Objective: Meta-analyses of behavior change (BC) interventions typically find large heterogeneity in effectiveness and small effects. This study aimed to assess the effectiveness of active BC interventions designed to promote physical activity and healthy eating and investigate whether theoretically specified BC techniques improve outcome. Design: Interventions, evaluated in experimental or quasi-experimental studies, using behavioral and/or cognitive techniques to increase physical activity and healthy eating in adults, were systematically reviewed. Intervention content was reliably classified into 26 BC techniques and the effects of individual techniques, and of a theoretically derived combination of self-regulation techniques, were assessed using meta-regression. Main Outcome Measures: Valid outcomes of physical activity and healthy eating. Results: The 122 evaluations (N 44,747) produced an overall pooled effect size of 0.31 (95% confidence interval 0.26 to 0.36, I 2 69%). The technique, “self-monitoring,” explained the greatest amount of among-study heterogeneity (13%). Interventions that combined selfmonitoring with at least one other technique derived from control theory were significantly more effective than the other interventions (0.42 vs. 0.26). Conclusion: Classifying interventions according to component techniques and theoretically derived technique combinations and conducting meta-regression enabled identification of effective components of interventions designed to increase physical activity and healthy eating.

/pdf/effective-techniques-in-healthy-eating-and-physical-activity-2s4u8fosnx.pdf

Effective Techniques in Healthy Eating and Physical Activity Interventions: A Meta-Regression

Increasing evidence suggests that public health and health-promotion interventions that are based on social and behavioral science theories are more effective than those lacking a theoretical base. This article provides an overview of the state of the science of theory use for designing and conducting health-promotion interventions. Influential contemporary perspectives stress the multiple determinants and multiple levels of determinants of health and health behavior. We describe key types of theory and selected often-used theories and their key concepts, including the health belief model, the transtheoretical model, social cognitive theory, and the ecological model. This summary is followed by a review of the evidence about patterns and effects of theory use in health behavior intervention research. Examples of applied theories in three large public health programs illustrate the feasibility, utility, and challenges of using theory-based interventions. This review concludes by identifying cross-cutting themes and important future directions for bridging the divides between theory, practice, and research.

https://www.annualreviews.org/doi/pdf/10.1146/annurev.publhealth.012809.103604

The role of behavioral science theory in development and implementation of public health interventions.

Abbreviated Contents Figures and Tables Preface Introduction and Examples Concepts Relevant to Information Behavior Models, Paradigms, and Theories in the Study of Information Behavior Methods for Studying Information Behavior Research Results and Reflections Appendix: Glossary Appendix: Questions for Discussion and Application References Index

Looking for Information: A Survey of Research on Information Seeking, Needs and Behavior

https://stacks.cdc.gov/view/cdc/33529/cdc_33529_DS5.pdf

Bridging research and practice: models for dissemination and implementation research.

