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Preventive campaigns for older adults must decide how to allocate limited resources across media channels. However, these channel allocation and budget decisions rarely use explicit criteria for distributional equity or structured strategic planning tools. Consequently, health systems may optimize average uptake while leaving large gaps across socioeconomic groups and media use profiles. This study aimed to develop and apply a data-driven agent-based model as a strategic planning tool for preventive campaigns targeting older adults, comparing channel allocation, personalization, and loss framing options under explicit budget and equity guardrails. We built an agent-based model calibrated to national survey data from South Korea on influenza vaccination and routine health screening among older adults (vaccination, N=2405; screening, N=2400). Fifteen prespecified campaign scenarios varied channel allocation across television, digital, and print media; budget intensity; 2 equity-focused personalization strategies; and graded loss framing. Primary outcomes were final adoption and time to adoption. Equity outcomes included the minimum class-level adoption and 90-10 gap across latent classes. Each scenario was simulated over 12 monthly steps with 100 Monte Carlo replications. We conducted sensitivity analyses varying link functions and key social reinforcement parameters. Personalization improved uptake and equity relative to the integrated baseline. In the vaccination model (N=2405), adoption increased from 91.2% (n=2193) to 93.3% (n=2244) and 94.6% (n=2275). Minimum class-level adoption increased from 86.8% to 90.3% and 90.9%. The 90-10 gap narrowed from 5.7 to 4.5 and 4.7 percentage points. In the screening model (N=2400), adoption increased from 83.8% (n=2011) to 88.2% (n=2117) and 89.5% (n=2148). Minimum class-level adoption increased from 77.6% to 83.2% and 85.3%. The 90-10 gap narrowed from 9.2 to 7.4 and 6.2 percentage points. Television-only strategies achieved high adoption but had less favorable equity profiles than personalization. High-budget strategies achieved high adoption but required higher total exposure. Stronger loss framing produced small, monotonic gains in adoption and shortened the time to adoption without worsening equity in the tested range. Scenario rankings were stable in sensitivity analyses. This agent-based modeling study illustrates how ex ante planning can improve preventive campaign design by comparing channel allocation and personalization options under explicit equity and budget criteria. For campaigns targeting older adults, equity-focused reweighting and class-tailored television-digital portfolios improved or preserved mean adoption while strengthening distributional equity under fixed budgets. In contrast, undifferentiated channel diversification without personalization offered a less favorable efficiency-equity trade-off. These findings support integrating explicit equity guardrails into early-stage channel allocation and prioritizing targeted personalization over simple channel diversification. Future work should validate these patterns in other populations and health systems and link simulated diffusion trajectories with observed exposure and engagement in real-world campaigns. It should also extend guardrail-based planning tools to organizational settings and multiyear decision contexts.

Although digital health technology (DHT) is widely used in the United States at both hospital provider and individual levels, it is beset with several challenges that have contributed to inequities in the health service delivery. Previous studies have shown that health inequities observed may be amplified many times by DHT requirements. The objectives of this scoping review are aimed at synthesizing information on DHT inequities by exploring evidence that describes DHT infrastructure needs focused on promoting health equity in the United States and identifying key challenges both at the individual or patient level and at the health service provider's level. We adapted Arksey and O'Malley's scoping review guidelines in our review. PubMed, Web of Science, CINAHL, and PsycINFO were searched. We also conducted supplementary searches on Google Scholar. The inclusion criteria were peer-reviewed publications that broadly conceptualize or analyze DHT infrastructure from a health equity perspective and the challenges of DHT requirements between 2020 and 2024. We have screened the full text of articles using eligibility criteria such as studies that were included if they examined DHT infrastructure in the United States from a health equity perspective, discussed health disparities resulting from DHT interventions, or investigated the variables influencing health inequities connected to DHT. Two researchers (SR and ZZ) evaluated each citation individually at the title and abstract levels. The thematic approach and qualitative analysis determined this scoping review's outcome. Of the 628 research papers from the search, 27 were included in the analysis based on the inclusion criteria. In this review, we discussed factors such as older adult population, education, race, ethnicity, and socioeconomic status leading to health inequities in DHT. Patients and service providers face challenges related to health inequities in the use of DHT. The most common challenges for service providers were infrastructure and technical issues such as inadequate integration with existing workflows, user-unfriendly health information exchange interfaces, and lack of skilled staff, while for individuals or patients, this included limited broadband web-based access, cultural or linguistic appropriateness, and access to digital tools. The study identified that in the United States, DHT is an essential part of the delivery of health services; yet, it is saddled with key challenges leading to health inequities. Finding pragmatic solutions to these challenges can improve health equity in DHT.

