Effects of Mobile Health Prompts on Self-Monitoring and Exercise Behaviors Following a Diabetes Prevention Program: Secondary Analysis From a Randomized Controlled Trial

The Impact of Digital Self-Monitoring of Weight on Improving Diabetes Clinical Outcomes: Quasi-Randomized Study

BACKGROUND

The management of type 2 diabetes (T2D) and obesity, particularly in the context of self-monitoring, remains a critical challenge in health care. As nearly 80% to 90% of patients with T2D have overweight or obesity, there is a compelling need for interventions that can effectively manage both conditions simultaneously. One of the goals in managing chronic conditions is to increase awareness and generate behavioral change to improve outcomes in diabetes and related comorbidities, such as overweight or obesity. There is a lack of real-life evidence to test the impact of self-monitoring of weight on glycemic outcomes and its underlying mechanisms.

OBJECTIVE

This study aims to assess the efficacy of digital self-monitoring of weight on blood glucose (BG) levels during diabetes management, investigating whether the weight changes may drive glucose fluctuations.

METHODS

In this retrospective, real-world quasi-randomized study, 50% of the individuals who regularly used the weight monitoring (WM) feature were propensity score matched with 50% of the users who did not use the weight monitoring feature (NWM) based on demographic and clinical characteristics. All the patients were diagnosed with T2D and tracked their BG levels. We analyzed monthly aggregated data 6 months before and after starting their weight monitoring. A piecewise mixed model was used for analyzing the time trajectories of BG and weight as well as exploring the disaggregation effect of between- and within-patient lagged effects of weight on BG.

RESULTS

The WM group exhibited a significant reduction in BG levels post intervention (P<.001), whereas the nonmonitoring group showed no significant changes (P=.59), and both groups showed no differences in BG pattern before the intervention (P=.59). Furthermore, the WM group achieved a meaningful decrease in BMI (P<.001). Finally, both within-patient (P<.001) and between-patient (P=.008) weight variability was positively associated with BG levels. However, 1-month lagged back BMI was not associated with BG levels (P=.36).

CONCLUSIONS

This study highlights the substantial benefits of self-monitoring of weight in managing BG levels in patients with diabetes, facilitated by a digital health platform, and advocates for the integration of digital self-monitoring tools in chronic disease management. We also provide initial evidence of testing the underlying mechanisms associated with BG management, underscoring the potential role of patient empowerment.

Enhancing Behavioural Changes: A Narrative Review on the Effectiveness of a Multifactorial APP-Based Intervention Integrating Physical Activity

The rapid evolution of technologies is a key innovation in the organisation and management of physical activities (PA) and sports. The increase in benefits and opportunities related to the adoption of technologies for both the promotion of a healthy lifestyle and the management of chronic diseases is evident. In the field of telehealth, these devices provide personalised recommendations, workout monitoring and injury prevention. The study aimed to provide an overview of the landscape of technology application to PA organised to promote active lifestyles and improve chronic disease management. This review identified specific areas of focus for the selection of articles: the utilisation of mobile APPs and technological devices for enhancing weight loss, improving cardiovascular health, managing diabetes and cancer and preventing osteoporosis and cognitive decline. A multifactorial intervention delivered via mobile APPs, which integrates PA while managing diet or promoting social interaction, is unquestionably more effective than a singular intervention. The main finding related to promoting PA and a healthy lifestyle through app usage is associated with "behaviour change techniques". Even when individuals stop using the APP, they often maintain the structured or suggested lifestyle habits initially provided by the APP. Various concerns regarding the excessive use of APPs need to be addressed.

Evaluating Wall-Mounted Prompts to Facilitate Physical Activity-Related Discussion between Individuals with Cancer and Oncology Health Care Providers: A Pre-post Survey Study

Purpose

To evaluate the use of wall-mounted prompts in facilitating physical activity (PA)-related discussions between individuals with cancer and oncology care providers.

Methods

Individuals with cancer were approached to participate in a survey-based pre-post study. Half of participants (n = 100) completed a survey prior to installation of wall-mounted prompts in clinic while the other half (n = 100) completed a survey following installation of the prompts. Survey questions included content of PA-related discussion, satisfaction with PA education across treatment, and current PA level. The post-prompt survey also asked questions related to the prompt. Survey responses were analyzed using descriptive statistics. Chi-squared tests were performed to determine significance between timepoints.

