The majority of Black women with hypertension in the United States have smartphones or tablets and use social media, and many use wearable activity trackers and health or wellness apps, digital tools that can be used to support lifestyle changes and medication adherence.

BACKGROUND: SMS text messages through mobile phones are a common means of interpersonal communication. SMS text message surveys are gaining traction in health care and research due to their feasibility and patient acceptability. However, challenges arise in implementing SMS text message surveys, especially when targeting marginalized populations, because of barriers to accessing phones and data as well as communication difficulties. In primary care, traditional surveys (paper-based and online) often face low response rates that are particularly pronounced among disadvantaged groups due to financial limitations, language barriers, and time constraints.
OBJECTIVE: This study aimed to investigate the potential of SMS text message-based patient recruitment and surveys within general practices situated in lower socioeconomic areas. This study was nested within the Reducing Alcohol-Harm in General Practice project that aimed to reduce alcohol-related harm through screening in Australian general practice.
METHODS: This study follows a 2-step SMS text message data collection process. An initial SMS text message with an online survey link was sent to patients, followed by subsequent surveys every 3 months for consenting participants. Interviews were conducted with the local primary health network organization staff, the participating practice staff, and the clinicians. The qualitative data were analyzed using constructs from the Consolidated Framework for Implementation Research.
RESULTS: Out of 6 general practices, 4 were able to send SMS text messages to their patients. The initial SMS text message was sent to 8333 patients and 702 responses (8.2%) were received, most of which were not from a low-income group. This low initial response was in contrast to the improved response rate to the ongoing 3-month SMS text message surveys (55/107, 51.4% at 3 months; 29/67, 43.3% at 6 months; and 44/102, 43.1% at 9 months). We interviewed 4 general practitioners, 4 nurses, and 4 administrative staff from 5 of the different practices. Qualitative data uncovered barriers to engaging marginalized groups including limited smartphone access, limited financial capacity (telephone, internet, and Wi-Fi credit), language barriers, literacy issues, mental health conditions, and physical limitations such as manual dexterity and vision issues. Practice managers and clinicians suggested strategies to overcome these barriers, including using paper-based surveys in trusted spaces, offering assistance during survey completion, and offering honoraria to support participation.
CONCLUSIONS: While SMS text message surveys for primary care research may be useful for the broader population, additional efforts are required to ensure the representation and involvement of marginalized groups. More intensive methods such as in-person data collection may be more appropriate to capture the voice of low-income groups in primary care research.
UNASSIGNED: RR2-10.3399/BJGPO.2021.0037.

BACKGROUND: The COVID-19 pandemic prompted various containment strategies, such as work-from-home policies and reduced social contact, which significantly altered people\'s sleep routines. While previous studies have highlighted the negative impacts of these restrictions on sleep, they often lack a comprehensive perspective that considers other factors, such as seasonal variations and physical activity (PA), which can also influence sleep.
OBJECTIVE: This study aims to longitudinally examine the detailed changes in sleep patterns among working adults during the COVID-19 pandemic using a combination of repeated questionnaires and high-resolution passive measurements from wearable sensors. We investigate the association between sleep and 5 sets of variables: (1) demographics; (2) sleep-related habits; (3) PA behaviors; and external factors, including (4) pandemic-specific constraints and (5) seasonal variations during the study period.
METHODS: We recruited working adults in Finland for a 1-year study (June 2021-June 2022) conducted during the late stage of the COVID-19 pandemic. We collected multisensor data from fitness trackers worn by participants, as well as work and sleep-related measures through monthly questionnaires. Additionally, we used the Stringency Index for Finland at various points in time to estimate the degree of pandemic-related lockdown restrictions during the study period. We applied linear mixed models to examine changes in sleep patterns during this late stage of the pandemic and their association with the 5 sets of variables.
RESULTS: The sleep patterns of 27,350 nights from 112 working adults were analyzed. Stricter pandemic measures were associated with an increase in total sleep time (TST) (β=.003, 95% CI 0.001-0.005; P<.001) and a delay in midsleep (MS) (β=.02, 95% CI 0.02-0.03; P<.001). Individuals who tend to snooze exhibited greater variability in both TST (β=.15, 95% CI 0.05-0.27; P=.006) and MS (β=.17, 95% CI 0.03-0.31; P=.01). Occupational differences in sleep pattern were observed, with service staff experiencing longer TST (β=.37, 95% CI 0.14-0.61; P=.004) and lower variability in TST (β=-.15, 95% CI -0.27 to -0.05; P<.001). Engaging in PA later in the day was associated with longer TST (β=.03, 95% CI 0.02-0.04; P<.001) and less variability in TST (β=-.01, 95% CI -0.02 to 0.00; P=.02). Higher intradaily variability in rest activity rhythm was associated with shorter TST (β=-.26, 95% CI -0.29 to -0.23; P<.001), earlier MS (β=-.29, 95% CI -0.33 to -0.26; P<.001), and reduced variability in TST (β=-.16, 95% CI -0.23 to -0.09; P<.001).
CONCLUSIONS: Our study provided a comprehensive view of the factors affecting sleep patterns during the late stage of the pandemic. As we navigate the future of work after the pandemic, understanding how work arrangements, lifestyle choices, and sleep quality interact will be crucial for optimizing well-being and performance in the workforce.

