COVID-19 Pandemic: What We Have Learned on Stress, Technology Use, and Psychological Health Among University Students.

Nowadays, the medical COVID-19 emergency is ending worldwide, whereas there is an increasing need to understand the marks and the lessons learned from over two years of unprecedented changes in all life domains. Recent research has highlighted growing rates of psychological suffering among the general population as well as among university students, who were yet well-recognized as a vulnerable population even before the pandemic. The present work drives from university students' experience, and it aims to provide an overview of the key dimensions to take into account, in terms of main risks, changes, challenges, and resources, to develop updated tailored research and interventions promoting psychological health conditions in the current time within and beyond the educational context/university students' population. Implications for research and interventions are highlighted and discussed.

Technology Use for Social Interaction Amongst Older Adults During the COVID-19 Pandemic: A Qualitative Study.

The COVID-19 pandemic had an impact on socialization across all age groups but older adults experienced additional challenges. The purpose of this study was to explore older adults' perceptions and experiences of using technology to support social interactions during the COVID-19 pandemic. We used a qualitative interpretive descriptive approach to understand community dwelling older adults' perceptions of their experiences. We analyzed data using an interpretive thematic analysis approach. Forty-one older adults (median age 74yrs) participated in in-depth interviews exploring experiences of using technology to support their social interaction during the pandemic. Participants discussed the transition towards virtual means of socialization during the pandemic, perceptions of using technology for social interaction, and challenges to adapting to virtual connection. We discuss our findings and the implications for how we introduce technology to older adults.

Three Perspectives on Older Adults' Daily Performance, Health, and Technology Use During COVID-19: Focus Group Study.

Background: During COVID-19 lockdowns, older adults' engagement in daily activities was severely affected, causing negative physical and mental health implications. Technology flourished as a means of performing daily activities in this complex situation; however, older adults often struggled to effectively use these opportunities. Despite the important role of older adults' social environments-including their families and health professionals-in influencing their technology use, research into their unique perspectives is lacking. Objective: This study aimed to explore the daily activity performance, health, and technology use experiences of healthy independent Israeli adults (aged ≥65 years) during COVID-19 from a 3-dimensional perspective: older adults, older adults' family members, and health professionals. Methods: Nine online focus groups, averaging 6-7 participants per group, were conducted with older adults, family members, and health professionals (N=59). Data were analyzed using thematic analysis and constant comparative methods. Results: The intertwining of daily activity performance and health emerged as a central theme, with differences between the groups. Older adults prioritized their self-fulfilling routines based on motivation and choice, especially in social-familial activities. In contrast, family members and health professionals focused on serious physical and mental health COVID-19-related consequences. A consensus among all three groups revealed the meaningful role of technology use during this period in bridging functional limitations. Participants delved into technology's transformative power, focusing on the need for technology to get engaged in daily activities. Conclusions: This study illustrates the profound interplay between daily activity performances, physical and mental health, and technology use, using a 3-dimensional approach. Its focus on technology's uses and benefits sheds light on what older adults need to increase their technology use. Interventions for improving digital activity performance can be tailored to meet older adults' needs and preferences by focusing on motivational and preference-related activities.

Self-reported sensory impairment and social participation among Korean older adults: mediating roles of cognitive function and digital technology use.

OBJECTIVES: This study investigates the correlation between self-reported sensory impairment, cognitive function, digital technology use, and social participation among older adults in South Korea. METHOD: Data from the 2020 National Survey of Older Koreans, comprising a nationally representative sample of 7849 individuals aged 65 years or older, were analyzed. A serial mediation analysis (Model = 6) was conducted using the PROCESS macro for SPSS. RESULTS: Following adjustment for covariates, cognitive function and digital technology use serially mediated the relationship between self-reported sensory impairment and social participation among older adults (B = -0.0020, SE = 0.0005, 95% confidence interval [CI] = [-0.0030, -0.0010]). Specifically, self-reported sensory impairment exhibited a negative correlation with cognitive function (B = -0.3277, SE = 0.0753, p < .001), which was positively associated with digital technology use (B = 0.0763, SE = 0.0056, p < .001), subsequently linking to enhanced social participation (B = 0.0784, SE = 0.0037, p < .001). CONCLUSION: Through cross-sectional analysis, this study confirms that self-reported sensory impairment in older adults may precede cognitive decline, hindering digital technology use and reducing social participation. Early diagnosis and treatment are crucial in preventing cognitive decline, while age-friendly digital devices may alleviate cognitive burden and promote social engagement.

