Background Screening for cognitive impairment in primary care is important, yet primary care physicians (PCPs) report conducting routine cognitive assessments for less than half of patients older than 60 years of age. Linus Health’s Core Cognitive Evaluation (CCE), a tablet-based digital cognitive assessment, has been used for the detection of cognitive impairment, but its application in primary care is not yet studied. Objective This study aimed to explore the integration of CCE implementation in a primary care setting. Methods A cohort of participants was recruited from the upcoming schedules of participating PCPs at UMass Memorial Medical Center. Eligibility criteria included individuals aged ≥65 years; ability to read, write, and speak in English or Spanish; no previous diagnosis of cognitive impairment; and no known untreated hearing or vision impairment. Research coordinators collected consent from participants and facilitated the screening process. PCPs reviewed reports in real time, immediately before the scheduled visits, and shared results at their discretion. A report was uploaded to each participant’s REDCap (Research Electronic Data Capture; Vanderbilt University) record and linked to the encounter in the electronic health record. Feedback from patients and their caregivers (if applicable) was collected by a tablet-based survey in the clinic before and after screening. Participating PCPs were interviewed following the completion of the study. Results The screened cohort included 150 patients with a mean age of 74 (SD 7) years, of whom 65% (97/150) were female. The CCE identified 40 patients as borderline and 7 as positive for cognitive impairment. A total of 84 orders were placed for select laboratory tests or referrals to neurology and neuropsychology within 20 days of CCE administration. Before the assessment, 95% (143/150) of patients and all 15 caregivers expressed a desire to know if their or their loved one’s brain health was declining. All except one patient also completed the postassessment survey. Among them, 96% (143/149) of patients reported finding the CCE easy to complete, and 70% (105/149) felt that the experience was beneficial. In addition, 87% (130/149) of patients agreed or strongly agreed that they wanted to know their CCE results. Among the 7 participating PCPs, 6 stated that the CCE results influenced their patient care management, and all 7 indicated they would continue using the CCE if it were made available after the study. Conclusions We explored the integration of the CCE into primary care visits, which showed minimal disruption to the practice workflow. Future studies will be warranted to further validate the implementation of digital cognitive impairment screening tools within primary care settings in the real world.

In the postpandemic era, telemedicine continues to enable mental health care access for many people, especially persons living in areas with mental health care provider shortages. However, as lawmakers consider long-term telemedicine policy decisions, some question the safety and appropriateness of prescribing via telemedicine, and whether there should be requirements for in-person evaluation, especially for controlled substances. Our objective was to assess US telemental health care provider perceptions of comfort and perceived safety in prescribing medications, including controlled substances, via telemedicine. We conducted a web-based, cross-sectional survey of US telemental health care providers who prescribe via telemedicine, using nonprobability, availability sampling of a national telehealth research panel from February 13 to April 28, 2024. We used descriptive statistics, visualization, and thematic analysis to analyze results. We assessed differences in response distribution by health care provider licensure type (physician vs nonphysician) and specialty (psychiatry vs nonpsychiatry) using the Mann-Whitney U test. A total of 115 screened and eligible panelists completed the survey. Overall, participants indicated high levels of comfort with prescribing via telemedicine, with 84% (102/115) of health care providers indicating they strongly agree with the statement indicating comfort in prescribing medications via telemedicine. However, participants indicated less comfort in prescribing if they have never seen a patient in person, or if the patient is located out-of-state. Most participants indicated they can safely prescribe controlled substances via telemedicine, without having previously provided care to a patient in person. However, 14.8% (17/115) to 19.1% (30/115) of health care providers (by schedule) felt that they could rarely or never safely prescribe controlled substances. There were some differences in perception of comfort and safety by licensure and specialty. Among controlled substance schedules, participants indicated the least perceived safety with schedule IV medications, and the most safety with schedule II and III medications. These health care providers were highly comfortable prescribing both scheduled and unscheduled medications via telemedicine. Comfort and perceived safety with telemedicine prescribing varied somewhat by licensure type (physician vs nonphysician) and specialty (psychiatry vs nonpsychiatry). Perceived safety varied moderately for scheduled medications (controlled substances), especially for schedule IV and V medications. Participants indicated use of adaptive strategies to prescribe safely depending upon the clinical context. In ongoing efforts, we are analyzing additional survey results and conducting qualitative research related to telemedicine prescribing. A strong understanding of prescriber perspectives and experience with telemedicine prescribing is needed to support excellent clinical practice and effective policy making in the United States.

