Smartphone Apps for Food Purchase Choices: Scoping Review of Designs, Opportunities, and Challenges.

BACKGROUND: Smartphone apps can aid consumers in making healthier and more sustainable food purchases. However, there is still a limited understanding of the different app design approaches and their impact on food purchase choices. An overview of existing food purchase choice apps and an understanding of common challenges can help speed up effective future developments. OBJECTIVE: We examined the academic literature on food purchase choice apps and provided an overview of the design characteristics, opportunities, and challenges for effective implementation. Thus, we contribute to an understanding of how technologies can effectively improve food purchase choice behavior and provide recommendations for future design efforts. METHODS: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we considered peer-reviewed literature on food purchase choice apps within IEEE Xplore, PubMed, Scopus, and ScienceDirect. We inductively coded and summarized design characteristics. Opportunities and challenges were addressed from both quantitative and qualitative perspectives. From the quantitative perspective, we coded and summarized outcomes of comparative evaluation trials. From the qualitative perspective, we performed a qualitative content analysis of commonly discussed opportunities and challenges. RESULTS: We retrieved 55 articles, identified 46 unique apps, and grouped them into 5 distinct app types. Each app type supports a specific purchase choice stage and shares a common functional design. Most apps support the product selection stage (selection apps; 27/46, 59%), commonly by scanning the barcode and displaying a nutritional rating. In total, 73% (8/11) of the evaluation trials reported significant findings and indicated the potential of food purchase choice apps to support behavior change. However, relatively few evaluations covered the selection app type, and these studies showed mixed results. We found a common opportunity in apps contributing to learning (knowledge gain), whereas infrequent engagement presents a common challenge. The latter was associated with perceived burden of use, trust, and performance as well as with learning. In addition, there were technical challenges in establishing comprehensive product information databases or achieving performance accuracy with advanced identification methods such as image recognition. CONCLUSIONS: Our findings suggest that designs of food purchase choice apps do not encourage repeated use or long-term adoption, compromising the effectiveness of behavior change through nudging. However, we found that smartphone apps can enhance learning, which plays an important role in behavior change. Compared with nudging as a mechanism for behavior change, this mechanism is less dependent on continued use. We argue that designs that optimize for learning within each interaction have a better chance of achieving behavior change. This review concludes with design recommendations, suggesting that food purchase choice app designers anticipate the possibility of early abandonment as part of their design process and design apps that optimize the learning experience.

Targeting behavioral factors with digital health and shared decision-making to promote cardiac rehabilitation-a narrative review.

Cardiac rehabilitation (CR) represents an important steppingstone for many cardiac patients into a more heart-healthy lifestyle to prevent premature death and improve quality of life years. However, CR is underutilized worldwide. In order to support the development of targeted digital health interventions, this narrative review (I) provides understandings of factors influencing CR utilization from a behavioral perspective, (II) discusses the potential of digital health technologies (DHTs) to address barriers and reinforce facilitators to CR, and (III) outlines how DHTs could incorporate shared decision-making to support CR utilization. A narrative search of reviews in Web of Science and PubMed was conducted to summarize evidence on factors influencing CR utilization. The factors were grouped according to the Behaviour Change Wheel. Patients' Capability for participating in CR is influenced by their disease knowledge, awareness of the benefits of CR, information received, and interactions with healthcare professionals (HCP). The Opportunity to attend CR is impacted by healthcare system factors such as referral processes and HCPs' awareness, as well as personal resources including logistical challenges and comorbidities. Patients' Motivation to engage in CR is affected by emotions, factors such as gender, age, self-perception of fitness and control over the cardiac condition, as well as peer comparisons. Based on behavioral factors, this review identified intervention functions that could support an increase of CR uptake: Future DHTs aiming to support CR utilization may benefit from incorporating information for patients and HCP education, enabling disease management and collaboration along the patient pathway, and enhancing social support from relatives and peers. To conclude, considerations are made how future innovations could incorporate such functions.

Usability Testing of a Multi-Level Modeling Framework for Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health.