Technology Use Among Older Adults and Their Caregivers: Cross-Sectional Survey Study.

Background: Informal caregivers are called upon to provide substantial care, but more needs to be known about technology use among older adult and caregiver dyads. Objective: This study described technology use among older adults and their caregivers, explored potential correlates of technology use, and highlighted implications for practice. Methods: A cross-sectional survey was conducted among unpaid caregivers of older adults (n=486). Primary outcomes were self-reported technology (devices and functions) use among caregivers and their oldest care recipient. The concordance of technology use among caregivers and care recipients was also examined. Multivariable regression models were conducted separately for caregivers and care recipients. Results: Greater proportions of caregivers used all examined technologies, except for the medication alerts or tracking function, than care recipients. Caregivers used an average of 3.4 devices and 4.2 functions, compared to 1.8 devices and 1.6 functions used by their care recipients. Among caregivers, younger age, higher income, and higher education were associated with more technology use (P<.05). Among care recipients, younger age, not having cognitive dysfunction, and caregiver's technology use were associated with more technology use (P<.05). Conclusions: Understanding technology use patterns and device adoption across diverse caregiver and care recipient populations is increasingly important for enhancing geriatric care. Findings can guide recommendations about appropriate technology interventions and help providers communicate and share information more effectively with patients and their caregivers.

Technology use among the nation's medical examiner and coroner offices: Data from the 2018 Census of Medical Examiner and Coroner Offices.

Technology uses among medical examiner and coroner (MEC) offices in the United States are not well characterized, yet technology is essential to job-performing duties. Resources, operational infrastructure, and MECs' policies and procedures that affect technology use should be better understood. MEC offices need access to technologies like internet, case management systems (CMSs), databases, and advanced imaging to perform their basic duties. A current state of the technologies MEC offices use to complete a death investigation is presented by analyzing data from the 2018 Census of Medical Examiner and Coroner Offices. This analysis shows the New England division reported the most internet and CMS access. Many offices reported limited access to, and low participation in, databases for assessing and sharing case data. Offices serving populations >250,000 have more access to the internet, CMSs, databases, and advanced imaging. Although MEC office technology use has improved over time, it is still disparate.

Characterizing Technology Use and Preferences for Health Communication in South Asian Immigrants With Prediabetes or Diabetes: Cross-Sectional Descriptive Study.

