What Is Slowing Us Down? Six Challenges to Accelerating Advances in Health Behavior Change

Behaviour support in dentistry: A Delphi study to agree terminology in behaviour management

OBJECTIVES

Dental behaviour support (DBS) describes all specific techniques practiced to support patients in their experience of professional oral healthcare. DBS is roughly synonymous with behaviour management, which is an outdated concept. There is no agreed terminology to specify the techniques used to support patients who receive dental care. This lack of specificity may lead to imprecision in describing, understanding, teaching, evaluating and implementing behaviour support techniques in dentistry. Therefore, this e-Delphi study aimed to develop a list of agreed labels and descriptions of DBS techniques used in dentistry and sort them according to underlying principles of behaviour.

METHODS

Following a registered protocol, a modified e-Delphi study was applied over two rounds with a final consensus meeting. The threshold of consensus was set a priori at 75%. Agreed techniques were then categorized by four coders, according to behavioural learning theory, to sort techniques according to their mechanism of action.

RESULTS

The panel (n = 35) agreed on 42 DBS techniques from a total of 63 candidate labels and descriptions. Complete agreement was achieved regarding all labels and descriptions, while agreement was not achieved regarding distinctiveness for 17 techniques. In exploring underlying principles of learning, it became clear that multiple and differing principles may apply depending on the specific context and procedure in which the technique may be applied.

DISCUSSION

Experts agreed on what each DBS technique is, what label to use, and their description, but were less likely to agree on what distinguishes one technique from another. All techniques were describable but not comprehensively categorizable according to principles of learning. While objective consistency was not attained, greater clarity and consistency now exists. The resulting list of agreed terminology marks a significant foundation for future efforts towards understanding DBS techniques in research, education and clinical care.

Furthering Scientific Inquiry for Weight Loss Maintenance: Assessing the Psychological Processes Impacted by a Low intensity Technology-Assisted Intervention (NULevel Trial)

BACKGROUND

NULevel was a randomized control trial to evaluate a technology-assisted weight loss maintenance (WLM) program in the UK. The program included: (a) a face-to-face goal-setting session; (b) an internet platform, a pedometer, and wirelessly connected scales to monitor and report diet, physical activity, and weight, and; (c) regular automated feedback delivered by mobile phone, tailored to participants' progress. Components were designed to target psychological processes linked to weight-related behavior. Though intervention participants showed increased physical activity, there was no difference in WLM between the intervention and control groups after 12 months (Sniehotta FF, Evans EH, Sainsbury K, et al. Behavioural intervention for weight loss maintenance versus standard weight advice in adults with obesity: A randomized controlled trial in the UK (NULevel Trial). PLoS Med. 2019; 16(5):e1002793. doi:10.1371/journal.pmed.1002793). It is unclear whether the program failed to alter targeted psychological processes, or whether changes in these processes failed to influence WLM.

PURPOSE

We evaluate whether the program influenced 16 prespecified psychological processes (e.g., self-efficacy and automaticity toward diet and physical activity), and whether these processes (at 6 months) were associated with successful WLM (at 12 months).

METHODS

288 adults who had previously lost weight were randomized to the intervention or control groups. The control group received wireless scales and standard advice via newsletters. Assessments occurred in person at 0, 6, and 12 months.

RESULTS

The intervention significantly altered 10 of the 16 psychological processes, compared with the control group. However, few processes were associated with WLM, leading to no significant indirect effects of the intervention via the processes on WLM.

CONCLUSIONS

Changes in targeted processes were insufficient to support WLM. Future efforts may more closely examine the sequence of effects between processes, behavior, and WLM.

Effect of Intrapersonal and Interpersonal Behavior Change Strategies on Physical Activity Among Older Adults: A Randomized Clinical Trial

Importance

Despite guidelines that recommend physical activity (PA), little is known about which types of behavior change strategies (BCSs) effectively promote sustained increases in PA in older adults who are insufficiently active.

Objective

To determine whether intrapersonal BCSs (eg, goal setting) or interpersonal BCSs (eg, peer-to-peer sharing or learning) combined with the Otago Exercise Program (17 strength and balance exercises and a walking program that are learned and individually tailored, with instruction to perform 3 times per week at home or location of choice) and a wearable PA monitor help older adults sustain increases in their PA.

Design, Setting, and Participants

This 2 × 2 factorial randomized clinical trial (Community-Based Intervention Effects on Older Adults' Physical Activity) of community-dwelling older adults 70 years or older with PA levels below minimum national PA guidelines was conducted in urban community centers. Dates of enrollment were from November 17, 2017, to June 15, 2021, with final follow-up assessments completed on September 2, 2022.

