Long-Term Effectiveness of a Smartphone App for Improving Healthy Lifestyles in General Population in Primary Care: Randomized Controlled Trial (Evident II Study)

mHealth application for improving treatment outcomes for patients with multidrug-resistant tuberculosis in Vietnam: an economic evaluation protocol for the V-SMART trial

INTRODUCTION

The Strengthen the Management of Multidrug-Resistant Tuberculosis in Vietnam (V-SMART) trial is a randomised controlled trial of using mobile health (mHealth) technologies to improve adherence to medications and management of adverse events (AEs) in people with multidrug-resistant tuberculosis (MDR-TB) undergoing treatment in Vietnam. This economic evaluation seeks to quantify the cost-effectiveness of this mHealth intervention from a healthcare provider and societal perspective.

METHODS AND ANALYSIS

The V-SMART trial will recruit 902 patients treated for MDR-TB across seven participating provinces in Vietnam. Participants in both intervention and control groups will receive standard community-based therapy for MDR-TB. Participants in the intervention group will also have a purpose-designed App installed on their smartphones to report AEs to health workers and to facilitate timely management of AEs. This economic evaluation will compare the costs and health outcomes between the intervention group (mHealth) and the control group (standard of care). Costs associated with delivering the intervention and health service utilisation will be recorded, as well as patient out-of-pocket costs. The health-related quality of life (HRQoL) of study participants will be captured using the 36-Item Short Form Survey (SF-36) questionnaire and used to calculate quality-adjusted life-years (QALYs). Incremental cost-effectiveness ratios (ICERs) will be based on the primary outcome (proportion of patients with treatment success after 24 months) and QALYs gained. Sensitivity analysis will be conducted to test the robustness of the ICERs. A budget impact analysis will be conducted from a payer perspective to provide an estimate of the total budget required to scale-up delivery of the intervention.

ETHICS AND DISSEMINATION

Ethical approval for the study was granted by the University of Sydney Human Research Ethics Committee (2019/676), the Scientific Committee of the Ministry of Science and Technology, Vietnam (08/QD-HDQL-NAFOSTED) and the Institutional Review Board of the National Lung Hospital, Vietnam (13/19/CT-HDDD). Study findings will be published in peer-reviewed journals and conference proceedings.

TRIAL REGISTRATION NUMBER

ACTRN12620000681954.

[The Research Network on Preventive Activities and Health Promotion (redIAPP): a reference network and promoter of primary care research]

The Research Network on Preventive Activities and Health Promotion (redIAPP), a reference network and promoter of primary care research was created in 2003 thanks to the program Thematic Networks for Cooperative Research in Health (RETICS) of the Instituto de Salud Carlos III (ISCIII). Its creation has meant a radical change in the situation of research in primary care. Throughout its 19 years (2003-2021), different research groups and autonomous communities have participated, and different lines of research have been developed with numerous projects and publications. Despite the difficulties suffered, it has created a collaborative research experience between different autonomous communities with great vitality and with important results for primary care. The redIAPP, therefore, has been a great reference for research in primary care and for the deepening of its area of knowledge. Several lines of improvement are suggested for the future of primary care research.

Prediction of Relevant Training Control Parameters at Individual Anaerobic Threshold without Blood Lactate Measurement

BACKGROUND

Active exercise therapy plays an essential role in tackling the global burden of obesity. Optimizing recommendations in individual training therapy requires that the essential parameters heart rate HR(IAT) and work load (W/kg(IAT) at individual anaerobic threshold (IAT) are known. Performance diagnostics with blood lactate is one of the most established methods for these kinds of diagnostics, yet it is also time consuming and expensive.

METHODS

To establish a regression model which allows HR(IAT) and (W/kg(IAT) to be predicted without measuring blood lactate, a total of 1234 performance protocols with blood lactate in cycle ergometry were analyzed. Multiple linear regression analyses were performed to predict the essential parameters (HR(IAT)) (W/kg(IAT)) by using routine parameters for ergometry without blood lactate.

RESULTS

HR(IAT) can be predicted with an RMSE of 8.77 bpm (p < 0.001), R² = 0.799 (|R| = 0.798) without performing blood lactate diagnostics during cycle ergometry. In addition, it is possible to predict W/kg(IAT) with an RMSE (root mean square error) of 0.241 W/kg (p < 0.001), R² = 0.897 (|R| = 0.897).

CONCLUSIONS

It is possible to predict essential parameters for training management without measuring blood lactate. This model can easily be used in preventive medicine and results in an inexpensive yet better training management of the general population, which is essential for public health.

A Digital Lifestyle Coach (E-Supporter 1.0) to Support People With Type 2 Diabetes: Participatory Development Study

BACKGROUND

A healthy lifestyle, including regular physical activity and a healthy diet, is becoming increasingly important in the treatment of chronic diseases. eHealth interventions that incorporate behavior change techniques (BCTs) and dynamic tailoring strategies could effectively support a healthy lifestyle. E-Supporter 1.0 is an eCoach designed to support physical activity and a healthy diet in people with type 2 diabetes (T2D).

OBJECTIVE

This paper aimed to describe the systematic development of E-Supporter 1.0.

METHODS

Our systematic design process consisted of 3 phases. The definition phase included the selection of the target group and formulation of intervention objectives, and the identification of behavioral determinants based on which BCTs were selected to apply in the intervention. In the development phase, intervention content was developed by specifying tailoring variables, intervention options, and decision rules. In the last phase, E-Supporter 1.0 integrated in the Diameter app was evaluated using a usability test in 9 people with T2D to assess intervention usage and acceptability.

RESULTS

The main intervention objectives were to stimulate light to moderate-vigorous physical activities or adherence to the Dutch dietary guidelines in people with T2D. The selection of behavioral determinants was informed by the health action process approach and theories explaining behavior maintenance. BCTs were included to address relevant behavioral determinants (eg, action control, self-efficacy, and coping planning). Development of the intervention resulted in 3 types of intervention options, consisting of motivational messages, behavioral feedback, and tailor-made supportive exercises. On the basis of IF-THEN rules, intervention options could be tailored to, among others, type of behavioral goal and (barriers to) goal achievement. Data on these variables could be collected using app data, activity tracker data, and daily ecological momentary assessments. Usability testing revealed that user experiences were predominantly positive, despite some problems in the fixed delivery of content.

