A systematic review on eHealth technology personalization approaches

Despite the widespread use of personalization of eHealth technologies, there is a lack of comprehensive understanding regarding its application. This systematic review aims to bridge this gap by identifying and clustering different personalization approaches based on the type of variables used for user segmentation and the adaptations to the eHealth technology and examining the role of computational methods in the literature. From the 412 included reports, we identified 13 clusters of personalization approaches, such as behavior + channeling and environment + recommendations. Within these clusters, 10 computational methods were utilized to match segments with technology adaptations, such as classification-based methods and reinforcement learning. Several gaps were identified in the literature, such as the limited exploration of technology-related variables, the limited focus on user interaction reminders, and a frequent reliance on a single type of variable for personalization. Future research should explore leveraging technology-specific features to attain individualistic segmentation approaches.

Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity

BACKGROUND

Obesity is considered to be a risk factor for various diseases, and its incidence has tripled worldwide since 1975. In addition to potentially being at risk for adverse health outcomes, people with overweight or obesity are often stigmatised. Behaviour change interventions are increasingly delivered as mobile health (m-health) interventions, using smartphone apps and wearables. They are believed to support healthy behaviours at the individual level in a low-threshold manner.

OBJECTIVES

To assess the effects of integrated smartphone applications for adolescents and adults with overweight or obesity.

SEARCH METHODS

We searched CENTRAL, MEDLINE, PsycINFO, CINAHL, and LILACS, as well as the trials registers ClinicalTrials.gov and World Health Organization International Clinical Trials Registry Platform on 2 October 2023 (date of last search for all databases). We placed no restrictions on the language of publication.

SELECTION CRITERIA

Participants were adolescents and adults with overweight or obesity. Eligible interventions were integrated smartphone apps using at least two behaviour change techniques. The intervention could target physical activity, cardiorespiratory fitness, weight loss, healthy diet, or self-efficacy. Comparators included no or minimal intervention (NMI), a different smartphone app, personal coaching, or usual care. Eligible studies were randomised controlled trials of any duration with a follow-up of at least three months.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methodology and the RoB 2 tool. Important outcomes were physical activity, body mass index (BMI) and weight, health-related quality of life, self-efficacy, well-being, change in dietary behaviour, and adverse events. We focused on presenting studies with medium- (6 to < 12 months) and long-term (≥ 12 months) outcomes in our summary of findings table, following recommendations in the core outcome set for behavioural weight management interventions.

MAIN RESULTS

We included 18 studies with 2703 participants. Interventions lasted from 2 to 24 months. The mean BMI in adults ranged from 27 to 50, and the median BMI z-score in adolescents ranged from 2.2 to 2.5. Smartphone app versus no or minimal intervention Thirteen studies compared a smartphone app versus NMI in adults; no studies were available for adolescents. The comparator comprised minimal health advice, handouts, food diaries, smartphone apps unrelated to weight loss, and waiting list. Measures of physical activity: at 12 months' follow-up, a smartphone app compared to NMI probably reduces moderate to vigorous physical activity (MVPA) slightly (mean difference (MD) -28.9 min/week (95% confidence interval (CI) -85.9 to 28; 1 study, 650 participants; moderate-certainty evidence)). We are very uncertain about the results of estimated energy expenditure and cardiorespiratory fitness at eight months' follow-up. A smartphone app compared with NMI probably results in little to no difference in changes in total activity time at 12 months' follow-up and leisure time physical activity at 24 months' follow-up. Anthropometric measures: a smartphone app compared with NMI may reduce BMI (MD of BMI change -2.6 kg/m2, 95% CI -6 to 0.8; 2 studies, 146 participants; very low-certainty evidence) at six to eight months' follow-up, but the evidence is very uncertain. At 12 months' follow-up, a smartphone app probably resulted in little to no difference in BMI change (MD -0.1 kg/m2, 95% CI -0.4 to 0.3; 1 study; 650 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in body weight change (MD -2.5 kg, 95% CI -6.8 to 1.7; 3 studies, 1044 participants; low-certainty evidence) at 12 months' follow-up. At 24 months' follow-up, a smartphone app probably resulted in little to no difference in body weight change (MD 0.7 kg, 95% CI -1.2 to 2.6; 1 study, 245 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in self-efficacy for a physical activity score at eight months' follow-up, but the results are very uncertain. A smartphone app probably results in little to no difference in quality of life and well-being at 12 months (moderate-certainty evidence) and in little to no difference in various measures used to inform dietary behaviour at 12 and 24 months' follow-up. We are very uncertain about adverse events, which were only reported narratively in two studies (very low-certainty evidence). Smartphone app versus another smartphone app Two studies compared different versions of the same app in adults, showing no or minimal differences in outcomes. One study in adults compared two different apps (calorie counting versus ketogenic diet) and suggested a slight reduction in body weight at six months in favour of the ketogenic diet app. No studies were available for adolescents. Smartphone app versus personal coaching Only one study compared a smartphone app with personal coaching in adults, presenting data at three months. Two studies compared these interventions in adolescents. A smartphone app resulted in little to no difference in BMI z-score compared to personal coaching at six months' follow-up (MD 0, 95% CI -0.2 to 0.2; 1 study; 107 participants). Smartphone app versus usual care Only one study compared an app with usual care in adults but only reported data at three months on participant satisfaction. No studies were available for adolescents. We identified 34 ongoing studies.

