A lifestyle intervention supported by mobile health technologies to improve the cardiometabolic risk profile of individuals at risk for cardiovascular disease and type 2 diabetes: study rationale and protocol

Cardiovascular Disease Risk in Rural Adults

BACKGROUND

Cardiovascular disease (CVD) risk reduction programs led by a nurse/community health worker team are effective in urban settings. This strategy has not been adequately tested in rural settings.

OBJECTIVE

A pilot study was conducted to examine the feasibility of implementing an evidence-based CVD risk reduction intervention adapted to a rural setting and evaluate the potential impact on CVD risk factors and health behaviors.

METHODS

A 2-group, experimental, repeated-measures design was used; participants were randomized to a standard primary care group (n = 30) or an intervention group (n = 30) where a registered nurse/community health worker team delivered self-management strategies in person, by phone, or by videoconferencing. Outcomes were measured at baseline and at 3 and 6 months. A sample of 60 participants was recruited and retained in the study.

RESULTS

In-person (46.3%) and telephone (42.3%) meetings were used more than the videoconferencing application (9%). Mean change at 3 months differed significantly between the intervention and control groups for CVD risk (-1.0 [95% confidence interval (CI), -3.1 to 1.1] vs +1.4 [95% CI, -0.4 to 3.3], respectively), total cholesterol (-13.2 [95% CI, -32.1 to 5.7.] vs +21.0 [95% CI, 4.1-38.1], respectively), and low-density lipoprotein (-11.5 [95% CI, -30.8 to 7.7] vs +19.6 [95% CI, 1.9-37.2], respectively). No between-group differences were seen in high-density lipoprotein, blood pressure, or triglycerides.

CONCLUSIONS

Participants receiving the nurse/community health worker-delivered intervention improved their risk CVD profiles, total cholesterol, and low-density lipoprotein levels at 3 months. A larger study to explore the intervention impact on CVD risk factor disparities experienced by rural populations is warranted.

Effects of Personal Hygiene Habits on Self-Efficacy for Preventing Infection, Infection-Preventing Hygiene Behaviors, and Product-Purchasing Behaviors

Since there is no cure for the COVID-19 pandemic yet, personal hygiene management is important for protecting oneself from the deadly virus. Personal hygiene management comes from personal hygiene habits. Thus, this study investigated the association between personal hygiene habits, consumers’ infection-prevention behaviors, and the effects of social support on the latter. Data were collected using a self-administered questionnaire survey of 620 Korean adults. An online survey agency was used to conduct the questionnaire over eight days, from 18 May to 25 May 2020. Data were analyzed using structural equation modeling. The results were as follows. First, personal hygiene habits positively affected self-efficacy for infection prevention (β = 0.123, p < 0.01). Moreover, personal hygiene habits indirectly affected virus spread-prevention behaviors (β = 0.457, p < 0.000) and product-purchasing behaviors for infection prevention (β = 0.146, p < 0.01) through self-efficacy for infection prevention. Second, informational support for infection prevention increased self-efficacy influence for infection prevention on the virus spread prevention behaviors among the public (composite reliability: −2.627). Thus, continued education of the public is imperative to ensuring compliance with personal hygiene practices. Furthermore, timely dissemination of relevant information on infection-prevention practices through various media during an infection outbreak is critical.

Clinical efficacy and plausibility of a smartphone-based integrated online real-time diabetes care system via glucose and diet data management: a pilot study

BACKGROUND

Smartphones have become novel healthcare tools for patients with diabetes. However, it is uncertain whether the smartphone application support system helps in glycaemic control in patients with type 2 diabetes.

AIMS

To evaluate the efficacy and plausibility of smartphone-based integrated online real-time diabetes care.

METHODS

Forty patients with type 2 diabetes were randomly assigned to the smartphone-based care (SC) (n = 20) and conventional care (CC) (n = 20) groups for 12 weeks. The SC group was instructed to use smartphone application (Noom Coach) and a glucose meter, and was provided medical supervision based on blood glucose level and food intake information sent to the central database server. The efficacy was evaluated by glycated haemoglobin (A1C ≤ 6.5%). The Summary of Diabetes Self-Care Activities (SDSCA) questionnaire was collected at baseline and at week 12.