CONCLUSIONS

The systematic development approach resulted in a theory-based and dynamically tailored eCoach. Future work should focus on expanding intervention content to other chronic diseases and lifestyle behaviors, enhancing the degree of tailoring and evaluating intervention effects on acceptability, use, and cost-effectiveness.

Patterns of Engagement With an Application-Based Dietary Self-Monitoring Tool Within a Randomized Controlled Feasibility Trial

Introduction

The Dietary Approaches to Stop Hypertension dietary pattern is a proven way to manage hypertension, but adherence remains low. Dietary tracking applications offer a highly disseminable way to self-monitor intake on the pathway to reaching dietary goals but require consistent engagement to support behavior change. Few studies use longitudinal dietary self-monitoring data to assess trajectories and predictors of engagement. We used dietary self-monitoring data from participants in Dietary Approaches to Stop Hypertension Cloud (N=59), a feasibility trial to improve diet quality among women with hypertension, to identify trajectories of engagement and explore associations between participant characteristics.

Methods

We used latent class growth modeling to identify trajectories of engagement with a publicly available diet tracking application and used bivariate and regression analyses to assess the associations of classifications of engagement with participant characteristics.

Results

We identified 2 latent classes of engagement: consistent engagers and disengagers. Consistent engagers were more likely to be older, more educated, and married or living with a partner. Although consistent engagers exhibited slightly greater changes in Dietary Approaches to Stop Hypertension score, the difference was not significant.

Conclusions

This study highlights an important yet underutilized methodologic approach for uncovering dietary self-monitoring engagement patterns. Understanding how certain individuals engage with digital technologies is an important step toward designing cost-effective behavior change interventions.

Trial registration

This study is registered at www.clinicaltrials.gov NCT03215472.

Assessing the Pragmatic Nature of mHealth Interventions Promoting Physical Activity: A Systematic Review and Meta-Analysis (Preprint)

BACKGROUND

Mobile health (mHealth) apps can promote physical activity; however, the pragmatic nature (ie, how well research translates into real-world settings) of these studies is unknown. The impact of study design choices, for example, intervention duration, on intervention effect sizes is also understudied.

OBJECTIVE

This review and meta-analysis aims to describe the pragmatic nature of recent mHealth interventions for promoting physical activity and examine the associations between study effect size and pragmatic study design choices.

METHODS

The PubMed, Scopus, Web of Science, and PsycINFO databases were searched until April 2020. Studies were eligible if they incorporated apps as the primary intervention, were conducted in health promotion or preventive care settings, included a device-based physical activity outcome, and used randomized study designs. Studies were assessed using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) and Pragmatic-Explanatory Continuum Indicator Summary-2 (PRECIS-2) frameworks. Study effect sizes were summarized using random effect models, and meta-regression was used to examine treatment effect heterogeneity by study characteristics.

RESULTS

Overall, 3555 participants were included across 22 interventions, with sample sizes ranging from 27 to 833 (mean 161.6, SD 193.9, median 93) participants. The study populations' mean age ranged from 10.6 to 61.5 (mean 39.6, SD 6.5) years, and the proportion of males included across all studies was 42.8% (1521/3555). Additionally, intervention lengths varied from 2 weeks to 6 months (mean 60.9, SD 34.9 days). The primary app- or device-based physical activity outcome differed among interventions: most interventions (17/22, 77%) used activity monitors or fitness trackers, whereas the rest (5/22, 23%) used app-based accelerometry measures. Data reporting across the RE-AIM framework was low (5.64/31, 18%) and varied within specific dimensions (Reach=44%; Effectiveness=52%; Adoption=3%; Implementation=10%; Maintenance=12.4%). PRECIS-2 results indicated that most study designs (14/22, 63%) were equally explanatory and pragmatic, with an overall PRECIS-2 score across all interventions of 2.93/5 (SD 0.54). The most pragmatic dimension was flexibility (adherence), with an average score of 3.73 (SD 0.92), whereas follow-up, organization, and flexibility (delivery) appeared more explanatory with means of 2.18 (SD 0.75), 2.36 (SD 1.07), and 2.41 (SD 0.72), respectively. An overall positive treatment effect was observed (Cohen d=0.29, 95% CI 0.13-0.46). Meta-regression analyses revealed that more pragmatic studies (-0.81, 95% CI -1.36 to -0.25) were associated with smaller increases in physical activity. Treatment effect sizes were homogenous across study duration, participants' age and gender, and RE-AIM scores.

CONCLUSIONS

App-based mHealth physical activity studies continue to underreport several key study characteristics and have limited pragmatic use and generalizability. In addition, more pragmatic interventions observe smaller treatment effects, whereas study duration appears to be unrelated to the effect size. Future app-based studies should more comprehensively report real-world applicability, and more pragmatic approaches are needed for maximal population health impacts.

TRIAL REGISTRATION

PROSPERO CRD42020169102; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=169102.

Adherence to eHealth-Delivered Exercise in Adults with no Specific Health Conditions: A Scoping Review on a Conceptual Challenge

Adherence has emerged as a focal point and critical determinant of success for physical activity interventions. The term is used for both traditional and digital interventions, and for prescribed and nonprescribed activities. Many other terms for adherence are being used interchangeably, as there is no consensus on its precise conceptualization. This scoping review aimed to advance the definition of adherence to eHealth programs, specifically for the adult population with no specific health conditions. A total of 2983 papers, published between 1 January 2016 and 13 March 2022, were retrieved from different databases (including grey literature). Of those, 13 studies met the eligibility criteria and were included for review. The selected studies used a wide array of technologies and consisted mainly of exercise interventions. Most of the reviewed publications contemplated exercise adherence as a percentage of expected dose. Most (8 out of 13) studies neither assessed nor specified an expected use of the involved technology. Results suggest a need for homogeneity in the conceptualization of adherence to physical activity and exercise, including those interventions delivered digitally.

Effectiveness of physical activity interventions delivered or prompted by health professionals in primary care settings: systematic review and meta-analysis of randomised controlled trials

OBJECTIVE

To examine the effectiveness of physical activity interventions delivered or prompted by primary care health professionals for increasing moderate to vigorous intensity physical activity (MVPA) in adult patients.

DESIGN

Systematic review and meta-analysis of randomised controlled trials.

