Digitization and Health in Germany: Cross-sectional Nationwide Survey

Improving health and reducing health inequality: An innovation of digitalization?

RATIONALE

The association between digitalization and individual health has attracted increasing attention from both scholars and policymakers. Existing research, however, has not agreed on whether digitization can improve health or reduce health inequality.

OBJECTIVE

The purpose of this study is to clarify whether and how the development of digitalization may be related to health and health disparities.

METHODS

We rely on China Family Panel Studies (CFPS) surveys from 2012 to 2018 to obtain a sample of 82,471 observations to explore the impact of digitalization on self-rated health and health inequality and its transmission mechanisms. The hypotheses are tested by Ordinary Least Squares Modeling.

RESULTS

As expected, digitalization is significantly and positively correlated with self-rated health. Furthermore, the development of digitalization has led to a notable decrease in health inequality. The influencing mechanisms of digitalization include income, healthcare consumption and health behaviors. Both dimensions of digitalization-internet development and digital finance-generate significant effects and the effects of internet development are greater.

CONCLUSIONS

This study is the first to systematically investigate the impact of digitalization development on health and health inequality. Our findings provide evidence for the health promotion theory by clarifying the benefits of digitalization in improving residents' health and reducing health inequality. Therefore, utilizing the tools of digitalization efficiently could be a focus of policymakers aiming to accomplish the SDGs' health targets.

[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.

[Social inequality in the context of digital health applications: digital divides in access, use, effectiveness, and privacy]

Given the massive increase in digital health tools, the question about the impact of these tools on health equity has gained importance. The aim of this narrative review is to discuss the extent and central aspects of the digital divide. To illustrate the extent of the digital divide, we draw on data from the Liter@te study, which interviewed low-literacy individuals regarding their use of digital health tools and their digital health literacy. The results of the Liter@te study are compared with population surveys conducted in parallel. Four areas can be distinguished in relation to digital divides: access, use, effectiveness, and privacy. Inequalities can be observed in all four areas. While differences in access or material infrastructure, as well as in usage patterns and the required literacies, have already been investigated in some studies, the data basis for a comprehensive assessment of the unequal effects of digital health tools in different population groups is still lacking. Digital divides in the area of privacy protection is an emerging field. However, transparent and understandable privacy measures will undoubtedly be an important prerequisite for the widespread use of digital health tools. Overall, in addition to a better data base, involvement of disadvantaged population groups in the development of digital health interventions is necessary.

Interventions to promote health literacy among working-age populations experiencing socioeconomic disadvantage: systematic review

Background

Experiencing financial insecurity and being underserved is often associated with low health literacy, i.e., the ability to identify, obtain, interpret and act upon health information, which may result in poor health outcomes. Little is known about effective interventions for promoting health literacy among underserved populations. The objective of this systematic review is to summarize the literature on such interventions and identify characteristics that differentiate more effective interventions.

Methods

Following PRISMA guidelines we searched the databases SCOPUS, Pubmed, Web of Science core collection and CINAHL. We included primary studies with a quantitative study design and control groups testing interventions to increase health literacy or health knowledge in underserved populations between 18 and 65 years. Where possible, we converted effect sizes into Cohen's d and compared mean differences of intervention and control groups. Albatross plots were created to summarize the results according to different health literacy and health knowledge outcomes.

Results

We screened 3,696 titles and abstracts and 206 full texts. In total, 86 articles were analyzed, of which 55 were summarized in seven albatross plots. The majority of the studies (n = 55) were conducted in the United States and had a randomized controlled study design (n = 44). More effective intervention approaches assessed needs of participants through focus group discussions prior to conducting the intervention, used bilingual educational materials, and included professionals fluent in the first languages of the study population as intervention deliverers. Additionally, the use of educational materials in video and text form, fotonovelas and interactive group education sessions with role playing exercises were observed to be effective.

Discussion

Although the outcomes addressed in the included studies were heterogeneous, effective intervention approaches were often culturally sensitive and developed tailored educational materials. Interventions aiming to promote health literacy in underserved populations should hence consider applying similar approaches.Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=323801, PROSPERO registration ID: CRD42022323801.

Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study

BACKGROUND

Rapid digitalization in health care has led to the adoption of digital technologies; however, limited trust in internet-based health decisions and the need for technical personnel hinder the use of smartphones and machine learning applications. To address this, automated machine learning (AutoML) is a promising tool that can empower health care professionals to enhance the effectiveness of mobile health apps.

OBJECTIVE

We used AutoML to analyze data from clinical studies involving patients with chronic hand and/or foot eczema or psoriasis vulgaris who used a smartphone monitoring app. The analysis focused on itching, pain, Dermatology Life Quality Index (DLQI) development, and app use.

METHODS

After extensive data set preparation, which consisted of combining 3 primary data sets by extracting common features and by computing new features, a new pseudonymized secondary data set with a total of 368 patients was created. Next, multiple machine learning classification models were built during AutoML processing, with the most accurate models ultimately selected for further data set analysis.

RESULTS

Itching development for 6 months was accurately modeled using the light gradient boosted trees classifier model (log loss: 0.9302 for validation, 1.0193 for cross-validation, and 0.9167 for holdout). Pain development for 6 months was assessed using the random forest classifier model (log loss: 1.1799 for validation, 1.1561 for cross-validation, and 1.0976 for holdout). Then, the random forest classifier model (log loss: 1.3670 for validation, 1.4354 for cross-validation, and 1.3974 for holdout) was used again to estimate the DLQI development for 6 months. Finally, app use was analyzed using an elastic net blender model (area under the curve: 0.6567 for validation, 0.6207 for cross-validation, and 0.7232 for holdout). Influential feature correlations were identified, including BMI, age, disease activity, DLQI, and Hospital Anxiety and Depression Scale-Anxiety scores at follow-up. App use increased with BMI >35, was less common in patients aged >47 years and those aged 23 to 31 years, and was more common in those with higher disease activity. A Hospital Anxiety and Depression Scale-Anxiety score >8 had a slightly positive effect on app use.

CONCLUSIONS

This study provides valuable insights into the relationship between data characteristics and targeted outcomes in patients with chronic eczema or psoriasis, highlighting the potential of smartphone and AutoML techniques in improving chronic disease management and patient care.

Knowledge and Perception of the Use of AI and its Implementation in the Field of Radiology: Cross-Sectional Study

BACKGROUND

Artificial Intelligence (AI) has been developing for decades, but in recent years its use in the field of health care has experienced an exponential increase. Currently, there is little doubt that these tools have transformed clinical practice. Therefore, it is important to know how the population perceives its implementation to be able to propose strategies for acceptance and implementation and to improve or prevent problems arising from future applications.

OBJECTIVE

This study aims to describe the population's perception and knowledge of the use of AI as a health support tool and its application to radiology through a validated questionnaire, in order to develop strategies aimed at increasing acceptance of AI use, reducing possible resistance to change and identifying possible sociodemographic factors related to perception and knowledge.

METHODS

A cross-sectional observational study was conducted using an anonymous and voluntarily validated questionnaire aimed at the entire population of Catalonia aged 18 years or older. The survey addresses 4 dimensions defined to describe users' perception of the use of AI in radiology, (1) "distrust and accountability," (2) "personal interaction," (3) "efficiency," and (4) "being informed," all with questions in a Likert scale format. Results closer to 5 refer to a negative perception of the use of AI, while results closer to 1 express a positive perception. Univariate and bivariate analyses were performed to assess possible associations between the 4 dimensions and sociodemographic characteristics.

RESULTS

A total of 379 users responded to the survey, with an average age of 43.9 (SD 17.52) years and 59.8% (n=226) of them identified as female. In addition, 89.8% (n=335) of respondents indicated that they understood the concept of AI. Of the 4 dimensions analyzed, "distrust and accountability" obtained a mean score of 3.37 (SD 0.53), "personal interaction" obtained a mean score of 4.37 (SD 0.60), "efficiency" obtained a mean score of 3.06 (SD 0.73) and "being informed" obtained a mean score of 3.67 (SD 0.57). In relation to the "distrust and accountability" dimension, women, people older than 65 years, the group with university studies, and the population that indicated not understanding the AI concept had significantly more distrust in the use of AI. On the dimension of "being informed," it was observed that the group with university studies rated access to information more positively and those who indicated not understanding the concept of AI rated it more negatively.

