Journal of Medical Internet Research

Optimizing Web Links Used in Digital Vaccination Invitations to Raise Trust and Booking Intention: 3 Online Randomized Controlled Trials

2026-08-25T12:30:13-04:00

Background: People are encouraged to respond swiftly to digital health invitations, but they can be (rightly) skeptical about their legitimacy. Objective: Drawing on digital communication theory and psychological science, we hypothesized that easy-to-read web links that facilitate participants’ ability to identify the health organization as the website host would improve trust in and user engagement with digital communications. Methods: In 3 double-blind, randomized online experiments, adult UK residents were recruited via the online platform Prolific (experiment 1: N=569) or Qualtrics (experiment 2: N=596; experiment 3: N=1993). In each experiment, participants read a hypothetical email invitation for a COVID-19 vaccine from the UK’s National Health Service (NHS). Participants reported trust in the email (primary outcome), whether the web link was easy to read, who they thought the website host was, and their intention to book an appointment via the web link. We manipulated the booking web link (between-participants, double-blind allocation via the Qualtrics randomizer). Across experiments, the control group read the email containing a deactivated NHS vaccination booking web link: “accurx.thirdparty.nhs.uk/r/aafwaczmd5.” In experiment 1, participants read the email with the control link (randomized n=300, analyzed n=286) or an experimental clear link (“vaccine-booking.nhs.uk”; randomized n=301, analyzed n=283). In experiment 2, participants read the email with the control link (randomized n=203, analyzed n=201) or one of 2 experimental links: a shortened web link (“https://bit.ly/3GtTL0c”; randomized n=201, analyzed n=201) or a text-embedded link (“book ”; randomized n=196, analyzed n=194). In experiment 3, participants read the email with the control link (randomized n=655, analyzed n=655), the clear link (randomized n=669, analyzed n=668), or the text-embedded link (randomized n=670, analyzed n=670). Results: Across experiments, the control web link was poorly perceived, with most participants (729/1142, 63%) unsure or unlikely to use it. Relative to the control web link, the clear web link improved trust (β coefficient=0.26, 95% CI 0.18-0.36; β coefficient=0.24, 95% CI 0.19-0.30). The text-embedded web link also improved trust (β coefficient=0.18, 95% CI 0.09-0.27; β coefficient=0.17, 95% CI 0.11-0.22), but the shortened web link did not (β coefficient=0.01, 95% CI −0.09 to 0.11). Across experiments, improved host identification and ease of reading explained increased trust, which was significantly associated with increased booking intention. The clear and text-embedded web link (vs control) effects were robust when controlling for demographics. Conclusions: We extend digital communication research by investigating how web link design can reduce people’s justified suspicion in health messaging. Moving beyond the previous research focus on health message content, we experimentally test the role of web link wording. We bring causal evidence that easier-to-read links that have easy-to-identify host health institutions increased trust and intention to use the link. We provide simple, practical design guidance to improve real-world engagement with digital health communications. Trial Registration: ClinicalTrials.gov NCT07516600; https://clinicaltrials.gov/study/NCT07516600 and NCT07532967; https://clinicaltrials.gov/study/NCT07532967 and NCT07538349; https://clinicaltrials.gov/study/NCT07538349

Patients’ Perspectives on Applications of AI and Personalized Medicine in Life-Threatening Heart Disease: European Cross-Sectional Patient Questionnaire Study

