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Medication abortion accounts for the majority of abortions in the United States, driven in part by the growth in access to telehealth provision of medication abortion. While research indicates high patient satisfaction with telehealth medication abortion care, research on care preferences of patients who use medication abortion remains understudied. Understanding these preferences is essential to informing evidence-based policies that enable people to access person-centered abortion services that meet their values, preferences, and needs. The aim of this study is to compare the abortion care features rated as most important among patients receiving medication abortion via telehealth vs in-person care and to assess participants' access to technologies required for telehealth care. We hypothesized that participants receiving telehealth care would place greater importance on features supporting limited in-person clinic interaction. From May 2021 to March 2023, we surveyed participants (≤70 d of gestation, English or Spanish speakers, aged ≥15 y) obtaining medication abortion at 4 organizations providing care in 6 US states. Participants rated the importance of 12 abortion care features (ie, getting care at home, convenience, cost, safety, effectiveness, and privacy) and described access to technologies required for telehealth. We used bivariable logistic and ordinal regressions with robust SEs to assess whether features rated as \"extremely important\" differed by the medication abortion model received (telehealth vs in-person). Among 1017 patients approached, 876 were eligible, 583 participants enrolled, 487 initiated a survey, 477 (242 telehealth and 235 in-person) completed survey questions regarding access to technologies for telehealth, and 397 completed questions about abortion care features. Across groups, the features most often rated as \"extremely important\" included effectiveness (340/397, 85.6%), safety (326/397, 82.1%), timeliness (307/397, 77.3%), and privacy (165/211, 78.2%), with no significant differences (P>.05) between groups. Compared to in-person participants, telehealth participants were more likely to report getting care at home (65.9% vs 43.5%; odds ratio [OR] 2.48, 95% CI 1.57-3.89; P<.001) and having a medication abortion (62.1% vs 51.1%; OR 1.58, 95% CI 1.11-2.23; P=.01) as extremely important. They were less likely to report having an in-person meeting with a clinician (16.1% vs 45.7%; OR 0.23, 95% CI 0.19-0.26; P<.001) and ultrasonography (15.2% vs 38.2%; OR 0.28, 95% CI 0.20-0.40; P<.001) as extremely important. Abortion care features rated as extremely important were sometimes discordant with the care received. Almost all participants had access to the technologies required for telehealth. While telehealth abortion services offer many features that people find important, the availability of both telehealth and in-person abortion care remains critical to ensuring that care aligns with patient preferences. In addition to efforts focused on expanding access to telehealth medication abortion services, advocates and policymakers should continue their work to ensure access to in-person care for those who need or prefer this model.

The increased integration of telehealth services into health care systems, especially during the COVID-19 pandemic, transformed patient-provider interactions. Despite numerous benefits that promote health equity and resource allocation, patients' acceptance and use of telehealth have declined post pandemic. To enhance health care delivery and patient satisfaction, we study the factors of this decline from the perspective of patient characteristics that influence the adoption and use of telehealth services. This study examines the direct impact of patient trust, social determinants of health, and health self-efficacy on telehealth usage, the indirect effect of confidence in health information seeking, patient-centered communication, and health literacy barriers on telehealth usage through trust. This paper uses secondary data from cycle 6 of the Health Information National Trends Survey, a nationally representative dataset collected by the National Cancer Institute. This dataset used a mixed-mode experimental design, with data collected between March and November 2022. The survey included 2 experimental conditions: concurrent (web and paper surveys offered simultaneously) and sequential (web survey offered first, followed by paper). A total of 6252 respondents participated, with a household response rate of 28.1% (6252/22,471). Respondents were randomly assigned to 1 of 3 web-based survey groups to address data quality issues such as speeding and straight lining. We use structural equation modeling to test our research questions, evaluating both direct and indirect pathways influencing telehealth usage. Common method bias is addressed through Harman's single-factor test, and robustness checks ensure the validity and reliability of our results. Out of 5554 participants who had at least 1 doctor visit within the past 12 months, 44.89% used telehealth services in the past year. Trust has an inverted U-shaped relationship with confidence in health information seeking (β=-.031; P=.002); we find trust positively influenced by patient-centered communication (β=.156; P<.001) and negatively affected by health literacy barriers (β=-.063; P<.001). Trust enhances telehealth usage (β=.025; P<.001), with social determinants of health exerting a positive impact (β=.105; P<.001) and health self-efficacy having a negative impact (β=-.019; P=.007). This study finds that trust, social determinants of health, and health self-efficacy directly impact telehealth usage. Additionally, telehealth usage is indirectly influenced by patient characteristics, such as confidence in health information seeking and health literacy barriers, as well as by a patient-centered communication environment. The findings emphasize the need for targeted interventions to improve patient health literacy and engagement, thereby promoting the telehealth services usage.

