Multicomponent mHealth Intervention for Large, Sustained Change in Multiple Diet and Activity Risk Behaviors: The Make Better Choices 2 Randomized Controlled Trial

The moderating effect of access to food facilities and recreational activity space on mHealth multiple health behavior change intervention

OBJECTIVE

To evaluate whether the neighborhood social and built environment moderates response to a mobile health multiple health behavior change intervention targeting fruit/vegetable intake, sedentary behavior, and physical activity.

METHODS

Participants were 156 Chicago-residing adults with unhealthy lifestyle behaviors. Using linear mixed models, we evaluated whether access to food facilities (fast food restaurants and grocery stores) and recreational activity spaces (gyms and parks) moderated the difference in behavior change between the active intervention condition relative to control. Using spatial data analysis (cross K functions), we also assessed whether participants who achieved goal levels of behaviors ("responders") were more or less likely than those who did not achieve intervention goals ("non-responders") to reside near fast food restaurants, grocery stores, gyms, or parks.

RESULTS

According to linear mixed models, none of the neighborhood social and built environment factors moderated the difference in behavior change between the active intervention condition and the control condition (Likelihood Ratio (χ²[1] = 0.02-2.33, P-values > 0.05). Cross K functions showed that diet behavior change responders were more likely than non-responders to reside near fast food restaurants, but not grocery stores. The results for activity behavior change were more variable. Sedentary screen time responders were more likely to reside around recreational activity spaces than non-responders. Moderate-vigorous physical activity responders had greater and lesser clustering than non-responders around parks, dependent upon distance from the park to participant residence.

CONCLUSIONS

A complex relationship was observed between residential proximity to Chicago facilities and response to multiple health behavior change intervention. Replication across diverse geographic settings and samples is necessary.

An Adaptive Behavioral Intervention for Weight Loss Management: A Randomized Clinical Trial

Importance

Lifestyle interventions for weight loss are difficult to implement in clinical practice. Self-managed mobile health implementations without or with added support after unsuccessful weight loss attempts could offer effective population-level obesity management.

Objective

To test whether a wireless feedback system (WFS) yields noninferior weight loss vs WFS plus telephone coaching and whether participants who do not respond to initial treatment achieve greater weight loss with more vs less vigorous step-up interventions.

Design, Setting, and Participants

In this noninferiority randomized trial, 400 adults aged 18 to 60 years with a body mass index of 27 to 45 were randomized in a 1:1 ratio to undergo 3 months of treatment initially with WFS or WFS plus coaching at a US academic medical center between June 2017 and March 2021. Participants attaining suboptimal weight loss were rerandomized to undergo modest or vigorous step-up intervention.

Interventions

The WFS included a Wi-Fi activity tracker and scale transmitting data to a smartphone app to provide daily feedback on progress in lifestyle change and weight loss, and WFS plus coaching added 12 weekly 10- to 15-minute supportive coaching calls delivered by bachelor's degree-level health promotionists viewing participants' self-monitoring data on a dashboard; step-up interventions included supportive messaging via mobile device screen notifications (app-based screen alerts) without or with coaching or powdered meal replacement. Participants and staff were unblinded and outcome assessors were blinded to treatment randomization.

Main Outcomes and Measures

The primary outcome was the between-group difference in 6-month weight change, with the noninferiority margin defined as a difference in weight change of -2.5 kg; secondary outcomes included between-group differences for all participants in weight change at 3 and 12 months and between-group 6-month weight change difference among nonresponders exposed to modest vs vigorous step-up interventions.

Results

Among 400 participants (mean [SD] age, 40.5 [11.2] years; 305 [76.3%] women; 81 participants were Black and 266 were White; mean [SD] body mass index, 34.4 [4.3]) randomized to undergo WFS (n = 199) vs WFS plus coaching (n = 201), outcome data were available for 342 participants (85.5%) at 6 months. Six-month weight loss was -2.8 kg (95% CI, -3.5 to -2.0) for the WFS group and -4.8 kg (95% CI, -5.5 to -4.1) for participants in the WFS plus coaching group (difference in weight change, -2.0 kg [90% CI, -2.9 to -1.1]; P < .001); the 90% CI included the noninferiority margin of -2.5 kg. Weight change differences were comparable at 3 and 12 months and, among nonresponders, at 6 months, with no difference by step-up therapy.

Conclusions and Relevance

A wireless feedback system (Wi-Fi activity tracker and scale with smartphone app to provide daily feedback) was not noninferior to the same system with added coaching. Continued efforts are needed to identify strategies for weight loss management and to accurately select interventions for different individuals to achieve weight loss goals.

Trial Registration

ClinicalTrials.gov Identifier: NCT02997943.

Community engagement through social media: A promising low-cost strategy for rural recruitment?

PURPOSE

For the same reasons that rural telehealth has shown promise for enhancing the provision of care in underserved environments, social media recruitment may facilitate more inclusive research engagement in rural areas. However, little research has examined social media recruitment in the rural context, and few studies have evaluated the feasibility of using a free social media page to build a network of rural community members who may be interested in a research study. Here, we describe the rationale, process, and protocols of developing and implementing a social media approach to recruit rural residents to participate in an mHealth intervention.

METHODS

Informed by extensive formative research, we created a study Facebook page emphasizing community engagement in an mHealth behavioral intervention. We distributed the page to local networks and regularly posted recruitment and community messages. We collected data on the reach of the Facebook page, interaction with our messages, and initiations of our study intake survey.

FINDINGS

Over 21 weeks, our Facebook page gained 429 followers, and Facebook users interacted with our social media messages 3,080 times. Compared to messages that described desirable study features, messages that described community involvement resulted in higher levels of online interaction. Social media and other recruitment approaches resulted in 225 people initiating our in-take survey, 9 enrolling in our pilot study, and 26 placing their names on a waiting list.

CONCLUSIONS

A standalone social media page highlighting community involvement shows promise for recruiting in rural areas.

Effectiveness of DialBetesPlus, a self-management support system for diabetic kidney disease: Randomized controlled trial

We evaluated the effectiveness of a mobile health (mHealth) intervention for diabetic kidney disease patients by conducting a 12-month randomized controlled trial among 126 type 2 diabetes mellitus patients with moderately increased albuminuria (urinary albumin-to-creatinine ratio (UACR): 30-299 mg/g creatinine) recruited from eight clinical sites in Japan. Using a Theory of Planned Behavior (TPB) behavior change theory framework, the intervention provides patients detailed information in order to improve patient control over exercise and dietary behaviors. In addition to standard care, the intervention group received DialBetesPlus, a self-management support system allowing patients to monitor exercise, blood glucose, diet, blood pressure, and body weight via a smartphone application. The primary outcome, change in UACR after 12 months (used as a surrogate measure of renal function), was 28.8% better than the control group's change (P = 0.029). Secondary outcomes also improved in the intervention group, including a 0.32-point better change in HbA1c percentage (P = 0.041). These improvements persisted when models were adjusted to account for the impacts of coadministration of drugs targeting albuminuria (GLP-1 receptor agonists, SGLT-2 inhibitors, ACE inhibitors, and ARBs) (UACR: -32.3% [95% CI: -49.2%, -9.8%] between-group difference in change, P = 0.008). Exploratory multivariate regression analysis suggests that the improvements were primarily due to levels of exercise. This is the first trial to show that a lifestyle intervention via mHealth achieved a clinically-significant improvement in moderately increased albuminuria.

The Effect of a Program to Improve Adherence to the Mediterranean Diet on Cardiometabolic Parameters in 7034 Spanish Workers

BACKGROUND

Cardiovascular and metabolic diseases include a large group of pathologies and constitute one of the most serious chronic health problems facing the 21st century, with high rates of morbidity and mortality worldwide. Unhealthy diets influence the development of these pathologies. The Mediterranean diet can be an important part in the treatment of these diseases. The objective of this study was to assess the effect of a program that aims to increase adherence to the Mediterranean diet on the improvement of different cardiometabolic risk parameters.

METHODS

A prospective intervention study was carried out on 7034 Spanish workers. Prior to the intervention, 22 cardiometabolic risk scales were evaluated. Participants in this study were informed both orally and in writing of the characteristics and benefits of the Mediterranean diet and were given the website of the Ministry of Health, Consumption and Social Welfare of Spain, which provides advice on nutrition. Adherence to the Mediterranean diet was reinforced by sending a monthly SMS to their mobile phones. After six months of follow-up, the 22 risk scales were re-evaluated to assess changes. Means and standard deviations were calculated using Student's t test to analyse quantitative variables. Prevalence was calculated using the Chi-square test when the variables were qualitative.

RESULTS

All the cardiometabolic risk scales studied decreased after implementing a program to improve and enhance adherence to the Mediterranean diet. The number of losses in the sample was very low, standing at 4.31%.

CONCLUSIONS

The Mediterranean diet is effective in reducing all cardiovascular risk scales evaluated. The mean values and prevalence of high values of the different cardiometabolic risk scales analysed led to lower values after the implementation of the program to increase adherence to the Mediterranean diet. We observed a significant positive difference in metabolic age in both sexes. We have obtained a significant improvement in the insulin resistance index, especially in the SPISE-IR index, data that we have not found in previous publications. Easy access to the Internet and new information and communication technologies facilitate adherence to a diet and can reduce the number of losses.

Does breast cancer modify the long-term relationship between lifestyle behaviors and mortality? A prospective analysis of breast cancer survivors and population-based controls

BACKGROUND

Modifiable lifestyle factors are known to impact survival. It is less clear whether this differs between postmenopausal women ever diagnosed with breast cancer and unaffected women.

METHODS

Women diagnosed with breast cancer and unaffected women of comparable age were recruited from 2002 to 2005 and followed up until 2020. Using baseline information, a lifestyle adherence score (range 0-8; categorized as low [0-3.74], moderate [3.75-4.74], and high [≥4.75]) was created based on the 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations. Cox regression and competing risks analysis were used to analyze the association of adherence to WCRF/AICR lifestyle recommendations with overall mortality and with death due to cardiovascular diseases and cancer, respectively.