RESULTS

Seventeen and 18 patients of the SC and CC groups completed the study respectively. In the SC group, more patients achieved target A1C compared with the CC group (47.1% vs 11.1%, P = 0.019). In both group, SDSCA scores excluding the exercise item showed overall improvement (general diet, 1.4 ± 2.0 → 2.6 ± 2.3 vs 0.4 ± 1.1 → 1.8 ± 2.2; specific diet, 4.2 ± 1.7 → 5.4 ± 1.2 vs 3.8 ± 1.6 → 5.1 ± 1.1; blood glucose test, 3.3 ± 2.8 → 4.9 ± 2.3 vs 1.0 ± 2.2 → 4.7 ± 2.3; foot care, 1.5 ± 1.6 → 3.6 ± 2.8 vs 1.4 ± 1.9 → 6.1 ± 1.4; all P < 0.05). There was no difference between both groups other than the aspect of foot care (P = 0.008).

CONCLUSIONS

The smartphone-based integrated online real-time diabetes care system through glucose and diet data management showed clinical plausibility in glucose control in real clinical practice.

The effect of active occupational stress management on psychosocial and physiological wellbeing: a pilot study

Background

The aim of the study was to address the working population with an occupational stress prevention program using mHealth solution and encourage them for healthy lifestyle choices.

Methods

Seventeen participants were randomized from the corporate setting. A 24alife app with a good compliance program was selected. Test battery has been designed to test the physical readiness, psychological evaluation and biological blood markers for stress. Participants were followed up after 30, 60 and 90 days, respectively, within the intervention period. Weight of participants was tracked three times per month. Univariate analysis compared the continuous variables by One-Way Repeated-Measures ANOVA test when the data were normally distributed, or Wilcoxon rank sum test for abnormal distribution of variables.

Results

Participants used the app with a compliance rate of 94.1%. The psychological evaluation revealed higher motivation for work, lower burnout scores and participants gave subjective responses of better general wellbeing. Some of the participants lost up to four kg of body mass. Physical readiness has also improved.

Conclusions

Results of mHealth projects on corporate could include primary health care institutions and health ministry to extend the existing system to patients’ pockets where they can monitor their disease and increase the ability of self-care.

The HealtheSteps™ lifestyle prescription program to improve physical activity and modifiable risk factors for chronic disease: a pragmatic randomized controlled trial

BACKGROUND

Our objective was to determine the influence of the HealtheSteps™ lifestyle prescription program on physical activity and modifiable risk factors for chronic disease in individuals at risk.

METHODS

One hundred eighteen participants were recruited from 5 sites in Southwestern Ontario, Canada and randomized to either the intervention (HealtheSteps™ program, n = 59) or a wait-list control group (n = 59). The study comprised three phases: an Active Phase (0 to 6 months) consisted of bi-monthly in-person lifestyle coaching with access to a suite of eHealth technology supports (Heathesteps app, telephone coaching and a private HealtheSteps™ social network) followed by a Minimally-Supported Phase I (6 to 12 months), in which in-person coaching was removed, but participants still had access to the full suite of eHealth technology supports. In the final stage, Minimally-Supported Phase II (12 to 18 months), access to the eHealth technology supports was restricted to the HealtheSteps™ app. Assessments were conducted at baseline, 6, 12 and 18 months. The study primary outcome was the 6-month change in average number of steps per day. Secondary outcomes included: self-reported physical activity and sedentary time; self-reported eating habits; weight and body composition measures; blood pressure and health-related quality of life. Data from all participants were analyzed using an intent-to-treat approach. We applied mixed effects models for repeated measurements and adjusted for age, sex, and site in the statistical analyses.

RESULTS

Participants in HealtheSteps™ increased step counts (between-group [95% confidence interval]: 3132 [1969 to 4294], p < 0.001), decreased their sitting time (- 0.08 [- 0.16 to - 0.006], p = 0.03), and improved their overall healthful eating (- 1.5 [- 2.42 to - 0.58], p = 0.002) to a greater extent compared to control at 6 months. Furthermore, exploratory results showed that these individuals maintained these outcomes 12 months later, after a minimally-supported phase; and retained improvements in sedentary time and improved healthful eating after 18 months. No differences in self-reported physical activity, health-related quality of life, weight, waist circumference or blood pressure were observed between groups at 6 months.

