Health Policy and Privacy Challenges Associated With Digital Technology

Current Implementation of Digital Health in Chronic Disease Management: Scoping Review

BACKGROUND

Approximately 1 in 3 adults live with multiple chronic diseases. Digital health is being harnessed to improve continuity of care and management of chronic diseases. However, meaningful uptake of digital health for chronic disease management remains low. It is unclear how these innovations have been implemented and evaluated.

OBJECTIVE

This scoping review aims to identify how digital health innovations for chronic disease management have been implemented and evaluated: what implementation frameworks, methods, and strategies were used; how successful these strategies were; key barriers and enablers to implementation; and lessons learned and recommendations shared by study authors.

METHODS

We used the Joanna Briggs Institute methodology for scoping reviews. Five databases were searched for studies published between January 2015 and March 2023: PubMed, Scopus, CINAHL, PsycINFO, and IEEE Xplore. We included primary studies of any study design with any type of digital health innovations for chronic diseases that benefit patients, caregivers, or health care professionals. We extracted study characteristics; type of digital health innovation; implementation frameworks, strategies, and outcome measures used; barriers and enablers to implementation; lessons learned; and recommendations reported by study authors. We used established taxonomies to synthesize extracted data. Extracted barriers and enablers were grouped into categories for reporting. Descriptive statistics were used to consolidate extracted data.

RESULTS

A total of 252 studies were included, comprising mainly mobile health (107/252, 42.5%), eHealth (61/252, 24.2%), and telehealth (97/252, 38.5%), with some studies involving more than 1 innovation. Only 23 studies (23/252, 9.1%) reported using an implementation science theory, model, or framework; the most common were implementation theories, classic theories, and determinant frameworks, with 7 studies each. Of 252 studies, 144 (57.1%) used 2 to 5 implementation strategies. Frequently used strategies were "obtain and use patient or consumer feedback" (196/252, 77.8%); "audit and provide feedback" (106/252, 42.1%); and piloting before implementation or "stage implementation scale-up" (85/252, 33.7%). Commonly measured implementation outcomes were acceptability, feasibility, and adoption of the digital innovation. Of 252 studies, 247 studies (98%) did not measure service outcomes, while patient health outcomes were measured in 89 studies (35.3%). The main method used to assess outcomes was surveys (173/252, 68.7%), followed by interviews (95/252, 37.7%). Key barriers impacting implementation were data privacy concerns and patient preference for in-person consultations. Key enablers were training for health care workers and personalization of digital health features to patient needs.

CONCLUSIONS

This review generated a summary of how digital health in chronic disease management is currently implemented and evaluated and serves as a useful resource for clinicians, researchers, health system managers, and policy makers planning real-world implementation. Future studies should investigate whether using implementation science frameworks, including how well they are used, would yield better outcomes compared to not using them.

Service quality evaluation of county-level public hospitals in Chongqing under smart healthcare

BACKGROUND

This study explores patients' perceptions and expectations of smart healthcare services from the perspective of patient experience.The aim is to provide insights for the development of smart healthcare services in hospitals.

METHODS

A cluster sampling method was used to select 10 public county-level hospitals from October to November 2021 in a municipality in southwestern China. Patient expectations and perceptions about smart healthcare services were assessed using SERVQUAL scale, which included 24 items across four dimensions: ability, application, platform, and effectiveness. The perception-expectation gap was calculated, and factors influencing this gap were analyzed. The Importance-Performance Analysis (IPA) model was then applied to evaluate the results.

RESULTS

A total of 915 patients from outpatient and inpatient departments participated in the study. The average perception score was 3.86, while the average expectation score was 4.44, resulting in a gap of -0.58. Paired sample t-tests revealed significant differences between patients' perceptions and expectations across the 24 items (P < 0.05). IPA quadrant analysis identified 5 items in quadrant IV. A generalized linear model indicated that patients with a college degree, income between 2001 ~ 3500RMB, and income between 3501 ~ 5000RMB were associated with differences in service quality evaluation. Patients covered by urban and rural residents' medical insurance also showed variations in their evaluations.

CONCLUSIONS

The study highlights that smart healthcare services in public county-level hospitals fall short of meeting patients' expectations. It emphasizes the importance of addressing individualized medical needs and improving aspects such as cost control, system design, technology-human care balance, and operational efficiency.

Gaps in the Global Regulatory Frameworks for the Use of Artificial Intelligence (AI) in the Healthcare Services Sector and Key Recommendations

Artificial Intelligence (AI) has shown remarkable potential to revolutionise healthcare by enhancing diagnostics, improving treatment outcomes, and streamlining administrative processes. In the global regulatory landscape, several countries are working on regulating AI in healthcare. There are five key regulatory issues that need to be addressed: (i) data security and protection-measures to cover the "digital health footprints" left unknowingly by patients when they access AI in health services; (ii) data quality-availability of safe and secure data and more open database sources for AI, algorithms, and datasets to ensure equity and prevent demographic bias; (iii) validation of algorithms-mapping of the explainability and causability of the AI system; (iv) accountability-whether this lies with the healthcare professional, healthcare organisation, or the personified AI algorithm; (v) ethics and equitable access-whether fundamental rights of people are met in an ethical manner. Policymakers may need to consider the entire life cycle of AI in healthcare services and the databases that were used for the training of the AI system, along with requirements for their risk assessments to be publicly accessible for effective regulatory oversight. AI services that enhance their functionality over time need to undergo repeated algorithmic impact assessment and must also demonstrate real-time performance. Harmonising regulatory frameworks at the international level would help to resolve cross-border issues of AI in healthcare services.

Discursive framework for a multi-disease digital health passport in Africa: a perspective

Africa's dual burden of rising incidence of infectious diseases and increasing prevalence of non-communicable diseases (NCDs), such as cardiovascular diseases and diabetes, demands innovative approaches to disease surveillance, response, and cross-border health management in response to growing economic integration and global connectivity. In this context, we propose a discursive framework for the development and implementation of a multi-disease digital health passport (MDDHP) in Africa. The MDDHP would serve as a secure platform for storing and sharing individual health data, offering a comprehensive solution to track and respond to infectious diseases, facilitate the management of NCDs, and improve healthcare access across borders. Empowering individuals to proactively manage their health and improve overall outcomes is a key aspect of the MDDHP. In the paper, we examine the key elements necessary to effectively implement MDDHP, focusing on minimizing risks, maintaining efficacy, and driving its adoption while also taking into consideration the unique contexts of the continent. The paper is intended to provide an understanding of the key principles involved and contribute to the discussion on the development and successful implementation of MDDHP in Africa.