Results

One hundred participants completed the survey at each timepoint. A significant difference was found pre and post-prompt in the number of PA discussions occurring overall during care (p = 0.03). Some participants (53%) were satisfied with the PA education received during treatment. There was no significant difference in occurrence of PA discussion (p = 0.36) pre and post-prompt and no difference in PA behaviour was observed (p = 0.130).

Conclusions

Wall-mounted prompts may be effective in increasing the frequency of PA-related discussions between individuals with cancer and their oncology team across treatment. Additional strategies, such as easy referral to rehabilitation professionals, are also needed to facilitate safe and effective PA behaviour during and after cancer treatments.

Designing and Developing a Mobile App for Management and Treatment of Gestational Diabetes in Nepal: User-Centered Design Study

BACKGROUND

Mobile apps can aid with the management of gestational diabetes mellitus (GDM) by providing patient education, reinforcing regular blood glucose monitoring and diet/lifestyle modification, and facilitating clinical and social support.

OBJECTIVE

This study aimed to describe our process of designing and developing a culturally tailored app, Garbhakalin Diabetes athawa Madhumeha-Dhulikhel Hospital (GDM-DH), to support GDM management among Nepalese patients by applying a user-centered design approach.

METHODS

A multidisciplinary team of experts, as well as health care providers and patients in Dhulikhel Hospital (Dhulikhel, Nepal), contributed to the development of the GDM-DH app. After finalizing the app's content and features, we created the app's wireframe, which illustrated the app's proposed interface, navigation sequences, and features and function. Feedback was solicited on the wireframe via key informant interviews with health care providers (n=5) and a focus group and in-depth interviews with patients with GDM (n=12). Incorporating their input, we built a minimum viable product, which was then user-tested with 18 patients with GDM and further refined to obtain the final version of the GDM-DH app.

RESULTS

Participants in the focus group and interviews unanimously concurred on the utility and relevance of the proposed mobile app for patients with GDM, offering additional insight into essential modifications and additions to the app's features and content (eg, inclusion of example meal plans and exercise videos).The mean age of patients in the usability testing (n=18) was 28.8 (SD 3.3) years, with a mean gestational age of 27.2 (SD 3.0) weeks. The mean usability score across the 10 tasks was 3.50 (SD 0.55; maximum score=5 for "very easy"); task completion rates ranged from 55.6% (n=10) to 94.4% (n=17). Findings from the usability testing were reviewed to further optimize the GDM-DH app (eg, improving data visualization). Consistent with social cognitive theory, the final version of the GDM-DH app supports GDM self-management by providing health education and allowing patients to record and self-monitor blood glucose, blood pressure, carbohydrate intake, physical activity, and gestational weight gain. The app uses innovative features to minimize the self-monitoring burden, as well as automatic feedback and data visualization. The app also includes a social network "follow" feature to add friends and family and give them permission to view logged data and a progress summary. Health care providers can use the web-based admin portal of the GDM-DH app to enter/review glucose levels and other clinical measures, track patient progress, and guide treatment and counseling accordingly.

CONCLUSIONS

To the best of our knowledge, this is the first mobile health platform for GDM developed for a low-income country and the first one containing a social support feature. A pilot clinical trial is currently underway to explore the clinical utility of the GDM-DH app.

The Effectiveness of a Traditional Chinese Medicine-Based Mobile Health App for Individuals With Prediabetes: Randomized Controlled Trial

BACKGROUND

Traditional Chinese medicine (TCM) theories assert that body constitution and meridian energy lay the foundation for disease prevention. TCM-based health concepts have not yet been incorporated into mobile health (mHealth) apps for individuals with prediabetes.

OBJECTIVE

The aim of this study was to examine the effectiveness of a TCM mHealth app for individuals with prediabetes.

METHODS

This randomized controlled trial recruited 121 individuals with prediabetes at a teaching hospital in New Taipei City between February 2020 and May 2021. The participants were randomly assigned to the TCM mHealth app group (n=42), ordinary mHealth app group (n=41), or control group (n=38). All participants received the usual care that included 15-20 minutes of health education about the disease, along with healthy diet and exercise encouragement. The ordinary mHealth app included physical activity (PA), diet, and disease education, along with individual records. The TCM mHealth app additionally included qi and body constitution information, along with constitution-based PA and diet advice. The control group received the usual care alone and did not have access to any app. Data were collected at baseline, at the end of the 12-week intervention, and 1 month after the intervention. Body constitution, including yang-deficiency, yin-deficiency, and phlegm-stasis, was measured according to the Body Constitution Questionnaire, with higher scores indicating a greater deficiency. Body energy was examined using the Meridian Energy Analysis Device. The Short-Form 36 questionnaire was used to evaluate health-related quality of life (HRQOL), which yielded physical component scores and mental component scores, with higher scores indicating better physical and mental aspects of HRQOL, respectively.

