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Record W2172224437 · doi:10.1080/03069880500132581

Rationale and development of a general population well-being measure: Psychometric status of the GP-CORE in a student sample

2005· article· en· W2172224437 on OpenAlexfundno aff
Chris Evans, Janice Connell, Kerry Audin, Alice Sinclair, Michael Barkham

Bibliographic record

VenueBritish Journal of Guidance and Counselling · 2005
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsnot available
FundersPetroleum Technology Research CentreUniversity of Leeds
KeywordsCore (optical fiber)PsychologyPopulationClinical psychologySample (material)Reliability (semiconductor)Convergent validityMental healthPsychometricsMeasure (data warehouse)MedicinePsychiatryComputer scienceEnvironmental health

Abstract

fetched live from OpenAlex

Abstract This paper presents the rationale, development, and psychometric status of a non-clinical self-report measure for the general population (GP) – including students – derived from the Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM) and hence termed the GP-CORE. In contrast to the CORE-OM, the GP-CORE does not comprise items denoting high-intensity of presenting problems or risk and thereby increases its acceptability in a non-clinical population. Uniquely, over half the items in the GP-CORE are positively keyed. Analyses showed the GP-CORE to have good reliability, to distinguish between clinical and non-clinical populations, and have convergent validity against the full version. Norms for student populations are presented. It is suggested that the GP-CORE has considerable utility as a means of tapping the psychological well being of students and can then interface with counselling and mental health services using the CORE-OM.

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)0.001
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 score0.396
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.035
GPT teacher head0.322
Teacher spread0.286 · 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

Citations96
Published2005
Admission routes1
Has abstractyes

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