Prevalence and factors associated with cyberbullying among adolescents (15-19 years) in Gurugram District - A community based cross-sectional study

Background

Digitalization in the form of increased Internet use through screen media has also shown its ramification like cyberbullying. They are aggressive acts with the intention or motivation to harm another person through technology. The aim is to study the prevalence of cyberbullying and its association with mental illness in the adolescent age group (15-19 years).

Methods

This community-based cross-sectional study was rolled out among adolescents aged 15-19 years. A total of 387 were given a semistructured interviewer-administered questionnaire consisting of general details, cyberbullying victimization, and offending questions, PHQ-9 and GAD-7.

Results

The mean (SD) age was 16.8 (1.3) years. More than half (53.2%) were males, and nearly three-fourths (74.4%) were school-going. Around 28.2% reported being cyberbullied at least once in their lifetime. About 7.0% of adolescents were cyberbullied more than once, and 0.8% more than five times in the past 30 days. The most common ways were posting a mean or hurtful picture (31.9%) and the concerned person's comments (24.2%) online. Multivariable logistic regression analysis found that adolescents attending colleges (AOR 1.9, 95% CI 1.1 to 3.4), using tobacco (AOR 2.5, 95% CI 1.4 to 4.5), and depressed (of any severity, AOR 2.0, 95% CI 1.1 to 4.3) were at significantly increased risk of being cyberbullied (P < 0.05).

Conclusion

The prevalence of cyberbullying among adolescents aged 15-19 is notable, with significant associations found between cyberbullying and attending college, tobacco use, and depression. Understanding the correlates of cyberbullying can inform targeted interventions to support mental health and well-being among adolescents.

Implications of Online Self-Diagnosis in Psychiatry

Online self-diagnosis of psychiatric disorders by the general public is increasing. The reasons for the increase include the expansion of Internet technologies and the use of social media, the rapid growth of direct-to-consumer e-commerce in healthcare, and the increased emphasis on patient involvement in decision making. The publicity given to artificial intelligence (AI) has also contributed to the increased use of online screening tools by the general public. This paper aims to review factors contributing to the expansion of online self-diagnosis by the general public, and discuss both the risks and benefits of online self-diagnosis of psychiatric disorders. A narrative review was performed with examples obtained from the scientific literature and commercial articles written for the general public. Online self-diagnosis of psychiatric disorders is growing rapidly. Some people with a positive result on a screening tool will seek professional help. However, there are many potential risks for patients who self-diagnose, including an incorrect or dangerous diagnosis, increased patient anxiety about the diagnosis, obtaining unfiltered advice on social media, using the self-diagnosis to self-treat, including online purchase of medications without a prescription, and technical issues including the loss of privacy. Physicians need to be aware of the increase in self-diagnosis by the general public and the potential risks, both medical and technical. Psychiatrists must recognize that the general public is often unaware of the challenging medical and technical issues involved in the diagnosis of a mental disorder, and be ready to treat patients who have already obtained an online self-diagnosis.

Connecting Health and Technology: A Comprehensive Review of Social Media and Online Communities in Healthcare

This review provides an in-depth analysis of the intersection between health and technology, focusing specifically on social media's and online communities' role in healthcare. It explores the significance of these digital platforms in patient education, empowerment, and support, highlighting their potential to improve healthcare delivery and patient outcomes. Key findings are synthesized by examining existing literature, including the wide-reaching impact of social media on health information dissemination and the value of online communities in facilitating peer support. However, privacy concerns and misinformation are also addressed, emphasizing the need for careful consideration and strategic implementation of these technologies. The implications for healthcare practice and research are discussed, with recommendations for future actions and priorities outlined. Overall, this review underscores the transformative potential of social media and online communities in reshaping the healthcare landscape. It also highlights the importance of ethical and responsible use to maximize benefits.

Medical Malpractice and Diagnostic Radiology: Challenges and Opportunities

Medicolegal challenges in radiology are broad and impact both radiologists and patients. Radiologists may be affected directly by malpractice litigation or indirectly due to defensive imaging ordering practices. Patients also could be harmed physically, emotionally, or financially by unnecessary tests or procedures. As technology advances, the incorporation of artificial intelligence into medicine will bring with it new medicolegal challenges and opportunities. This article reviews the current and emerging direct and indirect effects of medical malpractice on radiologists and summarizes evidence-based solutions.

Safe and sound: Strengthening cybersecurity in healthcare through robust staff educational programs

This article emphasizes the importance of comprehensive cybersecurity education programs in the healthcare industry. The rapid development of technology in healthcare has brought numerous advantages, including electronic health records and telehealth services. However, these advancements also expose the healthcare industry to significant cybersecurity risks. The healthcare industry is an attractive target for cybercriminals due to the presence of sensitive personal and financial information. Current regulations, such as HIPAA and PIPEDA, are in place to protect patient information, but 95% of healthcare industry breaches result from human error. Healthcare organizations must prioritize robust cybersecurity measures and implement comprehensive education programs for all healthcare professionals. This article recommends tailoring educational content to different healthcare roles and incorporating ongoing learning and awareness as essential elements of cybersecurity education. Overall, it calls for a holistic approach to cybersecurity education in healthcare to protect patient information and mitigate cyberthreats.

Digital health interventions to improve adherence to oral antipsychotics among patients with schizophrenia: a scoping review

OBJECTIVES

To assess the current evidence on the potential of digital health interventions (DHIs) to improve adherence to oral antipsychotics among patients with schizophrenia by assessing the methodologies, feasibility and effectiveness of DHIs as well as the perceptions of relevant stakeholders.

DESIGN

The scoping review was conducted based on the methodologies outlined by Levac et al and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.

DATA SOURCES

PubMed, Embase, Web of Science, Scopus, CINAHL, PsycINFO and the Cochrane Library were searched in August 2023 to identify relevant publications from the previous decade.

ELIGIBILITY CRITERIA

Studies published in English focused on improving medication adherence among adult patients with schizophrenia or schizoaffective disorder via DHIs were selected. Protocols, editorials, comments, perspectives, reviews, correspondence and conference abstracts were excluded.

DATA EXTRACTION AND SYNTHESIS

The extracted data included general information about the study, framework, participants, features and strategies of DHIs, measurement tools for adherence used, and main findings.