AUTHORS' CONCLUSIONS

The available evidence is limited and does not demonstrate a clear benefit of smartphone applications as interventions for adolescents or adults with overweight or obesity. While the number of studies is growing, the evidence remains incomplete due to the high variability of the apps' features, content and components, which complicates direct comparisons and assessment of their effectiveness. Comparisons with either no or minimal intervention or personal coaching show minor effects, which are mostly not clinically significant. Minimal data for adolescents also warrants further research. Evidence is also scarce for low- and middle-income countries as well as for people with different socio-economic and cultural backgrounds. The 34 ongoing studies suggest sustained interest in the topic, with new evidence expected to emerge within the next two years. In practice, clinicians and healthcare practitioners should carefully consider the potential benefits, limitations, and evolving research when recommending smartphone apps to adolescents and adults with overweight or obesity.

Smartphone intervention to optimize medication-assisted treatment outcomes for opioid use disorder: study protocol for a randomized controlled trial

BACKGROUND

Opioids accounted for 75% of drug overdoses in the USA in 2020, with rural states particularly impacted by the opioid crisis. While medication-assisted treatment (MAT) with Suboxone remains one of the more efficacious treatments for opioid use disorder (OUD), approximately 40% of people receiving Suboxone for outpatient MAT for OUD (MOUD) relapse within the first 6 months of treatment. We developed the smartphone app-based intervention OptiMAT as an adjunctive intervention to improve MOUD outcomes. The aims of this study are to (1) evaluate the efficacy of adjunctive OptiMAT use in reducing opioid misuse among people receiving MOUD and (2) evaluate the role of specific OptiMAT features in reducing opioid misuse, including the use of GPS-driven just-in-time intervention.

METHODS

We will conduct a two-arm, single-blind, randomized controlled trial of adults receiving outpatient MOUD in the greater Little Rock AR area. Participants are English-speaking adults ages 18 or older recently enrolled in outpatient MOUD at one of our participating study clinics. Participants will be allocated via 1:1 randomized block design to (1) MOUD with adjunctive use of OptiMAT (MOUD+OptiMAT) or (2) MOUD without OptiMAT (MOUD-only). Our blinded research statistician will evaluate differences between the two groups in opioid misuse (as determined by quantitative urinalysis conducted by clinical lab staff blinded to group membership) during the 6-months following study enrolment. Secondary analyses will evaluate if OptiMAT-usage patterns within the MOUD+OptiMAT group predict opioid misuse or continued abstinence.

DISCUSSION

This study will test if adjunctive use of OptiMAT improve MOUD outcomes. Study findings could lead to expansion of OptiMAT into rural clinical settings, and the identification of OptiMAT features which best predict positive clinical outcome could lead to refinement of this and similar smartphone app-based interventions.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT05336188 , registered March 21, 2022.

