In vitro Fertilization-Embryo Transfer Patients with Alexithymia and Its Influencing Factors: A Potential Profile Analysis
Notice bibliographique
Résumé
Purpose: This study aims to explore the classification characteristics of alexithymia in patients undergoing in vitro fertilization-embryo transfer (IVF-ET) and analyze the differences among these classifications in female patients, in order to alleviate the patients’ alexithymia and improve their mental health and reproductive quality of life. Methods: A total of 385 patients undergoing IVF-ET were selected through convenience sampling from the Reproductive Endocrinology Clinic of a Grade III A-level obstetrics and gynecology hospital in mainland China between June 2024 and December 2024. Data collection included the general information survey form, the Toronto Alexithymia Scale, and the General Self-efficacy Scale. Latent profile analysis was used to explore the potential categories of alexithymia among patients receiving IVF-ET treatment. Univariate and multiple logistic regression analyses were conducted to identify the factors correlated with the potential profiles. Results: The alexithymia in patients receiving IVF-ET treatment was categorized into three potential groups: low-risk (48.0%), moderate-risk (46.0%), and high-risk alexithymia groups (6.0%). Multiple logistic regression analysis results indicated that educational level, average monthly household income, and self-efficacy are correlated with alexithymia in patients receiving IVF-ET treatment ( P < 0.05). Conclusion: The alexithymia in patients receiving IVF-ET treatment can be categorized into three potential profile types. The clinical medical staff should consider the characteristics of patients and implement targeted interventions for those with lower levels of education, lower average monthly household income, and poorer self-efficacy, in order to reduce the degree of alexithymia. Plain Language Summary: This study aimed to understand how patients undergoing in vitro fertilization-embryo transfer (IVF-ET), struggle to identify and express their emotions (alexithymia) and find ways to improve their mental health and quality of life. From June to December 2024, 385 IVF-ET patients were recruited from a Chinese gynecology hospital, and researchers used questionnaires to gather information on their personal background, emotional recognition ability, and self-confidence. The data analysis showed that patients’ alexithymia could be categorized into low-risk (48%), moderate-risk (46%), and high-risk (6%) groups, and that lower education level, less family income, and lower self-confidence were associated with a higher likelihood of alexithymia in patients. As such, medical staff should consider patients’personal situations and provide special care and support to those with lower education, income, and self-confidence in an effort to assist them in better managing emotions and potentially enhancing their mental well-being. Keywords: In vitro fertilization-embryo transfer, alexithymia, self-efficacy, latent profile analysis, influencing factors
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».