Adolescent Insomnia Study Data

Overview

Data are based on self-report rating of demographic data and standardized questionnaires assessing insomnia-relevant factors in adolescents, including sleep quality and habits, sleep-related cognition, stress, and stress reactivity, coping and emotion regulation behavior, mood, personality, and childhood trauma. Data was collected as part of a larger study funded by the National Heart, Lung and Blood Institute investigating the pathophysiology of insomnia in adolescence. The study involved clinical interview for insomnia diagnosis, self-report evaluation of trait insomnia features, multi-nights of in-lab polysomnographic recordings, experimental manipulation of pre-sleep psychophysiological state, and actigraphy based remote assessment.

• The dataset (insomnia_data.csv) includes empirical self-report data assessment. The insomnia_data.csv contains 95 records with 95 fields of the questionnaire composite scores, and 95 fields of the z-scored composite scores. The first column in all data tables contains the unidentified ID of the human subjects.

• The insomnia_data_dictionary.csv describes the data dictionary in 95 rows and two columns: short name of the variables and the name of the instrument.

• The insomnia_item_level_data.csv contains the-self reported data of the same subjects (95 records). The first row identifies the instrument (as shown in the insomnia_data_dictionary.csv), the second row identifies the questionnaire item as seen by the participants, and the third row represents the short name of the variable (insomnia_data_dictionary.csv).

Value of the Data

• This data highlights the unique clinical features of adolescent insomnia by focusing on a sample of adolescents with clinical and sub-clinical insomnia as diagnosed from a semi-structured clinical interview according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria, considering adolescents’ specific bio-behavioral and psychosocial aspects (e.g., preference for later bedtimes, early school start times).

• The data presented here originates from rigorous and comprehensive assessment of a broad range of clinical features (>70 psychosocial factors measured via validated questionnaires) directly and indirectly associated with insomnia disorder.

• We can extract easy to digest data visualization, highlighting the severity and the complexity of insomnia symptomatology across several behavioral and psychosocial factors.

• This dataset and the associated figures have the potential to inform clinicians, data scientists and researchers from the developmental psychology and sleep domains.