BACKGROUND: For many young people, the transition from child to adult mental health services is a vulnerable time associated with treatment disengagement and illness progression. Providing service information and options to youth, appealing to them, and tailoring to their needs during this period could help overcome systematic barriers to a successful transition. We know little about how SMS text message-based interventions might be leveraged to support the motivational, informational, and behavioral needs of youth during this time. Ascertaining youth preferences for the content and functionality of an SMS text message service could inform prototype development.
OBJECTIVE: This study investigated consensus preferences among youth on important content, technology features, and engagement supports to inform a transition-focused SMS text message service.
METHODS: A modified e-Delphi survey design was used to collect demographics, current levels of technology use, importance ratings on message content, preferred technical features, and barriers and enablers to engagement for youth in Canada aged 16-26 years who have accessed mental health services within the past 5 years. Survey items on content were categorized according to the information-motivation-behavioral skills (IMB) model. Survey items on technical features were categorized according to the persuasive system design (PSD) model. A predefined consensus rating matrix and descriptive statistics were used to characterize the sample. The high consensus threshold was 70%.
RESULTS: A total of 100 participants, predominantly non-White (n=47, 47%), aged 20-26 years (n=59, 59%), and who had first accessed mental health services between the ages of 13 and 19 years (n=60, 60%), were selected. The majority (n=90, 90%) identified as daily SMS text message users. A high level of consensus on importance ratings was reported in 45% (9/20) of content items based on the IMB model. There were higher levels of consensus on importance ratings related to behavior domain items (3/3, 100%) than information domain items (4/9, 44%) or motivation domain items (2/8, 25%). A high level of consensus on importance ratings was reported in only 19% (4/21) of feature and functionality items based on the PSD model. Among PSD model categories, there was a high level of consensus on importance ratings in 8% (1/12) of the primary task support domain items and 100% (3/3) of the system credibility support domain items. None of the dialogue-support and social-support domain items met the high level of consensus thresholds. In total, 27% (27/100) of youth indicated that the most significant enabler for engaging with a transition-focused SMS text message intervention was the personalization of text messages.
CONCLUSIONS: Scientists developing next-generation SMS text messaging interventions for this population need to consider how levels of consensus on different features may impact feasibility and personalization efforts. Youth can (and should) play an integral role in the development of these interventions.

BACKGROUND: Leveraging electronic health record (EHR) data for clinical or research purposes heavily depends on data fitness. However, there is a lack of standardized frameworks to evaluate EHR data suitability, leading to inconsistent quality in data use projects (DUPs). This research focuses on the Medical Informatics for Research and Care in University Medicine (MIRACUM) Data Integration Centers (DICs) and examines empirical practices on assessing and automating the fitness-for-purpose of clinical data in German DIC settings.
OBJECTIVE: The study aims (1) to capture and discuss how MIRACUM DICs evaluate and enhance the fitness-for-purpose of observational health care data and examine the alignment with existing recommendations and (2) to identify the requirements for designing and implementing a computer-assisted solution to evaluate EHR data fitness within MIRACUM DICs.
METHODS: A qualitative approach was followed using an open-ended survey across DICs of 10 German university hospitals affiliated with MIRACUM. Data were analyzed using thematic analysis following an inductive qualitative method.
RESULTS: All 10 MIRACUM DICs participated, with 17 participants revealing various approaches to assessing data fitness, including the 4-eyes principle and data consistency checks such as cross-system data value comparison. Common practices included a DUP-related feedback loop on data fitness and using self-designed dashboards for monitoring. Most experts had a computer science background and a master\'s degree, suggesting strong technological proficiency but potentially lacking clinical or statistical expertise. Nine key requirements for a computer-assisted solution were identified, including flexibility, understandability, extendibility, and practicability. Participants used heterogeneous data repositories for evaluating data quality criteria and practical strategies to communicate with research and clinical teams.
CONCLUSIONS: The study identifies gaps between current practices in MIRACUM DICs and existing recommendations, offering insights into the complexities of assessing and reporting clinical data fitness. Additionally, a tripartite modular framework for fitness-for-purpose assessment was introduced to streamline the forthcoming implementation. It provides valuable input for developing and integrating an automated solution across multiple locations. This may include statistical comparisons to advanced machine learning algorithms for operationalizing frameworks such as the 3×3 data quality assessment framework. These findings provide foundational evidence for future design and implementation studies to enhance data quality assessments for specific DUPs in observational health care settings.

