Attitudes Toward Mobile Apps for Pandemic Research Among Smartphone Users in Germany: National Survey

Public perceptions and engagement in mHealth: a European survey on attitudes toward health apps use and data sharing

This study investigates public perceptions and engagement with mobile health (mHealth) across eight European countries: Italy, the Netherlands, France, Germany, Spain, Poland, Romania, and Hungary. The focus is on attitudes toward health app usage and data sharing, addressing data privacy and security concerns while highlighting generational and educational differences. A cross-sectional survey was conducted with 6581 participants from the selected countries. The survey assessed current usage of health apps, interest in future use, willingness to share health data, and concerns about data privacy. Demographic factors such as age, education level, and geographical location were analyzed to determine their influence on mHealth engagement. The survey revealed that 21.87% of respondents currently use health apps, while 42.71% expressed interest in future use. Regarding data sharing, 52.82% were willing to share health data with healthcare providers, and 25.48% with public and private research institutions. However, concerns about data misuse (72.34%) and hacking (63.68%) were prevalent. Significant generational differences emerged, with older generations showing lower adoption rates of health apps. Education level was a key factor; individuals with tertiary education were more likely to use health apps and demand transparency. The findings emphasize the need for targeted strategies to improve digital literacy, address privacy concerns, and ensure equitable access to mHealth technologies across Europe. Tailored interventions are essential to bridge generational and educational gaps in mHealth engagement while fostering trust in data security measures.

Disease Prediction Using Machine Learning on Smartphone-Based Eye, Skin, and Voice Data: Scoping Review

BACKGROUND

The application of machine learning methods to data generated by ubiquitous devices like smartphones presents an opportunity to enhance the quality of health care and diagnostics. Smartphones are ideal for gathering data easily, providing quick feedback on diagnoses, and proposing interventions for health improvement.

OBJECTIVE

We reviewed the existing literature to gather studies that have used machine learning models with smartphone-derived data for the prediction and diagnosis of health anomalies. We divided the studies into those that used machine learning models by conducting experiments to retrieve data and predict diseases, and those that used machine learning models on publicly available databases. The details of databases, experiments, and machine learning models are intended to help researchers working in the fields of machine learning and artificial intelligence in the health care domain. Researchers can use the information to design their experiments or determine the databases they could analyze.

METHODS

A comprehensive search of the PubMed and IEEE Xplore databases was conducted, and an in-house keyword screening method was used to filter the articles based on the content of their titles and abstracts. Subsequently, studies related to the 3 areas of voice, skin, and eye were selected and analyzed based on how data for machine learning models were extracted (ie, the use of publicly available databases or through experiments). The machine learning methods used in each study were also noted.

RESULTS

A total of 49 studies were identified as being relevant to the topic of interest, and among these studies, there were 31 different databases and 24 different machine learning methods.

CONCLUSIONS

The results provide a better understanding of how smartphone data are collected for predicting different diseases and what kinds of machine learning methods are used on these data. Similarly, publicly available databases having smartphone-based data that can be used for the diagnosis of various diseases have been presented. Our screening method could be used or improved in future studies, and our findings could be used as a reference to conduct similar studies, experiments, or statistical analyses.

Stakeholders' perceptions of personal health data sharing: A scoping review

The rapid advancement of digital health technologies has heightened demand for health data for secondary uses, highlighting the importance of understanding global perspectives on personal information sharing. This article examines stakeholder perceptions and attitudes toward the use of personal health data to improve personalized treatments, interventions, and research. It also identifies barriers and facilitators in health data sharing and pinpoints gaps in current research, aiming to inform ethical practices in healthcare settings that utilize digital technologies. We conducted a scoping review of peer reviewed empirical studies based on data pertaining to perceptions and attitudes towards sharing personal health data. The authors searched three electronic databases-Embase, MEDLINE, and Web of Science-for articles published (2015-2023), using terms relating to health data and perceptions. Thirty-nine articles met the inclusion criteria with sample size ranging from 14 to 29,275. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines for the design and analysis of this study. We synthesized the included articles using narrative analysis. The review captured multiple stakeholder perspectives with an up-to-date range of diverse barriers and facilitators that impact data-sharing behavior. The included studies were primarily cross-sectional and geographically concentrated in high-income settings; often overlooking diverse demographics and broader global health challenges. Most of the included studies were based within North America and Western Europe, with the United States (n = 8) and the United Kingdom (n = 7) representing the most studied countries. Many reviewed studies were published in 2022 (n = 11) and used quantitative methods (n = 23). Twenty-nine studies examined the perspectives of patients and the public while six looked at healthcare professionals, researchers, and experts. Many of the studies we reviewed reported overall positive attitudes about data sharing with variations around sociodemographic factors, motivations for sharing data, type and recipient of data being shared, consent preference, and trust.

