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Background and Purpose Interventions are effective in promoting health behavior change to the extent that (a) intervention strategies modify targets (i.e., mechanisms of action), and (b) modifying targets leads to changes in behavior. To complement taxonomies that characterize the variety of strategies used in behavioral interventions, we outline a new principle that specifies how strategies modify targets and thereby promote behavior change. We distinguish two dimensions of targets—value (positive vs. negative) and accessibility (activation level)—and show that intervention strategies operate either by altering the value of what people think, feel, or want (target change) or by heightening the accessibility of behavior-related thoughts, feelings, and goals (target activation). Methods and Results We review strategies designed to promote target activation and find that nudges, cue-reminders, goal priming, the question-behavior effect, and if-then planning are each effective in generating health behavior change, and that their effectiveness accrues from heightened accessibility of relevant targets. We also identify several other strategies that may operate, at least in part, via target activation (e.g., self-monitoring, message framing, anticipated regret inductions, and habits). Conclusions The Activation Vs. Change Principle (AVCP) offers a theoretically grounded and parsimonious means of distinguishing among intervention strategies. By focusing on how strategies modify targets, the AVCP can aid interventionists in deciding which intervention strategies to deploy and how to combine different strategies in behavioral trials. We outline a research agenda that could serve to further enhance the design and delivery of interventions to promote target activation.

Background/Purpose We address four questions about interventions to promote physical activity in cancer survivors: (a) How often is both the adoption and maintenance of behavior change tested in trials? (b) How often do interventions generate adoption-plus-maintenance of behavior change? (c) Are intervention strategies specifically geared at promoting maintenance of behavior change deployed in trials? and (d) Which intervention strategies distinguish trials that promote both the adoption and maintenance of physical activity from trials that promote adoption-only or generate no behavioral changes? Methods Computerized literature searches identified 206 reports of randomized trials that measured physical activity in the wake of the intervention. Results Only 51 reports (24%) measured both behavioral adoption (postintervention) and behavioral maintenance (≥3 months follow-up). The 51 reports included 58 tests of interventions; 22% of tests observed both adoption and maintenance of physical activity, 26% reported adoption-only, and 52% found no change in behavior. Change techniques designed to promote behavioral maintenance were used much less frequently than adoption techniques or adoption and maintenance techniques. Interventions that aimed to improve quality of life, used supervised exercise sessions, were undertaken in community centers, and deployed fewer behavior change techniques were associated with adoption-plus-maintenance of physical activity in cancer survivors. Conclusions The present findings offer new insights into the adoption and maintenance of physical activity and highlight the need to routinely assess these forms of behavior change in future trials. More extensive testing of intervention strategies specifically geared at maintenance of behavior change is warranted.

BACKGROUND Encouraging older adults to use physical activity monitors can augment efforts to promote increased physical activity. However, little is known about the frequency and type of technical assistance needed during long-term physical activity monitor (PAM) use. OBJECTIVE The objective of this study was to examine PAM-related technical problems reported and assistance received by a sample of older adults in an 18-month community-based, physical activity trial, Ready Steady 3.0 (RS3). METHODS This was an ad-hoc, longitudinal analysis of process variables representing technical problems reported and assistance received by 113 study participants in the 18 months after their orientation to PAMs. Variables included date of contact, problem(s) reported, mode of technical assistance, and equipment replacement. Analysis was descriptive including frequencies and incidence rates of distinct contacts, types of problems, and modes of technical assistance. RESULTS On average, participants were 77 years old (+ 5.2). Most identified as female (77%), reported experience using smart phones (81.4%), and used the PAM between 2 and 18 months. Eighty-two participants (73%) reported 1 to 9 problems with using PAMs, resulting in a total of 150 technical assistance contacts with a mean of 1.3 (SD=1.3). The incidence rate of new, distinct contact for technical assistance was 99, per 100 persons, per year from 2018 to 2021. The most common problems were wearing the PAM (28.7%), reading its display (15.3%), logging into its app (13.3%), charging the PAM (12%), and synchronizing the PAM to the app (10.7%). The modalities of technical assistance were in-person (35%), telephone (34%), email (17%), and U.S. mail (14%). CONCLUSIONS Results provide a detailed description of the types and quantity of technical assistance needs to expect when planning supportive structures to facilitate the long-term use of PAMs among older adults. Health promotion programs and researchers should further examine technical assistance for PAM problems experienced by older adults, such as proactive and responsive support, variations by PAM models, and expanded assistance strategies, such as the use of short graphics interchange formats and video calls. CLINICALTRIAL Clinical Trials.gov NCT03326141

Conflicting recommendations about mammography screening have received ample media coverage, emphasizing scientists' debate over the value of breast cancer screening and differences in professional organizations' guidelines about the appropriate starting age and frequency of routine mammograms. Whereas past research suggests that exposure to such media coverage of conflicting recommendations can have undesirable consequences, both on topic-specific (e.g., ambivalence about mammography) and more general outcomes (e.g., backlash toward cancer prevention recommendations), experimental evidence, especially for effects on more general health cognitions, is limited. Using data from a population-based sample of U.S. women aged 35-55 years (

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.