As the rapid advancement of digital health technologies has significantly improved health management, digital health literacy (DHL) has emerged as a crucial determinant of health outcomes. The aim of this study was to assess DHL among Korean adults using a task-based assessment tool and to examine how sociodemographic and health literacy factors are associated with DHL, with the goal of identifying vulnerable groups and informing equitable digital health strategies. This cross-sectional survey was conducted from July 20 to July 31, 2022, among adults aged 19 years and older in South Korea. Participants were recruited nationally, with those younger than 55 years completing an online survey and those aged 55 years and older participating in face-to-face interviews to address the digital divide. Participants' DHL was assessed using the 34-item Digital Health Technology Literacy Assessment Questionnaire, a tool designed to evaluate practical task-based competencies. Among 1041 Korean adults, 27.8% (n=289) demonstrated low DHL, with the largest gaps observed in mobile app use and critical evaluation of health information. The mean DHL score (on a 100-point scale) was 73.8 (SD 29.7). The high and low DHL groups scored 90.3 (SD 35.6) and 31.5 (SD 20.0), respectively. Specifically, only 49 (17%) of the low DHL group were able to sign up for an app, compared with 716 (95.2%) in the high DHL group. Similarly, 52 (18%) of the low DHL group could update an app, whereas 712 (94.7%) could in the high DHL group. Multivariate analysis revealed that older age (≥60 years), lower income (≤US $2000/month), unemployment, and inadequate general health literacy were significantly associated with lower DHL, highlighting the need to target modifiable factors beyond age. This study highlights the ongoing digital health disparities, emphasizing the need for tailored strategies in mobile apps and digital health technologies. Addressing modifiable factors such as health literacy is key to ensuring equitable access and the effective use of digital health resources.

Digital sexually transmitted and blood-borne infection (STBBIs) testing services are used to improve testing access, but might replicate existing social inequities. Previous research has shown that the digital STBBI testing service GetCheckedOnline has improved access to testing in British Columbia (BC), Canada. As part of the program's continuous evaluation, we examined awareness and use of the service in 5 urban, suburban, and rural communities where the program has expanded. This study aimed to determine if social location is associated with differences in awareness and use of the service in 5 communities outside Vancouver, BC. From July to September 2022, we conducted a cross-sectional survey recruiting (in-person and online) sexually active people aged 16 years or older in 5 urban, suburban, and rural communities where GetCheckedOnline had sample collection sites available at the time. We examined differences in awareness and use by age, gender identity, sexual identity, race/ethnicity, education, and income using logistic regression models informed by the Health Equity Measurement Framework. Of the 1658 participants (n=1058, 63.8% in-person and n=600, 36.2% online), 35.3% (586/1658) were aware of GetCheckedOnline and 19.5% (324/1658) had used it. Awareness and use were lower in the first and last age quartiles compared to the second quartile (>38 years: awareness odds ratio [OR] 0.23, 95% CI 0.17-0.32; use OR 0.19, 95% CI 0.12-0.28; <25 years: awareness OR 0.39, 95% CI 0.28-0.53; use OR 0.28, 95% CI 0.18-0.41). Awareness and use were also lower in the lowest income group compared to the highest (awareness OR 0.39, 95% CI 0.24-0.65; use OR 0.36, 95% CI 0.20-0.65). Awareness and use were higher among genderfluid, genderqueer, and nonbinary participants compared to men (awareness OR 2.27, 95% CI 1.63-3.18; use OR 1.97, 95% CI 1.36-2.84), transgender compared to cisgender participants (awareness OR 2.17, 95% CI 1.54-3.06; use OR 2.15, 95% CI 0.46-3.13), and nonheterosexual compared to heterosexual participants (awareness OR 2.37, 95% CI 1.89-2.97; use OR 2.53, 95% CI 1.91-3.38). People of color had higher awareness and use vs White participants (awareness OR 1.74, 95% CI 1.34-2.26; use OR 2.01, 95% CI 1.48-2.72). Indigenous participants had higher awareness than White participants (OR 1.65, 95% CI 1.19-2.20) but no difference in use. Women had similar awareness but lower use compared to men (OR 0.68, 95% CI 0.50-0.92). GetCheckedOnline is an equitable means of access to STBBI testing for some but not all equity-owed groups in BC. Further adaptations should consider factors such as differences in material circumstances to improve its accessibility for all.

