Sociodemographic characteristics determine download and use of a Corona contact tracing app in Germany-Results of the COSMO surveys

The Saudi Community View of the Use of Artificial Intelligence in Health Care

OBJECTIVES

Artificial intelligence (AI) holds the promise to revolutionize the field of medicine and enhance the well-being of countless patients. Its capabilities span various areas, including disease prevention, accurate diagnosis, and the development of innovative treatments. Moreover, AI has the potential to streamline health-care delivery and lower expenses. The community should be aware of the potential applications of AI in health care, so that they can advocate for its development and adoption. Hence, the objective of this study is to assess the community's perspectives regarding the utilization of AI in health care.

METHODS

A cross-sectional, questionnaire-based study was conducted in Saudi Arabia during the period of June to October 2023. The questionnaire was distributed to people on various social media platforms using a convenience sampling method. The collected data were analyzed using Statistical Package for the Social Sciences.

RESULTS

The study included 771 individuals, with 42.5% having a positive outlook on the use of AI in health care, 31.8% having a neutral view, and 7.5% having a negative view. The only factor associated with a positive opinion was regional differences (P = 0.006). Moreover, participants who used medical apps or programs (P = 0.026), wearables (P = 0.027), felt more confident in using technology (P < 0.001), enjoyed using technology (P < 0.001), found it easier to familiarize themselves with new devices or programs (P < 0.001), and had more knowledge about AI (P < 0.001) had more positive opinions regarding the use of AI in health care.

CONCLUSIONS

The study found that most Saudis, especially those who were familiar with the use of technology, support the use of AI in health care, with a positive or neutral view. Yet, targeted campaigns in certain regions are needed to educate the entire community about AI's potential benefits.

Ethics of Nudging in the COVID-19 Crisis and the Necessary Return to the Principles of Shared Decision Making: A Critical Review

Nudging, a controversial technique for modifying people's behavior in a predictable way, is claimed to preserve freedom of choice while simultaneously influencing it. Nudging had been largely confined to situations such as promoting healthy eating choices but has been employed in the coronavirus disease 2019 (COVID-19) crisis in a shift towards measures that involve significantly less choice, such as shoves and behavioral prods. Shared decision making (SDM), a method for direct involvement and autonomy, is an alternative approach to communicate risk. Predominantly peer-reviewed scientific publications from standard literature databases like PubMed, PsycInfo, and Psyndex were evaluated in a narrative review. The so-called fear nudges, as well as the dissemination of strongly emotionalizing or moralizing messages can lead to intense psycho-physical stress. The use of these nudges by specialized units during the COVID-19 pandemic generated a societal atmosphere of fear that precipitated a deterioration of the mental and physical health of the population. Major recommendations of the German COVID-19 Snapshot Monitoring (COSMO) study, which are based on elements of nudging and coercive measures, do not comply with ethical principles, basic psychological principles, or evidence-based data. SDM was misused in the COVID-19 crisis, which helped to achieve one-sided goals of governments. The emphasis on utilitarian thinking is criticized and the unethical behavior of decision makers is explained by both using the concept of moral disengagement and the maturity level of coping strategies. There should be a return to an open-ended, democratic, and pluralistic scientific debate without using nudges. It is therefore necessary to return to the origins of SDM.

[Developments in the digitalization of public health since 2020 : Examples from the Leibniz ScienceCampus Digital Public Health Bremen]

Digital public health has received a significant boost in recent years, especially due to the demands associated with the COVID-19 pandemic. In this report, we provide an overview of the developments in digitalization in the field of public health in Germany since 2020 and illustrate these with examples from the Leibniz ScienceCampus Digital Public Health Bremen (LSC DiPH).The following topics are central: How do digital survey methods as well as digital biomarkers and artificial intelligence methods shape modern epidemiology and prevention research? What is the status of digitalization in public health offices? Which approaches to health economics evaluation of digital public health interventions have been utilized so far? What is the status of training and further education in digital public health?The first years of the Leibniz ScienceCampus Digital Public Health Bremen (LSC DiPH) were also strongly influenced by the COVID-19 pandemic. Repeated population-based digital surveys of the LSC indicated an increase in use of health apps in the population, for example, in applications to support physical activity. The COVID-19-pandemic has also shown that the digitalization of public health enhances the risk of misinformation and disinformation.

