The Relationship between Alexithymia and Psychological Well-being among Pregnant Women
Bibliographic record
Abstract
Objective: Over the past two decades, there has been widespread scientific attention to emotion regulation and the impact of emotional dysregulation on physical and mental health. The concept of alexia is rooted in the psychology of emotions and psychosomatic diseases. Many patients with psychosomatic complaints showed problems in emotional self-regulation. This research aimed to explore the association between alexithymia and psychological well-being in pregnant women during their 5th to 7th month of pregnancy.Methods: The study population consisted of pregnant women from the Mazandaran province, Iran, during 2022-2023. Employing purposive sampling, 200 pregnant women were selected from health centers. Participants completed the Toronto Alexithymia Scale-20 (FTAS-20) and the Psychological Well-being Scale (RSPWB). Pearson's correlation coefficient and regression test were used to analyze the data.Results: Results revealed an inverse relationship between alexithymia and psychological well-being (r = -0.388, p < 0.01). Approximately 53% of the variance in psychological well-being scores could be attributed to alexithymia.Conclusion: In conclusion, alexithymia serves as an effective predictor of maternal 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 | 0.000 | 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".