RESULTS

Compared to the control group, the TCM mHealth app group showed greater improvement in hemoglobin A1c (HbA1c), yang-deficiency and phlegm-stasis body constitution, and BMI; however, no significant differences were found in these outcomes between the TCM mHealth app and ordinary mHealth app groups. The TCM mHealth app group showed better improvement in body energy and mental component scores than the ordinary mHealth app group. There were no significant differences in fasting plasma glucose, yin-deficiency body constitution, Dietary Approaches to Stop Hypertension dietary behavior, and total PA among the three groups after the intervention.

CONCLUSIONS

Use of either the ordinary or TCM mHealth app improved HRQOL among individuals with prediabetes. Compared to the outcomes of controls not using any app, use of the TCM mHealth app was effective at improving HbA1c, BMI, yang-deficiency and phlegm-stasis body constitution, and HRQOL. Moreover, using the TCM mHealth app seemed to improve the body energy and HRQOL more than when using the ordinary mHealth app. Further studies with a larger sample size and longer follow-up period may be necessary to determine whether the differences favoring the TCM app are clinically meaningful.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04096989; https://clinicaltrials.gov/ct2/show/NCT04096989.

Combining Behavioral Economics-Based Incentives With the Anchoring Strategy: Protocol for a Randomized Controlled Trial

BACKGROUND

Chronic (ie, long-term) elevated stress is associated with a number of mental and physical health conditions. Mindfulness meditation mobile apps are a promising tool for stress self-management that can overcome several barriers associated with in-person interventions; however, to date, poor app-based intervention adherence has limited the efficacy of these mobile health tools. Anchoring, or pairing, a new behavior with an existing routine has been shown to effectively establish habits that are maintained over time, but this strategy typically only works for those with high initial motivation and has yet to be tested for maintaining meditation with a mobile app.

OBJECTIVE

This study will test novel combinations of behavioral economics-based incentives with the anchoring strategy for establishing and maintaining adherence to an effective dose of meditation with a mobile app.

METHODS

This 16-week study will use a 5-arm, parallel, partially blinded (participants only), randomized controlled design. We will implement a fractional factorial study design that varies the use of self-monitoring messages and financial incentives to support participants' use of their personalized anchoring strategy for maintaining adherence to a ≥10 minute-per-day meditation prescription during an 8-week intervention period, followed by an 8-week postintervention observation period. Specifically, we will vary the use of self-monitoring messages of either the target behavior (ie, meditation tracking) or the outcome associated with the target behavior (ie, mood symptom tracking). We will also vary the use of financial incentives conditional on either meditation at any time of day or meditation performed at approximately the same time of day as participants' personalized anchors.

RESULTS

Continuous meditation app use data will be used to measure weekly meditation adherence over the 16-week study period as a binary variable equal to 1 if participants complete ≥10 minutes of meditation for ≥4 days per week and 0 otherwise. We will measure weekly anchoring plan adherence as a binary variable equal to 1 if participants complete ≥10 minutes of meditation within +1 or -1 hour of the timing of their chosen anchor on ≥4 days per week and 0 otherwise. In addition to these primary measures of meditation and anchoring plan adherence, we will also assess the secondary measures of stress, anxiety, posttraumatic stress disorder, sleep disturbance, and meditation app habit strength at baseline, week 8, and week 16.

CONCLUSIONS

This study will fill an important gap in the mobile health literature by testing novel intervention approaches for establishing and maintaining adherence to app-based mindfulness meditation. If successful, this study will identify an accessible and scalable stress self-management intervention that can help combat stress in the United States.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05217602; https://clinicaltrials.gov/ct2/show/NCT05217602.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/39930.