Digital recruitment methods offer opportunities to address challenges in clinical research participation, particularly in neurology. However, the impact of digital approaches across socioeconomic and demographic groups remains inadequately understood. This study investigates the influence of sociodemographic factors on recruitment and attrition in a remote neurological research cohort, mapping participation pathways and identifying disparities to inform inclusive digital strategies. We conducted a nonexperimental, observational longitudinal cohort study at Mayo Clinic using patient-portal invitations between March and July 2024 as part of a remote speech capture study. Eligibility criteria included age 18 years and older, US residence, and English proficiency. Of 5846 invited patients, progression was tracked across checkpoints (invitation, eligibility screening, electronic consent, and task completion) using Epic (Epic Systems Corporation) to obtain demographic information, Qualtrics (Qualtrics, LLC) for screening, PTrax (a Mayo Clinic-developed Participant Tracking System) for consent tracking, and the recording platform. Socioeconomic context was assessed using the Housing-based Socioeconomic Status (HOUSES) index, where higher values indicate higher socioeconomic status, and the Area Deprivation Index (ADI), where higher values reflect greater neighborhood disadvantage. Data diagnostics included Anderson-Darling tests for non-normality and Little missing completely at random (MCAR) test to characterize missingness. Associations between participation outcomes and age, sex, urbanicity, and socioeconomic indices were examined using nonparametric tests. Exact P values and 95% CIs are reported. Analyses were conducted using BlueSky Statistics (BlueSky Statistics, LLC) and the Python SciPy package. Overall, 415 out of 5846 participants (7.1%) completed all study requirements. Completers were older (median age 66.4, IQR 56.0-72.5; 95% CI 65.1-67.6 years) than noncompleters (median age 62.8, IQR 47.5-72.7; 95% CI 62.2-63.2 years; P<.001). Participants from more socioeconomically disadvantaged neighborhoods were less likely to respond (invitation nonresponder median ADI 45.0, IQR 29.0-63.0 vs interested median ADI 42.0, IQR 27.0-59.0; P<.001), and completers had slightly lower ADI ranks than noncompleters (median 41.0, IQR 27.0-56.0 vs median 44.5, IQR 28.0-62.0; P=.04). Urban participants enrolled faster (median 32.0, IQR 9.0-58.0; 95% CI 31.0-37.0 days) than rural (median 41.0, IQR 22.0-65.0; 95% CI 37.0-49.0 days; P=.01). Female participants responded slower (median 38.5, IQR 14.8-66.3; 95% CI 35.0-41.0 days) than males (median 32.0, IQR 8.0-57.5; 95% CI 29.0-38.0 days; P=.01). No significant differences were observed for the HOUSES index, and device type was unrelated to completion or timelines. Missingness for key variables was completely at random (MCAR χ²3=3.45; P=.24). Digital recruitment does not overcome traditional barriers to participation and may introduce new disparities related to age, urbanicity, and neighborhood disadvantage. These findings inform inclusive digital research strategies, including multichannel outreach, age-specific engagement, and rural technical support. This study applies longitudinal pathway analysis to digital neurology recruitment, offering actionable insights for improving inclusivity in remote research.

