Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Electronic health (eHealth) literacy was conceptualized in 2006 as the ability of Internet users to locate, evaluate, and act upon online health information. eHealth advancements have cultivated transactional opportunities for patients to access, share, and monitor health information. However, empirical evidence shows that existing models and measures have limited theoretical underpinnings that reflect the transactional capabilities of eHealth. The current manuscript describes a conceptual model based on the Transactional Model of Communication (TMC), in which eHealth literacy is conceptualized as dynamic, cyclical, and shaped by contextual factors. Objective: This study systematically examined eHealth literacy definitions, models, and measures to propose a refined conceptual and operational definition based on the TMC. Methods: An adapted version of Walker and Avant’s concept analysis method was used to guide the systematic review of eHealth literacy definitions (N = 10), rating scales (N = 6), models (N = 4), and peer-reviewed model applications (N = 16). An inductive cluster analysis was conducted to identify salient themes across definitions. Dimensions, antecedents, and consequences within models and measures were extracted, deductively analyzed based on codes consistent with the TMC. Results: A disconnect remains between operational skills in definitions and the literacies within models and measures. Theoretical underpinnings of eHealth literacy remain dismal, although recent measures incorporate tenants of the social cognitive theory. Despite the transactional capabilities of eHealth, the role of “communication” remains underdeveloped and limited to the physical and cognitive processing of two-way interactions that occur in eHealth. Conclusions: The Transactional Model of eHealth Literacy (TMeHL) and a corresponding definition is proposed. eHealth literacy is a hierarchical and multidimensional intrapersonal skillset that mediates the cyclical effect of contextual factors (i.e., user-oriented, task-oriented) on factors related to patient activation. The intrapersonal skillset is comprised of four eHealth literacies, which correspond with operational behaviors central to defining eHealth literacy: functional (i.e., locate, understand), communicative (i.e., exchange), critical (i.e., evaluate), and translational (i.e., apply). As posited by the model and consistent with the TMC, this four-dimensional intrapersonal skillset counteracts the negative effect of noise produced by preceding contextual factors, to ultimately influence patient activation and expectations of future eHealth experiences.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Electronic health (eHealth) information is engrained in the healthcare experience to engage patients across the lifespan. Both eHealth accessibility and optimization are influenced by lifespan development, as older adults experience greater challenges accessing and using eHealth tools as compared to their younger counterparts. The eHealth Literacy Scale (eHEALS) is the most popular measure used to assess patient confidence locating, understanding, evaluating, and acting upon online health information. Currently, however, the factor structure of the eHEALS across discrete age groups is not well understood, which limits its usefulness as a measure of eHealth literacy across the lifespan. Objective: The purpose of this study was to examine the structure of eHEALS scores and the degree of measurement invariance among United States (U.S.) adults representing the following generations: Millennials (18-35 year olds), Generation X (36-51 year olds), Baby Boomers (52-70 year olds), and the Silent Generation (71-84 year olds). Methods: Millennials (N = 281; M = 26.54 years, SD = 5.14 years), Generation X (N = 164; M = 42.97 years, SD = 5.01 years), and Baby Boomers/Silent Generation (N = 384; M = 62.80 years, SD = 6.66 years) members completed the eHEALS. The 3-factor (RMSEA = .06; CFI = .99; TLI = .98) and 4-factor (RSMEA = .06; CFI = .99; TLI = .98) models showed the best global fit, as compared to the 1- and 2-factor models. However, the 4-factor model did not have statistically significant factor loadings on the 4th factor, which led to the acceptance of the 3-factor eHEALS model. The 3-factors included eHealth Information Awareness, Search, and Engagement. Pattern invariance was supported with acceptable model fit (RMSEA = .06; ΔX2 = P > .05; ΔCFI = 0). Compared to Millennials and members of Generation X, those in the Baby Boomer and Silent Generations reported less confidence in their awareness of eHealth resources (P < .001), information seeking skills (P = .003), and ability to evaluate and act on health information found in the Internet (P < .001). Results: Young (18-48 years old; N = 411) and old (49-84 years old; N = 419) adults completed the survey. A 3-factor model had the best fit (RMSEA = .06; CFI = .99; TLI = .98), as compared to the 1-factor, 2-factor, and 4-factor models. These 3-factors included eHealth Information Awareness (2 items), Information Seeking (2 Items), and Information and Evaluation (4 items). Pattern invariance was supported with acceptable model fit (RMSEA = .06; ΔX2 = p > .05; ΔCFI = 0). Compared with younger adults, older adults had less confidence in eHealth resource awareness (p < .001), information seeking skills (p < .01), and ability to evaluate and act upon online health information (p < .001). Conclusions: The eHEALS can be used to uniquely assess, monitor, and evaluate Internet users’ awareness of eHealth resources, information seeking skills, and engagement abilities. Configural and pattern invariance was observed across all generation groups in the 3-factor eHEALS model. To meet gold standards for factor interpretation (i.e., 3 items or indicators per factor), future research is needed to create and assess additional eHEALS items. Future research is also needed to identify and test items for a fourth factor, one that captures the social nature of eHealth.

