Factors Associated With Digital Health Literacy in the United Kingdom: Cross-Sectional Online Survey

Clinical Snapshot

Key Findings

• P Value: Age ≥65: p=0.04; social grade: p=0.02; female sex: p<0.001; undergraduate degree: p<0.001; postgraduate degree: p=0.002; daily socialising: p=0.05

• Effect Size: Age ≥65 vs 18–44 years: OR 1.43 for low DHL; lower vs higher social grade: OR 1.37; female vs male sex: OR 0.60 (protective); undergraduate degree vs below degree: OR 0.52 (protective); postgraduate degree vs below degree: OR 0.58 (protective); daily socialising vs never/rarely: OR 0.64 (marginally protective)

• Primary Outcome: 21% (320/1525) of UK adult internet users had low DHL (eHEALS <26); median eHEALS score 31 (IQR 27–32). In multivariable analysis, older age (≥65 years), lower social grade, male sex, lower educational attainment, and less frequent socialising were independently associated with low DHL.

• Nnt Or Sensitivity: Not applicable (cross-sectional association study). Population-attributable fractions not reported. Absolute prevalence of low DHL: 21% in internet-using sample; true population prevalence likely higher given internet-user sampling frame.

• Confidence Interval: Age ≥65: 95% CI 1.02–2.01; social grade: 95% CI 1.05–1.80; female sex: 95% CI 0.46–0.77; undergraduate degree: 95% CI 0.37–0.74; postgraduate degree: 95% CI 0.40–0.82; daily socialising: 95% CI 0.42–1.00

Clinical Application

The eHEALS is an 8-item, freely available, validated instrument that can be feasibly administered in primary care, community health, or digital health onboarding contexts to screen for low DHL. Identified risk groups (older males, lower educational attainment, lower socioeconomic status) can inform targeted digital health support interventions. However, the authors appropriately caution that intervention design should not rely solely on these factors given the model's modest explanatory power. The findings have moderate relevance to Australian primary care and digital health policy. Australia's digital health transformation — including My Health Record, the National Digital Health Strategy 2023–2028, and expanded telehealth services — creates analogous equity concerns. The RACGP's digital health guidelines and the Australian Digital Health Agency's work on digital inclusion align with the study's policy implications. The eHEALS has been validated and used in Australian populations. Key differences include Australia's greater geographic dispersion, higher rates of internet access in urban areas versus remote/rural communities, and the specific digital divide affecting Aboriginal and Torres Strait Islander peoples — a dimension not captured in this UK study. PBS-listed digital therapeutics and telehealth MBS items make DHL a clinically relevant competency for Australian patients. Australian GPs should consider DHL screening, particularly for older patients, those with lower educational attainment, and those from lower socioeconomic backgrounds, when onboarding patients to digital health tools. UK adult internet users; findings most directly applicable to primary care and public health planning for digital health service design. Subgroup findings in chronic disease patients are relevant to chronic disease management programmes. Caution required before applying prevalence estimates to the general population given internet-user sampling.

Abstract

BACKGROUND: Digital health literacy (DHL), the ability to seek, understand, and apply digital health information, is increasingly important in the United Kingdom, with a focus on digital transformation within the health service. While digital tools offer potential to improve access and equity, they may exacerbate existing health inequities if segments of the population are unable to engage with them effectively. Understanding the sociodemographic, economic, and social factors associated with DHL is essential to designing inclusive digital health services. OBJECTIVE: This study aimed to measure DHL among UK adults and identify its sociodemographic, economic, and social associates. METHODS: A cross-sectional online survey was disseminated to a nationally representative sample of UK adult internet users from November to December 2024. DHL was self-reported using the validated eHealth Literacy Scale (eHEALS), which ranges from 8 to 40. eHEALS score was dichotomized into high and low DHL based on a cutoff of 26. Multivariable logistic regression was used to identify associates of DHL, with missing data handled using multiple imputation by chained equations. RESULTS: The median eHEALS score was 31 (IQR 27-32); 21% (320/1525) of the participants had low DHL, while 79% (1205/1525) had high DHL. Those aged 65 years and older, compared with those in the age group of 18-44 years, had higher odds of low DHL (odds ratio [OR] 1.43, 95% CI 1.02-2.01; P=.04). Those belonging to a lower social grade also had higher odds of low DHL, compared with those belonging to the higher social grade (OR 1.37, 95% CI 1.05-1.80; P=.02). Females had lower odds of low DHL (OR 0.60, 95% CI 0.46-0.77; P<.001), as did those with an undergraduate or postgraduate degree or higher, compared with those educated to below degree level (undergraduate degree OR 0.52, 95% CI 0.37-0.74, P<.001; postgraduate degree or higher OR 0.58, 95% CI 0.40-0.82, P=.002). Those who socialized daily, compared to those who did this never or rarely, had marginally lower odds of low DHL (OR 0.64, 95% CI 0.42-1.00; P=.05). In subgroup analysis among participants with chronic health conditions, age and social grade were not significant associates of DHL. CONCLUSIONS: Among UK internet users, male sex, lower educational attainment, lower social grade, less frequent socializing, and older age were statistically significant associates of low DHL. The model's modest explanatory power suggests that additional factors beyond those examined play an important role. As findings are based on internet users, the prevalence of low DHL in the general population is likely higher than reported. This study provides a partial basis for identifying groups who may benefit from additional support, but intervention design should not rely solely on factors identified here. Inclusive interventions accounting for a broader range of factors are needed to ensure that digital transformation in health care narrows rather than widens health inequities.