Common Behavior Change Techniques Research Articles

Effectiveness of behaviour change techniques in lifestyle interventions for non-communicable diseases: an umbrella review

ObjectiveTo identify the most commonly reviewed behaviour change techniques (BCTs) and their effectiveness based on consistency across reviews for lifestyle interventions of non-communicable diseases.DesignUmbrella review of systematic reviews.Data sourcesPubMed, Embase, PsycINFO, Cochrane CENTRAL, Global Health.Data extraction and synthesisA narrative synthesis of extracted findings was conducted. The Behaviour Change Technique v1 Taxonomy was used to identify and code behaviour change techniques (e.g., goal setting) in a standardised manner, which were independently assessed by two reviewers. Study quality was independently assessed by two reviewers using the assessment of multiple systematic review tools.Results26 reviews were included with a total of 72 BCT labels evaluated across the different lifestyle interventions and non-communicable diseases. A total of 13 BCT clusters were identified to be reported as effective. The most commonly reviewed BCTs and their effectiveness/ineffectiveness were as follows: ‘Goals and Planning’ (12 effective/1 ineffective), ‘Feedback and monitoring’ (9 effective/3 ineffective), ‘Social support’ (9 effective/1 ineffective), ‘Shaping knowledge’ (11 effective/1 ineffective), and ‘Natural consequences’ (6 effectiveness/ 2 ineffective). The vast majority of the studies were conducted in high-income and a few in upper middle-income countries, with hardly any studies from lower middle-income and lower income studies.ConclusionThe most common BCTs were ‘Goals and Planning’, ‘Feedback and Monitoring’, ‘Shaping Knowledge’, ‘Social Support’, and ‘Natural Consequence’. Based on consistency across reviews, several BCTs such as ‘Goals and Planning’, Feedback and Monitoring’, ‘Shaping Knowledge’, and ‘Social Support’ have demonstrated effectiveness (Recommendation Grade A) in improving health behaviours across a limited range of NCDs. The evidence is less clear for other BCT techniques. It is also likely that not all BCTs will be transferable across different settings. There is a need for more research in this area, especially in low-middle-income countries.Protocol registrationRegistered on the International Prospective Register of Systematic Reviews; PROSPERO (CRD42020222832).

Electronic screening and brief interventions promoting healthy diet and physical activity among adult patients in medical settings: A systematic review

Background & AimsElectronic screening and brief interventions (eSBIs) are promising health promoting approaches but their utilization towards nutrition outcomes has been little documented so far. The aim of this systematic review is to examine the nature and findings of eSBIs targeting diet and/or physical activity (PA) among adult patients in healthcare settings since smartphone technologies emerged. MethodsThree systematic searches in PubMed, ScienceDirect and PsycINFO were conducted from January 2010 to May 2023. We include all studies assessing eSBI towards lifestyle habits (dietary habits and/or PA at least), implemented in healthcare settings and targeting adult participants. ResultsOf 1981 articles identified, 15 studies met inclusion criteria. Most of them documented eSBIs implemented in primary care (n=11), targeting PA (n=11) and diet (n=9) alone or combined (n=5). Some eSBIs targeted additional behaviors (e.g. smoking, drinking). Delivery modes included computer (n=8), printed documents (n=8) or phone (n=2) but only four eSBIs were interactive (or partially automated). In addition to personalized feedback, most common behavior change techniques were “information about social and environmental consequences” (n=9), “goal setting” (n=7), and “information about health consequences” (n=7). Most studies assessing behavior change had a control group (8 in 10), and eight studies found positive changes in behavior. ConclusionsAlthough implementing eSBIs towards PA/diet among adult patients in medical settings seems promising for primary, secondary and tertiary prevention, common conceptual framework, intervention and outcomes are severely lacking, and the extent to which they follow existing SBI guidelines remains unclear. Demonstrating their effectiveness requires fixing these issues before conducting prospective assessment studies in medical settings.