RESULTS

A total of 8584 women were included (2785 with breast cancer and 5799 without). With a median follow-up of 16.1 years there were 2006 total deaths. Among the deaths of known causes (98.6%), 445 were cardiovascular-related and 1004 were cancer-related. The average lifestyle score was 4.2. There was no differential effect of lifestyle score by case-control status on mortality. After adjusting for covariates, moderate (hazard ratio [HR], 0.66; 95% confidence interval [CI], 0.57-0.76) and high (HR, 0.54; 95% CI, 0.47-0.63) adherence to WCRF/AICR lifestyle recommendations were significantly associated with a decrease in overall mortality. Similarly, in competing risks analysis, moderate and high adherence were associated with decreased mortality from cardiovascular diseases and from cancer.

CONCLUSIONS

A healthy lifestyle can substantially reduce mortality risk in women. With low adherence to all WCRF/AICR guidelines in about a third of study participants, health interventions are warranted.

StandUPTV: Preparation and optimization phases of a mHealth intervention to reduce sedentary screen time in adults

Recreational sedentary screen time (rSST) is the most prevalent sedentary behavior for adults outside of work, school, and sleep, and is strongly linked to poor health. StandUPTV is a mHealth trial that uses the Multiphase Optimization Strategy (MOST) framework to develop and evaluate the efficacy of three theory-based strategies for reducing rSST among adults. This paper describes the preparation and optimization phases of StandUPTV within the MOST framework. We identified three candidate components based on previous literature: (a) rSST electronic lockout (LOCKOUT), which restricts rSST through electronic means; (b) adaptive prompts (TEXT), which provides adaptive prompts based on rSST behaviors; and (c) earning rSST through increased moderate-vigorous physical activity (MVPA) participation (EARN). We also describe the mHealth iterative design process and the selection of an optimization objective. Finally, we describe the protocol of the optimization randomized controlled trial using a 23 factorial experimental design. We will enroll 240 individuals aged 23-64 y who engage in >3 h/day of rSST. All participants will receive a target to reduce rSST by 50% and be randomized to one of 8 combinations representing all components and component levels: LOCKOUT (yes vs. no), TEXT (yes vs. no), and EARN (yes vs. no). Results will support the selection of the components for the intervention package that meet the optimization objective and are acceptable to participants. The optimized intervention will be tested in a future evaluation randomized trial to examine reductions in rSST on health outcomes among adults.

Study protocol of a clinical randomized controlled trial on the efficacy of an innovative Digital thErapy to proMote wEighT loss in patients with obesity by incReasing their Adherence to treatment: the DEMETRA study

Despite the increasing importance of innovative medications and bariatric surgery for the treatment of obesity, lifestyle interventions (diet and physical activity) remain the first-line therapy for this disease. The use of digital devices in healthcare aims to respond to the patient's needs, in order to make obesity treatment more accessible, so our study aims to assess the safety and efficacy of a Digital Therapy for Obesity App (DTxO) for achieving weight loss and its maintenance in patients affected with obesity undergoing an experimental non-pharmacological treatment. Here we present the study protocol of a prospective, multicenter, pragmatic, randomized, double-arm, placebo-controlled, parallel, single-blind study on obese patients who will be treated with a new digital therapy to obtain an improvement in their disease condition through the application of different simultaneous strategies (a dietary regimen and personalized advice program, a tailored physical exercise program, a cognitive-behavioural assessment and program, alerts and reminders, dedicated section on prescribed drugs intake, and chat and online visits with clinical professionals). We believe that DTxO will offer a promising intervention channel and self-regulation tool holding the potentiality to decrease treatment burden and treat more patients thanks to the partial replacement of traditional medical consultation with digital or telephone management, improving self- engagement and reducing the high demands the "obesity pandemic" for both patients and national health services in terms of time, cost, and effort. Clinical trial registration: clinicaltrials.gov, identifier, NCT05394779.

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.

Moderators of a Diet and Physical Activity Intervention: who Responds Best to Sequential vs. Simultaneous Approaches

BACKGROUND

Given that low physical activity levels and poor dietary intake are co-occurring risk factors for chronic disease, there is a need for interventions that target both health behaviors, either sequentially or simultaneously. Little is known about participant characteristics that are associated with better or worse response to sequential and simultaneous interventions.

METHOD

The 12-month Counseling Advice for Lifestyle Management (CALM) randomized trial (N = 150; Mage = 55.3 years) targeted these two behaviors either via a sequential approach - dietary advice first then exercise advice added ("Diet-First") or exercise advice first then dietary advice added ("Exercise-First") - or via a simultaneous approach. The objective was to examine demographic, clinical, and psychosocial moderators of intervention effects on 12-month change in (1) moderate-to-vigorous physical activity (MVPA), (2) fruit/vegetable intake, (3) caloric intake from saturated fat, and (4) weight. Hierarchical regressions first compared Diet-First to Exercise-First, followed by comparisons of these arms combined ("sequential") to the simultaneous arm.

RESULTS

Older age, higher baseline BMI, and lower social support were associated with higher MVPA in Exercise-First vs. Diet-First, while lower tangible support was associated with higher fruit/vegetable intake in Exercise-First but not in Diet-First. Poor sleep was associated with higher levels of MVPA in the sequential arm than in the simultaneous arm. Lower vitality was associated with greater weight loss in the sequential arm than in the simultaneous arm, while the opposite was true for those who were not married.

CONCLUSION

Identifying moderators of treatment response can allow the behavioral medicine field to enhance intervention efficacy by matching participant subgroups to their best-fitting interventions.

TRIAL REGISTRATION

NCT00131105.

Study Design, Rationale, and Methodology for Promote Weight Loss in Patients With Peripheral Artery Disease Who Also Have Obesity: The PROVE Trial

Background Overweight and obesity are associated with adverse functional outcomes in people with peripheral artery disease (PAD). The effects of weight loss in people with overweight/obesity and PAD are unknown. Methods The PROVE (Promote Weight Loss in Obese PAD Patients to Prevent Mobility Loss) Trial is a multicentered randomized clinical trial with the primary aim of testing whether a behavioral intervention designed to help participants with PAD lose weight and walk for exercise improves 6-minute walk distance at 12-month follow-up, compared with walking exercise alone. A total of 212 participants with PAD and body mass index ≥25 kg/m2 will be randomized. Interventions are delivered using a Group Mediated Cognitive Behavioral intervention model, a smartphone application, and individual telephone coaching. The primary outcome is 12-month change in 6-minute walk distance. Secondary outcomes include total minutes of walking exercise/wk at 12-month follow-up and 12-month change in accelerometer-measured physical activity, the Walking Impairment Questionnaire distance score, and the Patient-Reported Outcomes Measurement Information System mobility questionnaire. Tertiary outcomes include 12-month changes in perceived exertional effort at the end of the 6-minute walk, diet quality, and the Short Physical Performance Battery. Exploratory outcomes include changes in gastrocnemius muscle biopsy measures of mitochondrial cytochrome C oxidase activity, mitochondrial biogenesis, capillary density, and inflammatory markers. Conclusions The PROVE randomized clinical trial will evaluate the effects of exercise with an intervention of coaching and a smartphone application designed to achieve weight loss, compared with exercise alone, on walking performance in people with PAD and overweight/obesity. Results will inform optimal treatment for the growing number of patients with PAD who have overweight/obesity. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT04228978.

A systematic review of behaviour change techniques used in the context of stillbirth prevention

BACKGROUND

Stillbirth is one of the most devastating pregnancy outcomes that families can experience. Previous research has associated a wide range of risk factors with stillbirth, including maternal behaviours such as substance use, sleep position and attendance and engagement with antenatal care. Hence, some preventive efforts have been focused on tackling the behavioural risk factors for stillbirth. This study aimed to identify the Behaviour Change Techniques (BCTs) used in behaviour change interventions tacking behavioural risk factors for stillbirth such as substance use, sleep position, unattendance to antenatal care and weight management.

STUDY DESIGN

A systematic review of the literature was conducted in June 2021 and updated in November 2022 in five databases: CINHAL, Psyhinfo, SociIndex, PubMed and Web of Science. Studies published in high-income countries describing interventions designed in the context of stillbirth prevention, reporting stillbirth rates and changes in behaviour were eligible for inclusion. BCTs were identified using the Behaviour Change Technique Taxonomy v1.

RESULTS

Nine interventions were included in this review identified in 16 different publications. Of these, 4 interventions focused on more than one behaviour (smoking, monitoring fetal movements, sleep position, care-seeking behaviours), one focused on smoking, three on monitoring fetal movements and one on sleep position. Twenty-seven BCTs were identified across all interventions. The most commonly used was "Information about health consequences" (n = 7/9) followed by "Adding objects to the environment" (n = 6/9). One of the interventions included in this review has not been assessed for efficacy yet, of the remaining eight, three showed results in the reduction of stillbirth rates. and four interventions produced behaviour change (smoking reductions, increased knowledge, reduced supine sleeping time).

CONCLUSIONS

Our findings suggest that interventions designed to date have limited effects on the rates of stillbirth and utilise a limited number of BCTs which are mostly focused on information provision. Further research is necessary to design evidence base behaviour change interventions with a greater focus to tackle all the other factors influencing behaviour change during pregnancy (e.g.: social influence, environmental barriers).

Effect of using mobile phone communication on dietary management of Type 2 Diabetes Mellitus patients in Kenya

Purpose

Advancements in management of non-communicable diseases using regular reminders on lifestyle and dietary behaviors have been effectively achieved using mobile phones. This study evaluates the effects of regular communication using a mobile phone on dietary management of Type 2 Diabetes Mellitus (T2DM) among patients attending Kitui County Referral Hospital (KCRH) in Kenya.

Methods

Pre/post-study design among eligible and consenting T2DM patients visiting KCRH was used for this study. One hundred and thirty-eight T2DM patients were enrolled; 67 in the intervention group (IG) and 71 in the control group (CG). The IG received regular reminders on key dietary practices through their mobile phones for six months while the CG did not. The Net Effect of Intervention (NEI) and bivariate logistic regression were used to determine the impact of mobile phone communication intervention at p < 0.05. SPSS version 24 was used to analyze the data.

