EMPOWERing Patients With Diabetes Using Profiling and Targeted Feedbacks Delivered Through Smartphone App and Wearable (EMPOWER): Protocol for a Randomized Controlled Trial on Effectiveness and Implementation

Digital health technologies/interventions in smart ward development for elderly patients with diabetes: A perspective from China and beyond

Diabetes is highly prevalent among the elderly worldwide, with the highest number of diabetes cases in China. Yet, the management of diabetes remains unsatisfactory. Recent advances in digital health technologies have facilitated the establishment of smart wards for diabetes patients. There is a lack of smart wards tailored specifically for older diabetes patients who encounter unique challenges in glycemic control and diabetes management, including an increased vulnerability to hypoglycemia, the presence of multiple chronic diseases, and cognitive decline. In this review, studies on digital health technologies for diabetes in China and beyond were summarized to elucidate how the adoption of digital health technologies, such as real-time continuous glucose monitoring, sensor-augmented pump technology, and their integration with 5th generation networks, big data cloud storage, and hospital information systems, can address issues specifically related to elderly diabetes patients in hospital wards. Furthermore, the challenges and future directions for establishing and implementing smart wards for elderly diabetes patients are discussed, and these challenges may also be applicable to other countries worldwide, not just in China. Taken together, the smart wards may enhance clinical outcomes, address specific issues, and eventually improve patient-centered hospital care for elderly patients with diabetes.

Patient engagement in radiation oncology: a large retrospective study of survey response dynamics

Purpose

Patient satisfaction surveys are pivotal in evaluating healthcare quality and enhancing patient care. Understanding the factors influencing patient engagement with these surveys in radiation oncology can guide improvements in patient-centered care.

Methods

This retrospective study analyzed data from radiation oncology patients at a large multi-site single-institution center from May 2021 to January 2024. We assessed the influence of demographic, clinical, and socioeconomic factors on the likelihood of survey participation using univariate (UVA) and multivariable (MVA) logistic regression analyses. Factors included age, gender, race, socioeconomic status (SES) via Area Deprivation Index (ADI), language, marital status, smoking, employment, insurance type, mental health disorders (MHD), comorbidity index (CCI), and cancer type.

Results

In a comprehensive analysis of 11,859 patients, most were female (57.2%), over 65 years old (60.7%), and primarily insured by Medicare (45.9%). MVA showed that higher socioeconomic disadvantage significantly decreased survey participation (ADI third tertile vs. first tertile OR=0.708, p<0.001), with each unit increase in ADI reducing the odds of completion by 1% (p<0.001). Older adults, and patients with head and neck or genitourinary cancers were significantly more likely to participate, while those with higher comorbidities, MHD, or other minority status were less engaged (p<0.001). Telemedicine encounters also significantly increased participation compared to in-person visits (OR=1.149, p=0.006).

Conclusions

Multiple factors including age, race, SES, insurance type, cancer type, health conditions, and modality of healthcare delivery influence patient engagement with satisfaction surveys in radiation oncology. Strategies to enhance patient engagement must consider these diverse influences to ensure comprehensive and inclusive feedback mechanisms in healthcare settings. Tailored interventions to mitigate barriers specific to underrepresented groups are crucial for capturing a broad spectrum of patient experiences and improving the overall quality of patient care.

Scoping review of digital health technologies and interventions that target lifestyle behavior change in Singapore

Objective

A rise in non-communicable diseases, driven by poor lifestyle behaviors, demands a shift from conventional, reactive, and episodic care to next-gen, proactive, and real-time lifestyle management. Digital health technologies (DHTs) and digital health interventions (DHIs) are poised to shepherd this transformation. Given the proliferation of digital health applications, a scoping review was conducted to map the DHTs and DHIs targeting lifestyle behavior change in Singapore.

Methods

A systematic search of PubMed, Scopus, and clinical trial registries and a manual search of gray literature and mobile app stores were conducted to identify patient-facing IoT (internet of things) technologies (wearables, apps, bots, websites) that target physical activity, diet, tobacco/alcohol use, sleep quality, and/or mindfulness in Singapore from 2013 to 2023.

Results

Forty-six DHTs and thirty-five DHIs were identified. Apps were the most common while websites and bots were the least common. Most DHTs and DHIs played monitoring or preventative behavior change functions. Most applications targeted multiple behaviors, with physical activity being the most common and tobacco/alcohol use being the least common. Behavioral change strategies included feedback and monitoring (80%), goals and planning (70%), associations (62%), personalization (59%), gamification (54%), rewards (33%), human coaching (30%), and just-in-time adaptations (4%).

Conclusion

This review identified gaps in digital health applications that address addictive behaviors and the elderly. Future efforts should prioritize adaptive, personalized technologies based on user-centric designs and robust behavioral frameworks to enhance long-term behavioral change. Insights from Singapore's experience can guide the global development of more effective health-improving digital applications.