The rapid integration of information technology into daily life has exacerbated the digital divide (DD), particularly among older adults, who often face barriers to technology adoption. Although prior research has linked technology use to cognitive benefits, the long-term neurostructural and cognitive consequences of the DD remain poorly understood. The aim of this study is to use large-scale neuroimaging data to examine how the DD affects long-term brain structure and cognitive aging in older adults. It specifically investigates (1) structural and cognitive differences between older adults with and without DD engagement, (2) predictive relationships between group-distinctive brain regions and cognitive outcomes, and (3) longitudinal impacts of DD exposure on accelerated aging trajectories of neural substrates and cognitive functions. The study included 1280 community-dwelling older adults (aged 65-90 y) who completed comprehensive cognitive assessments and structural magnetic resonance imaging scans at baseline. Longitudinal data were available for 689 participants (mean follow-up 3.2 y). Participants were classified into the DD (n=640) and overcoming DD (n=640) groups using rigorous propensity score matching to control for age, education, gender, and baseline health conditions. A computational framework using the searchlight technique and cross-validation classification model investigated group differences in structural features and cognitive representation. The aging rate of each voxel's structural feature was calculated to explore the long-term influence of the DD. The DD group showed significant deficits in executive function (t=4.75; P<.001; Cohen d=0.38) and processing speed (t=4.62; P<.001; Cohen d=0.37) compared to the overcoming DD group. Reduced gray matter volume in the DD group spanned the fusiform gyrus, hippocampus, parahippocampal gyrus, and superior temporal sulcus (false discovery rate-corrected P<.05). The computational framework identified the key structural substrates related to executive function and processing speed, excluding the ventro-orbitofrontal lobe (classification accuracy <0.6). Longitudinal findings highlighted the long-term impact of the DD. The DD group exhibited faster gray matter volume decline in the middle frontal gyrus (t=3.95 for the peak voxel in this cluster, false discovery rate-corrected P<.05), which mediated 17% of episodic memory decline (P=.02). Older adults who overcome the DD demonstrate preserved gray matter structure and slower cognitive decline, particularly in frontotemporal regions critical for executive function. Our findings underscore that mobile digital interventions should be explored as potential cognitive decline prevention strategies.

Despite numerous research studies examining the digital divide in the context of eHealth, studies specifically targeting inpatients remain limited. In comparison with the general population, inpatients typically undergo a progression from outpatient consultations to inpatient treatment and subsequent out-of-hospital rehabilitation. This sequential process gives rise to requirements across nearly all usage scenarios of eHealth services. Therefore, this study focuses on inpatients with potential interest in eHealth as the research subjects. This study aimed to analyze the digital divide in the awareness of, want for, and adoption of diverse eHealth services and further explore factors influencing these disparities among inpatients. A cross-sectional study was conducted in 2023, involving 1322 inpatients aged ≥15 years from 3 tertiary hospitals in Jinan, China. Data were collected through a face-to-face questionnaire survey. eHealth services were categorized into 3 types (ie, information-based, treatment intermediary, and treatment eHealth services). The adoption gap ratio is used to explore the gap between eHealth services' adoption and awareness or want. The awareness, want, and adoption gap segment matrix was used to further analyze the digital divide in eHealth services and categorize inpatients into 4 groups (ie, opened, perception deficiency, desire deficiency, and closed group), each of which was further divided into 4 subcategories (ie, strong, generic, want-bias, and awareness-bias). Binary logistic regression was used to explore potential influencing factors of awareness, want, and adoption across diverse eHealth services. The results showed that of 1322 inpatients, 1204 (91.1%) have awareness of eHealth services, 1169 (88.4%) have want for eHealth services, and 847 (64.1%) have adopted 1 or more of these services. Digital divides were observed in information-based eHealth, treatment intermediary, and treatment eHealth services, with adoption gap ratios reaching 32.1%, 34.1%, and 66.5%, respectively. Notably, all 3 eHealth services fell into the opened group. Among the 3 services, information-based eHealth services were located in the want-bias subgroup, treatment services belonged to the generic subgroup, and treatment intermediary services fell into the strong group. Binary logistic regression revealed that the influence of age, place of residence, educational attainment, income, self-rated health, chronic disease, eHealth literacy, perceived usefulness, and perceived ease of use on the awareness of, want for, and adoption of eHealth services showed notable difference and differed significantly depending on the types of eHealth services. This study provides empirical evidence on the existence of a digital divide in awareness, want, and adoption across diverse eHealth services among inpatients in Jinan, China. Given the promise and opportunities that eHealth services increase access to health care, future digital interventions should both address or bridge the digital divide in various eHealth services and consider the implementation of differentiated marketing strategies for diverse eHealth services.