Results

The results revealed an increase of respondents who adhered to the meal plan in the IG from 47.8% to 59.7% compared to a decrease from 49.3% to 45.1% in CG with corresponding NEI increasing (16.1%) significantly (p < 0.05). The proportion of respondents with an increased frequency of meals increased from 41.8 to 47.8% in the IG compared to a reduction from 52.1% to 45.1% in the CG with corresponding NEI increasing (13.0%) significantly (p < 0.05).

Conclusion

Regular reminders on lifestyle and dietary behaviors using mobile phone communication improved adherence to dietary practices such as meal planning and frequency of meals in the management of T2DM.

Will they or won't they? Understanding New Zealand adults' attitudes towards using digital interventions

Background

Digital interventions deliver healthcare via the internet or smartphone application to support people's well-being and health. Yet uptake is relatively poor. Furthermore, several studies exploring attitudes towards digital interventions have found inconsistent attitudes. In addition to this, regional and cultural nuances may further influence attitudes to digital interventions.

Objective

This study aimed to understand New Zealand adults' attitudes towards digital interventions and their influences.

Results

A mixed-method design consisting of a cross-sectional survey and semi-structured interviews found that New Zealand adults hold varied and complex attitudes towards digital interventions. Attitudes were found to be influenced by group membership and the scenarios in which digital interventions are made available. In addition, beliefs about the benefits and concerns surrounding digital interventions, knowledge, perceived views of others, and previous experience and confidence influenced these attitudes.

Conclusions

Findings indicated that digital interventions would be acceptable if offered as part of the healthcare service rather than a standalone intervention. Key modifiable factors that could positively influence attitudes were identified and could be leveraged to increase the perceived acceptability of digital interventions.

Dietary Intervention on Overweight and Obesity after Confinement by COVID-19

BACKGROUND

Obesity has become a public health problem in our society and is associated with many diseases, including type 2 diabetes mellitus, cardiovascular diseases, dyslipidemia, respiratory diseases, and cancer. Several studies relate weight loss in obese patients to improved anthropometric measurements and cardiometabolic risk. The objective of our study was to evaluate anthropometric changes, analytical parameters, insulin resistance, fatty liver, and metabolic scales, after a personalized weight loss program, through dietary advice to increase adherence to the Mediterranean diet and a motivational booster via mobile SMS messaging.

METHODS

Intervention study on a sample of 1964 workers, in which different anthropometric parameters were evaluated before and after dietary intervention: the metabolic score of insulin resistance; non-alcoholic fatty liver disease using different scales; metabolic syndrome; atherogenic dyslipidemia; and the cardiometabolic index. A descriptive analysis of the categorical variables was performed, by calculating the frequency and distribution of the responses for each one. For quantitative variables, the mean and standard deviation were calculated, since they followed a normal distribution. Bivariate association analysis was performed by applying the chi-squared test (corrected by Fisher's exact statistic when conditions required it) and Student's t-test for independent samples (for comparison of means).

RESULTS

The population subjected to the Mediterranean diet improved in all the variables evaluated at 12 months of follow-up and compliance with the diet.

CONCLUSIONS

Dietary advice on a Mediterranean diet and its reinforcement with reminder messages through the use of mobile phones may be useful to improve the parameters evaluated in this study and reduce the cardiometabolic risk of patients.

Virtual Behavioral Intervention to Promote Healthy Lifestyle Behaviors: A Feasibility RCT during COVID-19 Pandemic

BACKGROUND

the COVID-19 pandemic has had a substantial impact on human health, affecting many lifestyle behaviors such as physical activity, sedentary behavior, dietary habits and sleep.

PURPOSE

to assess the feasibility of six sessions of a virtual behavioral intervention to promote healthy lifestyle practices during a stay-at-home advisory phase of the COVID-19 pandemic.

METHODS

A participant-blinded randomized controlled trial was performed through a virtual platform setting. Participants were randomly assigned into two groups. They were assigned to a motivational interviewing (MI) intervention or attention group, with pre- and postintervention assessments. The MI treatment consisted of six sessions (twice each week). The same number of virtual structured sessions were provided for the attention group, and they provided brief advice to promote healthy lifestyles. The study was conducted from April to June 2020.

RESULTS

The feasibility outcomes indicated that 39 of the 50 participants (78%) completed the trial. The dropout rate was 21.7% for the attention group and 22.2% for the intervention group. Participating in MI had a significant positive interventional effect on physical activity level, distress and fear of COVID-19.

CONCLUSIONS

It is feasible to deliver behavioral change interventions virtually. Further, MI can be used as a useful strategy for the favorable promotion of a healthy lifestyle.

TRIAL REGISTRATION

NCT05392218 (26/05/2022).

Characteristics of smartphone-based dietary assessment tools: a systematic review

Smartphones have become popular in assessing eating behaviour in real-life and real-time. This systematic review provides a comprehensive overview of smartphone-based dietary assessment tools, focusing on how dietary data is assessed and its completeness ensured. Seven databases from behavioural, social and computer science were searched in March 2020. All observational, experimental or intervention studies and study protocols using a smartphone-based assessment tool for dietary intake were included if they reported data collected by adults and were published in English. Out of 21,722 records initially screened, 117 publications using 129 tools were included. Five core assessment features were identified: photo-based assessment (48.8% of tools), assessed serving/ portion sizes (48.8%), free-text descriptions of food intake (42.6%), food databases (30.2%), and classification systems (27.9%). On average, a tool used two features. The majority of studies did not implement any features to improve completeness of the records. This review provides a comprehensive overview and framework of smartphone-based dietary assessment tools to help researchers identify suitable assessment tools for their studies. Future research needs to address the potential impact of specific dietary assessment methods on data quality and participants' willingness to record their behaviour to ultimately improve the quality of smartphone-based dietary assessment for health research.

Long-Term Effectiveness of a Smartphone App and a Smart Band on Arterial Stiffness and Central Hemodynamic Parameters in a Population with Overweight and Obesity (Evident 3 Study): Randomised Controlled Trial

BACKGROUND

mHealth technologies could help to improve cardiovascular health; however, their effect on arterial stiffness and hemodynamic parameters has not been explored to date.

OBJECTIVE

To evaluate the effect of a mHealth intervention, at 3 and 12 months, on arterial stiffness and central hemodynamic parameters in a sedentary population with overweight and obesity.

METHODS

Randomised controlled clinical trial (Evident 3 study). 253 subjects were included: 127 in the intervention group (IG) and 126 in the control group (CG). The IG subjects were briefed on the use of the Evident 3 app and a smart band (Mi Band 2, Xiaomi) for 3 months to promote healthy lifestyles. All measurements were recorded in the baseline visit and at 3 and 12 months. The carotid-femoral pulse wave velocity (cfPWV) and the central hemodynamic parameters were measured using a SphigmoCor System^® device, whereas the brachial-ankle pulse wave velocity (baPWV) and the Cardio Ankle Vascular Index (CAVI) were measured using a VaSera VS-2000^® device.

RESULTS

Of the 253 subjects who attended the initial visit, 237 (93.7%) completed the visit at 3 months of the intervention, and 217 (85.3%) completed the visit at 12 months of the intervention. At 12 months, IG showed a decrease in peripheral augmentation index (PAIx) (-3.60; 95% CI -7.22 to -0.00) and ejection duration (ED) (-0.82; 95% CI -1.36 to -0.27), and an increase in subendocardial viability ratio (SEVR) (5.31; 95% CI 1.18 to 9.44). In CG, cfPWV decreased at 3 months (-0.28 m/s; 95% CI -0.54 to -0.02) and at 12 months (-0.30 m/s, 95% CI -0.54 to -0.05), central diastolic pressure (cDBP) decreased at 12 months (-1.64 mm/Hg; 95% CI -3.19 to -0.10). When comparing the groups we found no differences between any variables analyzed.

CONCLUSIONS

In sedentary adults with overweight or obesity, the multicomponent intervention (Smartphone app and an activity-tracking band) for 3 months did not modify arterial stiffness or the central hemodynamic parameters, with respect to the control group. However, at 12 months, CG presented a decrease of cfPWV and cDBP, whereas IG showed a decrease of PAIx and ED and an increase of SEVR.

Adaptation and study protocol of the evidence-based Make Better Choices (MBC2) multiple diet and activity change intervention for a rural Appalachian population

BACKGROUND

Rural Appalachian residents experience among the highest prevalence of chronic disease, premature mortality, and decreased life expectancy in the nation. Addressing these growing inequities while avoiding duplicating existing programming necessitates the development of appropriate adaptations of evidence-based lifestyle interventions. Yet few published articles explicate how to accomplish such contextual and cultural adaptation.

METHODS

In this paper, we describe the process of adapting the Make Better Choices 2 (MBC2) mHealth diet and activity randomized trial and the revised protocol for intervention implementation in rural Appalachia. Deploying the NIH's Cultural Framework on Health and Aaron's Adaptation framework, the iterative adaptation process included convening focus groups (N = 4, 38 participants), conducting key informant interviews (N = 16), verifying findings with our Community Advisory Board (N = 9), and deploying usability surveys (N = 8), wireframing (N = 8), and pilot testing (N = 9. This intense process resulted in a comprehensive revision of recruitment, retention, assessment, and intervention components. For the main trial, 350 participants will be randomized to receive either the multicomponent MBC2 diet and activity intervention or an active control condition (stress and sleep management). The main outcome is a composite score of four behavioral outcomes: two outcomes related to diet (increased fruits and vegetables and decreased saturated fat intake) and two related to activity (increased moderate vigorous physical activity [MVPA] and decreased time spent on sedentary activities). Secondary outcomes include change in biomarkers, including blood pressure, lipids, A1C, waist circumference, and BMI.

