Feasibility Randomized Controlled Trial of ImpulsePal: Smartphone App-Based Weight Management Intervention to Reduce Impulsive Eating in Overweight Adults

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.

Exploring the benefits and costs of a growth mindset in a digital app weight management program

We explored the potential benefits and costs of believing one can change their weight (i.e. growth mindset) in the context of a digital weight management program. We investigated mechanisms by which growth mindsets relate to weight loss achievement and body shame. Among participants seeking to lose weight (N = 1626; 74.7% female; 77.9% White; Mage = 45.7), stronger growth mindsets indirectly predicted greater weight loss achievement through positive offset expectations and subsequent increased program engagement. Additionally, stronger growth mindsets predicted less body shame through positive offset expectations but predicted more body shame through increased onset responsibility, replicating the double-edged sword model of growth mindsets. We conclude with applications that leverage growth mindsets for optimal behavior change while mitigating costs such as body shame.

"It helps me to stay on the right path, rather than give in": Mixed-method process evaluation of the ImpulsePal app-based intervention for weight management

Background

Empirical research indicates that impulsive processes that operate below conscious monitoring can undermine peoples' attempts to change behaviour patterns, especially those that have become habitual. This may, therefore, be a serious challenge for those trying to lose weight. A novel smartphone app-based intervention (ImpulsePal) offers practical strategies to manage impulsive urges to facilitate reductions in the consumption of energy-dense processed food and overeating.

Aim

This process evaluation of ImpulsePal aimed to explore what was delivered/received and used, mechanisms of action, and potential contextual factors impacting intervention engagement and outcomes.

Methods

A mixed-methods process evaluation, with composite analysis of the quantitative (app usage statistics) and qualitative data (semi-structured interviews), was conducted alongside a feasibility randomised controlled trial with individuals with a body mass index of at least 25 kg/m2 who wanted to lose weight.

Results

Of 58 participants receiving ImpulsePal, 56 had successfully shared app usage statistics, and 36 (62%) were interviewed. Although usage statistics indicated reductions in the use of some features, interviews indicated that participants were still using app-recommended strategies without requiring them to open ImpulsPal. Overall, interviews highlighted that participants valued having access to in-the-moment support, felt more aware of their own eating behaviour and influences on it, and felt an increased ability to avoid and reconceptualise, in-the-moment temptations.

Conclusion

This process evaluation offers support for a logic model suggesting that impulse management, using ImpulsePal, can promote healthier eating among those motivated to lose weight. It also highlights the necessity of using multimodal methods to explore the delivery and use of digital interventions.

White Paper: Open Digital Health - accelerating transparent and scalable health promotion and treatment

In this White Paper, we outline recommendations from the perspective of health psychology and behavioural science, addressing three research gaps: (1) What methods in the health psychology research toolkit can be best used for developing and evaluating digital health tools? (2) What are the most feasible strategies to reuse digital health tools across populations and settings? (3) What are the main advantages and challenges of sharing (openly publishing) data, code, intervention content and design features of digital health tools? We provide actionable suggestions for researchers joining the continuously growing Open Digital Health movement, poised to revolutionise health psychology research and practice in the coming years. This White Paper is positioned in the current context of the COVID-19 pandemic, exploring how digital health tools have rapidly gained popularity in 2020-2022, when world-wide health promotion and treatment efforts rapidly shifted from face-to-face to remote delivery. This statement is written by the Directors of the not-for-profit Open Digital Health initiative (n = 6), Experts attending the European Health Psychology Society Synergy Expert Meeting (n = 17), and the initiative consultant, following a two-day meeting (19-20th August 2021).

A Tailored Gender-Sensitive mHealth Weight Loss Intervention (I-GENDO): Development and Process Evaluation

BACKGROUND

Given the increase in the prevalence of overweight and obesity worldwide, the number of digital weight loss interventions has also risen. However, these interventions often lack theoretical background and data on long-term effectiveness. The consideration of individual and gender differences in weight-related psychological parameters might enhance the efficacy and sustainability of mobile-based weight loss interventions.

OBJECTIVE

This paper presented an introduction to and the process evaluation of a 12-week gender-sensitive mobile health (mHealth) weight loss intervention (I-GENDO) combining computer-based and self-tailoring features.

