Supplemental Material for Do Single and Multiple Behavior Change Interventions Contain Different Behavior Change Techniques? A Comparison of Interventions Targeting Physical Activity in Obese Populations

2014 ◽  
Keyword(s):  
Physical Activity ◽  
Behavior Change ◽  
Behavior Change Techniques ◽  
Multiple Behavior Change ◽  
Behavior Change Interventions

scholarly journals Do Combinations of Behavior Change Techniques That Occur Frequently in Interventions Reflect Underlying Theory?

2020 ◽  
Vol 54 (11) ◽  
pp. 827-842
Author(s):  
Lauren Connell Bohlen ◽  
Susan Michie ◽  
Marijn de Bruin ◽  
Alexander J Rothman ◽  
Michael P Kelly ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Behavior Change ◽  
Behavioral Interventions ◽  
Intervention Development ◽  
Evidence Base ◽  
Behavior Change Techniques ◽  
Multiple Behavior Change ◽  
Behavior Change Interventions ◽  
Theory Use ◽  
Behavior Change Theories

Abstract Background Behavioral interventions typically include multiple behavior change techniques (BCTs). The theory informing the selection of BCTs for an intervention may be stated explicitly or remain unreported, thus impeding the identification of links between theory and behavior change outcomes. Purpose This study aimed to identify groups of BCTs commonly occurring together in behavior change interventions and examine whether behavior change theories underlying these groups could be identified. Methods The study involved three phases: (a) a factor analysis to identify groups of co-occurring BCTs from 277 behavior change intervention reports; (b) examining expert consensus (n = 25) about links between BCT groups and behavioral theories; (c) a comparison of the expert-linked theories with theories explicitly mentioned by authors of the 277 intervention reports. Results Five groups of co-occurring BCTs (range: 3–13 BCTs per group) were identified through factor analysis. Experts agreed on five links (≥80% of experts), comprising three BCT groups and five behavior change theories. Four of the five BCT group–theory links agreed by experts were also stated by study authors in intervention reports using similar groups of BCTs. Conclusions It is possible to identify groups of BCTs frequently used together in interventions. Experts made shared inferences about behavior change theory underlying these BCT groups, suggesting that it may be possible to propose a theoretical basis for interventions where authors do not explicitly put forward a theory. These results advance our understanding of theory use in multicomponent interventions and build the evidence base for further understanding theory-based intervention development and evaluation.

scholarly journals Behavior change techniques in mobile applications for sedentary behavior

2018 ◽  
Vol 4 ◽  
pp. 205520761878579 ◽  
Author(s):  
Emily E Dunn ◽  
Heather L Gainforth ◽  
Jennifer E Robertson-Wilson
Keyword(s):  
Physical Activity ◽  
Behavior Change ◽  
Sedentary Behavior ◽  
Mobile Applications ◽  
Health Behavior Change ◽  
Behavior Change Techniques ◽  
Self Monitoring ◽  
Behavior Change Interventions ◽  
And Behavior ◽  
Keyword Searches

Objective Mobile applications (apps) are increasingly being utilized in health behavior change interventions. To determine the presence of underlying behavior change mechanisms, apps for physical activity have been coded for behavior change techniques (BCTs). However, apps for sedentary behavior have yet to be assessed for BCTs. Thus, the purpose of the present study was to review apps designed to decrease sedentary time and determine the presence of BCTs. Methods Systematic searches of the iTunes App and Google Play stores were completed using keyword searches. Two reviewers independently coded free ( n = 36) and paid ( n = 14) app descriptions using a taxonomy of 93 BCTs (December 2016–January 2017). A subsample ( n = 4) of free apps were trialed for one week by the reviewers and coded for the presence of BCTs (February 2017). Results In the free and paid app descriptions, only 10 of 93 BCTs were present with a mean of 2.42 BCTs (range 0–6) per app. The BCTs coded most frequently were “prompts/cues” ( n = 43), “information about health consequences” ( n = 31), and “self-monitoring of behavior” ( n = 17). For the four free apps that were trialed, three additional BCTs were coded that were not coded in the descriptions: “graded tasks,” “focus on past successes,” and “behavior substitution.” Conclusions These sedentary behavior apps have fewer BCTs compared with physical activity apps and traditional (i.e., non-app) physical activity and healthy eating interventions. The present study sheds light on the behavior change potential of sedentary behavior apps and provides practical insight about coding for BCTs in apps.

scholarly journals Key facets to build up eHealth and mHealth interventions to enhance physical activity, sedentary behavior and nutrition in healthy subjects – An umbrella review

2020 ◽  
Author(s):  
Janis Fiedler ◽  
Tobias Eckert ◽  
Kathrin Wunsch ◽  
Alexander Woll
Keyword(s):  
Physical Activity ◽  
Behavior Change ◽  
Sedentary Behavior ◽  
Healthy Eating ◽  
Social Contexts ◽  
Just In Time ◽  
Umbrella Review ◽  
Behavior Change Techniques ◽  
Adaptive Interventions ◽  
The Impact