Behavior Change Techniques Used in Self-Management Interventions Based on mHealth Apps for Adults With Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Hypertension has become an important global public health challenge. Mobile health (mHealth) intervention is a viable strategy to improve outcomes for patients with hypertension. However, evidence on the effect of mHealth app interventions on self-management in patients with hypertension is yet to be updated, and the active ingredients promoting behavior change in interventions remain unclear. We aimed to evaluate the effect of mHealth app self-management interventions on blood pressure (BP) management and investigate the use of behavior change techniques (BCTs) in mHealth app interventions. We conducted a literature search in 6 electronic databases from January 2009 to October 2023 for studies reporting the application of mHealth apps in self-management interventions. The Cochrane Risk of Bias (version 2) tool for randomized controlled trials was used to assess the quality of the studies. BCTs were coded according to the Taxonomy of BCTs (version 1). The extracted data were analyzed using RevMan5.4 software (Cochrane Collaboration). We reviewed 20 studies, of which 16 were included in the meta-analysis. In total, 21 different BCTs (mean 8.7, SD 3.8 BCTs) from 12 BCT categories were reported in mHealth app interventions. The most common BCTs were self-monitoring of outcomes of behavior, feedback on outcomes of behavior, instruction on how to perform the behavior, and pharmacological support. The mHealth app interventions resulted in a -5.78 mm Hg (95% CI -7.97 mm Hg to -3.59 mm Hg; P<.001) reduction in systolic BP and a -3.28 mm Hg (95% CI -4.39 mm Hg to -2.17 mm Hg; P<.001) reduction in diastolic BP. The effect of interventions on BP reduction was associated with risk factors, such as hypertension, that were addressed by the mHealth app intervention (multiple risk factors vs a single risk factor: -6.50 mm Hg, 95% CI -9.00 mm Hg to -3.99 mm Hg vs -1.54 mm Hg, 95% CI -4.15 mm Hg to 1.06 mm Hg; P=.007); the presence of a theoretical foundation (with vs without behavior change theory: -10.06 mm Hg, 95% CI -16.42 mm Hg to -3.70 mm Hg vs -4.13 mm Hg, 95% CI -5.50 to -2.75 mm Hg; P=.07); intervention duration (3 vs ≥6 months: -8.87 mm Hg, 95% CI -10.90 mm Hg to -6.83 mm Hg vs -5.76 mm Hg, 95% CI -8.74 mm Hg to -2.77 mm Hg; P=.09); and the number of BCTs (≥11 vs <11 BCTs: -9.68 mm Hg, 95% CI -13.49 mm Hg to -5.87 mm Hg vs -2.88 mm Hg, 95% CI -3.90 mm Hg to -1.86 mm Hg; P<.001). The self-management interventions based on mHealth apps were effective strategies for lowering BP in patients with hypertension. The effect of interventions was influenced by factors related to the study's intervention design and BCT.

Automated information extraction for behavioural interventions: evaluation and reflections on interdisciplinary AI development

Background The HBCP knowledge system identifies and extracts entities from randomised controlled trials of behaviour change interventions organised by a behaviour change intervention ontology (BCIO) to populate: 1) an outcome prediction tool; and 2) a research browser tool. This knowledge system requires automated information extraction algorithms to query and interpret evidence from behaviour change intervention (BCI) reports. This paper reports the results of an evaluation of the automated information extraction and reflects on the results in relation to the challenges of interdisciplinary working and collaboration. Methods The evaluation used a dataset of 117 previously unseen BCI reports to assess its performance. The automatically extracted information was compared to the full text PDF by trained annotators on essential BCIO entities required for the outcome prediction tool and research browser tool and whether the extracted information was assigned to the correct arm of the randomised trial. Essential entities were the outcome value, a selection of the most common Behaviour Change Techniques (BCTs), the mode of intervention delivery, and key population characteristics. Results The evaluation found an outcome value present in 53.85% (n=63) of the output from the information extraction system but it never extracted both the correct outcome values (interventions and control arms) and assigned them to the correct study arms (intervention and control). Although 84.62% (n=99) of the papers contained information relevant to Behaviour Change Techniques (BCTs), the information extraction algorithm correctly extracted only 58.59% (n=58) of BCTs. Conclusions The evaluation found that the information extraction algorithm did not extract the outcome values and key BCIO entities correctly against the correct arms in any of the papers in our sample, making it unsuitable for deployment in the outcome prediction and research browser tools. Several challenges with working in interdisciplinary teams were identified and discussed along with lessons learned for future work.