METHODS

Between August 2020 and August 2021, individuals with overweight (BMI 25.0-29.9 kg/m²), those with obesity class I (BMI 30.0-34.9 kg/m²), and those with obesity class II (BMI 35.0-39.9 kg/m²) were recruited to the I-GENDO project, a multicenter study in Germany. The mHealth intervention aimed at targeting individual psychological factors associated with the development and persistence of overweight and obesity (eg, emotional eating) using computer-based tailoring. Moreover, the intervention took a gender-sensitive approach by implementing self-tailoring of gender-targeted module versions. The computer-based assignment of the main modules, self-selection of gender-targeted module versions, and use patterns were evaluated while considering gender. Moreover, gender differences in the usability assessment were analyzed.

RESULTS

Data from the intervention arm of the study were processed. A total of 116 individuals with overweight and obesity (77/116, 66.4% women; age mean 47.28, SD 11.66 years; BMI mean 33.58, SD 3.79 kg/m2) were included in the analyses. Overall, the compliance (90/109, 82.6%) and satisfaction with the app (mean 86% approval) were high and comparable with those of other mobile weight loss interventions. The usability of the intervention was rated with 71% (5.0/7.0 points) satisfaction. More women obtained the main module that focused on emotion regulation skills. Most men and women selected women-targeted versions of the main modules. Women used the app more frequently and longer than men. However, women and men did not differ in the progress of use patterns throughout the intervention.

CONCLUSIONS

We developed a tailored gender-sensitive mHealth weight loss intervention. The usability of and engagement with the intervention were satisfactory, and the overall satisfaction with the intervention was also high. Gender differences must be considered in the evaluation of the effectiveness and sustainability of the intervention.

Efficacy of a New Low-Protein Multimedia Diet App for PKU

Patients with phenylketonuria (PKU) require a phenylalanine/protein-restricted diet, with limited food choice. Interpreting food labels, calculating protein intake, and determining food suitability are complex and confusing tasks. A mobile multi-media low-protein diet app was developed to guide food choice, label interpretation, and protein calculation. ‘PKU Bite’® includes >1100 specialist and regular low-protein foods, is colour-coded for suitability, and features a protein calculator. A 12-week randomised controlled trial assessed app efficacy, compared with written/pictorial material, in 60 parents/caregivers of children with PKU, aged 1−16 years, and 21 adolescents with PKU. Questionnaires examined self-efficacy and label-reading knowledge; food records evaluated natural-protein intake, compared with prescriptions. There was no difference between groups in label-reading knowledge or self-efficacy, but there was a trend for improved accuracy of dietary protein calculation, when using the app (baseline/12-weeks: app 35%/48%; control 39%/35%). Parents of children <10 years of age (median 5.5 years), were most likely to use the app to check the phenylalanine/protein content of a food or to verify suitability of foods. Whilst the app was popular (43%), so too was contacting the dietitian (43%), using written/pictorial information (24%), or using social media (18%). This is the first dietary app for PKU to be studied in a systematic way as well as validated by healthcare professionals. It is a useful adjunct to existing resources and will be a valuable tool for educating parents of younger children.

Transcranial Direct-Current Stimulation as an Adjunct to Verb Network Strengthening Treatment in Post-stroke Chronic Aphasia: A Double-Blinded Randomized Feasibility Study

Background

Difficulties in discourse production are common in post-stroke chronic aphasia. Previous studies have found that speech and language therapy combined with transcranial direct-current stimulation (tDCS) may improve language skills like naming and enhance aphasia treatment outcomes. However, very few studies have investigated the effect of tDCS when combined with interventions for improving higher level language skills such as the Verb Network Strengthening Treatment (VNeST).

Aims

This study aimed to determine the feasibility of anodal tDCS as an adjunct to VNeST to improve discourse production in post-stroke chronic aphasia.

Methods

Six people with post-stroke chronic aphasia took part in this double-blinded randomized feasibility study. Participants were randomly allocated to either the experimental group receiving a 6-week block of once weekly VNeST sessions combined with active tDCS over the left inferior frontal gyrus (LIFG) or a control group that received VNeST with sham stimulation. Feasibility outcomes included screening, eligibility, retention, and completion rates, and adverse events. Preliminary response to intervention was also examined using discourse production, functional communication, quality of life, psychological state, and cognition outcomes.

