Clinicians are tasked with predicting and preventing suicidal behavior among their patients; however, there is currently no method for accurately predicting whether a person will make a suicide attempt (SA) in the near future. We tested whether brief, smartphone-based surveys, combined with passively collected survey metadata, could predict the occurrence of suicidal behavior over the next 7 days among those at elevated risk. Participants were 619 patients presenting to the hospital with suicidal thoughts/behavior. They were sent brief (20-item) smartphone-based surveys 6 times/day for 3 months. Survey responses (N = 79,448) and metadata (e.g., time since last survey submission) were used as predictors of next-week SA and suicide-related event (SRE; which also included hospitalization to prevent an SA) in a series of machine learning models. The most accurate prediction was achieved using bidirectional long short-term memory and simple lasso-penalized logistic regression models, with the best performing model using bidirectional long short-term memory to predict SRE, which with specificity at .90, had area under the curve = .94, sensitivity = .87, and positive predictive value = .30, and SAs with area under the curve = .90, sensitivity = .74, positive predictive value = .16. Prediction accuracy was higher than has been achieved in prior studies and was strongest for models that predicted SREs (vs. SAs), included more sources of data, focused on adults (vs. adolescents), and when participants' own data were included in the model training process (vs. being held out). The strongest and most consistent predictors of next-week SA included within-study history of SREs (from adult lasso regression: OR = 1.47) and self-reported agitation (OR = 1.11), whereas odds of next-week SA were decreased for surveys submitted on weekends (OR = 0.87) and in the context of feelings that one could resist suicidal urges (OR = 0.88-0.96). Brief smartphone-based surveys can predict next-week SAs/SREs with a fairly high degree of accuracy. Future work is needed to further improve accuracy and test just-in-time interventions targeting high-risk periods. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Ecological momentary assessment (EMA) holds great potential for understanding suicidal thoughts and behaviors (STBs) in real time. However, since the burden of EMA can lower participant engagement, more research is needed to understand how individuals engage with it, particularly during high suicide risk periods. This study aims to better understand participant engagement with EMA using both qualitative and quantitative indices. One hundred adults were enrolled in an EMA study during psychiatric inpatient hospitalization for STBs and completed six brief EMA surveys per day assessing STBs and related factors during hospitalization and for four weeks after. At the end of the study, participants completed a qualitative interview assessing motivations to participate, study perceptions, perspectives on EMA, engagement barriers, and recommendations. Participants completed 14,464 EMA surveys in total, with an average completion rate of 58%. Engagement was higher during hospitalization (66%) than after (54%). In interviews, most found EMA acceptable (59% enjoyed participation), noting that surveys often increased emotional awareness (51%). Some found EMA repetitive or tedious, and only a small minority found it distressing. Primary motivations were financial compensation (73%) and contributing to research (69%). Main barriers were schedules (92%) and momentary distress (60%). Recommendations largely focused on improving EMA administration, such as survey frequency. Most qualitative themes did not significantly differ by EMA engagement, although lower engagers gave more recommendations and had more unique barriers than high engagers. Quantitative and qualitative findings indicate EMA of STBs is generally acceptable during and after psychiatric hospitalization, with important recommendations for improvement. Integrating participant experiences is critical as researchers and clinicians work to optimize EMA with individuals at risk for suicide.

This study demonstrates that changes in mindfulness predict subsequent changes in well-being in a data set including individuals who recently engaged in psychedelic use.

Ecological momentary assessment (EMA) is increasingly used to study suicidal thoughts and behaviors (STBs). There is a potential ethical obligation for researchers to intervene when receiving information about suicidal thoughts in real time. A possible concern, however, is that intervening when receiving responses that indicate high risk for suicide during EMA research may impact how participants respond to questions about suicidal thoughts and thus affect the validity and integrity of collected data. We leveraged data from a study of adults and adolescents (N = 434) recruited during a hospital visit for STBs to examine whether monitoring and intervening on high-risk responses affects subsequent participant responding. Overall, we found mixed support for the notion that intervening on high-risk responses influences participants' ratings. Although we observed some evidence of discontinuity in subsequent responses at the threshold used to trigger response-contingent interventions, it was not clear that such discontinuity was caused by the interventions; lower subsequent responses could be due to effective intervention, participant desire to not be contacted again, or regression to the mean. Importantly, the likelihood of completing surveys did not change from before to after response-contingent intervention. Adolescents were significantly more likely than adults, however, to change their initial suicidal intent ratings from above to below the high-risk threshold after viewing automated response-contingent pop-up messages. Studies explicitly designed to assess the potential impact of intervening on high-risk responses in real-time monitoring research are needed, as this will inform effective, scalable strategies for intervening during moments of high suicide risk. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

