Thinking Clearly About Biology and Childhood Adversity: Next Steps for Continued Progress
Seth D. Pollak and Karen E. Smith
Pollak and Smith respond to McLaughlin and colleagues’ commentary on their original article. They summarize where their perspectives diverge and overlap, emphasizing how the agreement on many issues could stimulate new ideas for research on the effects of childhood adversity. They suggest that, to progress, the field needs a sound basis for classifying adversity and that the most promising approaches might be those that emphasize how children perceive their experiences and the circumstances influencing these perceptions instead of the adverse events themselves.
The Value of Dimensional Models of Early Experience: Thinking Clearly About Concepts and Categories
Katie A. McLaughlin, Margaret A. Sheridan, Kathryn L. Humphreys, Jay Belsky, and Bruce J. Ellis
McLaughlin and colleagues comment on an article by Smith and Pollak about the conceptual challenges of researching the effects of childhood adversity. Smith and Pollak had suggested that relying on categorizations created by lumping together or separating out different types of adversity, such as domestic violence and poverty, results in categories that overlap or that lack consistent biological evidence. McLaughlin and colleagues disagree with some of the criticisms and defend the utility of dimensional models of early experience. According to them, these models identify core dimensions of early experience that cut across categorical exposures to threat. The models also articulate specific mechanisms through which threat dimensions influence outcomes. They argue that these models advance falsifiable hypotheses, grounded in neurodevelopmental and evolutionary principles, that are supported by accumulating evidence.
Applying the Science of Habit Formation to Evidence-Based Psychological Treatments for Mental Illness
Allison G. Harvey, Catherine A. Callaway, Garret G. Zieve, Nicole B. Gumport, and Courtney C. Armstrong
Harvey and colleagues recommend exploring habit-formation principles, theories, and measures for the development of evidence-based psychological treatments (EBPTs) for mental illness (i.e., interventions targeting psychological processes that contribute to mental illness and that have been evaluated scientifically). They specify six characteristics of habit formation that may improve the success of EBPTs: Habits are independent of goals, cued by specific contexts, learned via repetition, automatic, and promoted by reinforcers; in addition, they take time to develop. The researchers suggest the need for more research to guide the application of the science of habit formation and disruption to real-life habits that underlie EBPTs.
Critique of the Bias-of-Crowds Model Simply Restates the Model: Reply to Connor and Evers (2020)
B. Keith Payne, Heidi Vuletich, and Kristjen B. Lundberg
In their bias-of-crowds model, Payne and colleagues suggested that implicit bias can be understood as a feature of situations. However, in a 2020 article, Connor and Evers argued that implicit bias is best understood as a feature of individuals, whose measurement includes errors. In this reply, Payne and colleagues argue that the 2020 critique simply restated the bias-of-crowds model, that is, it agreed that implicit bias varies across persons and situations and that the disagreement, if any, appears to be about what it means to be an “individual construct” or a “feature of situations,” Payne and colleagues write.
Humans tend to explain things by their purpose rather than their cause. This teleological reasoning can be rationally and thoughtfully used, Scott proposes. It can be associated with good outcomes (e.g., finding meaning in misfortune) and bad outcomes (e.g., believing in conspiracy theories). Scott synthesizes psychological research on teleology with Daniel Dennett’s intentional-systems theory to define teleology as a rational mode of reasoning that creates useful explanations. The available knowledge helps shape these explanations, as does the individuals’ selected intellectual stance, which is either an intentional stance (using estimates of a rational agent’s beliefs to predict its behavior) or design stance (using knowledge of a target’s function to predict its behavior).
The Rise, Demise, and Reprise of the Increasingly Protracted APA Journal Article?
Gregory D. Webster, Val Wongsomboon, and Elizabeth A. Mahar
Scientific articles might be getting longer, Webster and colleagues suggest. The researchers analyzed the length of American Psychological Association journal articles published between 1986 and 2019. Results indicated that article length increased in the 1980s and the 1990s, plateaued in the 2000s, and increased again in the 2010s. Journals with a higher impact factor also had the largest increases in article length. Moreover, it appears that pages per article increased most on average after psychology’s credibility crisis. These findings might be related to an increased emphasis on reporting experimental details and transparency.
Three Theories of Choice and Their Psychology of Losses
Tomás Lejarraga and Ralph Hertwig
Lejarraga and Hertwig review three theories of how people make decisions and avert potential losses when risk is a factor. Expected-utility theory posits that people may be concerned about the long term and tend to be risk averse when losses loom larger than gains. According to prospect theory, although people tend to prefer sure gains over risky gains, they tend to avoid sure losses while risking an even bigger loss. Finally, risk-sensitivity theory posits that people may shift from risk aversion to risk preference, depending on the situation. Lejarraga and Hertwig evaluate where the theories differ, including the conceptualization of loss aversion and risk aversion.
Psychological Science in the Wake of COVID-19: Social, Methodological, and Metascientific Considerations
Daniel L. Rosenfeld et al.
Rosenfeld and a large group of researchers from different institutions write about how to optimize psychological research in the wake of COVID-19, when preventing transmission of COVID-19 remains a factor influencing everyday behavior. They highlight the psychological phenomena (namely, socially driven) that are most likely to have changed because of the pandemic. The authors also evaluate theoretical, methodological, and practical considerations of researching the changed phenomena. In addition, they discuss metascientific issues amplified by the pandemic and suggest that theoretically grounded views on COVID-19 may help to strengthen psychological science.