To disentangle the two kinds of uncertainty, the team designed a three-option probabilistic reversal-learning task framed as a fishing game, in which participants chose among three islands to maximize their catch. The researchers independently manipulated two dimensions: stochasticity, the random variability of outcomes under stable rules, and volatility, the rate at which the underlying reward contingencies actually changed. In the low-stochasticity environment, the best patch paid off on 80 percent of trials; in the high-stochasticity environment, it paid off only 60 percent of the time, making individual outcomes far less informative. Volatility was manipulated by reversing which patch was best every 25 trials in slow conditions and every 10 trials in fast ones. Because normative learning theory predicts that learning rates should rise under volatility but fall under high stochasticity, this design allowed the researchers to test whether anxious individuals violate these prescriptions in a selective way.

In the first experiment, fifty participants completed six 50-trial blocks spanning all combinations of stochasticity and volatility, and trait anxiety was measured with the State-Trait Anxiety Inventory. The results were unambiguous: participants with high trait anxiety, defined as a trait score of 45 or above, earned significantly fewer rewards than their low-anxiety peers, but only in environments that were stable yet noisy, that is, under slow volatility combined with medium or high stochasticity. When the environment genuinely changed rapidly, the two groups performed identically. This selectivity is the study’s central surprise. It rules out the idea that anxiety produces a blanket overestimation of environmental change; instead, anxious individuals remain sensitive to true volatility but fail to discount random outcome noise appropriately when the environment is actually stable.

Computational modeling revealed the mechanism behind this performance gap. The researchers fit a hierarchical Bayesian reinforcement-learning model with separate learning rates for rewards and punishments, allowing them to quantify how strongly each participant updated their beliefs after positive and negative feedback. Contrary to the widely held view that anxiety amplifies learning from negative outcomes, the elevated learning rates in high trait anxiety were reward-driven. Under slow volatility, higher trait anxiety predicted increasing reward learning rates as stochasticity rose, with 95 percent highest density intervals well above zero in both medium and high stochasticity conditions. Under fast volatility, reward learning rates did not vary with anxiety at all. Punishment learning rates, meanwhile, remained below task-optimal levels in both groups and did not differ between them, indicating that punishment sensitivity could not explain the performance differences.

To determine whether these elevated learning rates were actually harmful, the team simulated reinforcement-learning agents across nearly sixty thousand parameter combinations to identify the reward-maximizing learning rate for each environment. As normative theory predicts, the optimal learning rate increased with volatility and decreased with stochasticity. Against this benchmark, high trait anxious individuals significantly exceeded the optimal reward learning rate in the stable, noisy environments, with Bayes factors exceeding ten billion in the medium-stochasticity condition. Higher learning rates were in turn associated with lower reward accumulation, and anxious participants clustered in the region of high learning rates and low earnings. In other words, anxious learners were overfitting noise, updating their beliefs on the basis of random reward fluctuations as if each surprise signaled a genuine shift in the world.

The decision process itself was also altered. Using hierarchical drift-diffusion modeling, which decomposes reaction times into parameters such as drift rate, the speed of evidence accumulation, and boundary separation, the threshold of information required before committing to a choice, the researchers found that in the slow-volatility, high-stochasticity environment, high trait anxious participants showed drift rates centered near zero, dramatically slower than those of low-anxiety peers, along with elevated decision boundaries. Under fast volatility, none of these differences appeared. This means anxious individuals were not only updating their beliefs too aggressively but also accumulating evidence more slowly and cautiously when valuing the most rewarding option, a double computational burden confined precisely to environments that demand a clean separation of signal from noise.

The second experiment asked whether sleep, a physiological state tightly intertwined with anxiety, could modulate these computational phenotypes. Forty participants performed the task before and after sleeping in the laboratory, with overnight sleep recorded using a validated wearable EEG headband. Greater N3 sleep, the deepest stage of non-REM sleep characterized by slow delta oscillations and strongly linked to synaptic plasticity, was associated with a larger evening-to-morning reduction in state anxiety. Contrary to the researchers’ initial prediction, it was the high trait anxious participants who derived the greatest anxiolytic benefit, showing the steepest dissipation of morning state anxiety as their N3 duration increased. No comparable associations emerged for lighter N1 or N2 sleep or for REM sleep.