Can healthcare apps and smart speakers improve the health behavior and depression of older adults? A quasi-experimental study

Purpose

This study identified the effects of applying information and communication technologies (ICT) to the health management of older adults aged 65 or older.

Methods

Older adults registered at public health centers were provided with the health management app "Health Today" and a smart speaker for 6 months to perform assigned healthcare missions. The program was conducted for 6 months by dividing participants into two groups: one that received both the health management app and the smart speaker, and another that used only the health management app. Depression, self-efficacy, number of days of moderate-intensity exercise, relative grip strength, balance tests, and five-times-sit-to-stand tests were measured during the pre- and post-evaluation.

Results

Both groups showed a positive health status and behavioral changes at post-evaluation. However, no reduced depression was observed due to communication and music listening functions in the group that was additionally provided smart speakers.

Conclusion

ICT use in healthcare can be beneficial for older adults. However, whether these devices meet the purpose of the national health project must be determined, and an effect evaluation must be undertaken prior to providing these ICT devices for the health management of older adults in the public domain.

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.

Randomized Trial for Weight Loss Using a Digital Therapeutic Application

BACKGROUND

Smartphones present a near-ubiquitous channel through which structured lifestyle change can reduce risk or progression of the most common noncommunicable diseases. We explored whether a digital structured lifestyle program enhances weight loss.

METHODS

We randomized overweight and obese participants attending a four-month lifestyle change program to either standard weekly coaching sessions (controls), or standard treatment supplemented with a digital therapeutic mobile application (intervention). Changes in body mass index after four months were the main outcome measure. Odds ratios of achieving 5% weight loss were estimated with unconditional logistic regression.

RESULTS

Of 234 eligible persons, 146 (62%) agreed to participate, were block-randomized, showed up for the baseline measures, and constituted the intention-to-treat (ITT) sample (n = 95 intervention group, n = 51 control group). In the intervention group, 70 (74%) downloaded the mobile application and completed the program (intervention per-protocol). Significant weight loss and BMI reduction were observed for both the intention-to-treat intervention group (P < 0.05, P = 0.01) and the per-protocol intervention group (P < 0.0001, P < 0.0001). For the intervention per-protocol group, the odds ratio of achieving 5% weight loss, compared to not treated per-protocol, was 3.3 (95% CI 1.3-8.2), adjusting for age and weight at baseline.Attendance to weekly coaching sessions decreased by 18% during the program in the control group while it increased by 3% amongst the per-protocol group (P = 0.004).

CONCLUSIONS

These preliminary findings support the benefit of a digital therapeutic to enhance weight reduction and attendance in a structured lifestyle change program. Larger trials of longer duration are needed to confirm these findings.

The Effectiveness of a Mobile Health Care App and Human Coaching Program in Primary Care Clinics: Pilot Multicenter Real-World Study

Background

As the global burden of chronic conditions increases, their effective management is a concern. Although the need for chronic disease management using mobile self-management health care apps is increasing, there are still many barriers to their practical application in the primary care field.

Objective

This study evaluated the effectiveness of primary care services combining a mobile self-management health care app with human coaching for patients with chronic diseases in the current primary care system.

Methods

A total of 110 patients (mean age 53.2, SD 9.2 years; 64 of 110, 58.2% female) with hypertension, diabetes, dyslipidemia, or metabolic syndrome who visited one of 17 participating primary care clinics from September to November 2020 were included in this study. All participants recorded data regarding changes in body weight, sleep conditions, quality of life, depression, anxiety, stress, BMI, waist circumference, blood sugar levels, blood pressure, and blood lipids levels. The app user group (n=65) used a mobile self-management health care app with human coaching for 12 weeks, and the control group (n=45) underwent conventional self-managed health care.

Results

Patients in the app user group reported significantly more weight loss than those in the control group—the body weight of the app user group decreased by 1.43 kg (95% CI –2.07 to –0.79) and that of the control group decreased by 0.13 kg (95% CI –0.67 to 0.41; P=.002). The weight loss was markedly greater after using the app for 9 weeks than that when used for 4 weeks or 5-8 weeks (P=.002). Patients in the app user group reported better sleep quality (P=.04) and duration (P=.004) than those in the control group.

