Screening the Digital Skills of Patients in Geriatric Rehabilitation: Multicenter Cross-Sectional Study
Background: Digitalization in geriatric rehabilitation presents unique challenges, making it essential to align eHealth solutions with patients’ digital skills. The Quickscan Digital Skills (QDS) is a tool designed to help health care professionals match eHealth interventions to individual skill levels. Objective: This study aimed to explore the applicability of QDS by comparing it to self-reported digital skills and to gain insight into the digital skills of patients in geriatric rehabilitation. Methods: In this multicenter cross-sectional study, participants from 13 geriatric rehabilitation centers in the Netherlands completed a survey, including demographic questions, QDS, and a numeric rating scale (NRS) for self-reported digital skills. Participants were categorized into 3 skill levels (beginner, intermediate, and experienced) based on the cutoff points in QDS scores. Cutoff points were predetermined, guided by the information provided on QDS. Descriptive statistics for median age and frequencies for skill levels were calculated. Comparative analysis using a Kruskal-Wallis test assessed differences between QDS and NRS within these groups, and Spearman rank-order correlation examined the relationship between the two measures. To gain more insight into the different skill levels between groups, data were visualized and associations among age, gender, and digital skill levels were examined using ordinal logistic regression analysis. Results: A total of 463 patients (median age 78, IQR 12 years; 282/463, 60.9% female) participated in this study. Based on QDS scores, 42.1% (195/463) were classified as beginners, 19.4% (90/463) as intermediates, and 38.4% (178/463) as experienced users. A moderate positive correlation was found between QDS and NRS scores. Digital skills generally declined with age: 69.8% (37/53) of participants younger than 65 years were experienced users compared to only 13.2% (5/38) of those older than 91 years. A logistic regression analysis showed that increasing age was significantly associated with lower digital skill levels (odds ratio 0.93, 95% CI 0.92-0.95; P