Interventions

Participants were randomized to intrapersonal (eg, goal setting) BCSs, interpersonal (eg, problem-solving with peer-to-peer sharing and learning) BCSs, intrapersonal and interpersonal BCSs, or an attention control group. All interventions included a PA monitor and 8 weekly small-group meetings with discussion, practice, and instructions to implement the exercise program and relevant BCSs independently between meetings and after the intervention.

Main Outcomes and Measures

The primary outcome was daily minutes of objectively measured total PA (light, moderate, or vigorous intensities) averaged over 7 to 10 days, measured at baseline and after the intervention at 1 week, 6 months, and 12 months.

Results

Among 309 participants (mean [SD] age, 77.4 [5.0] years; 240 women [77.7%]), 305 (98.7%) completed the intervention, and 302 (97.7%) had complete data. Participants receiving PA interventions with interpersonal BCS components exhibited greater increases in total PA than did those who did not at 1 week (204 vs 177 PA minutes per day; adjusted difference, 27.1 [95% CI, 17.2-37.0]; P < .001), 6 months (195 vs 175 PA minutes per day; adjusted difference, 20.8 [95% CI, 10.0-31.6]; P < .001), and 12 months (195 vs 168 PA minutes per day; adjusted difference, 27.5 [95% CI, 16.2-38.8]; P < .001) after the intervention. Compared with participants who did not receive interventions with intrapersonal BCS components, participants who received intrapersonal BCSs exhibited no significant changes in total PA at 1 week (192 vs 190 PA minutes per day; adjusted difference, 1.8 [95% CI, -8.6 to 12.2]; P = .73), 6 months (183 vs 187 PA minutes per day; adjusted difference, -3.9 [95% CI, -15.0 to 7.1]; P = .49), or 12 months (177 vs 186 PA minutes per day; adjusted difference, -8.8 [95% CI, -20.5 to 2.9]; P = .14) after the intervention. Interactions between intrapersonal and interpersonal BCSs were not significant.

Conclusions and Relevance

In this randomized clinical trial, older adults with low levels of PA who received interpersonal BCSs, the exercise program, and a PA monitor exhibited significant increases in their PA for up to 12 months after the intervention. Intrapersonal BCSs elicited no significant PA changes and did not interact with interpersonal BCSs. Our findings suggest that because effects of a PA intervention on sustained increases in older adults' PA were augmented with interpersonal but not intrapersonal BCSs, approaches to disseminating and implementing the intervention should be considered.

Trial Registration

ClinicalTrials.gov Identifier: NCT03326141.

Potential Mediators of a School-Based Digital Intervention Targeting Six Lifestyle Risk Behaviours in a Cluster Randomised Controlled Trial of Australian Adolescents

Lifestyle risk behaviours-physical inactivity, poor diet, poor sleep, recreational screen time, and alcohol and tobacco use-collectively known as the "Big 6" emerge during adolescence and significantly contribute to chronic disease development into adulthood. To address this issue, the Health4Life program targeted the Big 6 risk behaviours simultaneously via a co-designed eHealth school-based multiple health behaviour change (MHBC) intervention. This study used multiple causal mediation analysis to investigate some potential mediators of Health4Life's effects on the Big 6 primary outcomes from a cluster randomised controlled trial of Health4Life among Australian school children. Mediators of knowledge, behavioural intentions, self-efficacy, and self-control were assessed. The results revealed a complex pattern of mediation effects across different outcomes. Whilst there was a direct effect of the intervention on reducing moderate-to-vigorous physical activity risk, the impact on sleep duration appeared to occur indirectly through the hypothesised mediators. Conversely, for alcohol and tobacco use, both direct and indirect effects were observed in opposite directions cancelling out the total effect (competitive partial mediation). The intervention's effects on alcohol and tobacco use highlighted complexities, suggesting the involvement of additional undetected mediators. However, little evidence supported mediation for screen time and sugar-sweetened beverage intake risk. These findings emphasise the need for tailored approaches when addressing different risk behaviours and designing effective interventions to target multiple health risk behaviours. The trial was pre-registered with the Australian and New Zealand Clinical Trials Registry: ACTRN12619000431123.

Labels and descriptions of dental behaviour support techniques: A scoping review of clinical practice guidelines

INTRODUCTION

There is no agreed taxonomy of the techniques used to support patients to receive professional oral healthcare. This lack of specification leads to imprecision in describing, understanding, teaching and implementing behaviour support techniques in dentistry (DBS).