Relationship partners affect one another’s health outcomes through their health behaviors, yet how this occurs is not well understood. To fill this gap, we present the Dyadic Health Influence Model (DHIM). The DHIM identifies three routes through which a person (the agent) can impact the health beliefs and behavior of their partner (the target). An agent may (a) model health behaviors and shape the shared environment, (b) enact behaviors that promote their relationship, and/or (c) employ strategies to intentionally influence the target’s health behavior. A central premise of the DHIM is that agents act based on their beliefs about their partner’s health and their relationship. In turn, their actions have consequences not only for targets’ health behavior but also for their relationship. We review theoretical and empirical research that provides initial support for the routes and offer testable predictions at the intersection of health behavior change research and relationship science.

Objective This study examines the impact of COVID-19 restrictions on exercise routines and engagement in moderate-vigorous physical activity (MVPA). Design Individuals (N = 397) who reported meeting recommended guidelines for MVPA prior to COVID-19 completed an online questionnaire during the United States' COVID-19 lockdowns in April/May 2020. Main outcome measures Participants reported their MVPA currently and before COVID-19, and answered questions about five contextual cues (e.g. time of day, interaction partners, type of workout, surrounding events, location of exercise) that characterized their exercise routines currently and before COVID-19. Results Contextual cues were perceived as highly disrupted and less consistent during COVID-19 (vs. before) and these changes were associated with greater declines in MVPA. For each cue, distinct effects predicting MVPA declines also emerged for perceived disruption due to COVID-19 restrictions, perceived importance of cue in getting one to exercise, and cue consistency over time. Conclusion Building on prior research, COVID-19 restrictions affected the context in which people exercised, and changes in these contextual cues were related to declines in MVPA. Re-establishing consistency in certain cues (e.g. time of day) after a disruption may help to forestall declines in MVPA compared to others (e.g. type of workout).

The COVID-19 pandemic altered daily life in the United States and disrupted how people engage in routine health behaviors, such as physical activity (PA). This study investigates factors that may have helped people sustain recommended levels of moderate to vigorous PA (MVPA) during this time. Using a cross-sectional design, we recruited from Amazon's Mechanical Turk in April/May 2020 a sample of individuals who reported that they had met recommended PA guidelines (≥ 150 weekly MVPA minutes; N = 397) prior to structural changes brought about by COVID-19. We assessed via self-report whether these individuals were meeting recommended levels of MVPA during the COVID-19 pandemic, their intrinsic motivation and identified regulation for exercise, exercise self-efficacy, perceived disruption to their exercise routine, and access to resources for PA. Higher identified regulation, self-efficacy, access to PA resources, and lower perceived disruption were associated with meeting PA guidelines during COVID-19. These findings provide insight into factors that may be important for continued engagement in MVPA when one experiences major disruptions to their exercise routine.Supplemental data for this article is available online at https://doi.org/10.1080/08964289.2021.1929811 .

Matching the content of persuasive messages to the characteristics (e.g., motives, personality) of people receiving them is a widely used technique to improve persuasion. However, little is known about how to optimize matching beyond simply using the technique. We propose that matching interventions can be strengthened by matching messages to multiple characteristics at a time, and introduce the concept of matching thresholds to improve the way interventionists assign messages. Matching thresholds are defined as the points along characteristics where people change from being most responsive to one message type to another. We provide statistical and methodological tools to estimate matching thresholds, and evaluate these tools in two simulation studies. We then report an online experiment (N=568) where we find an advantage for simultaneously matching messages to two characteristics (promotion focus and interdependent self-construal) and provide estimates of the matching thresholds to guide the assignment of gain/loss frames, and independence/interdependence appeals.

Recent research has examined psychological factors that forestalled declines in physical activity (PA) during the early stages of the COVID-19 pandemic. Surprisingly, there has been limited evidence of an association between intrinsic motivation (IM) and PA. We reasoned that IM may have not predicted PA because COVID-19 restrictions limited opportunities to engage in exercise in ways that produced positive affective experiences (i.e., inherent rewards). Using data from a cross-sectional survey (

Background Exposure to conflicting health information can produce negative affective and cognitive responses, including confusion and backlash, and the effects of this exposure can even “carry over” and reduce people’s receptivity to subsequent messages about health behaviors for which there is scientific consensus. What is not known is whether certain population subgroups are more vulnerable to such carryover effects. Aims This study investigates whether carryover effects of exposure to conflicting information are moderated by two factors, trust in news media and research literacy, testing the hypothesis that lower trust and higher literacy could protect against such effects. Method The analysis draws on data from a longitudinal population-based experiment ( N = 2,716), in which participants were randomly assigned to view health news stories and social media posts that either did or did not feature conflicting information, and subsequently exposed to ads from existing health campaigns about behaviors for which there is scientific consensus. Structural equation modeling was used to test study hypotheses. Results Neither lower trust in news media nor higher research literacy protected against carryover effects, as effects were observed across levels of both trust and literacy. Although level of research literacy did not affect whether carryover effects were observed, it did shape how those effects emerged. Conclusion The public, regardless of their level of trust in news media or research literacy, is vulnerable to the downstream effects of exposure to conflicting health information. Targeted health communication interventions are needed to improve messaging about evolving science and, in turn, increase receptivity to public health recommendations.