The restorative benefit of deep sleep extended directly into the realm of learning. Post-sleep reward accumulation was higher than pre-sleep performance overall, and greater N3 sleep specifically predicted higher post-sleep earnings and more accurate identification of the most rewarding patch in high trait anxious individuals, particularly under slow volatility. At the computational level, reward learning rates decreased from pre- to post-sleep under high stochasticity across all participants, consistent with normative adjustment, and greater N3 sleep was associated with significantly reduced post-sleep reward learning rates in the anxious group. When compared against the simulated optimal benchmarks, participants with more N3 sleep showed learning rates that were statistically indistinguishable from optimal values after sleep, whereas those with less N3 sleep continued to exceed the optimal benchmark. Post-sleep drift rates also rose, indicating faster, more confident evidence accumulation favoring the best option.

Taken together, the two experiments sketch a coherent picture in which trait anxiety selectively corrupts the inference that separates stochastic noise from genuine environmental change, inflating reward learning rates in stable but noisy settings and slowing the accumulation of decision evidence, while N3 sleep acts as a state-dependent corrective that nudges these parameters back toward their task-optimal values. The authors caution that N3 sleep was measured rather than experimentally manipulated, so its effects remain partly correlational, and that related constructs such as intolerance of uncertainty were not assessed, leaving open whether the observed effects are unique to trait anxiety. The sample was also drawn from a single campus community, and circadian factors were not controlled. Even so, because the trade-off between stochasticity and volatility is fundamental to countless real-world learning problems, from financial markets to social relationships, the study raises the provocative possibility that protecting deep sleep could be a tangible, physiological lever for improving how anxious minds learn under uncertainty.

Subject of Research: How trait anxiety and N3 sleep shape reward learning and decision-making under stochasticity and volatility

Article Title: Trait anxiety selectively amplifies reward learning under uncertainty, while N3 sleep attenuates it

Article References: Deshmukh, R., & Ramakrishnan, A. (2026). Trait anxiety selectively amplifies reward learning under uncertainty, while N3 sleep attenuates it. iScience, 29(10), Article 117745. https://doi.org/10.1016/j.isci.2026.117745

Image Credits: AI Generated

DOI: 10.1016/j.isci.2026.117745

Keywords: trait anxiety, reward learning, uncertainty, stochasticity, volatility, N3 sleep, reinforcement learning, drift-diffusion model, reversal learning, decision-making, sleep EEG, computational psychiatry

The research team, led by Carina Berglund of Nantes Université’s Movement – Interactions – Performance laboratory, together with colleagues from Université Lumière Lyon 2 and Université d’Angers, focused on the Festival du Froid, held in France in 2024. Unlike controlled intervention trials, this was a field study embedded in a genuine community event, capturing the full context in which people actually engage with breathwork and cold exposure: outdoors, in groups, over consecutive days, and amid the social energy of a festival. This ecological realism is precisely what most existing evidence lacks, since the bulk of research on cold exposure and breathwork has examined acute physiological responses or momentary mood shifts in single sessions.

The investigators distributed surveys before and after the festival and received 85 responses in total. Of these, 19 participants, or 22 percent, provided complete paired data from both time points, forming the analytical sample. The primary outcome was trait anxiety, measured with the State-Trait Anxiety Inventory’s trait subscale, a widely used instrument that assesses the tendency to experience anxiety as a relatively stable characteristic. The researchers also tracked resilience and cognitive emotion regulation, expecting that these psychological resources might shift alongside anxiety, though that is not what the data ultimately showed.