CONCLUSIONS

The majority of the sample investigated reported being familiar with the concept of AI, with varying degrees of acceptance of its implementation in radiology. It is clear that the most conflictive dimension is "personal interaction," whereas "efficiency" is where there is the greatest acceptance, being the dimension in which there are the best expectations for the implementation of AI in radiology.

Sociodemographic determinants of digital health literacy: A systematic review and meta-analysis

INTRODUCTION

Differences in digital health literacy levels are associated with a lack of access to digital tools, usage patterns, and the ability to effectively use digital technologies. Although some studies have investigated the impact of sociodemographic factors on digital health literacy, a comprehensive evaluation of these factors has not been conducted. Therefore, this study sought to examine the sociodemographic determinants of digital health literacy by conducting a systematic review of the existing literature.

METHODS

A search of four databases was conducted. Data extraction included information on study characteristics, sociodemographic factors, and the digital health literacy scales used. Meta-analyses for age and sex were conducted using RStudio software with the metaphor package.

RESULTS

A total of 3922 articles were retrieved, of which 36 were included in this systematic review. Age had a negative effect on digital health literacy (B = -0.05, 95%CI [-0.06; -0.04]), particularly among older adults, whereas sex appeared to have no statistically significant influence among the included studies (B = - 0.17, 95%CI [-0.64; 0.30]). Educational level, higher income, and social support also appeared to have a positive influence on digital health literacy.

DISCUSSION

This review highlighted the importance of addressing the digital health literacy needs of underprivileged populations, including immigrants and individuals with low socioeconomic status. It also emphasizes the need for more research to better understand the influence of sociodemographic, economic, and cultural differences on digital health literacy.

CONCLUSIONS

Overall, this review suggests digital health literacy is dependent on sociodemographic, economic, and cultural factors, which may require tailored interventions that consider these nuances.

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.

The Influence of Sex, Gender, or Age on Outcomes of Digital Technologies for Treatment and Monitoring of Chronic Obstructive Pulmonary Disease: Protocol for an Overview of Systematic Reviews

Background

Chronic obstructive pulmonary disease (COPD) is a common chronic disease that can be treated and monitored with various digital technologies. Digital technologies offer unique opportunities for treating and monitoring people with chronic diseases, but little is known about whether the outcomes of such technologies depend on sex, gender, or age in people with COPD.

Objective

The general objective of this study is to assess the possible influence of sex, gender, or age on outcomes of digital technologies for treatment and monitoring of COPD through an overview of systematic reviews.

Methods

The study is planned as an overview of systematic reviews. Study reporting is based on the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) 2020 guidelines because guidelines for overviews are not available as of this writing. The information sources for the overview will include 4 bibliographic databases (MEDLINE, Cochrane Library, Epistemonikos, and Web of Science) as well as the bibliographies of the included systematic reviews. The electronic search strategy will be developed and conducted in collaboration with an experienced database specialist. The search results will be presented in accordance with the PRISMA 2020 guidelines. The eligibility of studies is based on the population, intervention, comparison, outcomes, and study design (PICOS) criteria: (1) people with COPD (population), (2) digital technology intervention for treatment or monitoring (intervention), (3) any control group or no control group (comparison), (4) any outcome, and (5) systematic review of randomized controlled trials or non–randomized controlled trials with or without a meta-analysis (study design). Critical appraisal of the included systematic reviews will be performed using A Measurement Tool to Assess Systematic Reviews, version 2 (AMSTAR 2). Data will be extracted using a standardized data extraction sheet.

Results

The literature search is scheduled for June 2022. We expect to select the relevant systematic reviews, code the data, and appraise the systematic reviews by December 2022.