RESULTS

In total, 64 studies were included in the qualitative synthesis. Features used in DHIs to improve medication adherence included phone calls, text messages, mobile apps, sensors, web-based platforms and electronic devices. Strategies included medication reminders and monitoring, providing medication-related information and suggestions, other illness management suggestions and individual support. Texting and mobile apps were commonly used as medication reminders and monitoring methods. Additionally, the use of sensors combined with other digital technologies has garnered significant attention. All the interventions were considered acceptable and feasible, and several were assessed in pilot trials. Preliminary findings suggest that DHIs could enhance medication adherence in patients with schizophrenia. However, further validation of their effectiveness is required.

CONCLUSION

DHIs are a promising approach to enhancing medication adherence among patients with schizophrenia. Future interventions should be interactive, focusing on user preference, experience and privacy.

Data management in the digital health environment scale development study

PURPOSE

This study aims to develop a scale that measures individuals' perceptions of privacy, security, use, sharing, benefit and satisfaction in the digital health environment.

METHOD

Within the scope of the study, in the scale development process; The stages of literature review, creation of items, getting expert opinion, conducting a pilot study, ensuring construct and criterion validity, and reliability analyses were carried out. The literature was searched for the formation of the question items. To evaluate the created question items, expert opinion was taken, and the question items were arranged according to the feedback from the experts. In line with the study's purpose and objectives, the focus group consisted of individuals aged 18 and above within the community. The convenience sampling method was employed for sample selection. Data were collected using an online survey conducted through Google Forms. Before commencing the survey, participants were briefed on the research's content. A pilot study was conducted with 30 participants, and as a result of the feedback from the participants, eliminations were made in the question items and the scale was made ready for application. The research was conducted by reference to 812 participants in the community. Expert evaluations of the question items were obtained, and a pilot study was conducted. A sociodemographic information form, a scale developed by the researcher, Norman and Skinner's e-Health Literacy Scale, and the Mobile Health and Personal Health Record Management Scale were used as data collection tools.

RESULTS

The content validity of the research was carried out by taking expert opinions and conducting a pilot study. Exploratory factor analysis and confirmatory factor analysis were performed to ensure construct validity. The total variance explained by the scale was 60.43%. The results of confirmatory factor analysis indicated that the 20-Item 5-factor structure exhibited good fit values. According to the analysis of criterion validity, there are significant positive correlations among the Data Management in the Digital Health Environment Scale, Norman and Skinner's e-Health Literacy Scale and the Mobile Health and Personal Health Record Management Scale (p < 0.01; r = .669, .378). The Cronbach's alpha value of the scale is .856, and the test-retest reliability coefficient is .909.

CONCLUSION

The Data Management in the Digital Health Environment Scale is a valid and reliable measurement tool that measures individuals' perceptions of privacy, security, use, sharing, benefit and satisfaction in the digital health environment.

Ethical Responsibilities for Companies That Process Personal Data

It has become increasingly difficult for individuals to exercise meaningful control over the personal data they disclose to companies or to understand and track the ways in which that data is exchanged and used. These developments have led to an emerging consensus that existing privacy and data protection laws offer individuals insufficient protections against harms stemming from current data practices. However, an effective and ethically justified way forward remains elusive. To inform policy in this area, we propose the Ethical Data Practices framework. The framework outlines six principles relevant to the collection and use of personal data-minimizing harm, fairly distributing benefits and burdens, respecting autonomy, transparency, accountability, and inclusion-and translates these principles into action-guiding practical imperatives for companies that process personal data. In addition to informing policy, the practical imperatives can be voluntarily adopted by companies to promote ethical data practices.

Patient Perspectives on Artificial Intelligence in Radiology

There are two major areas for patient engagement in radiology artificial intelligence (AI). One is in the sharing of data for AI development; the second is the use of AI in patient care. In general, individuals support sharing deidentified data if used for the common good, to help others with similar health conditions, or for research. However, there is concern with risk to privacy including reidentification and use for other than intended purposes. Lack of trust is mentioned as a barrier for data sharing. Individuals want to be involved in the data-sharing process. In the use of AI in medical care, patients generally support AI as an assist to the radiologist but lack trust in unsupervised AI. Patients worry about liability in case of bad outcomes. Patients are concerned about loss of the human connection and the loss of empathy during a vulnerable time in their lives. Patients expressed concern about risk of discrimination due to bias in AI algorithms. Building trust in AI requires transparency, explainability, security, and privacy protection. Radiologists can take action to prepare their patients to become more trusting of AI. Developing and implementing data-sharing agreements allows patients to voluntarily help in the algorithm development process. Developing AI disclosure guidelines and having AI use disclosure discussions with patients will help them understand the use of AI in their care. As the use of AI increases, there is an opportunity for radiologists to develop and maintain close relationships with their patients and to become more involved in their care.

Widespread Third-Party Tracking On Hospital Websites Poses Privacy Risks For Patients And Legal Liability For Hospitals

Computer code that transfers data to third parties (third-party tracking) is common across the web and is subject to few federal privacy regulations. We determined the presence of potentially privacy-compromising data transfers to third parties on a census of US nonfederal acute care hospital websites, and we used descriptive statistics and regression analyses to determine the hospital characteristics associated with a greater number of third-party data transfers. We found that third-party tracking is present on 98.6 percent of hospital websites, including transfers to large technology companies, social media companies, advertising firms, and data brokers. Hospitals in health systems, hospitals with a medical school affiliation, and hospitals serving more urban patient populations all exposed visitors to higher levels of tracking in adjusted analyses. By including third-party tracking code on their websites, hospitals are facilitating the profiling of their patients by third parties. These practices can lead to dignitary harms, which occur when third parties gain access to sensitive health information that a person would not wish to share. These practices may also lead to increased health-related advertising that targets patients, as well as to legal liability for hospitals.

An Assessment of Perspectives and Concerns Among Research Participants of Childbearing Age Regarding the Health-Relatedness of Data, Online Data Privacy, and Donating Data to Researchers: Survey Study

BACKGROUND

The June 2022 US Supreme Court decision to ban abortion care in Dobbs v Jackson Women's Health Organization sparked ominous debate about the privacy and safety of women and families of childbearing age with digital footprints who actively engage in family planning, including abortion and miscarriage care.

OBJECTIVE

To assess the perspectives of a subpopulation of research participants of childbearing age regarding the health-relatedness of their digital data, their concerns about the use and sharing of personal data online, and their concerns about donating data from various sources to researchers today or in the future.