The rapid advancement of digital health technologies (DHTs) offers substantial potential for improving health care access; however, it simultaneously risks exacerbating existing inequities for marginalized populations. Previous research on the digital divide has often treated individuals with blindness as a homogenous group, primarily focusing on barriers related to digital access and skills. However, less is known about the nuanced experiences of specific subgroups, such as educated and digitally literate young adults. This study focuses on this demographic to understand how their advanced digital capabilities interact with systemic and infrastructural barriers in health care. This study aimed to explore the lived health care experiences of educated young adults with blindness in China, specifically identifying how DHTs simultaneously contribute to their empowerment and exclusion. Eligible participants were educated young adults with blindness in China (aged 18-30 years, Mandarin speakers, smartphone users, and holding or pursuing higher education). A total of 12 semistructured interviews were conducted in Mandarin during September 2024. All interviews were audio-recorded and transcribed verbatim. An inductive thematic analysis was used to interpret the data and identify key themes. Participants' experiences highlighted an \"empowered but excluded\" dynamic. Seven key themes emerged, categorized into empowerment and exclusion. Empowerment themes included: (1) digital platforms empowering self-management and health care access, where DHTs enabled independent appointment booking and access to comprehensive health information; and (2) digital platforms empowering for finding medical visit companions, facilitating the discovery of companions for physical and emotional support. Exclusion themes comprised: (3) inaccessible online appointment systems, due to noninclusive designs; (4) inaccessible health care environments and information formats, stemming from nonaccessible self-service machines and written materials; (5) lack of provider competencies in respecting patient autonomy, as providers often assumed digital incompetence; (6) data privacy and security concerns, heightened by increased digitalization and reliance on assistive tools; and (7) challenges related to the quality and consistency of online companion support, highlighting the limitations of platform-based assistance. Our findings reveal an \"empowered but excluded\" dynamic: the potential for digital empowerment and enhanced independence is often curtailed by systematic barriers. Addressing this necessitates a multifaceted approach: enhancing technological accessibility through robust standards adherence and inclusive co-design processes; improving health care provider competencies in patient-centered care via targeted training; and empowering educated young adults with blindness by building their capacity for self-determination to achieve equitable health care access.

