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Record W4382776620 · doi:10.1177/13591053231184065

Mediation of cognitive interference on depression during the Russo-Ukrainian war in three national samples

2023· article· en· W4382776620 on OpenAlexafffundabout
Petra Begic, Esther R. Greenglass, Taina Hintsa, Petri Karkkola, Petra Buchwald

Bibliographic record

VenueJournal of Health Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsYork University
FundersYork UniversityUniversity of York
KeywordsUkrainianMediationDepression (economics)CognitionPsychologyClinical psychologyPsychiatryPolitical scienceLaw

Abstract

fetched live from OpenAlex

Media coverage of large-scale violence can result in interfering thoughts and depression. This research investigates the relationship between interfering thoughts and depression when watching the Russo-Ukrainian war. In the theoretical model, the more the war is watched, the more it is related to interfering thoughts, which are related to depression. With the ongoing pandemic, depression, when watching the war, was related to coronavirus threat. Data was collected online from April to June, 2022, with university students in Germany, Finland, and Canada ( N = 865). Path analysis results in each sample showed that the model fit the data with sample-specific modification indices. There was full mediation of watching the war by interference on depression, indicating that it is not watching the war, per se, but rather its relationship to cognitive interference, that is associated with depression. Denial and coronavirus threat were positively related to depression. Implications for research and student support are considered.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.195
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.129
GPT teacher head0.462
Teacher spread0.332 · 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

Citations3
Published2023
Admission routes3
Has abstractyes

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