Childhood maltreatment and insomnia in college students: The role of alexithymia and psychological distress
Bibliographic record
Abstract
Insomnia, which is highly prevalent among college students, has been identified as one of the negative consequences of childhood maltreatment. While prior studies have uncovered distinct correlations between childhood maltreatment, insomnia, and other variables, the potential underlying mechanisms need to be further explored. This study focused on the chain-mediating role of alexithymia and psychological distress in the relationship between childhood maltreatment and insomnia. An online cross-sectional survey was conducted among Chinese college students, yielding 999 valid questionnaires that included demographic information, the Childhood Trauma Questionnaire-Short Form (CTQ-SF), the Toronto Alexithymia Scale (TAS), the 21-item Depression Anxiety Stress Scales (DASS-21), and the Insomnia Severity Index (ISI). A chain-mediating model was then tested. The results revealed significant positive correlations between each pair of the four variables. Alexithymia and psychological distress separately mediated the link between childhood maltreatment and insomnia (effect of alexithymia was 0.06 with 95 % CI [0.03, 0.09]; effect of psychological distress was 0.24 with 95 % CI [0.19, 0.29]). Additionally, a chain-mediating effect of alexithymia and psychological distress was observed (chain-mediating effect was 0.12 with 95 % CI [0.09, 0.15]). The findings suggest that emotional interventions may mitigate the long-term effect of childhood maltreatment on sleep problems among college students, by improving the ability to recognize emotions and decreasing emotional problems.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".