Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
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JMIR human factors
Engaging Older Adults With Neurocognitive Disorders in Digital Health Technologies: Scoping Review
BACKGROUND: Population aging is associated with a growing prevalence of neurocognitive disorders among adults aged 65 years and older. Digital health technologies offer promising opportunities to support cognitive health and well-being in this population. However, their effectiveness largely depends on users' level of engagement. Despite the recognized importance of engagement in digital health, limited evidence exists on how engagement is conceptualized, measured, and related to intervention outcomes among older adults living with neurocognitive disorders. OBJECTIVE: This scoping review aimed to describe how engagement with digital health technologies among older adults with neurocognitive disorders is conceptualized and measured, examine the relationship between engagement and the effectiveness of digital health interventions, and identify factors that facilitate or hinder engagement. METHODS: A scoping review was conducted following the Joanna Briggs Institute methodological guidance and reported in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. A comprehensive search strategy, developed in collaboration with an information specialist, was applied to MEDLINE, Embase, CINAHL, Web of Science, and Google Scholar, without date restrictions. Empirical studies involving adults aged 65 years and older living with neurocognitive disorders and using digital health technologies were included. Study selection and data extraction were performed independently by at least 2 reviewers, and the results were synthesized narratively. RESULTS: Of the 1665 records identified after duplicate removal, 2 studies met the inclusion criteria. One study examined computerized cognitive stimulation and cognitive engagement programs among community-dwelling older adults with mild neurocognitive disorders, whereas the other explored the use of a personalized digital reminiscence application in long-term care settings among individuals with major neurocognitive disorders. No study used a validated instrument to directly measure engagement. However, observable indicators and markers related to the behavioral, cognitive, and affective components of engagement were reported. Both studies also documented concurrent cognitive or psychosocial outcomes. Factors facilitating engagement included professional support, content personalization, and involvement of informal caregivers, whereas limiting factors included cognitive fluctuations, fatigue, technical complexity, and reliance on external support. CONCLUSIONS: This scoping review highlights a significant gap in the literature regarding the explicit conceptualization and standardized measurement of engagement with digital health technologies among older adults living with neurocognitive disorders. The findings underscore the need to develop and apply multidimensional, context-sensitive engagement measurement tools tailored to this population to better understand and optimize digital health interventions.
18 July 2026
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Sensor-Based Monitoring of Knee Osteoarthritis Symptoms in Free-Living Settings: Scoping Review
BACKGROUND: Knee osteoarthritis is a heterogeneous condition characterized by chronic pain, stiffness, and fatigue that fluctuate rapidly over time. Traditional clinical assessments provide only static diagnoses of disease severity, failing to capture the dynamic, day-to-day symptom variability that impacts patient quality of life. While wearable technologies offer the potential for continuous, high-frequency monitoring, previous reviews have examined general technological interventions for knee osteoarthritis management, yet they lack a specific synthesis of technologies for symptom monitoring. OBJECTIVE: This study aims to synthesize current research on sensor technologies used for the continuous monitoring of knee osteoarthritis symptoms in free-living or simulated daily environments. Specifically, the review seeks to (1) map sensor modalities to specific symptom domains (biomechanical, physiological, and behavioral); (2) evaluate the alignment between objective sensor metrics and patient-reported outcome measures; and (3) identify gaps in current monitoring paradigms. METHODS: A systematic literature search was conducted across PubMed, Embase, Web of Science, and IEEE Xplore. The review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Eligibility criteria included studies involving participants with knee osteoarthritis using wearable or portable sensors capable of continuous monitoring (eg, inertial measurement units and electrocardiography) and assessing clinical symptoms (eg, pain, fatigue, and stiffness). Studies relying solely on stationary laboratory equipment (eg, force plates) without a portable component were excluded to ensure relevance to real-world applicability. Data regarding sensor types, sampling frequencies, monitored symptoms, and the statistical association between objective features and subjective symptom severity (key findings) were extracted. RESULTS: A total of 16 studies met the inclusion criteria. The summary constructed from the results revealed a distinct technological saturation: the majority of studies (n=6) used inertial measurement units to quantify biomechanical deficits (eg, gait asymmetry and range of motion), which showed robust correlations with functional limitations. In contrast, there was a notable scarcity of research using physiological sensors (eg, electrocardiography and bioimpedance) to monitor systemic symptoms. Crucially, findings highlighted a significant discrepancy between subjective and objective data, particularly in sleep monitoring, where poor self-reported sleep quality predicted pain exacerbations despite stable objective actigraphy metrics. Furthermore, most systems operated as passive data loggers, with a lack of integration into active feedback loops. CONCLUSIONS: Unlike previous reviews focused solely on biomechanics, this study innovatively maps the use of sensors across a multidimensional symptom spectrum, revealing a critical gap in the monitoring of fatigue and physiological stress. The findings suggest that current sensor applications are limited by a lack of integration with subjective patient experiences. Real-world implementation requires a hybrid monitoring paradigm that combines the ecological validity of wearable sensors with the clinical relevance of patient-reported outcomes. This approach paves the way for digital phenotyping and active feedback systems, offering a personalized strategy for managing the complex symptom burden of knee osteoarthritis.
3 July 2026
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