The headline finding was a statistically significant drop in trait anxiety scores. Before the festival, participants averaged 42.6 points with a standard deviation of 7.8; afterward, the average fell to 39.8 with a standard deviation of 8.3, a reduction of 6.6 percent. The mean difference was 2.79 points, with a 95 percent confidence interval ranging from 0.91 to 4.67. A Wilcoxon signed-rank test, appropriate for non-normally distributed paired data, yielded a p-value of .002, and the standardized effect size, Hedges’ g, came out at 0.68 with a confidence interval of 0.19 to 1.16, which by conventional benchmarks represents a moderate-to-large effect. Importantly, 16 of the 19 participants showed reduced or stable scores, suggesting the change was not driven by a handful of dramatic responders.

What makes this result conceptually interesting is the target of the measurement. Trait anxiety has traditionally been treated as a fixed disposition, something stable across situations and resistant to brief interventions. The authors instead interpret the STAI-Trait score as a marker of negative affectivity, a vulnerability to experiencing negative emotions that may be more malleable than the label trait implies. Viewed through this lens, a multi-day immersive experience combining physiological stressors with communal practices could plausibly shift this vulnerability in the short term, even if longer-lasting change remains an open question that the study was not designed to answer.

The physiological rationale for such an effect is grounded in plausible mechanisms, even though the study did not measure them directly. Cold-water immersion triggers a robust stress response, acutely elevating catecholamines and activating the sympathetic nervous system, and repeated controlled exposure has been hypothesized to improve top-down regulation of autonomic arousal. Deliberate breathwork practices, particularly those involving slow or patterned breathing, are associated with increased vagal tone and reduced subjective tension, while some intense hyperventilation-based protocols produce transient states of altered arousal that participants often describe as cathartic. Group movement and shared physical challenge add further layers, including social bonding, collective efficacy and the mood effects of sustained outdoor activity. A festival format stacks all of these elements together, which makes it impossible to isolate which ingredient, or which combination, produced the observed change.

Indeed, the authors are explicit that the study is exploratory and that no causal claims can be made. The design lacked a control group, so regression to the mean, expectancy effects, the simple passage of time, or the general experience of attending a restorative social event could all account for part of the improvement. The completion rate was low, with only 22 percent of respondents providing paired data, and the sample was small and self-selected, composed of people motivated enough to attend a cold-exposure festival and diligent enough to complete both surveys. Such participants may differ systematically from the general population in baseline anxiety, openness to experience and enthusiasm for the practices involved, all of which limit generalizability.

Two secondary findings add nuance to the picture. First, satisfaction with the festival was uniformly high, indicating strong acceptability of the format; this matters for any future intervention research, since adherence and enjoyment are prerequisites for scaling such programs. Second, and perhaps more surprising, neither resilience nor cognitive emotion regulation changed from before to after the event. If the anxiety reduction had been driven by a genuine strengthening of coping resources, one might expect these measures to move in parallel. Their stability suggests instead that the effect may be closer to an acute reduction in negative affective vulnerability, a temporary recalibration of emotional baseline, rather than a durable upgrade in psychological skills. The authors themselves characterize the finding as preliminary evidence that the festival format is associated with an acute reduction in negative affective vulnerability alongside high acceptability.

The study was conducted within the CNRS Collab Inspire research collaboration agreement between CNRS UMR 6590 ESO and Inspire Potential, with Mathilde Plard serving as scientific lead, and Berglund’s doctoral research is supported by the Horizon Europe Breath program. The protocol received approval from the Ethics Committee for Research of Nantes Université, and the study was performed in accordance with the Declaration of Helsinki. Participation was voluntary and anonymous, with responses linked only by a self-chosen four-digit code, and participants could withdraw at any time without consequence. The sponsors had no role in data collection, analysis or manuscript preparation, and the authors declare no competing interests.

For the growing audience drawn to breathwork circles, ice baths and cold-water plunges, the study offers a cautiously encouraging signal rather than a prescription. It suggests that a multi-day, community-based format combining these practices is safe enough, enjoyable enough and potentially effective enough to justify more rigorous investigation, ideally with randomized or matched control conditions, larger samples, longer follow-up periods and physiological monitoring to identify mechanisms. Until such trials arrive, the Festival du Froid data stand as an intriguing naturalistic data point: a modest but consistent drop in anxiety vulnerability among ordinary people who spent three days breathing, moving and shivering together in the French outdoors, and a reminder that some of the most popular wellness practices of the moment are only now beginning to meet the standards of careful psychological science.

