The Electronic CardioMetabolic Program (eCMP) for Patients With Cardiometabolic Risk: A Randomized Controlled Trial

Empirical Evidence of Internal and External Factors Influencing Users' Motivation Toward Teleconsultation Use

Introduction: The use of teleconsultation systems has increased in recent years, which has improved patients' access to health care providers and enabled seamless interaction between them. The literature points out several factors that either facilitate or impede the use of teleconsultation. However, there is a lack of studies that provide empirical evidence of factors that influence consumers' motivation toward the use of teleconsultation systems. Aim and Objective: This study aimed to provide empirical evidence of the internal and external factors that influence consumers' motivation toward the use of teleconsultation systems. Methods: A cross-sectional survey was used to collect data from consumers who used a real-time teleconsultation system called the Sehha application in Saudi Arabia between March 13 and June 14, 2021. SPSS 27.0.1 was used for descriptive analysis. Results: Four hundred eighty-five participants completed the survey, 471 of whom were included in the analysis. The findings confirmed that internal and external factors exert an influence on consumers' motivation toward the use of teleconsultation systems. The findings indicated that the presence of factors such as saving time, saving cost, accessibility to health care, ease-of-use, reliable internet access, availability of devices, and appropriate places during the online connection would increase consumers' motivation toward teleconsultation systems use. Also, the findings indicated that users' familiarity with systems similar to teleconsultation systems, users' perception of teleconsultation convenience, the influence of others on users' decision to use teleconsultation, and user's skills and confidence in using teleconsultation easily, and their trust in the teleconsultation system would also increase their motivation to use it. Furthermore, the findings showed that demographic factors, including age, gender, level of education, and employment status, did not influence users' motivation toward the use of teleconsultation Conclusions: This study provided empirical evidence of a variety of internal and external factors that exert an influence on consumers' motivation toward the use of teleconsultation systems.

Centralized health management based on hot spring resort improves physical examination indicators and sleep quality in people at high risk of chronic diseases: a randomized controlled trial

We study the effects of centralized health management based on hot spring resorts on the physical examination index and sleep quality of people at high risk of chronic diseases. We recruited 114 volunteers at high risk of chronic diseases. We then divided them into 57 in the intervention group and 57 in the control group. The intervention group collectively received 4 weeks (28 days) of comprehensive health management interventions at Tongjing Hotspring Resort, including regular schedules, balanced diet, appropriate exercise, targeted health education, etc. The main outcomes are physical examination indicators (height, weight, waist circumference, blood pressure, lipids, and glucose) and sleep quality. Both groups underwent a questionnaire and physical examination at baseline, 2 weeks and 4 weeks. Intragroup comparisons grouped by exposure criteria showed decreases in BMI, waist circumference, triglycerides, total cholesterol, and blood glucose in the intervention group at both 2 and 4 weeks (all P < 0.05); however, in the control group, only triglycerides decreased at 4 weeks (P < 0.05). Intergroup comparisons showed BMI and waist circumference were significantly lower in the intervention group than in the control group at 4 weeks (all P < 0.05). Intragroup comparisons of insomnia severity index (ISI) scores showed a significant decrease in the intervention group at both 2 and 4 weeks (all P < 0.001) with no significant change in the control group (P > 0.05). Intergroup comparisons showed that the insomnia severity index (ISI) scores were significantly higher in the intervention group than in the control group at baseline (P = 0.006) but became significantly lower than the control group at 2 and 4 weeks (all P < 0.001). Thus, this pattern significantly improved BMI, waist circumference, triglycerides, and sleep in the intervention group. TRIAL REGISTRATION NUMBER: Chinese Clinical Trials Registry: ChiCTR2100053201, registered 14 Nov 2021. (Retroactive Registration).

Effects of an Individualized mHealth-Based Intervention on Health Behavior Change and Cardiovascular Risk Among People With Metabolic Syndrome Based on the Behavior Change Wheel: Quasi-Experimental Study

BACKGROUND

Metabolic syndrome (MetS) is a common public health challenge. Health-promoting behaviors such as diet and physical activity are central to preventing and controlling MetS. However, the adoption of diet and physical activity behaviors has always been challenging. An individualized mobile health (mHealth)-based intervention using the Behavior Change Wheel is promising in promoting health behavior change and reducing atherosclerotic cardiovascular disease (ASCVD) risk. However, the effects of this intervention are not well understood among people with MetS in mainland China.

OBJECTIVE

We aimed to evaluate the effects of the individualized mHealth-based intervention using the Behavior Change Wheel on behavior change and ASCVD risk in people with MetS.

METHODS

We conducted a quasi-experimental, nonrandomized study. Individuals with MetS were recruited from the health promotion center of a tertiary hospital in Zhejiang province, China. The study involved 138 adults with MetS, comprising a control group of 69 participants and an intervention group of 69 participants. All participants received health education regarding diet and physical activity. The intervention group additionally received a 12-week individualized intervention through a WeChat mini program and a telephone follow-up in the sixth week of the intervention. Primary outcomes included diet, physical activity behaviors, and ASCVD risk. Secondary outcomes included diet self-efficacy, physical activity self-efficacy, knowledge of MetS, quality of life, and the quality and efficiency of health management services. The Mann-Whitney U test and Wilcoxon signed rank test were primarily used for data analysis. Data analysis was conducted based on the intention-to-treat principle using SPSS (version 25.0; IBM Corp).

RESULTS

Baseline characteristics did not differ between the 2 groups. Compared with the control group, participants in the intervention group showed statistically significant improvements in diet behavior, physical activity behavior, diet self-efficacy, physical activity self-efficacy, knowledge of MetS, physical health, and mental health after a 12-week intervention (P=.04, P=.001, P=.04, P=.04, P=.001, P=.04, P=.04, and P<.05). The intervention group demonstrated a statistically significant improvement in outcomes from pre- to postintervention evaluations (P<.001, P=.03, P<.001, P=.04, P<.001, P<.001, and P<.001). The intervention also led to enhanced health management services and quality.