The JITAI is an intervention design to support health behavior change. We designed a multi-level modeling framework for JITAIs and developed a proof-of-concept prototype (POC). This study aimed at investigating the usability of the POC by conducting two usability tests with students. We assessed the usability and the students' workload and success in completing tasks. In the second usability test, however, they faced difficulties in completing the tasks. We will work on hiding the complexity of the framework as well as improving the frontend and the instructions.

Multi-Stakeholder Design for Complex Digital Health Systems: Development of a Modular Open Research Platform (MORE).

BACKGROUND: The Modular Open Research Platform (MORE) is being developed as an open-source platform for long-term situated digital health (DH) research and observations with the potential to facilitate studies, evaluations of DH interventions, and remote telehealth monitoring. OBJECTIVES: To implement an iterative development approach that integrates multi-stakeholder perspectives to support a single platform development process. METHOD: Capture, fulfil and balance the requirements of a multi-disciplinary group of stakeholders interacting with the system through a Delphi-inspired, iterative and participatory design process encompassing a series of workshops and online surveys. RESULTS: Through interaction with a multi-disciplinary group of key platform stakeholders, diverse feedback and requirements for the design and development process were elicited and integrated. CONCLUSION: Findings from the initial rounds of stakeholder involvement lay the stepping stone towards further iterations in the process. Experts who participated in the process reported being generally supportive of and feeling involved in the development process.

Investigating shared decision-making during the use of a digital health tool for physical activity planning in cardiac rehabilitation.

Background: Shared decision making (SDM) between healthcare professionals and persons with CVD can have a positive impact on motivation, adherence, or sustainability regarding long-term goals and integration of cardiovascular disease (CVD) rehabilitation in the everyday lives of persons with CVD. SDM can foster the transition between regular heart-healthy activity at rehabilitation facilities and more independent activity at home, but it is often challenging to implement SDM given limited time and resources, e.g., in the daily practice of rehabilitation. Digital tools can help but must be appropriately tailored for situated use and user needs. Objective: We aimed to (1) describe in how far SDM is manifested in the situated context when using a digital tool developed by our group, and, based on that, (2) reflect on how digital health tools can be designed to facilitate and improve the SDM process. Methods: In the context of a field study, we investigated how SDM is already naturally applied and manifested when using a digital tool for joint physical activity planning in cardiac rehabilitation in clinical practice. In a two-week qualitative study, we collected data on expectations, experiences and interactions during the use of a digital health tool by seven persons with CVD and five healthcare professionals. Data was collected by means of observations, interviews, questionnaires and a self-reported diary, and analysed with a particular focus on episodes related to SDM. Results: We found that SDM was manifested in the situated context to limited extent. For example, we identified high improvement potential for more structured goal-setting and more explicit consideration of preferences and routines. Based on mapping our findings to temporal phases where SDM can be adopted, we highlight implications for design to further support SDM in clinical practice. We consider this as "SDM supportive design in digital health apps," suggesting for example step-by-step guidance to be used during the actual consultation. Conclusion: This study contributes to further understanding and integration of SDM in digital health tools with a focus on rehabilitation, to empower and support both persons with CVD and healthcare professionals.

Research on Digital Technology Use in Cardiology: Bibliometric Analysis.