METHODS

This review aims to identify the labels and associated descriptors used by practitioners to describe DBS techniques, as a first step in developing a shared terminology for DBS techniques. Following registration of a protocol, a scoping review limited to Clinical Practice Guidelines only was undertaken to identify the labels and descriptors used to refer to DBS techniques.

RESULTS

From 5317 screened records, 30 were included, generating a list of 51 distinct DBS techniques. General anaesthesia was the most commonly reported DBS (n = 21). This review also explores what term is given to DBS techniques as a group (Behaviour management was most commonly used (n = 8)) and how these techniques were categorized (mainly distinguishing between pharmacological and non-pharmacological).

CONCLUSIONS

This is the first attempt to generate a list of techniques that can be selected for patients and marks an initial step in future efforts at agreeing and categorizing these techniques into an accepted taxonomy, with all the benefits this brings to research, education, practice and patients.

On the importance of identifying mechanisms and active ingredients of psychological treatments

This commentary addresses the thought-provoking article by Lorenzo-Luaces (in press). We review areas of both agreement and disagreement with the author's points, noting that readers should not infer that research into active ingredients and mechanisms is pointless. We conclude with a call for more research into the mechanisms of therapeutic change and the active ingredients of therapeutic interventions, with the aim of disseminating treatments that are both effective and efficient.

Longitudinal comparisons of self-affirmation approaches for sun protection

OBJECTIVES

Self-affirmation approaches for health behaviour demonstrate consistent small to medium effects on message acceptance, health intentions and behaviour change. There are several forms of self-affirmation (e.g., values affirmations, implementation intentions), but few empirical comparisons to guide selection in empirical work. Further, there has been little emphasis on the putative mechanisms of self-affirmation driving behaviour change. The current investigation compared a control and four self-affirmation approaches: values, social, implementation intention, and perspective taking.

METHODS

Participants were recruited through CloudResearch (N = 666) and reported baseline sun exposure and protection behaviour at Time 1. One week later (Time 2), returning participants (N = 535) were randomly assigned to condition, viewed a message conveying risks of sun exposure, and reported sun exposure and protection intentions for the next week. Follow-up one week later (Time 3; N = 449) assessed past week sun exposure (i.e., number of days spent outside during peak hours), sun protection behaviour (e.g., sunscreen use), future sun exposure and protection intentions and engagement with resources conveying further health information (i.e., viewing infographics, following links to websites with more information). The association of putative mechanisms with self-affirmation conditions and health outcomes was also examined.

RESULTS

Unexpectedly, there were few differences between self-affirmation conditions and the control on intentions, information seeking, or behaviour at follow-up. At follow-up, perspective circle participants reported fewer days spent outside, spent longer viewing infographics, and, along with social values participants, followed more weblinks seeking information than control participants. The putative mechanisms were unrelated to health outcomes.

CONCLUSIONS

The current investigation was a first step in comparing novel online self-affirmation approaches and had largely null findings. Results suggest that the perspective circle performed best at promoting information seeking and, to some extent, behaviour change. Suggestions for future directions are discussed.

An Experimental Therapeutics Focus on Novel Mechanistic Targets in Cognitive Behavioral Treatments: Introduction to the Special Section

This article introduces the special section, "An Experimental Therapeutics Focus on Novel Mechanistic Targets in Cognitive Behavioral Treatments." The purpose of this special section is to highlight research that follows the recommended Science of Behavior Change (SOBC) developmental progression for an experimental medicine approach to identifying and testing mechanisms of behavior change. Emphasis was placed on the earlier stage "pipeline" of investigations of novel mechanisms for behavior change: mechanisms that are undergoing the initial stages of validation. In this series, seven empirical articles are presented and are followed by an article detailing a checklist for reporting mechanistic research studies in order to improve communication of findings in the field. The final article in this series discusses the history, current status, and future directions for the SOBC approach to mechanistic science as viewed by National Institute of Health program officials.

The NIH Science of Behavior Change Program: Looking Toward the Future

The National Institutes of Health established the Science of Behavior Change (SOBC) program to promote basic research on the initiation, personalization, and maintenance of health behavior change. The SOBC Resource and Coordinating Center now leads and supports activities to maximize the creativity, productivity, scientific rigor, and dissemination of the experimental medicine approach and experimental design resources. Here, we highlight those resources, including the Checklist for Investigating Mechanisms in Behavior-change Research (CLIMBR) guidelines introduced in this special section. We describe the ways in which SOBC can be applied across a range of domains and contexts, and end by considering ways to extend SOBC's perspective and reach, so as to best promote behavior change linked with health, quality of life, and well-being.