Using data from the Family Life, Activity, Sun, Health, and Eating (FLASHE) study, we examined how adolescents’ age as well as parents’ and their adolescent’s gender are associated with the influence strategies parents use to promote healthy behaviors. Parents reported their use of intentional modeling and social control for four health behaviors: fruit and vegetable consumption, junk food consumption, physical activity, and screen time. We found that parents’ reports of both intentional modeling and social control were lower for adolescents who were older. Additionally, parents reported using more intentional modeling with their same-gender children, but more social control with their sons. For certain health behaviors, the gender of parents and adolescents interacted with adolescents’ age to predict the reported use of social control. Overall, this work highlights the importance of delineating both the similarities and differences in how mothers and fathers use influence to shape the health behavior of their adolescents.

Background Many global health challenges may be targeted by changing people’s behaviour. Behaviours including cigarette smoking, physical inactivity and alcohol misuse, as well as certain dietary behaviours, contribute to deaths and disability by increasing the risk of cancers, cardiovascular diseases and diabetes. Interventions have been designed to change these health behaviours with a view to reducing these health risks. However, the effectiveness of these interventions has been quite variable and further information is needed to enhance their success. More information is needed about the specific processes that underlie the effectiveness of intervention strategies. Aim Researchers have developed a taxonomy of 93 behaviour change techniques (i.e. the active components of an intervention that bring about behavioural change), but little is known regarding their potential mechanisms of action (i.e. the processes through which a behaviour change technique affects behaviour). We therefore aimed to examine links between behaviour change techniques and mechanisms of action. Method First, we conducted a literature synthesis study of 277 behaviour change intervention studies, from which we extracted information on links, described by authors, between behaviour change techniques and mechanisms of action, and identified an average of 10 links per intervention report. Second, behaviour change experts (n = 105) were engaged in a three-round consensus study in which they discussed and rated their confidence in the presence/absence of ‘links’ and ‘non-links’ between commonly used behaviour change techniques (n = 61) and a set of mechanisms of action (n = 26). Ninety links and 460 ‘non-links’ reached the pre-set threshold of 80% agreement. To enhance the validity of these results, a third study was conducted that triangulated the findings of the first two studies. Discrepancies and uncertainties between the studies were included in a reconciliation consensus study with a new group of experts (n = 25). The final results identified 92 definite behaviour change technique–mechanism of action links and 465 definite non-links. In a fourth study, we examined whether or not groups of behaviour change techniques used together frequently across interventions revealed shared theoretical underpinnings. We found that experts agreed on the underlying theory for three groups of behaviour change techniques. Results Our results are potentially useful to policy-makers and practitioners in selecting behaviour change techniques to include in behaviour change interventions. However, our data do not demonstrate that the behaviour change techniques are effective in targeting the mechanism of action; rather, the links identified may be the ‘best bets’ for interventions that are effective in changing mechanisms of action, and the non-links are unlikely to be effective. Researchers examining effectiveness of interventions in either primary studies or evidence syntheses may consider these links for further investigation. Conclusion To make our results usable by researchers, practitioners and policy-makers, they are available in an online interactive tool, which enables discussion and collaboration (https://theoryandtechniquetool.humanbehaviourchange.org/); accessed 1 March 2020. This work, building on previous work to develop the behaviour change technique taxonomy, is part of an ongoing programme of work: the Human Behaviour Change Project (www.humanbehaviourchange.org/; accessed 1 March 2020). Funding This project was funded by the Medical Research Council via its Methodology Panel: ‘Developing methodology for designing and evaluating theory-based complex interventions: an ontology for linking behaviour change techniques to theory’ (reference MR/L011115/1).

BackgroundAccelerating advances in health behavior change requires releasing the brake, as well as applying the throttle. This paper discusses six challenges or “brakes” that have slowed progress.Purpose/Methods/ResultsWe engage with six issues that limit investigators’ ability to delineate and test the strategy–target and target–behavior relations that underlie effective interventions according to the experimental medicine approach. We discuss the need for guidance on how to identify the relevant mechanism of action (target) in an intervention and whether a periodic table of health behavior constructs might aid investigators. Experimental and correlational analyses (prospective surveys and behavior change techniques) have been used to test the validity of targets, and we present evidence that there is little agreement among the findings from different research designs. Whereas target engagement is typically analyzed in terms of increasing scores on constructs that impel behavior change, we discuss the role of impeding targets and the benefits of adopting a broader construal of potential targets and approaches to engagement. There is presently a paucity of competitive tests regarding which strategies best engage targets and we discuss empirical criteria and conceptual developments that could enhance the evidence base. Finally, we highlight the need to take “context” or conditional intervention effects more seriously by leveraging the interplay between questions about why interventions work and questions about when and for whom they work.ConclusionCandid appraisal of the challenges facing research on health behavior change can generate new opportunities for theoretical development and offer direction and cumulative impetus for empirical work.

