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Record W4405074009 · doi:10.1037/tra0001808

Associations of war-related PTSD symptoms with sleep disturbance: The explanatory roles of emotion regulation difficulties and intolerance of uncertainty.

2024· article· en· W4405074009 on OpenAlexaff
Mehdi Zemestani, Pegah Seidi, Jafar Bakhshaie, Gordon J. G. Asmundson

Bibliographic record

VenuePsychological Trauma Theory Research Practice and Policy · 2024
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPsychologySleep (system call)Clinical psychologyDisturbance (geology)Sleep disorderPsycINFOPsychiatryMEDLINECognition

Abstract

fetched live from OpenAlex

OBJECTIVE: Although associations between posttraumatic stress disorder (PTSD) and sleep disturbance are well-established, relatively little work has examined mechanisms that may underlie this association. This study aimed to examine the explanatory role of emotion regulation difficulties and intolerance of uncertainty (IU) in associations between PTSD symptoms and sleep disturbance among a sample of war-exposed Iraqi individuals. METHOD: = 4.81; 46.03% females) to model indirect effects from PTSD symptoms to the sleep disturbance via emotion regulation difficulties and IU. Participants completed PTSD symptoms, sleep disturbance, difficulties in emotion regulation, and IU scales. RESULTS: s < .001). CONCLUSION: Findings add to the emerging body of literature examining potential mechanisms that may help to explain the maintenance or even escalation of PTSD-related sleep disturbance. Findings have clinical implications in designing specialized treatments for individuals with PTSD and suggest focusing on emotion regulation difficulties and IU as potential therapeutic targets that putatively underlie PTSD-related sleep disturbance. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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)0.001
metaresearch head score (Gemma)0.009
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.458
Teacher spread0.358 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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