A Mobile-Based Tailored Recommendation System for Parents of Children with Overweight or Obesity: A New Tool for Health Care Centers

Health recommender systems to facilitate collaborative decision-making in chronic disease management: A scoping review

Objective

Health recommender systems (HRSs) are increasingly used to complement existing clinical decision-making processes, but their use for chronic diseases remains underexplored. Recognizing the importance of collaborative decision making (CDM) and patient engagement in chronic disease treatment, this review explored how HRSs support patients in managing their illness.

Methods

A scoping review was conducted using the framework proposed by Arksey and O'Malley, advanced by Levac et al., in line with the PRISMA-ScR checklist. Quantitative (descriptive numerical summary) and qualitative (inductive content analysis) methods wered used to synthesize the data.

Results

Forty-five articles were included in the final review, most commonly covering diabetes (9/45, 20%), mental health (9/45, 20.0%), and tobacco dependence (7/45, 15.6%). Behavior change theories (10/45, 22.2%) and authoritative sources (10/45, 22.2%) were the most commonly referenced sources for design and development work. From the thematic analysis, we conclude: (a) the main goal of HRSs is to induce behavior change, but limited research investigates their effectiveness in achieving this aim; (b) studies acknowledge that theories, models, frameworks, and/or guidelines help design HRSs to elicit specific behavior change, but they do not implement them; (c) connections between CDM and HRS purpose should be more explicit; and (d) HRSs can often offer other self-management services, such as progress tracking and chatbots.

Conclusions

We recommend a greater emphasis on evaluation outcomes beyond algorithmic performance to determine HRS effectiveness and the creation of an evidence-driven, methodological approach to creating HRSs to optimize their use in enhancing patient care.

Lay summary

Our work aims to provide a summary of the current landscape of health recommender system (HRS) use for chronic disease management. HRSs are digital tools designed to help people manage their health by providing personalized recommendations based on their health history, behaviors, and preferences, enabling them to make more informed health decisions. Given the increased use of these tools for personalized care, and especially with advancements in generative artificial intelligence, understanding the current methods and evaluation processes used is integral to optimizing their effectiveness. Our findings show that HRSs are most used for diabetes, mental health, and tobacco dependence, but only a small percentage of publications directly reference and/or use relevant frameworks to help guide their design and evaluation processes. Furthermore, the goal for most of these HRSs is to induce behavior change, but there is limited research investigating how effective they are in accomplishing this. Given these findings, we recommend that evaluations shift their focus from algorithms to more holistic approaches and to be more intentional about the processes used when designing the tool to support an evidence-driven approach and ultimately create more effective and useful HRSs for chronic disease management.

Recommender systems use in weight management mHealth interventions: A scoping review

The use of recommender systems in mobile health apps for weight control has grown, but user app uptake and engagement remain limited. The objective of our scoping review was to explore the influence of recommender systems on mHealth app user engagement, identify the theoretical frameworks that have been applied on digital health interventions designed for weight management, and examine the key aspects that support tailoring user engagement through recommender systems. Based on existing literature, we identified 13 articles on recommender systems for weight management. Themes emerged, including theoretical underpinnings, authors' domain knowledge, user motivation, and design. Most studies used constructs from the social cognitive theory. We found inconsistencies between authors' domain knowledge and the intervention's content, with few professionals from the health and psychology fields. Only 46% of articles measured user engagement, whereas gamification and tailored messages were common app features. Despite some positive weight change results, more attention is needed toward implementing behavior theory and other strategies to promote app user engagement. Future studies should more accurately measure user motivation and identify the best features and behavioral constructs to increase app user interaction. Larger studies with a more diverse population are needed to generalize findings and evaluate weight loss maintenance and physical activity habits among users of recommender system.

Analysis of Strategies to Increase User Retention of Fitness Mobile Apps during and after the COVID-19 Pandemic

The COVID-19 pandemic has changed the fitness-related field. More people started working out at home, and the use of fitness mobile apps that can measure the amount of exercise through a scientific method has increased compared to before the COVID-19 pandemic. This phenomenon is likely to continue even after the COVID-19 pandemic, and therefore this study aimed to investigate the importance of and satisfaction with a fitness app's functions according to consumers while using the fitness mobile app. Through this study, we intended to provide data for creating an environment where users can use fitness mobile apps consistently. A total of 420 questionnaires were distributed through Google Survey for about 3 months, from 13 September to 20 November 2020, and a total of 399 complete questionnaires were analyzed in this study. Regarding the data processing methods, frequency analysis, exploratory factor analysis, reliability analysis, descriptive statistical analysis, and IPA were used. The results are as follows. First, the first quadrant of the IPA matrix indicated the high importance of and satisfaction with the fitness mobile app, and included five attributes: cost-effectiveness, easy-to-understand information, ease of use and application, privacy protection, and compatibility with other devices. Second, the second quadrant of the matrix indicated relatively low satisfaction in association to high importance and included five attributes: accurate exercise information provision, design efficiency, daily exercise amount setting, convenient icons and interface, and provision of images and videos in appropriate proportions. Third, the third quadrant of the matrix, indicating low importance and low satisfaction, included five attributes: not sharing personal information, overall design composition and color, customer service, reliable security level, and providing information on goal achievement after exercising. Fourth, in the quadrant of the matrix, indicating low importance and high satisfaction, five attributes were included: exercise notification function, continuous service provision, step count and heart rate information, individual exercise recommendation, and individual body type analysis information.

Tailoring Can Improve Consumers’ Hygienic Food-Handling Behavior to Reduce the Transmission Risk of Antimicrobial-Resistant Bacteria through Food

Antimicrobial-resistant (AMR) bacteria spread via food to humans and can seriously impair infection treatment. Hygienic food handling is an effective measure to avoid the transmission of bacteria. Therefore, we tested three types of interventions (tailored, generic, and no intervention) for their effectiveness in improving consumers’ hygienic food handling against the spread of antimicrobial-resistant bacteria through foods in a longitudinal randomized control trial. We based the determinants of hygienic food-handling behavior on the Health Action Process Approach (HAPA). The tailored intervention raised self-reported hygienic food handling, self-efficacy, and perceived likelihood of risk compared to no intervention. Moreover, interventions yielded different effects for participants with high vs. low intentions to improve their food-handling behavior. However, there were no differences between the tailored and generic interventions. More research is needed to find out whether including other behavior change techniques in the tailored intervention may increase the effect of tailoring.