Acceptability of an AI-enabled family module in a mobile app for enhanced diabetes management: Patient and family perspectives

Objective

To explore the acceptability of family support through an AI-enabled mobile app and identify preferences for its novel family module features among patients with type 2 diabetes (T2DM) and family members.

Methods

Semi-structured interviews were conducted with patients with T2DM and family members. A mock wireframe of the FAMILY module was created to help participants visualize the module features. All interviews were audio-recorded and transcribed verbatim. Inductive thematic analysis using the constant-comparative method was performed to identify and interpret patterns within the data.

Results

A total of 25 patients with T2DM and 25 family members participated in the study. Participants viewed the FAMILY module as a valuable tool for reinforcing patients' self-discipline. However, some patients expressed concerns about family involvement, particularly among those who preferred greater control and autonomy over their self-management plan. Family members also raised concerns about caregiving burden and feelings of self-blame if they were unable to provide adequate support. Regarding module features, participants appreciated algorithm-driven nudges and in-app interactions but emphasized the importance of controlling the frequency of nudges. Features such as collaborative goal setting, report cards, and AI-powered smart logging were found useful. However, family members expressed a need for more personalized in-app advice on patient data and medical terminology to better support patient's self-care. In-app family resources should be tailored to meet the needs of first-time caregivers to enhance the module's usability.

Conclusion

The insights from this study will guide the development of the novel FAMILY module and inform targeted interventions aimed at mitigating risks, managing T2DM-related comorbidities, and enhancing self-care.

Association of Novel Clinical and Behavioural Markers with HbA1c Improvement: A Latent Class Analysis of 912 Patients with Type 2 Diabetes Mellitus

OBJECTIVE

The escalating prevalence of Type 2 Diabetes Mellitus (T2DM) overwhelms healthcare systems. Lifestyle interventions enhancing patient monitoring and adherence vary in efficacy, emphasizing the need to understand differential response across patient subgroups. This study aimed to segment patients with T2DM into distinct latent classes and identify characteristics associated with optimal 12-month glycated haemoglobin (HbA1c) reduction.

METHODS

We prospectively recruited 1000 patients with T2DM from government-funded outpatient clinics in Singapore, aged ≥ 40-year-old with HbA1c ≥ 7.0 %. Exclusion criteria included insulin treatment and cognitive impairment. Latent class analysis was applied to 912 patients, using mHealth interventions, age, education, living arrangement, baseline HbA1c, step count, and motivation (Patient Activation Measure) as indicators. 12-Month HbA1c reduction was assessed with one-way ANOVA and pairwise T-test.

RESULTS

Within cohort, younger patients with higher education, physical activity, and baseline HbA1c exhibited the greatest HbA1c improvement (1.14 ± 1.79 %). Younger patients with lower education, despite high baseline HbA1c, exhibited a moderately lower HbA1c improvement (0.52 ± 1.41 %).

CONCLUSION

Individuals with higher baseline HbA1c, education, motivation, and activity levels experienced the most significant HbA1c reductions in response to lifestyle interventions. A tailored approach to these modifiable characteristics may help patients achieve substantial 12-month HbA1c reductions.

Medication Management Initiatives Using Wearable Devices: Scoping Review

Background

Wearable devices (WDs) have evolved beyond simple fitness trackers to sophisticated health monitors capable of measuring vital signs, such as heart rate and blood oxygen levels. Their application in health care, particularly medication management, is an emerging field poised to significantly enhance patient adherence to treatment regimens. Despite their widespread use and increasing incorporation into clinical trials, a comprehensive review of WDs in terms of medication adherence has not been conducted.

Objective

This study aimed to conduct a comprehensive scoping review to evaluate the impact of WDs on medication adherence across a variety of diseases, summarizing key research findings, outcomes, and challenges encountered.

Methods

Adhering to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, a structured search was conducted across MEDLINE, Web of Science, and Embase databases, covering the literature from January 1, 2010, to September 30, 2022. The search strategy was based on terms related to WDs and medication adherence, specifically focusing on empirical studies to ensure the inclusion of original research findings. Studies were selected based on their relevance to medication adherence, usage of WDs in detecting medication-taking actions, and their role in integrated medication management systems.

Results

We screened 657 articles and identified 18 articles. The identified studies demonstrated the diverse applications of WDs in enhancing medication adherence across diseases such as Parkinson disease, diabetes, and cardiovascular conditions. The geographical distribution and publication years of these studies indicate a growing interest in this research area. The studies were divided into three types: (1) studies reporting a correlation between data from WDs or their usage and medication adherence or drug usage as outcomes, (2) studies using WDs to detect the act of medication-taking itself, and (3) studies proposing an integrated medication management system that uses WDs in managing medication.