Predictors for response to electronic patient-reported outcomes in routine care in patients with rheumatoid arthritis: a retrospective cohort study

Routine collection of electronic patient-reported outcomes (ePROs) can improve clinical care. However, a low response rate may counteract the benefits. To optimize adoption, the aim of this study was to investigate which patient factors and/or timing of the invitation predicted response to ePROs sent prior to consultations in patients with rheumatoid arthritis. We performed a retrospective database study with clinical data collected as part of usual care from the electronic medical records at Reade Amsterdam. The dataset comprised the email invitations to complete the ePRO sent prior to consultation. Multiple patient factors and factors defining the timing of the invitation were investigated if they predicted response to the ePRO through a multivariable logistic generalized estimating equation analysis. In total, 17.070 ePRO invitations were sent to 3194 patients (mean age 60 (SD 14), 74% female), of which 40% was completed. Patients between 55 and 73 years (OR 1.39, 95%CI 1.09-1.77) and with higher social economic status (SES) (OR 1.51, 95%CI 1.22-1.88) had significantly higher odds for completing the ePRO, while patients living in an urban area had lower odds (OR 0.69, 95% CI 0.62-0.76). In year 4 after implementation, the OR was increased to 3.69 (95% CI 2.91-4.90). The implementation of ePROs in daily clinical practice needs improvement since 40% of the ePROs sent prior to consultations were completed. Patients that had higher odds to report the next ePRO were between the age of 55-73, had a higher socio-economic status, and were residents in a rural area. The adoption of reporting the PRO increased over time, but the timing of the prompt did not predict response. Additional research is needed to understand ePRO completion, especially for patients with lower socio-economic status.

Weight loss in a digital app-based diabetes prevention program powered by artificial intelligence

Objective

The National Diabetes Prevention Program (DPP) reduces diabetes incidence and associated medical costs but is typically staffing-intensive, limiting scalability. We evaluated an alternative delivery method with 3933 members of a program powered by conversational Artificial Intelligence (AI) called Lark DPP that has full recognition from the Centers for Disease Control and Prevention (CDC).

Methods

We compared weight loss maintenance at 12 months between two groups: 1) CDC qualifiers who completed ≥4 educational lessons over 9 months (n  =  191) and 2) non-qualifiers who did not complete the required CDC lessons but provided weigh-ins at 12 months (n  =  223). For a secondary aim, we removed the requirement for a 12-month weight and used logistic regression to investigate predictors of weight nadir in 3148 members.

Results

CDC qualifiers maintained greater weight loss at 12 months than non-qualifiers (M  =  5.3%, SE  =  .8 vs. M  =  3.3%, SE  =  .8; p  =  .015), with 40% achieving ≥5%. The weight nadir of 3148 members was 4.2% (SE  =  .1), with 35% achieving ≥5%. Male sex (β = .11; P  =  .009), weeks with ≥2 weigh-ins (β = .68; P < .0001), and days with an AI-powered coaching exchange (β = .43; P < .0001) were associated with a greater likelihood of achieving ≥5% weight loss.

Conclusions

An AI-powered DPP facilitated weight loss and maintenance commensurate with outcomes of other digital and in-person programs not powered by AI. Beyond CDC lesson completion, engaging with AI coaching and frequent weighing increased the likelihood of achieving ≥5% weight loss. An AI-powered program is an effective method to deliver the DPP in a scalable, resource-efficient manner to keep pace with the prediabetes epidemic.

The Effect of Periodic Email Prompts on Participant Engagement with a Behavior Change mHealth App: Longitudinal Study (Preprint)

BACKGROUND

Following the need for the prevention of noncommunicable diseases, mobile health (mHealth) apps are increasingly used for promoting lifestyle behavior changes. Although mHealth apps have the potential to reach all population segments, providing accessible and personalized services, their effectiveness is often limited by low participant engagement and high attrition rates.

OBJECTIVE

This study concerns a large-scale, open-access mHealth app, based in the Netherlands, focused on improving the lifestyle behaviors of its participants. The study examines whether periodic email prompts increased participant engagement with the mHealth app and how this effect evolved over time. Points gained from the activities in the app were used as an objective measure of participant engagement with the program. The activities considered were physical workouts tracked through the mHealth app and interactions with the web-based coach.

METHODS

The data analyzed covered 22,797 unique participants over a period of 78 weeks. A hidden Markov model (HMM) was used for disentangling the overtime effects of periodic email prompts on participant engagement with the mHealth app. The HMM accounted for transitions between latent activity states, which generated the observed measure of points received in a week.

RESULTS

The HMM indicated that, on average, 70% (15,958/22,797) of the participants were in the inactivity state, gaining 0 points in total per week; 18% (4103/22,797) of the participants were in the average activity state, gaining 27 points per week; and 12% (2736/22,797) of the participants were in the high activity state, gaining 182 points per week. Receiving and opening a generic email was associated with a 3 percentage point increase in the likelihood of becoming active in that week, compared with the weeks when no email was received. Examining detailed email categories revealed that the participants were more likely to increase their activity level following emails that were in line with the program's goal, such as emails regarding health campaigns, while being resistant to emails that deviated from the program's goal, such as emails regarding special deals.

