Background: Sleep distrurbances involves daytime preoccupation about sleep, which plays a critical role in perpetuating sleep disturbances. Recent cognitive models highlight the importance of daytime processes, like processing sleep-related information and interpretations during waking hours, in influencing sleep quality and quantity. The Sleep Preoccupation Scale (SPS) quantifies this daytime cognitive activity related to sleep. This study aimed to translate and validate an Arabic version of the SPS for assessing sleep preoccupation among Arabic speakers. Methods: 523 Arabic speakers (mean age 23.6 years, 75% female) from four countries completed the Arabic SPS alongside the Athens Insomnia Scale, Generalized Anxiety Disorder-7 Scale, and the Anxiety and Preoccupation about Sleep Questionnaire (APSQ). The sample repeated the SPS after two weeks for test-retest reliability. Confirmatory factor analysis evaluated the SPS's two-factor structure. Internal consistency, item response theory, and convergent validity with the other scales were examined. Results: Confirmatory factor analysis supported the two-factor model's fit. Measurement invariance results suggest that the SPS exhibits a similar basic factor structure across both insomnia and non-insomnia groups. The Arabic SPS demonstrated good internal consistency (Cronbach's alpha = 0.92, McDonald's omega = 0.92) and two-way mixed effects, consistency, single rater/measurement intraclass correlation coefficient (ICC) test-retest reliability (ICC = 0.95). Most items exhibited satisfactory item response theory fit statistics and discrimination. The SPS total score showed strong positive correlations with insomnia severity (r = 0.48, p < 0.001), generalized anxiety (r = 0.57, p < 0.001), and sleep-related anxiety/preoccupation (r = 0.79, p < 0.001), demonstrating convergent validity. Conclusion: The Arabic version of the SPS demonstrated good psychometric properties and validity, supporting its use for assessing sleep preoccupation among Arabic speakers. This culturally-adapted version enhances sleep assessment capabilities for improving insomnia understanding and treatment within Arabic-speaking populations.