Social determinants of health strongly influence clinical outcomes. Social needs are the individual-level, actionable facets of the broader social determinants of health framework, including food security, stable housing, and access to essential services. When these needs go unmet, they adversely affect well-being and quality of care. Systematically detecting social needs is therefore critical, and emerging digital tools now offer efficient, scalable approaches for screening and identification. This scoping review aimed to examine the use of digital health technology (DHT) or DHT-based interventions documented for screening and identifying unmet social needs in populations with high needs. We explore trends, effects, challenges, and limitations associated with these technologies. Following PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we searched databases including MEDLINE, Embase, Scopus, ACM Digital Library, and Web of Science for studies published from 2010 to 2025. Eligible studies used technology to screen for and identify unmet social needs in populations with health and socioeconomic challenges. Data extraction focused on the types of technology, screening processes, and social needs identified. Our findings highlight a limited yet evolving landscape of technological applications. We identified 14 studies using tools such as self-assessment surveys, tablet-based systems, and electronic portals. These tools were applied across diverse groups, such as refugees and patients in emergency departments. Innovative approaches, such as chatbots and multidimensional risk appraisal systems for older adults, showed potential. However, challenges included single-site studies, small samples, and integration issues with medical records. The effectiveness of these tools in screening for unmet social needs shows mixed outcomes. DHTs play a pivotal role in improving the identification of unmet social needs. The findings underscore the need for broader, more integrated research to fully understand the impact of technology-based assessments and screening processes for social needs. Future efforts should focus on facilitated screening using technology both within and outside of the visit, ensuring the linkage to appropriate resources and care.

Text mining of mental health-related posts from Singapore-based Reddit communities uncovered 10 themes, with loneliness, access to affordable mental health care, and education challenges emerging as the most prevalent, alongside rising discussions on social isolation and emotional struggles, as well as access to mental health support and services.