CONCLUSIONS

Participant engagement with a behavior change mHealth app can be positively influenced by email prompts, albeit to a limited extent. Given the relatively low costs associated with emails and the high population reach that mHealth apps can achieve, such instruments can be a cost-effective means of increasing participant engagement in the stride toward improving program effectiveness.

Mobile Health Interventions and RCTs: Structured Taxonomy and Research Framework

Mobile Health Interventions (MHIs) have addressed a range of healthcare challenges and have been evaluated using Randomized Controlled Trials (RCTs) to establish clinical effectiveness. Using PRISMA we conducted a systematic literature review of RCTs for MHIs and identified 70 studies which were analyzed and classified using Nickerson-Varshney-Muntermann (NVM) taxonomy. From the resultant iterations of the taxonomy, we extracted insights from the categorized studies. RCTs cover a wide range of health conditions including chronic diseases, general wellness, unhealthy practices, family planning, end-of-life, and post-transplant care. The MHIs that were utilized by the RCTs were varied as well, although most studies did not find significant differences between MHIs and usual care. The challenges for MHI-based RCTs include the use of technologies, delayed outcomes, patient recruitment, patient retention, and complex regulatory requirements. These variances can lead to a higher rate of Type I/Type II errors. Further considerations are the impact of infrastructure, contextual and cultural factors, and reductions in the technological relevancy of the intervention itself. Finally, due to the delayed effect of most outcomes, RCTs of insufficient duration are unable to measure significant, lasting improvements. Using the insights from seventy identified studies, we developed a classification of existing RCTs along with guidelines for MHI-based RCTs and a research framework for future RCTs. The framework offers opportunities for (a) personalization of MHIs, (b) use of richer technologies, and (c) emerging areas for RCTs.

Developing mHealth Interventions with Implementation in Mind: Application of the Multiphase Optimization Strategy (MOST) Preparation Phase to Diabetes Prevention Programming (Preprint)

With thousands of mobile health (mHealth) solutions on the market, patients and health care providers struggle to identify which solution to use and prescribe. The lack of evidence-based mHealth solutions may be because of limited research on intervention development and the continued use of traditional research methods for mHealth evaluation. The Multiphase Optimization Strategy (MOST) is a framework that aids in developing interventions that produce the best-expected outcomes (ie, effectiveness), given constraints imposed on affordability, scalability, and efficiency (also known as achieving intervention EASE). The preparation phase of the MOST highlights the importance of formative intervention development—a stage often overlooked and rarely published. The aim of the preparation phase of the MOST is to identify candidate intervention components, create a conceptual model, and define the optimization objective. Although the MOST sets these 3 targets, no guidance is provided on how to conduct quality research within the preparation phase and what specific steps can be taken to identify potential intervention components, develop the conceptual model, and achieve intervention EASE with the implementation context in mind. To advance the applicability of the MOST within the field of implementation science, this study provides an account of the methods used to develop an mHealth intervention using the MOST. Specifically, we provide an example of how to achieve the goals of the preparation phase by outlining the formative development of an mHealth-prompting intervention within a diabetes prevention program. In addition, recommendations are proposed for future researchers to consider when conducting formative research on mHealth interventions with implementation in mind. Given its considerable reach, mHealth has the potential to positively affect public health by decreasing implementation costs and improving accessibility. The MOST is well-suited for the efficient development and optimization of mHealth interventions. By using an implementation-focused lens and outlining the steps in developing an mHealth intervention using the preparation phase of the MOST, this study may guide future intervention developers toward maximizing the impact of mHealth outside academia.

mHealth prompts within diabetes prevention programs: a scoping review

BACKGROUND

Mobile health (mHealth) prompts (e.g., text messaging, push notifications) are a commonly used technique within behaviour change interventions to prompt or cue a specific behaviour. Such prompts are being increasingly integrated into diabetes prevention programs (DPPs). While mHealth prompts provide a convenient and cost-effective way to reinforce behaviour change, no reviews to date have examined mHealth prompt use within DPPs. This scoping review aims to: (I) understand how mHealth prompts are being used within behaviour change interventions for individuals at risk for developing type 2 diabetes (T2D); and (II) provide recommendations for future mHealth prompt research, design, and application.