BACKGROUND: Type 2 diabetes disproportionately affects South Asian subgroups. Lifestyle prevention programs help prevent and manage diabetes; however, there is a need to tailor these programs for mobile health (mHealth). OBJECTIVE: This study examined technology access, current use, and preferences for health communication among South Asian immigrants diagnosed with or at risk for diabetes, overall and by sex. We examined factors associated with interest in receiving diabetes information by (1) text message, (2) online (videos, voice notes, online forums), and (3) none or skipped, adjusting for sociodemographic characteristics and technology access. METHODS: We used baseline data collected in 2019-2021 from two clinical trials among South Asian immigrants in New York City (NYC), with one trial focused on diabetes prevention and the other focused on diabetes management. Descriptive statistics were used to examine overall and sex-stratified impacts of sociodemographics on technology use. Overall logistic regression was used to examine the preference for diabetes information by text message, online (videos, voice notes, or forums), and no interest/skipped response. RESULTS: The overall sample (N=816) had a mean age of 51.8 years (SD 11.0), and was mostly female (462/816, 56.6%), married (756/816, 92.6%), with below high school education (476/816, 58.3%) and limited English proficiency (731/816, 89.6%). Most participants had a smartphone (611/816, 74.9%) and reported interest in receiving diabetes information via text message (609/816, 74.6%). Compared to male participants, female participants were significantly less likely to own smartphones (317/462, 68.6% vs 294/354, 83.1%) or use social media apps (Viber: 102/462, 22.1% vs 111/354, 31.4%; WhatsApp: 279/462, 60.4% vs 255/354, 72.0%; Facebook: Messenger 72/462, 15.6% vs 150/354, 42.4%). A preference for receiving diabetes information via text messaging was associated with male sex (adjusted odds ratio [AOR] 1.63, 95% CI 1.01-2.55; P=.04), current unemployment (AOR 1.62, 95% CI 1.03-2.53; P=.04), above high school education (AOR 2.17, 95% CI 1.41-3.32; P<.001), and owning a smart device (AOR 3.35, 95% CI 2.17-5.18; P<.001). A preference for videos, voice notes, or online forums was associated with male sex (AOR 2.38, 95% CI 1.59-3.57; P<.001) and ownership of a smart device (AOR 5.19, 95% CI 2.83-9.51; P<.001). No interest/skipping the question was associated with female sex (AOR 2.66, 95% CI 1.55-4.56; P<.001), high school education or below (AOR 2.02, 95% CI 1.22-3.36; P=.01), not being married (AOR 2.26, 95% CI 1.13-4.52; P=.02), current employment (AOR 1.96, 95% CI 1.18-3.29; P=.01), and not owning a smart device (AOR 2.06, 95% CI 2.06-5.44; P<.001). CONCLUSIONS: Technology access and social media usage were moderately high in primarily low-income South Asian immigrants in NYC with prediabetes or diabetes. Sex, education, marital status, and employment were associated with interest in mHealth interventions. Additional support to South Asian women may be required when designing and developing mHealth interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT03333044; https://classic.clinicaltrials.gov/ct2/show/NCT03333044, ClinicalTrials.gov NCT03188094; https://classic.clinicaltrials.gov/ct2/show/NCT03188094. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s13063-019-3711-y.

Use of Electronic Patient Messaging by Pregnant Patients Receiving Prenatal Care at an Academic Health System: Retrospective Cohort Study.

Background: The COVID-19 pandemic accelerated telemedicine and mobile app use, potentially changing our historic model of maternity care. MyChart is a widely adopted mobile app used in health care settings specifically for its role in facilitating communication between health care providers and patients with its messaging function in a secure patient portal. However, previous studies analyzing portal use in obstetric populations have demonstrated significant sociodemographic disparities in portal enrollment and messaging, specifically showing that patients who have a low income and are non-Hispanic Black, Hispanic, and uninsured are less likely to use patient portals. Objective: The study aimed to estimate changes in patient portal use and intensity in prenatal care before and during the pandemic period and to identify sociodemographic and clinical disparities that continued during the pandemic. Methods: This retrospective cohort study used electronic medical record (EMR) and administrative data from our health system's Enterprise Data Warehouse. Records were obtained for the first pregnancy episode of all patients who received antenatal care at 8 academically affiliated practices and delivered at a large urban academic medical center from January 1, 2018, to July 22, 2021, in Chicago, Illinois. All patients were aged 18 years or older and attended ≥3 clinical encounters during pregnancy at the practices that used the EMR portal. Patients were categorized by the number of secure messages sent during pregnancy as nonusers or as infrequent (≤5 messages), moderate (6-14 messages), or frequent (≥15 messages) users. Monthly portal use and intensity rates were computed over 43 months from 2018 to 2021 before, during, and after the COVID-19 pandemic shutdown. A logistic regression model was estimated to identify patient sociodemographic and clinical subgroups with the highest portal nonuse. Results: Among 12,380 patients, 2681 (21.7%) never used the portal, and 2680 (21.6%), 3754 (30.3%), and 3265 (26.4%) were infrequent, moderate, and frequent users, respectively. Portal use and intensity increased significantly over the study period, particularly after the pandemic. The number of nonusing patients decreased between 2018 and 2021, from 996 of 3522 (28.3%) in 2018 to only 227 of 1743 (13%) in the first 7 months of 2021. Conversely, the number of patients with 15 or more messages doubled, from 642 of 3522 (18.2%) in 2018 to 654 of 1743 (37.5%) in 2021. The youngest patients, non-Hispanic Black and Hispanic patients, and, particularly, non-English-speaking patients had significantly higher odds of continued nonuse. Patients with preexisting comorbidities, hypertensive disorders of pregnancy, diabetes, and a history of mental health conditions were all significantly associated with higher portal use and intensity. Conclusions: Reducing disparities in messaging use will require outreach and assistance to low-use patient groups, including education addressing health literacy and encouraging appropriate and effective use of messaging.

