DIGITAL HEALTH LITERACY AND PRACTICES OF EVALUATING MEDICAL INFORMATION AMONG ADULT INTERNET USERS IN UKRAINE: RESULTS OF A CROSS-SECTIONAL ONLINE SURVEY

Abstract

Introduction. Searching for medical information online and consulting AI chatbots have become a routine practice for most people. However, the level of digital health literacy varies substantially across populations, and no data on this literacy among the adult population of Ukraine have been available until now. The aim of the study was to assess the level of digital health literacy among adult internet users in Ukraine using the full structure of the Digital Health Literacy Instrument (DHLI). Additional objectives were to examine practices of using artificial intelligence for self-diagnosis, methods of verifying medical information, and the relationship between digital activity and lifestyle domains. Materials and methods. A cross-sectional online survey of 412 adult respondents was conducted (52.9% male, 47.1% female; age M=32.1, SD=9.2) using snowball and convenience sampling. An adapted DHLI instrument (7 subscales, 21 items) was used, supplemented with blocks on artificial intelligence use, information verification, and the impact of digital resources on lifestyle. Statistical analysis was performed in IBM SPSS Statistics: descriptive statistics, Pearson correlation, independent-samples t-test, Pearsonʼs χ² test with Cramérʼs V, multiple linear regression, and Cronbachʼs alpha. Results and discussion. The overall digital health literacy score was M=3.09 (SD=0.59) on a 1–4 scale, closely matching the result of the original validation study of the instrument (M=3.11). All subscales demonstrated acceptable-to-excellent reliability (α=0.746–0.924). The weakest skill was critical evaluation of information: 47.6% of respondents found it difficult to determine the reliability of a source, and 45.9% its commercial nature. Age (r=−0.453, p<0.001) and education level (t=11.36, p<0.001) were confirmed as factors consistently associated with literacy, in line with international data. In multiple regression, the model explained 46.1% of the variance in the total score; age, higher education, residence in a large city, and frequency of health information seeking were independent predictors. Artificial intelligence for selfdiagnosis is used regularly by 30.8% of respondents. A statistically significant association was found between AI use and the experience of being misled by digital information (χ²=69.87, df=6, p<0.001, Cramérʼs V=0.29): 76.4% of regular AI users versus 31.6% of non-users reported being misled. The self-reported impact of digital resources on lifestyle was selective and ambivalent. The greatest benefit was observed for timely doctor visits (69.4%) and preventive check-ups (66.0%), while sleep and psycho-emotional state remained the most contradictory domains. Conclusions. Digital health literacy among adult internet users in Ukraine had a mean overall score of 3.09±0.59 on the 4-point DHLI scale. The weakest link was critical evaluation of information rather than technical device skills. The use of artificial intelligence for selfdiagnosis is a widespread practice associated with more frequent reports of being misled, which likely reflects the overall intensity of digital activity. These findings substantiate the need for targeted digital hygiene and media literacy programmes focused on developing critical thinking, particularly among older and less educated individuals.