METHODS

An 18-item electronic survey was developed using Qualtrics and administered to adults (aged ≥18 years) registered in the ResearchMatch database in April 2021. Individuals were invited to participate in the survey regardless of health status, race, gender, or any other mutable or immutable characteristics. Descriptive statistical analyses were conducted using Microsoft Excel and manual queries (single layer, bottom-up topic modeling) and used to categorize illuminating quotes from free-text survey responses.

RESULTS

A total of 470 participants initiated the survey and 402 completed and submitted the survey (for an 86% completion rate). Nearly half the participants (189/402, 47%) self-reported to be persons of childbearing age (18 to 50 years). Most participants of childbearing age agreed or strongly agreed that social media data, email data, text message data, Google search history data, online purchase history data, electronic medical record data, fitness tracker and wearable data, credit card statement data, and genetic data are health-related. Most participants disagreed or strongly disagreed that music streaming data, Yelp review and rating data, ride-sharing history data, tax records and other income history data, voting history data, and geolocation data are health-related. Most (164/189, 87%) participants were concerned about fraud or abuse based on their personal information, online companies and websites sharing information with other parties without consent, and online companies and websites using information for purposes that are not explicitly stated in their privacy policies. Free-text survey responses showed that participants were concerned about data use beyond scope of consent; exclusion from health care and insurance; government and corporate mistrust; and data confidentiality, security, and discretion.

CONCLUSIONS

Our findings in light of Dobbs and other related events indicate there are opportunities to educate research participants about the health-relatedness of their digital data. Developing strategies and best privacy practices for discretion regarding digital-footprint data related to family planning should be a priority for companies, researchers, families, and other stakeholders.

Consumer Views on Privacy Protections and Sharing of Personal Digital Health Information

IMPORTANCE

Digital health information has many potential health applications, but privacy is a growing concern among consumers and policy makers. Consent alone is increasingly seen as inadequate to safeguard privacy.

OBJECTIVE

To determine whether different privacy protections are associated with consumers' willingness to share their digital health information for research, marketing, or clinical uses.

DESIGN, SETTING, AND PARTICIPANTS

This 2020 national survey with an embedded conjoint experiment recruited US adults from a nationally representative sample with oversampling of Black and Hispanic individuals. Willingness to share digital information across 192 different scenarios reflecting the product of 4 possible privacy protections, 3 uses of information, 2 users of information, and 2 sources of digital information was evaluated. Each participant was randomly assigned 9 scenarios. The survey was administrated between July 10 and July 31, 2020, in Spanish and English. Analysis for this study was conducted between May 2021 and July 2022.

MAIN OUTCOMES AND MEASURES

Participants rated each conjoint profile on a 5-point Likert scale measuring their willingness to share their personal digital information (with 5 indicating the most willingness to share). Results are reported as adjusted mean differences.

RESULTS

Of the 6284 potential participants, 3539 (56%) responded to the conjoint scenarios. A total of 1858 participants (53%) were female, 758 (21%) identified as Black, 833 (24%) identified as Hispanic, 1149 (33%) had an annual income less than $50 000, and 1274 (36%) were 60 years or older. Participants were more willing to share health information with the presence of each individual privacy protection, including consent (difference, 0.32; 95% CI, 0.29-0.35; P < .001), followed by data deletion (difference, 0.16; 95% CI, 0.13-0.18; P < .001), oversight (difference, 0.13; 95% CI, 0.10-0.15; P < .001), and transparency of data collected (difference, 0.08; 95% CI, 0.05-0.10; P < .001). The relative importance (importance weight on a 0%-100% scale) was greatest for the purpose of use (29.9%) but when considered collectively, the 4 privacy protections together were the most important (51.5%) factor in the conjoint experiment. When the 4 privacy protections were considered separately, consent was the most important (23.9%).

CONCLUSIONS AND RELEVANCE

In this survey study of a nationally representative sample of US adults, consumers' willingness to share personal digital health information for health purposes was associated with the presence of specific privacy protections beyond consent alone. Additional protections, including data transparency, oversight, and data deletion may strengthen consumer confidence in sharing their personal digital health information.

Reproductive Health Policy in the United States: An American College of Physicians Policy Brief

The legal landscape around access to reproductive health care services was substantially altered after the Supreme Court decision in Dobbs v Jackson Women's Health Organization. In the aftermath of the decision, some state governments have begun to impose stringent restrictions and complete bans on the provision of abortion, whereas others have sought to protect and expand access. Some have gone as far as imposing criminal and civil penalties on physicians and other clinicians who provide evidence-based, clinically indicated reproductive health care services and information that is guided by biomedical ethics and provided in the best interest of the patient's health and well-being. In several states, lawmakers have attempted and successfully used new approaches to enforcing and achieving these prohibitions, including prohibitions on crossing state lines to obtain abortion care, prohibitions on the mailing of medication abortion, and the authorization of third-party civil lawsuits. In this policy brief, the American College of Physicians (ACP) updates and expands on its previous public policy positions on abortion from its 2018 policy paper, "Women's Health Policy in the United States," to reflect this new reality. The College also offers policymakers and payers recommendations to promote equitable access to reproductive health care services and safeguard maternal health. ACP reaffirms its opposition to undue and unnecessary governmental interference in the patient-physician relationship that criminalizes the provision of health care made in the physician's clinical judgment and based on clinical evidence and the standard of care.

Acceptability and preliminary effectiveness of a single-arm 12-week digital behavioral health intervention in patients with knee osteoarthritis

BACKGROUND

Digital health interventions may improve osteoarthritis (OA) management. This study evaluated the acceptability and preliminary effectiveness of a multimodal digital nutrition, exercise, and mindfulness intervention in adults with knee OA.

METHODS

Adults with advanced knee OA and an orthopaedic referral were invited to self-enroll in a pragmatic 12-week single-arm intervention. OA-focused nutrition and exercise resources were delivered weekly by email, and secondary components accessed on-demand (web-platform, webinars, and nutrition consultation). Acceptability was assessed by qualitative interview data and completion rates. Preliminary effectiveness on clinical outcomes was assessed by change in health-related quality of life, well-being, mindfulness, self-efficacy, and interest in total knee arthroplasty (TKA) between baseline and 12-weeks.