Conclusions

WDs are increasingly being recognized for their potential to enhance medication management and adherence. This review underscores the need for further empirical research to validate the effectiveness of WDs in real-life settings and explore their use in predicting adherence based on activity rhythms and activities. Despite technological advancements, challenges remain regarding the integration of WDs into routine clinical practice. Future research should focus on leveraging the comprehensive data provided by WDs to develop personalized medication management strategies that can improve patient outcomes.

Visual analysis of patient safety research hotspots and trends in the context of telemedicine based on Web of Science

To analyze the research status, hotspots, and trends of patient safety in the context of international telemedicine, and to provide reference for future research in various countries. The literature pertaining to patient safety within the realm of telemedicine was systematically retrieved from the Web of Science core collection database, encompassing the period from January 2010 to December 2023. Visual analysis of publication quantity, primary authorship, and keyword trends was conducted using CiteSpace (6.2R6) software. The geographical distribution of research focus was visualized through VOSviewer software and SCImago Graphica software, while research institutions were depicted using VOSviewer software and Highcharts software. Data organization was facilitated by Excel 2019 software. A total of 5356 related articles were included, and the number of published papers showed an overall upward trend, and the countries and institutions with the largest number of papers were the United States and Harvard University, respectively, and a stable core author research population had not yet been formed in this research field. Through keyword analysis, it can be seen that the research hotspots mainly focus on the research on the influencing factors of patient safety in the context of telemedicine, the research on the application value of telemedicine, and the research on coping strategies that affect patient safety. The research on patient safety in the context of telemedicine in foreign countries has a certain depth and breadth, which has important reference significance for improving the medical quality and patient safety of Internet hospitals in various countries.

Exploring the Implementation of Shared Decision-Making Involving Health Coaches for Diabetes and Hypertension Self-Management: Qualitative Study

BACKGROUND

An emerging focus on person-centered care has prompted the need to understand how shared decision-making (SDM) and health coaching could support self-management of diabetes and hypertension.

OBJECTIVE

This study aims to explore preferences for the scope of involvement of health coaches and health care professionals (HCPs) in SDM and the factors that may influence optimal implementation of SDM from the perspectives of patients and HCPs.

METHODS

We conducted focus group discussions with 39 patients with diabetes and hypertension and 45 HCPs involved in their care. The main topics discussed included the roles of health coaches and HCPs in self-management, views toward health coaching and SDM, and factors that should be considered for optimal implementation of SDM that involves health coaches. All focus group discussions were audio recorded, transcribed verbatim, and analyzed using thematic analysis.

RESULTS

Participants agreed that the main responsibility of HCPs should be identifying the patient's stage of change and medication education, while health coaches should focus on lifestyle education, monitoring, and motivational conversation. The health coach was seen to be more effective in engaging patients in lifestyle education and designing goal management plans as health coaches have more time available to spend with patients. The importance of a health coach's personal attributes (eg, sufficient knowledge of both medical and psychosocial management of disease conditions) and credentials (eg, openness, patience, and empathy) was commonly emphasized. Participants viewed that addressing the following five elements would be necessary for the optimal implementation of SDM: (1) target population (newly diagnosed and less stable patients), (2) commitment of all stakeholders (discrepancy on targeted times and modality), (3) continuity of care (familiar faces), (4) philosophy of care (person-centered communication), and (5) faces of legitimacy (physician as the ultimate authority).

CONCLUSIONS

The findings shed light on the appropriate roles of health coaches vis-à-vis HCPs in SDM as perceived by patients and HCPs. Findings from this study also contribute to the understanding of SDM on self-management strategies for patients with diabetes and hypertension and highlight potential opportunities for integrating health coaches into the routine care process.

Smartphone applications for nutrition Support: A systematic review of the target outcomes and main functionalities

INTRODUCTION

A proper nutrition is essential for human life. Recently, special attention on this topic has been given in relation to three health statuses: obesity, malnutrition and specific diseases that can be related to food or treated with specific diets. Mobile technology is often used to assist users that wish to regulate their eating habits, and identifying which fields of application have been explored the most by the app developers and which main functionalities have been adopted can be useful in view of future app developments.

METHODS

We selected 322 articles mentioning nutrition support apps through a literature database search, all of which have undergone an initial screening. After the exclusion of papers that were already reviews, not presenting apps or not focused on nutrition, not relevant or not developed for human subjects, 100 papers were selected for subsequent analyses that aimed at identifying the main treated conditions, outcome measures and functionalities implemented in the Apps.

