Self-Efficacy in Habit Building: How General and Habit-Specific Self-Efficacy Influence Behavioral Automatization and Motivational Interference

Abstract

In this article, we investigate the role of self-efficacy (SE) in intentional habit building. We analyzed event sampling data from a habit building app we created that helps define and track habit data. We used hierarchical growth curve modeling and multilevel mediation to test our hypotheses. In a first study, N = 91 university students built new study habits over a period of 6 weeks in a controlled study. We found that the trait-like (Level 2) general self-efficacy predicted automaticity (i.e., habit strength) but not the experience of motivational interference (MI). In a second study with real user data, N = 265 idiographic habits have been analyzed. The specific SE associated with these habits – habit-specific self-efficacy (Level 1, HSE) – was measured during habit formation. We found that lagged HSE predicted automaticity and that lagged automaticity predicted HSE, indicating a positive feedback mechanism in habit building. Furthermore, we found that lagged HSE predicted less MI during habit performance. A multilevel mediation analysis showed significant effects of lagged HSE (Level 1) and aggregated HSE (Level 2) on MI, which were both partially mediated by automaticity. These results show the importance of defining the specificity of SE beliefs and how they interact with automaticity in the habit building process.

Context Stability in Habit Building Increases Automaticity and Goal Attainment

“…So, it would be fair to assume that context stability should support behavioral automatization. Furthermore, we already have evidence that more automaticity leads to less motivational interference during habit performance (Stojanovic et al, 2020(Stojanovic et al, , 2021. This leads us to assume that context stability increases the degree to which the habit-repetition-specific goal is attained.…”

“…When investigating habit formation, automaticity is typically the dependent variable, which grows over time by habit repetition (Lally et al, 2010;Stojanovic et al, 2020Stojanovic et al, , 2021. A very automized habit would be considered a strong habit.…”

“…Empiric support for the popular notion of "the most important thing is to start" is provided by Gardner et al (2016) who found that habitual instigation automaticity is more predictive for behavioral frequency than habit execution automaticity. Non-specific automaticity on the other hand reduces motivational interference (i.e., bad mood, distractibility, thoughts about alternatives, task switching and low persistence) during habit performance (Stojanovic et al, 2020(Stojanovic et al, , 2021.…”

“…The second dataset (Study 2) contains real user data from a habit building app (Stojanovic, 2019). Other variables of the second dataset have already been analyzed in another paper (Stojanovic et al, 2021), while the first dataset (Study 1) is analyzed for the first time in this paper. In both datasets, context stability, automaticity, and HRGA were measured as Level-1-variables after each habit repetition.…”

“…Longitudinal studies, in which the intentional acquisition of habits is tracked within-person after each habit repetition, are scarce. We identified only five relevant published papers to date (Lally et al, 2010;Fournier et al, 2017;Stojanovic et al, 2020Stojanovic et al, , 2021Van der Weiden et al, 2020) and in none of them context stability has been tested for a possible influence on the habit building process. To fill this gap and add to the scarce longitudinal habit research, we measure perceived context stability in two longitudinal studies (including a context stability manipulation in Study 1), and test the effects of context stability during habit acquisition on automaticity and goal attainment, which are both variables tied to the quality of habit execution.…”