DISCUSSION

Adaptation and implementation of evidence-based interventions is necessary to ensure efficacious contextually and culturally appropriate health services and programs, particularly for underserved and vulnerable populations. This article describes the development process of an adapted, community-embedded health intervention and the final protocol created to improve health behavior and, ultimately, advance health equity.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier NCT04309461. The trial was registered on 6/3/2020.

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.

Innovations in Cardio-oncology Resulting from the COVID-19 Pandemic

The COVID pandemic has transformed our approach to patient care, research, and training in cardio-oncology. While the early phases of the COVID pandemic were exceptionally frightening, we now can reflect on the innovative changes that brought more effective and patient-centered care to our doorsteps: expansion of telemedicine, integration of digital health, wider adoption of cardiac biomarkers, consolidation, and coordination of cardio-oncology testing. Normally, it takes years for health care systems to adopt new technology or modify patient care pathways; however, COVID pushed healthcare providers and the health systems to change at warp speed. All of these innovations have improved our efficacy and provided a more “patient-centered” approach for our cardio-oncology patients. The changes we have made in cardio-oncology will likely remain well beyond the pandemic and continue to grow improving the cardiovascular care of oncology patients.

Behavioral Counseling Interventions to Promote a Healthy Diet and Physical Activity for Cardiovascular Disease Prevention in Adults Without Known Cardiovascular Disease Risk Factors: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

IMPORTANCE

Unhealthful dietary patterns, low levels of physical activity, and high sedentary time increase the risk of cardiovascular disease.

OBJECTIVE

To synthesize the evidence on benefits and harms of behavioral counseling interventions to promote a healthy diet and physical activity in adults without known cardiovascular disease (CVD) risk factors to inform a US Preventive Services Task Force recommendation.

DATA SOURCES

MEDLINE, PsycINFO, and the Cochrane Central Register of Controlled Trials through February 2021, with ongoing surveillance through February 2022.

STUDY SELECTION

Randomized clinical trials (RCTs) of behavioral counseling interventions targeting improved diet, increased physical activity, or decreased sedentary time among adults without known elevated blood pressure, elevated lipid levels, or impaired fasting glucose.

DATA EXTRACTION AND SYNTHESIS

Independent data abstraction and study quality rating and random effects meta-analysis.

MAIN OUTCOMES AND MEASURES

CVD events, CVD risk factors, diet and physical activity measures, and harms.

RESULTS

One-hundred thirteen RCTs were included (N = 129 993). Three RCTs reported CVD-related outcomes: 1 study (n = 47 179) found no significant differences between groups on any CVD outcome at up to 13.4 years of follow-up; a combined analysis of the other 2 RCTs (n = 1203) found a statistically significant association of the intervention with nonfatal CVD events (hazard ratio, 0.27 [95% CI, 0.08 to 0.88]) and fatal CVD events (hazard ratio, 0.31 [95% CI, 0.11 to 0.93]) at 4 years. Diet and physical activity behavioral counseling interventions were associated with small, statistically significant reductions in continuous measures of blood pressure (systolic mean difference, -0.8 [95% CI, -1.3 to -0.3]; 23 RCTs [n = 57 079]; diastolic mean difference, -0.4 [95% CI, -0.8 to -0.0]; 24 RCTs [n = 57 148]), low-density lipoprotein cholesterol level (mean difference, 2.2 mg/dL [95% CI, -3.8 to -0.6]; 15 RCTs [n = 6350]), adiposity-related outcomes (body mass index mean difference, -0.3 [95% CI, -0.5 to -0.1]; 27 RCTs [n = 59 239]), dietary outcomes, and physical activity at 6 months to 1.5 years of follow-up vs control conditions. There was no evidence of greater harm among intervention vs control groups.

CONCLUSIONS AND RELEVANCE

Healthy diet and physical activity behavioral counseling interventions for persons without a known risk of CVD were associated with small but statistically significant benefits across a variety of important intermediate health outcomes and small to moderate effects on dietary and physical activity behaviors. There was limited evidence regarding the long-term health outcomes or harmful effects of these interventions.

Measurement of Adherence to mHealth Physical Activity Interventions and Exploration of the Factors That Affect the Adherence: Scoping Review and Proposed Framework

BACKGROUND

Mobile health (mHealth) is widely used as an innovative approach to delivering physical activity (PA) programs. Users' adherence to mHealth programs is important to ensure the effectiveness of mHealth-based programs.

OBJECTIVE

Our primary aim was to review the literature on the methods used to assess adherence, factors that could affect users' adherence, and the investigation of the association between adherence and health outcomes. Our secondary aim was to develop a framework to understand the role of adherence in influencing the effectiveness of mHealth PA programs.

METHODS

MEDLINE, PsycINFO, EMBASE, and CINAHL databases were searched to identify studies that evaluated the use of mHealth to promote PA in adults aged ≥18 years. We used critical interpretive synthesis methods to summarize the data collected.

RESULTS

In total, 54 papers were included in this review. We identified 31 specific adherence measurement methods, which were summarized into 8 indicators; these indicators were mapped to 4 dimensions: length, breadth, depth, and interaction. Users' characteristics (5 factors), technology-related factors (12 factors), and contextual factors (1 factor) were reported to have impacts on adherence. The included studies reveal that adherence is significantly associated with intervention outcomes, including health behaviors, psychological indicators, and clinical indicators. A framework was developed based on these review findings.

CONCLUSIONS

This study developed an adherence framework linking together the adherence predictors, comprehensive adherence assessment, and clinical effectiveness. This framework could provide evidence for measuring adherence comprehensively and guide further studies on adherence to mHealth-based PA interventions. Future research should validate the utility of this proposed framework.

Short-Term Pilot Study to Evaluate the Impact of Salbi Educa Nutrition App in Macronutrients Intake and Adherence to the Mediterranean Diet: Randomized Controlled Trial

Promoting a healthy diet is a relevant strategy for preventing non-communicable diseases. This study aims to evaluate the impact of an innovative tool, the SAlBi educa nutrition app, in primary healthcare dietary counseling to improve dietary profiles as well as adherence to the Mediterranean diet. A multi-center randomized control trial comprising 104 participants was performed. Both control (n = 49) and intervention (n = 55) groups attended four once-weekly sessions focusing on healthy eating habits and physical activity, over one month. As well as attending the meetings, the intervention group used the app, which provides self-monitoring and tailored dietary advice based on the Mediterranean diet model. In a second intervention (one arm trial), the potential of SAlBi educa was evaluated for three months during the COVID-19 pandemic. At 4 weeks, the intervention group had significantly increased their carbohydrate intake (7.7% (95% CI: 0.16 to 15.2)) and decreased their total fat intake (−5.7% (95% CI: −10.4 to −1.15)) compared to the control group. Significant differences were also found for carbohydrates (3.5% (95% CI: −1.0 to 5.8)), total fats (−5.9% (95% CI: −8.9 to −3.0)), fruits and vegetables (266.3 g/day (95% CI: 130.0 to 402.6)), legumes (7.7g/day (95% CI: 0.2 to 15.1)), starchy foods (36.4 g/day (95% CI: 1.1 to 71.7)), red meat (−17.5 g/day (95% CI: −34.0 to −1.1)), and processed meat (−6.6 g/day (95% CI: −13.1 to −0.1)) intakes during the COVID-19 pandemic. SAlBi educa is a useful tool to support nutrition counseling in primary healthcare, including in special situations such as the COVID-19 pandemic. Trial registration: ISRCTN57186362.

Clinical Outcomes Among Working Adults Using the Health Integrator Smartphone App: Analyses of Prespecified Secondary Outcomes in a Randomized Controlled Trial

Background

There is a need to find new methods that can enhance the individuals’ engagement in self-care and increase compliance to a healthy lifestyle for the prevention of noncommunicable diseases and improved quality of life. Mobile health (mHealth) apps could provide large-scale, cost-efficient digital solutions to implement lifestyle change, which as a corollary may enhance quality of life.

Objective

Here we evaluate if the use of a smartphone-based self-management system, the Health Integrator app, with or without telephone counseling by a health coach, had an effect on clinical variables (secondary outcomes) of importance for noncommunicable diseases.

Methods

The study was a 3-armed parallel randomized controlled trial. Participants were randomized to a control group or to 1 of 2 intervention groups using the Health Integrator app with or without additional telephone counseling for 3 months. Clinical variables were assessed before the start of the intervention (baseline) and after 3 months. Due to the nature of the intervention, targeting lifestyle changes, participants were not blinded to their allocation. Robust linear regression with complete case analysis was performed to study the intervention effect among the intervention groups, both in the entire sample and stratifying by type of work (office worker vs bus driver) and sex.

Results

Complete data at baseline and follow-up were obtained from 205 and 191 participants, respectively. The mean age of participants was 48.3 (SD 10) years; 61.5% (126/205) were men and 52.2% (107/205) were bus drivers. Improvements were observed at follow-up among participants in the intervention arms. There was a small statistically significant effect on waist circumference (β=–0.97, 95% CI –1.84 to –0.10) in the group receiving the app and additional coach support compared to the control group, but no other statistically significant differences were seen. However, participants receiving only the app had statistically significantly lower BMI (β=–0.35, 95% CI –0.61 to –0.09), body weight (β=–1.08, 95% CI –1.92 to –0.26), waist circumference (β=–1.35, 95% CI –2.24 to –0.45), and body fat percentage (β=–0.83, 95% CI –1.65 to –0.02) at follow-up compared to the controls. There was a statistically significant difference in systolic blood pressure between the two intervention groups at follow-up (β=–3.74, 95% CI –7.32 to –0.16); no other statistically significant differences in outcome variables were seen.

Conclusions

Participants randomized to use the Health Integrator smartphone app showed small but statistically significant differences in body weight, BMI, waist circumference, and body fat percentage compared to controls after a 3-month intervention. The effect of additional coaching together with use of the app is unclear.