Rethinking how and when to report descriptions of behavior change content within interventions: a case study of an ongoing physical activity trial (ready steady 3.0)

Specifications of what and how much health behavior change (BC) content within research interventions are needed to advance BC science, its implementation, and dissemination. We analyzed the types and dosages of the smallest potentially active BC ingredients and associated behavioral prescriptions intended to be delivered in an ongoing physical activity optimization trial for older adults (Ready Steady 3.0 [RS3]). We defined BC types as behavior change techniques (BCT) and behavioral prescriptions. Our protocol integrated the BCT Taxonomy coding procedures with BCT roles (primary or secondary) and, when relevant, linkages to behavioral prescriptions. Primary BCTs targeted theoretical mechanisms of action, whereas secondary BCTs supported primary BCT delivery. Behavioral prescriptions represented what participants were encouraged to do with each primary BCT in RS3 (ascertain, practice, implement). We assessed dosage parameters of duration, frequency, and amount in each BCT and prescription. Results provided a catalog of in-depth, multidimensional content specifications with 12 primary BCTs, each supported by 2-7 secondary BCTs, with dosages ranging from 2 to 8 weeks, 1 to 8 contacts, and 5 to 451 minutes. Minutes spent on behavioral prescriptions varied: ascertain (1 to 41), practice (5 to 315), and implement (0 to 38). Results can be organized and summarized in varied ways (e.g., by content component) to strengthen future assessments of RS3 fidelity and intervention refinement. Results highlight potential benefits of this early, integrated approach to analyzing BC content and frames questions about how such information might be incorporated and disseminated with reporting research outcomes.

Development and Validation of a Two-component Perceived Control Measure

BACKGROUND

Research indicates that perceived behavioral control (PBC) is an important determinant of behavior and that it is composed of perceived capability and opportunity. However, typical measurement of these constructs may be confounded with motivation and outcome expectations. Vignettes presented before questionnaire items may clarify construct meaning leading to precise measurement.

PURPOSE

The purpose of this study was to develop and validate measures of perceived capability and opportunity that parse these constructs from the influence of motivation and outcome expectations using vignettes.

METHODS

Study 1 collected feedback from experts (N = 9) about the initial measure. Study 2a explored internal consistency reliability and construct and discriminant validity of the revised measure using two independent samples (N = 683 and N = 727). Finally, using a prospective design, Study 2b (N = 1,410) investigated test-retest reliability, construct and discriminant validity at Time 2, and nomological validity.

RESULTS

After Study 1, the revised measure was tested in Studies 2a and 2b. Overall, the evidence suggests that the measure is optimal with four items for perceived capability and three for the perceived opportunity. The measure demonstrated strong internal consistency ( > 0.90) and test-retest reliability (intraclass correlation coefficients [ICCs] > .78). The measure also showed construct and discriminant validity by differentiating itself from behavioral intentions (i.e., motivation) and affective attitude (based on expected outcomes) (SRMR = 0.03; RMSEA = 0.06). It also demonstrated evidence of nomological validity as behavior 2 weeks later was predicted.

CONCLUSIONS

We recommend researchers use this tool in future correlational and intervention studies to parse motivation and outcome expectations from perceived capability and opportunity measurement.

The utility of the integrated behavior change model as an extension of the theory of planned behavior

Introduction

There are several widely used theories of health behavior change, which mostly utilize the social cognitive approach. These theories tend to posit that intention is a direct predictor of behavior, do not include automatic influences on behavior, and propose a one-size-fits-all theory for both initiators and maintainers. However, the intention-behavior gap is a well-observed phenomenon, researchers have highlighted that both automatic and reflective factors promote behavioral engagement, and predictors of behavior have been shown to differ between initiators and maintainers—three issues that necessitate theory advancement. To that end, the present research compares the utility of the Integrated Behavior Change Model (IBCM) – a social cognitive model that includes automatic factors involved in behavioral engagement and a moderator of the intention-behavior gap – to its theoretical predecessor, the Theory of Planned Behavior (TPB). Further, the relevance of the IBCM factors for predicting exercise behavior is compared in initiators versus maintainers.

Method

Participants were 494 US undergraduates. Participants reported on variables from the IBCM (and TPB) at baseline and reported on their exercise behavior in two surveys at seven- and 14-days post-baseline.

