Alexithymia and postpartum anxiety and depression symptoms: a follow-up study in a pregnancy cohort
Bibliographic record
Abstract
INTRODUCTION: There is a lack of longitudinal studies assessing the significance of alexithymia on the emergence of mental illnesses. We aimed to evaluate the potential effect of alexithymia on postpartum anxiety and depression symptoms in a sample of parents to be. METHODS: In a pregnancy cohort, longitudinal data were available from three time points (gestational weeks 18-20, and 3 and 12 months postpartum) for 100 mothers and 65 fathers. The 20-item Toronto Alexithymia Scale (TAS-20) was used to assess alexithymia, the State-Trait Anxiety Inventory (STAI) to evaluate anxiety symptoms and the Edinburgh Postnatal Depression Scale (EPDS) to assess depression. Linear regression analyses were used to estimate the effect of alexithymia on the symptom scale score changes from baseline. RESULTS: Both in mothers and fathers, the TAS-20 total score was significantly correlated with the STAI and EPDS scores at several time-points, with a higher TAS-20 score indicating more symptoms. In the regression analyses, the association of alexithymia with later symptoms became non-significant in mothers. However, in fathers, the TAS-20 score had a statistically significant effect on the increase of the STAI score at 3 months postpartum (p = 0.006). For the separate TAS-20 subscales, difficulty identifying feelings had a significant effect on the increase of anxiety by 12 months postpartum (p = 0.023) and difficulty describing feelings on the increase by 3 months postpartum (p < 0.001). DISCUSSION: Although the setting did not facilitate the assessment of actual diagnoses regarding the anxiety and depression symptoms, alexithymia appears to have a significant effect on the increase of postpartum anxiety symptoms in fathers-to-be.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".