The features of posttraumatic and associated sleep disorders in young War-affected women
Bibliographic record
Abstract
The purpose of this study was to assess the specifics of PTSD symptom manifestations with accompanying sleep disturbances by identifying relationships between individual clusters of PTSD symptoms and indicators of sleep quality among the sample of younger women affected by military events. The study design is cross-sectional observational. Identical in basic parameters and socio-demographic indicators, the study population consisted of women aged from 18 to 45 years (M=23), (n=22). The study data included Ukrainian-language: demographic data, Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder Assessment-7 (GAD-7), PTSD Checklist for DSM-5 (PCL-5), Pittsburgh Sleep Quality Questionnaire (PSQQ), Toronto alexithymia scale (TAS-26) and Quality of Life Scale, edited by Prof. Chaban (CQLS). Statistical analysis including descriptive statistics and Pearson correlation was performed using SPSS Statistics 23.0 software. Significant relationships were identified and evaluated between the following indicators: individual clusters of PTSD symptoms with manifestations of anxiety-depressive symptoms and alexithymia, and the quality of life and sleep in young women with symptoms of post-traumatic disorders with accompanying sleep disorders due to military events. Consequently, significant relationships were established between the manifestations of individual clusters of PTSD symptoms and parameters of sleep quality with symptoms of anxiety, depression, alexithymia, and low quality of life. This may indicate the higher risk of development and degree of manifestation of symptoms of stress-related disorders with accompanying sleep disturbances in the future in individuals with corresponding indicators according to the results of the scales used.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".