A bidirectional model of sleep and technology use: A theoretical review of How much, for whom, and which mechanisms.

The link between technology and sleep is more complex than originally thought. In this updated theoretical review, we propose a new model informed by the growing body of evidence in the area over the past 10 years. The main theoretical change is the addition of bi-directional links between the use of technology and sleep problems. We begin by reviewing the evidence to date for the originally proposed mechanisms of bright light, arousal, nighttime sleep disruptions, and sleep displacement. Then, in support of the new direction of effect (sleep problems preceding technology use), we propose two new mechanisms: technology before sleep might be used as a time filler and/or as an emotional regulation strategy to facilitate the sleep-onset process. Finally, we present potential moderators of the association between technology and sleep, in recognition of protective and vulnerability factors that may mitigate or exacerbate the effects of technology on sleep and vice versa. The goal of this theoretical review is to update the field, guide future public health messages, and to prompt new research into how much technology and sleep affect each other, for whom it may be problematic, and which mechanisms may explain their association.

Examining Students' Acceptance and Use of ChatGPT in Saudi Arabian Higher Education.

This study examines students' acceptance and use of ChatGPT in Saudi Arabian (SA) higher education, where there is growing interest in the use of this tool since its inauguration in 2022. Quantitative research data, through a self-reporting survey drawing on the "Unified Theory of Acceptance and Use of Technology" (UTAUT2), were collected from 520 students in one of the public universities in SA at the start of the first semester of the study year 2023-2024. The findings of structural equation modeling partially supported the UTAUT and previous research in relation to the significant direct effect of performance expectancy (PE), social influence (SI), and effort expectancy (EE) on behavioral intention (BI) on the use of ChatGPT and the significant direct effect of PE, SI, and BI on actual use of ChatGPT. Nonetheless, the results did not support earlier research in relation to the direct relationship between facilitating conditions (FCs) and both BI and actual use of ChatGPT, which was found to be negative in the first relationship and insignificant in the second one. These findings were because of the absence of resources, support, and aid from external sources in relation to the use of ChatGPT. The results showed partial mediation of BI in the link between PE, SI, and FC and actual use of ChatGPT in education and a full mediation in the link of BI between EE and actual use of ChatGPT in education. The findings provide numerous implications for scholars and higher education institutions in SA, which are also of interest to other institutions in similar contexts.

Living Lab Data of Patient Needs and Expectations for eHealth-Based Cardiac Rehabilitation in Germany and Spain From the TIMELY Study: Cross-Sectional Analysis.

BACKGROUND: The use of eHealth technology in cardiac rehabilitation (CR) is a promising approach to enhance patient outcomes since adherence to healthy lifestyles and risk factor management during phase III CR maintenance is often poorly supported. However, patients' needs and expectations have not been extensively analyzed to inform the design of such eHealth solutions. OBJECTIVE: The goal of this study was to provide a detailed patient perspective on the most important functionalities to include in an eHealth solution to assist them in phase III CR maintenance. METHODS: A guided survey as part of a Living Lab approach was conducted in Germany (n=49) and Spain (n=30) involving women (16/79, 20%) and men (63/79, 80%) with coronary artery disease (mean age 57 years, SD 9 years) participating in a structured center-based CR program. The survey covered patients' perceived importance of different CR components in general, current usage of technology/technical devices, and helpfulness of the potential features of eHealth in CR. Questionnaires were used to identify personality traits (psychological flexibility, optimism/pessimism, positive/negative affect), potentially predisposing patients to acceptance of an app/monitoring devices. RESULTS: All the patients in this study owned a smartphone, while 30%-40% used smartwatches and fitness trackers. Patients expressed the need for an eHealth platform that is user-friendly, personalized, and easily accessible, and 71% (56/79) of the patients believed that technology could help them to maintain health goals after CR. Among the offered components, support for regular physical exercise, including updated schedules and progress documentation, was rated the highest. In addition, patients rated the availability of information on diagnosis, current medication, test results, and risk scores as (very) useful. Of note, for each item, except smoking cessation, 35%-50% of the patients indicated a high need for support to achieve their long-term health goals, suggesting the need for individualized care. No major differences were detected between Spanish and German patients (all P>.05) and only younger age (P=.03) but not sex, education level, or personality traits (all P>.05) were associated with the acceptance of eHealth components. CONCLUSIONS: The patient perspectives collected in this study indicate high acceptance of personalized user-friendly eHealth platforms with remote monitoring to improve adherence to healthy lifestyles among patients with coronary artery disease during phase III CR maintenance. The identified patient needs comprise support in physical exercise, including regular updates on personalized training recommendations. Availability of diagnoses, laboratory results, and medications, as part of a mobile electronic health record were also rated as very useful. TRIAL REGISTRATION: ClinicalTrials.gov NCT05461729; https://clinicaltrials.gov/study/NCT05461729.