Subject of Research: Psychological effects of a multiday breathwork and cold-water immersion festival on trait anxiety

Article Title: A multiday outdoor festival combining breathwork and cold water immersion is associated with reduced trait anxiety in a naturalistic pre-post study

Article References: Berglund, C., Hallez, Q., Deschamps, T., & Plard, M. (2026). A multiday outdoor festival combining breathwork and cold water immersion is associated with reduced trait anxiety in a naturalistic pre-post study. Discover Psychology. https://doi.org/10.1007/s44202-026-00914-1

Image Credits: AI Generated

DOI: 10.1007/s44202-026-00914-1

Keywords: breathwork, cold-water immersion, trait anxiety, negative affectivity, naturalistic pre-post study, festival, mental health, emotion regulation, resilience, well-being, stress response, Discover Psychology

The study was conducted by Omar Afeef Wattad of Assuta Medical Centers and the Emergency Department of Hillel Yaffe Medical Center, together with Merav Ben Natan of Tel Aviv University and the Hillel Yaffe Academic School of Nursing. Between May 2023 and May 2024, the researchers surveyed 300 registered nurses employed at a tertiary medical center in Israel, a country where the health system maintains a high state of alert for emergencies ranging from armed conflict to natural disasters. Participants completed validated self-report questionnaires measuring disaster preparedness, psychological disaster preparedness, the organizational work environment, resilience, optimism, and trait anxiety.

A central conceptual contribution of the work is the distinction it draws between two related but separate constructs. Operational disaster preparedness refers to the practical readiness to perform during an emergency: knowing the protocols, having the technical skills, and being able to function within a coordinated response. Psychological disaster preparedness, by contrast, captures the mental and emotional readiness to face a catastrophic event, including the ability to tolerate stress, anticipate one’s own emotional reactions, and remain psychologically stable under extreme pressure. The researchers found that the two dimensions were moderately correlated, with a correlation coefficient of 0.56, statistically significant at p less than 0.001. In plain terms, a nurse who feels operationally ready is somewhat more likely to feel psychologically ready, but knowing the drill does not guarantee emotional readiness, and vice versa.

To understand what drives each dimension, the team used descriptive statistics, correlation analyses, and multiple regression models that allowed them to isolate the independent contribution of each variable while controlling for the others. The results were striking. The full model predicting operational disaster preparedness explained 45.4 percent of the variance, a substantial share for a behavioral outcome in a real-world clinical population. Within that model, several factors emerged as positive independent correlates: workplace disaster training, optimism, lower trait anxiety, participation in organizational decision-making, adequate staffing and resources, good collegial nurse-physician relations, and completion of an advanced nursing course.

The picture for psychological preparedness was markedly different. The full model for that outcome explained 45.1 percent of the variance, almost identical in strength, but the predictor pattern diverged in important ways. Age, ward experience, resilience, staffing and resource adequacy, positive nurse-nurse interaction, and male gender were all positive independent correlates of psychological readiness. Most notably, workplace disaster training, which strongly boosted operational preparedness, was a negative correlate of psychological preparedness, and higher trait anxiety also predicted lower psychological readiness. In other words, the very training programs that make nurses technically proficient may, in some circumstances, leave them feeling less emotionally equipped, perhaps by heightening awareness of how overwhelming a real disaster could be.

These findings carry significant implications for how hospitals prepare their nursing workforce. For decades, disaster preparedness programs have concentrated on drills, protocols, and technical competencies, treating readiness as a matter of knowledge and skill. The new data suggest this approach captures only half the picture. A nurse can complete every training module and still feel psychologically unprepared to face mass casualties, and the regression results indicate that psychological readiness depends more on accumulated clinical experience, personal resilience, and the quality of daily working relationships than on formal instruction alone.