RESULTS

N = 102 patients self-enrolled (73.5% female, age 64 ± 7 years, body mass index 32.9 ± 7.3 kg/m2); n = 53 completed the 12-week intervention (71.7% female, age 65 ± 7 years, body mass index 33.4 ± 6.3 kg/m2). Acceptability was demonstrated by positive perceptions of tailored intervention resources. In study completers, health-related quality of life components of pain and physical functioning domains improved at 12-weeks [change in SF36 4.4 (95%CI 0.2-8.6), p = 0.016, and 6.7 (95%CI 2.7-10.7), p < 0.001, respectively]. Self-efficacy for managing daily activities improved [change in PROMIS T-score 4.4 (95%CI 2.8-6.0), p < 0.001].

CONCLUSION

A 12-week digital multimodal intervention for knee OA was acceptable to patients and shows preliminary effectiveness in improving self-efficacy, aspects of quality of life, and decreasing interest in TKA. Digital behavioral interventions for knee OA may be an acceptable approach to improve patient outcomes and OA self-management while potentially reducing utilization of costly health system resources.

A Survey of Research Participants’ Privacy-Related Experiences and Willingness to Share Real-World Data with Researchers

Background: Real-world data (RWD) privacy is an increasingly complex topic within the scope of personalized medicine, as it implicates several sources of data. Objective: To assess how privacy-related experiences, when adjusted for age and education level, may shape adult research participants’ willingness to share various sources of real-world data with researchers. Methods: An electronic survey was conducted in April 2021 among adults (≥18 years of age) registered in ResearchMatch, a national health research registry. Descriptive analyses were conducted to assess survey participant demographics. Logistic regression was conducted to assess the association between participants’ five distinct privacy-related experiences and their willingness to share each of the 19 data sources with researchers, adjusting for education level and age range. Results: A total of 598 ResearchMatch adults were contacted and 402 completed the survey. Most respondents were over the age of 51 years (49% total) and held a master’s or bachelor’s degree (63% total). Over half of participants (54%) had their account accessed by someone without their permission. Almost half of participants (49%) reported the privacy of their personal information being violated. Analyses showed that, when adjusted for age range and education level, participants whose reputations were negatively affected as a result of information posted online were more likely to share electronic medical record data (OR = 2.074, 95% CI: 0.986–4.364) and genetic data (OR = 2.302, 95% CI: 0.894–5.93) versus those without this experience. Among participants who had an unpleasant experience as a result of giving out information online, those with some college/associates/trade school compared to those with a doctoral or other terminal degree were significantly more willing to share genetic data (OR = 1.064, 95% CI: 0.396–2.857). Across all privacy-related experiences, participants aged 18 to 30 were significantly more likely than those over 60 years to share music streaming data, ridesharing history data, and voting history data. Additionally, across all privacy-related experiences, those with a high school education were significantly more likely than those with a doctorate or other terminal degree to share credit card statement data. Conclusions: This study offers the first insights into how privacy-related experiences, adjusted for age range and education level, may shape ResearchMatch participants’ willingness to share several sources of real-world data sources with precision medicine researchers. Future work should further explore these insights.

Designing, Developing, Evaluating, and Implementing a Smartphone-Delivered, Rule-Based Conversational Agent (DISCOVER): Development of a Conceptual Framework

BACKGROUND

Conversational agents (CAs), also known as chatbots, are computer programs that simulate human conversations by using predetermined rule-based responses or artificial intelligence algorithms. They are increasingly used in health care, particularly via smartphones. There is, at present, no conceptual framework guiding the development of smartphone-based, rule-based CAs in health care. To fill this gap, we propose structured and tailored guidance for their design, development, evaluation, and implementation.

OBJECTIVE

The aim of this study was to develop a conceptual framework for the design, evaluation, and implementation of smartphone-delivered, rule-based, goal-oriented, and text-based CAs for health care.

METHODS

We followed the approach by Jabareen, which was based on the grounded theory method, to develop this conceptual framework. We performed 2 literature reviews focusing on health care CAs and conceptual frameworks for the development of mobile health interventions. We identified, named, categorized, integrated, and synthesized the information retrieved from the literature reviews to develop the conceptual framework. We then applied this framework by developing a CA and testing it in a feasibility study.

RESULTS

The Designing, Developing, Evaluating, and Implementing a Smartphone-Delivered, Rule-Based Conversational Agent (DISCOVER) conceptual framework includes 8 iterative steps grouped into 3 stages, as follows: design, comprising defining the goal, creating an identity, assembling the team, and selecting the delivery interface; development, including developing the content and building the conversation flow; and the evaluation and implementation of the CA. They were complemented by 2 cross-cutting considerations-user-centered design and privacy and security-that were relevant at all stages. This conceptual framework was successfully applied in the development of a CA to support lifestyle changes and prevent type 2 diabetes.

CONCLUSIONS

Drawing on published evidence, the DISCOVER conceptual framework provides a step-by-step guide for developing rule-based, smartphone-delivered CAs. Further evaluation of this framework in diverse health care areas and settings and for a variety of users is needed to demonstrate its validity. Future research should aim to explore the use of CAs to deliver health care interventions, including behavior change and potential privacy and safety concerns.

Rebuilding Stakeholder Confidence in Health-Relevant Big Data Applications: A Social Representations Perspective

Big data applications are at the epicentre of recent breakthroughs in digital health. However, controversies over privacy, security, ethics, accountability, and data governance have tarnished stakeholder trust, leaving health-relevant big data projects under threat, delayed, or abandoned. Taking the notion of big data as social construction, this work explores the social representations of the big data concept from the perspective of stakeholders in Kenya’s digital health environment. Through analysing the similarities and differences in the way health professionals and information technology (IT) practitioners comprehend the idea of big data, we draw strategic implications for restoring confidence in big data initiatives. Respondents associated big data with a multiplicity of concepts and were conflicted in how they represented big data’s benefits and challenges. On this point, we argue that peculiarities and nuances in how diverse players view big data contribute to the erosion of trust and the need to revamp stakeholder engagement practices. Specifically, decision makers should complement generalised informational campaigns with targeted, differentiated messages designed to address data responsibility, access, control, security, or other issues relevant to a specialised but influential community.

Design, Implementation, and Outcomes of a Volunteer-Staffed Case Investigation and Contact Tracing Initiative at an Urban Academic Medical Center

IMPORTANCE

The COVID-19 pandemic has claimed nearly 6 million lives globally as of February 2022. While pandemic control efforts, including contact tracing, have traditionally been the purview of state and local health departments, the COVID-19 pandemic outpaced health department capacity, necessitating actions by private health systems to investigate and control outbreaks, mitigate transmission, and support patients and communities.