Trial Registration

ClinicalTrials.gov NCT03579342; https://clinicaltrials.gov/ct2/show/NCT03579342

International Registered Report Identifier (IRRID)

RR2-10.1186/s12889-019-6595-6

Six-month outcomes of the HOPE smartphone application designed to support treatment with medications for opioid use disorder and piloted during an early statewide COVID-19 lockdown

Background

Morbidity and mortality related to opioid use disorder (OUD) in the U.S. is at an all-time high. Innovative approaches are needed to address gaps in retention in treatment with medications for opioid use disorder (MOUD). Mobile health (mHealth) approaches have shown improvement in engagement in care and associated clinical outcomes for a variety of chronic diseases, but mHealth tools designed specifically to support patients treated with MOUD are limited.

Methods

Following user-centered development and testing phases, a multi-feature smartphone application called HOPE (Heal. Overcome. Persist. Endure) was piloted in a small cohort of patients receiving MOUD and at high risk of disengagement in care at an office-based opioid treatment (OBOT) clinic in Central Virginia. Outcomes were tracked over a six-month period following patient enrollment. They included retention in care at the OBOT clinic, usage of various features of the application, and self-rated measures of mental health, substance use, treatment and recovery.

Results

Of the 25 participants in the HOPE pilot study, a majority were retained in care at 6 months (56%). Uptake of bi-directional features including messaging with providers and daily check-ins of mood, stress and medication adherence peaked at one month, and usage persisted through the sixth month. Patients who reported that distance to clinic was a problem at baseline had higher loss to follow up compared to those without distance as a reported barrier (67% vs 23%, p = 0.03). Patients lost to in-person clinic follow up continued to engage with one or more app features, indicating that mHealth approaches may bridge barriers to clinic visit attendance. Participants surveyed at baseline and 6 months (N = 16) scored higher on scales related to overall self-control and self-efficacy related to drug abstinence.

Conclusions

A pilot study of a novel multi-feature smartphone application to support OUD treatment showed acceptable retention in care and patient usage at 6 months. Further study within a larger population is needed to characterize ‘real world’ uptake and association with outcomes related to retention in care, relapse prevention, and opioid-associated mortality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13722-022-00296-4.

Long-term Effectiveness of a Smartphone App Combined With a Smart Band on Weight Loss, Physical Activity, and Caloric Intake in a Population With Overweight and Obesity (Evident 3 Study): Randomized Controlled Trial

BACKGROUND

Multicomponent mobile health approaches can improve lifestyle intervention results, although little is known about their long-term effectiveness.

OBJECTIVE

This study aims to evaluate the long-term effectiveness (12 months) of a multicomponent mobile health intervention-combining a smartphone app, an activity tracker wristband, and brief counseling, compared with a brief counseling group only-on weight loss and improving body composition, physical activity, and caloric intake in Spanish sedentary adults with overweight or obesity.

METHODS

We conducted a randomized controlled, multicenter clinical trial (Evident 3). A total of 650 participants were recruited from 5 primary care centers, with 318 participants in the intervention group (IG) and 332 in the control group (CG). All participants were briefly counseled about a healthy diet and physical activity at the baseline visit. For the 3-month intervention period, the IG received training to use the app to promote healthy lifestyles and the smart band (Mi Band 2, Xiaomi). All measurements were performed at baseline and at 3 and 12 months. Physical activity was measured using the International Physical Activity Questionnaire-Short Form. Nutritional habits were assessed using the Food Frequency Questionnaire and Adherence to Mediterranean diet questionnaire.

RESULTS

Of the 650 participants included, 563 (86.6%) completed the 3-month visit and 443 (68.2%) completed the 12-month visit. After 12 months, the IG showed net differences in weight (-0.26, 95% CI -1.21 to 0.70 kg; P=.02), BMI (-0.06, 95% CI -0.41 to 0.28 points; P=.01), waist-height ratio (-0.25, 95% CI -0.94 to 0.44; P=.03), body adiposity index (-0.33, 95% CI -0.77 to 0.11; P=.03), waist circumference (-0.48, 95% CI -1.62 to 0.66 cm, P=.04) and hip circumference (-0.69, 95% CI -1.62 to 0.25 cm; P=.03). Both groups lowered daily caloric intake and increased adherence to the Mediterranean diet, with no differences between the groups. The IG increased light physical activity time (32.6, 95% CI -30.3 to 95.04 min/week; P=.02) compared with the CG. Analyses by subgroup showed changes in body composition variables in women, people aged >50 years, and married people.

CONCLUSIONS

The low-intensity intervention of the Evident 3 study showed, in the IG, benefits in weight loss, some body composition variables, and time spent in light physical activity compared with the CG at 3 months, but once the devices were collected, the downward trend was not maintained at the 12-month follow-up. No differences in nutritional outcomes were observed between the groups.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03175614; https://clinicaltrials.gov/ct2/show/NCT03175614.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1097/MD.0000000000009633.

Digitally characterizing the dynamics of multiple health behavior change

OBJECTIVE

We applied the ORBIT model to digitally define dynamic treatment pathways whereby intervention improves multiple risk behaviors. We hypothesized that effective intervention improves the frequency and consistency of targeted health behaviors and that both correlate with automaticity (habit) and self-efficacy (self-regulation).

METHOD

Study 1: Via location scale mixed modeling we compared effects when hybrid mobile intervention did versus did not target each behavior in the Make Better Choices 1 (MBC1) trial (n = 204). Participants had all of four risk behaviors: low moderate-vigorous physical activity (MVPA) and fruit and vegetable consumption (FV), and high saturated fat (FAT) and sedentary leisure screen time (SED). Models estimated the mean (location), between-subjects variance, and within-subject variance (scale).

RESULTS

Treatment by time interactions showed that location increased for MVPA and FV (Bs = 1.68, .61; ps < .001) and decreased for SED and FAT (Bs = -2.01, -.07; ps < .05) more when treatments targeted the behavior. Within-subject variance modeling revealed group by time interactions for scale (taus = -.19, -.75, -.17, -.11; ps < .001), indicating that all behaviors grew more consistent when targeted.

METHOD

Study 2: In the MBC2 trial (n = 212) we examined correlations between location, scale, self-efficacy, and automaticity for the three targeted behaviors.

RESULTS

For SED, higher scale (less consistency) but not location correlated with lower self-efficacy (r = -.22, p = .014) and automaticity (r = -.23, p = .013). For FV and MVPA, higher location, but not scale, correlated with higher self-efficacy (rs = .38, .34, ps < .001) and greater automaticity (rs = .46, .42, ps < .001).

CONCLUSIONS

Location scale mixed modeling suggests that both habit and self-regulation changes probably accompany acquisition of complex diet and activity behaviors. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Self-regulatory behaviour change techniques in interventions to promote healthy eating, physical activity, or weight loss: a meta-review

Poor quality diet, physical inactivity, and obesity are prevalent, covariant risk factors for chronic disease, suggesting that behaviour change techniques (BCTs) that effectively change one risk factor might also improve the others. To examine that question, registered meta-review CRD42019128444 synthesised evidence from 30 meta-analyses published between 2007 and 2017 aggregating data from 409,185 participants to evaluate whether inclusion of 14 self-regulatory BCTs in health promotion interventions was associated with greater improvements in outcomes. Study populations and review quality varied, with minimal overlap among summarised studies. AMSTAR-2 ratings averaged 37.31% (SD = 16.21%; range 8.33-75%). All BCTs were examined in at least one meta-analysis; goal setting and self-monitoring were evaluated in 18 and 20 reviews, respectively. No BCT was consistently related to improved outcomes. Although results might indicate that BCTs fail to benefit diet and activity self-regulation, we suggest that a Type 3 error occurred, whereby the meta-analytic research design implemented to analyse effects of multi-component intervention trials designed for a different purpose was mismatched to the question of how BCTs affect health outcomes. An understanding of independent and interactive effects of individual BCTs on different health outcomes and populations is needed urgently to ground a cumulative science of behaviour change.

Challenges in Participant Engagement and Retention using Mobile Health Apps: A Literature Review (Preprint)

Background

Mobile health (mHealth) apps are revolutionizing the way clinicians and researchers monitor and manage the health of their participants. However, many studies using mHealth apps are hampered by substantial participant dropout or attrition, which may impact the representativeness of the sample and the effectiveness of the study. Therefore, it is imperative for researchers to understand what makes participants stay with mHealth apps or studies using mHealth apps.

Objective

This study aimed to review the current peer-reviewed research literature to identify the notable factors and strategies used in adult participant engagement and retention.

Methods

We conducted a systematic search of PubMed, MEDLINE, and PsycINFO databases for mHealth studies that evaluated and assessed issues or strategies to improve the engagement and retention of adults from 2015 to 2020. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Notable themes were identified and narratively compared among different studies. A binomial regression model was generated to examine the factors affecting retention.

Results

Of the 389 identified studies, 62 (15.9%) were included in this review. Overall, most studies were partially successful in maintaining participant engagement. Factors related to particular elements of the app (eg, feedback, appropriate reminders, and in-app support from peers or coaches) and research strategies (eg, compensation and niche samples) that promote retention were identified. Factors that obstructed retention were also identified (eg, lack of support features, technical difficulties, and usefulness of the app). The regression model results showed that a participant is more likely to drop out than to be retained.

Conclusions

Retaining participants is an omnipresent challenge in mHealth studies. The insights from this review can help inform future studies about the factors and strategies to improve participant retention.