Depression and Anxiety in Adolescents During the COVID-19 Pandemic in Relation to the Use of Digital Technologies: Longitudinal Cohort Study.

BACKGROUND: Adolescents are susceptible to mental illness and have experienced substantial disruption owing to the COVID-19 pandemic. The digital environment is increasingly important in the context of a pandemic when in-person social connection is restricted. OBJECTIVE: This study aims to estimate whether depression and anxiety had worsened compared with the prepandemic period and examine potential associations with sociodemographic characteristics and behavioral factors, particularly digital behaviors. METHODS: We analyzed cross-sectional and longitudinal data from a large, representative Greater London adolescent cohort study: the Study of Cognition, Adolescents and Mobile Phones (SCAMP). Participants completed surveys at T1 between November 2016 and July 2018 (N=4978; aged 13 to 15 years) and at T2 between July 2020 and June 2021 (N=1328; aged 16 to 18 years). Depression and anxiety were measured using the Patient Health Questionnaire and Generalized Anxiety Disorder scale, respectively. Information on the duration of total mobile phone use, social network site use, and video gaming was also collected using questionnaires. Multivariable logistic regression was used to assess the cross-sectional and longitudinal associations of sociodemographic characteristics, digital technology use, and sleep duration with clinically significant depression and anxiety. RESULTS: The proportion of adolescents who had clinical depression and anxiety significantly increased at T2 (depression: 140/421, 33.3%; anxiety: 125/425, 29.4%) compared with the proportion of adolescents at T1 (depression: 57/421, 13.5%; anxiety: 58/425, 13.6%; P for 2-proportion z test <.001 for both depression and anxiety). Depression and anxiety levels were similar between the summer holiday, school opening, and school closures. Female participants had higher odds of new incident depression (odds ratio [OR] 2.5, 95% CI 1.5-4.18) and anxiety (OR 2.11, 95% CI 1.23-3.61) at T2. A high level of total mobile phone use at T1 was associated with developing depression at T2 (OR 1.89, 95% CI 1.02-3.49). Social network site use was associated with depression and anxiety cross-sectionally at T1 and T2 but did not appear to be associated with developing depression or anxiety longitudinally. Insufficient sleep at T1 was associated with developing depression at T2 (OR 2.26, 95% CI 1.31-3.91). CONCLUSIONS: The mental health of this large sample of adolescents from London deteriorated during the pandemic without noticeable variations relating to public health measures. The deterioration was exacerbated in girls, those with preexisting high total mobile phone use, and those with preexisting disrupted sleep. Our findings suggest the necessity for allocating resources to address these modifiable factors and target high-risk groups.

Older Adults' and Family Caregivers' Technological Arrangements on Risk of Institutionalization.

Internet-enabled resources could facilitate older adults' ability to live in the community longer, but studies have often overlooked how family caregivers utilize the internet to assist older care recipients. We examined whether different family-level arrangements of internet use may affect the risk of institutionalization among older adults. Using the National Health and Aging Trends Study (2015-2020) and National Study on Caregiving (2015), we estimated multinominal logistic regression and inverse-probability weighted Cox proportional hazard models to investigate the determinants of technological arrangements in 2015 (i.e., no internet use, only caregiver use, only care recipient use, both caregiver and care recipient internet use) and how they may affect the risk of moving to an assisted living or nursing facility between 2015 and 2020. The most prevalent technological arrangement in 2015 was the one where neither the care recipient nor their caregiver reported using the internet. Relatively disadvantaged older care recipients (e.g., people of color, fewer years of education, less income, worse cognitive functioning) and caregivers (e.g., older, fewer years of education) were more likely to be in a non-internet use arrangement. Compared to older adults in other categories, older adults who were internet users and had a family caregiver who also used the internet in their caregiving tasks had a much lower risk of relocation during the study period. Findings suggest that digital interventions aimed at serving the older adult population should assess the gap in access and utilization at a family level and consider the role of older adults' social partners.

