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Development and Validation of the Pediatric Sleep Practices Questionnaire: A Self-Report Measure for Youth Ages 8-17 Years.

Lisa J MeltzerChristopher B ForrestAnna de la MotteJodi A MindellKatherine B Bevans
Published in: Behavioral sleep medicine (2020)
Objective: To develop and evaluate the validity of a self-report measure of sleep practices for youth 8-17 years. Methods: Following recommended guidelines for the development of patient reported outcomes (PROs), sleep practice concepts were identified through expert (n = 8) and child (n = 28) concept elicitation interviews and a systematic literature review. Items were developed based on these concepts and tested in cognitive interviews with children (n = 32). Psychometric analyses were applied to item response data collected from a diverse sample of youth 8-17 years (n = 307). Construct validity was evaluated through tests of associations between sleep practices and sleep disturbance and sleep-related impairment. Finally, clinical validity of the tool was assessed by comparing scores of youth with and without a parent-identified sleep problem. Results: The final Pediatric Sleep Practices Questionnaire (PSPQ) included 15 items that were used to identify 5 sleep practices: sleep timing, sleep routines and consistency, technology use before bedtime, sleep environment, and the need for parental presence to fall asleep. A confirmatory factor analysis supported the hypothesized structure (all factor loadings ≥ 0.72) and PSPQ indices were significantly associated with self-reported sleep disturbances and sleep-related impairment. Finally, children with parent-reported sleep problems had shorter sleep opportunity, later bedtimes, greater need for parental presence, poorer bedtime routines, and more technology use than children without parent-reported sleep problems. Conclusions: The PSPQ was developed using best-practice PRO development methodology. The PSPQ can be used in clinical settings and for research assessment to capture modifiable sleep practices that may promote or interfere with healthy sleep.
Keyphrases
  • physical activity
  • sleep quality
  • primary care
  • healthcare
  • mental health
  • young adults
  • depressive symptoms
  • machine learning
  • deep brain stimulation
  • electronic health record
  • data analysis