Time spent following the Russian-Ukranian war (RUW) and psychological distress: The role of sleep problems
Bibliographic record
Abstract
Background: The Russian-Ukranian war (RUW) broke in 2022. Finland is a neighboring country of Russia. People in Finland could be assumed to be especially vulnerable to war-related stress. We examined the relationship between time spent following the RUW from media, sleep problems and psychological distress in university students. Methods: The participants were university students who responded anonymously to a questionnaire. They reported their age, gender, time spent following RUW, anxiety, depressive symptoms, and sleep problems. Statistical analyses were conducted using SPSS and Mplus for structural equation modeling. Results: The time spent following RUW from media was associated with greater psychological distress, and more sleep disturbances. Sleep disturbances accounted for more than 12% of the association between time spent following RUW and psychological distress. Conclusions: Present findings suggest that sleep problems should be taken into account when supporting students. Support programs should emphasize the importance of sleep in psychological well-being.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".