[Implementation and participatory design of digital health interventions]

Methods, Indicators, and End-User Involvement in the Evaluation of Digital Health Interventions for the Public: Scoping Review

BACKGROUND

Digital health interventions (DHIs) have the potential to enable public end users, such as citizens and patients, to manage and improve their health. Although the number of available DHIs is increasing, examples of successfully established DHIs in public health systems are limited. To counteract the nonuse of DHIs, they should be comprehensively evaluated while integrating end users. Unfortunately, there is a wide variability and heterogeneity according to the approaches of evaluation, which creates a methodological challenge.

OBJECTIVE

This scoping review aims to provide an overview of the current established processes for evaluating DHIs, including methods, indicators, and end-user involvement. The review is not limited to a specific medical field or type of DHI but offers a holistic overview.

METHODS

This scoping review was conducted following the JBI methodology for scoping reviews based on the framework by Arksey & O'Malley and complies with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Three scientific databases (PubMed, Scopus, and Science Direct) were searched in April 2023. English and German studies between 2008 and 2023 were considered when evaluating DHIs that explicitly address public end users. The process of study selection was carried out by several researchers to avoid reviewer bias.

RESULTS

The search strategy identified 9618 publications, of which 160 were included. Among these included articles, 200 evaluations were derived and analyzed. The results showed that there is neither a consensus on the methods to evaluate DHIs nor a commonly agreed definition or usage of the evaluated indicators, which results in a broad variety of evaluation practices. This aligns with observations of the existing literature. It was found that there is a lack of references to existing frameworks for the evaluation of DHIs. The majority of the included studies referred to user-centered approaches and involved end users in the evaluation process. As assistance for people developing and evaluating DHIs and as a basis for thinking about appropriate ways to evaluate DHIs, a results matrix was created where the findings were combined per DHI cluster. Additionally, general recommendations for the evaluators of DHIs were formulated.

CONCLUSIONS

The findings of this scoping review offer a holistic overview of the variety and heterogeneity according to the approaches of evaluation of DHIs for public end users. Evaluators of these DHIs should be encouraged to reference established frameworks or measurements for justification. This would ease the transferability of the results among similar evaluation studies within the digital health sector, thereby enhancing the coherence and comparability of research in this area.

[Factors influencing the implementation of AI-based decision support systems for antibiotic prescription in hospitals: a qualitative analysis from the perspective of health professionals]

BACKGROUND

Decision support systems based on artificial intelligence might optimize antibiotic prescribing in hospitals and prevent the development of antimicrobial resistance. The aim of this study was to identify impeding and facilitating factors for successful implementation from the perspective of health professionals.

METHODS

Problem-centered individual interviews were conducted with health professionals working in hospitals. Data evaluation was based on the structured qualitative content analysis according Kuckartz.

RESULTS

Attitudes of health professionals were presented along the Human-Organization -Technology-fit model. Technological and organizational themes were the most important factors for system implementation. Especially, compatibility with existing systems and user-friendliness were seen to play a major role in successful implementation. Additionally, the training of potential users and the technical equipment of the organization were considered essential. Finally, the importance of promoting technical skills of potential users in the long term and creating trust in the benefits of the system were highlighted.

CONCLUSION

The identified factors provide a basis for prioritizing and quantifying needs and attitudes in a next step. It becomes clear that, beside technological factors, attention to context-specific and user-related conditions are of fundamental importance to ensure successful implementation and system trust in the long term.

One Digital Health Intervention for Monitoring Human and Animal Welfare in Smart Cities: Viewpoint and Use Case