CONCLUSIONS

The individualized mHealth-based intervention using the Behavior Change Wheel was effective in promoting diet and physical activity behaviors in patients with MetS. Nurses and other health care professionals may incorporate the intervention into their health promotion programs.

Aspects of Program Engagement in an Online Physical Activity Intervention and Baseline Predictors of Engagement

PURPOSE

Participant engagement in an online physical activity (PA) intervention is described and baseline factors related to engagement are identified.

DESIGN

Longitudinal Study Within Randomized Controlled Trial.

SETTING

Online/Internet.

SAMPLE

Primary care patients (21-70 years).

INTERVENTION

ActiveGOALS was a 3-month, self-directed online PA intervention (15 total lessons, remote coaching support, and a body-worn step-counter).

MEASURES

Engagement was measured across six outcomes related to lesson completion (total number and time to complete), coach contact, and behavior tracking (PA, sedentary). Self-reported baseline factors were examined from seven domains (confidence, environment, health, health care, demographic, lifestyle, and quality of life).

ANALYSIS

General linear and nonlinear mixed models were used to examine relationships between baseline factors and engagement outcomes within and across all domains.

RESULTS

Seventy-nine participants were included in the sample (77.2% female; 74.7% white non-Hispanic). Program engagement was high (58.2% completed all lessons; PA was tracked ≥3 times/week for 11.3 ± 4.0 weeks on average). Average time between completed lessons (days) was longer than expected and participants only contacted their coach about 1 of every 3 weeks. Individual predictors related to health, health care, demographics, lifestyle, and quality of life were significantly related to engagement.

CONCLUSION

Examining multiple aspects of engagement and a large number of potential predictors of engagement is likely needed to determine facilitators and barriers for high engagement in multi-faceted online intervention programs.

Development of an individualized WeChat mini program-based intervention to increase adherence to dietary recommendations applying the behaviour change wheel among individuals with metabolic syndrome

BACKGROUND

Metabolic Syndrome (MetS) is a serious public health issue. Dietary changes form the core of MetS treatment. The adherence to dietary recommendations is critical for reducing the severity of MetS components and preventing complications. However, the adherence to dietary recommendations was not adequate among adults with MetS. This study utilizes the Behaviour Change Wheel (BCW) to develop an individualized WeChat mini program-based behavioural change intervention aimed at strengthening adherence to dietary recommendations in people with MetS.

METHODS

The BCW theory was used to design an individualized WeChat mini program-based behavioural change intervention. A descriptive qualitative study was conducted to identify the determinants of adherence to dietary recommendations in individuals with MetS. The study was conducted at the health promotion centre of a prominent general university hospital in Zhejiang, China. Subsequently, the intervention functions (IFs) and policy categories were selected following the identified determinants. Afterwards, behaviour change techniques (BCTs) were chosen to translate into potential intervention strategies, and the delivery mode was determined.

RESULTS

Our study identified fifteen barriers to improve the adherence to dietary recommendations in this population. These were linked with six IFs: education, training, persuasion, enablement, modelling, and environmental restructuring. Then, twelve BCTs were linked with the IFs and fifteen barriers. The delivery mode was a WeChat mini program. After these actions, an individualized WeChat mini program-based behavioural change intervention was developed to enhance adherence to dietary recommendations for individuals with MetS.

CONCLUSIONS

The BCW theory helped scientifically and systematically develop an individualized WeChat mini program-based behavioural change intervention for individuals with MetS. In the future, our research team will refine and upgrade the WeChat mini program and then test the usability and effectiveness of the individualized WeChat mini program-based behavioural change intervention program.

The effect of a lifestyle intervention program using a mobile application versus the effect of a program using a booklet for adults with metabolic syndrome: A three-arm randomized controlled trial

PURPOSE

The research aimed to examine the effect of a lifestyle intervention program using mobile application versus booklet for adults with metabolic syndrome in Hong Kong. The outcomes comprised body weight (primary outcome), exercise amount, improvement of cardiometabolic risk factors, cardiovascular endurance, perceived stress scale, and exercise self-efficacy.

DESIGN

A three-arm randomized controlled trial namely App group, Booklet group, and control group was adopted.

METHODS

Two hundred sixty-four adults with metabolic syndrome were recruited from community centers from 2019 to December 2021. Inclusion criteria are those adults with metabolic syndrome, able to use a smart phone. All participants received a 30-min health talk. App group additionally received a mobile application, while Booklet group received a booklet, and the control group received a placebo booklet. Data were collected at baseline, Weeks 4, 12, and 24. SPSS and generalized estimating equations (GEE) model were employed for data analysis.

FINDINGS

Attrition rates were minimal, ranged from 2.65% to 6.44%. Both app and booklet group showed significant improvement in outcomes (exercise amount, waist circumference) when compared to control group. However, statistically significant and superior results were observed in app group, including body weight, exercise amount, waist circumference, body mass index, and systolic blood pressure when compared to booklet group.

CONCLUSION

The lifestyle intervention supported with app was found to be superior to the booklet support for reducing body weight and maintaining exercise.

CLINICAL RELEVANCE

The lifestyle intervention program using mobile application support could be used widely for adults with metabolic syndrome in the community. Suggest nurses may incorporate this program in their health promotion strategies focusing on a healthy lifestyle to reduce the risk of progression to metabolic syndrome.

Enhancing knowledge of Diabetes self-management and quality of life in people with Diabetes Mellitus by using Guru Diabetes Apps-based health coaching

Introduction

Virtual diabetes coaching through applications has the potential to improve self-management in people with Type 2 Diabetes Mellitus. However, applications designed for Asian's diabetic have never been studied. Therefore, our study aimed to identify the effect of Guru Diabetes Apps-Based Health Coaching on the level of glycemic hemoglobin, knowledge, and quality of life in Indonesians, as one of Asian ethnicities.