Identifying and characterising digital behaviour change interventions to improve fruit and vegetable intake in low-socioeconomic status primary school children: a systematic review

BackgroundDigital behaviour change interventions aiming to improve dietary intakes; specifically fruit and vegetable intake, in low-socioeconomic children are being developed and tested. However there is currently no synthesis of the characteristics or reported effectiveness of these interventions. This systematic review aims to: (1) identify existing digital interventions targeting fruit and vegetable intake in low-socioeconomic status children, (2) identify and synthesise characteristics and reported effectiveness of these interventions using the Behaviour Change Intervention Ontology.MethodCINAHL, ERIC, PubMed, Cochrane Library, ACM Digital Library and Scopus were searched in December 2021 – February 2022 and in February–March 2024. Inclusion criteria for studies were: 1) children of low-SES families, aged between 5–11 years old; 2) Digital intervention to improve fruit and vegetable intake; 3) Comparison groups could be digital or non-digital; 4) Outcome measures were fruit and vegetable intake and antecedents to diet behaviours; 5) Randomised controlled trials (cluster and parallel designs). Characteristics of identified studies were coded using the Behaviour Change Techniques Taxonomy and Modes of Delivery, Setting and Source ontologies of the Behaviour Change Intervention Ontology.ResultsFive studies met all inclusion criteria, with majority reporting significant effects of interventions on improving fruit and vegetable intake. Most common Behaviour Change Techniques found were Goal Setting (k = 4), Problem Solving (k = 3), Instruction on how to perform a Behaviour (k = 3), and Prompts and Cues (k = 3). Characteristics relating to intervention source were unclear.ConclusionsDigital interventions had positive outcomes in fruit and vegetable intake in children; particularly more for fruit than vegetable intake. Characteristics in digital interventions which have direct effects on child fruit and vegetable intake in low-socioeconomic families should be further investigated. Furthermore, clearer reporting on intervention characteristics is needed.

Behavior Change Techniques Within Digital Interventions for the Treatment of Eating Disorders: Systematic Review and Meta-Analysis.

Previous systematic reviews of digital eating disorder interventions have demonstrated effectiveness at improving symptoms of eating disorders; however, our understanding of how these interventions work and what contributes to their effectiveness is limited. Understanding the behavior change techniques (BCTs) that are most commonly included within effective interventions may provide valuable information for researchers and developers. Establishing whether these techniques have been informed by theory will identify whether they target those mechanisms of action that have been identified as core to changing eating disorder behaviors. It will also evaluate the importance of a theoretical approach to digital intervention design. This study aims to define the BCTs within digital self-management interventions or minimally guided self-help interventions for adults with eating disorders that have been evaluated within randomized controlled trials. It also assessed which of the digital interventions were grounded in theory and the range of modes of delivery included. A literature search identified randomized controlled trials of digital intervention for the treatment of adults with eating disorders with minimal therapist support. Each digital intervention was coded for BCTs using the established BCT Taxonomy v1; for the application of theory using an adapted version of the theory coding scheme (TCS); and for modes of delivery using the Mode of Delivery Ontology. A meta-analysis evaluated the evidence that any individual BCT moderated effect size or that other potential factors such as the application of theory or number of modes of delivery had an effect on eating disorder outcomes. Digital interventions included an average of 14 (SD 2.6; range 9-18) BCTs. Self-monitoring of behavior was included in all effective interventions, with Problem-solving, Information about antecedents, Feedback on behavior, Self-monitoring of outcomes of behavior, and Action planning identified in >75% (13/17) of effective interventions. Social support and Information about health consequences were more evident in effective interventions at follow-up compared with postintervention measurement. The mean number of modes of delivery was 4 (SD 1.6; range 2-7) out of 12 possible modes, with most interventions (15/17, 88%) being web based. Digital interventions that had a higher score on the TCS had a greater effect size than those with a lower TCS score (subgroup differences: χ21=9.7; P=.002; I²=89.7%) within the meta-analysis. No other subgroup analyses had statistically significant results. There was a high level of consistency in terms of the most common BCTs within effective interventions; however, there was no evidence that any specific BCT contributed to intervention efficacy. The interventions that were more strongly informed by theory demonstrated greater improvements in eating disorder outcomes compared to waitlist or treatment-as-usual controls. These results can be used to inform the development of future digital eating disorder interventions. PROSPERO CRD42023410060; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=410060.

Care partners experience of an oral health intervention for individuals with mild cognitive impairment and mild dementia using behavior change technique: A qualitative study

Oral health declines in older adults with cognitive impairment. We aimed to improve oral hygiene outcomes for individuals with mild cognitive impairment (MCI) or mild dementia (MD) by fostering behavior changes among carepartners assisting them. We used qualitative data of verbatim transcripts of coaching sessions with carepartners (n = 17 dyads:10 dyads for MCI, 7 dyads for MD). Directed and emergent coding were used to understand behavior change techniques (BCTs). BCTs were compared with carepartners of participants with MCI and MD. Most frequently used BCTs in both groups: prompts and cues, instruction on how to perform the behavior, review behavioral goal, and problem solving. Different BCTs emerged in study: social support-unspecified of the MCI group and credible source for MD group. Findings clarified active intervention components, common BCTs used by carepartners, and different BCT approaches for both participants. Findings help to elucidate the mechanisms of changes in individuals’ behaviors in these interventions.

