Breathing as Input Modality in a Gameful Breathing Training App: Development and Evaluation of Breeze 2 (Preprint)

A holistic lifestyle mobile health intervention for the prevention of type 2 diabetes and common mental disorders in Asian women with a history of gestational diabetes: a randomised control trial with 3-year follow-up protocol

BACKGROUND

Women with a history of gestational diabetes mellitus (GDM) are 12-fold more likely to develop type 2 diabetes (T2D) 4-6 years after delivery than women without GDM. Similarly, GDM is associated with the development of common mental disorders (CMDs) (e.g. anxiety and depression). Evidence shows that holistic lifestyle interventions focusing on physical activity (PA), dietary intake, sleep, and mental well-being strategies can prevent T2D and CMDs. This study aims to assess the effectiveness of a holistic lifestyle mobile health intervention (mHealth) with post-GDM women in preventing T2D and CMDs in a community setting in Singapore.

METHODS

The study consists of a 1-year randomised controlled trial (RCT) with a 3-year follow-up period. Post-GDM women with no current diabetes diagnosis and not planning to become pregnant will be eligible for the study. In addition, participants will complete mental well-being questionnaires (e.g. depression, anxiety, sleep) and their child's socio-emotional and cognitive development. The participants will be randomised to either Group 1 (Intervention) or Group 2 (comparison). The intervention group will receive the "LVL UP App", a smartphone-based, conversational agent-delivered holistic lifestyle intervention focused on three pillars: Move More (PA), Eat Well (Diet), and Stress Less (mental wellbeing). The intervention consists of health literacy and psychoeducational coaching sessions, daily "Life Hacks" (healthy activity suggestions), slow-paced breathing exercises, a step tracker (including brisk steps), a low-burden food diary, and a journaling tool. Women from both groups will be provided with an Oura ring for tracking physical activity, sleep, and heart rate variability (a proxy for stress), and the "HAPPY App", a mHealth app which provides health promotion information about PA, diet, sleep, and mental wellbeing, as well as display body mass index, blood pressure, and results from the oral glucose tolerance tests. Short-term aggregate effects will be assessed at 26/27 weeks (midpoint) and a 1-year visit, followed by a 2, 3, and 4-year follow-up period.

DISCUSSION

High rates of progression of T2D and CMDs in women with post-GDM suggest an urgent need to promote a healthy lifestyle, including diet, PA, sleep, and mental well-being. Preventive interventions through a holistic, healthy lifestyle may be the solution, considering the inextricable relationship between physical and psychological health. We expect that holistic lifestyle mHealth may effectively support behavioural changes among women with a history of GDM to prevent T2D and CMDs.

TRIAL STATUS

The protocol study was approved by the National Healthcare Group in Singapore, Domain Specific Review Board (DSRB) [2023/00178]; June 2023. Recruitment began on October 18, 2023.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05949957. The first submission date is June 08, 2023.

Engagement With a Relaxation and Mindfulness Mobile App Among People With Cancer: Exploratory Analysis of Use Data and Self-Reports From a Randomized Controlled Trial

BACKGROUND

Mobile health (mHealth) apps offer unique opportunities to support self-care and behavior change, but poor user engagement limits their effectiveness. This is particularly true for fully automated mHealth apps without any human support. Human support in mHealth apps is associated with better engagement but at the cost of reduced scalability.

OBJECTIVE

This work aimed to (1) describe the theory-informed development of a fully automated relaxation and mindfulness app to reduce distress in people with cancer (CanRelax app 2.0), (2) describe engagement with the app on multiple levels within a fully automated randomized controlled trial over 10 weeks, and (3) examine whether engagement was related to user characteristics.

METHODS

The CanRelax app 2.0 was developed in iterative processes involving input from people with cancer and relevant experts. The app includes evidence-based relaxation exercises, personalized weekly coaching sessions with a rule-based conversational agent, 39 self-enactable behavior change techniques, a self-monitoring dashboard with gamification elements, highly tailored reminder notifications, an educational video clip, and personalized in-app letters. For the larger study, German-speaking adults diagnosed with cancer within the last 5 years were recruited via the web in Switzerland, Austria, and Germany. Engagement was analyzed in a sample of 100 study participants with multiple measures on a micro level (completed coaching sessions, relaxation exercises practiced with the app, and feedback on the app) and a macro level (relaxation exercises practiced without the app and self-efficacy toward self-set weekly relaxation goals).

RESULTS

In week 10, a total of 62% (62/100) of the participants were actively using the CanRelax app 2.0. No associations were identified between engagement and level of distress at baseline, sex assigned at birth, educational attainment, or age. At the micro level, 71.88% (3520/4897) of all relaxation exercises and 714 coaching sessions were completed in the app, and all participants who provided feedback (52/100, 52%) expressed positive app experiences. At the macro level, 28.12% (1377/4897) of relaxation exercises were completed without the app, and participants' self-efficacy remained stable at a high level. At the same time, participants raised their weekly relaxation goals, which indicates a potential relative increase in self-efficacy.

CONCLUSIONS

The CanRelax app 2.0 achieved promising engagement even though it provided no human support. Fully automated social components might have compensated for the lack of human involvement and should be investigated further. More than one-quarter (1377/4897, 28.12%) of all relaxation exercises were practiced without the app, highlighting the importance of assessing engagement on multiple levels.

