Document Type

Presentation

Publication Date

2024

Faculty Mentor

Michelle Woodberry

Abstract

Purpose: The purpose of this MUSC Occupational Therapy (OT) Doctoral Capstone project was to elucidate the concept of post-stroke sleep disturbance by 1) gathering quantitative data from stroke patients using a sleep disturbance questionnaire, 2) conducting qualitative interviews to understand stroke patients' subjective experiences of sleep disturbance, and 3) utilizing Rasch item response theory analysis to develop a person-item map, i.e., a “keyform”, that visualizes the interplay between a patient's sleep disturbance severity-level and specific sleep disturbance symptoms that the patient demonstrates.

Background: Sleep disturbances (SD) affect over 50% of stroke survivors, negatively impacting recovery and increasing risk of mortality (Jeffers et al., 2023; Väyrynen et al., 2014). Although comprehensive management of SD throughout the continuum of care improves outcomes, multifaceted barriers within the stroke rehabilitation system, including resource constraints and fragmented care, limits SD assessment and management. (Hasan et al., 2021; Frange et al., 2023; Brown et al., 2019). There is a pressing need to develop new methods that enable healthcare professionals to more precisely assess and therapeutically manage SD (Fulk et al., 2020).

Methods: This was a secondary analysis of existing data collected from 2 MUSC IRB- approved research projects and all procedures were conducted accordingly. Both studies had similar inclusion criteria: stroke survivors, ≥21 years of age, ≥3 months post-stroke, English as primary language, and able to participate in full study protocols. A trained evaluator administered the PROMIS Short Form v1.0 – Sleep Disturbance 8a questionnaire. Responses were recorded in a secure database (REDCap) and downloaded into Excel for processing. Data were analyzed using both standardized methods (Health Measures Scoring System T-cut off score charts to identify sleep disturbance severity-levels) and Rasch Analysis (Winsteps software). The Rasch analysis output a person-item Keyform map to link individual patient’s assessment scores to specific SD symptoms. In addition, semi-structured interviews were conducted, via HIPAA compliant zoom, with participants who had also completed the PROMIS questionnaire. Interview responses were audio recorded, transcribed, and analyzed using thematic analysis methods.

Results: N=51 participants completed the Sleep Disturbance Questionnaire. N=14 (28%) presented with sleep disturbance in the mild (n=5), moderate (n=6), or severe ranges (n=3). Rasch analysis results showed that individuals with severe SD exhibited higher scores on more severe SD symptoms (i.e. worried about not falling asleep, difficulty falling asleep), while individuals with mild SD exhibited higher scores on less severe SD symptoms (i.e. unrefreshing sleep, restless sleep). Thematic analysis of interviews with n=5 participants revealed a demand for personalized, non-pharmaceutical interventions to alleviate perceived helplessness in managing SD. Participants identified factors impacting their sleep, hindering daily activities, routines, and role fulfillment. SD Item-level perceptions and challenges were further explored to guide interventions.

Conclusion: Together, the Rasch Keyform map and qualitative data elucidated the broad concept of SD in terms of specific symptoms experienced by individuals with mild, moderate, and severe SD. Delineating distinct patient-specific SD issues enables occupational therapists to develop targeted and personalized SD interventions. The results this project reinforce existing literature on the prevalence of SD among stroke survivors while introducing an innovative approach to its assessment and management.

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