Behavior change techniques used to promote walking and cycling: a systematic review.
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ABSTRACT: Objective
Evidence on the effectiveness of walking and cycling interventions is mixed. This may be partly attributable to differences in intervention content, such as the cognitive and behavioral techniques (BCTs) used. Adopting a taxonomy of BCTs, this systematic review addressed two questions: (a) What are the behavior change techniques used in walking and cycling interventions targeted at adults? (b) What characterizes interventions that appear to be associated with changes in walking and cycling in adults?Method
Previous systematic reviews and updated database searches were used to identify controlled studies of individual-level walking and cycling interventions involving adults. Characteristics of intervention design, context, and methods were extracted in addition to outcomes. Intervention content was independently coded according to a 26-item taxonomy of BCTs.Results
Studies of 46 interventions met the inclusion criteria. Twenty-one reported a statistically significant effect on walking and cycling outcomes. Analysis revealed substantial heterogeneity in the vocabulary used to describe intervention content and the number of BCTs coded. "Prompt self-monitoring of behavior" and "prompt intention formation" were the most frequently coded BCTs.Conclusion
Future walking and cycling intervention studies should ensure that all aspects of the intervention are reported in detail. The findings lend support to the inclusion of self-monitoring and intention formation techniques in future walking and cycling intervention design, although further exploration of these and other BCTs is required. Further investigation of the interaction between BCTs and study design characteristics would also be desirable.
SUBMITTER: Bird EL
PROVIDER: S-EPMC3727344 | biostudies-literature | 2013 Aug
REPOSITORIES: biostudies-literature
Publications
Behavior change techniques used to promote walking and cycling: a systematic review.
Bird Emma L EL Baker Graham G Mutrie Nanette N Ogilvie David D Sahlqvist Shannon S Powell Jane J
Health psychology : official journal of the Division of Health Psychology, American Psychological Association 20130311 8
<h4>Objective</h4>Evidence on the effectiveness of walking and cycling interventions is mixed. This may be partly attributable to differences in intervention content, such as the cognitive and behavioral techniques (BCTs) used. Adopting a taxonomy of BCTs, this systematic review addressed two questions: (a) What are the behavior change techniques used in walking and cycling interventions targeted at adults? (b) What characterizes interventions that appear to be associated with changes in walking ...[more]
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Project description:Women in midlife experience health risks that could be mitigated by regular physical activity and reduced sedentary time, but this population rarely achieves physical activity levels that would protect their health. As a result, many behavioral interventions are designed to promote physical activity in this population, which are purportedly guided by theoretical models of health behavior (change) and activate an associated set of behavior change techniques (BCTs). The efficacy and effectiveness of these interventions appear to be limited, however, raising questions about their design and adaptation for women in midlife. Several aspects of these interventions are currently unclear. Specifically, which women they target (i.e., how "midlife" and "sedentary" or "inactive" are defined), which theoretical models or behavior BCTs are used, and how BCTs are activated in such interventions. A synthesis of this information would be useful as an initial step toward improving physical activity interventions for this at-risk group, and thus, represented the goal of the present scoping review. Eligibility required publication in a peer-reviewed journal in English between 2000 and 2021, inclusion of only women in midlife who did not have any medical or other restrictions on their physical activity (e.g., cancer diagnosis), and free-living physical activity or sedentary behavior as the target outcome (with associated assessment). Of the 4,410 initial results, 51 articles met inclusion criteria, and these described 36 unique interventions. More than half of the articles (59%) named an underlying theoretical model and interventions included an average of 3.76 identifiable BCTs (range 1-11). However, descriptions of many interventions were limited and did not provide enough detail to determine whether or how specific BCTs were activated. Interventions also used a wide range of inclusion criteria for age range and starting activity level, which has implications for targeting/tailoring and effectiveness, and many interventions focused on marginalized populations (e.g., women from racial/ethnic minority backgrounds, those un- or under-insured). The present review identifies some strengths and highlights important limitations of existing literature, as well as key opportunities for advancing the design and potential utility of physical activity interventions for women in midlife.Systematic review registrationhttps://osf.io/g8tuc.