CONCLUSIONS

Our findings suggest that HealtheSteps™ is effective at increasing physical activity (i.e., step counts per day), decreasing weekday sitting time, and improving healthful eating in adults at increased risk for chronic disease after 6 months; however, we did not see change in other risk factors. Nonetheless, the maintenance of these behaviours with minimal support after 12 and even 18 months indicates the promise of HealtheSteps™ for long-term sustainability.

TRIAL REGISTRATION

The trial was registered on April 6, 2015 with ClinicalTrials.gov (identifier: NCT02413385 ).

Conformity of Diabetes Mobile apps with the Chronic Care Model

Background

Despite the growing use of mobile applications (apps) for chronic disease management, the evidence on the effectiveness of this technology on clinical and behavioural outcomes of the patients is scant. Many studies highlight the importance of the theoretical foundations of mobile-based interventions. One of the most widely accepted models for the management of chronic diseases, such as diabetes, is the Chronic Care Model (CCM). In this study, we investigated the conformity of the selected diabetes mobile apps with CCM.

Method

We searched online journal databases related to diabetes mobile apps to find common features. Then considering the components of the CCM as a reference model, features of some popular and top-ranking apps were compared with CCM.

Results

Among 23 studied apps, 34 per cent of them had medium conformity and 66 per cent of these apps were in weak conformity. The self-management support component is covered by 100 per cent of them. Ninety-five per cent of apps have covered the proactive follow-up component.

Conclusions

App conformance with CCM is generally weak. App developers are recommended to give greater consideration to established theoretical models in their design and implementation.

Process evaluation of the HealtheSteps™ lifestyle prescription program

Physical inactivity, sedentary behavior, and poor diet are contributing to the rise in chronic disease rates throughout the world. HealtheSteps™ is a lifestyle prescription program focused on reducing risk factors for chronic disease through in-person coaching sessions, goal setting and tracking, and technology supports. A process evaluation was conducted alongside a pragmatic randomized controlled trial to: (a) explore the acceptability of HealtheSteps™ program from coach and participant perspectives; and (b) identify where the program can be improved. Participants at risk or diagnosed with a chronic disease were recruited from five primary care/health services organizations into HealtheSteps™. Participants met with a trained coach bi-monthly for 6 months and set goals for physical activity (step counts), exercise (moderate to vigorous activity), and healthy eating. Coaches were interviewed at month 6 and participants at month 12 (6 months postprogram). All coach interviews (n = 12) were analyzed along with a purposeful sample of participant interviews (n = 13). Coaches found that HealtheSteps™ was easy to deliver and recommendations for exercise and healthy eating were helpful. Including discussions on participant readiness to change, along with group sessions, and more in-depth healthy eating resources were suggested by coaches to improve the program. Participants described the multiple avenues of accountability provided in the program as helpful. However, more feedback and interaction during and postprogram from coaches were suggested by participants. HealtheSteps™ is an acceptable program from the perspectives of both coaches and participants with suggested improvements not requiring significant changes to the core program design.

The Effectiveness of a Smartphone Application on Modifying the Intakes of Macro and Micronutrients in Primary Care: A Randomized Controlled Trial. The EVIDENT II Study

Background: This study evaluates the effectiveness of adding a diet smartphone application to standard counseling to modify dietary composition over the long term (12 months). Methods: A randomized, controlled, multicenter clinical trial was conducted involving the participation of 833 subjects from primary care clinics (415 to the intervention (counseling + application) group (IG) and 418 to the control (counseling) group (CG)). Both groups were counseled about a healthy diet and physical activity. For the 3-month intervention period, the IG was also trained to use a diet smartphone application that involved dietary self-monitoring and tailored feedback. Nutritional composition was estimated using a self-reported food frequency questionnaire. Results: An analysis of repeated measures revealed an interaction between the group and the percentages of carbohydrates (p = 0.031), fats (p = 0.015) and saturated fats (p = 0.035) consumed. Both groups decreased their energy intake (Kcal) at 12 months (IG: −114 (95% CI: −191 to −36); CG: −108 (95% CI: −184 to −31)). The IG reported a higher percentage intake of carbohydrates (1.1%; 95% CI: 0.1 to 2.0), and lower percentage intakes of fats (−1.0%; 95% CI: −1.9 to −0.1) and saturated fats (−0.4%; 95%CI: −0.8 to −0.1) when compared to the CG. Conclusions: Better results were achieved in terms of modifying usual diet composition from counseling and the diet smartphone application compared to counseling alone. This was evaluated by a self-reported questionnaire, which indicated an increased percentage intake of carbohydrates, and decreased percentage intakes of fats and saturated fats.