The organizational findings are equally consequential. Staffing and resource adequacy appeared as a positive independent correlate of both operational and psychological preparedness, making it the one organizational factor that bridges the two dimensions. This suggests that nurses who feel their ward has enough staff and adequate resources are not only better positioned to execute emergency procedures but also more confident in their own emotional capacity to cope. Participation in decision-making and collegial nurse-physician relations contributed to operational readiness, while nurse-nurse interaction contributed to psychological readiness, indicating that different facets of the professional practice environment matter for different aspects of preparedness.

The psychological variables tell a coherent story of their own. Optimism and lower trait anxiety both independently predicted stronger operational preparedness, while resilience was the standout psychological predictor of psychological preparedness. Trait anxiety, a stable disposition toward experiencing worry and tension, was associated with lower scores on both outcomes, and it appeared as a negative correlate of psychological preparedness even after adjustment. This pattern implies that anxiety management deserves a place alongside clinical skills in disaster education, and that interventions designed to build resilience could pay dividends in nurses’ emotional readiness for catastrophic events.

The demographic findings add further nuance. Older nurses and those with more ward experience reported greater psychological preparedness, consistent with the idea that emotional readiness for disaster is cultivated over time through repeated exposure to demanding clinical situations. The association between male gender and higher psychological preparedness was an independent correlate in the adjusted model, a finding the authors report without overinterpreting. Completion of an advanced nursing course, meanwhile, strengthened operational preparedness specifically, reinforcing the value of continuing professional education for technical readiness.

Taken together, the study argues that nurses’ disaster preparedness is fundamentally multidimensional, reflecting both the resources the organization provides and the psychological capacity each nurse brings to the ward. The authors conclude that interventions should combine adequate staffing and collaborative practice environments with disaster training that explicitly addresses psychological responses, resilience, and anxiety management. As health systems worldwide confront an era of pandemics, climate-driven disasters, and geopolitical instability, the message for hospital leaders is clear: building a genuinely prepared nursing workforce means investing not only in drills and protocols but in the daily working conditions and inner psychological resources that determine whether nurses believe, deep down, that they can face the worst.

Subject of Research: Predictors of operational and psychological disaster preparedness among hospital nurses in Israel

Article Title: An integrated predictive model of nurses’ disaster preparedness: the joint role of organizational resources and psychological capacity

Article References: Wattad, O. A., & Natan, M. B. (2026). An integrated predictive model of nurses’ disaster preparedness: the joint role of organizational resources and psychological capacity. BMC Nursing. https://doi.org/10.1186/s12912-026-05264-w

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05264-w

Keywords: disaster preparedness, nurses, psychological preparedness, organizational work environment, resilience, trait anxiety, optimism, hospital staffing, emergency response, BMC Nursing, cross-sectional study, Israel

Trait anxiety, distinct from state anxiety, represents a relatively stable predisposition toward perceiving situations as threatening. It manifests cognitively and behaviorally, with sufferers often demonstrating heightened sensitivity not only to specific threats but also to stimuli bearing resemblance to learned fears. This can result in a maladaptive spread of anxiety responses—a phenomenon referred to as generalisation—that complicates clinical treatment and daily functioning. The precise cognitive mechanisms driving this expansive generalisation, however, have remained elusive until now.

The current study employs sophisticated experimental paradigms and neurocomputational modeling to dissect how aversive value—a negative emotional charge acquired through learning—transfers from known threatening stimuli to novel, yet similar, non-threatening cues. By applying rigorous psychophysiological measurements alongside behavioral assays, the researchers quantify the extent and specificity of value transfer that underpins anxiety generalisation in individuals exhibiting high levels of trait anxiety.

One groundbreaking aspect of this research is its focus on aversive value transfer as a dynamic process rather than a static phenomenon. The investigators demonstrate that aversive value is not confined to a singular stimulus but can spread through an associative network, effectively amplifying the perception of threat beyond the original learned context. This diffusion leads to an overgeneralised fear response, explaining why anxious individuals frequently respond with alarm to innocuous or ambiguous environments.

