Distinguishing initiation from maintenance in the Integrated Behavior Change Model

Most lifestyle interventions fail at instilling behavioral maintenance. This is likely a result of interventions being based on suboptimal theories, the majority of which focus exclusively on determinants of behavioral intentions. These theories and interventions based on them are limited in their ability to explain and promote, respectively, behavioral initiation and maintenance. First, fewer than 50% of people translate their intentions into behavior; second, only mechanisms of initiation are specified while mechanisms of maintenance are neglected. Thus, more basic, theoretical work regarding mechanisms of behavioral initiation (i.e. moderators of the intention-behavior relationship) and maintenance is required to advance health practices. The purpose of the present line of research was to (1) evaluate a contemporary theoretical framework—the Integrated Behavior Change Model (IBCM)—that claims to better account for behavioral initiation, which requires more research evidence; and (2) to propose and test the utility of an extension to the IBCM to more fully account for mechanisms of behavioral maintenance, within the context of exercise. A secondary purpose of the present study was to test whether mechanisms of behavioral engagement vary for people who are just starting to exercise (i.e., initiators) versus those who have been exercising from some time (i.e., maintainers). Results supported hypotheses that the original IBCM would be more relevant for initiators versus maintainers, but counter to hypotheses, the ICBM did not do a better job at predicting behavior than its theoretical predecessor - the Theory of Planned Behavior. Assessment of the extension of the IBCM with maintainers revealed that identity was a stronger predictor of behavior than habit and that identity was particularly important when people’s routines varied from day-to-day, as expected. These results highlight the continued need for theoretical refinement and development in the field of Health Psychology applied to behavior change interventions

Explicit Attitudes Towards Race: The Impact of Active Learning in Teaching Diversity

The majority of colleges and universities in the United States require students to take at least one diversity-related course to graduate. Considering the current political climate, this is a step in the right direction as it should encourage students to be more accepting and help facilitate an inclusive campus environment. However, these courses typically are not tailored towards addressing current diversity issues impacting Americans (e.g., New Zealand Film counts as a cultural diversity credit at Oberlin College in Ohio). In addition, very little empirical research has been conducted looking at the effectiveness of these courses or at which teaching methods are most beneficial for promoting inclusivity and attitude change. Therefore, we conducted an empirical study looking at the benefits of open discussion and active learning for starting the process of attitude change and to promote understanding of diverse groups and cultures. Results revealed that students were slightly more motivated to control their prejudice and that color-blind racial attitudes decreased. Contrary to expectations, results revealed that students were slightly more discriminatory after engaging with the course content

Some habits are more work than others:Deliberate self-regulation strategy use increases with behavioral complexity, even for established habits

Objective: We tested the hypothesis that complex behaviors are commonly supported by self-regulation strategies, even when those behaviors are supported by strong instigation habits. Background: Goal-directed and habit-mediated processes arise from separable systems that have been suggested to seldomly interact. Results: Self-regulation strategy use was lower for habitually instigated simple behaviors compared to nonhabitually instigated simple behaviors. However, participants' use of self-regulation strategies increased with the increasing complexity of behaviors, even when complex behaviors were habitually instigated. The difference in the extent of strategy use between habitually and nonhabitually instigated actions was absent when behavioral complexity was particularly high. Conclusion: These results point to a qualitative distinction—while simple behaviors may progress in a relatively automatic and unthinking manner, complex behaviors receive frequent support from self-regulation strategies, even if they are instigated habitually.</p

Evaluating behavior change factors over time for a simple vs. complex health behavior

BACKGROUND: Researchers are working to identify dynamic factors involved in the shift from behavioral initiation to maintenance—factors which may depend on behavioral complexity. We test hypotheses regarding changes in factors involved in behavioral initiation and maintenance and their relationships to behavioral frequency over time, for a simple (taking a supplement) vs. complex (exercise) behavior. METHODS: Data are secondary analyses from a larger RCT, in which young adult women, new to both behaviors, were randomly assigned to take daily calcium (N = 161) or to go for a daily, brisk walk (N = 171), for 4-weeks. Factors (intentions, self-efficacy, intrinsic motivation, self-identity, habit strength) were measured weekly. Multi-level modeling evaluated their change over time. Bivariate correlations and multiple regression determined the relationships between factors and the subsequent-week behavioral frequency (self-report and objective). FINDING: Results were partly in-line with expectations, in that individuals’ intentions and self-efficacy predicted initial behavioral engagement for both behaviors, and habit strength increased for both behaviors, becoming a significant predictor of behavioral frequency in later weeks of the study in some analyses. However, results depended on whether the outcome was self-reported or objectively measured and whether analyses were bivariate or multivariate (regression). DISCUSSION: The factors theorized to play a role in behavioral maintenance (intrinsic motivation, self-identity, and habit strength) started to develop, but only habit strength predicted behavioral frequency by study-end, for both behaviors. Differences in initiation and maintenance between behaviors of differing complexity may not be as stark as theorized, but longer follow-up times are required to evaluate maintenance factors

Some habits are more work than others:Deliberate self-regulation strategy use increases with behavioral complexity, even for established habits

Objective: We tested the hypothesis that complex behaviors are commonly supported by self-regulation strategies, even when those behaviors are supported by strong instigation habits. Background: Goal-directed and habit-mediated processes arise from separable systems that have been suggested to seldomly interact. Results: Self-regulation strategy use was lower for habitually instigated simple behaviors compared to nonhabitually instigated simple behaviors. However, participants' use of self-regulation strategies increased with the increasing complexity of behaviors, even when complex behaviors were habitually instigated. The difference in the extent of strategy use between habitually and nonhabitually instigated actions was absent when behavioral complexity was particularly high. Conclusion: These results point to a qualitative distinction—while simple behaviors may progress in a relatively automatic and unthinking manner, complex behaviors receive frequent support from self-regulation strategies, even if they are instigated habitually.</p

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

PAYING PARTICIPANTS:THE IMPACT OF COMPENSATION ON DATA QUALITY

Poor-quality data has the potential to increase error variance, reduce statistical power and effect sizes, and produce Type I or Type II errors. Paying participants is one technique researchers may use in an attempt to obtain high-quality data. Accordingly, two secondary datasets were used to examine the relationship between participant payment and data quality. The first dataset revealed that data quality did not differ between paid and unpaid undergraduates. Similarly, the second dataset showed that data quality did not differ between unpaid community participants and MTurkers. A comparison across studies showed that undergraduate students engaged in lower levels of careless responding than the community samples but the unpaid community sample outperformed the MTurk sample and both undergraduate samples. Taken together, the current findings suggest that offering financial incentives to undergraduate or community samples does not improve data quality but may improve data collection rates and increase the diversity of participants.</p