Novel App- and Web-Supported Diabetes Prevention Program to Promote Weight Reduction, Physical Activity, and a Healthier Lifestyle: Observation of the Clinical Application

BACKGROUND

The increasing incidence of type 2 diabetes mellitus presents as a tsunami of health problems and health care costs. Preventing this development needs to target the underlying rise in metabolic syndrome cases through obesity and unhealthy lifestyle. Obesity is frequently perceived as a social issue with implicit psychological strain; health apps/weight-reduction programs are mushrooming from this side. The present program intends to bring weight reduction into the hands of HCPs by utilizing advanced digital technology.

METHODS

The prospective observational study analyzed 166 patients with metabolic syndrome as treated for weight reduction in 23 medical practices in Germany. Two approaches were observed: usual care (UC; n = 57) and a personalized health management program (PHM; n = 109). Key for PHM was the interaction between HCP and patient: reinforcing lifestyle changes through personalized goals and HCP-feedback via app- and web-based communication. Comparing PHM/UC was based on a time-to-success (5% weight reduction) analysis by Cox regression. Further exploratory analyses addressed the comparison of achievers and nonachievers.

RESULTS

Cox regression adjusted for sex, age, and BMI revealed a chance ratio for weight reduction of 6.2 (2.4-16.2, p = .0003) favoring PHM. Expected success rates were 44.8% for PHM, 11.5% for UC. PHM achievers reduced their weight by 8.0% and lowered their BMI by 2.7 points. Motivation for lifestyle changes represented a key for success.

CONCLUSIONS

The approach of enhanced interaction of HCPs and patients via app- and web-based communication was a clear success and delivered favorable responder rates. Treating obesity from a medical viewpoint will help to deepen the motivation for changing lifestyles. The study represents a cornerstone for a wider scoped application of these novel digital health approaches.

Lessons Learned in the Implementation of HealtheSteps: An Evidence-Based Healthy Lifestyle Program

HealtheSteps is a pragmatic, evidence-based lifestyle prescription program aimed at reducing the rates of chronic disease, in particular, type 2 diabetes. A process evaluation was completed to assess the feasibility of the implementation of HealtheSteps in primary care and community-based settings across Canada. Key informant interviews (program providers and participants) were conducted to identify facilitators and barriers to implementation and opportunities for future program adaptation and improvement. Forty-three interviews were conducted across five regions in Canada (15 sites ranging from remote, rural, suburban, and urban). Transcripts were analyzed using a qualitative naturalistic inquiry approach with several facilitating factors identified: pragmatic program design, in-line goals with sites' mandates, and access to ongoing support. Barriers were related to administrative challenges such as booking space, personnel changeovers, and scheduling participants. Findings from this analysis revealed insights on program delivery, design, and importance of site champions. Key lessons learned focused on two areas: infrastructure support and program implementation. The application of these learnings from the HealtheSteps program may inform the development of strategies that can optimize program adaptation and support while reducing real and perceived barriers experienced, thus increasing the success of translation of the evidence-based diabetes program to different points of care.

Toward research-tested mobile health interventions to prevent diabetes and cardiovascular disease among persons with pre-diabetes

Background

About 35% of US adults have pre-diabetes and an increased risk of diabetes. Consumer-facing devices such as the Fitbit help users become more physically active and manage their weight which reduces risk of diabetes and cardiovascular disease.

Methods

In this commentary we provide a summary of healthy lifestyle intervention studies involving persons with pre-diabetes including those conducted in routine clinical practice. We also provide an account of how such interventions might be enhanced through the use of wearable devices linked to smartphone applications.