An individualized treatment rule (ITR) formalizes personalized medicine by assigning treatment as a function of patients' clinical information, which contrasts with a static treatment rule that assigns everyone the same treatment. ITR identification has become a common aim in randomized clinical trials but sample size considerations for this aim are lacking. One approach is to select a sample size that will reliably identify an ITR with a performance close to the theoretical optimal rule. However, this approach could still lead to identifying ITRs that perform worse than the optimal static rule, particularly in the absence of substantial effect heterogeneity. This limitation motivates sample size considerations aimed at reliable identification of a beneficial ITR, which outperforms the optimal static rule, and analysis methods that identify the estimated optimal static rule when there is substantial uncertainty about whether an ITR will improve outcomes. To address these limitations, we propose a sample size approach based on the probability of identifying a beneficial ITR and introduce an approach for selecting the LASSO penalty parameter such that in the absence of treatment effect heterogeneity the estimated optimal static rule is identified with high probability. We apply these approaches to the PLUTO trial aimed at developing methods to assist with smoking cessation.

Tools that are directly integrated with the electronic health record (EHR) workflow can reduce the hassle cost of certain guideline-concordant practices, such as querying a prescription drug monitoring program (PDMP) before prescribing opioids.To investigate the effect of integrating access to a PDMP within the EHR on the frequency of program queries by primary care clinicians.The PRINCE (Prescribing Interventions for Chronic Pain Using the Electronic Health Record) randomized trial used a factorial cluster design at the clinic level in 43 primary care clinics in Minnesota. In all, 309 clinicians participated; 161 clinicians were given EHR-integrated access to PDMP at the intervention clinics, and 148 clinicians had the usual access at the control clinics. The intervention went live on August 27, 2020, and data were collected through March 3, 2021.Single sign-on access to the Minnesota PDMP was integrated into the EHR, allowing clinicians to query a patient's controlled substance prescription and dispensing history as recorded in the Minnesota PDMP directly from the patient's EHR record without logging into a separate web portal. Additionally, the integration tool alerted clinicians and reminded them to review the PDMP if a patient had 3 or more opioid prescriptions in the past year and 1 or more in the past 6 months. Clinics in the control group did not receive access to the EHR-integrated PDMP tool; instead, these participants logged into the PDMP web portal separately.Monthly PDMP query counts for primary care clinicians, overall and by modality (EHR-based, web-based, via a clinical delegate), adjusted for clinician characteristics, including type (physician, nurse practitioner, physician assistant), sex, and years in practice. Data were analyzed from August 2021 to May 2022.Of the 43 participating clinics with 309 clinicians, 21 clinics with 161 clinicians (102 [63.4%] women; 114 [70.8%] physicians; tenure, 10.6 [4.4] years) received the PDMP integration intervention. Baseline unadjusted monthly PDMP query rates for the average clinician were 6.6 (95% CI, 4.4-9.9) vs 8.8 (95% CI, 6.0-13.1) queries in the control vs the PDMP integration group, respectively. During the intervention, PDMP query rates for the average clinician were 6.9 (95% CI, 4.7-10.3) vs 14.8 (95% CI, 10.0-22.0) queries among the control vs the PDMP integration group, respectively. Compared with the control group, the EHR-integrated PDMP tool produced a 60% greater increase in the relative change in monthly PDMP queries (95% CI, 51%-70%). An increase in PDMP queries via the EHR-integrated PDMP tool drove this increase, while web-based and delegate queries declined by 39% more among the intervention compared with the control group (95% CI, 34%-43%).This cluster randomized clinical trial found that integrating access to the PDMP in the EHR increased PDMP-querying rates, suggesting that direct access reduced hassle costs and can dramatically improve adherence to guideline-concordant care practices among primary care clinicians.ClinicalTrials.gov Identifier: NCT04601506.

Primary care is a frequent source of pain treatment and opioid prescribing. The objective of the Prescribing Interventions for Chronic Pain using the Electronic health record (PRINCE) study is to assess the effects of two behavioral economics-informed interventions embedded within the electronic health record (EHR) on guideline-concordant pain treatment and opioid prescribing decisions in primary care settings.Setting: The setting for this study is 43 primary care clinics in Minnesota.The PRINCE study uses a cluster-randomized 2 × 2 factorial design to test the effects of two interventions. An adaptive design allows for the possibility of secondary randomization to test if interventions can be titrated while maintaining efficacy.One intervention alters the "choice architecture" within the EHR to nudge clinicians toward non-opioid treatments for opioid-naïve patients and toward tapering for patients currently receiving a "high risk" opioid. The other intervention integrates the prescription drug monitoring program (PDMP) directly within the EHR.The primary outcome for opioid-naïve patients is whether an opioid is prescribed in a primary care visit without a non-opioid alternative pain treatment. The primary outcome for current opioid-using patients is whether opioid prescriptions were tapered with a documented rationale.The PRINCE study will provide real-world evidence on two approaches to improving pain treatment in primary care using the EHR. The adaptive study design strikes a balance between establishing intervention efficacy and testing whether efficacy varies with intervention intensity.

