Evidence map›Paper›PMID 41811098›Full record

ArticleJMIR formative research2026

Screening the Digital Skills of Patients in Geriatric Rehabilitation: Multicenter Cross-Sectional Study.

Michael Bg Zonneveld, Margriet C Pol, Marise J Kasteleyn, Wilco P Achterberg, Eléonore F van Dam van Isselt

Abstract readMulticenter Study
In one paragraph

Article in JMIR formative research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Michael Bg ZonneveldDepartment of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands.ORCID https://orcid.org/0000-0001-8959-6717
Margriet C PolDepartment of Medicine for Older People, Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Amsterdam, The Netherlands.ORCID https://orcid.org/0000-0002-7570-5190
Marise J KasteleynDepartment of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands.ORCID https://orcid.org/0000-0001-7751-7516
Wilco P AchterbergDepartment of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands.ORCID https://orcid.org/0000-0001-9227-7135
Eléonore F van Dam van IsseltDepartment of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands.ORCID https://orcid.org/0000-0002-5584-6295

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigitalization 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.

objectiveThis 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.

methodsIn 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.

resultsA 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<.001). The association between age and digital skills does not differ between males and females.

conclusionsThis study suggests that QDS is a promising and practical screening tool for assessing digital skills in patients in geriatric rehabilitation. Self-reported digital skills with an NRS do not capture the differentiation in the assessed abilities by QDS. QDS could be a practical tool for identifying digital skill levels in patients in geriatric rehabilitation and can support more personalized eHealth implementation. Further research should explore the parametric properties of QDS and how the scores relate to actual eHealth use.

Indexed as

Computer LiteracyGeriatricsRehabilitationAgedAged, 80 and overCross-Sectional StudiesDigital HealthFemaleHumansMaleNetherlandsSurveys and Questionnairesassessmentdigital healthdigital proficiencyolder adultsrehabilitationtelehealthtelerehabilitation

Identifiers

PMID41811098
PMCPMC13087556

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.