Sociodemographic factors and health digital divide among urban residents: Evidence from a population-based survey in China

Background

The deep integration of digital technology and healthcare services has propelled the healthcare system into the era of digital health. However, vulnerable populations in the field of information technology, they face challenges in benefiting from the digital dividends brought by digital health, leading to the emerging phenomenon of the "health digital divide."

Methods

This study utilized the sample of 3547 urban from the 2021 Chinese Social Survey data for analysis. Models were constructed with digital access divide, digital usage divide, and digital outcome divide for urban residents, and structural equation modeling was implemented for analysis.

Results

The impact β coefficients (95% CI) of urban residents' digital access on the frequency of digital use, internet healthcare utilization, and patient experience were (β = 0.737, P < 0.001), (β = 0.047, P < 0.05), and (β = 0.079, P < 0.001), respectively. Urban elderly groups were at a disadvantage in digital access and usage (β = -0.007, β = -0.024, and β = -0.004), as well as those with lower educational levels (β = 0.109, β = 0.162, and β = 0.045). However, these two factors did not have a significant direct impact on the patient experience in urban areas.

Conclusions

The health digital divide of urban residents exhibits a cascading effect, primarily manifested in the digital access and usage divide. To bridge health digital divide among urban residents, efforts must be made to improve digital access and usage among the elderly and those with lower educational levels.

Did the design and planning of testing and contact tracing interventions for COVID-19 consider social inequalities in health? A multiple case study from Brazil, Canada, France & Mali

The COVID-19 pandemic has led to an unprecedented global crisis. It has exposed and exacerbated weaknesses in public health systems worldwide, particularly with regards to reaching the most vulnerable populations, disproportionately impacted by the pandemic. The objective of our study was to examine whether and how social inequalities in health (SIH) were considered in the design and planning of public health responses to COVID-19 in jurisdictions of Brazil, Canada, France, and Mali. This article reports on a qualitative multiple case study of testing and contact tracing interventions in regions with high COVID-19 incidence in each country, namely: Manaus (Brazil), Montréal (Canada), Île-de-France (France), and Bamako (Mali). We conducted interviews with 108 key informants involved in these interventions in the four jurisdictions, focusing on the first and second waves of the pandemic. We analyzed our data thematically using a theoretical bricolage framework. Our analysis suggests that the lack of a common understanding of SIH among all actors involved and the sense of urgency brought by the pandemic eclipsed the prioritization of SIH in the initial responses. The pandemic increased intersectoral collaboration, but decision-making power was often unequal between Ministries of Health and other actors in each jurisdiction. Various adaptations to COVID-19 interventions were implemented to reach certain population groups, therefore improving the accessibility, availability, and acceptability of testing and contact tracing. Our study contributes to identifying lessons learned from the current pandemic, namely that the ways in which SIH are understood shape how interventions are planned; that having clear guidelines on how to integrate SIH into public health interventions could lead to more inclusive pandemic responses; that for intersectoral collaboration to be fruitful, there needs to be sufficient resources and equitable decision-making power between partners; and that interventions must be flexible to respond to emerging needs while considering long-standing structural inequalities.

User Compliance With the Health Emergency and Disaster Management System: Systematic Literature Review

BACKGROUND

Health-related hazards have a detrimental impact on society. The health emergency and disaster management system (Health EDMS), such as a contact-tracing application, is used to respond to and cope with health-related hazards. User compliance with Health EDMS warnings is key to its success. However, it was reported that user compliance with such a system remains low.

OBJECTIVE

Through a systematic literature review, this study aims to identify the theories and corresponding factors that explain user compliance with the warning message provided by Health EDMS.

METHODS

The systematic literature review was conducted using Preferred Reporting Items for Systematic reviews and Meta-Analyses 2020 guidelines. The search was performed using the online databases Scopus, ScienceDirect, ProQuest, IEEE, and PubMed, for English journal papers published between January 2000 and February 2022.

RESULTS

A total of 14 papers were selected for the review based on our inclusion and exclusion criteria. Previous research adopted 6 theories when examining user compliance, and central to the research was Health EDMS. To better understand Health EDMS, based on the literature reviewed, we mapped the activities and features of Health EDMS with the key stakeholders involved. We identified features that require involvement from individual users, which are surveillance and monitoring features and medical care and logistic assistance features. We then proposed a framework showing the individual, technological, and social influencing factors of the use of these features, which in turn affects compliance with the warning message from Health EDMS.

CONCLUSIONS

Research on the Health EDMS topic increased rapidly in 2021 due to the COVID-19 pandemic. An in-depth understanding of Health EDMS and user compliance before designing the system is essential for governments and developers to increase the effectiveness of Health EDMS. Through a systematic literature review, this study proposed a research framework and identified research gaps for future research on this topic.