Background Research suggests that focusing on the process of losing weight (i.e. how to eat and exercise) may be more advantageous for sustained engagement with goal pursuit than focusing on weight loss itself. However, gym-based weight loss programs focus almost exclusively on outcomes (e.g. weight, appearance). Using a quasi-experimental design, this study provides a test of subjective and behavioral outcomes of a process- versus an outcome-focused approach integrated into an 8-week workout challenge at four fitness studios. Methods Four hundred and forty-eight individuals who were enrolled in the workout challenge consented to participate in study assessments at the start of the 8-week challenge, the end of the 8-week challenge, and again 8 weeks later. Results The process- and outcome-focused programs produced similar subjective experiences, but the process-focused program was associated with greater workout attendance, more adoption of supplemental weight-loss strategies, and higher completion of the program requirements. Conclusions As compared to traditional outcome-focused approaches, process-focused weight loss programs may elicit behavioral benefits, such as maintaining engagement with the behavioral demands of weight loss.

Objective: To examine whether manipulating the frame used in email subject lines affects open or click-through rate. Participants: Students (N = 38,538) at a Midwestern university received emails f...

Background Parents can influence their children to live healthier lifestyles by modeling healthy behaviors and/or trying to persuade their children to engage in healthier activities. Adolescents and their parents tend to have similar eating and exercise patterns, but less is known about the simultaneous influence of parent’s health behavior and social control on adolescents’ self-efficacy and health behaviors, including whether their effect is moderated by parenting style. Purpose We examine the degree to which parents’ social control and health behaviors are associated with their adolescent’s self-efficacy and health behaviors, including whether parenting styles moderate these associations. Method We analyzed data from the Family Life, Activity, Sun, Health, and Eating project. Results We found that parents’ own health behaviors are positively and strongly associated with their adolescent’s health behaviors across four domains: fruit/vegetable consumption, junk food consumption, physical activity, and nonacademic screen time. We found positive, moderate-to-strong associations between parents’ use of social control and their adolescents’ fruit/vegetable and junk food consumption, small negative associations with screen time, and no associations with physical activity. The effects of social control for junk food consumption and screen time, however, depended on parents’ own behavior in those domains. Parent responsiveness moderated the relation between parents’ social control and their adolescent children’s self-efficacy and health behaviors. Conclusions The health behaviors parents model and their social control efforts are associated with their adolescents’ beliefs and behavior. Efforts to leverage parents as sources of influence must consider the context in which influence is enacted.

COVID-19 has illuminated health inequity in the United States. The burdens of disease are much higher among Black and Indigenous people and other people of color. Disparities by income are also profound, as lower-wage workers were less able to adopt mitigating behaviors compared to higher-income counterparts. These disparities became part of public health discourse in 2020, with commentators frequently highlighting the connection between racism, socioeconomic position, and COVID-19. But what proportion of the public-and among key subgroups-recognized these social group disparities, relative to disparities associated with age and chronic illness, and did public recognition change over the first year of the pandemic? To address these questions, we analyzed data from three nationally-representative cross-sectional public opinion surveys, collected using the NORC AmeriSpeak panel in April 2020 (N = 1007), August 2020 (N = 2716), and April 2021 (N = 1020). The key outcomes were respondents' agreement with statements about disparities in COVID-19 mortality by age, chronic illness, income, and race. We found little change from 2020 to 2021 in Americans' recognition of disparities. At all three time points, most respondents acknowledged age and chronic illness disparities, while no more than half at any time point recognized income- and race-based disparities. Political party affiliation was not statistically associated with agreement with age or illness-related disparities, but was strongly associated with views about income- and race-based disparities. Efforts to promote recognition of racial and socioeconomic health disparities in the United States need to be mindful of the ways in which public understanding of health inequities is linked to partisanship.

