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Record W2096556506 · doi:10.1177/0146167209343811

Self-Criticism, Dependency, and Stress Reactivity: An Experience Sampling Approach to Testing Blatt and Zuroff’s (1992) Theory of Personality Predispositions to Depression in High-Risk Youth

2009· article· en· W2096556506 on OpenAlexaff
Philippe Adams, John R. Z. Abela, Randy P. Auerbach, Steven A. Skitch

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2009
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychologySelf-criticismPersonalityExperience sampling methodSocial psychologyReactivity (psychology)Depression (economics)Dependency (UML)CriticismClinical psychologyBig Five personality traitsDevelopmental psychology

Abstract

fetched live from OpenAlex

S. J. Blatt and D. C. Zuroff's 1992 theory of personality predispositions to depression posits that individuals who possess high levels of self-criticism and/or dependency are vulnerable to developing depression following negative events. The current study used experience sampling methodology to test this theory in a sample of 49 children ages 7 to 14. Children completed measures of dependency, self-criticism, and depressive symptoms. Subsequently, children were given a handheld computer that signaled them to complete measures of depressive symptoms and negative events at randomly selected times over 2 months. Results of hierarchical linear modeling analyses indicated that higher levels of both self-criticism and dependency were associated with greater elevations in depressive symptoms following negative events. Furthermore, each personality predisposition remained a significant predictor of such elevations after controlling for the interaction between the other personality predisposition and negative events. The results suggest that dependency and self-criticism represent distinct vulnerability factors to depression in youth.

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 score0.399
Threshold uncertainty score0.953

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 studies0.0000.000
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 head0.130
GPT teacher head0.422
Teacher spread0.292 · 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

Citations27
Published2009
Admission routes1
Has abstractyes

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