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. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Objective: The clinical literature on ADHD in adults suggests that “overly positive” or optimistic cognitions may contribute to impairment and failure to use self-regulation skills in this population, yet the research literature on this topic is limited. We developed the ADHD Cognitions Scale (ACS), a brief self-report measure of ADHD-related thoughts, and evaluated its psychometric properties. Method: We collected self-report measures, inculding the ACS, from two large community samples (Ns = 262, 304). Results: The measure demonstrated a one-factor solution that replicated in the second sample. Evidence of good internal consistency and also convergent and divergent validity was obtained for both samples. Scores on the ACS correlated with functional impairment, time management problems, and avoidant coping strategies. Conclusion: With additional study, the ACS may be useful to identify and track maladaptive ADHD-related cognitions during cognitive-behavioral treatment, and to further study the role of these thoughts in ADHD-related impairment.

Objective: Cognitive-behavioral therapy (CBT) has growing evidence of efficacy for Attention-Deficit/Hyperactivity Disorder (ADHD) in adults. Mobile health apps are promising tools for delivering scalable CBT. In a 7-week open study of Inflow, a CBT-based mobile app, we assessed usability and feasibility to prepare for a randomized controlled trial (RCT). Method: 240 adults recruited online completed baseline and usability assessments at 2 (n = 114), 4 (n = 97) and after 7 weeks (n = 95) of Inflow use. 93 participants self-reported ADHD symptoms and impairment at baseline and 7 weeks. Results: Participants rated Inflow’s usability favorably, used the app a median of 3.86 times per week, and a majority of those using the app for 7 weeks self-reported decreases in ADHD symptoms and impairment. Conclusion: Inflow demonstrated usability and feasibility among users. An RCT will determine whether Inflow is associated with improvement among more rigorously assessed users and beyond non-specific factors.