People’s representations of categories are shaped by normative value: More valuable stimuli are more likely to be judged as normal and more likely to spontaneously come to mind than less valuable stimuli. Why is this the case? One possibility, consistent with findings from the memory literature, is that people are simply more likely to attend to and encode things that are high value, which could in turn shape representations of what is normal. However, it is also possible that value can exert its influence on normality judgments and what comes to mind (WCTM) after the encoding of statistical information has already taken place. To explore whether selective encoding can explain the influence that value exerts on default judgments, we revisit a paradigm from past work that found a strong effect of value on normality judgments and WCTM. Within this paradigm, we explore whether higher-value stimuli are more likely to be judged as normal and more likely to come to mind even if information about value is only presented after all stimuli have been shown. Surprisingly, even in this case, value information exerts a strong influence on people’s judgments, casting doubt on explanations for past findings that involve selective attention or encoding of high-value statistical information.

Yarkoni argues that researchers making broad inferences often use impoverished statistical models that fail to include important sources of variation as random effects. We argue, however, that for many common study designs, random effects are inappropriate and insufficient to draw general inferences, as the source of variation is not random, but systematic.

Prediction problems vary in the extent to which accuracy is rewarded and inaccuracy is penalized—i.e., in their loss functions. Here, we focus on a particular feature of loss functions that controls how much large errors are penalized relative to how much precise correctness is rewarded: convexity. We show that prediction problems with convex loss functions (i.e., those in which large errors are particularly harmful) favor simpler models that tend to be biased, but exhibit low variability. Conversely, problems with concave loss functions (in which precise correctness is particularly rewarded) favor more complex models that are less biased, but exhibit higher variability. We discuss how this relationship between the bias-variance trade-off and the shape of the loss function may help explain features of human psychology, such as dual-process psychology and fast versus slow learning strategies, and inform statistical inference.

What can be done to combat political misinformation? One prominent intervention involves attaching warnings to headlines of news stories that have been disputed by third-party fact-checkers. Here we demonstrate a hitherto unappreciated potential consequence of such a warning: an implied truth effect, whereby false headlines that fail to get tagged are considered validated and thus are seen as more accurate. With a formal model, we demonstrate that Bayesian belief updating can lead to such an implied truth effect. In Study 1 (n = 5,271 MTurkers), we find that although warnings do lead to a modest reduction in perceived accuracy of false headlines relative to a control condition (particularly for politically concordant headlines), we also observed the hypothesized implied truth effect: the presence of warnings caused untagged headlines to be seen as more accurate than in the control. In Study 2 (n = 1,568 MTurkers), we find the same effects in the context of decisions about which headlines to consider sharing on social media. We also find that attaching verifications to some true headlines—which removes the ambiguity about whether untagged headlines have not been checked or have been verified—eliminates, and in fact slightly reverses, the implied truth effect. Together these results contest theories of motivated reasoning while identifying a potential challenge for the policy of using warning tags to fight misinformation—a challenge that is particularly concerning given that it is much easier to produce misinformation than it is to debunk it. This paper was accepted by Elke Weber, judgment and decision making.

When solving problems, like making predictions or choices, people often “sample” possibilities into mind. Here, we consider whether there is structure to the kinds of thoughts people sample by default—that is, without an explicit goal. Across three experiments we found that what comes to mind by default are samples from a probability distribution that combines what people think is likely and what they think is good. Experiment 1 found that the first quantities that come to mind for everyday behaviors and events are quantities that combine what is average and ideal. Experiment 2 found, in a manipulated context, that the distribution of numbers that come to mind resemble the mathematical product of the presented statistical distribution and a (softmax-transformed) prescriptive distribution. Experiment 3 replicated these findings in a visual domain. These results provide insight into the process generating people’s conscious thoughts and invite new questions about the value of thinking about things that are both likely and good.

People's devotion to, and love for, their romantic partners poses an evolutionary puzzle: Why is it better to stop your search for other partners once you enter a serious relationship when you could continue to search for somebody better? A recent formal model based on strategic ignorance suggests that such behavior can be adaptive and favored by natural selection, so long as you can signal your unwillingness to look for other potential mates to your current partner. Here, we re-examine this conclusion with a more detailed model designed to capture specific features of romantic relationships. We find, surprisingly, that devotion does not typically evolve in our model: Selection favors agents who choose to look while in relationships and who allow their partners to do the same. Non-looking is only expected to evolve if there is an extremely large cost associated with being left by your partner. Our results therefore raise questions about the role of strategic ignorance in explaining the evolution of love.

