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Record W2100943483 · doi:10.1037/0022-3514.88.4.673

Daily Depression and Cognitions About Stress: Evidence for a Traitlike Depressogenic Cognitive Style and the Prediction of Depressive Symptoms in a Prospective Daily Diary Study.

2005· article· en· W2100943483 on OpenAlexaff
Benjamin L. Hankin, R. Chris Fraley, John R. Z. Abela

Bibliographic record

VenueJournal of Personality and Social Psychology · 2005
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsMcGill University
FundersNational Institute of Mental Health
KeywordsPsychologyRuminationNeuroticismStressorDysfunctional familyCognitionCognitive styleDepression (economics)Multilevel modelDevelopmental psychologyClinical psychologyCognitive vulnerabilityDepressive symptomsPersonalityPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

The authors examined the stability and dynamic structure of negative cognitions made to naturalistic stressors and the prediction of depressive symptoms in a daily diary study. Young adults reported on dispositional depression vulnerabilities at baseline, including a depressogenic cognitive style, dysfunctional attitudes, rumination, neuroticism, and initial depression, and then completed short diaries recording the inferences they made to the most negative event of the day along with their experience of depressive symptoms every day for 35 consecutive days. Daily cognitions about stressors exhibited moderate stability across time. A traitlike model, rather than a contextual one, explained this pattern of stability best. Hierarchical linear modeling analyses showed that individuals' dispositional depressogenic cognitive style, neuroticism, and their daily negative cognitions about stressors predicted fluctuations in daily depressive symptoms. Dispositional neuroticism and negative cognitive style interacted with daily negative cognitions in different ways to predict daily depressive symptoms.

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)0.002
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 score0.150
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.097
GPT teacher head0.453
Teacher spread0.355 · 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

Citations152
Published2005
Admission routes1
Has abstractyes

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