A Systematic Review of the Effectiveness of Brief Health Behaviour Change Interventions on Service Users Accessing the Third and Social Economy Sector

There are well-established relationships between socioeconomic status (SES) and all aspects of health. Brief interventions offer a cost-effective method to target health behaviours, helping to reduce these health inequalities. Furthermore, the third and social economy (TSE) sector, which encompasses all not-for-profit groups and organisations that operate outside of the family, household, and government, offers access to those of lower SES and a motivated workforce with established relationships with service users. The aim of this systematic review was to investigate the effectiveness of brief interventions targeting health behaviours and their social determinants, when delivered within TSE settings or by TSE service providers (PROSPERO registration number: CRD42022301969). Eight databases were searched for brief health behaviour change interventions lasting under 30 minutes per session, delivered by volunteers within the TSE sector or delivered within the TSE sector provided by or within a TSE, from all possible publication dates to February 2022. Behaviours relating to smoking, diet, alcohol, physical activity, housing, or finance were included. Narrative synthesis and Cochrane risk of bias tools were applied. Eight eligible studies were identified, most measuring smoking behaviour and with a considerable risk of bias. Only one study was set both within a TSE setting and delivered by TSE providers. The most common behaviour change techniques applied were the provision of information on both the consequences of the behaviour and further support. Brief interventions showed a minimal, if any, reduction in smoking behaviour and cholesterol levels, with more intensive interventions resulting in a far greater improvement in smoking, diet, and physical activity behaviours than brief intervention. This study highlighted a lack of research on brief interventions within the TSE sector, particularly for alcohol consumption. More qualitative research is needed to explore the feasibility and acceptability of brief interventions within the TSE settings. Limitations are discussed, including the high risk of bias of included studies and the exclusion of mental health.

Behavioural change interventions encouraging clinicians to reduce carbon emissions in clinical activity: a systematic review

BackgroundClinical activity accounts for 70–80% of the carbon footprint of healthcare. A critical component of reducing emissions is shifting clinical behaviour towards reducing, avoiding, or replacing carbon-intensive healthcare. The objective of this systematic review was to find, map and assess behaviour change interventions that have been implemented in healthcare settings to encourage clinicians to reduce greenhouse gas emissions from their clinical activity.MethodsStudies eligible for inclusion were those reporting on a behaviour change intervention to reduce carbon emissions via changes in healthcare workplace behaviour. Six databases were searched in November 2021 (updated February 2022). A pre-determined template was used to extract data from the studies, and risk of bias was assessed. The behaviour change techniques (BCTs) used in the interventions were coded using the BCT Taxonomy.ResultsSix full-text studies were included in this review, and 14 conference abstracts. All studies used a before-after intervention design. The majority were UK studies (n = 15), followed by US (n = 3) and Australia (n = 2). Of the full-text studies, four focused on reducing the emissions associated with anaesthesia, and two aimed at reducing unnecessary test ordering. Of the conference abstracts, 13 focused on anaesthetic gas usage, and one on respiratory inhalers. The most common BCTs used were social support, salience of consequences, restructuring the physical environment, prompts and cues, feedback on outcome of behaviour, and information about environmental consequences. All studies reported success of their interventions in reducing carbon emissions, prescribing, ordering, and financial costs; however, only two studies reported the magnitude and significance of their intervention’s success. All studies scored at least one item as unclear or at risk of bias.ConclusionMost interventions to date have targeted anaesthesia or pathology test ordering in hospital settings. Due to the diverse study outcomes and consequent inability to pool the results, this review is descriptive only, limiting our ability to conclude the effectiveness of interventions. Multiple BCTs were used in each study but these were not compared, evaluated, or used systematically. All studies lacked rigour in study design and measurement of outcomes.Review registrationThe study was registered on Prospero (ID number CRD42021272526) (Breth-Petersen et al., Prospero 2021: CRD42021272526).

Biological age calculators to motivate lifestyle change: Environmental scan of online tools and evaluation of behaviour change techniques.