Conclusions

There is a growing recognition that the influence of sex, gender, or age should be considered in research design and outcome reporting in the context of health care interventions. Our overview will identify systematic reviews of various digital technologies for treatment or monitoring of COPD. The most interesting aspect of the overview will be to investigate if any systematic reviews considered the influence of sex, gender, or age on the outcomes of such digital technologies in COPD. Evidence from the overview could be used to guide more individualized (sex, gender, or age-based) recommendations for the use of digital technologies among people with COPD.

Trial Registration

PROSPERO International Prospective Register of Systematic Reviews CRD42022322924; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=322924

The digital rainbow: Digital determinants of health inequities

The widely used socioecological rainbow model from Dahlgren and Whitehead specifies determinants of health inequity on multiple hierarchical levels and suggests that these determinants may interact both within and between levels. At the time of its inception, digital determinants only played a minor role in tackling inequities in public health and were therefore not specifically considered. This has dramatically changed: From today's perspective, health inequities increasingly depend on digital determinants. In this article, we suggest adapting the Dahlgren-Whitehead model to reflect these developments. We propose a model that allows formulating testable hypotheses, interpreting research findings, and developing policy implications against the background of the global spread of digital technologies. This may facilitate the development of a new line of research and logic models for public health interventions in the digital age. Using the COVID-19 pandemic as a case study, we illustrate how the digitization of all aspects of life affects the different levels of determinants of health inequities in the Dahlgren-Whitehead model. In doing so, we deliberately argue for not introducing a separate digital sphere in its own right, but for understanding digitization as a phenomenon that permeates all levels of determinants of health inequities. As a result, we present a digital rainbow model that integrates Dahlgren and Whitehead's 1991 model with digital environments to identify current health promotion and research issues without changing the rainbow model's initial structure.

Research progress on digital health literacy of older adults: A scoping review

With the rapid development of digital health today, the lack of digital health literacy in older adults is an urgent problem. It is crucial that older adults adapt to the digital reform in medical treatment, pension, health management, and other fields. Therefore, we reviewed the current development status of digital health literacy among older adults. A total of 47 articles were included in this scoping review. Our findings revealed that research on digital health literacy in older adults is still in its infancy. Further development is warranted especially in terms of assessment tools and intervention methods.

Modifiable predictors of health literacy in working-age adults - a rapid review and meta-analysis

Background

Health literacy comprises the ability to identify, obtain, interpret and act upon health information. Low health literacy is a major risk factor for hospitalizations, use of emergency care and premature mortality among others. Known risk factors for low health literacy such as lower educational attainment, migration history and chronic illnesses overlap with those for long-term unemployment – in itself a risk factor for low health literacy. These factors are difficult to address in interventions to support health literacy. Therefore, the objective of this review is to identify potentially modifiable predictors of HL in populations potentially affected by long-term unemployment.

Methods

A rapid review (PROSPERO registration number: 290873) was carried out in Pubmed and SCOPUS including quantitative studies on potentially modifiable predictors of health literacy in working-age populations following PRISMA guidelines for systematic reviews. Where possible, reported effect sizes were transformed into r, and random-effects meta-analyses were conducted where appropriate to pool effect sizes for the association between modifiable predictors and health literacy.

Results

In total, 4765 titles and abstracts were screened, 114 articles were assessed in full-text screening, and 54 were included in the review. Forty-one effect sizes were considered for 9 different meta-analyses. Higher language proficiency, higher frequency of internet use, using the internet as a source of health information more often, being more physically active, more oral health behaviours, watching more health-related TV and a good health status were significantly associated with higher health literacy. Significant heterogeneity suggests between-study differences.

Conclusions

Improving language proficiency and/or providing information in multiple and simplified languages, together with reliable and accessible health information on the internet and in linear media are potentially promising targets to improve health literacy levels in working-age populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13851-0.

Digital Technologies for Health Promotion and Disease Prevention in Older People: Protocol for a Scoping Review

BACKGROUND

Digital technologies could contribute to health promotion and disease prevention. It is unclear if and how such digital technologies address the health needs of older people in nonclinical settings (ie, daily life).

OBJECTIVE

This study aims to identify digital technologies for health promotion and disease prevention that target the needs of older people in nonclinical settings by performing a scoping review of the published literature. The scoping review is guided by the framework of Arksey and O'Malley.