Conclusions

The combination of primary care clinics and a mobile self-management health care app with human coaching results in better management of chronic conditions. This study shows that the primary care services combining a mobile self-management health care app with human coaching are effective in the current primary care system. An implication of this study is the possibility that a mobile self-management health care app with human coaching is a treatment option in the current primary care system.

SAlBi educa (Tailored Nutrition App for Improving Dietary Habits): Initial Evaluation of Usability

In recent years, the use of applications to improve dietary habits has increased. Although numerous nutrition apps are available on the market, only few have been developed by health and nutrition professionals based on scientific evidence and subsequently tested to prove their usability. The main objective of this study was to design, develop, and evaluate the usability of a tailored nutrition application to be used to promote healthy eating habits. In order to decide app design and content, three focus groups took place with fifteen professionals from primary healthcare, nutrition, and food science and computer science, as well as expert users. For the general and feedback message design, a reference model based on the scientific literature was developed. To address the multi-perspective approach of users' and external healthcare professionals' feedback, a one-day pilot testing with potential users and healthcare professionals was conducted with four focus groups. To evaluate the relevance and potential usability of the app a 1-month pilot test was conducted in a real-life environment. A total of 42 volunteers participated in the one-day pilot testing, and 39 potential users participated in the 1-month pilot test. The SAlBi educa app developed includes an online dietary record, a self-monitoring tool to evaluate dietary patterns, general and feedback messages, and examples of traditional Mediterranean recipes. The usability study showed that volunteers think that SAlBi educa is pleasant (59%) and easy to learn to use (94%). Over 84% of the volunteers declared that the nutritional messages were clear and useful. Volunteers stated that general and tailored recommendations, as well as self-monitoring, were SAlBi educa's most motivating and useful features. SAlBi educa is an innovative, user-friendly nutritional education tool with the potential to engage and help individuals to follow dietary habits based on the Mediterranean model.

Effect of Mobile-Based Lifestyle Intervention on Weight Loss among the Overweight and Obese Elderly Population in China: A Randomized Controlled Trial

Background and Objective: Overweight or obesity, as an independent risk factor for chronic diseases, has been on the rise globally. Adopting a healthy lifestyle is positive to weight control. Mobile-based lifestyle interventions have shown potential benefits in weight loss, but most studies were carried out among non-elderly population, so it is necessary to perform well-designed randomized controlled trials among the elderly with overweight or obesity. The purpose of this study is to assess the effect of mobile-based lifestyle intervention on weight loss among the overweight and obese elderly population in China. Methods: This is a prospective, open-labeled, three-month, multicenter, randomized controlled trial involving 750 participants from five cities who were randomly assigned to dietary and physical activity interventions group (DPG; mobile phone with the App and bracelet), physical activity interventions group (PG; mobile phone with the App and bracelet) and control group (CG; no interventions and kept their lifestyle as before). The outcomes evaluated were changes in weight, body mass index (BMI), waist circumference (WC), and hip circumference (HC). Results: In total, 642 (85.6%) participants completed the study, 237 (94.8%), 203 (81.2%), and 202 (80.8%) for DPG, PG, and CG respectively. Comparing with PG and CG, the DPG showed a significant decrease in all outcomes after three months, including body weight (−4.1 kg vs. −1.0 kg; −4.1 kg vs. −0.8 kg; p < 0.05), BMI (−1.6 kg/m² vs. −0.4 kg/m²; −1.6 kg/m² vs. −0.3 kg/m²; p < 0.05), WC (−2.8 cm vs. −0.1 cm; −2.8 cm vs. −0.5 cm; p < 0.05), and HC (−3.8 cm vs. −1.3 cm; −3.8 cm vs. −1.3 cm; p < 0.05). Similar effects were seen across sex and BMI subgroups. Conclusions: Mobile-based lifestyle intervention obtained beneficial effect in weight loss among the elderly with overweight or obesity. Nevertheless, further studies are needed to confirm the effectiveness and its sustainability.