Examining technology use and mental health among parents with newborns in the intensive care unit during the COVID-19 pandemic: A cross-sectional study.

Objectives: To investigate the relationship between pandemic-related stressors, mental health, and technology use among parents of hospitalized infants during the COVID-19 pandemic. Methods: A cross-sectional study of 47 participants who had an infant in the Neonatal Intensive Care Unit (NICU) during the pandemic was completed. Participants ranked several statements on a Likert scale to assess mental health, technology use, and COVID-19-related stress during their infant's stay in the NICU. Results: Mental health wellness scores were negatively associated with COVID-19-related stress (rs - 0.40, p = .015). The most prevalent stressor was hospital visitation restriction. Higher COVID-19-related stress was associated with greater use of text and video chat [(rs0.35, p = 0.016) and (rs0.33, p = .025)]. Enjoyment of technology use and access to technology were positively associated with higher mental health wellness scores [(rs0.42, p = .003) and (rs0.38, p = .009)]. Conclusions: Social uses of technology were valuable in a cohort of parents with infants hospitalized during the COVID-19 pandemic. Innovation: Technology is a tool that can help parents cope with the stress of having a hospitalized infant. Digital literacy and technology access should be promoted in the post-pandemic landscape to help parents of infants in the NICU attain more benefit from these resources.

Internet-Enabled Behaviors in Older Adults During the Pandemic: Patterns of Use, Psychosocial Impacts, and Plans for Continued Utilization.

In response to social distancing measures during the COVID-19 pandemic, there was a need to increase the frequency of internet enabled behaviors (IEBs). To date, little is known about how the pandemic impacted IEBs in older adults, a population that has historically been linked to lower digital literacy and utilization. We administered an online survey between April and July 2021 to 298 adults who were over age 50 (mean age = 73 years; 93.5% non-Hispanic white; 94% smart phone owners; 83.5% retired). Older adults self-reported IEBs for social, shopping, medical, and leisure activities during the pandemic, plans for continued use of these behaviors, and completed measures of psychosocial functioning. 66.8% of respondents reported an overall increase in IEBs during the pandemic, most notably for online meeting attendance. More frequent online meeting use was associated with less depression (r = -0.12, p = .04) and less loneliness (r = -0.14, p = .02). With regard to plans for continued use, 82.5% of the sample reported at least one IEB (M = 2.18, SD = 1.65) that they increased during the pandemic and planned to maintain over time (e.g., online shopping for household goods). Plans for continued use were more likely in participants who used IEBs more overall during the pandemic (r = 0.56, p < .001), and who frequently sought technical support on search engines (r = 0.22, p < .001), or online video sites (r = 0.16, p = .006). In summary, IEBs during the pandemic were associated with favorable psychosocial functioning and expectations for continued use in this sample of predominantly white older adults who had some baseline technological familiarity.

Empowering the Care of Older Adults Through the Use of Technology.

In recent years, the COVID-19 pandemic and other global crises have significantly affected the lives of older adults, impacting their healthcare, social connections, and daily routines. While the increasing digitization and automation of services offer benefits such as remote healthcare access and reduced isolation, these technologies also pose challenges in terms of unfamiliarity, learning curves, and privacy and security concerns. Addressing these issues requires a collaborative approach across various fields, including health informatics, gerontology, social psychology, human-computer interaction, and cybersecurity and privacy. Understanding the cognitive, emotional, and sociocultural factors influencing older adults' use of technologies is crucial for creating inclusive and accessible digital tools. This multidisciplinary effort, as highlighted in the special issue of Work, Aging and Retirement, aims to enhance our understanding of aging and technology in today's world, empowering older adults to remain connected and maintain their well-being.