The German COVID-19 Digital Contact Tracing App: A Socioeconomic Evaluation

The COVID-19 pandemic posed challenges to governments in terms of contact tracing. Like many other countries, Germany introduced a mobile-phone-based digital contact tracing solution ("Corona Warn App"; CWA) in June 2020. At the time of its release, however, it was hard to assess how effective such a solution would be, and a political and societal debate arose regarding its efficiency, also in light of its high costs. This study aimed to analyze the effectiveness of the CWA, considering prevented infections, hospitalizations, intensive care treatments, and deaths. In addition, its efficiency was to be assessed from a monetary point of view, and factors with a significant influence on the effectiveness and efficiency of the CWA were to be determined. Mathematical and statistical modeling was used to calculate infection cases prevented by the CWA, along with the numbers of prevented complications (hospitalizations, intensive care treatments, deaths) using publicly available CWA download numbers and incidences over time. The monetized benefits of these prevented cases were quantified and offset against the costs incurred. Sensitivity analysis was used to identify factors critically influencing these parameters. Between June 2020 and April 2022, the CWA prevented 1.41 million infections, 17,200 hospitalizations, 4600 intensive care treatments, and 7200 deaths. After offsetting costs and benefits, the CWA had a net present value of EUR 765 m in April 2022. Both the effectiveness and efficiency of the CWA are decisively and disproportionately positively influenced by the highest possible adoption rate among the population and a high rate of positive infection test results shared via the CWA.

The Impact of Digital Contact Tracing Apps Overuse on Prevention of COVID-19: A Normative Activation Model Perspective

During the COVID-19 pandemic, many countries have used digital contact tracing apps (DCTAs) to implement contact tracing. Although the use of DCTAs has contributed to the prevention and control of COVID-19, there are doubts in academia about their actual effectiveness. In this study, the role of DCTAs in the prevention of COVID-19 was analyzed in terms of both the responsibility and inconvenience to life in a large-scale DCTA overuse environment, based on the normative activation model. The findings suggest that the overuse of a DCTA activates people’s personal norms by triggering awareness of the consequences and ascription of responsibility, leading people to consistently cooperate with the government to prevent COVID-19. However, the inconvenience of living with DCTA overuse weakens the effect of the awareness of consequences and ascription of responsibility and the role of the ascription of responsibility in influencing personal norms. These effects may bear on people’s willingness to consistently cooperate with the government to prevent COVID-19. The results of this study confirm the effectiveness of DCTA in counteracting pandemics from a social responsibility perspective in a large-scale environment where DCTA is used, enriching the literature on DCTA research in the COVID-19 pandemic. The results of this study can also help governments develop and improve policies to prevent COVID-19, as well as improve the DCTAs’ operating patterns.

The Association between mHealth App Use and Healthcare Satisfaction among Clients at Outpatient Clinics: A Cross-Sectional Study in Inner Mongolia, China

Mobile health (mHealth) applications (apps) have been developed in hospital settings to allocate and manage medical care services, which is one of the national strategies to improve health care in China. Little is known about the comprehensive effects of hospital-based mHealth app use on client satisfaction. The aim of this study was to determine the relationship between the full range of mHealth app use and satisfaction domains among clients attending outpatient clinics. A cross-sectional survey was conducted from January to February 2021 in twelve tertiary hospitals in Inner Mongolia. After the construction of the mHealth app use, structural equation modeling was used for data analysis. Of 1889 participants, the standardized coefficients β on environment/convenience, health information, and medical service fees were 0.11 (p < 0.001), 0.06 (p = 0.039), and 0.08 (p = 0.004), respectively. However, app use was not significantly associated with satisfaction of doctor−patient communication (β = 0.05, p = 0.069), short-term outcomes (β = 0.05, p = 0.054), and general satisfaction (β = 0.02, p = 0.429). Clients of the study hospitals were satisfied with the services, but their satisfaction was not much associated with mHealth use. The limitation of the mHealth system should be improved to enhance communication and engagement among clients, doctors, and healthcare givers, as well as to pay more attention to health outcomes and satisfaction of clients.