2026-08-25T12:30:13-04:00

Background: The growing integration of personalized risk prediction (PRP) and AI substantially reshapes diagnostic and therapeutic decision-making in health care. At the same time, its responsible adoption depends not only on technical performance, but also on patients’ perspectives and acceptance. Objective: This study systematically examined patients’ perspectives across several European countries and explored how patients’ technology-related attitudes relate to their evaluations of personalized and AI-supported approaches in cardiac care. As part of the PROFID (Prevention of Sudden Cardiac Death After Myocardial Infarction by Defibrillator Implantation) project, its focus is on the ethical use of PRP and AI in the clinical context of decision-making regarding sudden cardiac death (SCD) prevention and implantable cardioverter-defibrillator (ICD) implantation. Methods: The study used a cross-sectional survey design with a standardized questionnaire including multimedia content. The target population comprised adults aged 18 years or older living in 6 European countries who met at least one of the following (self-reported) clinical criteria: heart failure, myocardial infarction (MI), cardiac arrest, or current ICD implantation. An exploratory factor analysis (EFA) was used to identify and evaluate internally consistent factors, and subsequent regression analyses examined associations between these factors and technological openness, sociodemographic characteristics, and patients’ views on PRP and AI in cardiac care. Results: The sample consisted of 470 participants from Germany (n=210), the Netherlands (n=86), the United Kingdom (n=145), and 3 other European countries (n=29; Austria, Belgium, and Spain). Overall, 51.9% (244/470) of respondents were male and 48.1% (226/470) were female. The mean age of the sample was 61.12 (SD 12.62) years. The EFA showed six clearly interpretable factors: (1) perceived benefits and support of PRP models in medical decision-making (MDM), (2) perceived benefits and support of AI in MDM, (3) transparency expectations in algorithmic decision-making, (4) support for delegating decisions to algorithms, (5) self-reported AI literacy, and (6) preference for shared decision-making (SDM). The regression analysis showed the relations of technological readiness, self-reported AI literacy, support for delegation of decisions to algorithms, transparency expectations in algorithmic decision-making, preferences for SDM, educational attainment, gender, and age to find associations with patients’ perceived benefits and support of PRP or AI in MDM. Conclusions: The findings support existing assumptions while also highlighting additional aspects that should be considered if high-level technologies are used in decision-making processes related to ICD implantation. PRP and AI were generally perceived as useful tools to support decision-making regarding ICD indication, provided transparency is ensured and patients remain actively involved in the decision-making process. Mandatory use and full delegation to decision-making directly by AI were broadly rejected. The attributed acceptance of delegation to PRP models was significantly higher than AI. In summary, implementation should support empathetic communication, patient involvement, and individual and institutional responsibility.

Wireless Electroencephalography in Research on Children With Developmental Disabilities: Scoping Review

2026-08-25T12:00:18-04:00

Background: Wireless electroencephalography (EEG) systems offer practical advantages over conventional wired devices in the assessment of children with developmental disabilities (DDs), including enhanced portability, reduced participant burden, and ease of use. However, how these systems have been applied across diverse DD populations, research purposes, and clinical contexts remains unclear. Objective: This scoping review aimed to map available evidence on wireless EEG applications in children with DDs, characterize device specifications by application purpose, identify neurobehavioral challenges and corresponding methodological solutions, and assess data quality–related reporting practices. Methods: This scoping review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews), PRISMA-S (PRISMA Statement for Reporting Literature Searches in Systematic Reviews), and the population, concept, and context framework: population, children aged<19 years with DDs; concept, studies using wireless EEG devices for data collection; and context, all research and clinical settings. A systematic search was conducted across 7 databases (PubMed, Embase, IEEE Xplore, Web of Science, CINAHL, PsycINFO, and Scopus) from their inception through December 2025. Screening was performed independently by 4 reviewers. Data on study characteristics, device specifications, neurobehavioral recording challenges, and data quality reporting were extracted and synthesized descriptively, including cross-tabulation of devices by application purpose. Results: Of 594 identified records, 64 studies enrolling 3103 participants met the inclusion criteria. Studies were published between 2005 and 2025, with an increasing trend in both publications and sample sizes. Attention-deficit/hyperactivity disorder (38/64, 59.4%) and autism spectrum disorder (20/64, 31.3%) were the most frequently studied conditions. Primary application domains were biomarker-driven assessment and diagnosis (33/64, 51.6%), brain-computer interface (BCI) technology (18/64, 28.1%), intervention evaluation (8/64, 12.5%), and task or state monitoring (5/64, 7.8%). Across 65 study-device pairs, consumer-grade devices predominated (31/65, 47.7%), followed by research-use-only (19/65, 29.2%) and medical devices (15/65, 23.1%). Purpose-driven patterns emerged: BCI studies favored low-channel, dry-electrode, consumer-grade devices, whereas biomarker-driven and intervention studies used higher channel counts and greater signal fidelity. Recurring neurobehavioral challenges (eg, inattention, sensory hypersensitivity, and motor impairment) were addressed through rapid, low-preparation electrode setups, child-friendly device designs, and adapted recording protocols such as home-based or caregiver-mediated sessions. Data quality–related reporting was substantially incomplete: 85.9% (55/64) did not report validation against a wired EEG system, 79.7% (51/64) did not specify impedance thresholds, and 12.5% (8/64) described no artifact handling. Conclusions: This scoping review is the first to comprehensively map wireless EEG research in children across a broad spectrum of DDs—integrating diagnosis, study context, and device characteristics—rather than focusing on a single condition or purpose. This review highlights critical gaps in data quality–related reporting that limit the interpretability and comparability of current findings. Future studies should prioritize rigorous validation within DD cohorts and the development of population-specific guidelines for device selection, signal quality assurance, and reporting transparency.