Despite abundant observational and experimental tests, it is not yet clear whether enhancing autonomous motivation or perceived competence leads to health behavior change. We identified interventions that aimed to change these constructs and quantified the magnitude of changes in behavior observed when interventions generated increases in autonomous motivation, perceived competence, or both.Computerized searches and additional strategies identified 67 articles that yielded 135 effect sizes relevant to our research questions. Random effects meta-analyses were conducted via STATA.Interventions increased autonomous motivation and perceived competence in 31% and 38% of tests, respectively. Increasing autonomous motivation led to a medium change in health behaviors (d+ = .47, 95% CI [.44, .83]) and increasing perceived competence generated a small-to-medium change (d+ = .34, 95% CI [.22, .47]). Interventions that failed to generate significant improvements in autonomous motivation and perceived competence had much smaller effects on behavior change (d+ = .13 and .10, respectively). There was little evidence of synergistic effects. Changing both autonomous motivation and perceived competence (d+ = .42) did not lead to a larger effect on behavior compared with changing autonomous motivation on its own (d+ = .61), but had a larger effect compared with changing perceived competence on its own (d+ = .21).The present review suggests that autonomous motivation and perceived competence are valid targets for interventions to promote health behavior change but also indicates that research is warranted to ensure that interventions more effectively engage these targets. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Lung cancer screening (LCS) combined with smoking cessation intervention is currently recommended for older individuals with a history of heavy smoking. Tailoring tobacco treatment for this patient population of older, people who smoke (PWS) may improve cessation rates while efficiently using limited smoking cessation resources. Although some older people who smoke will need more intensive treatment to achieve sustained abstinence, others may be successful with less intensive treatment. A framework to identify themBaseline demographic, smoking, and health data are reported from a randomized clinical trial of longitudinal smoking cessation interventions delivered in the setting of LCS. Candidate variables were factor analyzed to identify latent factors, or constructs, to identify subgroups of older participants among the heterogenous population of older people who smoke.We identified three factor-derived constructs: self-reported health status, heaviness of smoking, and nicotine dependence. Nicotine dependence was moderately correlated with both of the other two factors.This factor analysis of baseline participant characteristics identified a set of latent constructs - based on a few practical clinical variables -- that can be used to classify the heterogenous population of older people who smoke to identify. We propose this framework to identify subgroups of people who smoke who might successfully quit with less intense treatment at the time of lung cancer screening.

We issue a call for the design and conduct of experimental trials to test the effects of researchers' adoption of Open Science (OS) research practices. OS emerged to address lapses in the transparency, quality, integrity, and reproducibility of research by proposing that investigators institute practices, such as preregistering study hypotheses, procedures, and statistical analyses, before launching their research. These practices have been greeted with enthusiasm by some parts of the scientific community, but empirical evidence of their effects relies mainly on observational studies; furthermore, questions remain about the time and effort required by these practices and their ultimate benefit to science. To assess the outcomes of OS research practices, we propose they be viewed as behavioral interventions for scientists and tested in randomized controlled trials (RCTs), to identify potential benefits and (unintended) harms. As this is a call to action rather than an action plan per se, we sketch out four potential trial designs to encourage further deliberation and planning. Experimental tests to document the outcomes of OS practices can provide evidence to optimize how scientists, funders, policymakers, and institutions utilize these strategies to advance scientific practice. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Two approaches may shift attention from short-term rewards to longer-term weight-loss goals: focusing on long-term consequences of unhealthy choices (prevention) or benefits of healthy choices (promotion). This randomized controlled trial tested the impact of prevention- versus promotion-focused strategies in an internet-delivered behavioral weight-loss intervention (iBWL).A total of 95 participants with overweight/obesity were randomized to one of three 12-week iBWLs: (1) STANDARD (n = 31), (2) PREVENT (standard iBWL+prevention-focused training; n = 32), or (3) PROMOTE (standard iBWL+promotion-focused training; n = 32). Participants in the two enhanced arms were trained in their assigned strategy, and lessons and weekly feedback featured arm-specific content and reminders.Intent-to-treat analysis revealed significant differences in weight loss and self-control use at 12 weeks (weight loss p = 0.002, self-control p = 0.0006). PREVENT was associated with 6.6% (±4.5%) weight loss and a 20.3% (±26.5%) increase in self-control, STANDARD and PROMOTE were associated with 4.4% (±4.2%) and 3.1% (±3.1%) weight losses, respectively, and neither STANDARD nor PROMOTE participants exhibited significant changes in self-control. Across arms, increased self-control was associated with greater weight loss (p = 0.0005).Cognitive strategies to focus on preventing negative consequences of unhealthy choices led to greater weight loss and self-control compared with both standard iBWL and promotion-focused iBWL. Prevention strategies should be given further attention for overweight/obesity treatment.

Background Accumulating evidence suggests that exposure to conflicting health information can adversely affect public understanding of and trust in health recommendations. What is not known is whether prior exposure to such information renders people less receptive to subsequent unrelated health messages about behaviors for which the evidence is clear and consistent. Purpose This study tests this “carryover” effects hypothesis, positing that prior exposure to conflict will reduce receptivity to subsequent unrelated health messages, and examines potential affective and cognitive pathways through which such effects might occur. Methods A three-wave, online, population-based survey experiment (N = 2,716) assessed whether participants who were randomly assigned to view a series of health news stories and social media posts featuring conflict at Times 1 and 2 were ultimately less receptive at Time 3 to ads from existing health campaigns about behaviors for which there is scientific consensus, compared to those who saw the same series of stories and posts that did not feature conflict. Results Structural equation modeling revealed evidence of carryover effects of exposure to conflict on two dimensions of message receptivity: greater resistance to the unrelated ads and lower perceptions of the health behaviors featured in the ads. Modeling indicated that carryover effects were a function of generalized backlash toward health recommendations and research elicited by prior exposure to conflicting information. Conclusions Findings suggest that the broader public information environment, which is increasingly characterized by messages of conflict and controversy, could undermine the success of large-scale public health messaging strategies.