The digital health literacy instrument (DHLI) was developed in 2017 to measure individuals' ability to access, understand, evaluate, and apply online health information. Since that time, digital health has shifted from desktop-based internet use to mobile devices, and there has been a rapidly expanding range of health apps. Additionally, heightened privacy and data security requirements have increased the complexity of user competencies needed to engage with digital health tools. These developments underscore the need to update the original DHLI. This study aimed to create an updated version of the DHLI (DHLI 2.0) that reflects current digital health practices and to examine its reliability and validity by exploring associations with user characteristics. Additionally, we aimed to develop a short-form version to facilitate broader use in research and practice. The instrument was iteratively updated and pilot-tested to retain the original theoretical framework while reflecting current digital health practices, devices, and emerging challenges such as mobile use and data security. Several items were reworded and a new 2-item subscale on digital safety was added. The full DHLI 2.0 comprises 24 items across 8 skill domains. A 16-item short form was developed by iteratively removing 1 or 2 items per subscale based on the \"α if item deleted\" criterion, while retaining the same subscale structure as the full form. Data to validate the new version of the instrument were collected in June 2024 through an online survey among members of a representative citizen panel in Friesland, a province in the Netherlands (N=2728). Sociodemographics, internet and health-related internet use, general health literacy (measured with the Single Item Literacy Screener), self-reported health, and health care use were assessed. Internal consistency was evaluated using Cronbach α, and construct validity was assessed via Spearman ρ correlations with related constructs. Internal consistency was high for both the full (α=0.94) and short-form (α=0.90) scales. Most subscales showed satisfactory to excellent reliability (α=0.71-0.93), while \"Securing privacy\" and \"Using security measures\" demonstrated moderate reliability (α=0.65-0.66). The DHLI 2.0 total scores were approximately normally distributed (skewness -0.5; kurtosis 0.4). As expected, digital health literacy was negatively correlated with age (ρ=-0.39, P<.001) and positively correlated with education (ρ=0.22, P<.001), income (ρ=0.27, P<.001), time spent online (ρ=0.32, P<.001), and general health literacy (ρ=-0.42, P<.001). The DHLI 2.0 provides an updated, reliable, and valid measure of digital health literacy covering 8 key domains, including data security. The 16-item short form offers a concise alternative suitable for research and possibly practical applications in health and eHealth contexts.

Short-video platforms, characterized by algorithmic curation and passive consumption, have emerged as dominant components of digital life. However, the associations between short-video platform use and health across different groups and usage behaviors remain understudied. This study investigates associations between short-video platform use and health, examining whether these relationships vary across health status, usage behaviors, and socioeconomic status. A cross-sectional study was conducted using multistage stratified sampling across eastern, central, and western China from July to September 2024. The inclusion criteria were age 18 years or older, ability to communicate effectively, and no cognitive disorders or mental disturbance. Of 7725 participants enrolled, 46.96% (n=3628) were male, and the average age was 65.49 (SD 8.39) years. The data were collected via face-to-face interviews using a structured questionnaire. Self-rated health and relative health deprivation (Kakwani index) were used to measure health. Quantile regression explored associations between whether using short-video platform and health varies across the health distribution, while linear regression examined associations of years, frequency, daily duration, and purpose diversity of short-video platform use with health. Moderating effect analysis explored the role of socioeconomic status in the relationship between the daily duration of use and health. Coefficients were tested using 2-tailed t tests, and statistical significance was defined as a 2-sided P value less than .05. Quantile regression revealed heterogeneous associations. Compared to nonusers, short-video platform users had better self-rated health at the 70th to 90th quantiles and lower relative health deprivation at the 10th to 30th quantiles. However, the users at the 10th quantile of self-rated health had worse self-rated health (β=-2.224, 95% CI -3.835 to -0.613). Longer engagement (≥3 y) correlated with lower relative health deprivation (β=1.970, 95% CI 0.308-3.632), while daily use of 1-4 hours was associated with poorer self-rated health (β=-3.385, 95% CI -4.872 to -1.898; β=-3.038, 95% CI -5.054 to -1.022) and higher relative health deprivation (β=0.035, 95% CI 0.021-0.050; P<.001; β=0.034, 95% CI 0.014-0.054). Compared to no purposeful use, using with 2 purposes was associated with better self-rated health (β=6.082, 95% CI 0.250-11.914) and lower relative health deprivation (β=-0.063, 95% CI -0.120 to -0.005). The association was stronger for use with 3 or more purposes. Socioeconomic status moderated the relationship between daily duration of use and health. This study provides a more specific investigation of how these associations vary across health strata and usage patterns. The findings reveal patterns of benefit and risk across population subgroups, underscoring that how and why individuals engage with platforms matter more than mere access or frequency. These insights necessitate targeted digital well-being policies that protect vulnerable groups, particularly those in poor health or with lower socioeconomic status. Furthermore, policies should actively encourage intentional, functionally grounded use to reduce health inequities and advance equitable digital inclusion.