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A dataset reflecting the multidimensionality of insomnia symptomatology in adolescence using standardized questionnaires

Insomnia is the most common sleep disorder in adolescence, and frequently emerges during this vulnerable period of profound biobehavioral maturation. Insomnia tends to be chronic, and if left untreated, could be detrimental for the teenagers’ mental and physical health, social, and emotional develop...

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Detalles Bibliográficos
Autores principales: Kiss, Orsolya, Yuksel, Dilara, Prouty, Devin E., Baker, Fiona C, de Zambotti, Massimiliano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9411582/
https://www.ncbi.nlm.nih.gov/pubmed/36034640
http://dx.doi.org/10.1016/j.dib.2022.108523
Descripción
Sumario:Insomnia is the most common sleep disorder in adolescence, and frequently emerges during this vulnerable period of profound biobehavioral maturation. Insomnia tends to be chronic, and if left untreated, could be detrimental for the teenagers’ mental and physical health, social, and emotional development. However, there is a paucity of data about insomnia in adolescence, strongly limiting the understanding and management of the disorder. In the current work, psychological and behavioral questionnaire data are provided for 95 adolescents (age range between 16-19 years, 62% female) with and without clinical or subclinical insomnia symptoms, determined from the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Data were collected as part of a larger study investigating insomnia pathophysiology and cardiovascular health in adolescence. The data collection strategy was designed to capture the complexity of the insomnia symptomology in adolescence, and its unique clinical features, across different psychological and behavioral domains. The dataset covers a broad range of clinical measures describing sleep quality and habits, sleep-related cognitions, stress, stress reactivity, coping and emotion regulation behavior, mood, personality, and childhood trauma. The relationships between symptoms are analyzed and visualized via a network analysis approach, including outputs reflecting network structures and centrality measures. This dataset, and associated data visualizations, could be beneficial in the fields of sleep medicine, adolescent health, and development of psychopathology, highlighting the specific factors implicated in adolescent insomnia, as well as the heterogeneity of symptom combinations. Results can potentially inform the development of therapeutic approaches targeting key factors implicated in the insomnia pathophysiology in adolescents.