The effects of a physical activity intervention based on a fatness and fitness smartphone app for University students

Since the 2012 Lancet Series on physical activity, progress regarding this topic has been negligible at global level. Thus, improving physical activity levels in specific populations through new methodologies is positioned as a priority. The aim of this study was to determine the effects of a physical activity intervention on body fatness composition, and measured and self-reported physical fitness components based on the use of a smartphone app. The investigation included 100 Spanish university students, cluster-randomized into the smartphone app intervention group or a control group (n = 35 and n = 31 respectively, after applying exclusion criteria). The physical activity intervention comprised a 9-week programme designed to promote a healthy physical activity pattern using a smartphone app. Specifically, an mHealth approach was taken containing five BCTs. The results showed that the intervention group improved their physical fitness (F = 8.1, p = .006) and reported better general scores in self-reported physical fitness (F = 7.4, p = .008) over time, in comparison to the control group. However, the intervention group did not show any changes to their fatness. Further research is needed to disentangle which BCTs are more effective to achieve physical health improvements when using physical activity apps.

Evaluating mobile health technologies: does the traditional randomized controlled trial serve our needs?

Mobile health technologies are increasingly used by cardiovascular nurses and allied health clinicians to support behaviour change and self-care in patients. Randomized controlled trials provide rigorous methodology for evaluation but progress slowly, so the technology is often outdated by completion. A helpful modification to the trial design includes identification of the behaviour intervention principles involved and concurrently track in-app usage data, allowing updates to be made. These data collected alongside user experiences enables analysis of effects on outcomes and determination of the relative influence of component parts. Cardiovascular and mental health mHealth strategies are used to exemplify these recommendations.

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.

Effectiveness of eHealth Nutritional Interventions for Middle-Aged and Older Adults: Systematic Review and Meta-analysis

BACKGROUND

The risk of development of chronic diseases related to poor nutrition increases with age. In the face of an aging population, it is important for health care sectors to find solutions in delivering health services efficiently and effectively to middle-aged and older adults.

OBJECTIVE

The aim of this systematic review and meta-analysis was to consolidate the literature that reported the effectiveness of eHealth apps in delivering nutritional interventions for middle-aged and older adults.

METHODS

A literature search from five databases (PubMed, CINAHL, Cochrane, Web of Science, and Global Health) from the past 5 years was performed. Studies were selected for inclusion that used eHealth to deliver nutritional interventions to adults aged 40 years and above, and reported health and behavioral outcomes. Two independent reviewers searched for research articles and assessed the eligibility of studies to be included in the review. A third reviewer resolved disagreements on study inclusion. We also assessed the quality of the included studies using the CONSORT 2010 checklist.

RESULTS

A total of 70 studies were included for analysis. The study quality ranged from 44% to 85%. The most commonly used eHealth intervention type was mobile apps (22/70, 31%). The majority of studies (62/70, 89%) provided multicomponent health interventions, which aimed to improve nutrition and other health behaviors (eg, exercise, smoking cessation, medication adherence). Meta-analysis results indicated high and significant heterogeneity; hence, conclusions based on these results should be considered with caution. Nonetheless, the results generally showed that eHealth interventions improved anthropometric and clinical outcomes, but not behavioral outcomes such as fruit and vegetable consumption.

CONCLUSIONS

The use of eHealth apps to deliver health interventions has been increasing in recent years, and these apps have the potential to deliver health services to a larger group of people. Our findings showed that the effectiveness of eHealth apps to deliver health interventions for middle-aged to older adults was supported by the improvement of anthropometric and clinical outcomes. Future work could aim to develop research frameworks in administering eHealth interventions to address heterogeneity in this field of research.

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.

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.

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.

Emerging Mobile Platforms to Aid in Stone Management

Nephrolithiasis is an increasingly common condition worldwide and mobile technology is revolutionizing how patients with kidney stone are being diagnosed and managed. Emerging platforms include software applications to increase adherence to stone prevention, mobile compatible hardware, online social media communities, and telemedicine. Applications and hardware specifically relevant to increasing hydration, diet modification, medication adherence, and rapid diagnosis (ie, mobile ultrasound and endoscopy) have the greatest potential to reduce stone recurrence and expedite treatment. Social media and online communities have also been rapidly adopted by patients and providers to promote education and support.

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.

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

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