"Biological age" calculators are widely used as a way of communicating health risk. This study evaluated the behaviour change techniques (BCTs) within such tools, underlying algorithm differences and suitability for people with varying health literacy. Two authors entered terms into Google (eg, biological/heart age) and recorded the first 50 results. A standard patient profile was entered into eligible biological age calculators. Evaluation was based on Michie et al's BCT taxonomy and a readability calculator. From 4000 search results, 20 calculators were identified: 11 for cardiovascular age, 7 for general biological age and 2 for fitness age. The calculators gave variable results for the same 65-year-old profile: biological age ranged from younger to older (57-87 years), while heart age was always older (69-85+ years). Only 11/20 (55%) provided a reference explaining the underlying algorithm. The average reading level was Grade 10 (range 8.7-12.4; SD 1.44). The most common BCTs were salience of consequences, information about health consequences and credible source. Biological age tools have highly variable results, BCTs and readability. Developers are advised to use validated models, explain the result at the average Grade 8 reading level, and incorporate a clear call to action using evidence-based behaviour change techniques.

MHealth Apps Using Behavior Change Techniques to Self-report Data: Systematic Review.

BackgroundThe popularization of mobile health (mHealth) apps for public health or medical care purposes has transformed human life substantially, improving lifestyle behaviors and chronic condition management.ObjectiveThis review aimed to identify behavior change techniques (BCTs) commonly used in mHealth, assess their effectiveness based on the evidence reported in interventions and reviews to highlight the most appropriate techniques to design an optimal strategy to improve adherence to data reporting, and provide recommendations for future interventions and research.MethodsWe performed a systematic review of studies published between 2010 and 2021 in relevant scientific databases to identify and analyze mHealth interventions using BCTs that evaluated their effectiveness in terms of user adherence. Search terms included a mix of general (eg, data, information, and adherence), computer science (eg, mHealth and BCTs), and medicine (eg, personalized medicine) terms.ResultsThis systematic review included 24 studies and revealed that the most frequently used BCTs in the studies were feedback and monitoring (n=20), goals and planning (n=14), associations (n=14), shaping knowledge (n=12), and personalization (n=7). However, we found mixed effectiveness of the techniques in mHealth outcomes, having more effective than ineffective outcomes in the evaluation of apps implementing techniques from the feedback and monitoring, goals and planning, associations, and personalization categories, but we could not infer causality with the results and suggest that there is still a need to improve the use of these and many common BCTs for better outcomes.ConclusionsPersonalization, associations, and goals and planning techniques were the most used BCTs in effective trials regarding adherence to mHealth apps. However, they are not necessarily the most effective since there are studies that use these techniques and do not report significant results in the proposed objectives; there is a notable overlap of BCTs within implemented app components, suggesting a need to better understand best practices for applying (a combination of) such techniques and to obtain details on the specific BCTs used in mHealth interventions. Future research should focus on studies with longer follow-up periods to determine the effectiveness of mHealth interventions on behavior change to overcome the limited evidence in the current literature, which has mostly small-sized and single-arm experiments with a short follow-up period.

Components of interventions to reduce restrictive practices with children and young people in institutional settings: the Contrast systematic mapping review

Background Incidents in which children or young people experience severe distress or harm or cause distress or harm to others occur frequently in children and young people’s institutional settings. These incidents are often managed using restrictive practices, such as restraint, seclusion, sedation or constant observation; however, these also present significant risks of physical and psychological harm to children and young people as well as staff. Numerous interventions aim to reduce the use of restrictive techniques, but research is hampered by limited attention to specific intervention components. The behavior change technique taxonomy may improve reporting by providing a common language for specifying the content and mechanisms of behaviour change. This study aimed to identify, standardise and report the effectiveness of components of interventions to reduce restrictive practices in children and young people’s institutional settings. Objectives To map interventions aimed at reducing restrictive practices in children and young people’s institutional settings internationally, to conduct behaviour change technique analysis of intervention components, to identify process elements, and to explore effectiveness evidence to identify promising behaviour change techniques and compare the results with those found in adult psychiatric inpatient settings in a companion review. Design Systematic mapping review with programme content coding using the behavior change technique taxonomy. Review methods Eleven relevant English-language health and social care research databases 1989–2019 [including Applied Social Sciences Index (ASSIA), Criminal Justice Abstracts, Educational Resources Information Center (ERIC), MEDLINE and PsycInfo®], grey literature and social media were searched during 2019 (updated January 2020). Data extraction, guided by Workgroup for Intervention Development and Evaluation Research (WIDER), Cochrane Library and theory coding scheme recommendations, included intervention characteristics and study design and reporting. Screening and quality appraisal used the Mixed Methods Appraisal Tool. The behavior change technique taxonomy was applied systematically, and interventions were coded for behaviour change technique components. Outcomes data were then related back to these components. Results There were 121 records, including 76 evaluations. Eighty-two interventions, mostly multicomponent, were identified. Evaluation approaches commonly used a non-randomised design. There were no randomised controlled trials. Behaviour change techniques from 14 out of a possible 16 clusters were detected. Four clusters (i.e. goals and planning, antecedents, shaping knowledge, and feedback and monitoring) contained the majority of identified behaviour change techniques and were detected in over half of all interventions. Two clusters (i.e. self-belief and covert learning) contained no identified behaviour change techniques. The most common setting in which behaviour change techniques were found was ‘mental health’. The most common procedure focused on staff training. The two most common behaviour change techniques were instruction on how to perform the behaviour and restructuring the social environment. Promising behaviour change techniques included instruction on how to perform the behaviour, restructuring the social environment, feedback on outcomes of behaviour and problem-solving. Compared with the companion review, service user perspectives were more sparse and there was more interest in trauma-informed approaches. Effectiveness evidence, range of interventions and reporting were broadly similar. Limitations Poor reporting may have prevented detection of some behaviour change techniques. The finding that the evidence was weak restricted the feasibility of examining behaviour change technique effectiveness. Literature searches were restricted to English-language sources. Conclusions This study generated, to our knowledge, the first review of evidence on the content and effectiveness of interventions to reduce restrictive practices in children and young people’s institutional settings. Interventions tend to be complex, reporting is inconsistent and robust evaluation data are limited, but some behaviour change techniques seem promising. Future work Promising behaviour change techniques could be further explored. Better evidence could help address the urgent need for effective strategies. Study registration This study is registered as PROSPERO CRD42019124730. Funding This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme and will be published in full in Health and Social Care Delivery Research; Vol. 10, No. 8. See the NIHR Journals Library website for further project information.