Materials and methods

This study used an experimental design. Participants with T2DM were recruited from three primary care health centers. The intervention included 3 months of virtual health coaching through the Guru Diabetes application. The daily monitoring of glycemic blood glucose, blood pressure, body weight, nutrition intake, and activity provided were used as baseline to conduct virtual in-person coaching. The glycemic hemoglobin level, knowledge level, and quality of life were assessed at baseline and post-enrollment. A multilevel modeling approach was used for statistical analysis.

Results

A total of 66 respondents were enrolled, and 62 respondents (93.93%) remained in the study at 3 months. After completing the intervention, the HbA1c level decreased in all groups, however it did not differ among the groups. On the other hand, the results indicate significant improvement in the average diabetes self-management knowledge score (pre = 14.97 vs post = 19.07, p < 0.05) and quality of life score (pre = 54.34 vs post = 60.28, p < 0.05), with significant difference among the groups (p < 0.05).

Conclusion

Participants in the Android Application-Based Health Coaching experienced a significant improvement in diabetes self-management knowledge and quality of life scores at 3 months. In conclusion, the Guru Diabetes Apps-Based Health Coaching has the potential to support people with T2DM in performing diabetes self-management at home.

Effectiveness of dietary interventions delivered by digital health to adults with chronic conditions: Systematic review and meta-analysis

BACKGROUND

Digital health interventions may facilitate management of chronic conditions; however, no reviews have systematically assessed the effectiveness of dietary interventions delivered by digital health platforms for improving dietary intake and clinical outcomes for adults with diet-related chronic conditions.

METHODS

Databases CINAHL, CENTRAL, Embase and MEDLINE were searched from inception to April 2021 to identify controlled trials for dietary education delivered by digital health (mobile or electronic health) to adults with diet-related chronic conditions. Random effects analysis was performed for diet quality, food groups, nutrients and clinical outcomes. Screening, data extraction and quality checking were completed in duplicate.

RESULTS

Thirty-nine studies were included involving 7333 participants. Significant changes were found for Mediterranean diet adherence score (standardised mean difference [SMD] = 0.79; 95% confidence interval [CI] = 0.18 to 1.40), overall fruit and vegetable intake (mean difference [MD]: 0.63 serves/day; 95% CI = 0.27-0.98), fruit intake alone (MD = 0.58 serves/day; 95% CI = 0.39 to 0.77) and sodium intake (SMD = -0.22; 95% CI = -0.44 to -0.01). Improvements were also found for waist circumference [MD = -2.24 centimetres; 95% CI = -4.14 to -0.33], body weight (MD = -1.94 kg; 95% CI = -2.63 to -1.24) and haemoglobin A1c (MD = -0.17%; 95% CI = -0.29 to -0.04). Validity of digital assessment tools to measure dietary intake were not reported. The quality of evidence was considered to have low to moderate certainty.

CONCLUSIONS

Modest improvements in diet and clinical outcomes may result from intervention via digital health for those with diet-related chronic conditions. However, additional robust trials with better reporting of digital dietary assessment tools are needed to support implementation within clinical practice.

A Pilot Study to Examine the Feasibility and Acceptability of a Virtual Adaptation of an In-Person Adolescent Diabetes Prevention Program

BACKGROUND

Rates of prediabetes and type 2 diabetes are alarmingly high among racial/ethnic minority youth. The current study examines the virtual adaptation of an in-person peer-led youth diabetes prevention program.

METHODS

The initial phase involved the study team adapting workshop sessions from an in-person to a virtual format (Zoom). We conducted a 2-h feasibility pilot in December 2020 and implemented the full 12 session pilot program from June to September 2021 with 14 prediabetic adolescents recruited from our hospital-based general pediatric clinic. Weekly sessions were led by trained peer educators and focused on promoting healthy eating and physical activity using behavioral techniques (e.g., goal setting, brainstorming, and problem solving).

RESULTS

The virtual adaptation of our program was shown to be feasible and acceptable among our pilot participants. We were able to deliver the same workshop content and behavioral skills development as the in-person workshop using a variety of Zoom features.

CONCLUSIONS

Our peer-led youth diabetes prevention program was successfully adapted and implemented in a virtual format and was well accepted by at-risk youth. Future research is needed to examine the impact of virtual youth lifestyle interventions on behavioral and clinical outcomes such as weight and diabetes risk.

Development of a behavior change intervention to improve physical activity adherence in individuals with metabolic syndrome using the behavior change wheel

Background

Adherence to physical activity is inadequate in adults with metabolic syndrome. Adherence to physical activity recommendations is crucial and can result in improved health outcomes and reduced medical burdens. A comprehensive behavior change intervention, including identifying determinants of adherence to physical activity recommendations, intervention options, intervention content and implementation options, was imperative for enhancing physical activity adherence. The aim of the study is to develop an intervention to increase physical activity adherence among individuals with metabolic syndrome.

Methods

The study followed the eight steps of the Behavior Change Wheel guide, including defining the problem in behavioral terms (Step 1), selecting target behavior (Step 2), specifying target behavior (Step 3), identifying what needs to change (Step 4), identifying intervention functions (Step 5), identifying policy categories (Step 6), identifying behavior change techniques (Step 7), and determining model of delivery (Step 8). The semi-structured, in-depth interviews were employed to identify the determinants of adherence to physical activity among twenty-eight individuals with metabolic syndrome based on capability, opportunity, motivation and behavior model. Next, the intervention functions and policy categories were chosen to address these determinants. Finally, behavior change techniques were selected to assist in the delivery of the intervention functions and be translated into intervention content.

