Sleep Disturbance Scale for Children: Italian Validation in Autism Spectrum Disorder Population

Mignolli, Ester; Scialpi, Alessia; Valente, Donatella; Berardi, Anna; Tofani, Marco

doi:10.3390/ijerph191610163

Cited by 3 publications

(1 citation statement)

References 51 publications

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“…Considering that the treatment of sleep disorders needs to be tailored individually according to the predominant clinical symptomatology and underlying specific sleep-related diagnosis [ 5 ], secondly, we assess this population’s psychometric characteristics of the General Sleep Disturbances Scale (GSDS). The GSDS is a useful tool for assessing the presence of sleep disorders in the general population and has been validated in Italian [ 23 ] in various pathologies such as spinal cord injuries [ 24 ], hip replacement [ 25 ], and autistic spectrum disorder [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Psychometric Characteristics of Parkinson’s Disease Sleep Scale 2 and Analysis of a Cut-Off Score for Detecting Insomnia in Italian Patients with Parkinson’s Disease: A Validation Study

Liguori,

Frontani,

Francescangeli

et al. 2024

JPM

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Introduction: Sleep disorders are frequent non-motor symptoms affecting patients with Parkinson’s disease (PD). Insomnia represents the most common sleep disorder. Parkinson’s disease Sleep Scale 2 (PDSS-2) is a specific tool to investigate sleep problems in PD. The General Sleep Disturbances Scale (GSDS) was a general scale validated for the Italian population. Our goal was to assess the psychometric characteristics of PDSS-2 and the GSDS in this population, calculating a cut-off score for insomnia symptoms by using subitems of PDSS-2. Methods: Patients admitted at the PD Unit of the Hospital of Rome Tor Vergata outpatient clinic and those afferent to PD associations were asked to complete PDSS-2 and GSDS to be correlated to identify a cut-off for insomnia symptoms. Items 1,2,3,8,13 of PDSS-2 were used to detect insomnia. An ROC curve to assess a cut-off score for insomnia was determined. A cross-cultural analysis of PD population characteristics was performed. Results: In total, 350 PD patients were recruited. Cronbach’s alpha was high for the total score (0.828 for PDSS-2 and 0.832 for GSDS). A cross-cultural analysis did not show any significant p-value. The ROC curve yielded an AUC of 0.79 (CI: 0.75–0.84). The cut-off value for insomnia disorder based on items 1,2,3,8,13 of PDSS-2 was >10, demonstrating a sensitivity of 76% and a specificity of 69% in determining the presence of subjective insomnia symptoms in PD. Discussion: PDSS-2 is demonstrated to be a valid, specific tool to address sleep disturbances in PD patients. A cut-off score of 10 for items 1,2,3,8,13 was identified for detecting insomnia symptoms in PD patients.

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