STUDY OBJECTIVES: This study explores relationships between clinically encountered sleep problems in children. DESIGN: The Sleep Disturbance Scale for Children (SDSC) (Bruni et al 1996), which screens 26 sleep problems and results in 6 sleep disorder-subscales, was used as core in a larger health-behavior questionnaire (HBQ). PARTICIPANTS: Caregivers of 3045 6- to 12-year-olds filled out the HBQ. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: 21 SDSC-items plus 15 new sleep items were selected. Via structural equation modelling we explored (1) relations within and between disorder-subscales, (2) relations between the disorder-subscales with 3 indexes added (i.e., sleep efficiency index, sleep environment index, and sleep enuresis) and (3) relations of the disorder-subscales to their categorization: dyssomnia and parasomnia, without and with the indexes. CONCLUSIONS: The final model had a satisfying fit and approximates the Association of Sleep Disorders Centers' classification. Each disorder-subscale can be applied individually. However, some items are statistically of low value. For that reason, the use as the inference of relations between such items should be cautious. Adding the 3 indexes improved the fit of the model. The complexity of 'sleep enuresis' was especially revealed. For the practicing care provider, as for researchers, the statistical model proposed could be a valuable directive in the diagnostic classification process of pediatric sleep problems.
STUDY OBJECTIVES: This study explores relationships between clinically encountered sleep problems in children. DESIGN: The Sleep Disturbance Scale for Children (SDSC) (Bruni et al 1996), which screens 26 sleep problems and results in 6 sleep disorder-subscales, was used as core in a larger health-behavior questionnaire (HBQ). PARTICIPANTS: Caregivers of 3045 6- to 12-year-olds filled out the HBQ. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: 21 SDSC-items plus 15 new sleep items were selected. Via structural equation modelling we explored (1) relations within and between disorder-subscales, (2) relations between the disorder-subscales with 3 indexes added (i.e., sleep efficiency index, sleep environment index, and sleep enuresis) and (3) relations of the disorder-subscales to their categorization: dyssomnia and parasomnia, without and with the indexes. CONCLUSIONS: The final model had a satisfying fit and approximates the Association of Sleep Disorders Centers' classification. Each disorder-subscale can be applied individually. However, some items are statistically of low value. For that reason, the use as the inference of relations between such items should be cautious. Adding the 3 indexes improved the fit of the model. The complexity of 'sleep enuresis' was especially revealed. For the practicing care provider, as for researchers, the statistical model proposed could be a valuable directive in the diagnostic classification process of pediatric sleep problems.
Authors: Jesse T Fischer; H Julia Hannay; Candice A Alfano; Paul R Swank; Linda Ewing-Cobbs Journal: Neuropsychology Date: 2018-02 Impact factor: 3.295
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Authors: Vincent O Mancini; Daniel Rudaizky; Benjamin T D Pearcy; Angela Marriner; Carmela F Pestell; Rapson Gomez; Romola S Bucks; Wai Chen Journal: Sleep Med X Date: 2019-07-12
Authors: Chun Shen; Qiang Luo; Samuel R Chamberlain; Sarah Morgan; Rafael Romero-Garcia; Jingnan Du; Xingzhong Zhao; Évelyne Touchette; Jacques Montplaisir; Frank Vitaro; Michel Boivin; Richard E Tremblay; Xing-Ming Zhao; Philippe Robaey; Jianfeng Feng; Barbara J Sahakian Journal: Biol Psychiatry Date: 2020-03-31 Impact factor: 13.382