Journal of Patient-Reported Outcomes (Jul 2024)

Sleep-loss related to itch in atopic dermatitis: assessing content validity and psychometric properties of a patient-reported sleep-loss rating scale

  • Alissa Rams,
  • Jessica Baldasaro,
  • Laurine Bunod,
  • Laure Delbecque,
  • Sara Strzok,
  • Juliette Meunier,
  • Hany ElMaraghy,
  • Luna Sun,
  • Evangeline Pierce

DOI
https://doi.org/10.1186/s41687-024-00764-2
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 11

Abstract

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Abstract Background Sleep loss is a key factor contributing to disease burden in people with atopic dermatitis (AD). Mitigating itch to improve sleep is an important outcome of AD treatment. This study explored the content validity and measurement properties of the Sleep-Loss Scale, a single-item rating scale for assessing itch interference with sleep in clinical trials of AD treatments. Methods Concept elicitation and cognitive debriefing interviews were conducted with 21 adults and adolescents (12–17 years of age) with moderate-to-severe AD to develop a conceptual model of patient experience in AD and explore the content validity of the scale. Data collected from adults with moderate-to-severe AD enrolled in a phase 2b study (NCT03443024) were used to assess Sleep-Loss Scale’s psychometric performance, including reliability, construct validity, and ability to detect change. Meaningful within-patient change (MWPC) thresholds were also determined using anchor-based methods. Results Qualitative findings from concept elicitation highlighted the importance of sleep-loss related to itch in AD. Debriefing analysis of the Sleep-Loss Scale indicated that the scale was relevant, appropriate, and interpreted as intended. Trial data supported good reliability, construct validity and ability to detect improvement. MWPC was defined as a 1-point improvement using trial data, a finding supported by qualitative data. Conclusions The Sleep-Loss Scale provides a valid and reliable patient-reported measure of the impact of itch on sleep in patients with AD, and can detect change, indicating it is fit-for-purpose to evaluate the efficacy of AD treatments in moderate-to-severe patients.

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