METHODS

The scoping review methodology outlined by Arksey and O'Malley were followed. Medline, CINAHL, PsycInfo, Web of Science, and SportDiscus were searched. The search strategy combined keywords relating to T2D risk and mHealth prompts in conjunction with database-controlled vocabulary when available (e.g., MeSH for Medline).

RESULTS

Of the 4,325 publications screened, 44 publications (based on 33 studies) met the inclusion criteria and were included for data extraction. Text messaging was the most widely used mHealth prompt (73%) followed by push notifications (21%). Only 30% of studies discussed the theoretical basis for prompt content and time of day messages were sent, and only 27% provided justification for prompt timing and frequency. Fourteen studies assessed participant satisfaction with mHealth prompts of which only two reported dissatisfaction due to either prompting frequency (hourly) or message content (solely focused on weight). Nine studies assessed behavioural outcomes including weight loss, physical activity, and diabetes incidence, and found mixed effects overall.

CONCLUSIONS

While mHealth prompts were well-received by participants, there are mixed effects on the influence of mHealth prompts on behavioural outcomes and diabetes incidence. More thorough reporting of prompt content development and delivery is needed, and more experimental research is needed to identify optimal content, delivery characteristics, and impact on behavioural and clinical outcomes.

Mobile Health Biometrics to Enhance Exercise and Physical Activity Adherence in Type 2 Diabetes (MOTIVATE-T2D): protocol for a feasibility randomised controlled trial

INTRODUCTION

Exercise and physical activity (PA) are fundamental to the treatment of type 2 diabetes. Current exercise and PA strategies for newly diagnosed individuals with type 2 diabetes are either clinically effective but unsuitable in routine practice (supervised exercise) or suitable in routine practice but clinically ineffective (PA advice). Mobile health (mHealth) technologies, offering biometric data to patients and healthcare professionals, may bridge the gap between supervised exercise and PA advice, enabling patients to engage in regular long-term physically active lifestyles. This feasibility randomised controlled trial (RCT) will evaluate the use of mHealth technology when incorporated into a structured home-based exercise and PA intervention, in those recently diagnosed with type 2 diabetes.

METHODS AND ANALYSIS

This feasibility multicentre, parallel group RCT will recruit 120 individuals with type 2 diabetes (diagnosis within 5-24 months, aged 40-75 years) in the UK (n=60) and Canada (n=60). Participants will undertake a 6-month structured exercise and PA intervention and be supported by an exercise specialist (active control). The intervention group will receive additional support from a smartwatch and phone app, providing real-time feedback and enabling improved communication between the exercise specialist and participant. Primary outcomes are recruitment rate, adherence to exercise and loss to follow-up. Secondary outcomes include a qualitative process evaluation and piloting of potential clinical outcome measures for a future RCT.

ETHICS AND DISSEMINATION

The trial was approved in the UK by the South East Scotland Research Ethics Committee 01 (20/SS/0101) and in Canada by the Clinical Research Ethics Board of the University of British Columbia (H20-01936), and is being conducted in accordance with the Declaration of Helsinki and Good Clinical Practice. Results will be published in peer-reviewed journals and presented at national and international scientific meetings.

TRIAL REGISTRATION NUMBERS

ISRCTN14335124; ClinicalTrials.gov: NCT04653532.

Perceptions of physical activity and technology enabled exercise interventions among people with advanced chronic kidney disease: a qualitative study

BACKGROUND

Exercise improves health outcomes and quality of life in persons with chronic kidney disease (CKD). The numbers of persons with advanced CKD meeting physical activity guidelines however is low. We undertook a qualitative study of men and women aged 36-74 from various race/ethnic populations with advanced CKD not requiring dialysis to describe their experiences and opinions around prior physical activity, motivating factors for and barriers to exercise, and perceptions of exercise-promoting technology and group-based programming designed to improve physical activity levels.

METHODS

Nineteen persons with advanced CKD not requiring dialysis were interviewed at two high volume nephrology clinics enriched with racial/ethnic minority patients (Emory University and Santa Clara Valley Medical Center). We used thematic analysis to identify dominant themes (n = 4) and subthemes (n = 19) around exercise experience, barriers, motivators, views, and preferences.

RESULTS

Four dominant themes and 19 subthemes were identified. The most common motivators to exercise included physical and mental health benefits, appearance, improvement in energy levels, and potential social interaction in group-based programs. Common barriers included health concerns, particularly complications related to other co-morbidities, as well as time and transportation constraints. Participants were skeptical of exercise programs solely reliant on technology.

