Scholarlink

Objective <p>This study was conducted to identify the psychological factors that predict the severity of Premenstrual Syndrome (PMS) among young women in 2025.</p> Methods <p>In this cross-sectional study, researchers selected 673 female medical students through convenience sampling. They collected data using the Childhood Trauma Questionnaire (CTQ), the Premenstrual Symptoms Screening Tool (PSST), the Toronto Alexithymia Scale (TAS-20), the Kessler Psychological Distress Scale (K10), and a demographic questionnaire. They analyzed the data using Structural Equation Modeling (SEM) in Amos and SPSS (Version 26).</p> Results <p>The SEM model showed a good fit. PMS severity had significant positive relationships with psychological distress (B = 0.64, <i>p</i> &lt; 0.001), childhood adversity (B = 0.262, <i>p</i> &lt; 0.01), and alexithymia (B = 0.35, <i>p</i> &lt; 0.001). A moderate positive correlation existed between alexithymia and PMS severity (<i>r</i> = 0.409, <i>p</i> = 0.01).</p> Conclusion <p>Childhood adversity, alexithymia, and psychological distress significantly predict PMS severity. These findings highlight the importance of a biopsychosocial approach. We suggest that doctors, especially gynecologists, should consider these psychological factors when assessing and treating patients with PMS.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Relationship between childhood adversity and premenstrual syndrome: mediating role of alexithymia and psychological distress in medical students

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月21日

查看全文
  • Mahsa Abdollahpour Kahriz,
  • Negin Bahri,
  • Amir Sam Kianimoghadam,
  • Abbas Masjedi Arani,
  • Hedyeh Riazi

摘要

Objective

This study was conducted to identify the psychological factors that predict the severity of Premenstrual Syndrome (PMS) among young women in 2025.

Methods

In this cross-sectional study, researchers selected 673 female medical students through convenience sampling. They collected data using the Childhood Trauma Questionnaire (CTQ), the Premenstrual Symptoms Screening Tool (PSST), the Toronto Alexithymia Scale (TAS-20), the Kessler Psychological Distress Scale (K10), and a demographic questionnaire. They analyzed the data using Structural Equation Modeling (SEM) in Amos and SPSS (Version 26).

Results

The SEM model showed a good fit. PMS severity had significant positive relationships with psychological distress (B = 0.64, p < 0.001), childhood adversity (B = 0.262, p < 0.01), and alexithymia (B = 0.35, p < 0.001). A moderate positive correlation existed between alexithymia and PMS severity (r = 0.409, p = 0.01).

Conclusion

Childhood adversity, alexithymia, and psychological distress significantly predict PMS severity. These findings highlight the importance of a biopsychosocial approach. We suggest that doctors, especially gynecologists, should consider these psychological factors when assessing and treating patients with PMS.