Open AccessSleep monitoring challenges in patients with neurocognitive disorders: A cross‐sectional analysis of missing data from activity trackers
Author(s) -
Ahuja Manan,
Siddhpuria Shailee,
ReppasRindlisbacher Christina,
Wong Eric,
Gormley Jessica,
Lee Justin,
Patterson Christopher
Publication year - 2022
Publication title -
health science reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 7
ISSN - 2398-8835
DOI - 10.1002/hsr2.608
Subject(s) - neurocognitive , medicine , sleep (system call) , odds ratio , confidence interval , population , activity tracker , psychiatry , clinical psychology , physical therapy , cognition , physical activity , computer science , operating system , environmental health
Background and Aims Activity monitors, such as Fitbits®, are being used increasingly for research purposes and data have been validated in healthy community‐dwelling older adults. Given the lack of research in older adults with neurocognitive disorders, we investigated the consistency of sleep data recorded from a wrist‐worn activity monitor in this population. Methods Fitbit® activity monitors were worn by hospitalized older adults as part of a parent study investigating sleep and step count in patients recovering from hip fracture surgery in a tertiary care academic hospital in Hamilton, Canada between March 2018 and June 2019. In this secondary analysis, we compared the proportion of missing sleep data between participants with and without a neurocognitive disorder and used a multivariable model to assess the association between neurocognitive disorder and missing sleep data. Results Of 67 participants included in the analysis, 22 had a neurocognitive disorder (median age: 86.5 years). Sleep data were missing for 47% of the neurocognitive disorder group and 23% of the non‐neurocognitive disorder group. The presence of a neurocognitive disorder was associated with an increased likelihood of missing sleep data using the Fitbit® activity monitors (adjusted odds ratio: 3.41; 95% confidence interval: 1.06–11.73, p = 0.04). Conclusion The inconsistent nature of sleep data tracking in hospitalized older adults with neurocognitive disorders highlights the challenges of using interventions in patient populations who are often excluded from validation studies. As opportunities expand for activity monitoring in persons with neurocognitive disorders, novel technologies not previously studied in this group should be used with caution.