Delusion-prone individuals may be more likely to accept even delusion-irrelevant implausible ideas because of their tendency to engage in less analytic and less actively open-minded thinking Consistent with this suggestion, two online studies with over 900 participants demonstrated that although delusion-prone individuals were no more likely to believe true news headlines, they displayed an increased belief in "fake news" headlines, which often feature implausible content. Mediation analyses suggest that analytic cognitive style may partially explain these individuals' increased willingness to believe fake news. Exploratory analyses showed that dogmatic individuals and religious fundamentalists were also more likely to believe false (but not true) news, and that these relationships may be fully explained by analytic cognitive style. Our findings suggest that existing interventions that increase analytic and actively open-minded thinking might be leveraged to help reduce belief in fake news.

People can consciously think about only a few things at a time. But what determines the kind of things that come to mind, among a potentially infinite set of possibilities? Two experiments explored whether the things that come to mind are sampled from a probability distribution that combines what people think is statistically likely and what they think is prescriptively good. Experiment 1 found that when people are asked about the first quantities that come to mind for everyday behaviors and events (e.g., hours of TV that a person could watch in a day), they think of values that are proportional to, and intermediate between, what they think is average and what they think is ideal. Experiment 2 quantitatively manipulated distributions of times people devoted to engaging in a novel hobby (“flubbing”) and the corresponding distributions of goodness of doing this hobby for various amounts of time. The distribution of values that came to mind resembled the mathematical product of the statistical and prescriptive distributions we presented participants, suggesting that something must be both common and good to enter conscious awareness. These results provide insight into the algorithmic process generating people’s conscious thoughts and invite new questions about the adaptive value of thinking about things that are both common and good.

Poster Session I S147assessed with the PANSS.The relationship between SM biases and neuropsychological functioning was investigated with correlation analyses. Results:The correlations were found between incorrect action's presentation type discrimination and the results of test such as CTT 1 (r=-0.22,p<0.05),D2 (r=-0.25,p<0.05) and Block Design (r= -0.40, p<0.01).Correlational analyses showed no relations between incorrect self-monitoring and neuropsychological functioning.Knowledge corruption for self-monitoring turned out to be correlated with WCST (r=0,22, p<0.05),CVLT (r= -0.26, p<0.05) and Backward Digit Span (r= -0.27, p<0.05).These correlations remain significant when controlled for positive symptoms severity.Incorrect self-monitoring showed a significant relation with the PANSS positive subscale (r=0.23,p<0.05).Knowledge corruption was related to PANSS disorganization subscale (r=0.25,p<0.05).Discussion: In line with previous studies we found that deficits in selfmonitoring are related to symptoms severity and not to neuropsychological functioning.On the other hand, deficits in action's presentation discrimination are related exclusively to neuropsychological functioning.These results suggest that the relationship between SM and neuropsychological functioning depends on the type of SM deficits.The conclusions of the study may be of clinical importance -in light of our results it might be advisable to combine cognitive remediation techniques with those interventions that focus on cognitive biases like source monitoring deficits T83.

How does cognitive sophistication impact cooperation? We explore this question using a model of the co-evolution of cooperation and cognition. In our model, agents confront social dilemmas and coordination games, and make decisions using intuition or deliberation. Intuition is automatic and effortless, but relatively (although not necessarily completely) insensitive to context. Deliberation, conversely, is costly but relatively (although not necessarily perfectly) sensitive to context. We find that regardless of the sensitivity of intuition and imperfection of deliberation, deliberating undermines cooperation in social dilemmas, whereas deliberating can increase cooperation in coordination games if intuition is sufficiently sensitive. Furthermore, when coordination games are sufficiently likely, selection favours a strategy whose intuitive response ignores the contextual cues available and cooperates across contexts. Thus, we see how simple cognition can arise from active selection for simplicity, rather than just be forced to be simple due to cognitive constraints. Finally, we find that when deliberation is imperfect, the favoured strategy increases cooperation in social dilemmas (as a result of reducing deliberation) as the benefit of cooperation to the recipient increases.