Results

Overall 19 individuals were screened and ten met the inclusion criteria. Six individuals provided consent and participated in the study giving a consent rate of 60%. Participant retention and completion rates were 100% and no adverse effects were reported. Exploratory analyses revealed promising changes (i.e., estimated large effect size) in discourse production measures across discourse language tasks and functional communication for the active tDCS group.

Conclusions

Our results support the feasibility of tDCS as an adjunct to VNeST. Preliminary findings provide motivation for future large-scale studies to better understand the potential of tDCS as a safe and economical tool for enhancing rehabilitation in chronic aphasia.

App-based food-specific inhibitory control training as an adjunct to treatment as usual in binge-type eating disorders: A feasibility trial

Current treatments for binge eating disorder (BED) and bulimia nervosa (BN) only show moderate efficacy, warranting the need for novel interventions. Impairments in food-related inhibitory control contribute to BED/BN and could be targeted by food-specific inhibitory control training (ICT). The aim of this study was to establish the feasibility and acceptability of augmenting treatment for individuals with BN/BED with an ICT app (FoodT), which targets motor inhibition to food stimuli using a go/no-go paradigm. Eighty patients with BED/BN receiving psychological and/or pharmacological treatment were randomly allocated to a treatment-as-usual group (TAU; n = 40) or TAU augmented with the 5-min FoodT app daily (n = 40) for 4 weeks. This mixed-methods study assessed feasibility outcomes, effect sizes of clinical change, and acceptability using self-report measures. Pre-registered cut-offs for recruitment, retention, and adherence were met, with 100% of the targeted sample size (n = 80) recruited within 12 months, 85% of participants retained at 4 weeks, and 80% of the FoodT + TAU group completing ≤8 sessions. The reduction in binge eating did not differ between groups. However, moderate reductions in secondary outcomes (eating disorder psychopathology: SES = -0.57, 95% CI [-1.12, -0.03]; valuation of high energy-dense foods: SES = -0.61, 95% CI [-0.87, -0.05]) were found in the FoodT group compared to TAU. Furthermore, small greater reductions in food addiction (SES = -0.46, 95% CI [-1.14, 0.22]) and lack of premeditation (SES = -0.42, 95% CI [-0.77, -0.07]) were found in the FoodT group when compared to TAU. The focus groups revealed acceptability of FoodT. Participants discussed personal barriers (e.g. distractions) and suggested changes to the app (e.g. adding a meditation exercise). Augmenting treatment for BED/BN with a food-specific ICT app is feasible, acceptable, and may reduce clinical symptomatology with high reach and wide dissemination.

Breaking habits or breaking habitual behaviours? Old habits as a neglected factor in weight loss maintenance

Maintaining weight loss requires long-term behaviour change. Theory and evidence around habitual behaviour - i.e., action triggered by impulses that are automatically activated upon exposure to cues, due to learned cue-action associations - can aid development of interventions to support weight loss maintenance. Specifically, weight loss is more likely to be sustained where people develop new habits that support weight management, and break old habits that may undermine such efforts. Interventions seeking to break 'bad' weight-related habits have focused on inhibiting unwanted impulses or avoiding cues. This paper draws attention to the possibility that while such approaches may discontinue habitual behaviour, underlying habit associations may remain. We use evidence from existing qualitative studies to demonstrate that, left unchecked, unwanted habit associations can render people prone to lapsing into old patterns of unhealthy behaviours when motivation or willpower is momentarily weakened, or when returning to familiar settings following temporarily discontinued exposure. We highlight six behaviour change techniques especially suited to disrupting habit associations, but show that these techniques have been underused in weight loss maintenance interventions to date. We call for intervention developers and practitioners to adopt techniques conducive to forming new habit associations to directly override old habits, and to use the persistence of unwanted habit associations as a potential indicator of long-term weight loss intervention effectiveness.

App-based food Go/No-Go training: User engagement and dietary intake in an opportunistic observational study