OBJECTIVE

To investigate the process of designing and implementing a volunteer-staffed contact tracing program at a large academic health system from April 2020 to May 2021, including program structure, lessons learned through implementation, results of case investigation and contact tracing efforts, and reflections on how constrained resources may be best allocated in the current pandemic or future public health emergencies.

DESIGN, SETTING, AND PARTICIPANTS

This case series study was conducted among patients at the University of Pennsylvania Health System and in partnership with the Philadelphia Department of Public Health. Patients who tested positive for COVID-19 were contacted to counsel them regarding safe isolation practices, identify and support quarantine of their close contacts, and provide resources, such as food and medicine, needed during isolation or quarantine.

RESULTS

Of 5470 individuals who tested positive for COVID-19 and received calls from a volunteer, 2982 individuals (54.5%; median [range] age, 42 [18-97] years; 1628 [59.4%] women among 2741 cases with sex data) were interviewed; among 2683 cases with race data, there were 110 Asian individuals (3.9%), 1476 Black individuals (52.7%), and 817 White individuals (29.2%), and among 2667 cases with ethnicity data, there were 366 Hispanic individuals (13.1%) and 2301 individuals who were not Hispanic (82.6%). Most individuals lived in a household with 2 to 5 people (2125 of 2904 individuals with household data [71.6%]). Of 3222 unique contacts, 1780 close contacts (55.2%; median [range] age, 40 [18-97] years; 866 [55.3%] women among 1565 contacts with sex data) were interviewed; among 1523 contacts with race data, there were 69 Asian individuals (4.2%), 705 Black individuals (43.2%), and 573 White individuals (35.1%), and among 1514 contacts with ethnicity data, there were 202 Hispanic individuals (12.8%) and 1312 individuals (83.4%) who were not Hispanic. Most contacts lived in a household with 2 to 5 people (1123 of 1418 individuals with household data [79.2%]). Of 3324 cases and contacts who completed a questionnaire on unmet social needs, 907 (27.3%) experienced material hardships that would make it difficult for them to isolate or quarantine safely. Such hardship was significantly less common among White compared with Black participants (odds ratio, 0.20; 95% CI, 0.16-0.25).

CONCLUSIONS AND RELEVANCE

These findings demonstrate the feasibility and challenges of implementing a case investigation and contact tracing program at an academic health system. In addition to successfully engaging most assigned COVID-19 cases and close contacts, contact tracers shared health information and material resources to support isolation and quarantine, thus filling local public health system gaps and supporting local pandemic control.

Digital Health Competencies Among Health Care Professionals: Systematic Review

Background

Digitalization is not fully implemented in clinical practice, and several factors have been identified as possible barriers, including the competencies of health care professionals. However, no summary of the available evidence has been provided to date to depict digital health competencies that have been investigated among health care professionals, the tools used in assessing such competencies, and the effective interventions to improve them.

Objective

This review aims to summarize digital health competencies investigated to date and the tools used to assess them among health care professionals.

Methods

A systematic review based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist was performed. The MEDLINE, Cumulative Index to Nursing and Allied Health Literature, PsycINFO, and Scopus databases were accessed up to September 4, 2021. Studies assessing digital health competencies with quantitative designs, targeting health care professionals, and written in English were included. The methodological quality of included studies was evaluated using the Joanna Briggs Institute tools.

Results

A total of 26 studies, published from 1999 to 2021, met the inclusion criteria, and the majority were cross sectional in design, while only 2 were experimental study designs. Most studies were assessed with moderate to low methodological quality; 4 categories and 9 subcategories of investigated digital health competencies have been identified. The most investigated category was “Self-rated competencies,” followed by “Psychological and emotional aspects toward digital technologies,” “Use of digital technologies,” and “Knowledge about digital technologies.” In 35% (9/26) of the studies, a previously validated tool was used to measure the competencies assessed, while others developed ad hoc questionnaires.

Conclusions

Mainly descriptive studies with issues regarding methodology quality have been produced to date investigating 4 main categories of digital health competencies mostly with nonvalidated tools. Competencies investigated might be considered while designing curricula for undergraduate, postgraduate, and continuing education processes, whereas the methodological lacks detected might be addressed with future research. There is a need to expand research on psychological and emotional elements and the ability to use digital technology to self-learn and teach others.

Trial Registration

PROSPERO International Prospective Register of Systematic Reviews CRD42021282775; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=282775

Toward a digital citizen lab for capturing data about alternative ways of self-managing chronic pain: An attitudinal user study

Background

Myriad psychosocial and cultural factors influence personal ways of coping with chronic pain (CP). Mobile health (mHealth) apps facilitate creation of citizen laboratories outside clinical frameworks. However, issues of safety, privacy and technostress must be addressed. This attitudinal user study aimed to assess whether persons with persistent pain (PwPP) would be open to sharing qualitative and quantitative data about their self-management of CP via mHealth platforms.

Methods

In March 2020, we invited PwPPs, their personal or medical caregivers, or those interested in the development of an app for researching alternative ways of self-managing CP to complete an anonymous survey. We formulated an attitudinal survey within the theoretical framework of stress to estimate whether the novelty, unpredictability, and risks of data-sharing via mHealth apps concerned users. Descriptive statistics (% Part/Group) were used to interpret the survey, and open comments were reflectively analyzed to identify emerging themes.

Results

Of 202 responses (June 2021), 127 identified as PwPPs (average age 43.86 ± 14.97; 100/127 female), and listed several primary and secondary CP diagnoses. In almost 90% of PwPPs, physical and emotional wellbeing were affected by CP. More than 90% of PwPPs used alternative therapies (acupuncture, homeopathy, massage therapy, etc.). Attitude toward mHealth apps were positive even though nearly half of PwPPs were unfamiliar with them. More than 72% of respondents were open to using a health-related app as a research tool for data collection in real life situations. Comprehensive data collection (especially about psychosocial factors) was the most important requirement. More respondents (especially medical professionals) were concerned about health hazards of misinformation communicated via health-related information and communication systems (maximum 80%) than about privacy (maximum 40%). Qualitative analyses revealed several promises and impediments to creation of data-sharing platforms for CP.

Conclusions

This study shows a general willingness among PwPPs to become partners in studying alternative pain management. Despite a generally positive attitude toward the concept of sharing complex personal data to advance research, heterogeneity of attitudes shaped by personal experiences must be considered. Our study underlines the need for any digital strategy for CP research to be person-centered and flexible.