Psychologists, neuroscientists, and economists often conceptualize decisions as arising from processes that lie along a continuum from automatic (i.e., "hardwired" or overlearned, but relatively inflexible) to controlled (less efficient and effortful, but more flexible). Control is central to human cognition, and plays a key role in our ability to modify the world to suit our needs. Given its advantages, reliance on controlled processing may seem predestined to increase within the population over time. Here, we examine whether this is so by introducing an evolutionary game theoretic model of agents that vary in their use of automatic versus controlled processes, and in which cognitive processing modifies the environment in which the agents interact. We find that, under a wide range of parameters and model assumptions, cycles emerge in which the prevalence of each type of processing in the population oscillates between 2 extremes. Rather than inexorably increasing, the emergence of control often creates conditions that lead to its own demise by allowing automaticity to also flourish, thereby undermining the progress made by the initial emergence of controlled processing. We speculate that this observation may have relevance for understanding similar cycles across human history, and may lend insight into some of the circumstances and challenges currently faced by our species. (PsycINFO Database Record

Modelling and experiments have shown that strategic information can undermine 'altruistic' cooperation. Using a model that varies the distribution of costs for finding out, it is now shown that information can also promote self-interested 'strategic' cooperation.

The timing of thoughts and perceptions plays an essential role in belief formation. Just as people can experience in-the-moment perceptual illusions, however, they can also be deceived about how events unfold in time. Here, we consider how a particular type of temporal distortion, in which the apparent future influences "earlier" events in conscious awareness, might affect people's most fundamental beliefs about themselves and the world. Making use of a task that has been shown to elicit such reversals in the temporal experience of prediction and observation, we find that people who are more prone to think that they predicted an event that they actually already observed are also more likely to report holding delusion-like beliefs. Moreover, this relationship appears to be specific to how people experience prediction and is not explained by domain-general deficits in temporal discrimination. These findings may help uncover low-level perceptual mechanisms underlying delusional belief or schizotypy more broadly and may ultimately prove useful as a tool for identifying those at risk for psychotic illness.

Humans often cooperate with strangers, despite the costs involved. A long tradition of theoretical modeling has sought ultimate evolutionary explanations for this seemingly altruistic behavior. More recently, an entirely separate body of experimental work has begun to investigate cooperation's proximate cognitive underpinnings using a dual-process framework: Is deliberative self-control necessary to reign in selfish impulses, or does self-interested deliberation restrain an intuitive desire to cooperate? Integrating these ultimate and proximate approaches, we introduce dual-process cognition into a formal game-theoretic model of the evolution of cooperation. Agents play prisoner's dilemma games, some of which are one-shot and others of which involve reciprocity. They can either respond by using a generalized intuition, which is not sensitive to whether the game is one-shot or reciprocal, or pay a (stochastically varying) cost to deliberate and tailor their strategy to the type of game they are facing. We find that, depending on the level of reciprocity and assortment, selection favors one of two strategies: intuitive defectors who never deliberate, or dual-process agents who intuitively cooperate but sometimes use deliberation to defect in one-shot games. Critically, selection never favors agents who use deliberation to override selfish impulses: Deliberation only serves to undermine cooperation with strangers. Thus, by introducing a formal theoretical framework for exploring cooperation through a dual-process lens, we provide a clear answer regarding the role of deliberation in cooperation based on evolutionary modeling, help to organize a growing body of sometimes-conflicting empirical results, and shed light on the nature of human cognition and social decision making.

Do we see more than we can report? Psychologists and philosophers have been hotly debating this question, in part because both possibilities are supported by suggestive evidence. On one hand, phenomena such as inattentional blindness and change blindness suggest that visual awareness is especially sparse. On the other hand, experiments relating to iconic memory suggest that our in-the-moment awareness of the world is much richer than can be reported. Recent research has attempted to resolve this debate by showing that observers can accurately report the color diversity of a quickly flashed group of letters, even for letters that are unattended. If this ability requires awareness of the individual letters' colors, then this may count as a clear case of conscious awareness overflowing cognitive access. Here we explored this requirement directly: can we perceive ensemble properties of scenes even without being aware of the relevant individual features? Across several experiments that combined aspects of iconic memory with measures of change blindness, we show that observers can accurately report the color diversity of unattended stimuli, even while their self-reported awareness of the individual elements is coarse or nonexistent-and even while they are completely blind to situations in which each individual element changes color mid-trial throughout the entire experiment. We conclude that awareness of statistical properties may occur in the absence of awareness of individual features, and that such results are fully consistent with sparse visual awareness.