Radically different
PCOS is dead. Long live PMOS.
Revealed Tuesday, the one-letter change in nomenclature for a common metabolic condition in women may seem unremarkable, but it follows more than a decade of vigorous debate over the need for a name that more precisely and completely describes what until now was known as polycystic ovary syndrome (PCOS).
In early 2025, biotech experienced a “DeepSeek moment” when biotech and pharma leaders alike realized how quickly China was gaining ground with innovation, speed of drug development, and share of licensing deals. In 2020, global pharmaceutical companies spent about $9 billion on licensed drug assets from China. In 2025, that number shot to more than $137 billion. The first two months of 2026 alone accounted for nearly $50 billion in deals. As a December 2025 report from the National Security Commission on Emerging Biotechnology put it, “in just three years, China’s biopharmaceutical industry rose from near irrelevance to dominance.”
China’s rise is happening with the blessing of U.S. pharmaceutical executives, who are allowing their own industry to be destroyed.
I am a co-chair of a working group at the Council on Foreign Relations investigating the U.S.’s generic pharmaceutical dependence on China. An estimated 60% of our generic medications have an active ingredient that originates in China; some estimates have this figure as high as 80-90%. (The exact percentage is unknown because the Food and Drug Administration doesn’t formally track this information, and because a significant percentage of our drugs are imported from India, which in turn imports chemical precursors from China.)
WASHINGTON — Patient groups are jockeying for exemptions from Medicaid work requirements, but the unusually fast implementation timeline for states is causing headaches.
Federal officials have until June 1 to tell states how to implement a provision of President Trump’s tax cut bill that requires certain Medicaid beneficiaries to show that they’re working, in school, or volunteering in order to keep their coverage. Once that regulation is out, states will have to put their systems in place by Jan. 1.
Advocates for people with certain diseases have been meeting with federal officials to urge that those patients be automatically exempt from the work requirements. For example, Patients with sickle cell disease recently met with White House budget officials to request an exemption. Advocacy groups for people with HIV are making a similar push.
Psychological Review, Vol 133(4), Jul 2026, 771-819; doi:10.1037/rev0000596
One of the most common method of eliciting false memories in the laboratory is the Deese–Roediger–McDermott paradigm (Deese, 1959; Roediger & McDermott, 1995), where participants study a set of items that are all similar to a nonpresented critical lure. A common finding is that false recognition to critical lures is much higher than to other nonpresented items and in some cases is even comparable to true recognition, regardless of whether similarity is semantic or structural (e.g., phonological or orthographic) relations. While there exists a handful of computational models of this paradigm, they have only been applied to semantic but not structural false recognition, they have not been fit at the level of individual participants, and they have not been applied to response times. We present a global matching model that addresses all three of these current gaps. Global similarity of semantic and structural representations drives a pair of linear ballistic accumulators, which are used to produce decisions as well as complete response time distributions. In addition to being able to account for heightened false recognition of critical lures, the model was able to account for differences across both individual participants and items, lower correlations between semantic and structural false recognition than true recognition, differences in false recognition across levels of processing, improved true recognition but not false recognition with higher study time, and heightened false recognition under speed emphasis. The model suggests that semantic and structural false recognition can be explained using only a single retrieval mechanism. (PsycInfo Database Record (c) 2026 APA, all rights reserved)
Psychological Review, Vol 133(4), Jul 2026, 820-845; doi:10.1037/rev0000587
Transitivity of preference (ToP) is a central axiom of rational choice theory. While violating ToP is rare and subject to debate, there have been reports of such violations (Tsetsos et al., 2016a; Tversky, 1969, but see Iverson & Falmagne, 1985; Regenwetter et al., 2011). If humans indeed violate ToP, an important challenge is understanding the conditions and mechanisms that promote either transitive or intransitive preferences. Here, we report the presence of ToP violations using a data analysis method that was prescribed as statistically adequate (Regenwetter et al., 2011), and an experimental design where each choice is presented on a single visual display to avoid artifacts that can be associated with sequential presentation and aggregation across choice stimuli. We introduce two cognitive heuristics that predict certain violations of ToP and we translate them into probabilistic choice models. Then, in three experiments (one of which is a preregistered replication), we evaluate violations of ToP and we assess the models that predict such violations. We find that, despite pervasive individual differences, the ToP adherence rate is much enhanced when the task was presented in a fashion that facilitates within-alternative integration. We also find that the proposed heuristic models successfully explain those ToP violations that do occur. These findings shed light on the conditions and cognitive mechanisms that support ToP. (PsycInfo Database Record (c) 2026 APA, all rights reserved)