The Content, Quality, and Behavior Change Techniques in Nutrition-Themed Mobile Apps for Children in Canada: App Review and Evaluation Study.

BackgroundChildren increasingly use mobile apps. Strategies to increase child engagement with apps include the use of gamification and images that incite fun and interaction, such as food. However, the foods and beverages that children are exposed to while using apps are unknown and may vary by app type.ObjectiveThe aim of this study is to identify the app content (ie, types of foods and beverages) included in nutrition-themed apps intended for children, to assess the use of game-like features, and to examine app characteristics such as overall quality and behavior change techniques (BCTs).MethodsThis analysis used a cross-sectional database of nutrition-themed apps intended for children (≤12 years), collected between May 2018 and June 2019 from the Apple App Store and Google Play Store (n=259). Apps were classified into four types: food games or nongames that included didactic nutrition guides, habit trackers, and other. Food and beverages were identified in apps and classified into 16 food categories, as recommended (8/16, 50%) and as not recommended (8/16, 50%) by dietary guidelines, and quantified by app type. Binomial logistic regression assessed whether game apps were associated with foods and beverages not recommended by guidelines. App quality, overall and by subscales, was determined using the Mobile App Rating Scale. The BCT Taxonomy was used to classify the different behavioral techniques that were identified in a subsample of apps (124/259, 47.9%).ResultsA total of 259 apps displayed a median of 6 (IQR 3) foods and beverages. Moreover, 62.5% (162/259) of apps were classified as food games, 27.4% (71/259) as didactic nutrition guides, 6.6% (17/259) as habit trackers, and 3.5% (9/259) as other. Most apps (198/259, 76.4%) displayed at least one food or beverage that was not recommended by the dietary guidelines. Food game apps were almost 3 times more likely to display food and beverages not recommended by the guidelines compared with nongame apps (β=2.8; P<.001). The overall app quality was moderate, with a median Mobile App Rating Scale score of 3.6 (IQR 0.7). Functionality was the subscale with the highest score (median 4, IQR 0.3). Nutrition guides were more likely to be educational and contain informative content on healthy eating (score 3.7), compared with the other app types, although they also scored significantly lower in engagement (score 2.3). Most apps (105/124, 84.7%) displayed at least one BCT, with the most common BCT being information about health consequences.ConclusionsFindings suggest nutrition-themed apps intended for children displayed food and beverage content not recommended by dietary guidelines, with gaming apps more likely to display not recommended foods than their nongame counterparts. Many apps have a moderate app quality, and the use of consequences (instead of rewards) was the most common BCT.

A scoping review of interventions to improve strength training participation.

