scholarly journals Do Interventions Based on Behavioral Theory Work in the Real World?

2019 ◽  
Author(s):  
Martin S Hagger ◽  
Mike Weed
Keyword(s):  
Behavior Change ◽  
Health Outcomes ◽  
Real World ◽  
Behavioral Interventions ◽  
Population Level ◽  
Health Behavior Change ◽  
Individual Behavior ◽  
Behavioral Theory ◽  
The Real ◽  
Effectiveness Trials

BackgroundBehavioral scientists suggest that for behavior change interventions to work effectively, and deliver population-level health outcomes, they must be underpinned by behavioral theory. However, despite implementation of such interventions, population levels of both health outcomes and linked behaviors have remained relatively static. We debate the extent to which interventions based on behavioral theory work in the real world to address population health outcomes.DiscussionHagger argues there is substantive evidence supporting the efficacy and effectiveness of interventions based on behavioral theory in promoting population-level health behavior change in the ‘real world’. However, large-scale effectiveness trials within existing networks are relatively scarce, and more are needed leveraging insights from implementation science. Importantly, sustained investment in effective behavioral interventions is needed, and behavioral scientists should engage in greater advocacy to persuade gatekeepers to invest in behavioral interventions.Weed argues there is no evidence to demonstrate behavioral theory interventions are genuinely effective in real world settings in populations that are offered them: they are merely efficacious for those that receive them. Despite behavioral volatility that is a normal part of maintaining steady-state population behavior levels creating the illusion of effectiveness, interventions fail in shifting the curve of population behaviors because they focus on individuals rather than populations.Hagger responds that behavioral interventions work in the ‘real world’ in spite of, not because of, flux in health behaviors, and that the contention that behavioral theory focuses solely on individual behavior change is inaccurate.Weed responds that the focus on extending the controls of efficacy trials into implementation is impractical, uneconomic and futile, and this has squandered opportunities to conduct genuine effectiveness trials in naturalistic settings.SummaryHagger contends that interventions based on behavioral theory are effective in changing population-level behavior in ‘real world’ contexts, but more evidence on how best to implement them and how to engage policymakers and practitioners to provide sustained funding is needed. Weed argues for a paradigm shift, away from aggregative attempts to effect individual behavior change towards a focus on disrupting social practices, underpinned by understanding social and economic causation of the distribution and acceptance of behaviors in a population.

Antifragile Behavior Change through Digital Behavior Change Interventions (Preprint)

2021 ◽  
Author(s):  
Benjamin T Kaveladze ◽  
Sean D Young ◽  
Stephen M Schueller
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Behavior Change ◽  
Health Outcomes ◽  
Real World ◽  
Change Process ◽  
Digital Health ◽  
Health Behavior Change ◽  
Behavior Change Interventions ◽  
Future Work

UNSTRUCTURED Digital health behavior change interventions (DHBCIs) are popular and widely-accessible tools for helping people to pursue behavior change goals. However, their effectiveness tends to be low in real-world settings. Drawing from Nassim Nicholas Taleb’s concept of antifragility, we introduce antifragile behavior change, a strategy that leverages user-specific characteristics to make the behavior change process more efficient. Next, we propose two principles for designing DHBCIs to support antifragile behavior change: first, DHBCIs should provide personalized guidance that accounts for user-specific circumstances and goals; second, DHBCIs should prioritize user agency by refraining from using nudges that might manipulate user decision-making. We hope this paper will encourage researchers and product developers to reconsider DHBCI design through the lens of antifragility. Future work can examine if DHBCIs that are consistent with our principles of designing for antifragile behavior change lead to better mental health outcomes than other DHBCIs.

A Procedural Model for Planning and Evaluating Behavioral Interventions

2005 ◽  
Vol 44 (02) ◽  
pp. 299-302
Author(s):  
G. C. Hyner
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Behavioral Interventions ◽  
Health Behavior Change ◽  
Behavior Changes ◽  
Change Strategies ◽  
Innovative Strategies ◽  
Proposed Model ◽  
Influence Behavior

Summary Objective: A model for planning, implementing and evaluating health behavior change strategies is proposed. Variables are presented which can be used in the model or serve as examples for how the model is utilized once a theory of health behavior is adopted. Results: Examples of three innovative strategies designed to influence behavior change are presented so that the proposed model can be modified for use following comprehensive screening and baseline measurements. Three measurement priorities: clients, methods and agency are subjected to three phases of assessment: goals, implementation and effects. Conclusion: Lifestyles account for the majority of variability in quality-of-life and premature morbidity and mortality. Interventions designed to influence healthy behavior changes must be driven by theory and carefully planned and evaluated. The proposed model is offered as a useful tool for the behavior change strategist.

scholarly journals eHealth-Based Behavioral Intervention for Increasing Physical Activity in Persons With Multiple Sclerosis: Fidelity Protocol for a Randomized Controlled Trial (Preprint)

2018 ◽  
Author(s):  
Stephanie L Silveira ◽  
Justin McCroskey ◽  
Brooks C Wingo ◽  
Robert W Motl
Keyword(s):  
Physical Activity ◽  
Multiple Sclerosis ◽  
Behavior Change ◽  
Behavioral Intervention ◽  
Behavioral Interventions ◽  
Health Behavior Change ◽  
Phase Iii ◽  
Monitoring Plan ◽  
Randomized Controlled ◽  
Study Results

