Evidence map›Paper›PMID 41813120›Full record

ArticleJMIR human factors2026

Digital Health Literacy and Health Technology Readiness Among People With Epilepsy or Multiple Sclerosis: Cross-Sectional Study.

Anna Vahteristo, Virpi Jylhä, Hanna Kuusisto

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

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Anna VahteristoDepartment of Health and Social Management, University of Eastern Finland, P.O. Box 1627, Kuopio, 70211, Finland, 358 0504156223.ORCID 0000-0001-9427-8254
Virpi JylhäDepartment of Health and Social Management, University of Eastern Finland, P.O. Box 1627, Kuopio, 70211, Finland, 358 0504156223.ORCID 0000-0002-0725-1414
Hanna KuusistoDepartment of Health and Social Management, University of Eastern Finland, P.O. Box 1627, Kuopio, 70211, Finland, 358 0504156223.ORCID 0000-0002-3697-4961

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Digital health services (DHS) are an increasingly integral part of health care services. Understanding users' abilities to engage with DHS is crucial to ensuring that health technology meets their needs. Assessing digital health literacy (DHL) and health technology readiness can help identify the strengths and weaknesses of DHL in different subgroups. Objective: This study aimed to assess DHL and health technology readiness among people with epilepsy or multiple sclerosis (MS) and, accordingly, identify and categorize them into distinct subgroups or profiles. In addition, we aimed to investigate respondents' use of DHS in managing their chronic condition and differences in DHL and health technology readiness between DHS users and nonusers. Methods: An electronic survey was distributed to people with epilepsy or MS with the help of patient organizations. The questionnaire included the Finnish version of the Readiness and Enablement Index for Health Technology. The subgroups of respondents were identified using k-means cluster analysis. Nonparametric tests were used to compare health technology readiness among identified subgroups. Results: Respondents (N=289) had mid- to high-level scores in all the dimensions describing DHL and health technology readiness. A total of 4 distinct profiles emerged with different strengths and weaknesses in their DHL and health technology readiness. There was a significantly higher proportion of DHS users among the 2 profiles with the highest DHL, profile 1 (62/81, 76.5%) and profile 2 (59/80, 74.7%), compared with the profile with the lowest DHL, profile 4 (20/50, 40%; P<.001). In contrast, those with the lowest confidence in their DHL had higher emotional distress, reported lower confidence in the support from their health care providers, and had a smaller proportion of DHS users. In addition, the DHS users had significantly higher DHL levels in 6 of the 7 dimensions, as well as higher confidence in the support they received from their health care providers (mean 2.71, SD 0.72; P=.01) compared with nonusers (mean 2.42, SD 0.90) and in social support for health (mean 2.81, SD 0.71; P=.02), compared with nonusers (mean 2.54, SD 0.85). Conclusions: Identifying subgroups with distinct profiles, characterized by different strengths and weaknesses in their DHL and health technology readiness, is crucial in ensuring the development of responsive and inclusive DHS to meet the needs of all users, particularly those requiring support in using DHS. In addition, the nonusers had lower confidence in the support they received from their health care provider than the users. Further research is needed to understand this difference.

Indexed as

EpilepsyHealth LiteracyMultiple SclerosisAdultCross-Sectional StudiesDigital HealthFemaleFinlandHumansMaleMiddle AgedSurveys and Questionnairesdigital healthdigital health literacyepilepsyhealth technology readinessmultiple sclerosis

Identifiers

PMID41813120
PMCPMC12978907

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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 OpenQuestion graph.