Digital cognitive testing using a tablet-based app in patients with brain tumors: a single-center feasibility study comparing the app to the gold standard

OBJECTIVE

Healthcare digitization has led to increasing tablet-based apps to improve diagnostics, self-discipline, and well-being in patients. Moreover, patient-reported outcome measures are crucial for optimized treatment, with superior applicability if independent from patient visits. Whereas most uses cover health maintenance, only a few studies have focused on cognitive testing in neurosurgical patients despite its nature as one of the most integrative outcome measures in neurooncology.

METHODS

The authors performed a prospective single-center feasibility study including neurosurgical patients affected by intraaxial tumors and healthy subjects, testing cognitive function by using a digitized app-based approach and conventional paper-and-pencil (PP) tests. Healthy subjects underwent follow-up testing for retest reliability.

RESULTS

The authors included 24 patients with brain tumor and 10 healthy subjects, all of whom completed both tests. Equivalent mean performance results were found in the tablet-based digital app and PP counterparts; whereas the digital approach had shorter test duration in patients (29.9 minutes for PP vs 21.9 minutes for app, p = 0.019) and in the healthy cohort (23.2 minutes for PP vs 16.4 minutes for app, p = 0.003), patients with brain tumor scored lower when both test strategies were applied. Results were consistent in healthy subjects after a median of 3 months.

CONCLUSIONS

Cognitive function assessment is feasible using a digitized tablet-based app, with equivalent results to those of PP tests in healthy subjects and patients with brain tumor. Thus, this approach allows much closer follow-up independent of patient visits and might provide a viable option to improve patient follow-ups.

Passive Data Use for Ethical Digital Public Health Surveillance in a Postpandemic World

There is a fundamental need to establish the most ethical and effective way of tracking disease in the postpandemic era. The ubiquity of mobile phones is generating large amounts of passive data (collected without active user participation) that can be used as a tool for tracking disease. Although discussions of pragmatism or economic issues tend to guide public health decisions, ethical issues are the foremost public concern. Thus, officials must look to history and current moral frameworks to avoid past mistakes and ethical pitfalls. Past pandemics demonstrate that the aftermath is the most effective time to make health policy decisions. However, an ethical discussion of passive data use for digital public health surveillance has yet to be attempted, and little has been done to determine the best method to do so. Therefore, we aim to highlight four potential areas of ethical opportunity and challenge: (1) informed consent, (2) privacy, (3) equity, and (4) ownership.

Management of Medico-Legal Risks in Digital Health Era: A Scoping Review

Artificial intelligence needs big data to develop reliable predictions. Therefore, storing and processing health data is essential for the new diagnostic and decisional technologies but, at the same time, represents a risk for privacy protection. This scoping review is aimed at underlying the medico-legal and ethical implications of the main artificial intelligence applications to healthcare, also focusing on the issues of the COVID-19 era. Starting from a summary of the United States (US) and European Union (EU) regulatory frameworks, the current medico-legal and ethical challenges are discussed in general terms before focusing on the specific issues regarding informed consent, medical malpractice/cognitive biases, automation and interconnectedness of medical devices, diagnostic algorithms and telemedicine. We aim at underlying that education of physicians on the management of this (new) kind of clinical risks can enhance compliance with regulations and avoid legal risks for the healthcare professionals and institutions.

Consumer Willingness to Share Personal Digital Information for Health-Related Uses

IMPORTANCE

Consumers routinely generate digital information that reflects on their health.

OBJECTIVE

To evaluate the factors associated with consumers' willingness to share their digital health information for research, health care, and commercial uses.

DESIGN, SETTING, AND PARTICIPANTS

This national survey with an embedded conjoint experiment recruited US adults from a nationally representative sample, with oversampling of Black and Hispanic panel members. Participants were randomized to 15 scenarios reflecting use cases for consumer digital information from a total of 324 scenarios. Attributes of the conjoint analysis included 3 uses, 3 users, 9 sources of digital information, and 4 relevant health conditions. The survey was conducted from July 10 to 31, 2020.

MAIN OUTCOMES AND MEASURES

Participants rated each conjoint profile on a 5-point Likert scale (1-5) measuring their willingness to share their personal digital information (with 5 indicating the most willingness to share). Results reflect mean differences in this scale from a multivariable regression model.

RESULTS

Among 6284 potential participants, 3543 (56%) responded. A total of 1862 participants (53%) were female, 759 (21%) identified as Black, 834 (24%) identified as Hispanic, and 1274 (36%) were 60 years or older. In comparison with information from electronic health care records, participants were less willing to share information about their finances (coefficient, -0.56; 95% CI, -0.62 to -0.50), places they visit from public cameras (coefficient, -0.28; 95% CI, -0.33 to -0.22), communication on social media (coefficient, -0.20; 95% CI -0.26 to -0.15), and their search history from internet search engines (coefficient, -0.11; 95% CI, -0.17 to -0.06). They were more willing to share information about their steps from applications on their phone (coefficient, 0.22; 95% CI, 0.17-0.28). Among the conjoint attributes, the source of information (importance weight: 59.1%) was more important than the user (17.3%), use (12.3%), and health condition (11.3%). Four clusters of consumers emerged from the sample with divergent privacy views. While the context of use was important, these 4 groups expressed differences in their overall willingness to share, with 337 participants classified as never share; 1116 classified as averse to sharing (mean rating, 1.64; 95% CI, 1.62-1.65); 1616 classified as uncertain about sharing (mean rating, 2.84; 95% CI, 2.81-2.86); and 474 classified as agreeable to sharing (mean rating, 4.18; 95% CI, 4.16-4.21). Respondents who identified as White and non-Hispanic, had higher income, and were politically conservative were more likely to be in a cluster that was less willing to share (ie, never or averse clusters).

CONCLUSIONS AND RELEVANCE

These findings suggest that although consumers' willingness to share personal digital information for health purposes is associated with the context of use, many have strong underlying privacy views that affect their willingness to share. New protections may be needed to give consumers confidence to be comfortable sharing their personal information.

Determinants of the Intention to Use Smart Healthcare Devices: A Framework and Public Policy Implications

Healthcare industry is strongly influenced by new digital technologies. In this context, this study creates a framework and explores determinants of the intention to use smart healthcare devices. Several factors were identified, including usefulness, convenience, novelty, price, technological complexity, and perceived privacy risks of smart devices. Based on the samples from China, we find that usefulness, convenience, and novelty have positive influences on the intention to use smart healthcare devices. However, technological complexity is negatively related to the intention to use smart devices. The results further extend previous researches in the area of the healthcare industry.