Patients with chronic pain on long-term opioid therapy often face barriers to accessing effective nonpharmacological treatments, including the burden of multiple sessions, lack of trained clinicians, and travel time. Empowered Relief (ER), a 2-hour, single-session pain relief skills class, can improve pain and quality of life among patients with chronic pain when delivered in person or virtually. This study examined the impact of Zoom-delivered ER among people with chronic pain on long-term opioid therapy. We assessed (1) the feasibility and acceptability of Zoom-delivered ER; (2) changes in pain and opioid use outcomes at 3 and 6 months after treatment; and (3) daily associations among pain, opioid dose, and the Pain Catastrophizing Scale (PCS) before and after treatment. During the early COVID-19 pandemic, we conducted an uncontrolled pilot study of a Zoom-delivered ER among 60 adults (n=45, 76% female participants; n=52, 88% White participants) experiencing chronic pain who were receiving daily prescribed opioids (≥10 morphine-equivalent daily dose). Participants completed assessments at enrollment, before class, after class, 3 months after treatment, and 6 months after treatment. Furthermore, participants completed 2 daily assessment periods (spanning 14 consecutive days) before and after the class. We used a multilevel modeling approach to examine (1) the raw changes in PCS, average pain intensity, pain interference, and self-reported opioid dose at 3 and 6 months after treatment and (2) daily-level changes in average pain intensity and opioid dose before and after the class. Of the 60 participants enrolled, 41 (68%) attended the class and 24 (59% of the 41 class attendees) reported satisfaction with the Zoom-delivered class. PCS score was significantly reduced at 3 months (β=-3.49, P=.01; Cohen d=0.35) and 6 months after treatment (β=-3.61, P=.01; Cohen d=0.37), and pain intensity was significantly reduced at 3 months (β=-0.56, P=.01; Cohen d=0.39) compared to enrollment. There were no significant reductions in pain interference or opioid dose. Across daily assessments, higher daily pain catastrophizing was associated with worse daily pain (β=.42, P<.001) and higher self-reported opioid use (β=3.14, P<.001); daily pain intensity significantly reduced after the class (β=-.50, P<.001). People taking prescribed opioids as needed trended toward decreasing their daily opioid use after the class (β=-9.31, P=.02), although this result did not survive correction for multiplicity. Improvements to future Zoom-delivered ER iterations are needed to improve feasibility and acceptability among people with chronic pain and daily prescribed opioid use. Despite this, findings show a promising preliminary impact of the intervention on pain outcomes. A larger randomized controlled trial of Zoom-delivered ER among this patient population is currently under way.

Although electronic health record nursing summaries aim to provide a concise overview of patient data, they often fall short of meeting nurses' information needs, leading to underutilization. This gap arises from a lack of involvement of nurses in the design of health information technologies. The purpose of this exploratory co-design case study was to solicit insights from nurses regarding nursing summary design considerations, including key information types and the preferred design prototype. We recruited clinical nurses (N=33) from 7 inpatient units at a university hospital in the Midwestern United States using a purposive sampling method. We used images from a simulated nursing summary to generate visual card versions of the 46 information types currently included in an electronic health record vendor-generated nursing summary. Participants selected which cards to include and arranged them in their designs based on their perceived relevance of the information types to the summary and their preferred reading layout. The nurses' perceived relevance of information types to the summary was analyzed by quantifying the frequency of included cards, while the nurses' preferred reading layout was analyzed by quantifying the occurrence of closely paired cards to identify common groupings. After participants evaluated the information type cards, debriefing interviews were conducted and analyzed thematically to explore their rationales for the desired content and its arrangement. The participants demonstrated a high level of engagement in the activities. On average, all 33 participants included 61% (n=28) of the total information types (n=46). The most frequently included cards were "unit specimen" (results of the analysis of body fluid, tissue, or urine), "activity," "diet," and "hospital problems," each included by 33 participants. Participants most frequently preferred adjacency of the following pairs: "activity" and "diet" (paired by 26 participants; 79%) and "notes to physicians" and "notes to treatment team" (paired by 25 participants; 76%). Participants preferred arranging the cards to improve information accessibility, focusing on key information types. Involving nurses in the co-design process may result in more useful and usable designs, thereby reducing the time required to navigate nursing summaries. Future work should include refining and evaluating prototypes based on the designs created by the nurses.