Assessing Circumstances and Offering Resources for Needs (ACORN) is a US Department of Veterans Affairs (VA) clinical intervention designed to identify and address social needs to improve health and well-being among all veterans. We co-designed the ACORN Dashboard to facilitate access to real-time social needs and intervention data for VA clinical care teams and leadership. This study aimed to (1) describe the iterative development of the ACORN Dashboard, (2) assess end user feedback and Dashboard usage, and (3) discuss the role of social needs dashboards in facilitating continuous quality improvement in health care settings. An interprofessional team of subject-matter experts and end user feedback contributed to the design. Phase 1 included more than 7 months of weekly working meetings. We initially constructed a wireframe in Microsoft PowerPoint, then translated it into a prototype in Power BI, a data visualization software. Using Microsoft Power BI, we built data visualizations to communicate population-level sociodemographic and ACORN screening data. Through feedback sessions, staff from 8 VA medical centers (VAMCs) reviewed the prototype and recommended improvements regarding the Dashboard's purpose, content, and usability. Phase 2 involved 6 weeks of weekly working meetings, where we developed and iteratively refined 5 written drafts of clinically relevant variables for potential inclusion in the Patient-Level Data Page. This list informed a Power BI prototype. We also developed the ACORN Implementation Map page in Power BI to display implementation locations and settings. We again used feedback sessions with 8 VAMCs to review and refine the newly added pages and discuss improvements. To assess usage, we obtained metadata from a VA-specific Power BI report and user experience data from an ACORN VAMC survey. The ACORN Dashboard displays national data that are updated daily, reflecting 83,546 screens administered across 82 VAMCs facilities between July 1, 2021, and April 30, 2025. The Dashboard was viewed 18,192 times by 2251 unique users, and, on average, 263 (SD 91.2) unique users viewed the Dashboard every month between October 1, 2023, and April 30, 2025. Dashboard variables include the number of screens completed, sociodemographic characteristics of veterans screened, prevalence of social needs, and interventions provided to address needs. Phase 1 semistructured feedback sessions included recommendations for a page with patient-level data to supplement the population-level pages, incorporation of additional filters to select specific data, and development of a user guide. In phase 2, key insights included enhancement of end users' ability to search by veteran or staff name, guidance about screening frequency, changing the display order of variables, and the inclusion of variable definitions. Using co-design to develop, maintain, and continually refine data dashboards enhances implementation of social screening and interventions in health care settings. In addition to supporting individual-level patient care, population-level dashboard data inform continuous quality improvement, promote health equity, and identify gaps in services to address identified needs.

Patients' access to their electronic health record (EHR) supports their participation and satisfaction with care. Despite the benefits, some patients have been upset after reading their EHR. Additionally, health care professionals are concerned that patients, particularly those with mental health conditions, may be offended, and they have expressed a need for further guidelines on how to write EHRs. Experiences among various patient groups are essential to support the relationship between patients and professionals. However, prior studies have often focused on single patient groups or specific clinical contexts, leaving a limited understanding of differences across multiple patient groups. This study aimed to determine whether certain patient groups are more likely to feel offended while reading their EHRs and which information is perceived as offensive and to provide a comparison across multiple patient groups using a mixed methods approach. A cross-sectional survey was conducted via the Finnish national patient portal using a web-based patient survey, adopting a mixed methods approach. The survey included multiple-choice and open-ended questions. The total sample comprised 4681 respondents. The survey respondents were placed into 4 patient groups: those who had received care for mental health, cancer, or other conditions and those who had received no care. Associations between the type of care and patients who felt offended were estimated using multivariate binary logistic regression. Inductive content analysis (n=502) was conducted to identify information perceived as offensive in the EHR. The patients who had received mental health care (166/654, 25.4%) or cancer and mental health care (9/39, 23.1%) were more likely to be offended by information in their EHR compared to the other groups (cancer care: 37/375, 9.9%; other conditions care: 383/3316, 11.6%; no care: 22/206, 10.7%; other conditions care: odds ratio 0.37, 95% CI 0.29-0.46; P<.001; model A). Additionally, female patients, those with bad or very bad health conditions, and patients with bachelor's or master's degrees were significantly more likely to feel offended. Errors, the health care professionals' disrespectful language, and perceived unnecessary information were the most frequently mentioned reasons for being offended. Patients with mental health care reported more often that unnecessary information and professionals' opinions and word choices were experienced as offensive compared to other patients. This study contributes new knowledge by identifying differences across multiple patient groups. Although a minority of patients felt offended by their EHR, health care professionals should consider that some patients, particularly those who have received mental health care or cancer and mental health care, may be offended by specific information or word choices in their EHRs. To address this, health care professionals should receive education on how to write their notes in a neutral tone and avoid potentially offensive topics. Improving the quality of EHRs could strengthen the relationship between patients and professionals.

