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Record W2591130401 · doi:10.1177/1073191117694747

The Dimensions of Ruminative Thinking: One for All or All for One

2017· article· en· W2591130401 on OpenAlexaff
Ljiljana Mihić, Zdenka Novović, Milica Lazić, David J. A. Dozois, Radomir Belopavlović

Bibliographic record

VenueAssessment · 2017
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsWestern University
FundersScience and Engineering Research Board
KeywordsPsychologyPsychopathologyAnxietyRuminationClinical psychologyHomogeneousDepression (economics)CognitionPsychiatry

Abstract

fetched live from OpenAlex

The Ruminative Thought Scale (RTS) was developed to measure the ruminative thinking style, presumably common to various psychopathological disorders. However, prior factor-analytic research was inconclusive regarding unidimensionality versus multidimensionality of the RTS. The present study was conducted on a large, heterogeneous Serbian sample ( N = 838). A subsample was retested 6 months later providing information about symptoms of depression and various anxiety symptoms. Results showed that a bifactor model of the RTS (representing one general and four group factors) had a better fit than the second-order and one-factor models. The subscale scores were not prospective predictors of symptoms of depression and anxiety, over and above the contribution of the total score. The RTS is a reliable transdiagnostic measure of repetitive thinking. Although there is some clustering of more homogeneous items, there is not enough evidence to support interpretation of the subscales.

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)0.002
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
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 head0.167
GPT teacher head0.473
Teacher spread0.306 · 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

Citations14
Published2017
Admission routes1
Has abstractyes

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