BACKGROUND The rate of physical activity is substantially lower in persons with multiple sclerosis (MS) than in the general population. This problem can be reversed through rigorous and reproducible delivery of behavioral interventions that target lifestyle physical activity in MS. These interventions are, in part, based on a series of phase II randomized controlled trials (RCTs) supporting the efficacy of an internet-delivered behavioral intervention, which is based on social cognitive theory (SCT) for increasing physical activity in MS. OBJECTIVE This paper outlines the strategies and monitoring plan developed based on the National Institutes of Health Behavior Change Consortium (NIH BCC) treatment fidelity workgroup that will be implemented in a phase III RCT. METHODS The Behavioral Intervention for Physical Activity in Multiple Sclerosis (BIPAMS) study is a phase III RCT that examines the effectiveness of an internet-delivered behavioral intervention based on SCT and is supported by video calls with a behavioral coach for increasing physical activity in MS. BIPAMS includes a 6-month treatment condition and 6-month follow-up. The BIPAMS fidelity protocol includes the five areas outlined by the NIH BCC. The study design draws on the SCT behavior-change strategy, ensures a consistent dose within groups, and plans for implementation setbacks. Provider training in theory and content will be consistent between groups with monitoring plans in place such as expert auditing of calls to ensure potential drift is addressed. Delivery of treatment will be monitored through the study website and training will focus on avoiding cross-contamination between conditions. Receipt of treatment will be monitored via coaching call notes and website monitoring. Lastly, enactment of treatment for behavioral and cognitive skills will be monitored through coaching call notes among other strategies. The specific strategies and monitoring plans will be consistent between conditions within the constraints of utilizing existing evidence-based interventions. RESULTS Enrollment began in February 2018 and will end in September 2019. The study results will be reported in late 2020. CONCLUSIONS Fidelity-reporting guidelines provided by the NIH BCC were published in 2004, but protocols are scarce. This is the first fidelity-monitoring plan involving an electronic health behavioral intervention for increasing physical activity in MS. This paper provides a model for other researchers utilizing the NIH BCC recommendations to optimize the rigor and reproducibility of behavioral interventions in MS. CLINICALTRIAL ClinicalTrials.gov NCT03490240; https://www.clinicaltrials.gov/ct2/show/NCT03490240. INTERNATIONAL REGISTERED REPOR DERR1-10.2196/12319

scholarly journals Impact of the Method of Delivering Electronic Health Behavior Change Interventions in Survivors of Cancer on Engagement, Health Behaviors, and Health Outcomes: Systematic Review and Meta-Analysis (Preprint)

2019 ◽  
Author(s):  
Kate Furness ◽  
Mitchell N Sarkies ◽  
Catherine E Huggins ◽  
Daniel Croagh ◽  
Terry P Haines
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Health Behavior ◽  
Behavior Change ◽  
Health Outcomes ◽  
Meta Analysis ◽  
Health Behavior Change ◽  
Patients With Cancer ◽  
Behavior Change Interventions

BACKGROUND Increased accessibility to the internet and mobile devices has seen a rapid expansion in electronic health (eHealth) behavior change interventions delivered to patients with cancer and survivors using synchronous, asynchronous, and combined delivery methods. Characterizing effective delivery methods of eHealth interventions is required to enable improved design and implementation of evidence-based health behavior change interventions. OBJECTIVE This study aims to systematically review the literature and synthesize evidence on the success of eHealth behavior change interventions in patients with cancer and survivors delivered by synchronous, asynchronous, or combined methods compared with a control group. Engagement with the intervention, behavior change, and health outcomes, including quality of life, fatigue, depression, and anxiety, were examined. METHODS A search of Scopus, Ovid MEDLINE, Excerpta Medica dataBASE, Cumulative Index to Nursing and Allied Health Literature Plus, PsycINFO, Cochrane CENTRAL, and PubMed was conducted for studies published between March 2007 and March 2019. We looked for randomized controlled trials (RCTs) examining interventions delivered to adult cancer survivors via eHealth methods with a measure of health behavior change. Random-effects meta-analysis was performed to examine whether the method of eHealth delivery impacted the level of engagement, behavior change, and health outcomes. RESULTS A total of 24 RCTs were included predominantly examining dietary and physical activity behavior change interventions. There were 11 studies that used a synchronous approach and 11 studies that used an asynchronous approach, whereas 2 studies used a combined delivery method. Use of eHealth interventions improved exercise behavior (standardized mean difference [SMD] 0.34, 95% CI 0.21-0.48), diet behavior (SMD 0.44, 95% CI 0.18-0.70), fatigue (SMD 0.21, 95% CI −0.08 to 0.50; SMD change 0.22, 95% CI 0.09-0.35), anxiety (SMD 1.21, 95% CI: 0.36-2.07; SMD change 0.15, 95% CI −0.09 to 0.40), depression (SMD 0.15, 95% CI 0.00-0.30), and quality of life (SMD 0.12, 95% CI −0.10 to 0.34; SMD change 0.14, 95% CI 0.04-0.24). The mode of delivery did not influence the amount of dietary and physical activity behavior change observed. CONCLUSIONS Physical activity and dietary behavior change eHealth interventions delivered to patients with cancer or survivors have a small to moderate impact on behavior change and a small to very small benefit to quality of life, fatigue, depression, and anxiety. There is insufficient evidence to determine whether asynchronous or synchronous delivery modes yield superior results. Three-arm RCTs comparing delivery modes with a control with robust engagement reporting are required to determine the most successful delivery method for promoting behavior change and ultimately favorable health outcomes.

scholarly journals Efficacy of a Multiple Health Behavior Change Intervention on Women’s Health Outcomes

2017 ◽  
Vol 3 (1) ◽  
pp. 8-14
Author(s):  
Abigail Remenapp ◽  
◽  
Brantlee Broome ◽  
Gail Maetozo ◽  
Heather Hausenblas ◽  
...  
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Health Outcomes ◽  
Women’S Health ◽  
Women's Health ◽  
Health Behavior Change ◽  
Behavior Change Intervention ◽  
Multiple Health Behavior Change ◽  
Multiple Health
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