Behavior Change Techniques and the Effects Associated With Digital Behavior Change Interventions in Sedentary Behavior in the Clinical Population: A Systematic Review

Background: Sedentary behavior (SB) negatively impact health and is highly prevalent in the population. Digital behavior change interventions (DBCIs) have been developed to modify behaviors such as SB by technologies. However, it is unknown which behavior change techniques (BCTs) are most frequently employed in SB as well as the effect associated with DBCIs in this field. The aim of this systematic review was: (a) to evaluate the BCT most frequently employed in digital health including all technologies available and interventions aimed at increasing physical activity (PA), reducing sedentary time, and improving adherence to exercise in the clinical population, and (b) to review the effect associated with DBCIs in this field. Methods: The database used was Medline, as well as Scopus, Scielo, and Google Scholar. For the search strategy, we considered versions of behavior/behavioral, mHealth/eHealth/telemedicine/serious game/gamification. The terms related to PA and SB were included, the criteria for inclusion were randomized clinical trials (RCTs), adults, intervention based on digital media, and outcome variable lifestyle modification; a last 5 years filter was included. Michie's Taxonomy was used to identify BCTs. The study was registered under the number PROSPERO CRD42019138681. Results: Eighteen RCTs were included in the present systematic review, 5 of them healthy adults, and 13 of them with some illness. Studies included 2298 sedentary individuals who were followed up for 5 weeks-3 years. The most used BCTs were goal setting, problem solving, review outcomes/goals, feedback on behavior and outcomes of behavior, self-monitoring of behavior, social support, information about health consequences, and behavior practice/rehearsal. The effect associated with DBCIs showed improvements, among several related to PA and physiologic self-reported and anthropometric outcomes. Conclusion: The BCTs most used in digital health to change outcomes related to SB were goals and planning, feedback and monitoring, social support, natural consequences, repetition, and substitution. Besides these findings, DBCIs are influenced by several factors like the type of intervention, patients' preferences and values, or the number of BCTs employed. More research is needed to determine with precision which DBCIs or BCTs are the most effective to reduce SB in the clinical population.

Effect of a Telecare Case Management Program for Older Adults Who Are Homebound During the COVID-19 Pandemic: A Pilot Randomized Clinical Trial

IMPORTANCE

Older adults who are homebound can be difficult to reach owing to their functional limitations and social distancing during the COVID-19 pandemic, leaving their health needs unrecognized at an earlier stage.

OBJECTIVE

To determine the effectiveness of a telecare case management program for older adults who are homebound during the COVID-19 pandemic.

DESIGN, SETTING, AND PARTICIPANTS

This randomized clinical trial was conducted among 68 older adults in Hong Kong from May 21 to July 20, 2020, with a last follow-up date of October 20, 2020. Inclusion criteria were being 60 years or older, owning a smartphone, and going outside less than once a week in the previous 6 months.

INTERVENTIONS

Participants in the telecare group received weekly case management from a nurse supported by a social service team via telephone call and weekly video messages covering self-care topics delivered via smartphone for 3 months. Participants in the control group received monthly social telephone calls.

MAIN OUTCOMES AND MEASURES

The primary outcome was the change in general self-efficacy from before the intervention to after the intervention at 3 months. Self-efficacy was measured by the Chinese version of the 10-item, 4-point General Self-efficacy Scale, with higher scores representing higher self-efficacy levels. Analysis was performed on an intention-to-treat basis.

RESULTS

A total of 68 participants who fulfilled the criteria were enrolled (34 in the control group and 34 in the intervention group; 56 [82.4%] were women; and mean [SD] age, 71.8 [6.1] years). At 3 months, there was no statistical difference in self-efficacy between the telecare group and the control group. Scores for self-efficacy improved in both groups (β = 1.68; 95% CI, -0.68 to 4.03; P = .16). No significant differences were found in basic and instrumental activities of daily living, depression, and use of health care services. However, the telecare group showed statistically significant interactions of group and time effects on medication adherence (β = -8.30; 95% CI, -13.14 to -3.47; P = .001) and quality of life (physical component score: β = 4.99; 95% CI, 0.29-9.69; P = .04).

CONCLUSIONS AND RELEVANCE

In this randomized clinical trial, participants who received the telecare program were statistically no different from the control group with respect to changes in self-efficacy, although scores in both groups improved. After the intervention, the telecare group had better medication adherence and quality of life than the control group, although the small sample size may limit generalizability. A large-scale study is needed to confirm these results.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04304989.

Effect of a mobile just-in-time implementation intention intervention on momentary smoking lapses in smoking cessation attempts among Asian American young adults

Identifying vulnerable windows for a given problematic behavior and providing timely and appropriate support are critical for building an effective just-in-time (JIT) intervention for behavioral change. We developed and evaluated an implementation intention (II) based, JIT cessation intervention prototype to support Asian American young adult smokers to prevent lapses in their cessation attempts in real-time. We examined how a JIT II reminder may prevent lapses during self-identified high-risk smoking situation (HRSS) as a microtemporal process. We also tested whether the effect of JIT reminder changes over the course of study and differed between those who used their own versus project loan phones. Asian American young adult smokers (N = 57) who were interested in quitting or reducing smoking participated in a 4 week, mobile-based, cessation study (MyQuit USC, MQU). MQU is a JIT mobile app that deploys a user-specified II reminder at user-specified HRSS and assesses momentary lapse status. Generalized mixed linear models were conducted to assess the effect of the JIT intervention on lapse prevention. We found a significant interaction effect (p = .03) such that receiving JIT reminder reduced the likelihood of lapses for participants using their own phones but not for the loaners. The results also showed that when participants enacted the suggested II, they were less likely to lapse (p < .001). The JIT effect did not change over time in study (p = .21). This study provides evidence that receiving a reminder of a smoker's own plan just before a self-identified risky situation on a familiar device and successfully executing specified plans can be helpful in preventing lapses. Our results highlighted factors to consider when designing and refining a JIT intervention.

Effectiveness of Integrated Technology Apps for Supporting Healthy Food Purchasing and Consumption: A Systematic Review

A healthy diet is essential for good health and nutrition, though literature showed that there are various factors affecting the intention to purchase and consume healthy food. Technology integration is known to be useful in various aspects, but findings from studies on the efficacy of technology integration to improve healthy food consumption and purchase have largely been inconsistent. Therefore, we aimed to examine the efficacy of interventions that use technology apps to improve healthy food purchasing and consumption in adults. Relevant studies were identified through PubMed, Scopus, CINAHL, SportDiscuss and ACM Digital Library. Twenty studies were included in the systematic review. The majority of studies (n = 18) used a smartphone in the intervention, and only two studies used a personal digital assistant. The results showed that technology integration-based intervention favoured healthy changes in household food purchases, and increased consumption of healthy food and healthy eating outcomes - albeit to different extents. Overall, technology apps are convenient and user-friendly tools to encourage a change in healthy food purchase and consumption among people.

Identifying critical features of type two diabetes prevention interventions: A Delphi study with key stakeholders

Aims

This study aims to identify critically important features of digital type two diabetes mellitus (T2DM) prevention interventions.

Methods

A stakeholder mapping exercise was undertaken to identify key end-user and professional stakeholders, followed by a three-round Delphi procedure to generate and evaluate evidence statements related to the critical elements of digital T2DM prevention interventions in terms of product (intervention), price (funding models/financial cost), place (distribution/delivery channels), and promotion (target audiences).

Results

End-user (n = 38) and professional (n = 38) stakeholders including patients, dietitians, credentialed diabetes educators, nurses, medical doctors, research scientists, and exercise physiologists participated in the Delphi study. Fifty-two critical intervention characteristics were identified. Future interventions should address diet, physical activity, mental health (e.g. stress, diabetes-related distress), and functional health literacy, while advancing behaviour change support. Programs should be delivered digitally or used multiple delivery modes, target a range of population subgroups including children, and be based on collaborative efforts between national and local and government and non-government funded organisations.

Conclusions

Our findings highlight strong support for digital health to address T2DM in Australia and identify future directions for T2DM prevention interventions. The study also demonstrates the feasibility and value of stakeholder-led intervention development processes.

Smartphone-Based Interventions for Physical Activity Promotion: Scoping Review of the Evidence Over the Last 10 Years

Background

Several reviews of mobile health (mHealth) physical activity (PA) interventions suggest their beneficial effects on behavior change in adolescents and adults. Owing to the ubiquitous presence of smartphones, their use in mHealth PA interventions seems obvious; nevertheless, there are gaps in the literature on the evaluation reporting processes and best practices of such interventions.

Objective

The primary objective of this review is to analyze the development and evaluation trajectory of smartphone-based mHealth PA interventions and to review systematic theory- and evidence-based practices and methods that are implemented along this trajectory. The secondary objective is to identify the range of evidence (both quantitative and qualitative) available on smartphone-based mHealth PA interventions to provide a comprehensive tabular and narrative review of the available literature in terms of its nature, features, and volume.

Methods

We conducted a scoping review of qualitative and quantitative studies examining smartphone-based PA interventions published between 2008 and 2018. In line with scoping review guidelines, studies were not rejected based on their research design or quality. This review, therefore, includes experimental and descriptive studies, as well as reviews addressing smartphone-based mHealth interventions aimed at promoting PA in all age groups (with a subanalysis conducted for adolescents). Two groups of studies were additionally included: reviews or content analyses of PA trackers and meta-analyses exploring behavior change techniques and their efficacy.

Results

Included articles (N=148) were categorized into 10 groups: commercial smartphone app content analyses, smartphone-based intervention review studies, activity tracker content analyses, activity tracker review studies, meta-analyses of PA intervention studies, smartphone-based intervention studies, qualitative formative studies, app development descriptive studies, qualitative follow-up studies, and other related articles. Only 24 articles targeted children or adolescents (age range: 5-19 years). There is no agreed evaluation framework or taxonomy to code or report smartphone-based PA interventions. Researchers did not state the coding method, used various evaluation frameworks, or used different versions of behavior change technique taxonomies. In addition, there is no consensus on the best behavior change theory or model that should be used in smartphone-based interventions for PA promotion. Commonly reported systematic practices and methods have been successfully identified. They include PA recommendations, trial designs (randomized controlled trials, experimental trials, and rapid design trials), mixed methods data collection (surveys, questionnaires, interviews, and focus group discussions), scales to assess app quality, and industry-recognized reporting guidelines.

Conclusions

Smartphone-based mHealth interventions aimed at promoting PA showed promising results for behavior change. Although there is a plethora of published studies on the adult target group, the number of studies and consequently the evidence base for adolescents is limited. Overall, the efficacy of smartphone-based mHealth PA interventions can be considerably improved through a more systematic approach of developing, reporting, and coding of the interventions.