Perception of middle-aged and older adults towards mHealth apps: A comparative factor analysis between Australia and Germany

OBJECTIVE

Although evidence of the global effectiveness and usability of mobile health (mHealth) apps as non-drug interventions is growing, older adults often demonstrate low adoption rates of these apps. This study aims to identify the perspectives of older adults on introducing and adopting mHealth apps in Australia and Germany.

MATERIALS AND METHODS

We conducted two online cross-sectional surveys to examine factors from contextual, technological and personal perspectives that influence older adults in mHealth app adoption. Using descriptive statistics, chi-square tests and exploratory factor analysis, we identified the differences and similarities between respondents' perspectives across two countries.

RESULTS

A total of 290 respondents (149, Australia; 141, Germany) completed the survey. Older adults' ability to use a mHealth app, the user-friendliness of the app, their positive self-efficacy regarding their health and resource availability for using mHealth apps were related to intended adoption. Differences between Germany and Australia were found in issues concerned with data sharing and empowerment by the doctor, while similarities were related to trust in the doctor and their treatment approaches.

DISCUSSION AND CONCLUSION

This study highlights participants' perspectives and attitudes towards mHealth app use, unmet needs and barriers, and the facilitating influences in the two countries. These insights can be used to inform the development and implementation of mHealth apps and to construct tailored strategies to increase the adoption rates of mHealth apps among older adults and to maximise their potential benefits.

Trust and Health Information Exchanges: Qualitative Analysis of the Intent to Share Personal Health Information

BACKGROUND

Digital health has the potential to improve the quality of care, reduce health care costs, and increase patient satisfaction. Patient acceptance and consent are a prerequisite for effective sharing of personal health information (PHI) through health information exchanges (HIEs). Patients need to form and retain trust in the system(s) they use to leverage the full potential of digital health. Germany is at the forefront of approving digital treatment options with cost coverage through statutory health insurance. However, the German population has a high level of technology skepticism and a low level of trust, providing a good basis to illuminate various facets of eHealth trust formation.

OBJECTIVE

In a German setting, we aimed to answer the question, How does an individual form a behavioral intent to share PHI with an HIE platform? We discussed trust and informed consent through (1) synthesizing the main influence factor models into a complex model of trust in HIE, (2) providing initial validation of influence factors based on a qualitative study with patient interviews, and (3) developing a model of trust formation for digital health apps.

METHODS

We developed a complex model of the formation of trust and the intent to share PHI. We provided initial validation of the influence factors through 20 qualitative, semistructured interviews in the German health care setting and used a deductive coding approach to analyze the data.

RESULTS

We found that German patients show a positive intent to share their PHI with HIEs under certain conditions. These include (perceived) information security and a noncommercial organization as the recipient of the PHI. Technology experience, age, policy and regulation, and a disposition to trust play an important role in an individual's privacy concern, which, combined with social influence, affects trust formation on a cognitive and emotional level. We found a high level of cognitive trust in health care and noncommercial research institutions but distrust in commercial entities. We further found that in-person interactions with physicians increase trust in digital health apps and PHI sharing. Patients' emotional trust depends on disposition and social influences. To form their intent to share, patients undergo a privacy calculus. Hereby, the individual's benefit (eg, convenience), benefits for the individual's own health, and the benefits for public welfare often outweigh the perceived risks of sharing PHI.

