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Accumulated findings from studies in which implicit-bias measures correlate with discriminatory judgment and behavior have led many social scientists to conclude that implicit biases play a causal role in racial and other discrimination. In turn, that belief has promoted and sustained two lines of work to develop remedies: (a) individual treatment interventions expected to weaken or eradicate implicit biases and (b) group-administered training programs to overcome biases generally, including implicit biases. Our review of research on these two types of sought remedies finds that they lack established methods that durably diminish implicit biases and have not reproducibly reduced discriminatory consequences of implicit (or other) biases. That disappointing conclusion prompted our turn to strategies based on methods that have been successful in the domain of public health. Preventive measures are designed to disable the path from implicit biases to discriminatory outcomes. Disparity-finding methods aim to discover disparities that sometimes have obvious fixes, or that at least suggest where responsibility should reside for developing a fix. Disparity-finding methods have the advantage of being useful in remediation not only for implicit biases but also systemic biases. For both of these categories of bias, causes of discriminatory outcomes are understood as residing in large part outside the conscious awareness of individual actors. We conclude with recommendations to guide organizations that wish to deal with biases for which they have not yet found solutions.

There has been extensive discussion about gender gaps in representation and career advancement in the sciences. However, psychological science itself has yet to be the focus of discussion or systematic review, despite our field's investment in questions of equity, status, well-being, gender bias, and gender disparities. In the present article, we consider 10 topics relevant for women's career advancement in psychological science. We focus on issues that have been the subject of empirical study, discuss relevant evidence within and outside of psychological science, and draw on established psychological theory and social-science research to begin to chart a path forward. We hope that better understanding of these issues within the field will shed light on areas of existing gender gaps in the discipline and areas where positive change has happened, and spark conversation within our field about how to create lasting change to mitigate remaining gender differences in psychological science.

COVID-19 presents significant social, economic, and medical challenges. Because COVID-19 has already begun to precipitate huge increases in mental health problems, clinical psychological science must assert a leadership role in guiding a national response to this secondary crisis. In this article, COVID-19 is conceptualized as a unique, compounding, multidimensional stressor that will create a vast need for intervention and necessitate new paradigms for mental health service delivery and training. Urgent challenge areas across developmental periods are discussed, followed by a review of psychological symptoms that likely will increase in prevalence and require innovative solutions in both science and practice. Implications for new research directions, clinical approaches, and policy issues are discussed to highlight the opportunities for clinical psychological science to emerge as an updated, contemporary field capable of addressing the burden of mental illness and distress in the wake of COVID-19 and beyond. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The public health impact of psychological science is maximized when it is disseminated clearly and compellingly to audiences who can act on it. Dissemination research can generate knowledge to help achieve this, but dissemination is understudied in the field of implementation science. As a consequence, the designs of dissemination strategies are typically driven by anecdote, not evidence, and are often ineffective. We address this issue by synthesizing key theory and findings from consumer psychology and detailing a novel research approach for "data-driven dissemination." The approach has 3 parts: (a) formative audience research, which characterizes an audience's awareness about, adoption of, and attitudes toward an intervention, as well as preferences for receiving information about it; (b) audience segmentation research, which identifies meaningful subgroups within an audience to inform the tailoring of dissemination strategies; and (c) dissemination effectiveness research, which determines the strategies that are most effective. This approach is then illustrated using the dissemination of the American Psychological Association's (APA, 2017) Clinical Practice Guideline for the Treatment of Posttraumatic Stress Disorder (PTSD) in Adults as a case study. Data are presented from a 2018-2019 survey of licensed APA-member psychologists who treat adults with PTSD (n = 407, response rate = 29.8%). We present survey findings on awareness about, attitudes toward, and adoption of the guideline and find significant differences across these domains between psychologists who do and do not regularly use clinical practice guidelines. We conclude by discussing future directions to advance dissemination research and practice. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Evidence-based psychological interventions are growing in number but are not within reach of many individuals who could benefit from them. The recent revolution in digital technologies now makes it possible to reach people around the globe with digital interventions in the form of web sites, mobile applications, wearable devices, and so on. Although a plethora of digital interventions are available online few are evidence-based and individuals have little guidance to decide among the multitude of options. We propose the development of "digital apothecaries," that is, online repositories of evidence-based digital interventions. As portals to effective interventions, digital apothecaries would be useful to individuals who could access evidence-based interventions directly, to health care providers, who could identify specific digital tools to suggest to or use with their patients, and to researchers, who could study a range of tools with large samples, enabling comparative tests and evaluation of moderators of effects. We present a taxonomy of types of in-person and digital interventions ranging from traditional therapy without the use of digital tools to totally automated self-help interventions. This taxonomy highlights the potential of blending digital tools into health care systems to expand their reach. Digital apothecaries would provide access to evidence-based digital interventions (both free and paid versions), provide data on effectiveness (including effectiveness for diverse populations), and encourage the development and testing of more such tools. Other issues discussed include: criteria for inclusion of interventions into digital apothecaries; how digital tools could enhance health care for diverse populations; and cautionary notes regarding potential negative unintended consequences of the adoption of digital interventions into the health care system. In particular, we warn about the potential misuse of evidence-based digital interventions to justify reducing access to live providers. Digital apothecaries bring with them the promise of reducing health disparities by reaching large numbers of individuals across the world who need health interventions but are not currently receiving them. The health care field is encouraged to mindfully develop this promise, while being alert not to cause inadvertent harm.