Food Go/No-Go training aims to alter implicit food biases by creating associations between perceiving unhealthy foods and withholding a dominant response. Asking participants to repeatedly inhibit an impulse to approach unhealthy foods can decrease unhealthy food intake in laboratory settings. Less is known about how people engage with app-based Go/No-Go training in real-world settings and how this might relate to dietary outcomes. This pragmatic observational study investigated associations between the number of completed app-based food Go/No-Go training trials and changes in food intake (Food Frequency Questionnaire; FFQ) for different healthy and unhealthy food categories from baseline to one-month follow-up. In total, 1234 participants (m_(BMI) = 29 kg/m², m_(age) = 43years, 69% female) downloaded the FoodT app and completed food-Go/No-Go training at their own discretion (mean number of completed sessions = 10.7, sd = 10.3, range: 1-122). In pre-registered analyses, random-intercept linear models predicting intake of different foods, and controlled for baseline consumption, BMI, age, sex, smoking, metabolic syndrome, and dieting status, revealed small, significant associations between the number of completed training trials and reductions in unhealthy food intake (b = -0.0005, CI₉₅= [-0.0007;-0.0003]) and increases in healthy food intake (b = 0.0003, CI₉₅ = [0.0000; 0.0006]). These relationships varied by food category, and exploratory analyses suggest that more temporally spaced training was associated with greater changes in dietary intake. Taken together, these results imply a positive association between the amount of training completed and beneficial changes in food intake. However, the results of this pragmatic study should be interpreted cautiously, as self-selection biases, motivation and other engagement-related factors that could underlie these associations were not accounted for. Experimental research is needed to rule out these possible confounds and establish causal dose-response relationships between patterns of engagement with food Go/No-Go training and changes in dietary intake.

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.

ImpulsePal: The systematic development of a smartphone app to manage food temptations using intervention mapping

BACKGROUND

Impulsive processes driving eating behaviour can often undermine peoples' attempts to change their behaviour, lose weight and maintain weight loss.

AIM

To develop an impulse management intervention to support weight loss in adults.

METHODS

Intervention Mapping (IM) was used to systematically develop the "ImpulsePal" intervention. The development involved: (1) a needs assessment including a qualitative study, Patient and Public advisory group and expert group consultations, and a systematic review of impulse management techniques; (2) specification of performance objectives, determinants, and change objectives; (3) selection of intervention strategies (mapping of change techniques to the determinants of change); (4) creation of programme materials; (5) specification of adoption and implementation plans; (6) devising an evaluation plan.

RESULTS

Application of the IM Protocol resulted in a smartphone app that could support reductions in unhealthy (energy dense) food consumption, overeating, and alcoholic and sugary drink consumption. ImpulsePal includes inhibition training, mindfulness techniques, implementation intentions (if-then planning), visuospatial loading, use of physical activity for craving management, and context-specific reminders. An "Emergency Button" was also included to provide access to in-the-moment support when temptation is strong.

CONCLUSIONS

ImpulsePal is a novel, theory- and evidence-informed, person-centred app that aims to support impulse management for healthier eating. Intervention Mapping facilitated the incorporation of app components that are practical operationalisations of change techniques targeting our specific change objectives and their associated theoretical determinants. Using IM enabled transparency and provided a clear framework for evaluation, and enhances replicability and the potential of the intervention to accomplish the desired outcome of facilitating weight loss through dietary change.

Construal beliefs moderate the usability and effectiveness of a novel healthy eating mobile app

Reduced self-control is a strong predictor of overeating and obesity. Priming a high construal level mind-set has been shown to enhance self-control and reduce snack consumption in the lab but the long-term and real-world effects are not known. The use of digital technology is an efficient way to deliver priming cues in real-world settings. Many mobile apps claim to support healthy eating but few are grounded in psychological theories of self-control. The aim of this study was to test the feasibility and effectiveness of a novel, construal-theory-based mobile app to promote self-control and healthy eating. In an exploratory analysis, the moderating influence of user characteristics was also examined. Using an iterative process involving users at every stage of the process, a prototype mobile app was developed. The final version included a high construal, self-control priming task, sent personalised reminder cues before each eating occasion, provided a just-in time 'crave-buster' for unanticipated eating opportunities and an optional food log. In a longitudinal trial the app was used over an eight-week period (N=71; 51 females; M (SD) Age = 33.34 (11.68) years; M (SD) BMI = 26.22 (4.94)) with pre-post measures of weight, percent body fat and dietary intake. The app received high usability ratings on the System Usability Scale (M=76.55; SD=11.35), however food intake, per cent body fat and weight pre- and post- app use showed no significant change (p>.05). Exploratory analyses showed that baseline construal belief moderated the extent to which engagement with the app predicted dietary changes (p<.05). These findings indicate that this novel app was user-friendly and effective but that this was dependent on the user's characteristics. Future development in this area should consider tailoring apps to the specific characteristics of the user for improved support and effectiveness.

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.