Low participation rates (1-31%) and unique barriers to strength training (e.g., specialized knowledge, equipment, perceived complexity) suggest effective strength training interventions may differ from effective aerobic or general physical activity interventions. The purpose of this scoping review was to examine interventions used to improve strength training participation through mapping theory, intervention characteristics, prescription parameters, and behaviour change techniques. Recommendations by Levac et al. (2010) and PRISMA-ScR were followed in the conduct and reporting of this review, respectively. Patients and exercise professionals participated in developing the research question and data extraction form, interpreting the findings, and drafting the manuscript. Medline, Embase, PsycINFO, CINAHL, SPORTDiscus, and PubMed databases (inception-December 2020) were searched. The inclusion criteria were (a) original peer-reviewed articles and grey literature, (b) intervention study design, and (c) behavioural interventions targeted towards improving strength training participation. Two reviewers performed data screening, extraction, and coding. The interventions were coded using the Behaviour Change Technique Taxonomy version 1. Data were synthesized using descriptive and frequency reporting. Twenty-seven unique interventions met the inclusion criteria. Social cognitive theory (n = 9), the transtheoretical model (n = 4), and self-determination theory (n = 2) were the only behaviour change theories used. Almost all the interventions were delivered face-to-face (n = 25), with the majority delivered by an exercise specialist (n = 23) in community or home settings (n = 24), with high variability in exercise prescription parameters. Instructions on how to perform the behaviour, behavioural practice, graded tasks, goal setting, adding objects to the environment (e.g., providing equipment), and using a credible source (e.g., exercise specialist delivery) comprised the most common behaviour change techniques. Our results highlight gaps in theory, intervention delivery, exercise prescription parameters, and behaviour change techniques for future interventions to examine and improve our understanding of how to most effectively influence strength training participation.

Delivery of smoking cessation treatment via live chat: An analysis of client-centered coaching skills and behavior change techniques

ObjectiveThis qualitative study explored whether evidence-based tobacco cessation treatment components can be deployed via web-based live chat coaching. MethodsN = 100 randomly selected chats were coded. Researchers used a structured coding guide to note the presence of 3 Motivational Interviewing (MI) skills and 61 behavior change techniques (BCTs). ResultsMI skills were observed in 86% of chats: 31 chats incorporated one skill, 31 incorporated two, and 24 incorporated all three. Open-ended questions were most common (76%), followed by affirmations (47%) and reflective listening statements (38%). BCTs were observed in 100% of chats: 21% involved one-five BCTs, 69% involved six-10 BCTs, and 10% involved 11 or more BCTs. Mean number of BCTs per chat was 7.25 (SD=2.5; range 2–17). The most common BCTs were Social Support (99%), Reward/Threat (95%), Natural Consequences (82%), Regulation (82%), Goals/Planning (64%), and Self Belief (42%). ConclusionsTobacco cessation coaching using MI skills and evidence-based BCTs can be delivered via live chat. This synchronous modality allows the delivery of an intervention tailored to the user’s motivations and goals. Practice implicationsWeb-based live chat can broaden the reach of tobacco treatment specialists to deploy evidence-based counseling skills and behavior change techniques in personalized, accessible coaching.

Behavior Change Techniques in Wrist-Worn Wearables to Promote Physical Activity: Content Analysis.

BackgroundDecreasing levels of physical activity (PA) increase the incidences of noncommunicable diseases, obesity, and mortality. To counteract these developments, interventions aiming to increase PA are urgently needed. Mobile health (mHealth) solutions such as wearable sensors (wearables) may assist with an improvement in PA.ObjectiveThe aim of this study is to examine which behavior change techniques (BCTs) are incorporated in currently available commercial high-end wearables that target users’ PA behavior.MethodsThe BCTs incorporated in 5 different high-end wearables (Apple Watch Series 3, Garmin Vívoactive 3, Fitbit Versa, Xiaomi Amazfit Stratos 2, and Polar M600) were assessed by 2 researchers using the BCT Taxonomy version 1 (BCTTv1). Effectiveness of the incorporated BCTs in promoting PA behavior was assessed by a content analysis of the existing literature.ResultsThe most common BCTs were goal setting (behavior), action planning, review behavior goal(s), discrepancy between current behavior and goal, feedback on behavior, self-monitoring of behavior, and biofeedback. Fitbit Versa, Garmin Vívoactive 3, Apple Watch Series 3, Polar M600, and Xiaomi Amazfit Stratos 2 incorporated 17, 16, 12, 11, and 11 BCTs, respectively, which are proven to effectively promote PA.ConclusionsWearables employ different numbers and combinations of BCTs, which might impact their effectiveness in improving PA. To promote PA by employing wearables, we encourage researchers to develop a taxonomy specifically designed to assess BCTs incorporated in wearables. We also encourage manufacturers to customize BCTs based on the targeted populations.