Background Many couples undergoing fertility treatment face multiple lifestyle risk factors that lower their chances of achieving pregnancy. The MyFertiCoach (MFC) app was designed as an integrated lifestyle program featuring modules on healthy weight management, nutrition, exercise, quitting smoking, reducing alcohol and drug use, and managing stress. We hypothesized that supplementing standard care with the MFC app would improve lifestyle outcomes. Objective This study aims to assess the impact of the MFC app on changing multiple lifestyle habits in women seeking fertility treatment. The primary outcome is the change in the total risk score (TRS) at 3- and six-month follow-ups. The TRS is calculated for each individual as the sum of all risk scores per behavior (eg, vegetable/fruit/folic acid intake, smoking, and alcohol use) at 3 and 6 months. A higher TRS indicates unhealthier nutrition and lifestyle habits and a lower likelihood of achieving pregnancy. The secondary endpoints include changes in BMI, activity score, preconception dietary risk score, distress score (eg, perceived burden), smoking habits, alcohol intake, and program adherence. Methods This retrospective, observational, single-center evaluation included patients between January 1, 2022, and December 31, 2023. Subfertile female patients aged 18-43 years and their partners, who were referred to a gynecologist, were invited to participate in online lifestyle coaching via the MFC app. The gynecologist selected relevant lifestyle modules based on the results of integrated screening questionnaires. We used (hierarchical) linear mixed models (LMMs) to estimate changes in outcomes. For missing data patterns deemed missing not at random, joint modeling was applied. Statistical significance was set at P≤.05, with methods in place to maintain the same false-positive rate. Results A total of 1805 patients were invited to participate in the evaluation, with an average of 737 (40.83%) completing the screening questionnaire at baseline. For the TRS, 798 (44.21%) patients were included at baseline, of whom 517 (64.8%) involved their partner. On average, 282 of 744 (37.9%) patients submitted at least one follow-up questionnaire. Patients rated the app above average (n=137, median score of 7 on a 1-10 scale) on days 7 and 14. The TRS decreased by an average of 1.5 points (P&lt;.001) at T3 and T6 compared with baseline, a clinically meaningful improvement. All secondary outcomes showed statistically significant positive changes for patients who used a relevant lifestyle module (P&lt;.001). Most improvements were achieved by 3 months and remained significant at 6 months (P&lt;.001), except for alcohol intake (P&lt;.53). These findings were consistent across both LMMs and joint models. Conclusions Our evaluation of a mobile health app integrated into standard care demonstrates immediate and clinically meaningful improvements in key lifestyle parameters among women seeking to become pregnant. Additional scientific research is needed to identify the causal pathways leading to sustained effectiveness. To maintain and enhance these outcomes, further tailoring of patient-specific programs is essential.

Background Up to 75% of young adult cancer survivors (YACS) experience chronic insomnia, negatively affecting physical and emotional health and overall quality of life. Cognitive behavioral therapy for insomnia (CBT-I) is a gold-standard intervention to address insomnia. To improve CBT-I access and treatment adherence, screen-based digital CBT-I platforms have been developed. However, even with these digital products, widespread uptake of CBT-I remains limited, and new strategies for CBT-I delivery are warranted. Objective The objective of this study is to understand how YACS experience insomnia and how they might incorporate technology-delivered CBT-I into a daily routine and test the feasibility and acceptability of a novel screen-free voice-activated virtual assistant–delivered CBT-I prototype. Methods Eligible participants—ages 18-39, living with a history of cancer (any type, any stage), self-reporting on average less sleep than National Sleep Foundation recommendations, and English-speaking—were recruited from a major urban cancer center, 2 regional oncology clinics, and 2 cancer survivorship support groups. We conducted 4 focus groups to understand the YACS experience of insomnia, their routine use of technology at home, particularly voice-activated virtual assistants such as Amazon Alexa, and input on how CBT-I might be delivered at home through a smart speaker system. We developed a prototype device to deliver key elements of CBT-I at home along with circadian lighting and monitoring of post-bedtime device use, collected YACS user perspectives on this prototype, and then conducted a single-arm feasibility and acceptability study. Results In total, 26 YACS (6-7 participants per group) experiencing insomnia participated in focus groups to share experiences of insomnia during cancer survivorship and to provide input regarding a CBT-I prototype. Common triggers of insomnia included worry about disease management and progression, disease-related pain and other symptoms, choices regarding personal device use, and worry about the impact of poor sleep on daily functioning. In total, 12 participants completed device prototype testing, engaging with the prototype 94% of the assigned times (twice daily for 14 days; meeting predetermined feasibility cutoff of engagement ≥70% of assigned times) and rating the prototype with an overall mean score of 5.43 on the Satisfaction subscale of the Usability, Satisfaction, and Ease of Use scale (range 4.42-7; exceeding the predetermined cutoff score for acceptability of 5.0). All participants completing the study reported they would be interested in using the prototype again and would recommend it to someone else with insomnia. Conclusions YACS were highly engaged with our voice-activated virtual assistant–delivered CBT-I prototype and found it acceptable to use. Following final device development, future studies should evaluate the efficacy of this intervention among YACS. Trial Registration ClinicalTrials.gov NCT05875129; https://clinicaltrials.gov/study/NCT05875129