The purpose of this study was to examine psychosocial constructs targeted as potential mediators in a prior physical activity (PA) intervention study. This secondary analysis used data from 102 older adults randomized to one of four conditions—within a 2 (Interpersonal Strategies: yes, no) x 2 (Intrapersonal Strategies: yes, no) factorial design. We tested intervention effects on social support, self-efficacy, self-regulation, and goal attainment, and whether these constructs mediated intervention effects on PA. Participants who received interventions with interpersonal strategies, compared to those who did not, increased their readiness (post-intervention), the self-regulation subscale of self-assessment, and goal attainment (post-intervention, 6-months). Participants who received interventions with intrapersonal strategies, compared to those who did not, increased their social support from family (post-intervention). There was no statistically significant mediation. To understand mechanisms through which interventions increase older adults’ PA and to improve intervention effectiveness, researchers should continue to examine potential psychosocial mediators. Clinical Trial Registry: NCT02433249.

Adult friendships are important relationships, yet little work has examined the processes through which they end and the antecedents and consequences of endings. Building on work that has highlighted the reasons friendships end (Fehr, 1996), we propose an adult friendship dissolution process model that features how situational, personal, and interpersonal variables may influence whether friendships are ended via active or passive routes. Furthermore, potential intervening variables that could lead to different paths of friendship dissolution, including the emotional toll of experiencing dissolution via one path versus another, are discussed.

The current article describes a position statement and recommendations for actions that need to be taken to develop best practices for promoting scientific integrity through open science in health psychology endorsed at a Synergy Expert Group Meeting. Sixteen Synergy Meeting participants specializing in health, social and behavioural psychology convened to discuss priority issues regarding scientific integrity promotion and open science in health psychology. The group developed a set of recommendations for researchers, gatekeepers, and research end-users. The group process followed a nominal group technique and voting system to elicit and decide on the most relevant and topical issues. Seventeen priority areas were listed and voted on, 15 of them were endorsed by the group (5, 6 and 4 from each area). Each of the issues was considered by the group and formed the basis of this position statement. Specifically, the following priority actions for health psychology were endorsed: (1) for researchers: advancing when and how to make data open and accessible at various research stages and understanding researchers’ beliefs and attitudes regarding open data; (2) for educators: integrating open science in research curricula, e.g., through online open science training modules, promoting preregistration, transparent reporting, open data and applying open science as a learning tool; (3) for journal editors: providing an open science statement, and open data policies, including a minimal requirements submission checklist. Health psychology societies and journal editors should collaborate in order to develop a coordinated plan for research integrity and open science promotion across behavioural disciplines. peerReviewed

Contains fulltext : 243553.pdf (Publisher’s version ) (Open Access) Researchers, practitioners, and policymakers develop interventions to change behavior based on their understanding of how behavior change techniques (BCTs) impact the determinants of behavior. A transparent, systematic, and accessible method of linking BCTs with the processes through which they change behavior (i.e., their mechanisms of action [MoAs]) would advance the understanding of intervention effects and improve theory and intervention development. The purpose of this study is to triangulate evidence for hypothesized BCT-MoA links obtained in two previous studies and present the results in an interactive, online tool. Two previous studies generated evidence on links between 56 BCTs and 26 MoAs based on their frequency in literature synthesis and on expert consensus. Concordance between the findings of the two studies was examined using multilevel modeling. Uncertainties and differences between the two studies were reconciled by 16 behavior change experts using consensus development methods. The resulting evidence was used to generate an online tool. The two studies showed concordance for 25 of the 26 MoAs and agreement for 37 links and for 460 "nonlinks." A further 55 links were resolved by consensus (total of 92 [37 + 55] hypothesized BCT-MoA links). Full data on 1,456 possible links was incorporated into the online interactive Theory and Technique Tool (https://theoryandtechniquetool.humanbehaviourchange.org/). This triangulation of two distinct sources of evidence provides guidance on how BCTs may affect the mechanisms that change behavior and is available as a resource for behavior change intervention designers, researchers and theorists, supporting intervention design, research synthesis, and collaborative research.

Efficacious translational research in health psychology relies on specifying why intervention strategies change health behaviors and when, for what behaviors, and for whom, do these strategies promote change. Whereas interventions' mechanism of action (the why question) has attracted considerable attention, there is a need to conceptualize and integrate factors that moderate intervention effectiveness. Intervention effects on health behaviors are a function of 2 change processes: how effectively interventions change mechanisms of action (target engagement), and how effectively those mechanisms change behavior (target validity). We outline the Operating Conditions Framework (OCF) to articulate theoretical linkages between mechanisms and moderators and begin the process of specifying circumstances that promote target engagement and target validity. A review of 46 meta-analyses of behavioral interventions offers impetus for the OCF by revealing that heterogeneity of effect sizes is frequent, substantial, and largely unexplained in traditional moderator analyses. We present an approach to moderation grounded on the distinction between 2 foci-engagement moderation and validity moderation-and reveal that little is known about variation in how interventions change targets and how changing targets promotes behavior change. The OCF addresses this need by maintaining researchers' focus on mechanisms of behavior change but doing so while embracing the conditional nature of these processes. Because the OCF prioritizes consideration of contextual factors at the outset of a research program, early-phase translational research will be critical in specifying operating conditions and, ultimately, generating guidelines regarding why, when, for whom, and for what behaviors are intervention strategies effective. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