RESULTS

Of the selected studies, 33 focus on specific diseases, 24 on obesity, 2 on malnutrition and 41 on other targets (e.g., weight/diet control). Type 2 diabetes is the most targeted disease, followed by gestational diabetes, hypertension, colorectal cancer and CVDs which all were targeted by more than one app. Most Apps include self-monitoring and coaching functionalities, educational content and artificial intelligence (AI) tools are slightly less common, whereas counseling, gamification and questionnaires are the least implemented. Body weight and calories/nutrients were the most common general outcome measures, while glycated hemoglobin (HbA1c) was the most common clinical outcome. No statistically significant differences in the effectiveness of the different functionalities were found.

CONCLUSION

The use of mobile technology to improve nutrition has been widely explored in the last years, especially for weight control and specific diseases like diabetes; however, other food-related conditions such as Irritable Bowel Diseases appear to be less targeted by newly developed smartphone apps and their related studies. All different kinds of functionalities appear to be equally effective, but further specific studies are needed to confirm the results.

Acceptability of Mobile App-Based Motivational Interviewing and Preferences for App Features to Support Self-Management in Patients With Type 2 Diabetes: Qualitative Study

BACKGROUND

Patients with type 2 diabetes mellitus (T2DM) experience multiple barriers to improving self-management. Evidence suggests that motivational interviewing (MI), a patient-centered communication method, can address patient barriers and promote healthy behavior. Despite the value of MI, existing MI studies predominantly used face-to-face or phone-based interventions. With the growing adoption of smartphones, automated MI techniques powered by artificial intelligence on mobile devices may offer effective motivational support to patients with T2DM.

OBJECTIVE

This study aimed to explore the perspectives of patients with T2DM on the acceptability of app-based MI in routine health care and collect their feedback on specific MI module features to inform our future intervention.

METHODS

We conducted semistructured interviews with patients with T2DM, recruited from public primary care clinics. All interviews were audio recorded and transcribed verbatim. Thematic analysis was conducted using NVivo.

RESULTS

In total, 33 patients with T2DM participated in the study. Participants saw MI as a mental reminder to increase motivation and a complementary care model conducive to self-reflection and behavior change. Yet, there was a sense of reluctance, mainly stemming from potential compromise of autonomy in self-care by the introduction of MI. Some participants felt confident in their ability to manage conditions independently, while others reported already making changes and preferred self-management at their own pace. Compared with in-person MI, app-based MI was viewed as offering a more relaxed atmosphere for open sharing without being judged by health care providers. However, participants questioned the lack of human touch, which could potentially undermine a patient-provider therapeutic relationship. To sustain motivation, participants suggested more features of an ongoing supportive nature such as the visualization of milestones, gamified challenges and incremental rewards according to achievements, tailored multimedia resources based on goals, and conversational tools that are interactive and empathic.

CONCLUSIONS

Our findings suggest the need for a hybrid model of intervention involving both app-based automated MI and human coaching. Patient feedback on specific app features will be incorporated into the module development and tested in a randomized controlled trial.

A Mobile Application to Improve Diabetes Self-Management Using Rapid Prototyping: Iterative Co-Design Approach in Asian Settings

BACKGROUND

Diabetes is a global public health issue, causing burden on healthcare system and increasing risk of mortality. Mobile applications (apps) can be a promising approach to facilitate diabetes self-management. An increasingly utilized approach to facilitate engagement with mobile health (mHealth) technology is to involve potential users in the creation of the technology.

OBJECTIVE

The aim of this study was to use co-design for type 2 diabetes mellitus (T2DM) self-management mHealth development.

METHODS

Three rounds of iterative rapid prototyping panel sessions were conducted with a total of 9 T2DM participants in an Asian setting between Oct 2020 and April 2021. The participants were recruited through convenience sampling. For each round, feedback was gathered through qualitative interviews, and the feedback was used as a reference by the development team to develop and test a more refined version of the app in the next round. Transcribed semi-structured interview data was analyzed thematically using an inductive approach.

RESULTS

Participants' ages ranged from 40 to 69 years. Data saturation was reached, with no new themes emerging from the data. During the sessions, the participants expressed a variety of concerns and feedback on T2DM self-management using EMPOWER app and raised suggestions on the features of ideal T2DM self-management app. Important features include 1) reminders and notifications for medications, 2) Bluetooth integration with glucometers and blood pressure machines to minimize manual entry, 3) enlarged local food database including information on sugar content and recommendations for healthier options, 4) one touch for logging of routine medications and favorite foods, 5) export function for data sharing with physicians. Overall inputs concerned aspects such as user-friendliness of the app, customization possibilities, and educational content for the features in the mobile app.

CONCLUSION

In this study, we explored users' opinions on a T2DM self-management mobile app using co-design approach. This study adds to the growing body of literature on co-designing behavioral mHealth interventions and can potentially guide researchers in mobile app design for other chronic conditions.