Strategies to successfully prevent COVID-19 outbreak in vulnerable uro-oncology patient population

Purpose

As COVID-19 pandemic persists with variants, and despite effective vaccination campaigns, breakthrough infections surge. We implemented strategies to protect vulnerable patients of the uro-oncologic outpatient clinic. We adopted proactive non-symptomatic risk reduction measures, which include non-symptomatic testing requirements for both patients and health care professionals (HCP), intensified patient tracing and contact reduction by implementation of digital health options. Here, we present our best practice example to safely guide oncology professionals and patients with metastasized genitourinary cancers through the current and future pandemics.

Methods

Solely for this purpose, we created a registry of collected data (current telephone numbers, e-mail addresses, vaccination status). We collected a nasopharyngeal swab from every patient upon presentation for treatment. We implemented bi-weekly RNA-PCR assay tests for HCP with patient contact, and limited personal contact at our facility through digital patient consultations.

Results

We started implementing our COVID prevention model at the beginning of the second wave in September 2020 and included 128 patients with urologic malignancies requiring systemic treatment. After COVID vaccination became available in December 2020, all of our HCP were fully vaccinated within 6 weeks and 97% of our patients (125/128) within 9 months. We performed 1410 nasopharyngeal swabs during in-house visits, thereby detecting two COVID-19 infections among our patients, who both survived and successfully continued treatment. To further reduce personal contact, half of our consultations were fully operated digitally, with 76% (97/128) of our patients participating in our digital health offers.

Conclusion

The willingness of patients and HCPs to participate in the study allowed us to implement strict standards to prepare for the ongoing and future pandemics in outpatient cancer units. Next to general preventive measures such as frequent hand disinfection, wearing facial masks, and keeping distance, an important measure to protect vulnerable uro-oncology patients is the capability to perform virus genome sequencing to trace transmission chains.

Socio-demographic digital divide in mHealth app use among clients at outpatient departments in Inner Mongolia, China: a cross-sectional study (Preprint)

Background

Mobile health (mHealth) apps have become part of the infrastructure for access to health care in hospitals, especially during the COVID-19 pandemic. However, little is known about the effects of sociodemographic characteristics on the digital divide regarding the use of hospital-based mHealth apps and their benefits to patients and caregivers.

Objective

The aim of this study was to document the cascade of potential influences from digital access to digital use and then to mHealth use, as well as the potential influence of sociodemographic variables on elements of the cascade.

Methods

A cross-sectional survey was conducted from January to February 2021 among adult clients at outpatient departments in 12 tertiary hospitals of Inner Mongolia, China. Structural equation modeling was conducted after the construct comprising digital access, digital use, and mHealth use was validated.

Results

Of 2115 participants, the β coefficients (95% CI) of potential influence of digital access on digital use, and potential influence of digital use on mHealth use, were 0.28 (95% CI 0.22-0.34) and 0.51 (95% CI 0.38-0.64), respectively. Older adults were disadvantaged with regard to mHealth access and use (β=–0.38 and β=–0.41), as were less educated subgroups (β=–0.24 and β=–0.27), and these two factors had nonsignificant direct effects on mHealth use.

Conclusions

To overcome the mHealth use divide, it is important to improve digital access and digital use among older adults and less educated groups.

Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients

Objective

The attitudes about the usage of artificial intelligence in healthcare are controversial. Unlike the perception of healthcare professionals, the attitudes of patients and their companions have been of less interest so far. In this study, we aimed to investigate the perception of artificial intelligence in healthcare among this highly relevant group along with the influence of digital affinity and sociodemographic factors.

Methods

We conducted a cross-sectional study using a paper-based questionnaire with patients and their companions at a German tertiary referral hospital from December 2019 to February 2020. The questionnaire consisted of three sections examining (a) the respondents’ technical affinity, (b) their perception of different aspects of artificial intelligence in healthcare and (c) sociodemographic characteristics.

Results

From a total of 452 participants, more than 90% already read or heard about artificial intelligence, but only 24% reported good or expert knowledge. Asked on their general perception, 53.18% of the respondents rated the use of artificial intelligence in medicine as positive or very positive, but only 4.77% negative or very negative. The respondents denied concerns about artificial intelligence, but strongly agreed that artificial intelligence must be controlled by a physician. Older patients, women, persons with lower education and technical affinity were more cautious on the healthcare-related artificial intelligence usage.

Conclusions

German patients and their companions are open towards the usage of artificial intelligence in healthcare. Although showing only a mediocre knowledge about artificial intelligence, a majority rated artificial intelligence in healthcare as positive. Particularly, patients insist that a physician supervises the artificial intelligence and keeps ultimate responsibility for diagnosis and therapy.