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Record W2884754972 · doi:10.1080/02699052.2018.1502471

Convergent and divergent validity of the Connor-Davidson Resilience Scale in children with concussion and orthopaedic injury

2018· article· en· W2884754972 on OpenAlexaff
Christianne Laliberté Durish, Keith Owen Yeates, Brian L. Brooks

Bibliographic record

VenueBrain Injury · 2018
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsHotchkiss Brain InstituteAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsConcussionClinical psychologyConstruct validityPsychologyPsychological resilienceConvergent validityPopulationPoison controlConstruct (python library)PsychometricsAnxietyInjury preventionDevelopmental psychologyMedicinePsychiatryMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVE: Psychological resilience is an important predictor of outcome in concussion; however, there is no published evidence of psychometric support for use of a measure of psychological resilience in children with concussion. This study examined construct validity of the Connor-Davidson Resilience Scale (CD-RISC) in a paediatric concussion and orthopaedic injury sample. METHODS: Seventy-five children with a history of concussion or orthopaedic injury were recruited from a children's hospital. Total sample and within-group correlations between the CD-RISC (25- and 10-item versions) and measures presumed to be related or unrelated to the construct of psychological resilience were analysed. RESULTS: In the total sample, both versions of the CD-RISC were negatively correlated with self-reported depressive symptoms and general behaviour problems. The 10-item version was also negatively correlated with parent-reported general behaviour problems and self-reported anxiety, and was positively correlated with self-reported quality of life. The injury groups did not exhibit significantly different correlations. CONCLUSIONS: The construct validity of the CD-RISC is satisfactory when used with children with concussion. The 10-item version may provide a more efficient measure of resiliency with better construct validity in 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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.016
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.335
Teacher spread0.318 · 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.

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

Citations22
Published2018
Admission routes1
Has abstractyes

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