Health-Seeking Behaviors After Acute Respiratory Infection Among Urban and Rural Residents and Different Age Groups: Cross-Sectional Questionnaire Study

2026-08-25T11:30:09-04:00

Background: The choice of pathways in health-seeking behavior following acute respiratory infection (ARI) is critical for health care resource allocation, yet traditional logistic regression methods struggle to capture the dynamic evolution of such behaviors. Objective: This study aimed to quantify the dynamic process of changes in health-seeking behaviors following the onset of ARI and to identify differences in behavioral pathways associated with key factors such as urban-rural status and age. Methods: This study used a multistate Markov model to quantify transition probabilities and intensities between various health-seeking behaviors, using beta regression models to assess differences in state transition probabilities across urban-rural groups and age groups. Results: This analysis included 2340 patients with ARI from sampled areas of Chengdu. Subgroup analysis revealed that the rural population was more likely to go directly to a hospital after ARI onset, while the urban population was more likely to purchase medicine directly. Furthermore, there were no significant differences in information seeking and self-monitoring (ISM) use between urban and rural residents after ARI onset. However, following ISM, rural residents were significantly less likely than urban residents to visit a hospital or purchase medicine. Minors and older adults were significantly less likely than adults to engage in ISM after ARI onset. Minors were more likely than adults to directly visit hospitals after ARI onset. After ISM use, adults were more inclined to purchase medicine than minors and older adults, while older adults were more inclined to visit hospitals. Conclusions: The findings indicated that urban and rural populations, as well as different age groups, exhibited distinct patterns of seeking medical care after ARI onset, and their subsequent behaviors diverged when using ISM. The findings suggested that health interventions should leverage ISM to effectively drive offline actions, implementing targeted strategies tailored to the decision-making characteristics of different populations.

Clinical Specialty Expansion of AI-Enabled and Machine Learning–Enabled Medical Devices Authorized by the US Food and Drug Administration From 1995 to 2025: Longitudinal Content Analysis

2026-08-25T11:00:20-04:00

Background: The US Food and Drug Administration (FDA) has authorized AI-enabled and machine learning (ML)–enabled medical devices since 1995 and maintains a public registry of these authorizations. Prior analyses report that radiology dominates this landscape, but whether that concentration has persisted, intensified, or begun to reverse across 3 decades, particularly since 2022, remains insufficiently characterized. Objective: This study aimed to (1) characterize the longitudinal growth of FDA-authorized AI/ML-enabled devices from 1995 to 2025, (2) quantify the temporal evolution of clinical specialty distribution across 4 eras, (3) identify emerging specialties, and (4) examine the association between manufacturer type and nonradiology authorization. Methods: All 1430 devices in the FDA AI-Enabled Medical Devices registry (downloaded on March 1, 2026) with final marketing-authorization decisions through December 31, 2025, were analyzed. Devices were stratified by clinical specialty (FDA advisory committee panel) and 4 eras: Era 1 (1995‐2015), Era 2 (2016‐2019), Era 3 (2020‐2022), and Era 4 (2023‐2025). Concentration was quantified using the Herfindahl-Hirschman Index (HHI) with bootstrap CIs; the Cochran-Armitage test assessed trends in specialty share, with Bonferroni correction. Multivariable logistic regression estimated the odds of nonradiology authorization by manufacturer type and era, with an era-by-manufacturer interaction term. Sensitivity analyses used cluster-robust standard errors, a continuous authorization year variable, and Firth penalized regression. Manufacturers were classified using FDA records, Crunchbase, PitchBook, and company websites. Results: Annual authorizations rose from a mean of 2.0 (SD 2.0) in Era 1 to a mean of 264 (SD 58.2) in Era 4, with 331 authorizations in 2025 alone; the 510(k) pathway accounted for 96.2% (1376/1430). Radiology led in every era but followed a nonmonotonic trajectory, rising from 35.7% (15/42, Era 1) to a peak of 85.5% (347/406, Era 3) before declining to 77.5% (614/792, Era 4), the first significant decline on record (=.001). The HHI fell from 0.738 (Era 3) to 0.612 (Era 4; bootstrap <.001), indicating measurable diversification. Specialty distribution was associated with era (²=328.0; <.001; Cramér =0.28). Compared with incumbents, start-ups (odds ratio [OR] 5.09, 95% CI 3.33‐7.79) and technology companies (OR 50.62, 95% CI 12.90‐198.64) had higher odds of nonradiology authorization; the nonsignificant era-by-manufacturer interaction (likelihood ratio test ²=11.16; =.19) indicates a persistent rather than widening effect. The technology-company OR derives from only 13 devices across 5 firms; although directionally robust in sensitivity analyses, it is imprecise and warrants cautious interpretation. Conclusions: Radiology remained dominant, accounting for 77.5% (614/792) of Era 4 authorizations, but the specialty distribution showed measurable diversification during 2023 to 2025, associated with start-up and technology-company activity. Maturation of clinical data infrastructure beyond imaging is a plausible but unmeasured contributing condition, and authorization is not adoption. The findings bear on health-system readiness, workforce training, and specialty-specific regulatory frameworks.