DATA SOURCES

Databases (Medline and Medline in progress, Embase, PsycINFO, CINAHL, SPORTDiscus, Sports Medicine and Education Index, ASSIA, PEDro, Bibliomap, Science Citation Index, Conference Proceedings Citation Index), trial registries (Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, TRoPHI), and grey literature (OpenGrey) sources were searched (from inception to September 2020).

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Randomised controlled trials of aerobic based physical activity interventions delivered or prompted by health professionals in primary care with a usual care control group or another control group that did not involve physical activity.

STUDY SELECTION AND ANALYSIS

Two independent reviewers screened the search results, extracted data from eligible trials and assessed the risk of bias using the Cochrane risk of bias tool (version 2). Inverse variance meta-analyses using random effects models examined the primary outcome of difference between the groups in MVPA (min/week) from baseline to final follow-up. The odds of meeting the guidelines for MVPA at follow-up were also analysed.

RESULTS

14 566 unique reports were identified and 46 randomised controlled trials with a range of follow-ups (3-60 months) were included in the meta-analysis (n=16 198 participants). Physical activity interventions delivered or prompted by health professionals in primary care increased MVPA by 14 min/week (95% confidence interval 4.2 to 24.6, P=0.006). Heterogeneity was substantial (I2=91%, P<0.001). Limiting analyses to trials that used a device to measure physical activity showed no significant group difference in MVPA (mean difference 4.1 min/week, 95% confidence interval -1.7 to 9.9, P=0.17; I2=56%, P=0.008). Trials that used self-report measures showed that intervention participants achieved 24 min/week more MVPA than controls (95% confidence interval 6.3 to 41.8, P=0.008; I2=72%, P<0.001). Additionally, interventions increased the odds of patients meeting guidelines for MVPA by 33% (95% confidence interval 1.17 to 1.50, P<0.001; I2=25%, P=0.11) versus controls. 14 of 46 studies were at high risk of bias but sensitivity analyses excluding these studies did not alter the results.

CONCLUSIONS

Physical activity interventions delivered or prompted by health professionals in primary care appear effective at increasing participation in self-reported MVPA. Such interventions should be considered for routine implementation to increase levels of physical activity and improve health outcomes in the population.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42021209484.

Quality assessment of smartphone fitness apps used to increase physical activity level and improve general health in adults: A systematic review

Introduction

Mobile exercise apps for smartphones have been used with intervention measures to increase physical activity. This study aimed to identify and evaluate the quality of fitness apps for smartphones that were used to increase the level of physical activity and improve the overall health of healthy adults.

Methods

The systematic review was performed in five electronic databases EMBASE, MEDLINE, CINAHL, Academic Research Premier e Cochrane Reviews, and Trials. The search terms were grouped into three categories according to the principles of population, intervention, comparison, and outcomes. The following includes examples of the group terms: population (healthy adults), intervention (smartphone apps), and outcomes (physical activity level).

Results

Of the 3924 potential articles, 74 were read for full-text analysis. Only seven studies were included in the review. The methodological evaluation of the studies and the apps’ quality showed that only one study and one app were evaluated with good quality. All studies used a type of application to improve the level of physical activity (measured by the number of daily steps), reporting an increase and improvement in some general health indices (calorie expenditure, weight, BMI) in healthy adults, regardless of frequency and duration of intervention and applications.

Conclusion

We cannot say that the use of smartphone applications improves the level of physical activity and general health. The low methodological quality of the studies and the possibility to evaluate the applications used (Mars Scale) due to the lack of technical standardization presented in the studies, despite the app used showing positive results in all studies.

Technology-based nutrition interventions using the Mediterranean diet: a systematic review

CONTEXT

Over the past 2 decades, overweight and obesity rates have increased exponentially, along with related comorbidities including type 2 diabetes, hypertension, cardiovascular disease, and some cancers. The Mediterranean Diet (MDiet) has been suggested as a potential way to mitigate the health burdens related to overweight and obesity.

OBJECTIVE

For this review, the literature on MDiet-focused digital interventions was examined to determine efficacy, best practices, and potential limitations.

DATA SOURCES

The search was conducted across 15 databases for relevant publications published through April 2020 in English, French, Spanish, Arabic, or Italian.

DATA EXTRACTION

Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed using a combination of keywords and phrases and evaluated independently for relevance, merit, and inclusion and exclusion criteria.

DATA ANALYSIS

The systematic literature review resulted in 15 articles that met the search criteria. Ten interventions were delivered online, and 5 were delivered via smartphone using an app. The majority of online MDiet-focused interventions were effective, particularly when modeled after evidence-based and best-practice online nutrition education interventions. Such interventions also are effective for promoting positive health behaviors and health outcomes, such as increased physical activity, increased levels of high-density lipoprotein cholesterol, and a lower total high-density lipoprotein cholesterol ratio.

CONCLUSION

Technology-based interventions to educate and promote adherence to the MDiet are successful in helping individuals achieve the stated outcomes. More research is needed to determine the efficacy of MDiet interventions delivered via smartphone apps.

Associations between Digital Health Intervention Engagement and Dietary Intake: A Systematic Review

There has been a proliferation of digital health interventions (DHIs) targeting dietary intake. Despite their potential, the effectiveness of DHIs are thought to be dependent, in part, on user engagement. However, the relationship between engagement and the effectiveness of dietary DHIs is not well understood. The aim of this review is to describe the association between DHI engagement and dietary intake. A systematic search of four electronic databases and grey literature for records published before December 2019 was conducted. Studies were eligible if they examined a quantitative association between objective measures of engagement with a DHI (subjective experience or usage) and measures of dietary intake in adults (aged ≥18 years). From 10,653 citations, seven studies were included. Five studies included usage measures of engagement and two examined subjective experiences. Narrative synthesis, using vote counting, found mixed evidence of an association with usage measures (5 of 12 associations indicated a positive relationship, 7 were inconclusive) and no evidence regarding an association with subjective experience (both studies were inconclusive). The findings provide early evidence supporting an association between measures of usage and dietary intake; however, this was inconsistent. Further research examining the association between DHI engagement and dietary intake is warranted.