Health Information Privacy, Protection, and Use in the Expanding Digital Health Ecosystem: A Position Paper of the American College of Physicians

Technologic advancements and the evolving digital health landscape have offered innovative solutions to several of our health care system's issues as well as increased the number of digital interactions and type of personal health information that is generated and collected, both within and outside of traditional health care. This American College of Physicians' position paper discusses the state of privacy legislation and regulations, highlights existing gaps in health information privacy protections, and outlines policy principles and recommendations for the development of health information privacy and security protections that are comprehensive, transparent, understandable, adaptable, and enforceable. The principles and recommendations aim to improve on the privacy framework in which physicians have practiced for decades and expand similar privacy guardrails to entities not currently governed by privacy laws and regulations. The expanded privacy framework should protect personal health information from unauthorized, discriminatory, deceptive, or harmful uses and align with the principles of medical ethics, respect individual rights, and support the culture of trust necessary to maintain and improve care delivery.

Consumer Views on Health Applications of Consumer Digital Data and Health Privacy Among US Adults: Qualitative Interview Study

BACKGROUND

In 2020, the number of internet users surpassed 4.6 billion. Individuals who create and share digital data can leave a trail of information about their habits and preferences that collectively generate a digital footprint. Studies have shown that digital footprints can reveal important information regarding an individual's health status, ranging from diet and exercise to depression. Uses of digital applications have accelerated during the COVID-19 pandemic where public health organizations have utilized technology to reduce the burden of transmission, ultimately leading to policy discussions about digital health privacy. Though US consumers report feeling concerned about the way their personal data is used, they continue to use digital technologies.

OBJECTIVE

This study aimed to understand the extent to which consumers recognize possible health applications of their digital data and identify their most salient concerns around digital health privacy.

METHODS

We conducted semistructured interviews with a diverse national sample of US adults from November 2018 to January 2019. Participants were recruited from the Ipsos KnowledgePanel, a nationally representative panel. Participants were asked to reflect on their own use of digital technology, rate various sources of digital information, and consider several hypothetical scenarios with varying sources and health-related applications of personal digital information.

RESULTS

The final cohort included a diverse national sample of 45 US consumers. Participants were generally unaware what consumer digital data might reveal about their health. They also revealed limited knowledge of current data collection and aggregation practices. When responding to specific scenarios with health-related applications of data, they had difficulty weighing the benefits and harms but expressed a desire for privacy protection. They saw benefits in using digital data to improve health, but wanted limits to health programs' use of consumer digital data.

CONCLUSIONS

Current privacy restrictions on health-related data are premised on the notion that these data are derived only from medical encounters. Given that an increasing amount of health-related data is derived from digital footprints in consumer settings, our findings suggest the need for greater transparency of data collection and uses, and broader health privacy protections.

Consumer Views on Using Digital Data for COVID-19 Control in the United States

IMPORTANCE

Curbing COVID-19 transmission is currently the greatest global public health challenge. Consumer digital tools used to collect data, such as the Apple-Google digital contact tracing program, offer opportunities to reduce COVID-19 transmission but introduce privacy concerns.

OBJECTIVE

To assess uses of consumer digital information for COVID-19 control that US adults find acceptable and the factors associated with higher or lower approval of use of this information.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional survey study obtained data from a nationally representative sample of 6284 US adults recruited by email from the web-based Ipsos KnowledgePanel in July 2020. Respondents evaluated scenarios reflecting uses of digital data for COVID-19 control (case identification, digital contact tracing, policy setting, and enforcement of quarantines).

MAIN OUTCOMES AND MEASURES

Levels of support for use of personal digital data in 9 scenarios to mitigate the spread of COVID-19 infection, rated on a Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Multivariable linear regression models were fitted for each scenario and included factors hypothesized to be associated with views about digital data use for COVID-19 mitigation measures. Black and Hispanic survey respondents were oversampled; thus, poststratification weights were used so that results are representative of the general US population.

RESULTS

Of 6284 individuals invited to participate in the study, 3547 responded, for a completion rate of 56%. A total of 1762 participants (52%) were female, 715 (21%) identified as Black, 790 (23%) identified as Hispanic, and 1224 (36%) were 60 years or older; mean (SD) age was 51.7 (16.6) years. Approval of scenarios was low, ranging from 28% to 43% (52%-67% when neutral responses were included). Differences were found based on digital data source (smartphone vs social media: coefficient, 0.29 [95% CI, 0.23-0.35]; P < .001; smart thermometer vs social media: coefficient, 0.09 [95% CI, 0.03-0.16]; P = .004). County COVID-19 rates (coefficient, -0.02; 95% CI, -0.16 to 0.13 for quartile 4 compared with quartile 1) and prior family diagnosis of COVID-19 (coefficient, 0.00; 95% CI, -0.25 to 0.25) were not associated with support. Compared with self-described liberal individuals, conservative (coefficient, -0.81; 95% CI, -0.96 to -0.66; P < .001) and moderate (coefficient, -0.52; 95% CI, -0.67 to -0.38; P < .001) individuals were less likely to support the scenarios. Similarly, large political differences were observed in support of the Apple-Google digital contact tracing program, with less support from conservative (coefficient, -0.99; 95% CI, -1.11 to -0.87; P < .001) and moderate (coefficient, -0.59; 95% CI, -0.69 to -0.48; P < .001) individuals compared with liberal individuals. Respondents from racial/ethnic minority groups were more supportive of the scenarios than were White, non-Hispanic respondents. For example, compared with White respondents, Black respondents were more supportive of the Apple-Google contact tracing program (coefficient, 0.20; 95% CI, 0.07-0.32; P = .002).

CONCLUSIONS AND RELEVANCE

In this survey study of US adults, many were averse to their information being used on digital platforms to mitigate transmission of COVID-19. These findings suggest that in current and future pandemics, public health departments should use multiple strategies to gain public trust and accelerate adoption of tools such as digital contact tracing applications.

Artificial intelligence in medicine: A matter of joy or concern?

Artificial Intelligence (AI), a concept which dates back to the 1950s, is increasingly being developed by many medical specialties, especially those based on imaging or surgery. While the cognitive component of AI is far superior to that of human intelligence, it lacks consciousness, feelings, intuition and adaptation to unexpected situations. Furthermore, fundamental questions arise with regard to data security, the impact on healthcare professions, and the distribution of roles between physicians and AI especially concerning consent to medical care and liability in the event of a therapeutic accident.