CONCLUSIONS

The use of group-based exercise programs may motivate persons with CKD to increase exercise levels, while programs entirely based on technology may be less effective.

The Association of Mobile Health Applications with Self-Management Behaviors among Adults with Chronic Conditions in the United States

Background: Mobile applications related to health and wellness (mHealth apps) are widely used to self-manage chronic conditions. However, research on whether mHealth apps facilitate self-management behaviors of individuals with chronic conditions is sparse. We aimed to evaluate the association of mHealth apps with different types of self-management behaviors among patients with chronic diseases in the United States. Methods: This is a cross-sectional observational study. We used data from adult participants (unweighted n = 2340) of the Health Information National Trends Survey in 2018 and 2019. We identified three self-management behaviors: (1) resource utilization using electronic personal health records; (2) treatment discussions with healthcare providers; and (3) making healthcare decisions. We analyzed the association of mHealth apps to self-management behaviors with multivariable logistic and ordinal regressions. Results: Overall, 59.8% of adults (unweighted number = 1327) used mHealth apps. Adults using mHealth apps were more likely to use personal health records (AOR = 3.11, 95% CI 2.26–4.28), contact healthcare providers using technology (AOR = 2.70, 95% CI 1.93–3.78), and make decisions on chronic disease management (AOR = 2.59, 95% CI 1.93–3.49). The mHealth apps were associated with higher levels of self-management involvement (AOR = 3.53, 95% CI 2.63–4.72). Conclusion: Among individuals with chronic conditions, having mHealth apps was associated with positive self-management behaviors.

Evaluation and Refinement of a Bank of SMS Text Messages to Promote Behavior Change Adherence Following a Diabetes Prevention Program: Survey Study

Background

SMS text messaging is a low-cost and far-reaching modality that can be used to augment existing diabetes prevention programs and improve long-term diet and exercise behavior change adherence. To date, little research has been published regarding the process of SMS text message content development. Understanding how interventions are developed is necessary to evaluate their evidence base and to guide the implementation of effective and scalable mobile health interventions in public health initiatives and in future research.

Objective

This study aims to describe the development and refinement of a bank of SMS text messages targeting diet and exercise behavior change to be implemented following a diabetes prevention program.

Methods

A bank of 124 theory-based SMS text messages was developed using the Behaviour Change Wheel and linked to active intervention components (behavior change techniques [BCTs]). The Behaviour Change Wheel is a theory-based framework that provides structure to intervention development and can guide the use of evidence-based practices in behavior change interventions. Once the messages were written, 18 individuals who either participated in a diabetes prevention program or were a diabetes prevention coach evaluated the messages on their clarity, utility, and relevance via survey using a 5-point Likert scale. Messages were refined according to participant feedback and recoded to obtain an accurate representation of BCTs in the final bank.

Results

76/124 (61.3%) messages were edited, 4/124 (3.2%) were added, and 8/124 (6.5%) were removed based on participant scores and feedback. Of the edited messages, 43/76 (57%) received minor word choice and grammar alterations while retaining their original BCT code; the remaining 43% (33/76, plus the 4 newly written messages) were recoded by a reviewer trained in BCT identification.

Conclusions

This study outlines the process used to develop and refine a bank of SMS text messages to be implemented following a diabetes prevention program. This resulted in a bank of 120 theory-based, user-informed SMS text messages that were overall deemed clear, useful, and relevant by both individuals who will be receiving and delivering them. This formative development process can be used as a blueprint in future SMS text messaging development to ensure that message content is representative of the evidence base and is also grounded in theory and evaluated by key knowledge users.

Assessing a national policy on strengthening chronic care in primary care settings of a middle-income country using patients' perspectives

Background

To improve care for patients with chronic diseases, a recent policy initiative in Thailand focused on strengthening primary care based on the concept of Chronic Care Model (CCM). This study aimed to assess the perception of patients about the health care services after the implementation.

Methods

We conducted a cross-sectional survey of 4071 patients with hypertension and/or diabetes registered with 27 primary care units and 11 hospital non-communicable diseases (NCDs) clinics in 11 provinces.

The patients were interviewed using a validated questionnaire of the Patient Assessment of Chronic Illness Care. Upgraded primary care units (PCUs) were ordinary PCUs with the multi-professional team including a physician. Trained upgraded PCUs were upgraded PCUs with the training input. Structural equation modeling was used to create subscale scores for CCM and 5 A model characteristics. Mixed effect logistic models were employed to examine the association of subscales (high vs low score) of patient perception of the care quality with type of PCUs.