Psychological Review, Vol 133(4), Jul 2026, 864-891; doi:10.1037/rev0000584
Currently, formal models of addiction focus either on the complex individual decision-making processes involved in addiction or on the social dynamics of addiction. They do not integrate these two levels, which has been identified as a key shortcoming of current formal models of addiction. To address this, we propose a nonlinear dynamical modeling framework of addiction integrating both the individual level and social level of addictive behavior. The individual level of our modeling framework is a formalization of a dual-process theory, where one type of process increases the consumption of addictive goods, and another type of process limits consumption. For our formalization, we build on a well-studied model from ecology, originally used to model periodic outbreaks of the spruce budworm population. To this model, we add the process of incentive sensitization at the individual level and at the social level, we incorporate the critical processes of selection homophily and peer influence. We show that our integrated modeling framework can be used to explain key phenomena identified in addiction literature: a gradual transition to heavy use, sudden relapse and sudden quitting, relatively stable use states over time (i.e., abstinence moderate use, and heavy use), social contagion and sudden outbreaks, clustering of users, and social aid in recovery. In addition, we demonstrate how our modeling framework can be extended to include mutualistic, competitive, and more complex interactions between different addictive behaviors. Finally, we show how our framework can lead to new insights and predictions and suggest avenues for future research. (PsycInfo Database Record (c) 2026 APA, all rights reserved)
Psychological Review, Vol 133(4), Jul 2026, 846-863; doi:10.1037/rev0000576
A cornerstone of human intelligence is the ability to flexibly adjust our cognition and behavior as our goals change. For instance, achieving some goals requires efficiency, while others require caution. Different goals require us to engage different control processes, such as adjusting how attentive and cautious we are. Here, we show that performance incurs control adjustment costs when people adjust control to meet changing goals. Across four experiments, we provide evidence of these costs and validate a dynamical systems model explaining the source of these costs. Participants performed a single cognitively demanding task under varying performance goals (e.g., being fast or accurate). We modeled control allocation to include a dynamic process of adjusting from one’s current control state to a target state for a given performance goal. By incorporating inertia into this adjustment process, our model accounts for our empirical finding that people undershoot their target control state more (i.e., exhibit larger adjustment costs) when goals switch rather than remain fixed (Study 1). Further validating our model, we show that the magnitude of this cost is increased when: distances between target states are larger (Study 2), there is less time to adjust to the new goal (Study 3), and goal switches are more frequent (Study 4). Our findings characterize the costs of adjusting control to meet changing goals and show that these costs emerge directly from cognitive control dynamics. In so doing, they shed new light on the sources of and constraints on flexibility of goal-directed behavior. (PsycInfo Database Record (c) 2026 APA, all rights reserved)
Psychological Review, Vol 133(4), Jul 2026, 892-918; doi:10.1037/rev0000594
Understanding how people assign subjective value to outcomes with multiple attributes, such as risk and delay, is central to understanding the structure and manifestation of economic preferences. However, multiattribute preference has been primarily studied through binary choices. The price at which a person would buy, sell, or equate each prospect offers another measure of subjective value that may diverge from multiattribute choice. In both risky and intertemporal domains, choice and price preferences exhibit systematic preference reversals, where a smaller, sooner, or safer option is chosen while a larger, later, or riskier alternative is assigned a higher price. The present study takes a deep dive into how subjective value is assigned in each case in an attempt to reconcile these diverging measurements and methods of assessing value. To explain how and why preferences change across choice and price, the domains of gains and losses, price frames of buying and selling, and varying levels of time pressure, we develop a two-step neural network–based modeling approach. First, we tested cognitive mechanisms underlying value-based judgments and decisions using a switchboard model comparison. Next, we fit and evaluated individualized joint models, where all data from an individual are modeled using parameters and mechanisms that are specific to their best fitting model structure. While mechanisms like delay discounting and risk aversion are common to both models, our results suggest that anchoring and payoff sensitivity diverged between pricing and choice. Extensive differences across elicitation procedures indicate that a common representation of value may remain elusive. (PsycInfo Database Record (c) 2026 APA, all rights reserved)