METHODS

Our scoping review follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The information sources are bibliographic databases (MEDLINE, PsycINFO, CINAHL, and SCOPUS) and bibliographies of any included systematic reviews. Manual searches for additional studies will be performed in Google Scholar and most relevant journals. The electronic search strategy was developed in collaboration with a librarian who performed the search for studies on digital technologies for health promotion and disease prevention targeting the needs of older people. Study selection and data coding will be performed independently by 2 authors. Consensus will be reached by discussion. Eligibility is based on the PCC (Population, Concept, and Context) criteria as follows: (1) older people (population); (2) any digital (health) technology, such as websites, smartphone apps, or wearables (concept); and (3) health promotion and disease prevention in nonclinical (daily life, home, or community) settings (context). Primary studies with any design or reviews with a systematic methodology published in peer-reviewed academic journals will be included. Data items will address study designs, PCC criteria, benefits or barriers related to digital technology use by older people, and evidence gaps. Data will be synthesized using descriptive statistics or narratively described by identifying common themes. Quality appraisal will be performed for any included systematic reviews, using a validated instrument for this study type (A Measurement Tool to Assess Systematic Reviews, version 2 [AMSTAR2]).

RESULTS

Following preliminary literature searches to test and calibrate the search syntax, the electronic literature search was performed in March 2022 and manual searches were completed in June 2022. Study selection based on titles and abstracts was completed in July 2022, and the full-text screen was initiated in July 2022.

CONCLUSIONS

Our scoping review will identify the types of digital technologies, health targets in the context of health promotion and disease prevention, and health benefits or barriers associated with the use of such technologies for older people in nonclinical settings. This knowledge could guide further research on how digital technologies can support healthy aging.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/37729.

Evaluation of Digital Interventions for Physical Activity Promotion: Scoping Review

Background

Digital interventions are interventions supported by digital tools or technologies, such as mobile apps, wearables, or web-based software. Digital interventions in the context of public health are specifically designed to promote and improve health. Recent reviews have shown that many digital interventions target physical activity promotion; however, it is unclear how such digital interventions are evaluated.

Objective

We aimed to investigate evaluation strategies in the context of digital interventions for physical activity promotion using a scoping review of published reviews. We focused on the target (ie, user outcomes or tool performance), methods (ie, tool data or self-reported data), and theoretical frameworks of the evaluation strategies.

Methods

A protocol for this study was preregistered and published. From among 300 reviews published up to March 19, 2021 in Medline, PsycINFO, and CINAHL databases, 40 reviews (1 rapid, 9 scoping, and 30 systematic) were included in this scoping review. Two authors independently performed study selection and data coding. Consensus was reached by discussion. If applicable, data were coded quantitatively into predefined categories or qualitatively using definitions or author statements from the included reviews. Data were analyzed using either descriptive statistics, for quantitative data (relative frequencies out of all studies), or narrative synthesis focusing on common themes, for qualitative data.

Results

Most reviews that were included in our scoping review were published in the period from 2019 to 2021 and originated from Europe or Australia. Most primary studies cited in the reviews included adult populations in clinical or nonclinical settings, and focused on mobile apps or wearables for physical activity promotion. The evaluation target was a user outcome (efficacy, acceptability, usability, feasibility, or engagement) in 38 of the 40 reviews or tool performance in 24 of the 40 reviews. Evaluation methods relied upon objective tool data (in 35/40 reviews) or other data from self-reports or assessments (in 28/40 reviews). Evaluation frameworks based on behavior change theory, including goal setting, self-monitoring, feedback on behavior, and educational or motivational content, were mentioned in 22 out of 40 reviews. Behavior change theory was included in the development phases of digital interventions according to the findings of 20 out of 22 reviews.

Conclusions

The evaluation of digital interventions is a high priority according to the reviews included in this scoping review. Evaluations of digital interventions, including mobile apps or wearables for physical activity promotion, typically target user outcomes and rely upon objective tool data. Behavior change theory may provide useful guidance not only for development of digital interventions but also for the evaluation of user outcomes in the context of physical activity promotion. Future research should investigate factors that could improve the efficacy of digital interventions and the standardization of terminology and reporting in this field.