Acceptance of Medical Artificial Intelligence in Skin Cancer Screening: Choice-Based Conjoint Survey.

BACKGROUND: There is great interest in using artificial intelligence (AI) to screen for skin cancer. This is fueled by a rising incidence of skin cancer and an increasing scarcity of trained dermatologists. AI systems capable of identifying melanoma could save lives, enable immediate access to screenings, and reduce unnecessary care and health care costs. While such AI-based systems are useful from a public health perspective, past research has shown that individual patients are very hesitant about being examined by an AI system. OBJECTIVE: The aim of this study was two-fold: (1) to determine the relative importance of the provider (in-person physician, physician via teledermatology, AI, personalized AI), costs of screening (free, 10€, 25€, 40€; 1€=US $1.09), and waiting time (immediate, 1 day, 1 week, 4 weeks) as attributes contributing to patients' choices of a particular mode of skin cancer screening; and (2) to investigate whether sociodemographic characteristics, especially age, were systematically related to participants' individual choices. METHODS: A choice-based conjoint analysis was used to examine the acceptance of medical AI for a skin cancer screening from the patient's perspective. Participants responded to 12 choice sets, each containing three screening variants, where each variant was described through the attributes of provider, costs, and waiting time. Furthermore, the impacts of sociodemographic characteristics (age, gender, income, job status, and educational background) on the choices were assessed. RESULTS: Among the 383 clicks on the survey link, a total of 126 (32.9%) respondents completed the online survey. The conjoint analysis showed that the three attributes had more or less equal importance in contributing to the participants' choices, with provider being the most important attribute. Inspecting the individual part-worths of conjoint attributes showed that treatment by a physician was the most preferred modality, followed by electronic consultation with a physician and personalized AI; the lowest scores were found for the three AI levels. Concerning the relationship between sociodemographic characteristics and relative importance, only age showed a significant positive association to the importance of the attribute provider (r=0.21, P=.02), in which younger participants put less importance on the provider than older participants. All other correlations were not significant. CONCLUSIONS: This study adds to the growing body of research using choice-based experiments to investigate the acceptance of AI in health contexts. Future studies are needed to explore the reasons why AI is accepted or rejected and whether sociodemographic characteristics are associated with this decision.

Factors Influencing the Behavioral Intentions and Use Behaviors of Telemedicine in Patients With Diabetes: Web-Based Survey Study.

BACKGROUND: Telemedicine has great potential for diabetes management. The COVID-19 pandemic has boosted the development of telemedicine. However, the factors influencing the behavioral intentions to use and use behaviors of telemedicine in patients with diabetes in China are not clear. OBJECTIVE: We aimed to understand the determinants of behavioral intention to use telemedicine based on an extended Unified Theory of Acceptance and Use of Technology model and to identify demographic factors associated with telemedicine use in patients with diabetes in China. METHODS: Patients with diabetes who are aged ≥18 years were surveyed from February 1 to February 7, 2023. We distributed the survey link in 3 WeChat groups including a total of 988 patients with diabetes from the outpatient department or patients discharged from Changsha Central Hospital. Structural equation modeling was used to understand the determinants of behavioral intention. A multivariate logistic regression analysis was used to identify the demographic factors associated with telemedicine use. RESULTS: In total, 514 questionnaires were collected. Of the respondents, 186 (36.2%) were diagnosed with COVID-19. The measurement model showed acceptable reliability, convergent validity, discriminant validity, and data fit indices. The model explained 63.8% of the variance in behavioral intention. Social influence, performance expectancy, and facilitating conditions positively influenced behavioral intention (ß=.463, P<.001; ß=.153, P=.02; and ß=.257, P=.004, respectively). Perceived susceptibility, perceived severity, and effort expectancy had no significant impact on behavioral intention (all P>.05). The overall use of telemedicine was 20.6% (104/514). After adjusting for the behavioral intention score, the multivariate regression analysis showed that age, education, and family income were associated with telemedicine use. Telemedicine use was higher in the 40 to 59 years and 18 to 39 years age groups than in the ≥60 years age group (odds ratio [OR] 4.35, 95% CI 1.84-10.29, P=.001; OR 9.20, 95% CI 3.40-24.88, P<.001, respectively). Telemedicine use was higher in the senior high school and the university and more groups than in junior high school education and less group (OR 2.45, 95% CI 1.05-5.73, P=.04; OR 2.63, 95% CI 1.11-6.23, P=.03, respectively). Patients with a higher family income used telemedicine more often than the patients who had an annual family income ≤¥10,000 (CNY ¥1=US $0.1398; ¥10,000-¥50,000 group: OR 3.90, 95% CI 1.21-12.51, P=.02; ¥50,000-¥100,000 group: OR 3.91, 95% CI 1.19-12.79, P=.02; >¥100,000 group: OR 4.63, 95% CI 1.41-15.27, P=.01). CONCLUSIONS: Social influence, performance expectancy, and facilitating conditions positively affected the behavioral intention of patients with diabetes to use telemedicine. Young patients, highly educated patients, and patients with high family income use telemedicine more often. Promoting behavioral intention and paying special attention to the needs of older adult patients, patients with low income, and patients with low levels of education are needed to encourage telemedicine use.