Rapid integration of large language models (LLMs) in health care is sparking global discussion about their potential to revolutionize health care quality and accessibility. At a time when improving health care quality and access remains a critical concern for countries worldwide, the ability of these models to pass medical examinations is often cited as a reason to use them for medical training and diagnosis. However, the impact of their inevitable use as a self-diagnostic tool and their role in spreading health care misinformation has not been evaluated. This study aims to assess the effectiveness of LLMs, particularly ChatGPT, from the perspective of an individual self-diagnosing to better understand the clarity, correctness, and robustness of the models. We propose the comprehensive testing methodology evaluation of LLM prompts (EvalPrompt). This evaluation methodology uses multiple-choice medical licensing examination questions to evaluate LLM responses. Experiment 1 prompts ChatGPT with open-ended questions to mimic real-world self-diagnosis use cases, and experiment 2 performs sentence dropout on the correct responses from experiment 1 to mimic self-diagnosis with missing information. Humans then assess the responses returned by ChatGPT for both experiments to evaluate the clarity, correctness, and robustness of ChatGPT. In experiment 1, we found that ChatGPT-4.0 was deemed correct for 31% (29/94) of the questions by both nonexperts and experts, with only 34% (32/94) agreement between the 2 groups. Similarly, in experiment 2, which assessed robustness, 61% (92/152) of the responses continued to be categorized as correct by all assessors. As a result, in comparison to a passing threshold of 60%, ChatGPT-4.0 is considered incorrect and unclear, though robust. This indicates that sole reliance on ChatGPT-4.0 for self-diagnosis could increase the risk of individuals being misinformed. The results highlight the modest capabilities of LLMs, as their responses are often unclear and inaccurate. Any medical advice provided by LLMs should be cautiously approached due to the significant risk of misinformation. However, evidence suggests that LLMs are steadily improving and could potentially play a role in health care systems in the future. To address the issue of medical misinformation, there is a pressing need for the development of a comprehensive self-diagnosis dataset. This dataset could enhance the reliability of LLMs in medical applications by featuring more realistic prompt styles with minimal information across a broader range of medical fields.

The widespread use of smart devices, particularly among university students, has raised concerns about their impact on sleep quality. Bedtime usage of smart devices is associated with sleep disruptions and poor sleep quality. This study aimed to explore the behavioral and perceptual factors influencing university students' intention to stop using smart devices at bedtime in Saudi Arabia. A cross-sectional survey was conducted in June 2024 and distributed via social media platforms to university students (aged ≥18 years). The questionnaire collected data on demographics, smart device usage habits, perceived negative effects on sleep, and physical sleep disturbances. The Pittsburgh Sleep Quality Index was used to assess sleep quality. Path analysis was performed to evaluate relationships between the outcome variables, intended to stop using smart device usage, and 3 latent variables: sleep quality smartphone usage, sleep quality perceived negative effects, and sleep quality during the past month. Model fit was assessed using chi-square, comparative fit index, and root mean square error of approximation. Of the 774 participants, 90.43% (700/774) reported using their smart devices every night and 72.48% (561/774) believed bedtime device use negatively affected them the next morning. The most frequently reported next-morning symptoms were fatigue or drowsiness (480/774, 62.01%). Common purposes for bedtime device use were staying in touch with friends or family (432/774, 55.81%), entertainment (355/774, 45.86%), and filling up spare time (345/774, 44.57%). Overall, 58.26% (451/774) expressed an intention to stop bedtime device use within the next 3 months. Path analysis demonstrated that frequent nightly use (path coefficient=0.36) and after-lights-off usage (0.49) were positively associated with the intention to stop, whereas spending ≥3 hours on devices (-0.35) and engaging in multiple activities (-0.18) had negative associations. The strongest predictors of the intention to stop were perceived negative effects on next-morning well-being (0.71) and difficulty breathing comfortably during sleep (0.64). Model fit was excellent (comparative fit index=0.845 and root mean square error of approximation=0.039). Perceived negative effects on sleep quality and physical sleep disturbances are strong predictors of the intention to stop using smart devices at bedtime among university students in Saudi Arabia. Interventions aimed at improving sleep hygiene should focus on raising awareness about the impact of smart device use on well-being and addressing behaviors such as late-night usage and heavy screen time. Public health strategies should target both psychological and physiological aspects of bedtime smart device use to improve sleep quality in this population.

