Current Opinion in Psychology最新文献

How everyday self-control conflicts are resolved can have significant long-term personal and societal consequences, as readily illustrated by obesity, smoking, and unsustainable consumption. Here, we delineate connections between current self-control research and policymaking. We first discuss the achievements and shortcomings of the prevailing individual-level focus in self-control research. Next, we propose a multilevel perspective that incorporates structural factors operating at the micro, meso, and macro levels as the root cause of many issues framed as self-control problems. We then introduce a comprehensive framework (4LP) synthesizing four key levers for public policymaking. We conclude that future policy research may benefit from closer, interdisciplinary collaboration to better represent the complex interplay between individual agency and structural factors regarding self-control outcomes.

This review explores the impact of Generative Artificial Intelligence (GenAI)—a technology capable of autonomously creating new content, ideas, or solutions by learning from extensive data—on psychology. GenAI is changing research methodologies, diagnostics, and treatments by enhancing diagnostic accuracy, personalizing therapeutic interventions, and providing deeper insights into cognitive processes. However, these advancements come with significant ethical concerns, including privacy, bias, and the risk of depersonalization in therapy. By focusing on the current capabilities of GenAI, this study aims to provide a balanced understanding and guide the ethical integration of AI into psychological practices and research. We argue that while GenAI presents profound opportunities, its integration must be approached cautiously using robust ethical frameworks.

Highly motivated individuals are healthier, more academically and professionally successful, and have stronger relationships. What sets these individuals apart? We propose that highly motivated individuals know when to balance versus prioritize goals. Specifically, they seek harmony between their multiple goals: they see these goals as advancing or complementing each other (e.g., balancing work and family, finding foods that are both tasty and healthy). They also seek to prioritize pursuing a subset of these goals within a given time and place. They make consistent action choices that highlight more important goals (e.g., prioritize studying over social media while in class). The intuition to balance goals and prioritize actions is acquired through social learning and can be enhanced through mindfulness. In turn, it enables self-regulatory success.

Self-control is essential for outcomes in several life domains but is often seen as effortful. We discuss recent research indicating the possibility of effortless self-control. First, we discuss how high levels of self-control are associated with quicker self-control conflict identification and resolution. Second, we describe two pathways that may lead to these associations: (1) How automatization of behaviors plays a role in self-control outcomes. That is, self-control is associated with better, effortless habits. (2) We discuss that self-control conflicts can be anticipated and resolved with strategies that avoid effortful inhibition. Taken together, we aim to demonstrate that there is more to successful self-control than ‘simply’ working hard to resist your impulses – there may be easier roads to take.

Good self-control is highly valuable, but the processes that promote it are not fully understood. This review emphasizes that self-control is “inherently metacognitive” (p. 204, Duckworth et al., 2014) and describes the potential benefits of metacognitive knowledge for self-control. In line with research on metacognition in academic goal pursuit, we elaborate how three distinct types of metacognitive knowledge may aid self-control: strategy knowledge (for example, a repertoire of self-regulatory strategies), task knowledge (for example, understanding self-control demands), and person knowledge (for example, awareness of one's self-control strengths and weaknesses). Additionally, we identify research gaps and suggest that future studies should investigate the development and updating of metacognitive knowledge about self-control and how metacognitive knowledge can prevent individuals from justifying indulgence.

What do self-controlled individuals do that distinguishes them from those who are more impulsive? That is, why are some people better able to align their behavior with personal long-term goals despite alternatives that would be more immediately gratifying? To address this question, we use the Process Model of Self-Control [1], which posits that all impulses are generated via a four-stage, recursive process and can be regulated by intentionally intervening at any of these stages. We suggest that this framework illuminates not only individual states of self-control, but also the diverse ways that stable individual differences in self-control can come about.

How people respond to desires varies substantially across time and situations. Building on recent theoretical developments, we propose that motivation plays a central role in the dynamics of self-control as it unfolds across time. We illustrate the role of motivation in self-control by highlighting evidence that pursuing goals for intrinsic (vs. extrinsic) reasons plays a key role in shaping when and how people engage in self-control in service to their goals. We then expand this framework by outlining several promising directions for future research, specifically emphasizing the dynamic interplay between motivation and self-control at various stages in the regulation process. Ultimately, we posit that motivation is a key factor in helping people flexibly regulate desires in accordance with situational demands.

Underutilization of mental health services is a complex problem that requires the investigation of new strategies to facilitate treatment-seeking. Nudging is a relatively new approach which has shown promise in promoting healthy behaviors in a variety of domains, though little work has investigated how nudges may be applied to the initiation of mental health treatment. In this paper, we review the limited work examining nudging related to treatment initiation and discuss findings from a study evaluating the impact of nudges on treatment-seeking. Findings provide insights into the acceptability and efficacy of nudging as a strategy for increasing treatment, and implications for future work exploring this approach for improving treatment access are discussed.

As nudges—subtle changes to the way options are presented to guide choice—have gained popularity across policy domains in the past 15 years, healthcare systems and researchers have eagerly deployed these light-touch interventions to improve clinical decision-making. However, recent research has identified the limitations of nudges. Although nudges may modestly improve clinical decisions in some contexts, these interventions (particularly nudges implemented as electronic health record alerts) can also backfire and have unintended consequences. Further, emerging research on crowd-out effects suggests that healthcare nudges may direct attention and resources toward the clinical encounter and away from the main structural drivers of poor health outcomes. It is time to move beyond nudges and toward the development of multi-level, structurally focused interventions.

Misinformation has risen in recent years, negatively affecting domains ranging from politics to health. To curb the spread of misinformation it is useful to consider why, how, and when people decide to share information. Here we suggest that information-sharing decisions are value-based choices, in which sharers strive to maximize rewards and minimize losses to themselves and/or others. These outcomes can be tangible, in the form of monetary rewards or losses, or intangible, in the form of social feedback. On social media platforms these rewards and losses are not clearly tied to the accuracy of information shared. Thus, sharers have little incentive to avoid disseminating misinformation. Based on this framework, we propose ways to nudge sharers to prioritize accuracy during information-sharing.