Interventions for reducing sedentary behaviour in community-dwelling older adults

BACKGROUND

Older adults are the most sedentary segment of society, often spending in excess of 8.5 hours a day sitting. Large amounts of time spent sedentary, defined as time spend sitting or in a reclining posture without spending energy, has been linked to an increased risk of chronic diseases, frailty, loss of function, disablement, social isolation, and premature death.

OBJECTIVES

To evaluate the effectiveness of interventions aimed at reducing sedentary behaviour amongst older adults living independently in the community compared to control conditions involving either no intervention or interventions that do not target sedentary behaviour.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, CINAHL, PsycINFO, PEDro, EPPI-Centre databases (Trials Register of Promoting Health Interventions (TRoPHI) and the Obesity and Sedentary behaviour Database), WHO ICTRP, and ClinicalTrials.gov up to 18 January 2021. We also screened the reference lists of included articles and contacted authors to identify additional studies.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) and cluster-RCTs. We included interventions purposefully designed to reduce sedentary time in older adults (aged 60 or over) living independently in the community. We included studies if some of the participants had multiple comorbidities, but excluded interventions that recruited clinical populations specifically (e.g. stroke survivors).

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles and abstracts and full-text articles to determine study eligibility. Two review authors independently extracted data and assessed risk of bias. We contacted authors for additional data where required. Any disagreements in study screening or data extraction were settled by a third review author.

MAIN RESULTS

We included seven studies in the review, six RCTs and one cluster-RCT, with a total of 397 participants. The majority of participants were female (n = 284), white, and highly educated. All trials were conducted in high-income countries. All studies evaluated individually based behaviour change interventions using a combination of behaviour change techniques such as goal setting, education, and behaviour monitoring or feedback. Four of the seven studies also measured secondary outcomes. The main sources of bias were related to selection bias (N = 2), performance bias (N = 6), blinding of outcome assessment (N = 2), and incomplete outcome data (N = 2) and selective reporting (N=1). The overall risk of bias was judged as unclear. Primary outcomes The evidence suggests that interventions to change sedentary behaviour in community-dwelling older adults may reduce sedentary time (mean difference (MD) -44.91 min/day, 95% confidence interval (CI) -93.13 to 3.32; 397 participants; 7 studies; I2 = 73%; low-certainty evidence). We could not pool evidence on the effect of interventions on breaks in sedentary behaviour or time spent in specific domains such as TV time, as data from only one study were available for these outcomes. Secondary outcomes We are uncertain whether interventions to reduce sedentary behaviour have any impact on the physical or mental health outcomes of community-dwelling older adults. We were able to pool change data for the following outcomes. • Physical function (MD 0.14 Short Physical Performance Battery (SPPB) score, 95% CI -0.38 to 0.66; higher score is favourable; 98 participants; 2 studies; I2 = 26%; low-certainty evidence). • Waist circumference (MD 1.14 cm, 95% CI -1.64 to 3.93; 100 participants; 2 studies; I2 = 0%; low-certainty evidence). • Fitness (MD -5.16 m in the 6-minute walk test, 95% CI -36.49 to 26.17; higher score is favourable; 80 participants; 2 studies; I2 = 29%; low-certainty evidence). • Blood pressure: systolic (MD -3.91 mmHg, 95% CI -10.95 to 3.13; 138 participants; 3 studies; I2 = 73%; very low-certainty evidence) and diastolic (MD -0.06 mmHg, 95% CI -5.72 to 5.60; 138 participants; 3 studies; I2 = 97%; very low-certainty evidence). • Glucose blood levels (MD 2.20 mg/dL, 95% CI -6.46 to 10.86; 100 participants; 2 studies; I2 = 0%; low-certainty evidence). No data were available on cognitive function, cost-effectiveness or adverse effects.

AUTHORS' CONCLUSIONS

It is not clear whether interventions to reduce sedentary behaviour are effective at reducing sedentary time in community-dwelling older adults. We are uncertain if these interventions have any impact on the physical or mental health of community-dwelling older adults. There were few studies, and the certainty of the evidence is very low to low, mainly due to inconsistency in findings and imprecision. Future studies should consider interventions aimed at modifying the environment, policy, and social and cultural norms. Future studies should also use device-based measures of sedentary time, recruit larger samples, and gather information about quality of life, cost-effectiveness, and adverse event data.

Using Intervention Mapping in the Systematic Development of a Behaviour Change Intervention to Enhance Exercise Adherence among People with Persistent Musculoskeletal Pain

Purpose: This article describes the first four steps of the intervention mapping framework used to design a programme aimed at increasing adherence to prescribed exercise by people with persistent musculoskeletal pain. Method: In Step 1, a systematic review and qualitative study was completed to inform Step 2 and the identification of the Health Action Process Approach as an appropriate theoretical framework for establishing two programme objectives: enhancing self-management and providing tailored and accessible exercise instructions. Step 3 encompassed the selection of the programme methods, and the programme is described in Step 4. The resulting programme provides virtually delivered motivational interviewing and an app-based exercise programme to support individuals’ adherence to exercise. Results: The resulting intervention was assessed in a proof-of-concept feasibility and acceptability study and was shown to be feasible and acceptable. Refinements to the programme included additional tailoring of the exercise app and modifying the motivational interviewing schedule. Conclusions: Using the intervention mapping approach enabled us to successfully develop an intervention aimed at supporting the development of self-management behaviours and addressing maladaptive beliefs as a means of enhancing individuals’ adherence to exercise. Evaluation and implementation of the intervention should now be carried out.

mHealth Technology and CVD Risk Reduction

PURPOSE OF REVIEW

To review existing mHealth-based interventions and examine their efficacy in reducing cardiovascular disease (CVD) risk factors.

RECENT FINDINGS

A total of 50 articles are included in this review. The majority of the mHealth interventions targeted a specific CVD risk factor, while 4 addressed 2 or more CVD risk factors. Of the 9 mHealth-supported weight loss intervention trials, 4 resulted in significant weight loss. Four out of 7 RCTs targeting improvement in physical activity reported significant improvement, while 4 of the 8 mHealth-supported smoking cessation intervention trials resulted in smoking abstinence. Of the 10 mHealth-based diabetes intervention trials, 5 reported significant reductions in HbA1c; however, only 3 out of the 9 antihypertension interventions resulted in significant reductions in blood pressure. There is a growing body of literature focused on mHealth interventions that address CVD risk factors. Despite the immense potential of mHealth interventions, evidence of their efficacy in mitigating cardiovascular risk is heterogeneous.

Smartphone-Based Passive Sensing for Behavioral and Physical Monitoring in Free-Life Conditions: Technical Usability Study

BACKGROUND

Smartphone use is widely spreading in society. Their embedded functions and sensors may play an important role in therapy monitoring and planning. However, the use of smartphones for intrapersonal behavioral and physical monitoring is not yet fully supported by adequate studies addressing technical reliability and acceptance.

OBJECTIVE

The objective of this paper is to identify and discuss technical issues that may impact on the wide use of smartphones as clinical monitoring tools. The focus is on the quality of the data and transparency of the acquisition process.

METHODS

QuantifyMyPerson is a platform for continuous monitoring of smartphone use and embedded sensors data. The platform consists of an app for data acquisition, a backend cloud server for data storage and processing, and a web-based dashboard for data management and visualization. The data processing aims to extract meaningful features for the description of daily life such as phone status, calls, app use, GPS, and accelerometer data. A total of health subjects installed the app on their smartphones, running it for 7 months. The acquired data were analyzed to assess impact on smartphone performance (ie, battery consumption and anomalies in functioning) and data integrity. Relevance of the selected features in describing changes in daily life was assessed through the computation of a k-nearest neighbors global anomaly score to detect days that differ from others.

RESULTS

The effectiveness of smartphone-based monitoring depends on the acceptability and interoperability of the system as user retention and data integrity are key aspects. Acceptability was confirmed by the full transparency of the app and the absence of any conflicts with daily smartphone use. The only perceived issue was the battery consumption even though the trend of battery drain with and without the app running was comparable. Regarding interoperability, the app was successfully installed and run on several Android brands. The study shows that some smartphone manufacturers implement power-saving policies not allowing continuous sensor data acquisition and impacting integrity. Data integrity was 96% on smartphones whose power-saving policies do not impact the embedded sensor management and 84% overall.

CONCLUSIONS

The main technological barriers to continuous behavioral and physical monitoring (ie, battery consumption and power-saving policies of manufacturers) may be overcome. Battery consumption increase is mainly due to GPS triangulation and may be limited, while data missing because of power-saving policies are related only to periods of nonuse of the phone since the embedded sensors are reactivated by any smartphone event. Overall, smartphone-based passive sensing is fully feasible and scalable despite the Android market fragmentation.

Digital Therapeutics for Obesity and Eating-Related Problems

In recent years, digital technologies have rapidly advanced and are being applied to remedy medical problems. These technologies allow us to monitor and manage our physical and mental health in our daily lives. Since lifestyle modification is the cornerstone of the management of obesity and eating behavior problems, digital therapeutics (DTx) represent a powerful and easily accessible treatment modality. This review discusses the critical issues to consider for enhancing the efficacy of DTx in future development initiatives. To competently adapt and expand public access to DTx, it is important for various stakeholders, including health professionals, patients, and guardians, to collaborate with other industry partners and policy-makers in the ecosystem.

Rural Residents' Perspectives on an mHealth or Personalized Health Coaching Intervention: Qualitative Study With Focus Groups and Key Informant Interviews

Background

Compared with national averages, rural Appalachians experience extremely elevated rates of premature morbidity and mortality. New opportunities, including approaches incorporating personal technology, may help improve lifestyles and overcome health inequities.

Objective

This study aims to gather perspectives on whether a healthy lifestyle intervention, specifically an app originally designed for urban users, may be feasible and acceptable to rural residents. In addition to a smartphone app, this program—Make Better Choices 2—consists of personalized health coaching, accelerometer use, and financial incentives.