| S-EPMC9534296 | biostudies-literature
Project description:Behavior change interventions typically contain multiple potentially active components: behavior change techniques (BCTs). Identifying which specific BCTs or BCT combinations have the potential to be effective for a given behavior in a given context presents a major challenge. The aim of this study was to review the methods that have been used to identify effective BCTs for given behaviors in given contexts and evaluate their strengths and limitations. A scoping review was conducted of studies that had sought to identify effective BCTs. Articles referring to "behavio(u)r change technique(s)" in the abstract/text were located, and ones that involved identification of effective BCTs were selected. The methods reported were coded. The methods were analyzed in general terms using "PASS" criteria: Practicability (facility to apply the method appropriately), Applicability (facility to generalize from findings to contexts and populations of interest), Sensitivity (facility to identify effective BCTs), and Specificity (facility to rule out ineffective BCTs). A sample of 10% of the studies reviewed was then evaluated using these criteria to assess how far the strengths and limitations identified in principle were borne out in practice. One hundred and thirty-five studies were identified. The methods used in those studies were experimental manipulation of BCTs, observational studies comparing outcomes in the presence or absence of BCTs, meta-analyses of BCT comparisons, meta-regressions evaluating effect sizes with and without specific BCTs, reviews of BCTs found in effective interventions, and meta-classification and regression trees. The limitations of each method meant that only weak conclusions could be drawn regarding the effectiveness of specific BCTs or BCT combinations. Methods for identifying effective BCTs linked to target behavior and context all have important inherent limitations. A strategy needs to be developed that can systematically combine the strengths of the different methods and that can link these constructs in an ontology of behavior change interventions.
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Project description: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.
| S-EPMC9508675 | biostudies-literature
Project description:BackgroundDigital health interventions are efficacious in health-promoting behaviors (eg, healthy eating and regular physical activity) that mitigate health risks and menopausal symptoms in midlife. However, integrated evidence-based knowledge about the mechanisms of change in these interventions is unclear.ObjectiveThis systematic review aimed to evaluate studies on behavior change techniques (BCTs) and mechanisms of change in digital health interventions aimed at promoting health-enhancing behaviors in midlife women (aged 40-65 years).MethodsA systematic literature search of the electronic databases PubMed, Web of Science, PsycINFO, and Cochrane Central Register of Controlled Trials in the Cochrane Library was conducted. In total, 2 independent reviewers selected the studies for inclusion, extracted data, and completed BCT mapping of eligible studies. The mechanism of action and intervention functions of eligible studies were evaluated using the behavior change wheel framework. Reporting of psychological theory use within these interventions was explored using the Theory Coding Scheme. Mode of delivery, psychological theory, and BCTs were presented as descriptive statistics.ResultsIn total, 13 interventions (including 1315 women) reviewed used 13 (SD 4.30, range 6-21) BCTs per intervention on average. The "Shaping knowledge" and "Repetition and substitution" behavior change categories were used most frequently, with 92% (12/13) of the interventions implementing at least one of the BCTs from these 2 categories. Only 13.98% (169/1209) of the 93 available BCTs were used, with "Instructions on behaviour" most frequently used (12/13, 92%). The behavior change wheel mapping suggests that half of the intervention content aimed to increase "Capability" (49/98, 50% of the intervention strategies), "Motivation" (41/98, 42%), and "Opportunity" (8/98, 8%). "Behavioural Regulation" was the most frequently used mechanism of action (15/98, 15%), followed by increasing "Knowledge" (13/98, 13%) and "Cognitive and Interpersonal skills" (10/98, 10%). A total of 78% (7/9) of the intervention functions were used in the studies to change behavior, primarily through "Enablement" (60/169, 35.5%), whereas no study used "Restriction" or "Modelling" functions. Although 69% (9/13) of the interventions mentioned a psychological theory or model, most (10/13, 77%) stated or suggested rather than demonstrated the use of a theoretical base, and none reported explicit links between all BCTs within the intervention and the targeted theoretical constructs. Technological components were primarily based on web-based (9/13, 69%) modes of delivery, followed by phone or SMS text message (8/13, 62%) and wearables (7/13, 54%).ConclusionsThe findings of this review indicate an overall weak use of theory, low levels of treatment fidelity, insignificant outcomes, and insufficient description of several interventions to support the assessment of how specific BCTs were activated. Thus, the identified limitations in the current literature provide an opportunity to improve the design of lifestyle health-enhancing interventions for women in midlife.Trial registrationPROSPERO CRD42021259246; https://tinyurl.com/4ph74a9u.
