi-structured interview created by the lead author. Adolescent self-report was compared to adolescent narratives. RESULTS: Ten adolescents participated. Adolescent PedsQL™ total was within normal limits. Adolescents reported that changes identified by the PedsQL were not important and did not impact on their sense of QoL. The importance on social components of QoL-as opposed to cognitive-provide additional support of the emerging model of wellbeing in adolescents with TBI. CONCLUSIONS: The PedsQL can identify changes post-TBI, but fails to consider whether these changes are relevant to the adolescent. Alternate methods of exploring QoL-which emphasize the interaction of social networks and friendships, should be considered to avoid an oblique view of QoL outcomes after 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 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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.092
GPT teacher head0.367
Teacher spread0.275 · 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

Citations19
Published2015
Admission routes2
Has abstractyes

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