Methods

We convened 4 focus groups and 16 key informant interviews with diverse community stakeholders to assess perspectives on this novel, evidence-based diet and physical activity intervention. Participants were shown a slide presentation and asked open-ended follow-up questions. The focus group and key informant interview sessions were audiotaped, transcribed, and subjected to thematic analysis.

Results

We identified 3 main themes regarding Appalachian residents’ perspectives on this mobile health (mHealth) intervention: personal technology is feasible and desirable; challenges persist in implementing mHealth lifestyle interventions in Appalachian communities; and successful mHealth interventions should include personal connections, local coaches, and educational opportunities. Although viewed as feasible and acceptable overall, lack of healthy lifestyle awareness, habitual behavior, and financial constraints may challenge the success of mHealth lifestyle interventions in Appalachia. Finally, participants described several minor elements that require modification, including expanding the upper age inclusion, providing extra coaching on technology use, emphasizing personal and supportive connections, employing local coaches, and ensuring adequate educational content for the program.

Conclusions

Blending new technologies, health coaching, and other features is not only acceptable but may be essential to reach vulnerable rural residents.

Calibrating validation samples when accounting for measurement error in intervention studies

Many lifestyle intervention trials depend on collecting self-reported outcomes, such as dietary intake, to assess the intervention's effectiveness. Self-reported outcomes are subject to measurement error, which impacts treatment effect estimation. External validation studies measure both self-reported outcomes and accompanying biomarkers, and can be used to account for measurement error. However, in order to account for measurement error using an external validation sample, an assumption must be made that the inferences are transportable from the validation sample to the intervention trial of interest. This assumption does not always hold. In this paper, we propose an approach that adjusts the validation sample to better resemble the trial sample, and we also formally investigate when bias due to poor transportability may arise. Lastly, we examine the performance of the methods using simulation, and illustrate them using PREMIER, a lifestyle intervention trial measuring self-reported sodium intake as an outcome, and OPEN, a validation study measuring both self-reported diet and urinary biomarkers.

A Mobile Health App to Support Patients Receiving Medication-Assisted Treatment for Opioid Use Disorder: Development and Feasibility Study

Background

Opioid use disorder (OUD) is a public health crisis with more than 2 million people living with OUD in the United States. Medication-assisted treatment (MAT) is an evidence-based approach for the treatment of OUD that relies on a combination of behavioral therapy and medication. Less than half of those living with OUD are accessing this treatment. Mobile technology can enhance the treatment of chronic diseases in readily accessible and cost-effective ways through self-monitoring and support.

Objective

The aim of this study is to describe the adaptation of a mobile platform for patients undergoing treatment for OUD and preliminary pilot testing results.

Methods

Our study was conducted with patient and provider participants at the University of Virginia MAT clinic and was approved by the institutional review board. The formative phase included semistructured interviews to understand the needs of patients with OUD, providers’ perspectives, and opportunities for MAT support via a mobile app. A second round of formative interviews used mock-ups of app features to collect feedback on feature function and desirability. Formative participants’ input from 16 interviews then informed the development of a functional smartphone app. Patient participants (n=25) and provider participants (n=3) were enrolled in a 6-month pilot study of the completed platform. Patient app use and usability interviews, including a system usability score and open-ended questions, were completed 1 month into the pilot study. Open-ended responses were analyzed for prevalent themes.

Results

Formative interviews resulted in the development of a mobile app, named HOPE, which includes both evidence-based and participant-suggested features. The features included daily prompts for monitoring mood, stress, treatment adherence, and substance use; patient tracking of goals, reminders, and triggering or encouraging experiences; informational resources; an anonymous community board to share support with other patients; and secure messaging for communication between patients and providers. All patient participants engaged with at least one app feature during their first month of pilot study participation, and the daily self-monitoring prompts were the most used. Patients and providers reported high levels of system usability (mean 86.9, SD 10.2 and mean 83.3, SD 12.8, respectively). Qualitative analysis of open-ended usability questions highlighted the value of self-monitoring, access to support through the app, and perceived improvement in connection to care and communication for both patient and provider participants.

Conclusions

The use of the HOPE program by pilot participants, high usability scoring, and positive perceptions from 1-month interviews indicate successful program development. By engaging with end users and eliciting feedback throughout the development process, we were able to create an app and a web portal that was highly usable and acceptable to study participants. Further work is needed to understand the program’s effect on clinical outcomes, patient linkage, and engagement in care.

Harnessing SmartPhones to Personalize Nutrition in a Time of Global Pandemic

The soar in COVID-19 cases around the globe has forced many to adapt to social distancing and self-isolation. In order to reduce contact with healthcare facilities and other patients, the CDC has advocated the use of telemedicine, i.e., electronic information and telecommunication technology. While these changes may disrupt normal behaviors and routines and induce anxiety, resulting in decreased vigilance to healthy diet and physical activity and reluctance to seek medical attention, they may just as well be circumvented using modern technology. Indeed, as the beginning of the pandemic a plethora of alternatives to conventional physical interactions were introduced. In this Perspective, we portray the role of SmartPhone applications (apps) in monitoring healthy nutrition, from their basic functionality as food diaries required for simple decision-making and nutritional interventions, through more advanced purposes, such as multi-dimensional data-mining and development of machine learning algorithms. Finally, we will delineate the emerging field of personalized nutrition and introduce pioneering technologies and concepts yet to be incorporated in SmartPhone-based dietary surveillance.

A mHealth intervention to preserve and promote ideal cardiovascular health in college students: Design and protocol of a cluster randomized controlled trial

BACKGROUND

Cardiovascular disease (CVD) remains the leading cause of death globally. Seven health factors are associated with ideal cardiovascular health: being a non-smoker; not overweight; physically active; having a healthy diet; and normal blood pressure; fasting plasma glucose and cholesterol. Whereas approximately half of U.S. youth have ideal levels in at least 5 of the 7 components of cardiovascular health, this proportion falls to 16% by adulthood.

OBJECTIVE

We will evaluate whether the NUYou cardiovascular mHealth intervention is more effective than an active comparator to promote cardiovascular health during the transition to young adulthood.

METHODS

302 incoming freshmen at a midwest university will be cluster randomized by dormitory into one of two mHealth intervention groups: 1) Cardiovascular Health (CVH), addressing behaviors related to CVD risk; or 2) Whole Health (WH), addressing behaviors unrelated to CVD. Both groups will receive smartphone applications, co-designed with students to help them manage time, interact with other participants via social media, and report health behaviors weekly. The CVH group will also have self-monitoring features to track their risk behaviors. Cardiovascular health will be assessed at the beginning of freshman year and the end of freshman and sophomore years. Linear mixed models will be used to compare groups on a composite of the seven cardiovascular-related health factors.

SIGNIFICANCE

This is the first entirely technology-mediated multiple health behavior change intervention delivered to college students to promote cardiovascular health. Findings will inform the potential for primordial prevention in young adulthood.

TRIAL REGISTRATION NUMBER

clinicaltrials.gov #NCT02496728.

A systematic review of tailored mHealth interventions for physical activity promotion among adults

The purpose of this systematic review was to critically examine the effectiveness of tailored mHealth interventions for promoting physical activity (PA) in adult populations. Cochrane Library Central Register of Controlled Trials, Medline, SportDiscus, PubMed, PsycINFO, and ProQuest databases were searched systematically in June 2019. Studies were eligible if they were experimentally designed studies, included adult populations (18+ years), and consisted of a tailored intervention that was delivered via a mobile device (i.e., cell phone, tablet). The primary outcome was change in PA. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool. Sixteen articles were reviewed. Ten studies reported significant positive outcomes for the intervention groups compared to the controls. Three studies reported significant improvements in PA for the tailored intervention arms compared to the non-tailored treatment arms. Four of six studies that reported no between group differences used SMS to deliver tailored materials. Differences on tailoring dimension, PA outcomes, and measurement tools were not identified between studies. Tailored mHealth interventions appear to be promising for promoting PA among adults. Most interventions used multiple intervention components. Additional research is needed to identify best practices and to make programs scalable.

Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysis

Background

Chronic disease represents a large and growing burden to the health care system worldwide. One method of managing this burden is the use of app-based interventions; however attrition, defined as lack of patient use of the intervention, is an issue for these interventions. While many apps have been developed, there is some evidence that they have significant issues with sustained use, with up to 98% of people only using the app for a short time before dropping out and/or dropping use down to the point where the app is no longer effective at helping to manage disease.

Objective

Our objectives are to systematically appraise and perform a meta-analysis on dropout rates in apps for chronic disease and to qualitatively synthesize possible reasons for these dropout rates that could be addressed in future interventions.

Methods

MEDLINE (Medical Literature Analysis and Retrieval System Online), PubMed, Cochrane CENTRAL (Central Register of Controlled Trials), and Embase were searched from 2003 to the present to look at mobile health (mHealth) and attrition or dropout. Studies, either randomized controlled trials (RCTs) or observational trials, looking at chronic disease with measures of dropout were included. Meta-analysis of attrition rates was conducted in Stata, version 15.1 (StataCorp LLC). Included studies were also qualitatively synthesized to examine reasons for dropout and avenues for future research.

Results

Of 833 studies identified in the literature search, 17 were included in the review and meta-analysis. Out of 17 studies, 9 (53%) were RCTs and 8 (47%) were observational trials, with both types covering a range of chronic diseases. The pooled dropout rate was 43% (95% CI 29-57), with observational studies having a higher dropout rate (49%, 95% CI 27-70) than RCTs in more controlled scenarios, which only had a 40% dropout rate (95% CI 16-63). The studies were extremely varied, which is represented statistically in the high degree of heterogeneity (I²>99%). Qualitative synthesis revealed a range of reasons relating to attrition from app-based interventions, including social, demographic, and behavioral factors that could be addressed.

Conclusions

Dropout rates in mHealth interventions are high, but possible areas to minimize attrition exist. Reducing dropout rates will make these apps more effective for disease management in the long term.

Trial Registration

International Prospective Register of Systematic Reviews (PROSPERO) CRD42019128737; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019128737