Perceived stress and severity of depression mediate the association between alexithymia and suicidal ideation in patients with major depressive disorder
Bibliographic record
Abstract
Introduction: Alexithymia and perceived stress have been recognized as risk factors for suicide in patients with major depressive disorder (MDD). However, few studies have been conducted to examine the relationship between these factors. Methods: A cross-sectional study was conducted on 105 MDD patients. Alexithymia was assessed by the 20-Item Toronto Alexithymia Scale (TAS), perceived stress was assessed by the Perceived Stress Scale (PSS), severity of depression was assessed by the 17-item Hamilton Depression Rating Scale (HAMD), and suicidal ideation was assessed by the self-report Beck Scale for Suicide Ideation (SSI). A sequential mediation model was established to test the mediating effects of perceived stress and severity of depression on the association between alexithymia and suicidal ideation. Results: 81 of the 105 participants (77.14 %) had suicidal ideation. Patients with suicidal ideation had greater difficulty in identifying feelings (DIF) (p = 0.046), higher severity of depression (p = 0.005) and perceived stress (p = 0.003). DIF subscale score of TAS was associated with perceived stress (r = 0.292, p = 0.003), severity of depression (r = 0.349, p < 0.001) and suicidal ideation (r = 0.229, p = 0.012). Sequential mediation model showed that perceived stress and severity of depression mediated the effect of DIF on suicidal ideation. Conclusions: This study suggests that perceived stress and severity of depression fully mediate the relationship between difficulty in identifying feelings and suicidal ideation in MDD patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".