Effectiveness of Smartphone-Based Physical Activity Interventions on Individuals' Health Outcomes: A Systematic Review

Design

A systematic review. Data Sources. 114 studies were gathered using the following search descriptors: (“mobile phone” OR “smartphone” OR “cell phone” OR “mobile device” OR “mobile apps” OR “mHealth”) AND (“exercise” OR “physical activity” OR “physical fitness” OR “motor activity”) AND (“physiological outcomes” OR “weight outcomes” OR “psychological outcomes” OR “health” OR “health behavior”). Seven databases were used including databases such as Academic Search Premier and PubMed. PRISMA guidelines were followed in this review. Eligibility Criteria for Selecting Studies. The 20 articles included in this review met the following inclusion criteria: (1) randomized and controlled trials, (2) involving an outcome variable measured by accelerometer, and (3) intervention enforced by a smartphone application.

Results

Overall, 56% of the studies reviewed in this paper resulted in successful interventions. Of the 19 articles that examined the first individual health outcome of physical and physiological outcomes, 11 interventions resulted in a positive effect on one of the following parameters: MVPA/step count, sedentary behavior, cardiorespiratory fitness, and blood pressure. Six interventions examined the effects on the second individual health outcome, weight-related outcomes. Five of these interventions observed significant positive effects from mobile application interventions on weight and waist circumference. Six articles evaluated the effectiveness of smartphone-based physical activity interventions on the third and final individual health outcome, psychological outcomes, with four resulting in significant positive outcomes in self-efficacy, life enjoyment/satisfaction, and intrinsic PA motivation.

Conclusion

The findings in this review suggest that mobile application physical activity interventions, compared to unguided exercise activities, can effectively improve certain health outcomes for individuals such as physical/physiological and weight-related outcomes. It was found that research in the area of effectiveness of mobile application interventions on specific psychosocial health outcomes such as self-efficacy, life enjoyment, and intrinsic PA motivation is limited. Thus, the effect of mobile health applications remains unclear for psychosocial outcomes. Due to this limitation, more research is warranted to confirm the findings of this review.

Engineered diets to improve cancer outcomes

Cancer cells acquire a diverse range of metabolic adaptations that support their enhanced rates of growth and proliferation. While these adaptations help tune metabolism to support higher anabolic output and bolster antioxidant defenses, they can also decrease metabolic flexibility and increase dependence on nutrient uptake versus de novo synthesis. Diet is the major source of nutrients that ultimately support tumor growth, yet the potential impact of diet is currently underutilized during the treatment of cancer. Here, we review several forms of dietary augmentation therapy including those that alter the content of food, such as energy or macronutrient restriction, and those that alter the timing of food consumption, like intermittent fasting regimens. We discuss how these dietary strategies can be combined with pharmacologic therapies to exaggerate the metabolic liabilities of different cancer types.

Design, deployment, and usability of a mobile system for cardiovascular health monitoring within the electronic Framingham Heart Study

Background

The electronic Framingham Heart Study (eFHS) is an ongoing nested study, which includes FHS study participants, examining associations between health data from mobile devices with cardiovascular risk factors and disease.

Objective

To describe application (app) design, report user characteristics, and describe usability and survey response rates.

Methods

Eligible FHS participants were consented and offered a smartwatch (Apple Watch), a digital blood pressure (BP) cuff, and the eFHS smartphone app for administering surveys remotely. We assessed usability of the new app using 2 domains (functionality, aesthetics) of the Mobile App Rating Scale (MARS) and assessed survey completion rates at baseline and 3 months.

Results

A total of 196 participants were recruited using the enhanced eFHS app. Of these, 97 (49.5%) completed the MARS instrument. Average age of participants was 53 ± 9 years, 51.5% were women, and 93.8% were white. Eighty-six percent of participants completed at least 1 measure on the baseline survey, and 50% completed the 3-month assessment. Overall subjective score of the app was 4.2 ± 0.7 on a scale from 1 to 5 stars. Of those who shared their health data with others, 46% shared their BP and 7.7% shared their physical activity with a health care provider.

Conclusion

Participants rated the new, enhanced eFHS app positively overall. Mobile app survey completion rates were high, consistent with positive in-app ratings from participants. These mobile data collection modalities offer clinicians new opportunities to engage in conversations about health behaviors.

Nutrition and physical activity interventions for the general population with and without cardiometabolic risk: a scoping review

OBJECTIVE

The objective of this scoping review was to examine the research question: In the adults with or without cardiometabolic risk, what is the availability of literature examining interventions to improve or maintain nutrition and physical activity-related outcomes? Sub-topics included: (1) behaviour counseling or coaching from a dietitian/nutritionist or exercise practitioner, (2) mobile applications to improve nutrition and physical activity and (3) nutritional ergogenic aids.

DESIGN

The current study is a scoping review. A literature search of the Medline Complete, CINAHL Complete, Cochrane Database of Systematic Reviews and other databases was conducted to identify articles published in the English language from January 2005 until May 2020. Data were synthesised using bubble charts and heat maps.

SETTING

Out-patient, community and workplace.

PARTICIPANTS

Adults with or without cardiometabolic risk factors living in economically developed countries.

RESULTS

Searches resulted in 19 474 unique articles and 170 articles were included in this scoping review, including one guideline, thirty systematic reviews (SR), 134 randomised controlled trials and five non-randomised trials. Mobile applications (n 37) as well as ergogenic aids (n 87) have been addressed in several recent studies, including SR. While primary research has examined the effect of individual-level nutrition and physical activity counseling or coaching from a dietitian/nutritionist and/or exercise practitioner (n 48), interventions provided by these practitioners have not been recently synthesised in SR.

CONCLUSION

SR of behaviour counseling or coaching provided by a dietitian/nutritionist and/or exercise practitioner are needed and can inform practice for practitioners working with individuals who are healthy or have cardiometabolic risk.

Sociodemographic Characteristics Predicting Digital Health Intervention Use After Acute Myocardial Infarction

Increasing evidence suggests that digital health interventions (DHIs) are an effective tool to reduce hospital readmissions by improving adherence to guideline-directed therapy. We investigated whether sociodemographic characteristics influence use of a DHI targeting 30-day readmission reduction after acute myocardial infarction (AMI). Covariates included age, sex, race, native versus loaner iPhone, access to a Bluetooth-enabled blood pressure monitor, and disease severity as marked by treatment with CABG. Age, sex, and race were not significantly associated with DHI use before or after covariate adjustment (fully adjusted OR 0.98 (95%CI: 0.95-1.01), 0.6 (95%CI: 0.29-1.25), and 1.22 (95% CI: 0.60-2.48), respectively). Being married was associated with high DHI use (OR 2.12; 95% CI 1.02-4.39). Our findings suggest that DHIs may have a role in achieving equity in cardiovascular health given similar use by age, sex, and race. The presence of a spouse, perhaps a proxy for enhanced caregiver support, may encourage DHI use.