CONCLUSIONS

With the higher demand for timely PHI, HIE providers will need to clearly communicate the benefits of their solutions and their information security measures to health care providers (physicians, nursing and administrative staff) and patients and include them as key partners to increase trust. Offering easy access and educational measures as well as the option for specific consent may increase patients' trust and their intention to share PHI.

Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany

Germany introduced prescription-based mobile health (mHealth) apps in October 2020, becoming the first country to offer them fully reimbursed by health insurance. These regulated apps, known as DiGAs, undergo a rigorous approval process similar to pharmaceuticals, including data protection measures and sometimes clinical trials. This study compares the user experience of DiGAs with non-prescription mHealth apps in Germany, analyzing both average app store ratings and written reviews. Our study pioneers the use of BERTopic for sentiment analysis and topic modeling in the mHealth research domain. The dataset comprises 15 DiGAs and 50 comparable apps, totaling 17,588 German-language reviews. Results reveal that DiGAs receive higher contemporary ratings than non-regulated apps (Android: 3.82 vs. 3.77; iOS: 3.78 vs. 3.53; p < 0.01; non-parametric Mann-Whitney-Wilcoxon test). Key factors contributing to positive user experience with DiGAs are customer service and personalization (15%) and ease of use (13%). However, challenges for DiGAs include software bugs (24%) and a cumbersome registration process (20%). Negative user reviews highlight concerns about therapy effectiveness (11%). Excessive pricing is the main concern for the non-regulated group (27%). Data privacy and security receive limited attention from users (DiGAs: 0.5%; comparators: 2%). In conclusion, DiGAs are generally perceived positively based on ratings and sentiment analysis of reviews. However, addressing pricing concerns in the non-regulated mHealth sector is crucial. Integrating user experience evaluation into the review process could improve adherence and health outcomes.

Patients' and Members of the Public's Wishes Regarding Transparency in the Context of Secondary Use of Health Data: Scoping Review

BACKGROUND

Secondary use of health data has reached unequaled potential to improve health systems governance, knowledge, and clinical care. Transparency regarding this secondary use is frequently cited as necessary to address deficits in trust and conditional support and to increase patient awareness.

OBJECTIVE

We aimed to review the current published literature to identify different stakeholders' perspectives and recommendations on what information patients and members of the public want to learn about the secondary use of health data for research purposes and how and in which situations.

METHODS

Using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we conducted a scoping review using Medline, CINAHL, PsycINFO, Scopus, Cochrane Library, and PubMed databases to locate a broad range of studies published in English or French until November 2022. We included articles reporting a stakeholder's perspective or recommendations of what information patients and members of the public want to learn about the secondary use of health data for research purposes and how or in which situations. Data were collected and analyzed with an iterative thematic approach using NVivo.

RESULTS

Overall, 178 articles were included in this scoping review. The type of information can be divided into generic and specific content. Generic content includes information on governance and regulatory frameworks, technical aspects, and scientific aims. Specific content includes updates on the use of one's data, return of results from individual tests, information on global results, information on data sharing, and how to access one's data. Recommendations on how to communicate the information focused on frequency, use of various supports, formats, and wording. Methods for communication generally favored broad approaches such as nationwide publicity campaigns, mainstream and social media for generic content, and mixed approaches for specific content including websites, patient portals, and face-to-face encounters. Content should be tailored to the individual as much as possible with regard to length, avoidance of technical terms, cultural competence, and level of detail. Finally, the review outlined 4 major situations where communication was deemed necessary: before a new use of data, when new test results became available, when global research results were released, and in the advent of a breach in confidentiality.

CONCLUSIONS

This review highlights how different types of information and approaches to communication efforts may serve as the basis for achieving greater transparency. Governing bodies could use the results: to elaborate or evaluate strategies to educate on the potential benefits; to provide some knowledge and control over data use as a form of reciprocity; and as a condition to engage citizens and build and maintain trust. Future work is needed to assess which strategies achieve the greatest outreach while striking a balance between meeting information needs and use of resources.