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Project description:ObjectivesTo determine what interventions are effective in promoting cycling, the size of the effects of interventions, and evidence of any associated benefits on overall physical activity or anthropometric measures.DesignSystematic review.Data sourcesPublished and unpublished reports in any language identified by searching 13 electronic databases, websites, reference lists, and existing systematic reviews, and papers identified by experts in the field. Review methods Controlled "before and after" experimental or observational studies of the effect of any type of intervention on cycling behaviour measured at either individual or population level.ResultsTwenty five studies (of which two were randomised controlled trials) from seven countries were included. Six studies examined interventions aimed specifically at promoting cycling, of which four (an intensive individual intervention in obese women, high quality improvements to a cycle route network, and two multifaceted cycle promotion initiatives at town or city level) were found to be associated with increases in cycling. Those studies that evaluated interventions at population level reported net increases of up to 3.4 percentage points in the population prevalence of cycling or the proportion of trips made by bicycle. Sixteen studies assessing individualised marketing of "environmentally friendly" modes of transport to interested households reported modest but consistent net effects equating to an average of eight additional cycling trips per person per year in the local population. Other interventions that targeted travel behaviour in general were not associated with a clear increase in cycling. Only two studies assessed effects of interventions on physical activity; one reported a positive shift in the population distribution of overall physical activity during the intervention.ConclusionsCommunity-wide promotional activities and improving infrastructure for cycling have the potential to increase cycling by modest amounts, but further controlled evaluative studies incorporating more precise measures are required, particularly in areas without an established cycling culture. Studies of individualised marketing report consistent positive effects of interventions on cycling behaviour, but these findings should be confirmed using more robust study designs. Future research should also examine how best to promote cycling in children and adolescents and through workplaces. Whether interventions to promote cycling result in an increase in overall physical activity or changes in anthropometric measures is unclear.
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Project description:BackgroundDigital behavior change interventions (DBCIs) appear to reduce alcohol consumption, but greater understanding is needed of their mechanisms of action.PurposeTo describe the behavior change techniques (BCTs) used in DBCIs and examine whether individual BCTs, the inclusion of more BCTs or more Control Theory congruent BCTs is associated with increased effectiveness.MethodsForty-one randomized control trials were extracted from a Cochrane review of alcohol reduction DBCIs and coded for up to 93 BCTs using an established and reliable method. Random effects unadjusted and adjusted meta-regression models were performed to assess associations between BCTs and intervention effectiveness.ResultsInterventions used a mean of 9.1 BCTs (range 1-22), 23 different BCTs were used in four or more trials. Trials that used "Behavior substitution" (-95.112 grams per week [gpw], 95% CI: -162.90, -27.34), "Problem solving" (-45.92 gpw, 95% CI: -90.97, -0.87) and "Credible source" (-32.09 gpw, 95% CI: -60.64, -3.55) were significantly associated with greater alcohol reduction than trials without these BCTs. The "Behavior substitution" result should be treated as preliminary because it was reported in only four trials, three of which were conducted by the same research group. "Feedback" was used in 98% of trials (n = 41); other Control Theory congruent BCTs were used less frequently: for example, "Goal setting" 43% (n = 18) and "Self-monitoring" 29%, (n = 12).Conclusions"Behavior substitution," "Problem solving," and "Credible source" were associated with greater alcohol reduction. Many BCTs were used infrequently in DBCIs, including BCTs with evidence of effectiveness in other domains, such as "Self-monitoring" and "Goal setting."
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Project description:BackgroundMobile health (mHealth) apps targeting health behaviors using behavior change techniques (BCTs) have been successful in promoting healthy behaviors; however, their efficacy with sleep is unclear. Some work has shown success in promoting sleep through mHealth, whereas there have been reports that sleep apps can be adverse and lead to unhealthy obsessions with achieving perfect sleep.ObjectiveThis study aims to report and describe the use of BCTs in mHealth apps for sleep with the following research questions: How many BCTs are used on average in sleep apps, and does this relate to their effectiveness on sleep outcomes? Are there specific BCTs used more or less often in sleep apps, and does this relate to their effectiveness on sleep outcomes? Does the effect of mHealth app interventions on sleep change when distinguishing between dimension and measurement of sleep?MethodsWe conducted a systematic review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to review articles on mHealth app interventions for sleep published between 2010 and 2020.ResultsA total of 12 studies met the eligibility criteria. Most studies reported positive sleep outcomes, and there were no negative effects reported. Sleep quality was the most common dimension of sleep targeted. Subjective measures of sleep were used across all apps, whereas objective measures were often assessed but rarely reported as part of results. The average number of BCTs used was 7.67 (SD 2.32; range 3-11) of 16. Of the 12 studies, the most commonly used BCTs were feedback and monitoring (n=11, 92%), shaping knowledge (n=11, 92%), goals and planning (n=10, 83%), and antecedents (n=10, 83%), whereas the least common were scheduled consequences (n=0, 0%), self-belief (n=0, 0%), and covert learning (n=0, 0%). Most apps used a similar set of BCTs that unfortunately did not allow us to distinguish which BCTs were present when studies reported more positive outcomes.ConclusionsOur study describes the peer-reviewed literature on sleep apps and provides a foundation for further examination and optimization of BCTs used in mHealth apps for sleep. We found strong evidence that mHealth apps are effective in improving sleep, and the potential reasons for the lack of adverse sleep outcome reporting are discussed. We found evidence that the type of BCTs used in mHealth apps for sleep differed from other health outcomes, although more research is needed to understand how BCTs can be implemented effectively to improve sleep using mHealth and the mechanisms of action through which they are effective (eg, self-efficacy, social norms, and attitudes).
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