ArticleBMC public health2024
Digital health literacy and associated factors among internet users from China: a cross-sectional study.
Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.
- Barriers and facilitators of health information seeking behavior among older adults: a mixed-methods systematic review using the COM-B model.Frontiers in public health · 2026Pooled it
- Artificial intelligence attitudes in relation to Mediterranean diet adherence and environmental footprints: a cross-sectional study.BMC public health · 2026Article
- Observational
- Complex role of digital health literacy in awareness and use of digital sexually transmitted and blood-borne infections testing: a structural equation modelling analysis of the 2022 GetCheckedOnline survey.Sexually transmitted infections · 2026Article
- Digital health literacy and associated factors among health professionals in Kaski District, Nepal: a cross-sectional study.BMC health services research · 2026Article
- Digital Engagement and Health Behaviors Among Village Health Volunteers in Southern Thailand: A Cross-Sectional Study.International journal of environmental research and public health · 2026Article
- Understanding digital health literacy in later life: the role of sociodemographic and health-related factors - a cross-sectional study.BMC geriatrics · 2026Article
- Associations between digital healthy diet literacy, artificial intelligence attitudes, mediterranean diet adherence, and health-related quality of life in adults.BMC public health · 2026Article
- Relationship Among Internet Use, eHealth Literacy, Internet Addiction, and Physical Activity Among Adolescents: Cross-Sectional Study.JMIR pediatrics and parenting · 2026Article
- Explainable Machine Learning for Assessing Digital Health Literacy in Older Adults: Validation and Development of a Two-Stage Model Integrating Performance-Based and Self-Assessed Indicators.JMIR medical informatics · 2026Article
- Precision cardiovascular medicine with big data and AI.NPJ digital medicine · 2026Review
- Adoption, digital health literacy, and patient satisfaction of Ayushman Bharat Digital Mission: an analytical cross-sectional study among outpatient department attendees.BMC health services research · 2026Article
- Dose-response relationship between eHealth literacy and oral frailty in the elderly: a multicentric cross-sectional study.BMC geriatrics · 2026Article
- Understanding Health Literacy and eHealth Literacy in Nursing Students: A Cross-Sectional Cluster Analysis.Nursing reports (Pavia, Italy) · 2026Article
- Latent profile and associated factors of digital health literacy among patients with coronary heart disease: a cross-sectional study.Frontiers in public health · 2026Article
- A cross-sectional study on the current status and influencing factors of core competencies among public health students.Frontiers in public health · 2026Article
- Latent profile analysis of eHealth literacy and its sociodemographic correlates: a cross-sectional study.Frontiers in public health · 2026Article
- Latent profiles analysis and associated factors of digital health literacy among young and middle-aged adults with diabetes.Frontiers in public health · 2026Article
- Digital health literacy and associated factors in older adult patients with chronic obstructive pulmonary disease: a latent profile analysis.Frontiers in public health · 2026Article
- Digital health literacy, social support, and online health information-seeking behavior profiles among nursing students: a latent profile and structural equation modeling analysis.Frontiers in public health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAs the internet develops and 5G technology becomes increasingly prominent, the internet has become a major source of health-related information. Increasingly, people use the internet to find health-related information, and digital health literacy is now a set of essential capabilities to improve their health in the digital era. However, little is known about the factors that influencing digital health literacy. This study aimed to assess digital health literacy scores and identify its influencing factors among internet users in China. Additionally, this study explored the participant's actual skills using an additional set of performance-based items from the Digital Health Literacy Instrument (DHLI).
methodsAn online cross-sectional study was conducted in August 2022. Participants aged ≥18 years were recruited to complete the survey. Data were collected using the Chinese revised version of the DHLI, the self-reported internet use questionnaire, and the sociodemographic questionnaire. We conducted multivariate linear regression analyses to explore the relationships among the sociodemographic variables, behavior of internet use, and the digital health literacy scores.
resultsIn total, 702 participants completed the survey. The mean DHLI score was 2.69 ± 0.61. Multivariate linear regression analyses showed that the age groups 35-49 (β = - 0.08, P = 0.033), 50-64 (β = - 0.161, P < 0.001), and ≥ 65 (β = - 0.138, P < 0.001) were negatively associated with DHL scores. However, education level, including bachelor's or associate degree (β = 0.255, P = 0.002) and master's degree and above (β = 0.256, P < 0.001), frequency of health-related Internet usage (β = 0.192, P < 0.001), the number of digital devices used (β = 0.129, P = 0.001), and OHISB (β = 0.103, P = 0.006) showed a positive relationship with DHL scores.
conclusionsThe study findings demonstrate that age, educational levels, number of technological devices used, and greater use of the web for health information were independently associated with DHL scores. Healthcare providers should consider providing training programs tailored to specific sociodemographic factors to improve the ability that find and use accurate information online to meet digital health services, which contributes to enhance their self-management and reduce health disparities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.