Results

Our study identified eighteen facilitators and fifteen barriers to physical activity adherence. It resulted in the selection of seven intervention functions and nineteen behavior change techniques for the intervention program. Then, the current study identified an app as the delivery mode. Finally, a behavioral change intervention was generated for individuals with metabolic syndrome to increase physical activity recommendation adherence.

Conclusions

The Behavior Change Wheel provided a systematic approach to designing a behavior change intervention, which helped improve the health outcomes and reduce medical burdens and economic burdens among individuals with metabolic syndrome. The findings suggested that potential intervention should pay special attention to increasing knowledge in metabolic syndrome, imparting skills of physical activity, offering a supportive environment, and providing suggestions on regular physical activity using the appropriate behavior change techniques. A feasibility study will be undertaken to assess the acceptability and effectiveness of the intervention program in the future.

Digital Behavior Change Interventions for the Prevention and Management of Type 2 Diabetes: Systematic Market Analysis

BACKGROUND

Advancements in technology offer new opportunities for the prevention and management of type 2 diabetes. Venture capital companies have been investing in digital diabetes companies that offer digital behavior change interventions (DBCIs). However, little is known about the scientific evidence underpinning such interventions or the degree to which these interventions leverage novel technology-driven automated developments such as conversational agents (CAs) or just-in-time adaptive intervention (JITAI) approaches.

OBJECTIVE

Our objectives were to identify the top-funded companies offering DBCIs for type 2 diabetes management and prevention, review the level of scientific evidence underpinning the DBCIs, identify which DBCIs are recognized as evidence-based programs by quality assurance authorities, and examine the degree to which these DBCIs include novel automated approaches such as CAs and JITAI mechanisms.

METHODS

A systematic search was conducted using 2 venture capital databases (Crunchbase Pro and Pitchbook) to identify the top-funded companies offering interventions for type 2 diabetes prevention and management. Scientific publications relating to the identified DBCIs were identified via PubMed, Google Scholar, and the DBCIs' websites, and data regarding intervention effectiveness were extracted. The Diabetes Prevention Recognition Program (DPRP) of the Center for Disease Control and Prevention in the United States was used to identify the recognition status. The DBCIs' publications, websites, and mobile apps were reviewed with regard to the intervention characteristics.

RESULTS

The 16 top-funded companies offering DBCIs for type 2 diabetes received a total funding of US $2.4 billion as of June 15, 2021. Only 4 out of the 50 identified publications associated with these DBCIs were fully powered randomized controlled trials (RCTs). Further, 1 of those 4 RCTs showed a significant difference in glycated hemoglobin A1c (HbA1c) outcomes between the intervention and control groups. However, all the studies reported HbA1c improvements ranging from 0.2% to 1.9% over the course of 12 months. In addition, 6 interventions were fully recognized by the DPRP to deliver evidence-based programs, and 2 interventions had a pending recognition status. Health professionals were included in the majority of DBCIs (13/16, 81%,), whereas only 10% (1/10) of accessible apps involved a CA as part of the intervention delivery. Self-reports represented most of the data sources (74/119, 62%) that could be used to tailor JITAIs.

CONCLUSIONS

Our findings suggest that the level of funding received by companies offering DBCIs for type 2 diabetes prevention and management does not coincide with the level of evidence on the intervention effectiveness. There is considerable variation in the level of evidence underpinning the different DBCIs and an overall need for more rigorous effectiveness trials and transparent reporting by quality assurance authorities. Currently, very few DBCIs use automated approaches such as CAs and JITAIs, limiting the scalability and reach of these solutions.

Development and validation of a new tool to identify factors that influence users' motivation toward the use of teleconsultation systems: A modified Delphi study

BACKGROUND

Healthcare providers have improved consumer access to healthcare services by the adoption of information communication technology and the use of telemedicine. With the current COVID-19 pandemic, consumers are shifting to remote teleconsultation. There are several studies regarding consumers' acceptance and satisfaction with telemedicine among healthcare providers and a few among patients at healthcare facilities. However, studies about patients' motivation toward the use of teleconsultation systems are very few.

AIM

The aim of this study was to validate an instrument of a newly developed framework to identify factors that motivate patients to use a teleconsultation system.

METHOD

This study used a modified eDelphi method incorporating content validity index and content validity ratio procedures to validate the instrument among fifteen experts from different disciplines. The eDelphi consisted of three rounds to review each item's relevance, clarity, importance and the overall validity of the instrument.

RESULT

The result showed a significant level of agreement among experts for individual items' relevance, clarity and importance. For relevance, all items had excellent I-CVI above 0.889, except one item with I-CVI = 0.78, which is still acceptable. For clarity, all items had an excellent I-CVI > 0.889, except one with I-CVI = 0.667. For importance, most items had CVR above the threshold value of 0.778, except 5 items. Also, the result showed moderate to high content validity of the overall instrument (S-CVI/UA = 0.694; S-CVI/Ave = 0.996).

DISCUSSION

These findings support the validity and reliability of the developed instrument, which can be used to identify factors that motivated patients to use a teleconsultation system. Future testing of the instrument should be conducted with a larger population that uses a teleconsultation system.

CONCLUSION

An instrument was developed to identify factors that motivated consumers to use teleconsultation, using a modified eDelphi method among experts. The eDelphi method consisted of three rounds and the results showed that the instrument is a valid and reliable tool.

The Effect of a Lifestyle Intervention Program Using a Mobile Application for Adults with Metabolic Syndrome, versus the Effect of a Program Using a Booklet: A Pilot Randomized Controlled Trial

Purpose

This study aimed to examine the preliminary effect, feasibility, and acceptability of a lifestyle intervention program using a mobile application (app) versus the effect of a program using a booklet for adults with metabolic syndrome (MetS).

