Clinical child psychology and psychiatry · 2026
Persian Version of the University of California Los Angeles Loneliness Scale; a Validation Study in Iranian Children and Adolescence.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Arefian Mohadeseh, Abdollahpour Ibrahim, Yazdi Maryam, Kelishadi Roya
Аннотация
Background/objectivesLoneliness, characterized by the absence of meaningful social and personal connections, is recognized as a significant adverse health condition. This study aimed to evaluate the psychometric properties of the Persian version of the 8-item UCLA Loneliness Scale (P-ULS-8) among Iranian children and adolescents.MethodsThis cross-sectional study was conducted in 2024 among 100 school-aged students in Isfahan, Iran. Standard forward-backward translation procedures were used, and content validity indices were calculated. Reliability was assessed using Cronbach's α and intraclass correlation coefficients (ICC). Convergent validity was evaluated via Spearman's correlation between the 20-item UCLA Loneliness Scale (ULS-20) and P-ULS-8. Confirmatory factor analysis was performed to approve construct validity.ResultsCronbach α and ICC for the overall scale were 79.0% and 0.86, respectively. Scale content validity indices for relevancy, clarity, and comprehensiveness were 95%, 90%, and 80%, respectively. A significant correlation was found between P-ULS-8 and ULS-20 (r Pearson = 0.74, p < .001), suggesting satisfactory convergent validity. Confirmatory factor analysis approved a two-factor structure for the Persian version of ULS-8.ConclusionsP-ULS-8 demonstrated acceptable reliability and validity indices. Considering its brevity, the Persian version of ULS-8 can be easily used in large-scale studies.