Deep breathing in your hands: designing and assessing a DTx mobile app

Digital Therapeutics (DTx) are experiencing rapid advancements within mobile and mental healthcare sectors, with their ubiquity and enhanced accessibility setting them apart as uniquely effective solutions. In this evolving context, our research focuses on deep breathing, a vital technique in mental health management, aiming to optimize its application in DTx mobile platforms. Based on well-founded theories, we introduced a gamified and affordance-driven design, facilitating intuitive breath control. To enhance user engagement, we deployed the Mel Frequency Cepstral Coefficient (MFCC)-driven personalized machine learning method for accurate biofeedback visualization. To assess our design, we enlisted 70 participants, segregating them into a control and an intervention group. We evaluated Heart Rate Variability (HRV) metrics and collated user experience feedback. A key finding of our research is the stabilization of the Standard Deviation of the NN Interval (SDNN) within Heart Rate Variability (HRV), which is critical for stress reduction and overall health improvement. Our intervention group observed a pronounced stabilization in SDNN, indicating significant stress alleviation compared to the control group. This finding underscores the practical impact of our DTx solution in managing stress and promoting mental health. Furthermore, in the assessment of our intervention cohort, we observed a significant increase in perceived enjoyment, with a notable 22% higher score and 10.69% increase in positive attitudes toward the application compared to the control group. These metrics underscore our DTx solution's effectiveness in improving user engagement and fostering a positive disposition toward digital therapeutic efficacy. Although current technology poses challenges in seamlessly incorporating machine learning into mobile platforms, our model demonstrated superior effectiveness and user experience compared to existing solutions. We believe this result demonstrates the potential of our user-centric machine learning techniques, such as gamified and affordance-based approaches with MFCC, which could contribute significantly to the field of mobile mental healthcare.

Non-pharmaceutical interventions to optimize cancer immunotherapy

The traditional picture of cancer patients as weak individuals requiring maximum rest and protection is beginning to dissolve. Too much focus on the medical side and one's own vulnerability and mortality might be counterproductive and not doing justice to the complexity of human nature. Unlike cytotoxic and lympho-depleting treatments, immune-engaging therapies strengthen the immune system and are typically less harmful for patients. Thus, cancer patients receiving checkpoint inhibitors are not viewed as being vulnerable per se, at least not in immunological and physical terms. This perspective article advocates a holistic approach to cancer immunotherapy, with an empowered patient in the center, focusing on personal resources and receiving domain-specific support from healthcare professionals. It summarizes recent evidence on non-pharmaceutical interventions to enhance the efficacy of immune checkpoint blockade and improve quality of life. These interventions target behavioral factors such as diet, physical activity, stress management, circadian timing of checkpoint inhibitor infusion, and waiving unnecessary co-medication curtailing immunotherapy efficacy. Non-pharmaceutical interventions are universally accessible, broadly applicable, instantly actionable, scalable, and economically sustainable, creating value for all stakeholders involved. Most importantly, this holistic framework re-emphasizes the patient as a whole and harnesses the full potential of anticancer immunity and checkpoint blockade, potentially leading to survival benefits. Digital therapeutics are proposed to accompany the patients on their mission toward change in lifestyle-related behaviors for creating optimal conditions for treatment efficacy and personal growth.

Development of "LvL UP 1.0": a smartphone-based, conversational agent-delivered holistic lifestyle intervention for the prevention of non-communicable diseases and common mental disorders

Background

Non-communicable diseases (NCDs) and common mental disorders (CMDs) are the leading causes of death and disability worldwide. Lifestyle interventions via mobile apps and conversational agents present themselves as low-cost, scalable solutions to prevent these conditions. This paper describes the rationale for, and development of, "LvL UP 1.0″, a smartphone-based lifestyle intervention aimed at preventing NCDs and CMDs.

Materials and Methods

A multidisciplinary team led the intervention design process of LvL UP 1.0, involving four phases: (i) preliminary research (stakeholder consultations, systematic market reviews), (ii) selecting intervention components and developing the conceptual model, (iii) whiteboarding and prototype design, and (iv) testing and refinement. The Multiphase Optimization Strategy and the UK Medical Research Council framework for developing and evaluating complex interventions were used to guide the intervention development.

Results

Preliminary research highlighted the importance of targeting holistic wellbeing (i.e., both physical and mental health). Accordingly, the first version of LvL UP features a scalable, smartphone-based, and conversational agent-delivered holistic lifestyle intervention built around three pillars: Move More (physical activity), Eat Well (nutrition and healthy eating), and Stress Less (emotional regulation and wellbeing). Intervention components include health literacy and psychoeducational coaching sessions, daily "Life Hacks" (healthy activity suggestions), breathing exercises, and journaling. In addition to the intervention components, formative research also stressed the need to introduce engagement-specific components to maximise uptake and long-term use. LvL UP includes a motivational interviewing and storytelling approach to deliver the coaching sessions, as well as progress feedback and gamification. Offline materials are also offered to allow users access to essential intervention content without needing a mobile device.

Conclusions

The development process of LvL UP 1.0 led to an evidence-based and user-informed smartphone-based intervention aimed at preventing NCDs and CMDs. LvL UP is designed to be a scalable, engaging, prevention-oriented, holistic intervention for adults at risk of NCDs and CMDs. A feasibility study, and subsequent optimisation and randomised-controlled trials are planned to further refine the intervention and establish effectiveness. The development process described here may prove helpful to other intervention developers.