Digital health literacy (DHL) has the potential to improve health among older adults by enhancing access to health-related information and health care services. The aim of this study was to analyze the relationship between DHL and technology commitment in adults aged 65 years and older, while also investigating possible gender differences. The analytical sample consisted of 1824 individuals. The analysis included descriptive comparisons in terms of DHL, technology acceptance, competency, support, and internet use. Multivariate regression models (generalized linear models) were applied in order to test the association between DHL and technology commitment, controlling for internet use as well as health-related and sociodemographic characteristics. Male and female participants did not differ in terms of DHL (mean score: 3.5, SD 1.2 [men] and 3.5, SD 1.3 [women]; P=.70); however, male participants reported significantly higher technology acceptance (P<.001) and higher technology competencies (P<.001), but less support with regard to technology use (P<.001). Within regression models, only higher technology acceptance (coefficient=0.023, 95% CI 0.006-0.041; P=.01) and support (coefficient=0.027, 95% CI 0.014-0.040; P<.001) were significantly linked to greater DHL. The subgroup analysis revealed that DHL was significantly associated with technology acceptance among men (coefficient=0.036, 95% CI 0.012-0.060; P=.003) but not women (coefficient=0.024, 95% CI 0.008-0.040; P=.44). According to the current results, DHL is highly related to technology commitment. Gender differences should be taken into account when developing and evaluating appropriate interventions to improve DHL by addressing the acceptance of technologies and optimizing support infrastructures.

Online text-based counseling services are becoming increasingly popular. However, their text-based nature and anonymity pose challenges in tracking and understanding shifts in help-seekers' emotional experience within a session. These characteristics make it difficult for service providers to tailor interventions to individual needs, potentially diminishing service effectiveness and user satisfaction. This study aimed to identify distinct within-session sentiment trajectories among help-seekers in online text-based counseling and examine key variables associated with trajectory membership. A total of 6207 counseling sessions were randomly extracted from an online text-based counseling service in Hong Kong. A latent class trajectory analysis of help-seekers' in-session sentiment was conducted using a growth mixture model (GMM) to identify latent groups of help-seekers exhibiting specific sentiment trajectories. Sentiment scores of help-seeker messages, labeled by ChatGPT, served as the primary variable for trajectory modeling. Subsequently, a multinomial logistic regression was performed to identify variables associated with class membership. The GMM identified 3 distinct sentiment trajectories as the best fit: (1) steady improvement (1171/6207, 18.9%), (2) deterioration (1119/6207, 18.0%), and (3) dip-then-rebound (3917/6207, 63.1%). Compared with the Dip-Then-Rebound Class, help-seekers in the Deterioration Class were more likely to report suicidal ideation (OR=1.28, 95% CIs 1.07-1.52, P=.006), present with family (OR=1.56, 95% CIs 1.19-2.08, P=.002) or physical health-related concerns (OR=1.67, 95% CIs 1.02-2.74, P=.04), have an unknown gender status (OR=1.32, 95% CIs 1.04-1.67, P=.02), access the service through the anonymous channel (OR=1.30, 95% CIs 1.03-1.63, P=.03), depart from the session prematurely (OR=9.76, 95% CIs 8.33-11.36, P<.001), and have shorter session durations (OR=0.77, 95% CIs 0.71-0.84, P<.001). We identified 3 distinct trajectories of help-seekers' in-session sentiment. Identifying the most likely trajectory at an early stage in the session could potentially help counselors adjust their approaches, thereby improving the effectiveness of text-based counseling and enhancing help-seeker satisfaction.