Results

Findings supported the first hypothesis that the IBCM would be more relevant for initiators in comparison with maintainers, using structural equation modeling. Specifically, only the paths between intrinsic motivation and affective attitude, affective attitude and intention, and intention and behavior were reliably found for maintainers. For initiators, the aforementioned paths were also reliably supported and the additional following paths were also supported: intrinsic motivation and perceived behavioral control, perceived behavioral control and intention, and intention and action planning. However, results did not support the second hypothesis that the IBCM would predict significantly more variance in behavior than its theoretical predecessor, the TPB. Specifically, the addition of action planning, implicit attitude, implicit motivation, and the interaction between intention and action planning only predicted an additional 0.3% (p < 0:05) of the variance in exercise behavior above and beyond intention.

Conclusion

Results highlight the continued need for theoretical refinement in terms of delineating mechanisms of initiation and maintenance and the need for further development in terms of improving upon current predictions of behavior engagement and change.

Implementation intentions to express gratitude increase daily time co-present with an intimate partner, and moderate effects of variation in CD38

Close social connections drive mental and physical health and promote longevity. Positive, other-focused behavior like expressing gratitude may be a key mechanism for increasing close bonds. Existing evidence consistent with this claim is predominantly correlational, likely driven by challenges in causally influencing and sustaining behavior change in the context of ongoing relationships. This 5-week field experiment with daily data from couples provides the first evidence for a brief, low-cost behavioral technique to increase everyday expressed gratitude to a romantic partner. Random assignment to the gratitude expression treatment (GET) increased the amount of time couples spent co-present in everyday life, from the weeks before GET to the weeks after, relative to the control condition. This effect was mediated by the change in expressed gratitude. Voluntary co-presence is an important behavioral indicator of close bonds in non-human animals. Further analyses with a functional genotype related to the oxytocin system (rs6449182) suggest a neurochemical pathway involved in the effects of expressing gratitude. Together, this evidence bridges animal and human research on bonding behavior and sets up future experiments on biopsychosocial mechanisms linking close bonds to health.

Explanations for the Cloudy Evidence That Theory Benefits Health Promotion

Persuasive arguments for using theory have been influential in health behavior and health promotion research. The use of theory is expected to improve intervention outcomes and facilitate scientific advancement. However, current empirical evaluations of the benefits of theory have not consistently demonstrated strong effects. A lack of resolution on this matter can be attributed to several features of the current body of evidence. First, the use of theory may be confounded with other features that impact health-related outcomes. Second, measurement of theory use has not been reliable. Third, the field conflates models and theories. Lastly, the evidentiary status and applicability of theories are not considered. Addressing these challenges during the execution of meta-analyses and designing original research specifically to estimate the benefits of theory could improve research and practice.

Psychosocial-Behavioral Phenotyping: A Novel Precision Health Approach to Modeling Behavioral, Psychological, and Social Determinants of Health Using Machine Learning

BACKGROUND

The context in which a behavioral intervention is delivered is an important source of variability and systematic approaches are needed to identify and quantify contextual factors that may influence intervention efficacy. Machine learning-based phenotyping methods can contribute to a new precision health paradigm by informing personalized behavior interventions. Two primary goals of precision health, identifying population subgroups and highlighting behavioral intervention targets, can be addressed with psychosocial-behavioral phenotypes. We propose a method for psychosocial-behavioral phenotyping that models social determinants of health in addition to individual-level psychological and behavioral factors.

PURPOSE

To demonstrate a novel application of machine learning for psychosocial-behavioral phenotyping, the identification of subgroups with similar combinations of psychosocial characteristics.

METHODS

In this secondary analysis of psychosocial and behavioral data from a community cohort (n = 5,883), we optimized a multichannel mixed membership model (MC3M) using Bayesian inference to identify psychosocial-behavioral phenotypes and used logistic regression to determine which phenotypes were associated with elevated weight status (BMI ≥ 25kg/m2).

RESULTS

We identified 20 psychosocial-behavioral phenotypes. Phenotypes were conceptually consistent as well as discriminative; most participants had only one active phenotype. Two phenotypes were significantly positively associated with elevated weight status; four phenotypes were significantly negatively associated. Each phenotype suggested different contextual considerations for intervention design.

CONCLUSIONS

By depicting the complexity of psychological and social determinants of health while also providing actionable insight about similarities and differences among members of the same community, psychosocial-behavioral phenotypes can identify potential intervention targets in context.