Patients and Methods

This trial was conducted in two community centers of Hong Kong. Participants were included if they were adults with MetS, aged over 50, and able to use a smartphone. Eligible subjects were randomly assigned to either the app group or booklet group. Those in the booklet group received a health talk and a booklet, whereas those in the app group received a health talk and a MetS app to support their exercise maintenance and health records for 3 months. Both groups received similar educational content related to healthcare for MetS clients. Data were collected at baseline (T1) and at 1- (T2) and 3-month (T3) intervals. Outcomes were body weight (primary outcome), total amount of exercise, blood pressure, and lipid concentrations. Data were analyzed using the generalized estimating equation models. Feasibility and acceptability were assessed in process evaluation.

Results

Ninety-eight individuals were screened for eligibility and 77 were randomized into the app group (n = 38) or booklet group (n = 39). The attrition rate at T3 was 11.690%. The app group showed a significant reduction in body weight (β = −1.069, p = 0.012) and body mass index (β = −0.371, p = 0.026), a greater amount of exercise (β = 8.454, p = 0.032), and improved exercise self-efficacy (β = 10.62, p = 0.001) within 3 months. There were no significant differences between groups for other outcomes. The participants appreciated the proposed intervention of the programme.

Conclusion

The MetS app may be incorporated in the health promotion programme to support exercise maintenance and a healthy lifestyle in the community.

Weight loss effects in usual primary care: Findings from 5 behavioral weight loss RCTs

Primary care is an important setting for obesity treatment and behavior therapy is considered the first line. However, current practice often does not meet clinical guidelines and, furthermore, effects of usual care (UC) on weight loss are unclear. This makes it difficult to design sufficiently powered weight loss trials in primary care. This study analyzed data from UC control participants across 5 primary care-based randomized clinical trials of behavioral weight loss interventions to assess UC effects for 4 weight outcomes: body mass index (BMI), weight change (kg and %), and percent of participants achieving clinically significant 5% weight loss. Results indicated modest UC effects, suggesting modest weight loss is possible in usual primary care.

A Technology-Mediated Interventional Approach to the Prevention of Metabolic Syndrome: A Systematic Review and Meta-Analysis

BACKGROUND

Technology-mediated interventions help overcome barriers to program delivery and spread metabolic syndrome prevention programs on a large scale. A meta-analysis was performed to evaluate the impact of these technology-mediated interventions on metabolic syndrome prevention.

METHODS

In this meta-analysis, from 30 January 2018, three databases were searched to evaluate interventions using techniques to propagate diet and exercise lifestyle programs for adult patients with metabolic syndrome or metabolic risk.

RESULTS

Search results found 535 citations. Of these, 18 studies met the inclusion criteria analyzed in this article. The median duration of intervention was 4 months and the follow-up period ranged from 1.5 to 30 months. The standardized mean difference (SMD) between the two groups was waist circumference -0.35 (95% CI -0.54, -0.15), triglyceride -0.14 (95% CI -0.26, -0.03), fasting blood glucose -0.31 (95% CI -0.42, -0.19), body weight -1.34 (95% CI -2.04, -0.64), and body mass index -1.36 (95% CI -2.21, -0.51). There was no publication bias in this study.

CONCLUSION

Technology-mediated intervention improved clinically important metabolic syndrome related indicators such as excess body fat around the waist, fasting glucose, and body mass index. These interventions will play an important role in the dissemination of metabolic syndrome prevention programs.

Fitbit-Based Interventions for Healthy Lifestyle Outcomes: Systematic Review and Meta-Analysis

BACKGROUND

Unhealthy behaviors, such as physical inactivity, sedentary lifestyle, and unhealthful eating, remain highly prevalent, posing formidable challenges in efforts to improve cardiovascular health. While traditional interventions to promote healthy lifestyles are both costly and effective, wearable trackers, especially Fitbit devices, can provide a low-cost alternative that may effectively help large numbers of individuals become more physically fit and thereby maintain a good health status.

OBJECTIVE

The objectives of this meta-analysis are (1) to assess the effectiveness of interventions that incorporate a Fitbit device for healthy lifestyle outcomes (eg, steps, moderate-to-vigorous physical activity, and weight) and (2) to identify which additional intervention components or study characteristics are the most effective at improving healthy lifestyle outcomes.

METHODS

A systematic review was conducted, searching the following databases from 2007 to 2019: MEDLINE, EMBASE, CINAHL, and CENTRAL (Cochrane). Studies were included if (1) they were randomized controlled trials, (2) the intervention involved the use of a Fitbit device, and (3) the reported outcomes were related to healthy lifestyles. The main outcome measures were related to physical activity, sedentary behavior, and weight. All the studies were assessed for risk of bias using Cochrane criteria. A random-effects meta-analysis was conducted to estimate the treatment effect of interventions that included a Fitbit device compared with a control group. We also conducted subgroup analysis and fuzzy-set qualitative comparative analysis (fsQCA) to further disentangle the effects of intervention components.

RESULTS

Our final sample comprised 41 articles reporting the results of 37 studies. For Fitbit-based interventions, we found a statistically significant increase in daily step count (mean difference [MD] 950.54, 95% CI 475.89-1425.18; P<.001) and moderate-to-vigorous physical activity (MD 6.16, 95% CI 2.80-9.51; P<.001), a significant decrease in weight (MD -1.48, 95% CI -2.81 to -0.14; P=.03), and a nonsignificant decrease in objectively assessed and self-reported sedentary behavior (MD -10.62, 95% CI -35.50 to 14.27; P=.40 and standardized MD -0.11, 95% CI -0.48 to 0.26; P=.56, respectively). In general, the included studies were at low risk for bias, except for performance bias. Subgroup analysis and fsQCA demonstrated that, in addition to the effects of the Fitbit devices, setting activity goals was the most important intervention component.

CONCLUSIONS

The use of Fitbit devices in interventions has the potential to promote healthy lifestyles in terms of physical activity and weight. Fitbit devices may be useful to health professionals for patient monitoring and support.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42019145450; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019145450.