This special issue showcases how investigators working in different areas of health behavior change are utilizing early phase studies to advance intervention development. Through the publication of design or protocol papers for currently funded Science of Behavior Change (SOBC) network projects, the special issue illustrates how investigative teams are implementing the experimental medicine approach to advance our understanding of the mechanisms of action that underlie behavior change interventions and, in turn, develop an evidence base that can inform future intervention design. Given that a goal of the experimental medicine approach is the accumulation of an evidence base regarding the links between intervention strategies and putative mechanisms of action, it is critical that this evidence base is readily accessible to investigators and practitioners. Therefore, each of the included articles describes how it is implementing the open-science approach within its study protocol to ensure rigor and reproducibility. Each article provides information about how to register an early phase experiment before study conduct and how to publicly deposit the data, metadata, and publications. The special issue includes 10 design and protocol articles and 2 commentaries on a diverse array of scientific areas and approaches to test mechanisms of action for health behavior change interventions. By disseminating how the National Institutes of Health SOBC Initiative has supported the conduct of early phase intervention studies implementing the experimental medicine and open science approaches, the special issue provides a substantive roadmap to other scientists for how to adopt these approaches. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Conflicting information surrounding COVID-19 abounds, from disagreement over the effectiveness of face masks in preventing viral transmission to competing claims about the promise of certain treatments. Despite the potential for conflicting information about COVID-19 to produce adverse public health effects, little is known about whether the U.S. public notices this information, and whether certain population subgroups are particularly likely to do so. To address these questions, we fielded a nationally representative survey of U.S. adults in late April 2020 (N = 1,007). Results showed substantial self-reported exposure to conflicting information about COVID-19, with nearly 75% of participants reporting having recently heard such information from health experts, politicians, and/or others. Participants perceived disagreement across a range of COVID-19-related issues, though from politicians more than health experts. Factors including political affiliation, information source use, and personal experience with COVID-19 were associated with perceptions of disagreement. Future research should consider potential cognitive and behavioral consequences of such perceptions.

The Ready Steady 3.0 trial is designed to test the main and interactive effects of two behavior change intervention components, within an 8-week physical activity intervention, on older adults' physical activity (PA). Each component is comprised of behavior change strategies that emphasize two different evidence-based ways to motivate older adults to be active: interpersonal and intrapersonal. 308 adults ≥70 years old will be randomized to 1 of 4 conditions in a 2 × 2 full factorial trial in which the two factors represent the receipt (No, Yes) of interpersonal or intrapersonal behavior change strategies. Participants will also receive two core intervention components: the Otago Exercise Program adapted for small groups and a PA monitor. Interventions across conditions will be delivered during 8 weekly, small group, meetings in community settings. The primary outcome of PA, measured objectively, and secondary outcomes of falls and the quality of life will be assessed at baseline and post-intervention: 1 week, 6 months, and 12 months. Findings will enable the identification of behavior change content that contributes to physical activity outcomes within a physical activity intervention for older adults. This study is one of the first to use the MOST framework to guide the development of a community-based physical activity intervention for older adults to reduce the public health problems of low PA and falls. The results will enable the optimization of behavior change content within a PA intervention for older adults and, in turn, other PA interventions for older adults.

Objective We conducted a meta-analysis of randomized controlled trials (RCTs) to promote health behavior change based on self-determination theory (SDT). The review aimed to (a) quantify the impact of SDT interventions on health behaviors, (b) test mediation by theoretically specified variables (autonomous motivation and perceived competence), and (c) identify moderators of intervention effectiveness. Method Computerized searches and additional strategies identified 56 articles that yielded 65 independent tests of SDT interventions. Random effects meta-analysis and metaregressions were conducted via STATA; meta-analytic structural equation modeling (MASEM) was used to test mediation. Results The sample-weighted average effect size for SDT interventions was d+ = .23, and there were significant effects for physical activity, sedentary behavior, diet, alcohol consumption, and smoking cessation (.16 ≥ d+ ≥ .29). Effect sizes exhibited both publication bias and small sample bias but remained significantly different from zero, albeit of smaller magnitude, after correction for bias (d+ ≥ .15). MASEM indicated that autonomous motivation and perceived competence mediated intervention effects on behavior. Metaregression analyses indicated that features of the sample, intervention, or methodology generally did not moderate effect sizes. Conclusion The present review indicates that SDT interventions have a significant but small effect on health behavior change and suggests several directions for future research. (PsycInfo Database Record (c) 2020 APA, all rights reserved).