Deaf and hard-of-hearing (DHH) populations are understudied in health services research and underserved in healthcare systems. Existing data indicate that adult DHH patients are more likely to use the emergency department (ED) for less emergent conditions than non-DHH patients. However, the lack of research focused on this population’s ED utilization impedes the development of health promotion and quality improvement interventions to improve patient health and quality outcomes. The purpose of this study was to develop a conceptual model describing patient and non-patient (e.g., community, health system, provider) factors influencing ED utilization and ED care processes among DHH people. We conducted a critical review and used Andersen’s Behavioral Model of Health Services Use and the PRECEDE-PROCEED Model to classify factors based on their theoretical and/or empirically described role. The resulting Conceptual Model of Emergency Department Utilization Among Deaf and Hard-of-Hearing Patients provides predisposing, enabling, and reinforcing factors influencing DHH patient ED care seeking and ED care processes. The model highlights the abundance of DHH patient and non-DHH patient enabling factors. This model may be used in quality improvement interventions, health services research, or in organizational planning and policymaking to improve health outcomes for DHH patients.

Objective: Deaf and hard‐of‐hearing (DHH) patients are understudied in emergency medicine health services research. Theory and limited evidence suggest that DHH patients are at higher risk of emergency department (ED) utilization and poorer quality of care. This study assessed ED condition acuity, length of stay (LOS), and acute ED revisits among DHH patients. We hypothesized that DHH patients would experience poorer ED care outcomes.Methods: We conducted a retrospective chart review of a single health care system using data from a large academic medical center in the southeast United States. Data were received from the medical center's data office, and we sampled patients and encounters from between June 2011 and April 2020. We compared DHH American Sign Language (ASL) users (n = 108), DHH English speakers (n = 358), and non‐DHH English speakers (n = 302). We used multilevel modeling to assess the differences among patient segments in outcomes related to ED use and care.Results: As hypothesized, DHH ASL users had longer ED LOS than non‐DHH English speakers, on average 30 min longer. Differences in ED condition acuity, measured through Emergency Severity Index and triage pain scale, were not statistically significant. DHH English speakers represented a majority (61%) of acute ED revisit encounters.Conclusions: Our study identified that DHH ASL users have longer ED LOS than non‐DHH English speakers. Additional research is needed to further explain the association between DHH status and ED care outcomes (including ED LOS and acute revisit), which may be used to identify intervention targets to improve health equity.

Advancing HIV prevention and treatment among at-risk Southern communities of color requires understanding why voluntary HIV testing is accepted or declined. Reasons for testing decisions were investigated among young African American women (n = 223, mean age = 20.4 years) recruited from disadvantaged areas in a Southern US city. A free HIV test was offered following field interviews that assessed HIV risk behaviors and personal and social network characteristics; 69.1% accepted testing, and all were seronegative. After their decision, participants rated reasons for their choice, which were factor analyzed. A four-factor solution showed that test acceptance was related to (1) current sexual relationships and HIV risk concerns, (2) knowledge of HIV medical treatment benefits, (3) awareness of persons living with HIV, and (4) health protection and HIV test convenience. A three-factor solution showed that test refusal was related to (1) negative consequences of a positive test and privacy concerns, (2) low perception of HIV risk, and (3) anticipated social rejection if the test was positive. Comparisons of factor-based average item scores showed that health protection/HIV test convenience was rated as most influential in test acceptance decisions, whereas low perception of HIV risks was rated as most influential in test rejection decisions. The findings suggest that test acceptance can be promoted by offering free, convenient HIV testing as a health check in a testing context that assesses and provides feedback about participants' HIV risk levels.