Portugal is facing the challenge of population ageing, with a notable increase in the proportion of older individuals. This has positioned the country among those in Europe with a high prevalence of frailty. Frailty, a geriatric syndrome characterized by diminished physiological reserve and heightened vulnerability to stressors, imposes a substantial burden on public health. This study seeks to address two primary objectives: (1) translation and psychometric evaluation of the European Portuguese version of the Groningen Frailty Indicator (GFI); and (2) development and evaluation of the FRAILSURVEY app, a novel assessment tool for frailty based on the GFI. By achieving these objectives, the study aims to enhance the accuracy and reliability of frailty assessment in the Portuguese context, ultimately contributing to improved health care outcomes for older individuals in the region. To accomplish the objectives of the study, a comprehensive research methodology was used. The study comprised 2 major phases: the initial translation and validation of the GFI into European Portuguese and the development of the FRAILSURVEY app. Following this, an extensive examination of the app's validity and reliability was conducted compared with the conventional paper version of the GFI. A randomized repeated crossover design was used to ensure rigorous evaluation of both assessment methods, using both the paper form of the GFI and the smartphone-based app FRAILSURVEY. The findings of the study revealed promising outcomes in line with the research objectives. The meticulous translation process yielded a final version of the GFI with robust psychometric properties, ensuring clarity and comprehensibility for participants. The study included 522 participants, predominantly women (367/522, 70.3%), with a mean age of 73.7 (SD 6.7) years. Psychometric evaluation of the European Portuguese GFI in paper form demonstrates good reliability (internal consistency: Cronbach a value of 0.759; temporal stability: intraclass correlation coefficient=0.974) and construct validity (revealing a 4D structure explaining 56% of variance). Evaluation of the app-based European Portuguese GFI indicates good reliability (interinstrument reliability: Cohen k=0.790; temporal stability: intraclass correlation coefficient=0.800) and concurrent validity (r=0.694; P<.001). Both the smartphone-based app and the paper version of the GFI were feasible and acceptable for use. The findings supported that FRAILSURVEY exhibited comparable validity and reliability to its paper counterpart. FRAILSURVEY uses a standardized and validated assessment tool, offering objective and consistent measurements while eliminating subjective biases, enhancing accuracy, and ensuring reliability. This app holds promising potential for aiding health care professionals in identifying frailty in older individuals, enabling early intervention, and improving the management of adverse health outcomes associated with this syndrome. Its integration with electronic health records and other data may lead to personalized interventions, improving frailty management and health outcomes for at-risk individuals.

Iris scanning has increasingly been used for biometric identification over the past decade, with continuous advancements and expanding applications. To better understand the acceptability of this technology, we report the long-term experiences of health care providers and frontline worker participants with iris scanning as an identification tool in the EBL2007 Ebola vaccine trial conducted in the Democratic Republic of the Congo. This study aims to document the long-term experiences of using iris scanning for identity verification throughout the vaccine trial. Two years after the start of the EBL2007 vaccine trial (February to March 2022), 69 trial participants-including nurses, first aid workers, midwives, and community health workers-were interviewed through focus group discussions. Additionally, 13 in-depth individual interviews were conducted with physicians involved in the trial, iris scan operators, trial staff physicians, and trial participants who declined iris scanning. Qualitative content analysis was used to identify key themes. Initially, interviewees widely accepted the iris scan and viewed it as a distinctive tool for identifying participants in the EBL2007 vaccine trial. However, over time, perceptions became less favorable. Some participants expressed concerns that their vision had diminished shortly after using the tool and continued to decline until the end of the study. Others reported experiencing perceived vision loss long after the trial had concluded. However, no vision impairment was reported as an adverse event or assessed in the trial as being linked to the iris scan, which uses a previously certified safe infrared light for scanning. Our findings highlight the sustained acceptability and perceived high accuracy of the iris scan tool for uniquely identifying adult participants in a vaccine trial over time. Continued efforts to systematically disseminate and reinforce information about the function and safety of this technology are essential. Clearly presenting iris scanning as a safe procedure could help dispel misconceptions, concerns, and perceived risks among potential users in vaccine trials.