ObjectiveThis study explored the automatic and controlled processes that may influence performance on an implicit measure across cognitive-behavioral group therapy for panic disorder.MethodThe Quadruple Process model was applied to error scores from an Implicit Association Test evaluating associations between the concepts Me (vs. Not Me) + Calm (vs. Panicked) to evaluate four distinct processes: Association Activation, Detection, Guessing, and Overcoming Bias. Parameter estimates were calculated in the panic group (n = 28) across each treatment session where the IAT was administered, and at matched times when the IAT was completed in the healthy control group (n = 31).ResultsAssociation Activation for Me + Calm became stronger over treatment for participants in the panic group, demonstrating that it is possible to change automatically activated associations in memory (vs. simply overriding those associations) in a clinical sample via therapy. As well, the Guessing bias toward the calm category increased over treatment for participants in the panic group.ConclusionsThis research evaluates key tenets about the role of automatic processing in cognitive models of anxiety, and emphasizes the viability of changing the actual activation of automatic associations in the context of treatment, versus only changing a person's ability to use reflective processing to overcome biased automatic processing.

Background: Biases in social reinforcement learning, or the process of learning to predict and optimize behavior based on rewards and punishments in the social environment, may underlie and maintain some negative cognitive biases that are characteristic of social anxiety. However, little is known about how cognitive and behavioral interventions may change social reinforcement learning in individuals who are anxious., Objective: This study assessed whether a scalable, web-based cognitive bias modification for interpretations (CBM-I) intervention changed social reinforcement learning biases in participants with high social anxiety symptoms. This study focused on 2 types of social reinforcement learning relevant to social anxiety: learning about other people and learning about one's own social performance., Methods: Participants (N=106) completed 2 laboratory sessions, separated by 5 weeks of ecological momentary assessment tracking emotion regulation strategy use and affect. Approximately half (n=51, 48.1%) of the participants completed up to 6 brief daily sessions of CBM-I in week 3. Participants completed a task that assessed social reinforcement learning about other people in both laboratory sessions and a task that assessed social reinforcement learning about one's own social performance in the second session. Behavioral data from these tasks were computationally modeled using Q-learning and analyzed using mixed effects models., Results: After the CBM-I intervention, participants updated their beliefs about others more slowly (P=.04; Cohen d=-0.29) but used what they learned to make more accurate decisions (P=.005; Cohen d=0.20), choosing rewarding faces more frequently. These effects were not observed among participants who did not complete the CBM-I intervention. Participants who completed the CBM-I intervention also showed less-biased updating about their social performance than participants who did not complete the CBM-I intervention, learning similarly from positive and negative feedback and from feedback on items related to poor versus good social performance. Regardless of the intervention condition, participants at session 2 versus session 1 updated their expectancies about others more from rewarding (P=.003; Cohen d=0.43) and less from punishing outcomes (P=.001; Cohen d=-0.47), and they became more accurate at learning to avoid punishing faces (P=.001; Cohen d=0.20)., Conclusions: Taken together, our results provide initial evidence that there may be some beneficial effects of both the CBM-I intervention and self-tracking of emotion regulation on social reinforcement learning in individuals who are socially anxious, although replication will be important., (©Miranda L Beltzer, Katharine E Daniel, Alexander R Daros, Bethany A Teachman. Originally published in JMIR Formative Research (https://formative.jmir.org), 09.08.2023.)