Results

In initial trials focusing on overweight and obesity, consumer wearable devices have been shown to increase physical activity and reduce weight. However, the acceptability and effectiveness of these mHealth interventions among persons with impaired glucose tolerance or impaired fasting glucose is unknown; studies involving persons with pre-diabetes have not yet been reported.

Conclusions

Research is needed to determine the feasibility and efficacy of wearable devices in improving physical activity and weight management in persons with pre-diabetes who are at-risk of diabetes and cardiovascular disease.

HealtheSteps™ Study Protocol: a pragmatic randomized controlled trial promoting active living and healthy lifestyles in at-risk Canadian adults delivered in primary care and community-based clinics

BACKGROUND

Physical inactivity is one of the leading causes of chronic disease in Canadian adults. With less than 50% of Canadian adults reaching the recommended amount of daily physical activity, there is an urgent need for effective programs targeting this risk factor. HealtheSteps™ is a healthy lifestyle prescription program, developed from an extensive research base to address risk factors for chronic disease such as physical inactivity, sedentary behaviour and poor eating habits. HealtheSteps™ participants are provided with in-person lifestyle coaching and access to eHealth technologies delivered in community-based primary care clinics and health care organizations.

METHOD/DESIGN

To determine the effectiveness of Healthesteps™, we will conduct a 6-month pragmatic randomized controlled trial with integrated process and economic evaluations of HealtheSteps™ in 5 clinic settings in Southwestern Ontario. 110 participants will be individually randomized (1:1; stratified by site) to either the intervention (HealtheSteps™ program) or comparator (Wait-list control). There are 3 phases of the HealtheSteps™ program, lasting 6 months each. The active phase consists of bi-monthly in-person coaching with access to a full suite of eHealth technology supports. During the maintenance phase I, the in-person coaching will be removed, but participants will still have access to the full suite of eHealth technology supports. In the final stage, maintenance phase II, access to the full suite of eHealth technology supports is removed and participants only have access to publicly available resources and tools.

DISCUSSION

This trial aims to determine the effectiveness of the program in increasing physical activity levels and improving other health behaviours and indicators, the acceptability of the HealtheSteps™ program, and the direct cost for each person participating in the program as well as the costs associated with delivering the program at the different community sites. These results will inform future optimization and scaling up of the program into additional community-based primary care sites.

TRIAL REGISTRATION

NCT02413385 (Clinicaltrials.gov). Date Registered: April 6, 2015.

Hockey Fans in Training (Hockey FIT) pilot study protocol: a gender-sensitized weight loss and healthy lifestyle program for overweight and obese male hockey fans

Background

Effective approaches that engage men in weight loss and lifestyle change are important because of worldwide increases, including in Canada, in obesity and chronic diseases. Football Fans in Training (FFIT), developed in Scotland, successfully tackled these problems by engaging overweight/obese male football fans in sustained weight loss and positive health behaviours, through program deliveries at professional football stadia.

Methods

Aims: 1) Adapt FFIT to hockey within the Canadian context and integrate with HealtheSteps™ (evidence-based lifestyle program) to develop Hockey Fans in Training (Hockey FIT); 2) Explore potential for Hockey FIT to help overweight/obese men lose weight and improve other outcomes by 12 weeks, and retain these improvements to 12 months; 3) Evaluate feasibility of recruiting and retaining overweight/obese men; 4) Evaluate acceptability of Hockey FIT; and 5) Conduct program optimization via a process evaluation. We conducted a two-arm pilot pragmatic randomized controlled trial (pRCT) whereby 80 overweight/obese male hockey fans (35–65 years; body-mass index ≥28 kg/m²) were recruited through their connection to two junior A hockey teams (London and Sarnia, ON) and randomized to Intervention (Hockey FIT) or Comparator (Wait-List Control). Hockey FIT includes a 12-week Active Phase (classroom instruction and exercise sessions delivered weekly by trained coaches) and a 40-week Maintenance Phase. Data collected at baseline and 12 weeks (both groups), and 12 months (Intervention only), will inform evaluation of the potential of Hockey FIT to help men lose weight and improve other health outcomes. Feasibility and acceptability will be assessed using data from self-reports at screening and baseline, program fidelity (program observations and coach reflections), participant focus group discussions, coach interviews, as well as program questionnaires and interviews with participants. This information will be analyzed to inform program optimization.