Effectiveness of Mobile Health Interventions Promoting Physical Activity and Lifestyle Interventions to Reduce Cardiovascular Risk Among Individuals With Metabolic Syndrome: Systematic Review and Meta-Analysis

BACKGROUND

Physical activity and lifestyle interventions, such as a healthy diet, have been proven to be effective approaches to manage metabolic syndrome. However, these interventions require great commitment from patients and clinicians owing to their economic costs, time consumption, and lack of immediate results.

OBJECTIVE

The aim of this systematic review and meta-analysis was to analyze the effect of mobile-based health interventions for reducing cardiometabolic risk through the promotion of physical activity and healthy lifestyle behaviors.

METHODS

PubMed, Scopus, Web of Science, Cochrane Central Register of Controlled Trials, and SPORTdiscus databases were searched for experimental studies evaluating cardiometabolic risk indicators among individuals with metabolic syndrome who were included in technology-assisted physical activity and lifestyle interventions. Effect sizes, pooled mean changes, and their respective 95% CIs were calculated using the DerSimonian and Laird method. Outcomes included the following clinical and biochemical parameters: body composition (waist circumference [WC] and BMI), blood pressure (systolic blood pressure [SBP] and diastolic blood pressure [DBP]), glucose tolerance (fasting plasma glucose [FPG] and glycated hemoglobin A1c [HbA_1c]), and lipid profile (total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol [HDL-C], and triglycerides).

RESULTS

A total of nine studies were included in the meta-analysis. Owing to the scarcity of studies, only pooled mean pre-post changes in the intervention groups were estimated. Significant mean changes were observed for BMI (-1.70 kg/m2, 95% CI -3.20 to -0.20; effect size: -0.46; P=.03), WC (-5.77 cm, 95% CI -9.76 to -1.77; effect size: -0.54; P=.005), SBP (-7.33 mmHg, 95% CI -13.25 to -1.42; effect size: -0.43; P=.02), DBP (-3.90 mmHg, 95% CI -7.70 to -0.11; effect size: -0.44; P=.04), FPG (-3.65 mg/dL, 95% CI -4.79 to -2.51; effect size: -0.39; P<.001), and HDL-C (4.19 mg/dL, 95% CI 2.43-5.95; effect size: 0.23; P<.001).

CONCLUSIONS

Overall, mobile-based health interventions aimed at promoting physical activity and healthy lifestyle changes had a strong positive effect on cardiometabolic risk indicators among individuals with metabolic syndrome. Nevertheless, further research is required to compare this approach with usual care in order to support the incorporation of these technologies in health systems.

TRIAL REGISTRATION

PROSPERO CRD42019125461; https://tinyurl.com/y3t4wog4.

Barriers and Facilitators That Influence Telemedicine-Based, Real-Time, Online Consultation at Patients' Homes: Systematic Literature Review

Background

Health care providers are adopting information and communication technologies (ICTs) to enhance their services. Telemedicine is one of the services that rely heavily on ICTs to enable remote patients to communicate with health care professionals; in this case, the patient communicates with the health care professional for a follow-up or for a consultation about his or her health condition. This communication process is referred to as an e-consultation. In this paper, telemedicine services refer to health care services that use ICTs, which enable patients to share, transfer, and communicate data or information in real time (ie, synchronous) from their home with a care provider—normally a physician—at a clinical site. However, the use of e-consultation services can be positively or negatively influenced by external or internal factors. External factors refer to the environment surrounding the system as well as the system itself, while internal factors refer to user behavior and motivation.

Objective

This review aims to investigate the barriers and the facilitators that influence the use of home consultation systems in the health care context. This review also aims to identify the effectiveness of Home Online Health Consultation (HOHC) systems in improving patients’ health as well as their satisfaction with the systems.

Methods

We conducted a systematic literature review to search for articles—empirical studies—about online health consultation in four digital libraries: Scopus, Association for Computing Machinery, PubMed, and Web of Science. The database search yielded 2518 articles; after applying the inclusion and exclusion criteria, the number of included articles for the final review was 45. A qualitative content analysis was performed to identify barriers and facilitators to HOHC systems, their effectiveness, and patients’ satisfaction with them.

Results

The systematic literature review identified several external and internal facilitators and barriers to HOHC systems that were used in the creation of a HOHC framework. The framework consists of four requirements; the framework also consists of 17 facilitators and eight barriers, which were further categorized as internal and external influencers on HOHC.

Conclusions

Patients from different age groups and with different health conditions benefited from remote health services. HOHC via video conferencing was effective in delivering online treatment and was well-accepted by patients, as it simulated in-person, face-to-face consultation. Acceptance by patients increased as a result of online consultation facilitators that promoted effective and convenient remote treatment. However, some patients preferred face-to-face consultation and showed resistance to online consultation. Resistance to online consultation was influenced by some of the identified barriers. Overall, the framework identified the facilitators and barriers that positively and negatively influenced the uptake of HOHC systems, respectively.

A nurse-led lifestyle intervention using mobile application versus booklet for adults with metabolic syndrome-Protocol for a randomized controlled trial

AIMS

To compare the effect of a lifestyle intervention programme using mobile application versus booklet for adults with metabolic syndrome (MetS) living in the community.

DESIGN

A multisite randomized controlled trial with three parallel arms, namely metabolic syndrome app group, booklet group, and control group.

METHODS

The research study has been supported by the Health and Medical Research fund in Hong Kong in 2019. The protocol was approved by the study university and the selected community centres. Three hundred and sixty subjects will be recruited from community centres and randomized into either one arm. Inclusion criteria are those adult with MetS, able to use a smart phone. All participants received a 30-min health educational session. App group participants will receive a mobile application while booklet group participants will receive a specific booklet of MetS care and the control group receive a placebo booklet only. The primary outcomes comprises of body weight. The secondary outcomes include total physical exercise, cardiometablolic risk factors, cardiovascular endurance, self-efficacy for exercise, and stress level. Data will be collected at baseline, weeks 4, 12, and 24. SPSS and generalized estimating equations model will be employed for data analysis.

