Dataset Information

Do physical activity and dietary smartphone applications incorporate evidence-based behaviour change techniques?

ABSTRACT:

Background

There has been a recent proliferation in the development of smartphone applications (apps) aimed at modifying various health behaviours. While interventions that incorporate behaviour change techniques (BCTs) have been associated with greater effectiveness, it is not clear to what extent smartphone apps incorporate such techniques. The purpose of this study was to investigate the presence of BCTs in physical activity and dietary apps and determine how reliably the taxonomy checklist can be used to identify BCTs in smartphone apps.

Methods

The top-20 paid and top-20 free physical activity and/or dietary behaviour apps from the New Zealand Apple App Store Health & Fitness category were downloaded to an iPhone. Four independent raters user-tested and coded each app for the presence/absence of BCTs using the taxonomy of behaviour change techniques (26 BCTs in total). The number of BCTs included in the 40 apps was calculated. Krippendorff's alpha was used to evaluate interrater reliability for each of the 26 BCTs.

Results

Apps included an average of 8.1 (range 2-18) techniques, the number being slightly higher for paid (M?=?9.7, range 2-18) than free apps (M?=?6.6, range 3-14). The most frequently included BCTs were "provide instruction" (83% of the apps), "set graded tasks" (70%), and "prompt self-monitoring" (60%). Techniques such as "teach to use prompts/cues", "agree on behavioural contract", "relapse prevention" and "time management" were not present in the apps reviewed. Interrater reliability coefficients ranged from 0.1 to 0.9 (Mean 0.6, SD?=?0.2).

Conclusions

Presence of BCTs varied by app type and price; however, BCTs associated with increased intervention effectiveness were in general more common in paid apps. The taxonomy checklist can be used by independent raters to reliably identify BCTs in physical activity and dietary behaviour smartphone apps.

SUBMITTER: Direito A

PROVIDER: S-EPMC4080693 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Publications

Do physical activity and dietary smartphone applications incorporate evidence-based behaviour change techniques?

Direito Artur A Dale Leila Pfaeffli LP Shields Emma E Dobson Rosie R Whittaker Robyn R Maddison Ralph R

BMC public health 20140625

<h4>Background</h4>There has been a recent proliferation in the development of smartphone applications (apps) aimed at modifying various health behaviours. While interventions that incorporate behaviour change techniques (BCTs) have been associated with greater effectiveness, it is not clear to what extent smartphone apps incorporate such techniques. The purpose of this study was to investigate the presence of BCTs in physical activity and dietary apps and determine how reliably the taxonomy che ...[more]

PMID: 24965805

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Project description:BackgroundSmartphone apps are increasingly used to deliver physical activity and sedentary behaviour interventions for people with cardiovascular disease. However, the active components of these interventions which aim to change behaviours are unclear.AimsTo identify behaviour change techniques used in smartphone app interventions for improving physical activity and sedentary behaviour in people with cardiovascular disease. Secondly, to investigate the association of the identified techniques on improving these behaviours.MethodsSix databases (Medline, CINAHL Plus, Cochrane Library, SCOPUS, Sports Discus, EMBASE) were searched from 2007 to October 2020. Eligible studies used a smartphone app intervention for people with cardiovascular disease and reported a physical activity and/or sedentary behaviour outcome. The behaviour change techniques used within the apps for physical activity and/or sedentary behaviour were coded using the Behaviour Change Technique Taxonomy (v1). The association of behaviour change techniques on physical activity outcomes were explored through meta-regression.ResultsForty behaviour change techniques were identified across the 19 included app-based interventions. Only two studies reported the behaviour change techniques used to target sedentary behaviour change. The most frequently used techniques for sedentary behaviour and physical activity were habit reversal and self-monitoring of behaviour respectively. In univariable analyses, action planning (β =0.42, 90%CrI 0.07-0.78) and graded tasks (β =0.33, 90%CrI -0.04-0.67) each had medium positive associations with increasing physical activity. Participants in interventions that used either self-monitoring outcome(s) of behaviour (i.e. outcomes other than physical activity) (β = - 0.47, 90%CrI -0.79--0.16), biofeedback (β = - 0.47, 90%CrI -0.81--0.15) and information about health consequences (β = - 0.42, 90%CrI -0.74--0.07) as behaviour change techniques, appeared to do less physical activity. In the multivariable model, these predictors were not clearly removed from zero.ConclusionThe behaviour change techniques action planning and graded tasks are good candidates for causal testing in future experimental smartphone app designs.

