Search published articles


Showing 1 results for Premenstrual Symptoms Screening Tool (psst)

Yasaman Hashemi, Siavash Talepasand, Kave Alavi,
Volume 20, Issue 2 (8-2014)
Abstract

  Background & Aim: The aim of present study was to assess psychometric properties of premenstrual symptoms screening tool (PSST) to provide a fast and appropriate screening tool for women who suffer from severe PMS/PMDD and their clinicians .

  Methods & Materials: It was a cross-sectional study. The study included 404 female students studying at Semnan University who were randomly selected using stratified method. In order to assess psychometric properties, we used the exploratory factor analysis, convergent validity (evaluated by symptom checklist-90-Revised), criterion-related validity (calculated by comparing psychiatrist diagnosis and PSST). Sensitivity and specificity coefficients of optimal cutoff points were calculated by the ROC Curve and construct validity was evaluated by the PSST ability to separate PMS and PMDD groups from healthy group. Reliability was evaluated using the cronbach’s alpha and test-retest method . 

  Results: The p rinciple component analysis revealed that the PSST consists of four factors: interest reduction, interference in functions, physical and neurotic symptoms, and eating and sleep patterns. As an evidence of convergent validity, PSST scores showed significant correlations with the SCL-90-R’s dimensions. Agreement coefficient between psychiatrists and the PSST diagnosis was 0.314 for the PMS and 0.80 for the PMDD. This tool separated the PMS and PMDD groups from healthy group well. Optimal Cutoff point for separating females suffering from PMDD was 2.22. The sensitivity and specificity coefficients were 0.9 and 0.77, respectively. The cronbach’s alpha was 0.91 and the test-retest reliability was 0.56 for the total tool .

  Conclusion: The translated version of the premenstrual symptoms screening tool can be used as a valid tool for Iranian females. This instrument can be useful for rapid screening and identifying women who suffer from severe PMS/PMDD, especially in clinical settings .

  



Page 1 from 1     

© 2024 , Tehran University of Medical Sciences, CC BY-NC 4.0

Designed & Developed by : Yektaweb