Primary Health Care Providers' Perspectives on Developing an eHealth Tool for Physical Activity Counselling: A Qualitative Study

Purpose

Physical inactivity is a global health concern. Physical activity (PA) counselling is an effective intervention for promoting PA in primary health care (PHC) settings. The use of electronic health (eHealth) technology has the potential to support PA counselling. This study aimed to explore PHC providers’ perspectives on the development of an eHealth tool to aid PA counselling in the resource-limited settings.

Methods

This qualitative study employed interpretive phenomenology. The study was conducted at hospital-based PHC clinics among physicians and registered nurses. Data collection involved in-depth interviews (IDIs) and focus group discussions (FGDs). An inductive thematic approach was used to analyze the data.

Results

Three physicians participated in three IDIs and 12 nurses participated in four FGDs at three hospitals. The median age of the participants was 43 years. Participants saw 15–100 patients/day (median 40) and spent 2–20 min with each patient (median 5). Three themes emerged. Theme 1: requirements for PA counselling: the participants reflected the needs and characteristics of eHealth tool that may support PA counselling. Theme 2: enabling an eHealth tool for PA counselling: the eHealth should be easy to use, provide PA prescription function, and support follow-up PA counselling. Theme 3: reducing barriers to PA counselling: the eHealth tool was expected to help reduce service and workforce barriers and patients’ limitations.

Conclusion

A well-designed and practical eHealth tool has the potential to improve PA counselling practice in PHC settings. The eHealth tool may affect an indirect mechanism to reduce barriers to PA counselling. Future research should focus on the usability and utility as well as the process evaluation of the PA counselling eHealth tool that will be implemented in resource-limited settings.

User Engagement With Smartphone Apps and Cardiovascular Disease Risk Factor Outcomes: Systematic Review

Background

The use of mobile health (mHealth) interventions, including smartphone apps, for the prevention of cardiovascular disease (CVD) has demonstrated mixed results for obesity, hypercholesterolemia, diabetes, and hypertension management. A major factor attributing to the variation in mHealth study results may be mHealth user engagement.

Objective

This systematic review aims to determine if user engagement with smartphone apps for the prevention and management of CVD is associated with improved CVD health behavior change and risk factor outcomes.

Methods

We conducted a comprehensive search of PubMed, CINAHL, and Embase databases from 2007 to 2020. Studies were eligible if they assessed whether user engagement with a smartphone app used by an individual to manage his or her CVD risk factors was associated with the CVD health behavior change or risk factor outcomes. For eligible studies, data were extracted on study and sample characteristics, intervention description, app user engagement measures, and the relationship between app user engagement and the CVD risk factor outcomes. App user engagement was operationalized as general usage (eg, number of log-ins or usage days per week) or self-monitoring within the app (eg, total number of entries made in the app). The quality of the studies was assessed.

Results

Of the 24 included studies, 17 used a randomized controlled trial design, 4 used a retrospective analysis, and 3 used a single-arm pre- and posttest design. Sample sizes ranged from 55 to 324,649 adults, with 19 studies recruiting participants from a community setting. Most of the studies assessed weight loss interventions, with 6 addressing additional CVD risk factors, including diabetes, sleep, stress, and alcohol consumption. Most of the studies that assessed the relationship between user engagement and reduction in weight (9/13, 69%), BMI (3/4, 75%), body fat percentage (1/2, 50%), waist circumference (2/3, 67%), and hemoglobin A_1c (3/5, 60%) found statistically significant results, indicating that greater app user engagement was associated with better outcomes. Of 5 studies, 3 (60%) found a statistically significant relationship between higher user engagement and an increase in objectively measured physical activity. The studies assessing the relationship between user engagement and dietary and diabetes self-care behaviors, blood pressure, and lipid panel components did not find statistically significant results.

Conclusions

Increased app user engagement for prevention and management of CVD may be associated with improved weight and BMI; however, only a few studies assessed other outcomes, limiting the evidence beyond this. Additional studies are needed to assess user engagement with smartphone apps targeting other important CVD risk factors, including dietary behaviors, hypercholesterolemia, diabetes, and hypertension. Further research is needed to assess mHealth user engagement in both inpatient and outpatient settings to determine the effect of integrating mHealth interventions into the existing clinical workflow and on CVD outcomes.

Usability and utility of eHealth for physical activity counselling in primary health care: a scoping review

Background

Physical activity (PA) counselling is an effective approach to promote PA in primary health care (PHC). Barriers to PA counselling in PHC include time constraints, lack of knowledge and skills of providers, and systemic barriers. Using electronic health (eHealth) has the potential to promote PA. This scoping review aimed to identify usability and utility of eHealth for tailored PA counselling introduced in PHC settings.

Methods

A scoping review included primary research articles. The authors systematically searched six databases (Cochrane Library, CINAHL Complete, Embase, PubMed, Scopus and Web of Science) from the inception of the databases. The search terms consisted of three search components: intervention (PA counselling), platform (eHealth), and setting (PHC). Additional articles were included through reference lists. The inclusion criteria were research or original articles with any study designs in adult participants.

Results

Of 2501 articles after duplicate removal, 2471 articles were excluded based on the title and abstract screening and full text review. A total of 30 articles were included for synthesis. The eHealth tools had a wide range of counselling domains as a stand-alone PA domain and multiple health behaviours. The included articles presented mixed findings of usability and utility of eHealth for PA counselling among patients and providers in PHC settings. Technical problems and the complexity of the programmes were highlighted as barriers to usability. The majority of articles reported effective utility, however, several articles stated unfavourable outcomes.

Conclusions

eHealth has the potential to support PA counselling in PHC. Facilitators and barriers to eHealth usability should be considered and adapted to particular settings and contexts. The utility of eHealth for promoting PA among patients should be based on the pragmatic basis to optimise resources.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-020-01304-9.