Overreliance on inefficient computer-mediated information retrieval is countermanded by strategy advice that promotes memory-mediated retrieval.

With ubiquitous computing, problems can be solved using more strategies than ever, though many strategies feature subpar performance. Here, we explored whether and how simple advice regarding when to use which strategy can improve performance. Specifically, we presented unfamiliar alphanumeric equations (e.g., A + 5 = F) and asked whether counting up the alphabet from the left letter by the indicated number resulted in the right letter. In an initial choice block, participants could engage in one of three cognitive strategies: (a) internal counting, (b) internal retrieval of previously generated solutions, or (c) computer-mediated external retrieval of solutions. Participants belonged to one of two groups: they were either instructed to first try internal retrieval before using external retrieval, or received no specific use instructions. In a subsequent internal block with identical instructions for both groups, external retrieval was made unavailable. The 'try internal retrieval first' instruction in the choice block led to pronounced benefits (d = .76) in the internal block. Benefits were due to facilitated creation and retrieval of internal memory traces and possibly also due to improved strategy choice. These results showcase how simple strategy advice can greatly help users navigate cognitive environments. More generally, our results also imply that uninformed use of external tools (i.e., technology) can bear the risk of not developing and using even more superior internal processing strategies.

Capturing multiple assistive technology use and its impact in later life: lessons learned from distinct measurement approaches.

PURPOSE: Assistive technology (AT) use is prevalent in older adulthood and can accommodate activity difficulties to support well-being. However, within the context of multiple activity difficulties and multiple technology use, it is unclear how to best assess their combined effects on older adults' health outcomes. This study proposed four distinct approaches to quantify multiple AT use and examined their respective impact in later life. MATERIAL AND METHODS: Using data from the 2015 round of the National Health and Aging Trends Study (n = 6,936), we compared four indices to summarize the state of multiple AT use among the U.S. older population: binary, item-specific, cumulative, and accommodative. Separate regression analyses tested the impact of each index on older adults' well-being and restricted participation in meaningful activities. RESULTS: In 2015, 59.9% of the respondents were identified as AT users. Among these users, 53.8% reported using two or more technologies when performing daily self-care and mobility activities. The implications of multiple AT use for health outcomes varied across the four indices. Approaches that captured elements of person-technology fit provided the most nuanced and actionable insights on the benefits of using AT to support well-being. CONCLUSIONS: ATs were commonly adopted by older adults in everyday activities. Overall, findings suggest that there are multiple approaches to conceptualize the independent, cumulative, or balanced effects of multiple AT use. Each measurement approach has unique implications for understanding the impacts of using ATs on older adults' health outcomes.

Multiple assistive technology (AT) use is observed and prevalent in later life, highlighting that there is great need for older adults to deploy different technologies to help with different daily activities.The concept of multiple AT use can be approached in various ways (e.g., where effects of each AT are independent, cumulative, or dependent on fit), with each conceptualization based on distinct assumptions and capable of serving different purposes in rehabilitation research.This study demonstrates that information on person-technology fit plays a critical role in helping rehabilitation engineers and clinical practitioners assess the effects of AT use on health and well-being outcomes among older adults.