BACKGROUND: OpenAI\'s ChatGPT is a source of advanced online health information (OHI) that may be integrated into individuals\' health information-seeking routines. However, concerns have been raised about its factual accuracy and impact on health outcomes. To forecast implications for medical practice and public health, more information is needed on who uses the tool, how often, and for what.
OBJECTIVE: This study aims to characterize the reasons for and types of ChatGPT OHI use and describe the users most likely to engage with the platform.
METHODS: In this cross-sectional survey, patients received invitations to participate via the ResearchMatch platform, a nonprofit affiliate of the National Institutes of Health. A web-based survey measured demographic characteristics, use of ChatGPT and other sources of OHI, experience characterization, and resultant health behaviors. Descriptive statistics were used to summarize the data. Both 2-tailed t tests and Pearson chi-square tests were used to compare users of ChatGPT OHI to nonusers.
RESULTS: Of 2406 respondents, 21.5% (n=517) respondents reported using ChatGPT for OHI. ChatGPT users were younger than nonusers (32.8 vs 39.1 years, P<.001) with lower advanced degree attainment (BA or higher; 49.9% vs 67%, P<.001) and greater use of transient health care (ED and urgent care; P<.001). ChatGPT users were more avid consumers of general non-ChatGPT OHI (percentage of weekly or greater OHI seeking frequency in past 6 months, 28.2% vs 22.8%, P<.001). Around 39.3% (n=206) respondents endorsed using the platform for OHI 2-3 times weekly or more, and most sought the tool to determine if a consultation was required (47.4%, n=245) or to explore alternative treatment (46.2%, n=239). Use characterization was favorable as many believed ChatGPT to be just as or more useful than other OHIs (87.7%, n=429) and their doctor (81%, n=407). About one-third of respondents requested a referral (35.6%, n=184) or changed medications (31%, n=160) based on the information received from ChatGPT. As many users reported skepticism regarding the ChatGPT output (67.9%, n=336), most turned to their physicians (67.5%, n=349).
CONCLUSIONS: This study underscores the significant role of AI-generated OHI in shaping health-seeking behaviors and the potential evolution of patient-provider interactions. Given the proclivity of these users to enact health behavior changes based on AI-generated content, there is an opportunity for physicians to guide ChatGPT OHI users on an informed and examined use of the technology.

Noise barriers are path interventions between noise sources and human receivers used mainly along road corridors to improve the acoustic environment for affected residents. Despite their widespread use, the impact of these interventions on community perception is still insufficiently investigated. This paper presents findings from a longitudinal study evaluating the efficacy of noise barriers in three residential areas alongside highways, compared to a reference case in a relatively quiet area. Noise exposure was objectively quantified via acoustic measurements and noise modelling, while socio-acoustic surveys measured the residents\' subjective response in terms of noise annoyance as well as other aspects of quality of life. While noise exposure (Lday) decreased on average by 4.4-11.7 dBA at near-barrier points, direct reductions in pre to post-intervention noise annoyance were observed only in one case. Additionally, only in this particular case were the appraisals of the acoustic environment restored to a condition similar to low-level noise emissions (reference case). Contextual factors potentially downgrading the interventions\' effectiveness are discussed, such as the history of complaints and coping, mistrust towards road authorities, high expectations, and the impacts of the COVID-19 pandemic. While noise exposure reductions did not directly lead to noise annoyance decreases, an ordinal regression pooling all cases revealed that larger reductions in noise exposure were associated with a higher likelihood of residents reporting decreased traffic noise annoyance in the post-survey. No evidence was found regarding noise barriers\' impact on the subjective assessment of other aspects of quality of life, such as health complaints, concentration disturbance, and sleep quality.