The effects of step-count monitoring interventions on physical activity: systematic review and meta-analysis of community-based randomised controlled trials in adults

Background

Step-count monitors (pedometers, body-worn trackers and smartphone applications) can increase walking, helping to tackle physical inactivity. We aimed to assess the effect of step-count monitors on physical activity (PA) in randomised controlled trials (RCTs) amongst community-dwelling adults; including longer-term effects, differences between step-count monitors, and between intervention components.

Methods

Systematic literature searches in seven databases identified RCTs in healthy adults, or those at risk of disease, published between January 2000–April 2020. Two reviewers independently selected studies, extracted data and assessed risk of bias. Outcome was mean differences (MD) with 95% confidence intervals (CI) in steps at follow-up between treatment and control groups. Our preferred outcome measure was from studies with follow-up steps adjusted for baseline steps (change studies); but we also included studies reporting follow-up differences only (end-point studies). Multivariate-meta-analysis used random-effect estimates at different time-points for change studies only. Meta-regression compared effects of different step-count monitors and intervention components amongst all studies at ≤4 months.

Results

Of 12,491 records identified, 70 RCTs (at generally low risk of bias) were included, with 57 trials (16,355 participants) included in meta-analyses: 32 provided change from baseline data; 25 provided end-point only. Multivariate meta-analysis of the 32 change studies demonstrated step-counts favoured intervention groups: MD of 1126 steps/day 95%CI [787, 1466] at ≤4 months, 1050 steps/day [602, 1498] at 6 months, 464 steps/day [301, 626] at 1 year, 121 steps/day [− 64, 306] at 2 years and 434 steps/day [191, 676] at 3–4 years. Meta-regression of the 57 trials at ≤4 months demonstrated in mutually-adjusted analyses that: end-point were similar to change studies (+ 257 steps/day [− 417, 931]); body-worn trackers/smartphone applications were less effective than pedometers (− 834 steps/day [− 1542, − 126]); and interventions providing additional counselling/incentives were not better than those without (− 812 steps/day [− 1503, − 122]).

Conclusions

Step-count monitoring leads to short and long-term step-count increases, with no evidence that either body-worn trackers/smartphone applications, or additional counselling/incentives offer further benefit over simpler pedometer-based interventions. Simple step-count monitoring interventions should be prioritised to address the public health physical inactivity challenge.

Systematic review registration

PROSPERO number CRD42017075810.

Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review

Background

With a growing focus on patient interaction with health management, mobile apps are increasingly used to deliver behavioral health interventions. The large variation in these mobile health apps—their target patient group, health behavior, and behavioral change strategies—has resulted in a large but incohesive body of literature.

Objective

This systematic review aimed to assess the effectiveness of mobile apps in improving health behaviors and outcomes and to examine the inclusion and effectiveness of behavior change techniques (BCTs) in mobile health apps.

Methods

PubMed, EMBASE, CINAHL, and Web of Science were systematically searched for articles published between 2014 and 2019 that evaluated mobile apps for health behavior change. Two authors independently screened and selected studies according to the eligibility criteria. Data were extracted and the risk of bias was assessed by one reviewer and validated by a second reviewer.

Results

A total of 52 randomized controlled trials met the inclusion criteria and were included in the analysis—37 studies focused on physical activity, diet, or a combination of both, 11 on drug and alcohol use, and 4 on mental health. Participant perceptions were generally positive—only one app was rated as less helpful and satisfactory than the control—and the studies that measured engagement and usability found relatively high study completion rates (mean 83%; n=18, N=39) and ease-of-use ratings (3 significantly better than control, 9/15 rated >70%). However, there was little evidence of changed behavior or health outcomes.

Conclusions

There was no strong evidence in support of the effectiveness of mobile apps in improving health behaviors or outcomes because few studies found significant differences between the app and control groups. Further research is needed to identify the BCTs that are most effective at promoting behavior change. Improved reporting is necessary to accurately evaluate the mobile health app effectiveness and risk of bias.

Factors influencing user's adherence to physical activity applications: A scoping literature review and future directions

BACKGROUND

Although mobile app-delivered physical activity (PA) interventions have the potential to promote exercise, poor adherence to these apps is a common issue impeding their effectiveness. Gaining insights into the factors that influence PA app adherence is an important priority for app developers and intervention designers.

OBJECTIVE

The objective of this study is to perform a literature review to synthesize the factors influencing PA app adherence and to identify directions for future research in this area.

METHODS

A scoping review of prior research was conducted to uncover the factors influencing PA app adherence. Seven online journal databases were searched for relevant articles published from January 1, 2014, to December 31, 2018. The initial search identified 5,572 articles. After a screening and eligibility check based on inclusion criteria, 24 articles were finally selected. The definition of PA app adherence in this review could be categorized along four dimensions derived from previous studies: i.e., frequency of PA app usage, intention/motivation to sustain use of the PA app, degree of function use within the PA app, and the duration of PA app usage.

RESULTS

Of the 24 included studies (both qualitative and quantitative), 12 studies were conducted in the U.S. The methods and study designs varied considerably, with the study durations ranging from 2 weeks to 24 months. The synthesized evidence indicates that 89 distinct factors influenced PA app adherence, and these could be classified into three categories: Personal Factors (n = 28), Technology Features (n = 53), and Contextual Factors (n = 8). Nine more detailed sub-categories were also compiled. Factors in sub-categories, such as psychological factors, health-related factors and predefined goals, are essential for physical activity behavior change experts to implement interventions. Factors in technology features, including PA tracking, PA goal setting and customization of exercise, are specifically useful for PA app developers or PA intervention designers. Overall, evidence of causal factors was limited. Only 5 of the 24 articles explored causal factors that affect PA app adherence. Furthermore, longitudinal studies with long durations were also limited.

CONCLUSIONS

Uncovering the factors influencing PA app adherence is critical as it can expand our current knowledge and provide guidance for app-delivered PA interventions, as well as the design of PA apps. This scoping review identified and categorized factors that influence PA app adherence in prior studies. Based on the evidence synthesized, users are paying more attention to the "playfulness" and personalized features of PA apps, in addition to basic functional requirements. Also, app glitches are the most common factors found to negatively influence app adherence. Several important directions for future research are highlighted in this review, especially the design of studies to explore causality.

