This review builds on self-control theory (Carver & Scheier, 1998) to develop a theoretical framework for investigating associations of implicit theories with self-regulation. This framework conceptualizes self-regulation in terms of three crucial processes: goal setting, goal operating and goal monitoring. In this meta-analysis, we included articles that reported a quantifiable assessment of implicit theories and at least one self-regulatory process or outcome. Using a random effects approach, meta-analytic results (total unique N = 28,217; k = 113) across diverse achievement domains (68% academic) and populations (age range = 5-42; 10 different nationalities; 58% from United States; 44% female) demonstrated that implicit theories predict distinct self-regulatory processes, which, in turn, predict goal achievement. Incremental theories, which, in contrast to entity theories, are characterized by the belief that human attributes are malleable rather than fixed, significantly predicted goal setting (performance goals, r = -.151; learning goals, r = .187), goal operating (helpless-oriented strategies, r = -.238; mastery-oriented strategies, r = .227), and goal monitoring (negative emotions, r = -.233; expectations, r = .157). The effects for goal setting and goal operating were stronger in the presence (vs. absence) of ego threats such as failure feedback. Discussion emphasizes how the present theoretical analysis merges an implicit theory perspective with self-control theory to advance scholarship and unlock major new directions for basic and applied research. Abstract = 221; Overall Word Count = 32,266 KEY WORDS: implicit theories, self-regulation, self-control theory, achievement Implicit Theories and Self-Regulation 2 Mindsets Matter: A Meta-Analytic Review of Implicit Theories and Self-RegulationWhy do some students seek to gain competency, whereas others seek to outperform their peers? Why do some athletes redouble their efforts when facing setbacks, whereas others respond with helplessness? Why do some dieters feel confident in their ability to face challenges to their weight-loss goals, whereas others feel they lack the requisite skills? Research on implicit theories has sought to answer these and similar questions for decades, examining how lay beliefs, namely incremental theories (beliefs that human attributes can be improved or developed) and entity theories (beliefs that human attributes are fixed or invariant), influence self-regulation (Dweck & Leggett, 1988;Molden & Dweck, 2006).Although research on implicit theories originated within an academic context, scholars have extended the theory to additional achievement domains, such as athletics (e.g., Kasimatis, Miller, & Marcussen, 1996;Ommundsen, 2003), weight management (Burnette, 2010), and leadership (Burnette, Pollack, & Hoyt, 2010). Across these contexts, implicit theories have been postulated to be linked to various self-regulatory processes, including goal setting (e.g., Robins & Pals, 2002), social comparison (Nussbaum & Dweck, 2008), ...
The current research extended the implicit theory approach to a weight management context and merged it with value expectancy theory. Three studies investigated the hypothesis that individuals are especially unlikely to self-regulate effectively after dieting setbacks when they believe body weight to be fixed (entity theory) rather than malleable (incremental theory). Study 1 examined avoidant coping after a hypothetical dieting setback. Study 2 examined the implicit theory-avoidant coping relation after naturally occurring challenges to participants' weight-loss goals. Across both studies, entity theorists, relative to incremental theorists, reported more avoidant coping after setbacks. In Study 2, avoidant coping, in turn, predicted difficulty achieving weight-loss success. Study 3 manipulated implicit theories of weight to test the causal effects of implicit theories on effortful regulation. Entity theorists, relative to incremental theorists, reported less persistence following setbacks. Across the three studies, expectations about the potential for future dieting success mediated the link between implicit theory and self-regulation.
As growth mindset interventions increase in scope and popularity, scientists and policymakers are asking: Are these interventions effective? To answer this question properly, the field needs to understand the meaningful heterogeneity in effects. In the present systematic review and meta-analysis, we focused on two key moderators with adequate data to test: Subsamples expected to benefit most and implementation fidelity. We also specified a process model that can be generative for theory. We included articles published between 2002 (first mindset intervention) through the end of 2020 that reported an effect for a growth mindset intervention, used a randomized design, and featured at least one of the qualifying outcomes. Our search yielded 53 independent samples testing distinct interventions. We reported cumulative effect sizes for multiple outcomes (i.e., mindsets, motivation, behavior, end results), with a focus on three primary end results (i.e., improved academic achievement, mental health, or social functioning). Multilevel metaregression analyses with targeted subsamples and high fidelity for academic achievement yielded, d = 0.14, 95% CI [.06, .22]; for mental health, d = 0.32, 95% CI [.10, .54]. Results highlighted the extensive variation in effects to be expected from future interventions. Namely, 95% prediction intervals for focal effects ranged from −0.08 to 0.35 for academic achievement and from 0.07 to 0.57 for mental health. The literature is too nascent for moderators for social functioning, but average effects are d = 0.36, 95% CI [.03, .68], 95% PI [−.50, 1.22]. We conclude with a discussion of heterogeneity and the limitations of meta-analyses.
Exploitation is a fact of life for social organisms, and natural selection gives rise to revenge mechanisms that are designed to deter such exploitations. However, humans may also possess cognitive forgiveness mechanisms designed to promote the restoration of valuable social relationships following exploitation. In the current article, the authors test the hypothesis that decisions about forgiveness result from a computational system that combines information about relationship value and exploitation risk to produce decisions about whom to forgive following interpersonal offenses. The authors examined the independent and interactive effects of relationship value and exploitation risk across two studies. In Study 1, controlling for other constructs related to forgiveness, the authors assessed relationship value and exploitation risk. In Study 2, participants experienced experimental manipulations of relationship value and exploitation risk. Across studies, using hypothetical and actual offenses and varied forgiveness measures, the combination of low exploitation risk and high relationship value predicted the greatest forgiveness.
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