UNASSIGNED: Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality in the developed world. Timely detection of cardiac arrest and prompt activation of emergency medical services (EMS) are essential, yet challenging. Automated cardiac arrest detection using sensor signals from smartwatches has the potential to shorten the interval between cardiac arrest and activation of EMS, thereby increasing the likelihood of survival.
UNASSIGNED: This cross-sectional survey study aims to investigate users\' perspectives on aspects of continuous monitoring such as privacy and data protection, as well as other implications, and to collect insights into their attitudes toward the technology.
UNASSIGNED: We conducted a cross-sectional web-based survey in the Netherlands among 2 groups of potential users of automated cardiac arrest technology: consumers who already own a smartwatch and patients at risk of cardiac arrest. Surveys primarily consisted of closed-ended questions with some additional open-ended questions to provide supplementary insight. The quantitative data were analyzed descriptively, and a content analysis of the open-ended questions was conducted.
UNASSIGNED: In the consumer group (n=1005), 90.2% (n=906; 95% CI 88.1%-91.9%) of participants expressed an interest in the technology, and 89% (n=1196; 95% CI 87.3%-90.7%) of the patient group (n=1344) showed interest. More than 75% (consumer group: n= 756; patient group: n=1004) of the participants in both groups indicated they were willing to use the technology. The main concerns raised by participants regarding the technology included privacy, data protection, reliability, and accessibility.
UNASSIGNED: The vast majority of potential users expressed a strong interest in and positive attitude toward automated cardiac arrest detection using smartwatch technology. However, a number of concerns were identified, which should be addressed in the development and implementation process to optimize acceptance and effectiveness of the technology.

UNASSIGNED: To assess the utility of wearable cameras in medical examinations, we created a physician-view video-based examination question and explanation, and the survey results indicated that these cameras can enhance the evaluation and educational capabilities of medical examinations.

UNASSIGNED: Indonesia has rapidly embraced digital health, particularly during the COVID-19 pandemic, with over 15 million daily health application users. To advance its digital health vision, the government is prioritizing the development of health data and application systems into an integrated health care technology ecosystem. This initiative involves all levels of health care, from primary to tertiary, across all provinces. In particular, it aims to enhance primary health care services (as the main interface with the general population) and contribute to Indonesia\'s digital health transformation.
UNASSIGNED: This study assesses the information and communication technology (ICT) maturity in Indonesian health care services to advance digital health initiatives. ICT maturity assessment tools, specifically designed for middle-income countries, were used to evaluate digital health capabilities in 9 provinces across 5 Indonesian islands.
UNASSIGNED: A cross-sectional survey was conducted from February to March 2022, in 9 provinces across Indonesia, representing the country\'s diverse conditions on its major islands. Respondents included staff from public health centers (Puskesmas), primary care clinics (Klinik Pratama), and district health offices (Dinas Kesehatan Kabupaten/Kota). The survey used adapted ICT maturity assessment questionnaires, covering human resources, software and system, hardware, and infrastructure. It was administered electronically and involved 121 public health centers, 49 primary care clinics, and 67 IT staff from district health offices. Focus group discussions were held to delve deeper into the assessment results and gain more descriptive insights.
UNASSIGNED: In this study, 237 participants represented 3 distinct categories: 121 public health centers, 67 district health offices, and 49 primary clinics. These instances were selected from a sample of 9 of the 34 provinces in Indonesia. Collected data from interviews and focus group discussions were transformed into scores on a scale of 1 to 5, with 1 indicating low ICT readiness and 5 indicating high ICT readiness. On average, the breakdown of ICT maturity scores was as follows: 2.71 for human resources\' capability in ICT use and system management, 2.83 for software and information systems, 2.59 for hardware, and 2.84 for infrastructure, resulting in an overall average score of 2.74. According to the ICT maturity level pyramid, the ICT maturity of health care providers in Indonesia fell between the basic and good levels. The need to pursue best practices also emerged strongly. Further analysis of the ICT maturity scores, when examined by province, revealed regional variations.
UNASSIGNED: The maturity of ICT use is influenced by several critical components. Enhancing human resources, ensuring infrastructure, the availability of supportive hardware, and optimizing information systems are imperative to attain ICT maturity in health care services. In the context of ICT maturity assessment, significant score variations were observed across health care levels in the 9 provinces, underscoring the diversity in ICT readiness and the need for regionally customized follow-up actions.