Digital Health Competence and Attitudes Toward AI Among Health Care Professionals: Convergent Mixed Methods Study

2026-08-24T15:45:10-04:00

Background: Digital transformation is reshaping health care systems and requires health care professionals to develop advanced digital health competencies. The integration of AI into clinical practice introduces new demands related to critical evaluation, human oversight, ethical responsibility, and regulatory compliance. However, evidence linking validated measures of digital health competence with health care professionals’ attitudes toward AI remains limited. Objective: This study aimed to (1) assess digital health competence among health care professionals in Spain, (2) examine organizational conditions supporting competence development, (3) explore perceptions about AI use in the workplace, and (4) examine the association between digital health competence and attitudes toward AI. Methods: A national cross-sectional convergent mixed methods study was conducted between November 2023 and January 2024 with a voluntary convenience sample of 229 health care professionals. Digital health competence was assessed using DigiHealthCom (digital health competence instrument; 42 items, 5 domains) and DigiComInf (the aspects associated with digital health competence instrument; 15 items, 3 domains). Confirmatory factor analysis evaluated structural validity. Open-ended responses regarding AI perceptions were explored using inductive qualitative content analysis. AI attitudes were classified into 4 categories (positive, negative, ambivalent, and uncertain), and their association with digital health competence was examined using multinomial logistic regression adjusted for age and sex. Results: Participants were predominantly female (169/229, 73.8%) and nurses (123/229, 53.7%), with a mean age of 45.9 (SD 10) years. Overall digital health competence was moderate (mean 3.01, SD 0.51), with the highest scores in information and communication technology competence (3.34, SD 0.63) and the lowest in competence related to evaluating and implementing digital solutions (2.83, SD 0.63). Organizational and educational support for competence development was also moderate (mean 2.51, SD 0.57), with organizational planning receiving the lowest DigiComInf scores (2.21, SD 0.76). Confirmatory factor analysis supported the proposed factor structures for both instruments (DigiHealthCom: comparative fit index=0.95, root-mean-square error of approximation=0.049; DigiComInf: comparative fit index=0.95, root-mean-square error of approximation=0.084). Most participants expressed positive attitudes toward AI in the workplace (134/228, 58.77%). Qualitative findings revealed a pattern of conditional optimism, with expected benefits for efficiency and patient care balanced by concerns regarding training, governance, regulation, and human oversight. Conclusions: Digital health competence was positively associated with health care professionals’ attitudes toward AI. However, the cross-sectional design does not allow conclusions regarding the direction of this association. Deficiencies in higher-order competencies in evaluation and implementation, together with limited organizational support, highlight areas that may benefit from targeted educational and organizational strategies to promote the safe and responsible use of AI in health care.

Transformation Before Innovation: Getting the Foundations Right Is Harder, More Important Work

2026-08-24T14:45:10-04:00

To Bridge the Hepatitis B Diagnosis Gap in Africa, Innovation Must Go Beyond Digital

2026-08-21T17:00:18-04:00

When the Algorithm Starts Seeing the Patient First: China and the Changing Role of Physicians

2026-08-21T16:30:16-04:00

US Nursing Strikes Highlight Systemic Challenges: Can Digital Health Be Part of the Solution?

2026-08-21T15:45:03-04:00