Results

Compared to hospital NCD clinics, ordinary PCUs were the best in the odds of receiving high score for every CCM subscale (ORs: 1.46–1.85; p < 0.05), whereas the trained upgraded PCUs were better in terms of follow-up (ORs:1.37; p < 0.05), and the upgraded PCU did not differ in all domains. According to the 5 A model subscales, patient assessment also revealed better performance of ordinary PCUs in all domains compared to hospital NCD clinics whereas upgraded PCUs and trained upgraded PCUs did so in some domains. Seeing the same doctor on repeated visits (ORs: 1.82–2.17; p < 0.05) or having phone contacts with the providers (ORs:1.53–1.99; p < 0.05) were found beneficial using CCM subscales and the 5A model subscales. However, patient assessment by both subscales did not demonstrate a statistically significant association across health insurance status.

Conclusions

The policy implementation might not satisfy the patients’ perception on quality of chronic care according to the CCM and the 5A model subscale. However, the arrangement of chronic care with patients seeing the same doctors or patients having telephone contact with healthcare providers may satisfy the patients’ perceived needs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06220-x.

Engagement with a Web-Based Health Promotion Intervention among Vocational School Students: A Secondary User and Usage Analysis

Engagement with web-based interventions is both generally low and typically declining. Visits and revisits remain a challenge. Based on log data of a web-based cluster randomized controlled trial conducted in vocational schools, the present secondary analysis aimed to identify influencing factors on initially logging in to a health promotion platform among young adults and to examine the engagement over the course of an eight-week intervention. Data of 336 students (62.2% female, age span 18–25) from two intervention arms (web-based intervention and web-based intervention with an additional initial face-to-face contact) was included. Binary logistic regression and log-data visualization were performed. An additional initial face-to-face contact (odds ratio (OR) = 2.971, p = 0.005), female sex (OR = 2.237, p = 0.046) and the health-related skill “dealing with health information” (OR = 2.179, p = 0.030) significantly increased the likelihood of initially logging in. Other variables showed no influence. 16.6% of all potential users logged in at least once, of which 57.4% revisited the platform. Most logins were tracked at the beginning of the intervention and repeated engagement was low. To increase the engagement with web-based interventions, health-related skills should be fostered. In addition, a strategy could be to interlink comparable interventions in vocational schools more regularly with everyday teaching through multi-component interventions.

Cardiorespiratory fitness and accelerometer-determined physical activity following one year of free-living high-intensity interval training and moderate-intensity continuous training: a randomized trial

Background

Free-living adherence to high-intensity interval training (HIIT) has not been adequately tested. This randomized trial examined changes in cardiorespiratory fitness (CRF) and accelerometer-measured purposeful physical activity over 12 months of free-living HIIT versus moderate-intensity continuous training (MICT).

Methods

Ninety-nine previously low-active participants with overweight/obesity were randomly assigned to HIIT (n = 47) or MICT (n = 52). Both interventions were combined with evidence-based behaviour change counselling consisting of 7 sessions over 2 weeks. Individuals in HIIT were prescribed 10 X 1-min interval-based exercise 3 times per week (totalling 75 min) whereas individuals in MICT were prescribed 150 min of steady-state exercise per week (50 mins 3 times per week). Using a maximal cycling test to exhaustion with expired gas analyses, CRF was assessed at baseline and after 6 and 12 months of free-living exercise. Moderate-to-vigorous physical activity of 10+ minutes (MVPA10+) was assessed by 7-day accelerometry at baseline, 3, 6, 9, and 12 months. Intention to treat analyses were conducted using linear mixed models.

Results

CRF was improved over the 12 months relative to baseline in both HIIT (+ 0.15 l/min, 95% CI 0.08 to 0.23) and MICT (+ 0.11 l/min, 95% CI 0.05 to 0.18). Both groups improved 12-month MVPA10+ above baseline (HIIT: + 36 min/week, 95% CI 17 to 54; MICT: + 69 min/week, 95% CI 49 to 89) with the increase being greater (by 33 min, 95% CI 6 to 60) in MICT (between group difference, P = 0.018).

Conclusion

Despite being prescribed twice as many minutes of exercise and accumulating significantly more purposeful exercise, CRF improvements were similar across 12 months of free-living HIIT and MICT in previously low-active individuals with overweight/obesity.