Abstract Background: Electronic (eHealth) and mobile (mHealth) health interventions can provide a large coverage, and are promising tools to change health behavior (i.e. physical activity, sedentary behavior and healthy eating). However, the determinants of intervention effectiveness in primary prevention has not been explored yet. Therefore, the objectives of this umbrella review were to evaluate intervention effectiveness, to explore the impact of pre-defined determinants of effectiveness (i.e. theoretical foundations, behavior change techniques, social contexts or just-in-time adaptive interventions), and to provide recommendations for future research and practice in the field of primary prevention delivered via e/mHealth technology.Methods: PubMed, Scopus, Web of Science and the Cochrane Library were searched for systematic reviews and meta-analyses (reviews) published between January 1990 and May 2020. Reviews reporting on e/mHealth behavior change interventions in physical activity, sedentary behavior and/or healthy eating for healthy subjects (i.e. subjects without physical or physiological morbidities which would influence the realization of behaviors targeted by the respective interventions) were included if they also investigated respective theoretical foundations, behavior change techniques, social contexts or just-in-time adaptive interventions. Included studies were ranked concerning their methodological quality and qualitatively synthesized.Results: The systematic search reveled eleven systematic reviews and meta-analyses of moderate quality. The majority of original research studies within the reviews found e/mHealth interventions to be effective, but the results showed a high heterogeneity concerning assessment methods and outcomes, making them difficult to compare. Whereas theoretical foundation and behavior change techniques were suggested to be potential positive determinants of effective interventions, the impact of social context remains unclear. None of the reviews included just-in-time adaptive interventions.Conclusion: Findings of this umbrella review support the use of e/mHealth to enhance physical activity and healthy eating and reduce sedentary behavior. The general lack of precise reporting and comparison of confounding variables in reviews and original research studies as well as the limited number of reviews for each health behavior constrains the generalization and interpretation of results. Further research is needed on study-level to investigate effects of versatile determinants of e/mHealth efficiency, using a theoretical foundation and additionally explore the impact of social contexts and more sophisticated approaches like just-in-time adaptive interventions.Trial registration: The protocol for this umbrella review was a priori registered with PROSPERO: CRD42020147902.

scholarly journals Behavioral Intervention Components Associated With Cost-effectiveness: A Comparison of Six Domains

2021 ◽  
Author(s):  
E Beard ◽  
F Lorencatto ◽  
B Gardner ◽  
S Michie ◽  
L Owen ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Behavior Change ◽  
Lower Cost ◽  
Self Regulation ◽  
Cost Effective ◽  
Cost Effectiveness Ratio ◽  
Behavior Change Techniques ◽  
Multiple Health Behaviors ◽  
Behavior Change Interventions ◽  
Multiple Health

Abstract Background To help implement behavior change interventions (BCIs) it is important to be able to characterize their key components and determine their effectiveness. Purpose This study assessed and compared the components of BCIs in terms of intervention functions identified using the Behaviour Change Wheel Framework (BCW) and in terms of their specific behavior change techniques (BCTs) identified using the BCT TaxonomyV1, across six behavioral domains and the association of these with cost-effectiveness. Methods BCIs in 251 studies targeting smoking, diet, exercise, sexual health, alcohol and multiple health behaviors, were specified in terms of their intervention functions and their BCTs, grouped into 16 categories. Associations with cost-effectiveness measured in terms of incremental cost-effectiveness ratio (ICER) upper and lower estimates were determined using regression analysis. Results The most prevalent functions were increasing knowledge through education (72.1%) and imparting skills through training (74.9%). The most prevalent BCT groupings were shaping knowledge (86.5%), changing behavioral antecedents (53.0%), supporting self-regulation (47.7%), and providing social support (44.6%). Intervention functions associated with better cost-effectiveness were those based on training (βlow = −15044.3; p = .002), persuasion (βlow = −19384.9; p = .001; βupp = −25947.6; p < .001) and restriction (βupp = −32286.1; p = .019), and with lower cost-effectiveness were those based on environmental restructuring (β = 15023.9low; p = .033). BCT groupings associated with better cost-effectiveness were goals and planning (βlow = −8537.3; p = .019 and βupp = −12416.9; p = .037) and comparison of behavior (βlow = −13561.9, p = .047 and βupp = −30650.2; p = .006). Those associated with lower cost-effectiveness were natural consequences (βlow = 7729.4; p = .033) and reward and threat (βlow = 20106.7; p = .004). Conclusions BCIs that focused on training, persuasion and restriction may be more cost-effective, as may those that encourage goal setting and comparison of behaviors with others.

scholarly journals Prostate Cancer Survivors’ and Caregivers’ Experiences Using Behavior Change Techniques during a Web-Based Self-Management and Physical Activity Program: A Qualitative Study

2020 ◽  
Vol 9 (10) ◽  
pp. 3244
Author(s):  
Laura Hallward ◽  
Keryn Chemtob ◽  
Sylvie D. Lambert ◽  
Lindsay R. Duncan
Keyword(s):  
Physical Activity ◽  
Prostate Cancer ◽  
Qualitative Study ◽  
Behavior Change ◽  
Management Program ◽  
Self Management ◽  
Positive Outcomes ◽  
Structured Interviews ◽  
Behavior Change Techniques ◽  
Web Based

Both men with prostate cancer and their caregivers report experiencing a number of challenges and health consequences, and require programs to help support the cancer patient–caregiver dyad. A tailored, web-based, psychosocial and physical activity self-management program (TEMPO), which implements behavior change techniques to help facilitate behavior change for the dyads was created and its acceptability was tested in a qualitative study. The purpose of this secondary analysis was to explore the dyads’ experiences using behavior change techniques to change behavior and address current needs and challenges while enrolled in TEMPO. Multiple semi-structured interviews were conducted with 19 prostate cancer-caregiver dyads over the course of the program, resulting in 46 transcripts that were analyzed using an inductive thematic analysis. Results revealed four main themes: (1) learning new behavior change techniques, (2) engaging with behavior change techniques learned in the past, (3) resisting full engagement with behavior change techniques, and (4) experiencing positive outcomes from using behavior change techniques. The dyads’ discussions of encountering behavior change techniques provided unique insight into the process of learning and implementing behavior change techniques through a web-based self-management program, and the positive outcomes that resulted from behavior changes.

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