MétaCan
Menu
Back to cohort
Record W2769537613 · doi:10.5127/jep.041414

The Causal Role of Attentional Bias in a Cognitive Component of Depression

2015· article· en· W2769537613 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Experimental Psychopathology · 2015
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsWestern University
Fundersnot available
KeywordsAttentional biasPsychologyCognitionCognitive biasDepression (economics)Cognitive psychologyDevelopmental psychologyClinical psychologyNeuroscience

Abstract

fetched live from OpenAlex

Cognitive theories have, for years, postulated the causal role of attentional biases in depression and low self-esteem. However, this assumption has been based predominantly on correlational findings. With the advent of attentional bias modification techniques (Mathews & MacLeod, 2002), it became possible to modify attentional bias experimentally. The purpose of this study was to ascertain whether negative attentional biases are trainable and causally linked to changes in important characteristics of depression, namely self-esteem. Participants completed negative attentional training and a stress induction task. Consistent with the diathesis-stress model, a combination of negative attentional biases and stress resulted in changes in self-esteem, which was used as an indicator of depression. The effects on self-esteem were specific to the type of stimuli used. These findings have important implications for our understanding of self-esteem, cognitive models of depression, and for the future of cognitive bias modification research in self-esteem and depression.

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.

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 score0.108
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.099
GPT teacher head0.408
Teacher spread0.308 · 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