International Registered Report Identifier (IRRID)

RR2-10.2196/35332

Use and Perception of Digital Health Technologies by Surgical Patients in Germany in the Pre-COVID-19 Era: Survey Study

BACKGROUND

This survey study investigates surgical patients' use and perception of digital health technologies in Germany in the pre-COVID-19 era.

OBJECTIVE

The objective of this study was to relate surgical patients' characteristics to the use and perception of several digital health technologies.

METHODS

In this single-center, cross-sectional survey study in the outpatient department of a university hospital in Germany, 406 patients completed a questionnaire with the following three domains: general information and use of the internet, smartphones, and general digital health aspects. Analyses were stratified by age group and highest education level achieved.

RESULTS

We found significant age-based differences in most of the evaluated aspects. Younger patients were more open to using new technologies in private and medical settings but had more security concerns. Although searching for information on illnesses on the web was common, the overall acceptance of and trust in web-based consultations were rather low, with <50% of patients in each age group reporting acceptance and trust. More people with academic qualifications than without academic qualifications searched for information on the web before visiting physicians (73/121, 60.3% and 100/240, 41.7%, respectively). Patients with academic degrees were also more engaged in health-related information and communication technology use.

CONCLUSIONS

These results support the need for eHealth literacy, health literacy, and available digital devices and internet access to support the active, meaningful use of information and communication technologies in health care. Uncertainties and a lack of knowledge exist, especially regarding telemedicine and the use of medical and health apps. This is especially pronounced among older patients and patients with a low education status.

Evaluation of Digital Interventions for Physical Activity Promotion: Protocol for a Scoping Review

Background

Digital interventions (DIs) could support physical activity (PA) promotion, according to recent reviews. However, it remains unclear if and how DIs for PA promotion are evaluated; thus, it is unclear if they support behavior change in real-world settings. A mapping of evidence from published reviews is required to focus on the evaluation of DIs for PA promotion.

Objective

The aim of our study is to investigate evaluation strategies for any outcome in the context of DIs for PA promotion by conducting a scoping review of published reviews.

Methods

Our scoping review adheres to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The information sources include bibliographic databases (MEDLINE, PsycINFO, and CINAHL) and the bibliographies of the selected studies. The electronic search strategy was developed and conducted in collaboration with an experienced database specialist. The electronic search was conducted in English with no limits up to March 19, 2021, for sources with the terms digital intervention AND evaluation AND physical activity in titles or abstracts. After deduplication, 300 reviews selected from 4912 search results were assessed for eligibility by 2 authors working independently. The inclusion criteria were (1) healthy or clinical samples (population), (2) DIs for PA promotion (intervention), (3) comparisons to any other intervention or no intervention (comparison), (4) evaluation strategies (methods, results, or frameworks) for any outcome in the context of DIs for PA promotion (outcome), and (5) any published review (study type). According to the consensus reached during a discussion, 40 reviews met the inclusion criteria—36 from the electronic search and 4 from the manual search of the bibliographies of the 36 reviews. All reviews reported the evaluation strategies for any outcomes in the context of DIs for PA promotion in healthy or clinical samples. Data coding and the quality appraisal of systematic reviews are currently being performed independently by 2 authors.

Results

Our scoping review includes data from 40 published reviews (1 rapid review, 9 scoping reviews, and 30 systematic reviews). The focus of data coding is on evaluation strategies in the context of DIs for PA promotion and on the critical appraisal of the included systematic reviews. The final consensus regarding all data is expected in early 2022.

Conclusions

Interventions for PA promotion that are supported by digital technologies require evaluation to ensure their efficacy in real-world settings. Our scoping review is needed because it addresses novel objectives that focus on such evaluations and are not answered in the published reviews identified in our search. The evaluation strategies addressing DIs for PA promotion will be mapped to synthesize the results that have been reported in published reviews so far.

International Registered Report Identifier (IRRID)

DERR1-10.2196/35332

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.