Systematic evaluation of commercially available pain management apps examining behavior change techniques.

Mobile health (mHealth) apps have the potential to enhance pain management through the use of daily diaries, medication and appointment reminders, education, and facilitating communication between patients and providers. Although many pain management apps exist, the extent to which these apps use evidence-based behavior change techniques (BCTs) remains largely unknown, making it nearly impossible for providers to recommend apps with evidence-based strategies. This study systematically evaluated commercially available pain management apps for evidence-based BCTs and app quality. Pain management apps were identified using the search terms "pain" and "pain management" in the App and Google Play stores. Reviewed apps were specific to pain management, in English, for patients, and free. A total of 28 apps were coded using the taxonomy of BCTs. App quality was assessed using the Mobile App Rating Scale. Apps included 2 to 15 BCTs (M = 7.36) and 1 to 8 (M = 4.21) pain management-specific BCTs. Prompt intention formation, instruction, behavioral-health link, consequences, feedback, and self-monitoring were the most common BCTs used in the reviewed apps. App quality from the Mobile App Rating Scale ranged from 2.27 to 4.54 (M = 3.65) out of a possible 5, with higher scores indicating better quality. PainScale followed by Migraine Buddy demonstrated the highest number of overall and pain management BCTs as well as good quality scores. Although existing apps should be assessed through randomized controlled trials and future apps should include capabilities for electronic medical record integration, current pain management apps often use evidence-based pain management BCTs.

Using the behaviour change technique taxonomy v1 (BCTTv1) to identify the active ingredients of pharmacist interventions to improve non-hospitalised patient health outcomes

ObjectivesThe aim of this study was to identify which behaviour change techniques (BCTs) were present in intervention and control groups of randomised controlled trials (RCTs) included in a Cochrane systematic...

Dietary education programs for adults with neurological diseases: a scoping review protocol.

The objective of this review is to identify and map the evidence on the types of dietary education programs that have been implemented and evaluated in any setting for adults with neurological diseases. This review will also examine program characteristics, including program duration, length, and number of sessions, and common behavior change techniques used. Up to 1 billion people are affected by neurological diseases, most commonly Alzheimer's disease and dementias, epilepsy, Huntington's disease, motor neurone disease, multiple sclerosis, Parkinson's disease, and stroke. Dietary recommendations for most of these diseases follow national dietary guidelines. Dietary education programs are recommended by the World Health Organization to promote adherence to a healthy diet, but it is not clear which dietary education programs have been conducted for adults with neurological diseases or the characteristics of such programs. This review will consider qualitative and intervention studies (randomized controlled trials, non-randomized controlled trials, and pre-post studies) evaluating dietary education programs for adults with neurological diseases. Programs can be any format in any setting, and may include a comparator group (waitlist control, treatment as usual, or another intervention) or have no comparator group. CINAHL, Cochrane Database of Systematic Reviews, Emcare, MEDLINE, ProQuest (ProQuest Central and ProQuest Dissertations & Theses), PsycINFO, Cochrane Central Register of Controlled Trials, and Google Scholar will be searched for publications in English. Neurological organizations will be contacted for unpublished literature. Titles and abstracts will be screened, and full texts accessed for final inclusion. Intervention details, study outcomes, behavior change techniques, and findings will be extracted. Results will be presented in a table with accompanying description.

Unpacking mHealth interventions: A systematic review of behavior change techniques used in randomized controlled trials assessing mHealth effectiveness.

ObjectiveMobile health interventions have surged in popularity but their implementation varies widely and evidence of effectiveness is mixed. We sought to advance understanding of the diversity of behavior change techniques in mHealth interventions, especially those that leverage advanced mobile technologies.MethodsWe conducted a systematic review of articles published between 2007 and 2017 in high-impact journals in medicine, medical informatics, and health psychology to identify randomized controlled trials in which the effectiveness of an mobile health intervention was tested. Search terms included a mix of general (e.g. mobile health), hardware (e.g. Android, iPhone), and format (e.g. SMS, application) terms.ResultsIn a systematic review of 21 studies, we found the techniques of personalization, feedback and monitoring, and associations were most commonly used in mobile health interventions, but there remains considerable opportunity to leverage more sophisticated aspects of ubiquitous computing. We found that prompts and cues were the most common behavior change techniques used in effective trials, but there was notable overlap in behavior change techniques used in ineffective trials.ConclusionsOur results identify techniques that are commonly used in mobile health interventions and highlight pathways to advance the science of mobile health.