{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T17:47:20Z","timestamp":1782841640854,"version":"3.54.5"},"reference-count":58,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Hum Factors"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Digital health services (DHS) are an increasingly integral part of health care services. Understanding users\u2019 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.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n 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\u2019 use of DHS in managing their chronic condition and differences in DHL and health technology readiness between DHS users and nonusers.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n 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%;\n P<\/jats:italic>\n <.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;\n P<\/jats:italic>\n =.01) compared with nonusers (mean 2.42, SD 0.90) and in social support for health (mean 2.81, SD 0.71;\n P<\/jats:italic>\n =.02), compared with nonusers (mean 2.54, SD 0.85).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/85625","type":"journal-article","created":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T01:33:17Z","timestamp":1773279197000},"page":"e85625-e85625","source":"Crossref","is-referenced-by-count":0,"title":["Digital Health Literacy and Health Technology Readiness Among People With Epilepsy or Multiple Sclerosis: Cross-Sectional 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