Discussion

Hockey FIT is a gender-sensitive program designed to engage overweight/obese male hockey fans to improve physical activity and healthy eating choices, thereby leading to weight loss and other positive changes in health outcomes. We expect this study to provide evidence for a full-scale confirmatory pRCT.

Trial registration

NCT02396524 (Clinicaltrials.gov). Date of registration: Feb 26, 2015.

The Assessment of the Readiness of Molecular Biomarker-Based Mobile Health Technologies for Healthcare Applications

Mobile health technologies to detect physiological and simple-analyte biomarkers have been explored for the improvement and cost-reduction of healthcare services, some of which have been endorsed by the US FDA. Advancements in the investigations of non-invasive and minimally-invasive molecular biomarkers and biomarker candidates and the development of portable biomarker detection technologies have fuelled great interests in these new technologies for mhealth applications. But apart from the development of more portable biomarker detection technologies, key questions need to be answered and resolved regarding to the relevance, coverage, and performance of these technologies and the big data management issues arising from their wide spread applications. In this work, we analyzed the newly emerging portable biomarker detection technologies, the 664 non-invasive molecular biomarkers and the 592 potential minimally-invasive blood molecular biomarkers, focusing on their detection capability, affordability, relevance, and coverage. Our analysis suggests that a substantial percentage of these biomarkers together with the new technologies can be potentially used for a variety of disease conditions in mhealth applications. We further propose a new strategy for reducing the workload in the processing and analysis of the big data arising from widespread use of mhealth products, and discuss potential issues of implementing this strategy.

Does Systolic Blood Pressure Response to Lifestyle Intervention Indicate Metabolic Risk and Health-Related Quality-of-Life Improvement Over 1 Year?

The purpose of this study was to determine whether responders (minimum 4-mm Hg reduction of systolic blood pressure [BP]) at 24 weeks) to a 52-week lifestyle intervention had greater changes in metabolic risk factors and health-related quality of life than nonresponders. Participants (N=126; age, 57.4 [9.1] years) had waist circumference (WC), resting BP, glycated hemoglobin, lipids, and fitness assessed at baseline and at 12, 24, and 52 months. The 36-item short-form survey was administered to assess HRQOL. At baseline, responders had higher mental health scores (P=.04) and systolic and diastolic BPs (P<.001) than nonresponders. Across 52 weeks, responders also had greater improvements in diastolic BP (P<.001), WC (P=.01), and maximal oxygen uptake (P=.04) compared with nonresponders. Participants with clinically important changes in systolic BP at 24 weeks had greater metabolic improvements across 52 weeks, compared with those without clinically important systolic BP changes.

Mobile health, exercise and metabolic risk: a randomized controlled trial

Background

It was hypothesized that a mobile health (mHealth) intervention would elicit greater improvements in systolic blood pressure and other cardiometabolic risk factors at 12 weeks, which would be better maintained over 52 weeks, compared to the active control intervention.

Methods

Eligible participants (≥2 metabolic syndrome risk factors) were randomized to the mHealth intervention (n = 75) or the active control group (n = 74). Blood pressure and other cardiometabolic risk factors were measured at baseline and at 12, 24 and 52 weeks. Both groups received an individualized exercise prescription and the intervention group additionally received a technology kit for home monitoring of biometrics and physical activity.

Results

Analyses were conducted on 67 participants in the intervention group (aged 56.7 ± 9.7 years; 71.6% female) and 60 participants in the active control group (aged 59.1 ± 8.4 years; 76.7% female). At 12 weeks, baseline adjusted mean change in systolic blood pressure (primary outcome) was greater in the active control group compared to the intervention group (-5.68 mmHg; 95% CI -10.86 to -0.50 mmHg; p = 0.03), but there were no differences between groups in mean change for secondary outcomes. Over 52-weeks, the difference in mean change for systolic blood pressure was no longer apparent between groups, but remained significant across the entire population (time: p < 0.001).

Conclusions

In participants with increased cardiometabolic risk, exercise prescription alone had greater short-term improvements in systolic blood pressure compared to the mHealth intervention, though over 52 weeks, improvements were equal between interventions.

Trial registration

ClinicalTrials.gov http://NCT01944124

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2458-14-1082) contains supplementary material, which is available to authorized users.