The research methodology incorporates a series of carefully controlled conditioning procedures, where participants learn to associate specific neutral stimuli with an aversive outcome, such as an unpleasant sound or mild electric shock. Subsequent testing phases reveal that those with elevated trait anxiety levels display a generalized aversive response to perceptually similar stimuli—far beyond the conditioned cues. This empirical evidence supports the hypothesis that increased generalisation in anxiety stems from heightened sensitivity to aversive value transfer.

Neuroimaging data provided in the study highlight alterations in the amygdala, hippocampus, and prefrontal cortex circuits, which are critical regions involved in emotional regulation, memory encoding, and fear extinction. The authors propose that dysregulation within these interconnected networks facilitates the maladaptive transfer of aversive value, thus reinforcing the persistent overgeneralisation seen in trait anxiety. This aligns with prior neurobiological models but adds an essential clarification regarding the mechanism of value transfer as the causal factor.

Importantly, their findings differentiate trait anxiety-driven generalisation from state-induced transient fear responses, with the former exhibiting more durable and resistant patterns of fear spread. This distinction is clinically significant, suggesting that interventions need to specifically target the processes regulating aversive value transfer, not merely acute anxiety symptoms. Cognitive-behavioral strategies and novel neuromodulatory techniques could be refined to disrupt this generalized fear network, thereby improving treatment efficacy for chronic anxiety disorders.

The implications extend to understanding comorbid conditions where anxiety and heightened generalisation play a critical role, such as post-traumatic stress disorder (PTSD), obsessive-compulsive disorder (OCD), and generalized anxiety disorder (GAD). By elucidating the cognitive and neurobiological pathways involved, the study opens avenues for precision medicine approaches tailored to individual anxiety profiles based on their generalisation tendencies and aversive learning patterns.

Moreover, this research resonates beyond clinical populations, offering insights into everyday cognitive biases and decision-making processes. The propensity to overgeneralise negative experiences may contribute to maladaptive social interactions, risk assessment errors, and chronic stress susceptibility, underscoring the broad importance of understanding aversive value transfer mechanisms in general population psychology.

The reported data also call attention to the developmental trajectories of anxiety generalisation. The authors speculate that early life stressors and temperament variations could modulate the sensitivity of neural systems to aversive learning, potentially heightening risk for adult trait anxiety manifestation. This perspective advocates for early identification and preventive strategies that focus on modifying aversive value learning curves during critical neurodevelopmental windows.

Furthermore, the study sets a precedent for integrating computational models of learning with empirical psychological research. By mapping aversive value transfer onto formal computational frameworks, the investigators enhance interpretability and reproducibility while generating predictive models that may guide future experimental designs and therapeutic testing.

The authors acknowledge certain limitations, including the need for longitudinal data to establish causal sequences definitively, and the challenge of translating laboratory findings into real-world clinical practice. Nonetheless, the robust multidisciplinary approach they adopt—combining behavioral science, neuroimaging, computational modeling, and clinical psychology—makes this study a compelling contribution to anxiety research.

In conclusion, the pioneering work by Verra, Spitzer, Schuck, and colleagues offers a comprehensive analysis of the mechanisms by which trait anxiety fosters increased generalisation through aversive value transfer. This critical advance elucidates how negative emotional valence spreads across associative networks, aggravating anxiety symptoms and complicating treatment outcomes. Future research inspired by these findings promises to refine therapeutic interventions and enhance quality of life for millions affected by chronic anxiety disorders worldwide.

As science continues to probe the intricate architecture of the anxious mind, this research exemplifies how conceptual clarity regarding fundamental cognitive processes can spur innovation and deepen our grasp of pervasive mental health challenges. The identification of aversive value transfer as a key driver of anxiety generalisation marks a milestone in psychological science, with profound implications for both understanding and healing the anxious brain.

Subject of Research: Cognitive and neurobiological mechanisms underlying increased generalisation in trait anxiety, focusing on aversive value transfer.

Article Title: Increased generalisation in trait anxiety is driven by aversive value transfer.

Article References:
Verra, L., Spitzer, B., Schuck, N.W. et al. Increased generalisation in trait anxiety is driven by aversive value transfer. Commun Psychol (2026). https://doi.org/10.1038/s44271-026-00415-w

Image Credits: AI Generated