Validation of the 14-Item Shortened Version of the Positive and Negative Sleep Appraisal Measure Among Shift-Working Nurses

Abstract

Objective Insomnia is a common condition that significantly impacts physical and mental health. Dysfunctional sleep beliefs and cognitive hyperarousal are recognized as key mechanisms in its development and maintenance. The Positive and Negative Sleep Appraisal Measure (PANSAM) was developed to assess cognitive interpretations of changes in sleep quantity. A shortened version, PANSAM-14, was created using machine learning to enhance clinical usability. This study aimed to evaluate the psychometric characteristics and clinical applicability of PANSAM-14 among shift-working nurses, a high-risk group for insomnia. Methods A total of 299 shift-working nurses from Asan Medical Center completed an online survey including PANSAM-14, Insomnia Severity Index (ISI), Patient Health Questionnaire-9 (PHQ-9), and Glasgow Sleep Effort Scale (GSES). Confirmatory factor analysis (CFA), item response theory, and Rasch analyses were conducted to assess the construct validity, measurement precision, and item functioning. Reliability and convergent validity were also examined. Results CFA confirmed the four-factor structure of PANSAM-14 with good model fit indices. Rasch and graded response model analyses supported the measurement precision for most subscales, though subscale 4 showed lower item differentiation and reliability. PANSAM-14 demonstrated high internal consistency and significant positive correlations with ISI, PHQ-9, and GSES. Subscale scores increased in accordance with insomnia severity, supporting the scale’s sensitivity and clinical utility. Conclusion PANSAM-14 demonstrated acceptable psychometric properties for assessing sleep-related cognitive patterns, particularly among shift-working nurses. Its brief structure and acceptable psychometric properties suggest potential utility for clinical and occupational interpretation.