Smart cities and digital public health are closely related. Managing digital transformation in urbanization and living spaces is challenging. It is critical to prioritize the emotional and physical health and well-being of humans and their animals in the dynamic and ever-changing environment they share. Human-animal bonds are continuous as they live together or share urban spaces and have a mutual impact on each other's health as well as the surrounding environment. In addition, sensors embedded in the Internet of Things are everywhere in smart cities. They monitor events and provide appropriate responses. In this regard, accident and emergency informatics (A&EI) offers tools to identify and manage overtime hazards and disruptive events. Such manifold focuses fit with One Digital Health (ODH), which aims to transform health ecosystems with digital technology by proposing a comprehensive framework to manage data and support health-oriented policies. We showed and discussed how, by developing the concept of ODH intervention, the ODH framework can support the comprehensive monitoring and analysis of daily life events of humans and animals in technologically integrated environments such as smart homes and smart cities. We developed an ODH intervention use case in which A&EI mechanisms run in the background. The ODH framework structures the related data collection and analysis to enhance the understanding of human, animal, and environment interactions and associated outcomes. The use case looks at the daily journey of Tracy, a healthy woman aged 27 years, and her dog Mego. Using medical Internet of Things, their activities are continuously monitored and analyzed to prevent or manage any kind of health-related abnormality. We reported and commented on an ODH intervention as an example of a real-life ODH implementation. We gave the reader examples of a "how-to" analysis of Tracy and Mego's daily life activities as part of a timely implementation of the ODH framework. For each activity, relationships to the ODH dimensions were scored, and relevant technical fields were evaluated in light of the Findable, Accessible, Interoperable, and Reusable principles. This "how-to" can be used as a template for further analyses. An ODH intervention is based on Findable, Accessible, Interoperable, and Reusable data and real-time processing for global health monitoring, emergency management, and research. The data should be collected and analyzed continuously in a spatial-temporal domain to detect changes in behavior, trends, and emergencies. The information periodically gathered should serve human, animal, and environmental health interventions by providing professionals and caregivers with inputs and "how-to's" to improve health, welfare, and risk prevention at the individual and population levels. Thus, ODH complementarily combined with A&EI is meant to enhance policies and systems and modernize emergency management.

What are Digital Public Health Interventions? First Steps Toward a Definition and an Intervention Classification Framework

Digital public health is an emerging field in population-based research and practice. The fast development of digital technologies provides a fundamentally new understanding of improving public health by using digitalization, especially in prevention and health promotion. The first step toward a better understanding of digital public health is to conceptualize the subject of the assessment by defining what digital public health interventions are. This is important, as one cannot evaluate tools if one does not know what precisely an intervention in this field can be. Therefore, this study aims to provide the first definition of digital public health interventions. We will merge leading models for public health functions by the World Health Organization, a framework for digital health technologies by the National Institute for Health and Care Excellence, and a user-centered approach to intervention development. Together, they provide an overview of the functions and areas of use for digital public health interventions. Nevertheless, one must keep in mind that public health functions can differ among different health care systems, limiting our new framework’s universal validity. We conclude that a digital public health intervention should address essential public health functions through digital means. Furthermore, it should include members of the target group in the development process to improve social acceptance and achieve a population health impact.

Mapping digital public health interventions in practice: Protocol for a scoping review of existing digital technologies and Internet-based interventions to maintain and improve population health (Preprint)

Background

Rapid developments and implementation of digital technologies in public health domains throughout the last decades have changed the landscape of health delivery and disease prevention globally. A growing number of countries are introducing interventions such as online consultations, electronic health records, or telemedicine to their health systems to improve their populations’ health and improve access to health care. Despite multiple definitions for digital public health and the development of different digital interventions, no study has analyzed whether the utilized technologies fit the definition or the core characteristics of digital public health interventions. A scoping review is therefore needed to explore the extent of the literature on this topic.

Objective

The main aim of this scoping review is to outline real-world digital public health interventions on all levels of health care, prevention, and health. The second objective will be the mapping of reported intervention characteristics. These will include nontechnical elements and the technical features of an intervention.

Methods

We searched for relevant literature in the following databases: PubMed, Web of Science, CENTRAL (Cochrane Central Register of Controlled Trials), IEEE (Institute of Electrical and Electronics Engineers) Xplore, and the Association for Computing Machinery (ACM) Full-Text Collection. All original study types (observational studies, experimental trials, qualitative studies, and health-economic analyses), as well as governmental reports, books, book chapters, or peer-reviewed full-text conference papers were included when the evaluation and description of a digital health intervention was the primary intervention component. Two authors screened the articles independently in three stages (title, abstract, and full text). Two independent authors will also perform the data charting. We will report our results following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist.

Results

An additional systematic search in IEEE Xplore and ACM, performed on December 1, 2021, identified another 491 titles. We identified a total of 13,869 papers after deduplication. As of March 2022, the abstract screening state is complete, and we are in the state of screening the 1417 selected full texts for final inclusion. We estimate completing the review in April 2022.

Conclusions

To our knowledge, this will be the first scoping review to fill the theoretical definitions of digital public health with concrete interventions and their characteristics. Our scoping review will display the landscape of worldwide existing digital public health interventions that use information and communication technologies. The results of this review will be published in a peer-reviewed journal in early 2022, which can serve as a blueprint for the development of future digital public health interventions.