Project description:BackgroundSmartphone applications provide new opportunities for secondary prevention healthcare. This systematic review and meta-analysis aimed to determine if smartphone applications are effective at changing physical activity and sedentary behaviour in people with cardiovascular disease.MethodsSix electronic databases (Medline, CINAHL Plus, Cochrane Library, SCOPUS, Sports Discus and EMBASE) were searched from 2007 to October 2020. Cardiovascular disease secondary prevention physical activity or sedentary behaviour interventions were included where the primary element was a smartphone or tablet computer application (excluding SMS-only text-messaging). Study quality was assessed using validated tools appropriate for each study design. Random effects model was used and the pooled mean difference between post scores were calculated. Subgroup analyses were conducted to examine differences based on diagnosis, sample size, age, intervention duration, activity tracker use, target behaviour, and self-report versus device-measured outcome.ResultsNineteen studies with a total of 1,543 participants were included (coronary heart disease, n = 10; hypertension, n = 4; stroke, n = 3; heart failure, n = 1; peripheral artery disease, n = 1). Risk of bias was rated as high. Thirteen studies were included in the meta-analysis. Only two controlled studies reported on sedentary behaviour. Smartphone applications produced a significant increase of 40.35 minutes of moderate-to-vigorous intensity physical activity per week (7 studies; p = 0.04; 95% CI 1.03 to 79.67) and 2,390 steps per day (3 studies; p = 0.0007; 95% CI 1,006.9 to 3,791.2). Subgroup analyses found no difference when comparing diagnoses, sample size, activity tracker use, target behaviour and self-report versus device-measured outcome. Larger improvements in physical activity were noted in intervention durations of ≤3-months and participants ≥60yrs (95.35 mins.week-1; p = 0.05).ConclusionsSmartphone applications were effective in increasing physical activity in people with cardiovascular disease. Caution is warranted for the low-quality evidence, small sample and larger coronary heart disease representation. More rigorous research is needed to investigate the effect of smartphone applications across diagnoses and in sedentary behaviour.

Project description:BackgroundThe number of commercial apps to improve health behaviours in children is growing rapidly. While this provides opportunities for promoting health, the content and quality of apps targeting children and adolescents is largely unexplored. This review systematically evaluated the content and quality of apps to improve diet, physical activity and sedentary behaviour in children and adolescents, and examined relationships of app quality ratings with number of app features and behaviour change techniques (BCTs) used.MethodsSystematic literature searches were conducted in iTunes and Google Play stores between May-November 2016. Apps were included if they targeted children or adolescents, focused on improving diet, physical activity and/or sedentary behaviour, had a user rating of at least 4+ based on at least 20 ratings, and were available in English. App inclusion, downloading and user-testing for quality assessment and content analysis were conducted independently by two reviewers. Spearman correlations were used to examine relationships between app quality, and number of technical app features and BCTs included.ResultsTwenty-five apps were included targeting diet (n = 12), physical activity (n = 18) and sedentary behaviour (n = 7). On a 5-point Mobile App Rating Scale (MARS), overall app quality was moderate (total MARS score: 3.6). Functionality was the highest scoring domain (mean: 4.1, SD: 0.6), followed by aesthetics (mean: 3.8, SD: 0.8), and lower scoring for engagement (mean: 3.6, SD: 0.7) and information quality (mean: 2.8, SD: 0.8). On average, 6 BCTs were identified per app (range: 1-14); the most frequently used BCTs were providing 'instructions' (n = 19), 'general encouragement' (n = 18), 'contingent rewards' (n = 17), and 'feedback on performance' (n = 13). App quality ratings correlated positively with numbers of technical app features (rho = 0.42, p < 0.05) and BCTs included (rho = 0.54, p < 0.01).ConclusionsPopular commercial apps to improve diet, physical activity and sedentary behaviour in children and adolescents had moderate quality overall, scored higher in terms of functionality. Most apps incorporated some BCTs and higher quality apps included more app features and BCTs. Future app development should identify factors that promote users' app engagement, be tailored to specific population groups, and be informed by health behaviour theories.