Assessment of the Efficacy, Safety, and Effectiveness of Weight Control and Obesity Management Mobile Health Interventions: Systematic Review

BACKGROUND

The use of apps to tackle overweight and obesity by tracking physical and dietary patterns and providing recommendations and motivation strategies to achieve personalized goals has increased over recent years. However, evidence of the efficacy, effectiveness, and safety of these apps is severely lacking.

OBJECTIVE

The aim of this study was to identify efficacy, safety, and effectiveness criteria used to assess weight control, overweight, and obesity management in mobile health (mHealth) interventions through a systematic review.

METHODS

PubMed, PsycINFO, Scopus, UK Trial Database, ClinicalTrials.gov, and the Cochrane Library were surveyed up to May 2018. All types of clinical studies were considered. A total of 2 independent reviewers assessed quality using Scottish Intercollegiate Guidelines Network (SIGN) criteria. Ratings were used to provide an overall score for each study (low, moderate, or high). Data were synthesized in evidence tables.

RESULTS

From 233 potentially relevant publications, only 28 studies were included. Of these, 13 (46%) were randomized control trials, 11 were single-arm studies (39%), 3 were nonrandomized controlled trials (11%), and 1 study was a cluster randomized trial (4%). The studies were classified as low (15), high (7), and moderate (6) quality according to SIGN criteria. All studies focused on efficacy, with only 1 trial mentioning safety and another 1 effectiveness. In 11 studies, the apps were used as stand-alone interventions, the others were multicomponent studies that included other tools for support such as sensors or websites. The main management tool included in the apps was feedback messaging (24), followed by goal-setting mechanisms (20) and self-monitoring (19). The majority of studies took weight or body mass index loss as the main outcome (22) followed by changes in physical activity (14) and diet (12). Regarding outputs, usability, adherence, and engagement (17) were the most reported, followed by satisfaction (7) and acceptability (4).

CONCLUSIONS

There is a remarkable heterogeneity among these studies and the majority have methodological limitations that leave considerable room for improvement. Further research is required to identify all relevant criteria for assessing the efficacy of mHealth interventions in the management of overweight and obesity.

TRIAL REGISTRATION

PROSPERO CRD42017056761; https://tinyurl.com/y2zhxtjx.

Your Personal Motivator is with You: A Systematic Review of Mobile Phone Applications Aiming at Increasing Physical Activity

BACKGROUND

Literature shows mixed evidence about the power of mobile phone applications to foster physical activity. A systematic integration that offers insights into which mobile phone application techniques can or cannot foster physical activity is lacking, as is a theoretical integration of current research.

OBJECTIVES

We performed a systematic review guided by a theoretical framework focusing on effects that certain mobile phone application techniques have on physical activity, to improve our understanding of what techniques are more or less effective.

METHODS

We identified articles by searching EBSCO Business Source Complete, Science Direct, PsycINFO, Springer, PLoS ONE, Taylor and Francis, IEEE, Social Science Citation Index, Science Citation Index Expanded, PUBMED, MEDLINE, and Google Scholar. We considered articles if (1) they referred to the use of mobile phone applications to promote physical activity; (2) their methodological approach allowed one to derive appropriate results (e.g., intervention-based approach, observational study); (3) they were published in peer-reviewed journals or conference proceedings; and (4) they were written in English. The literature search resulted in 41 usable studies. Meta-synthesis and vote counting were applied to analyze these studies.

RESULTS

Based on the ratio of supportive versus non-supportive evidence in both the qualitative and the quantitative studies, we propose the following descending rank order for the effectiveness of application techniques to foster physical activity. This is tentative in nature because the current overall small body of literature made coming to definite conclusions difficult: (1) feedback, (2) goal setting and its sub-forms, (3) competition, social sharing with familiar users in both segregated and social network groups, and (4) social sharing with strangers in segregated groups, reward, and social sharing with strangers in social network groups. Rewards in particular provided mixed results, and social sharing with strangers in segregated and social network groups seemed rather ineffective but may work under special conditions that need to be identified in additional research. One limitation of our study was that our results are mostly derived from qualitative studies, since quantitative studies are underrepresented in the field.

CONCLUSION

Several mobile phone application techniques were identified that have the potential to foster physical activity, whereas others were identified that are unlikely to increase physical activity. Major avenues for future research include more theoretical development and more quantitative studies, among others.

Short- and Long-term Effects of a Mobile Phone App in Conjunction With Brief In-Person Counseling on Physical Activity Among Physically Inactive Women: The mPED Randomized Clinical Trial

IMPORTANCE

Mobile phone applications (apps) and activity trackers allow researchers to remotely deliver an intervention and monitor physical activity but have not been rigorously evaluated for longer periods.

OBJECTIVE

To determine whether a mobile phone-based physical activity education app, in conjunction with brief in-person counseling, increases and then maintains levels of physical activity.

DESIGN, SETTING, AND PARTICIPANTS

In this parallel randomized clinical trial, community-dwelling physically inactive women recruited between May 2011 and April 2014 were randomized in equal proportions into the control (n = 69), regular (n = 71), and plus (n = 70) groups. Data were analyzed using intention to treat from September 16, 2016, through June 30, 2018.

INTERVENTIONS

The regular and plus groups were instructed to use the app on their mobile phone and an accelerometer every day for 3 months and attend brief in-person counseling. During the 6-month maintenance period, the plus group continued to use the app and accelerometer, while the regular group stopped using the app but continued using the accelerometer. The control group used the accelerometer throughout.

MAIN OUTCOMES AND MEASURES

The primary and secondary outcomes were daily accelerometer-measured total steps and time spent in moderate to vigorous physical activity (MVPA).

RESULTS

The 210 participants had a mean (SD) age of 52.4 (11.0) years. At baseline, the mean (SD) daily total steps by accelerometer in the control, regular, and plus groups were 5384 (2920), 5063 (2526), and 5837 (3235), respectively. During the 3-month intervention period, daily steps and MVPA increased in the combined regular and plus groups compared with the control group (between-group differences, 2060 steps per day; 95% CI, 1296-2825 steps per day; P < .001 and 18.2 min/d MVPA; 95% CI, 10.9-25.4 min/d MVPA; P < .001). During the subsequent 6-month maintenance period, mean activity level remained higher in the combined plus and regular groups than among controls (between-group difference, 1360 steps per day; 95% CI, 694-2026 steps per day; P <. 001), but trends in total daily steps and MVPA were similar in the plus and regular groups.