International Registered Report Identifier (IRRID)

DERR1-10.2196/33404

[Acceptance of Digital Health Interventions in Light to Moderate Depressive Disorders - A Qualitative Analysis from the Perspective of Affected Persons, Relatives and Health Professionals]

OBJECTIVE

User acceptance of digital health interventions in light to moderate depressive disorders has been rudimentarily researched and is examined in this study.

METHODS

Problem-centered individual interviews were conducted with 3 affected persons, 3 relatives and 13 health care professionals. The data evaluation was based on the structured qualitative content analysis.

RESULTS

Along the Unified Theory of Acceptance and Use of Technology attitudes of affected persons, relatives and health care professionals were presented. Expectations of performance and the supportive framework conditions were the most significant influencing predictors for the positive intention to use.

CONCLUSION

The results provide a basis for prioritizing needs and attitudes in next step. In terms of ethical, sustainable and economical use further research on user acceptance is required.

Effectiveness of Smartphone-Based Cognitive Behavioral Therapy Among Patients With Major Depression: Systematic Review of Health Implications

BACKGROUND

Depression is often associated with rapid changes in mood and quality of life that persist for a period of 2 weeks. Despite medical innovations, there are problems in the provision of care. Long waiting times for treatment and high recurrence rates of depression cause enormous costs for health care systems. At the same time, comprehensive limitations in physical, psychological, and social dimensions are observed for patients with depression, which significantly reduce their quality of life. In addition to patient-specific limitations, undersupply and inappropriate health care have been determined. For this reason, new forms of care are discussed. Smartphone-based therapy is considered to have great potential due to its reach and easy accessibility. Low socioeconomic groups, which are always difficult to reach for public health interventions, can now be accessed due to the high dispersion of smartphones. There is still little information about the impact and mechanisms of smartphone-based therapy on depression. In a systematic literature review, the health implications of smartphone-based therapy were presented in comparison with standard care.

OBJECTIVE

The objective of this review was to identify and summarize the existing evidence regarding smartphone-based cognitive behavioral therapy for patients with depression and to present the health implications of smartphone-based cognitive behavioral therapy of considered endpoints.

METHODS

A systematic literature review was conducted to identify relevant studies by means of inclusion and exclusion criteria. For this purpose, the PubMed and Psyndex databases were systematically searched using a search syntax. The endpoints of depressive symptoms, depression-related anxiety, self-efficacy or self-esteem, and quality of life were analyzed. Identified studies were evaluated for study quality and risk of bias. After applying the inclusion and exclusion criteria, 8 studies were identified.

RESULTS

The studies examined in this review reported contradictory results regarding the investigated endpoints. In addition, due to clinical and methodological heterogeneity, it was difficult to derive evident results. All included studies reported effects on depressive symptoms. The other investigated endpoints were only reported by isolated studies. Only 50% (4/8) of the studies reported effects on depression-related anxiety, self-efficacy or self-esteem, and quality of life.

CONCLUSIONS

No clear implications of smartphone-based cognitive behavioral therapy could be established. Evidence for the treatment of depression using smartphone-based cognitive behavioral therapy is limited. Additional research projects are needed to demonstrate the effects of smartphone-based cognitive behavioral therapy in the context of evidence-based medicine and to enable its translation into standard care. Participatory technology development might help to address current problems in mobile health intervention studies.

[Digital interventions in prevention and health promotion: What kind of evidence do we have and what is needed?]

Digital technologies increasingly affect our daily lives and interact with our living environment. A high potential for prevention and health promotion is referred to digital interventions. So far, however, there is a lack of well-founded evidence on the effectiveness of such measures. This paper will address the challenges of evidence-based digital interventions in prevention and health promotion. The results are summarised in the form of a narrative review.So far, evidence-based medicine methods have not been sufficiently used in the evaluation of benefits and harms in the field of prevention and health promotion. The reasons for this are found in the complexity of the corresponding measures. This complexity is further increased by digital interventions. Nevertheless, it is urgently recommended to place a stronger focus on evidence-based interventions in order to enable meaningful and comprehensible evaluation procedures with regard to the effectiveness of digital interventions in prevention and health promotion.Digitalisation leads to new demands on prevention and health promotion. A critical perspective on the actual impact of digital interventions and their social implications is needed. The development of a solid knowledge base is necessary in order to promote acceptance of the technologies and to achieve sustainable implementation.