Patient portals can improve care delivery and the efficient use of health care resources. Barriers to uptake can hinder the realization of expected benefits for health services and patients, particularly for older adults (≥65 y) and those who are culturally and linguistically diverse (CALD). This study aimed to evaluate the usability and overall patient experience of a patient portal, particularly for CALD and older adults. A mixed methods study at a dental hospital was performed including a patient experience survey that was administered before (2111 patients) and after (2445 patients) portal implementation to all patients, semistructured interviews (18 patients), and a usability survey (235 patients) that was administered to all patients who had registered to use the portal and had an appointment at the clinic. Also, we conducted a scenario-based usability evaluation (17 patients) with CALD and people. The patient experience survey revealed that the portal had no impact on the ease of changing appointments when the clinic with the portal (Wilcoxon z=-1.62; P=.05) was compared with clinics without the portal in the same hospital (z=-1.54; P=.06). For the usability survey, >82% were completed by patients and 18% by carers, and 47.3% of respondents were older adults (≥65 years old). The majority spoke English (n=191, 81.3%), while others preferred to speak other languages (n=44, 18.7%) and were identified as CALD. Adult participants (18-64 years old) reported that the portal was easy to use and simple. However, design problems, including inadequate incorporation of inclusivity, were found to more often limit usability for older (≥65) and CALD people. The overall Simplified System Usability Scale (SUS) mean score was 63.3 (95% CI 60.9-65.7). Adult participants reflected higher SUS scores than older participants (F=10.4; P=.001). Interview results revealed how the portal was used and barriers to its uptake. Barriers related to poor usability and gaps in the implementation approach (eg, limited awareness of the purpose of the portal). Usability evaluations indicated that all participants could log in with the one-time password (OTP), but most were assisted. Only 3 of 17 participants were able to send a message to the clinic. Other usability problems identified were focused on display, content, layout, functionality, and navigation categories. The use of inclusive design principles when designing patient portals is necessary for successfully engaging all patients. Our study highlights the importance of normalizing inclusive designs in patient portals to ensure that priority populations, such as older and CALD people, are not marginalized by design. We provide recommendations to guide future design and implementation of patient portals.

Despite improvements in early cancer diagnosis worldwide, morbidity and mortality in Southern Africa continue to rise owing to challenges with funding, sociocultural beliefs, and health care access. Digital health (\"eHealth\") has the potential to expand access to health care, particularly to remote communities. However, few studies explored the use of eHealth to support symptomatic cancer diagnosis in Southern Africa. This study explored the barriers and facilitators to eHealth use by health care workers (HCWs) to support the management of people with symptoms of possible breast, cervical, or colorectal cancer in South Africa and Zimbabwe. We conducted semistructured in-depth interviews with HCWs (n=56) who managed people with symptoms of possible cancer. Interviews explored the barriers and facilitators to eHealth use and attitudes toward further adoption of eHealth. Interview schedules were guided by the sociotechnical theory, a model \"designed to address the socio-technical challenges involved in design, development, implementation, use, and evaluation of eHealth.\" The interviews were audio-recorded and transcribed. We used the framework method to analyze the data and developed themes that encompassed patterns and meaning in the data to answer the research question. The median age of participants was 44 (IQR 34-53) years, 38 (68%) were female, and most were nurses (n=34, 61%) or doctors (n=18, 32%). Four core themes were developed: (1) \"the lack of reliable infrastructure hindered eHealth use among HCWs\"; (2) \"the use of personal mobile devices increased eHealth access at the expense of patient privacy and personal cost\"; (3) \"information, workflow integration, and access\"; while eHealth improved access to information, many tools were already in use, were poorly integrated into workflow, and disrupted consultations; and (4) \"digital health is expanding whether we like it or not,\" which describes a spectrum of attitudes toward digital health, ranging from enthusiasm to resistance but willingness to adapt to those completely against its use. Themes from the workshops were concordant with the in-depth interview findings. To capitalize on the potential benefits of eHealth use among HCWs, such as to support early cancer diagnosis, infrastructural challenges must be addressed, and tools designed to meet user needs and be integrated into clinical workflow. As in many other resource-constrained settings, significant improvements in development are required for the value of eHealth to be realized in Southern Africa. Additionally, where resources such as electricity are limited, their use for eHealth needs to be weighed against use for other priorities such as operating ventilators. Furthermore, energy production in these regions is largely reliant on burning fossil fuels, and thus, the use of eHealth tools risks contributing negatively to climate change. The findings of this study can be used to guide future eHealth design or implementation strategies that are more contextually suitable.