BACKGROUND: Digital technology uses in cardiology have become a popular research focus in recent years. However, there has been no published bibliometric report that analyzed the corresponding academic literature in order to derive key publishing trends and characteristics of this scientific area. OBJECTIVE: We used a bibliometric approach to identify and analyze the academic literature on digital technology uses in cardiology, and to unveil popular research topics, key authors, institutions, countries, and journals. We further captured the cardiovascular conditions and diagnostic tools most commonly investigated within this field. METHODS: The Web of Science electronic database was queried to identify relevant papers on digital technology uses in cardiology. Publication and citation data were acquired directly from the database. Complete bibliographic data were exported to VOSviewer, a dedicated bibliometric software package, and related to the semantic content of titles, abstracts, and keywords. A term map was constructed for findings visualization. RESULTS: The analysis was based on data from 12,529 papers. Of the top 5 most productive institutions, 4 were based in the United States. The United States was the most productive country (4224/12,529, 33.7%), followed by United Kingdom (1136/12,529, 9.1%), Germany (1067/12,529, 8.5%), China (682/12,529, 5.4%), and Italy (622/12,529, 5.0%). Cardiovascular diseases that had been frequently investigated included hypertension (152/12,529, 1.2%), atrial fibrillation (122/12,529, 1.0%), atherosclerosis (116/12,529, 0.9%), heart failure (106/12,529, 0.8%), and arterial stiffness (80/12,529, 0.6%). Recurring modalities were electrocardiography (170/12,529, 1.4%), angiography (127/12,529, 1.0%), echocardiography (127/12,529, 1.0%), digital subtraction angiography (111/12,529, 0.9%), and photoplethysmography (80/12,529, 0.6%). For a literature subset on smartphone apps and wearable devices, the Journal of Medical Internet Research (20/632, 3.2%) and other JMIR portfolio journals (51/632, 8.0%) were the major publishing venues. CONCLUSIONS: Digital technology uses in cardiology target physicians, patients, and the general public. Their functions range from assisting diagnosis, recording cardiovascular parameters, and patient education, to teaching laypersons about cardiopulmonary resuscitation. This field already has had a great impact in health care, and we anticipate continued growth.

Towards Adaptability of Just-in-Time Adaptive Interventions.

Just-in-time adaptive interventions (JITAIs) can promote behavior change in patients. It was the aim of our study to make JITAIs adaptable, i.e., to configure JITAIs for different purposes and to personalize them for different participants, whilst enabling central maintenance and integrated data analysis across deployments and individuals. We present a concept for adaptable JITAIs that was created following a design science approach. It builds on multi-level conceptual modeling and knowledge graphs and will be evaluated in user studies.

Process and Outcome Evaluations of Smartphone Apps for Bipolar Disorder: Scoping Review.

BACKGROUND: Mental health apps (MHAs) provide opportunities for accessible, immediate, and innovative approaches to better understand and support the treatment of mental health disorders, especially those with a high burden, such as bipolar disorder (BD). Many MHAs have been developed, but few have had their effectiveness evaluated. OBJECTIVE: This systematic scoping review explores current process and outcome measures of MHAs for BD with the aim to provide a comprehensive overview of current research. This will identify the best practice for evaluating MHAs for BD and inform future studies. METHODS: A systematic literature search of the health science databases PsycINFO, MEDLINE, Embase, EBSCO, Scopus, and Web of Science was undertaken up to January 2021 (with no start date) to narratively assess how studies had evaluated MHAs for BD. RESULTS: Of 4051 original search results, 12 articles were included. These 12 studies included 435 participants, and of these, 343 had BD type I or II. Moreover, 11 of the 12 studies provided the ages (mean 37 years) of the participants. One study did not report age data. The male to female ratio of the 343 participants was 137:206. The most widely employed validated outcome measure was the Young Mania Rating Scale, being used 8 times. The Hamilton Depression Rating Scale-17/Hamilton Depression Rating Scale was used thrice; the Altman Self-Rating Mania Scale, Quick Inventory of Depressive Symptomatology, and Functional Assessment Staging Test were used twice; and the Coping Inventory for Stressful Situations, EuroQoL 5-Dimension Health Questionnaire, Generalized Anxiety Disorder Scale-7, Inventory of Depressive Symptomatology, Mindfulness Attention Awareness Scale, Major Depression Index, Morisky-Green 8-item, Perceived Stress Scale, and World Health Organization Quality of Life-BREF were used once. Self-report measures were captured in 9 different studies, 6 of which used MONARCA. Mood and energy levels were the most commonly used self-report measures, being used 4 times each. Furthermore, 11 of the 12 studies discussed the various confounding factors and barriers to the use of MHAs for BD. CONCLUSIONS: Reported low adherence rates, usability challenges, and privacy concerns act as barriers to the use of MHAs for BD. Moreover, as MHA evaluation is itself developing, guidance for clinicians in how to aid patient choices in mobile health needs to develop. These obstacles could be ameliorated by incorporating co-production and co-design using participatory patient approaches during the development and evaluation stages of MHAs for BD. Further, including qualitative aspects in trials that examine patient experience of both mental ill health and the MHA itself could result in a more patient-friendly fit-for-purpose MHA for BD.