DISCUSSION

Metabolic syndrome is a common health problem associated with the heightened risk of cardiovascular disease and the risks are potentially amenable to lifestyle intervention. The results will compare the relative effectiveness of a lifestyle intervention using an app versus a booklet on physical and psychological outcomes for adults with MetS.

IMPACT

What problem will the study address? The results will inform the healthcare professional and nurses about the effective way for health promotion, to enhance patient's lifestyle modification and exercise sustainability that will be beneficial to the clients' health.

Digital Health-Supported Lifestyle Change Programs to Prevent Type 2 Diabetes

IN BRIEF Type 2 diabetes can be prevented or delayed in people with prediabetes through participation in an intensive lifestyle change program (LCP), particularly one based on the Diabetes Prevention Program research study. Digital health offers opportunities to extend the reach of such LCPs and possibly improve on these programs, which traditionally have been delivered in person. In this review, we describe the current state of evidence regarding digital health-supported LCPs and discuss gaps in research and opportunities for future efforts.

Sleep Tracking and Exercise in Patients With Type 2 Diabetes Mellitus (Step-D): Pilot Study to Determine Correlations Between Fitbit Data and Patient-Reported Outcomes

Background

Few studies assessing the correlation between patient-reported outcomes and patient-generated health data from wearable devices exist.

Objective

The aim of this study was to determine the direction and magnitude of associations between patient-generated health data (from the Fitbit Charge HR) and patient-reported outcomes for sleep patterns and physical activity in patients with type 2 diabetes mellitus (T2DM).

Methods

This was a pilot study conducted with adults diagnosed with T2DM (n=86). All participants wore a Fitbit Charge HR for 14 consecutive days and completed internet-based surveys at 3 time points: day 1, day 7, and day 14. Patient-generated health data included minutes asleep and number of steps taken. Questionnaires assessed the number of days of exercise and nights of sleep problems per week. Means and SDs were calculated for all data, and Pearson correlations were used to examine associations between patient-reported outcomes and patient-generated health data. All respondents provided informed consent before participating.

Results

The participants were predominantly middle-aged (mean 54.3, SD 13.3 years), white (80/86, 93%), and female (50/86, 58%). Use of oral T2DM medication correlated with the number of mean steps taken (r=.35, P=.001), whereas being unaware of the glycated hemoglobin level correlated with the number of minutes asleep (r=−.24, P=.04). On the basis of the Fitbit data, participants walked an average of 4955 steps and slept 6.7 hours per day. They self-reported an average of 2.0 days of exercise and 2.3 nights of sleep problems per week. The association between the number of days exercised and steps walked was strong (r=.60, P<.001), whereas the association between the number of troubled sleep nights and minutes asleep was weaker (r=.28, P=.02).

Conclusions

Fitbit and patient-reported data were positively associated for physical activity as well as sleep, with the former more strongly correlated than the latter. As extensive patient monitoring can guide clinical decisions regarding T2DM therapy, passive, objective data collection through wearables could potentially enhance patient care, resulting in better patient-reported outcomes.

Outcomes of a Digital Health Program With Human Coaching for Diabetes Risk Reduction in a Medicare Population

OBJECTIVE

To examine the outcomes of a Medicare population who participated in a program combining digital health with human coaching for diabetes risk reduction.

METHOD

People at risk for diabetes enrolled in a program combining digital health with human coaching. Participation and health outcomes were examined at 16 weeks and 6 and 12 months.

RESULTS

A total of 501 participants enrolled; 92% completed at least nine of 16 core lessons. Participants averaged 19 of 31 possible opportunities for weekly program engagement. At 12 months, participants lost 7.5% ( SD = 7.8%) of initial body weight; among participants with clinical data, glucose control improved (glycosylated hemoglobin [HbA1c] change = -0.14%, p = .001) and total cholesterol decreased (-7.08 mg/dL, p = .008). Self-reported well-being, depression, and self-care improved ( p < .0001).

DISCUSSION

This Medicare population demonstrated sustained program engagement and improved weight, health, and well-being. The findings support digital programs with human coaching for reducing chronic disease risk among older adults.

HOMBRE: A randomized controlled trial to compare two approaches to weight loss for overweight and obese Latino men (Hombres con Opciones para Mejorar el Bienestar y bajar el Riesgo de Enfermedades crónicas; men with choices to improve well-being and decrease chronic disease risk)

Latino men bear a disproportionate burden of obesity, diabetes, and cardiovascular disease.However, limited behavioral lifestyle intervention research has focused on Latino men. This trial compares two approaches to weight loss for overweight and obese Latino men: 1) HOMBRE is a culturally adapted intervention that provides individual choice of either self-directed online videos, coach-facilitated in-person groups, and coach-facilitated online groups; and 2) a minimal intensity intervention that uses online videos with a coach available, if solicited by the participant.Latino men with a Body Mass Index (BMI) of ≥27 kg/m2 and one or more cardiometabolic risk factors (n = 424) will be randomly assigned to receive one of the two approaches.The RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework guides the planned evaluations.The primary aim is to determine the effectiveness of the HOMBRE intervention (the "E" in RE-AIM) on clinically significant weight loss (≥5% of baseline weight) at 18 months. We hypothesize that a significantly higher proportion of HOMBRE participants will maintain ≥5% of weight loss compared with those in the minimal intensity intervention.Secondary aims are to determine the effectiveness of HOMBRE on cardiometabolic risk factors (e.g., blood pressure, waist circumference), health behaviors (e.g., diet and physical activity), and psychosocial well-being (e.g., quality of life and depressive symptoms) and to evaluate the other attributes of RE-AIM. These findings have real word applicability with value to clinicians, patients, and other decision makers considering effective diabetes prevention programs for Latino men in primary care.