CONCLUSIONS AND RELEVANCE

In this trial, the intervention groups substantially increased their physical activity. However, use of both the app and accelerometer for an additional 6 months after the initial 3-month intervention did not help to maintain increases in physical activity compared with continued use of the accelerometer alone.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01280812.

What is the role of smartphones on physical activity promotion? A systematic review and meta-analysis

OBJECTIVES

To identify and evaluate the effect of interventions that used cell phones as a means to promote physical activity (PA).

METHODS

The databases searched were MedLine/PubMed, Scopus, SPORTDiscus, PsycINFO, Science Direct, Lilacs, and SciELO. After removing duplicates, applying exclusion criteria, and checking the reference lists, 45 studies were reviewed. The Downs and Black (D&B) scale measured methodological quality, and a random effect model was used to compute the meta-analysis of PA by the reported unit (minutes per day or steps per day), delivery agent (application (APP), SMS, or other), and PA measurement (questionnaire, accelerometer, pedometer).

RESULTS

Mobile phone-based PA interventions were efficient in increasing both minutes [10.49; CI (3.37-17.60); p = 0.004] and steps per day [735.17; CI (227.72-1242.61); p = 0.005] in adults when compared to baseline. Furthermore, APP-based interventions were able to increase the number of steps (p = 0.04) and minutes per day of PA (p = 0.04) in adults. Also, 85% of included manuscripts were classified as moderate- to high-quality articles.

CONCLUSIONS

Mobile phone-based PA interventions, inclusive those delivery by APP, were effective to increase minutes and steps per day in adults.

Combined use of smartphone and smartband technology in the improvement of lifestyles in the adult population over 65 years: study protocol for a randomized clinical trial (EVIDENT-Age study)

BACKGROUND

The increasing use of smartphones by older adults also increases their potential for improving different aspects of health in this population. Some studies have shown promising results in the improvement of cognitive performance through lifestyle modification. All this may have a broad impact on the quality of life and carrying out daily living activities. The objective of this study is to evaluate the effectiveness of combining the use of smartphone and smartband technology for 3 months with brief counseling on life habits, as opposed to providing counseling only, in increasing physical activity and improving adherence to the Mediterranean diet. Secondary objectives are to assess the effect of the intervention on body composition, quality of life, independence in daily living activities and cognitive performance.

METHODS

This study is a two-arm cluster-randomized trial that will be carried out in urban health centers in Spain. We will recruit 160 people aged between 65 and 80 without cardiovascular disease or cognitive impairment (score in the Mini-mental State Examination ≥24). On a visit to their center, intervention group participants will be instructed to use a smartphone application for a period of 3 months. This application integrates information on physical activity received from a fitness bracelet and self-reported information on the patient's daily nutritional composition. The primary outcome will be the change in the number of steps measured by accelerometer. Secondary variables will be adherence to the Mediterranean diet, sitting time, body composition, quality of life, independence in daily living activities and cognitive performance. All variables will be measured at baseline and on the assessment visit after 3 months. A telephone follow-up will be carried out at 6 months to collect self-reported data regarding physical activity and adherence to the Mediterranean diet.

DISCUSSION

Preventive healthy aging programs should include health education with training in nutrition and lifestyles, while stressing the importance of and enhancing physical activity; the inclusion of new technologies can facilitate these goals. The EVIDENT-AGE study will incorporate a simple, accessible intervention with potential implementation in the care of older adults.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03574480 . Date of trial Registration July 2, 2018.

Feasibility and Acceptability of Technology-Based Exercise and Posture Training in Older Adults With Age-Related Hyperkyphosis: Pre-Post Study

Background

Hyperkyphosis is common among older adults and is associated with multiple adverse health outcomes. Kyphosis-specific exercise and posture training programs improve hyperkyphosis, but in-person programs are expensive to implement and maintain over long periods. It is unclear if a technology-based posture training program disseminated through a mobile phone is a feasible or acceptable alternative to in-person training among older adults with hyperkyphosis.

Objective

The primary purpose was to assess the feasibility of subject recruitment, short-term retention and adherence, and acceptability of a technology-based exercise and posture training program disseminated as video clip links and text messaging prompts via a mobile phone. The secondary purpose was to explore the potential efficacy of this program for kyphosis, physical function, and health-related quality of life in older adults with hyperkyphosis.

Methods

In this 6-week pre-post design pilot trial, we recruited community-dwelling adults aged ≥65 years with hyperkyphosis ≥40° (±5°) and access to a mobile phone. The intervention had two parts: (1) exercise and posture training via video clips sent to participants daily via text messaging, including 6 weekly video clip links to be viewed on the participant’s mobile phone, and (2) text messaging prompts to practice good posture. We analyzed the subject recruitment, adherence, retention, and acceptability of the intervention. Outcomes included change in kyphometer-measured kyphosis, occiput-to-wall (OTW) distance, Short Physical Performance Battery score, Scoliosis Research Society (SRS-30) score, Center for Epidemiological Studies Depression score, and Physical Activity Scale for the Elderly (PASE) score.

Results

A total of 64 potential participants were recruited, 17 were enrolled, and 12 completed postintervention testing at 6 weeks. The average age was 71.6 (SD 4.9) years, and 50% were women. The median adherence to daily video viewing was 100% (range, 14%-100%) and to practicing good posture at least three times per day was 71% (range, 0%-100%). Qualitative evaluation of intervention acceptability revealed that the mobile phone screen was too small for participants to view the videos well and daily prompts to practice posture were too frequent. Kyphosis, OTW distance, and physical activity significantly improved after the 6-week intervention. Kyphosis decreased by 8° (95% CI –12 to –5; P<.001), OTW decreased by 1.9 cm (95% CI –3.3 to –0.7; P=.007), and physical activity measured by PASE increased by 29 points (95% CI 3 to 54; P=.03). The health-related quality of life SRS-30 score increased by 0.11 point (SD 0.19), but this increase was not statistically significant (P=.09).

Conclusions

Technology-based exercise and posture training using video clip viewing and text messaging reminders is feasible and acceptable for a small cohort of older adults with hyperkyphosis. Technology-based exercise and posture training warrants further study as a potential self-management program for age-related hyperkyphosis, which may be more easily disseminated than in-person training.