Project description:Crowdsourcing linguistic phenomena with smartphone applications is relatively new. In linguistics, apps have predominantly been developed to create pronunciation dictionaries, to train acoustic models, and to archive endangered languages. This paper presents the first account of how apps can be used to collect data suitable for documenting language change: we created an app, Dialäkt Äpp (DÄ), which predicts users' dialects. For 16 linguistic variables, users select a dialectal variant from a drop-down menu. DÄ then geographically locates the user's dialect by suggesting a list of communes where dialect variants most similar to their choices are used. Underlying this prediction are 16 maps from the historical Linguistic Atlas of German-speaking Switzerland, which documents the linguistic situation around 1950. Where users disagree with the prediction, they can indicate what they consider to be their dialect's location. With this information, the 16 variables can be assessed for language change. Thanks to the playfulness of its functionality, DÄ has reached many users; our linguistic analyses are based on data from nearly 60,000 speakers. Results reveal a relative stability for phonetic variables, while lexical and morphological variables seem more prone to change. Crowdsourcing large amounts of dialect data with smartphone apps has the potential to complement existing data collection techniques and to provide evidence that traditional methods cannot, with normal resources, hope to gather. Nonetheless, it is important to emphasize a range of methodological caveats, including sparse knowledge of users' linguistic backgrounds (users only indicate age, sex) and users' self-declaration of their dialect. These are discussed and evaluated in detail here. Findings remain intriguing nevertheless: as a means of quality control, we report that traditional dialectological methods have revealed trends similar to those found by the app. This underlines the validity of the crowdsourcing method. We are presently extending DÄ architecture to other languages.

Project description:BackgroundPhysical activity (PA) interventions are an important but underutilised component in the management of gestational diabetes mellitus (GDM). The challenge remains how to deliver cost effective PA interventions that have impact on individual behaviour. Digital technologies can support and promote PA remotely at scale. We describe the development of a behaviourally informed smartphone application (Stay-Active) for women attending an NHS GDM clinic. Stay-Active will support an existing motivational interviewing intervention to increase and maintain PA in this population.MethodsThe behaviour change wheel (BCW) eight step theoretical approach was used to design the application. It provided a systematic approach to understanding the target behaviour, identifying relevant intervention functions, and specifying intervention content. The target behaviour was to increase and maintain PA. To obtain a behavioural diagnosis, qualitative evidence was combined with focus groups on the barriers and facilitators to PA in women with GDM. The findings were mapped onto the Capability Opportunity Motivation-Behaviour (COM-B) model and Theoretical Domains Framework to identify what needs to change for the target behaviour and linked to appropriate intervention functions. Finally, behaviour changes techniques (BCT) and modes of delivery that are most likely to serve the intervention functions were selected. Current evidence, patient focus groups and input from key stakeholders informed Stay-Active's development.ResultsWe found that psychological capability, reflective and automatic motivation, social and physical opportunity needed to change to increase PA in women with GDM. The four key intervention functions identified were Enablement, Education, Persuasion and Training. Stay-Active incorporates these four intervention functions delivering ten BCTs including: goal setting, credible source, self-monitoring, action planning, prompts and cues. The final design of Stay-Active delivers these BCTs via an educational resource centre, with goal setting and action planning features, personalised performance feedback and individualised promotional messages.ConclusionThe BCW has enabled the systematic and comprehensive development of Stay-Active to promote PA in women with GDM within an NHS Maternity service. The next phase is to conduct a trial to assess the feasibility and acceptability of a multi-component intervention that combines Stay-Active with PA Motivational Interviewing.

Project description:BackgroundRegular engagement in physical activity has well-established physical and psychological health benefits. Despite this, over a quarter of the global adult population is insufficiently physically active. Physical activity interventions grounded in behaviour change theory, such as the social-cognitive theory, are widely considered to be more effective than non-theoretical approaches. Such interventions set out to intervene on the ultimate outcome (physical activity), but also influence intermediate factors (social-cognitive theory constructs) which in turn, are believed to influence physical activity behaviour. The primary aim of the study was to use mediation analysis to examine whether changes in the social-cognitive theory and related constructs, in particular self-efficacy, outcome expectations, intentions, barriers and goal setting, mediated the effects of a smartphone-based social networking physical activity intervention.MethodsMediation analyses were conducted using the PROCESS Macro in SPSS to (i) calculate the regression coefficients for the effect of the independent variable (group allocation) on the hypothesised mediators (social-cognitive theory constructs), (ii) calculate the regression coefficient for the effect of the hypothesised mediators (social-cognitive theory constructs) on the dependent variable (objectively measured physical activity or self-report physical activity), independent of group assignment and (iii) determine the total, direct and indirect intervention effects.ResultsData from 243 participants were included in the mediation analysis. There was no evidence of mediation for change in objectively measured MVPA or self-reported MVPA.ConclusionsThere was no conclusive evidence that any of the social-cognitive theory constructs mediated the relationship between an app-based intervention and change in physical activity. Ongoing efforts to develop and understand components that make physical activity app-based interventions effective are recommended.Trial registrationThis trial was registered with the Australian and New Zealand Clinical Trial Registry ( ACTRN12617000113358 , date of registration 23 January, 2017).

Dataset Information

Do physical activity and dietary smartphone applications incorporate evidence-based behaviour change techniques?

Background

Methods

Results

Conclusions

Publications

Do physical activity and dietary smartphone applications incorporate evidence-based behaviour change techniques?

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