Background: Although web-based interventions for promoting health and health-related behavior can be effective, poor adherence is a common issue that needs to be addressed Technology as a means to communicate the content in web-based interventions has been neglected in research Indeed, technology is often seen as a black-box, a mere tool that has no effect or value and serves only as a vehicle to deliver intervention content In this paper we examine technology from a holistic perspective We see it as a vital and inseparable aspect of web-based interventions to help explain and understand adherence
Objective: This study aims to review the literature on web-based health interventions to investigate whether intervention characteristics and persuasive design affect adherence to a web-based intervention
Methods: We conducted a systematic review of studies into web-based health interventions Per intervention, intervention characteristics, persuasive technology elements and adherence were coded We performed a multiple regression analysis to investigate whether these variables could predict adherence
Results: We included 101 articles on 83 interventions The typical web-based intervention is meant to be used once a week, is modular in set-up, is updated once a week, lasts for 10 weeks, includes interaction with the system and a counselor and peers on the web, includes some persuasive technology elements, and about 50% of the participants adhere to the intervention Regarding persuasive technology, we see that primary task support elements are most commonly employed (mean 29 out of a possible 70) Dialogue support and social support are less commonly employed (mean 15 and 12 out of a possible 70, respectively) When comparing the interventions of the different health care areas, we find significant differences in intended usage (p = 004), setup (p < 001), updates (p < 001), frequency of interaction with a counselor (p < 001), the system (p = 003) and peers (p = 017), duration (F = 6068, p = 004), adherence (F = 4833, p = 010) and the number of primary task support elements (F = 5631, p = 005) Our final regression model explained 55% of the variance in adherence In this model, a RCT study as opposed to an observational study, increased interaction with a counselor, more frequent intended usage, more frequent updates and more extensive employment of dialogue support significantly predicted better adherence
Conclusions: Using intervention characteristics and persuasive technology elements, a substantial amount of variance in adherence can be explained Although there are differences between health care areas on intervention characteristics, health care area per se does not predict adherence Rather, the differences in technology and interaction predict adherence The results of this study can be used to make an informed decision about how to design a web-based intervention to which patients are more likely to adhere

Persuasive System Design Does Matter: A Systematic Review of Adherence to Web-Based Interventions

Although there is a large and growing literature on tailored print health behavior change interventions, it is currently not known if or to what extent tailoring works. The current study provides a meta-analytic review of this literature, with a primary focus on the effects of tailoring. A comprehensive search strategy yielded 57 studies that met inclusion criteria. Those studies-which contained a cumulative N = 58,454-were subsequently meta-analyzed. The sample size-weighted mean effect size of the effects of tailoring on health behavior change was found to be r = .074. Variables that were found to significantly moderate the effect included (a) type of comparison condition, (b) health behavior, (c) type of participant population (both type of recruitment and country of sample), (d) type of print material, (e) number of intervention contacts, (f) length of follow-up, (g) number and type of theoretical concepts tailored on, and (h) whether demographics and/or behavior were tailored on. Implications of these results are discussed and future directions for research on tailored health messages and interventions are offered.

/pdf/does-tailoring-matter-meta-analytic-review-of-tailored-print-xsem787pqh.pdf

Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions.

With the recent emergence of the Healthy People 2030 goals there is a need to understand the role of SDOH on health inequalities from an upstream perspective. This review summarizes the recent body of evidence on the impact of SDOH across adolescence and youth health outcomes by race/ethnicity using the Health People 2030 Framework.A systematic, reproducible search was performed using PubMed, Academic Search Premier, PsychInfo, and ERIC. A total of 2078 articles were screened for inclusion. A total of 263 articles met inclusion criteria, resulting in 29 articles included for final synthesis.Across the 29 articles, 11 were cross-sectional, 16 were cohort, and 2 were experimental. Across SDOH categories (economic stability, education access and quality, health care access and quality, neighborhood and built environment, and social and community context), 1 study examined self-efficacy, 6 educational attainment, 10 behavior, 5 smoking, 11 alcohol use, 10 substance use, and 1 quality of life. The majority of outcomes represented in this search included health behaviors such as health risk behavior, smoking, alcohol use, and substance use. Across the 29 articles identified, significant differences existed across outcomes by race/ethnicity across SDOH factors, however magnitude of differences varied by SDOH category.SDOH differentially affect adolescents and youth across race/ethnicity. The lived adverse experiences, along with structural racism, increase the likelihood of adolescents and youth engaging in risky health behaviors and negatively influencing health outcomes during adolescence and youth. Research, public health initiatives, and policies integrating SDOH into interventions at early stage of life are needed to effectively reduce social and health inequalities at a population level. 

/pdf/racial-ethnic-differences-in-social-determinants-of-health-2vy9355y.pdf

Melissa Sue Harris

Papers

Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions.

Racial/ethnic differences in social determinants of health and health outcomes among adolescents and youth ages 10–24 years old: a scoping review