Impact of educational interventions on primary prevention of cardiovascular disease: A systematic review with a focus on physical activity

Background: Evidence from epidemiological and experimental studies illustrates the beneficial impact of healthy lifestyle behaviours on cardiovascular risk.

Objectives: To assess the effectiveness of primary care health education interventions designed to promote healthy lifestyles on physical activity levels and cardiovascular risk.

Methods: A computer-aided search on PubMed and Scopus was performed to identify relevant studies published from January 2000 to October 2016. Two authors independently selected studies for inclusion and extracted data, including intervention characteristics and outcome measures, namely physical activity and cardiovascular risk or risk factors.

Results: Of the 212 identified studies, 15 met the inclusion criteria. The 15 studies enrolled 6727 participants; the sample size varied between 74 and 878 adults. Fourteen studies assessed physical activity by questionnaire and only one study used accelerometry. Eight of the 15 studies showed improvements in the physical activity levels after the intervention, ranging from 5% to 26% in those where significant changes between groups were detected. Most studies reported significant positive effects of the health education interventions on cardiovascular risk factors, mainly on lipid profile, blood pressure and cardiovascular risk score.

Conclusion: The health education interventions, in primary care, seem to improve daily physical activity, cardiovascular risk factors and risk score.

Smart Devices for Older Adults Managing Chronic Disease: A Scoping Review

BACKGROUND

The emergence of smartphones and tablets featuring vastly advancing functionalities (eg, sensors, computing power, interactivity) has transformed the way mHealth interventions support chronic disease management for older adults. Baby boomers have begun to widely adopt smart devices and have expressed their desire to incorporate technologies into their chronic care. Although smart devices are actively used in research, little is known about the extent, characteristics, and range of smart device-based interventions.

OBJECTIVE

We conducted a scoping review to (1) understand the nature, extent, and range of smart device-based research activities, (2) identify the limitations of the current research and knowledge gap, and (3) recommend future research directions.

METHODS

We used the Arksey and O'Malley framework to conduct a scoping review. We identified relevant studies from MEDLINE, Embase, CINAHL, and Web of Science databases using search terms related to mobile health, chronic disease, and older adults. Selected studies used smart devices, sampled older adults, and were published in 2010 or after. The exclusion criteria were sole reliance on text messaging (short message service, SMS) or interactive voice response, validation of an electronic version of a questionnaire, postoperative monitoring, and evaluation of usability. We reviewed references. We charted quantitative data and analyzed qualitative studies using thematic synthesis. To collate and summarize the data, we used the chronic care model.

RESULTS

A total of 51 articles met the eligibility criteria. Research activity increased steeply in 2014 (17/51, 33%) and preexperimental design predominated (16/50, 32%). Diabetes (16/46, 35%) and heart failure management (9/46, 20%) were most frequently studied. We identified diversity and heterogeneity in the collection of biometrics and patient-reported outcome measures within and between chronic diseases. Across studies, we found 8 self-management supporting strategies and 4 distinct communication channels for supporting the decision-making process. In particular, self-monitoring (38/40, 95%), automated feedback (15/40, 38%), and patient education (13/40, 38%) were commonly used as self-management support strategies. Of the 23 studies that implemented decision support strategies, clinical decision making was delegated to patients in 10 studies (43%). The impact on patient outcomes was consistent with studies that used cellular phones. Patients with heart failure and asthma reported improved quality of life. Qualitative analysis yielded 2 themes of facilitating technology adoption for older adults and 3 themes of barriers.

CONCLUSIONS

Limitations of current research included a lack of gerontological focus, dominance of preexperimental design, narrow research scope, inadequate support for participants, and insufficient evidence for clinical outcome. Recommendations for future research include generating evidence for smart device-based programs, using patient-generated data for advanced data mining techniques, validating patient decision support systems, and expanding mHealth practice through innovative technologies.

mHealth Assessment: Conceptualization of a Global Framework

BACKGROUND

The mass availability and use of mobile health (mHealth) technologies offers the potential for these technologies to support or substitute medical advice. However, it is worrisome that most assessment initiatives are still not able to successfully evaluate all aspects of mHealth solutions. As a result, multiple strategies to assess mHealth solutions are being proposed by medical regulatory bodies and similar organizations.

OBJECTIVE

We aim to offer a collective description of a universally applicable description of mHealth assessment initiatives, given their current and, as we see it, potential impact. In doing so, we recommend a common foundation for the development or update of assessment initiatives by addressing the multistakeholder issues that mHealth technology adds to the traditional medical environment.

METHODS

Organized by the Mobile World Capital Barcelona Foundation, we represent a workgroup consisting of patient associations, developers, and health authority representatives, including medical practitioners, within Europe. Contributions from each group's diverse competencies has allowed us to create an overview of the complex yet similar approaches to mHealth evaluation that are being developed today, including common gaps in concepts and perspectives. In response, we summarize commonalities of existing initiatives and exemplify additional characteristics that we believe will strengthen and unify these efforts.

RESULTS

As opposed to a universal standard or protocol in evaluating mHealth solutions, assessment frameworks should respect the needs and capacity of each medical system or country. Therefore, we expect that the medical system will specify the content, resources, and workflow of assessment protocols in order to ensure a sustainable plan for mHealth solutions within their respective countries.

CONCLUSIONS

A common framework for all mHealth initiatives around the world will be useful in order to assess whatever mHealth solution is desirable in different areas, adapting it to the specifics of each context, to bridge the gap between health authorities, patients, and mHealth developers. We aim to foster a more trusting and collaborative environment to safeguard the well-being of patients and citizens while encouraging innovation of technology and policy.