The study, conducted by Aekyoung Kim of Jeonbuk University, Juliano Laran of Schema Behavioral Science, Omar Bastaki of the United Arab Emirates University, and Kristina M. Durante of Rutgers Business School, builds on a long tradition in psychology that treats stress as a multidimensional experience. Rather than asking simply whether stress is good or bad for consumers, the researchers isolated the perception of low control, the sense that events are unfolding beyond one’s influence. This component, they hypothesized, triggers a compensatory process: when people feel their control slipping, they seek out opportunities to reassert it, and the marketplace offers one surprisingly effective arena for doing so.

The theoretical foundation for this idea comes from decades of work on compensatory control. Classic research has shown that when people feel deprived of control, they respond in predictable ways: they perceive illusory patterns in random noise, gravitate toward hierarchical social structures, and even develop superstitious brand preferences. What the new research adds is a novel pathway for control restoration. Instead of reaching for structure in the environment, people may increase their engagement with it, processing information more deeply, attending more carefully, and investing more cognitive effort precisely because doing so feels like taking charge.

Across multiple studies, participants exposed to stress-inducing situations showed heightened engagement in several distinct domains. They were more willing to view advertisements, they spent more time examining the ads they did see, and they performed better on product attention tasks. These are not trivial outcomes for anyone who studies advertising. Engagement is widely regarded as a gateway variable in marketing: it predicts how well messages are encoded, how memorable brands become, and how persuasive content ultimately is. A state that reliably increases engagement therefore has consequences that ripple through the entire chain of consumer response.

The mechanism matters as much as the effect. The researchers found that the boost in engagement emerged specifically as a means of restoring a sense of control. In other words, stressed participants were not simply more aroused or more alert in a generic way; their heightened attention functioned as a control-restoration strategy. This distinction was confirmed by the boundary conditions of the effect, which are among the most technically interesting parts of the findings.

Two conditions weakened or eliminated the positive effect of stress on engagement. The first was direct address: when people could deal with the stressor itself, they no longer needed engagement as a compensatory tool, and the boost disappeared. If the source of the stress can be handled head-on, attention need not be redirected toward the marketplace as a substitute arena for control. The second condition was futility: when people believed that their control-restoration efforts would fail, the effect also weakened. Engagement, it seems, is not a reflexive response to low control but a motivated one, contingent on the expectation that investing effort can actually accomplish something.

This pattern aligns with a broader literature on stress and cognition that has often emphasized the negative side of the ledger. Acute stressors reliably elevate cortisol, and stress-level cortisol has been shown to enhance memory for emotional material while impairing delayed recall. Stress and time pressure degrade judgment and decision making, and cognitive load manipulations reduce consumers’ ability to perceive product value. Against this backdrop, the new findings do not contradict the stress-as-impairment view so much as complicate it. Stress is not a single lever; it is a bundle of components, and different components pull behavior in different directions. By decomposing stress and isolating the low-control element, the researchers demonstrate that the same physiological state that impairs some cognitive functions can sharpen others.

The work also connects to prior research by some of the same authors on how stress shapes consumer saving and spending, and to a growing body of evidence that low control drives preferences for high-effort products and services. Taken together, these findings sketch a coherent picture: control deprivation motivates effortful behavior across the consumer landscape, from choosing effortful products to engaging deeply with marketing messages. Engagement, in this framing, becomes a novel and previously underappreciated route through which people attempt to restore their sense of agency.

The practical implications are considerable, and the authors are candid about them. Marketers who understand that stress-induced engagement exists can strategically time and design their communications. Advertising encountered during stressful periods, a delayed flight, a tense news cycle, a demanding workday, may receive more attention than the same advertising encountered in calm conditions, provided the consumer cannot directly resolve the stressor and believes engagement is worthwhile. Public health communicators could exploit the same dynamics, since messages that demand attention, such as responsible drinking campaigns, may land harder with stressed audiences. At the same time, the boundary conditions serve as a caution: engagement gains evaporate when people can address the stressor or expect their efforts to be futile, so timing and framing are not optional details but essential design parameters.

There is also a consumer-protection reading of the research. If stress reliably increases engagement with commercial content, then periods of high stress are precisely when people are most cognitively available to marketers, a fact that raises questions about targeting practices during crises, elections, and economic downturns. The authors note that their findings contribute to the literature on stress, engagement, and personal control by showing that stress can have a positive effect on behavior, and by identifying increased engagement as a new way to restore control. Whether that restored control benefits the consumer, the marketer, or both depends on what is being engaged with. What the research makes clear is that the relationship between stress and attention is not a simple story of overload and distraction. Under the right conditions, the feeling of losing control sends people searching for it, and the screen in front of them is one of the places they look.

Subject of Research: The role of perceived low control in stress-induced increases in consumer engagement

Article Title: An examination of the role of stress in increasing engagement

Article References: Kim, A., Laran, J., Bastaki, O., & Durante, K. M. (2026). An examination of the role of stress in increasing engagement. Current Psychology, 45(18), Article 1501. https://doi.org/10.1007/s12144-026-10061-4

Image Credits: AI Generated

DOI: 10.1007/s12144-026-10061-4

Keywords: stress, consumer engagement, perceived control, advertising attention, compensatory control, cortisol, consumer behavior, marketing psychology, control restoration, cognitive effort, Current Psychology, boundary conditions

The study begins from a puzzle that has long divided the literature on anxiety and effort. Cognitively demanding tasks are widely understood to be perceived as costly, and this sense of cost can lead to effort avoidance, particularly in populations whose motivation is impaired. When researchers have examined where anxiety fits into this picture, however, the results have refused to line up neatly. Some studies suggest that anxiety raises the subjective price of mental effort, making people more likely to disengage. Others indicate that anxiety can actually motivate engagement, sharpening focus or driving people to invest more when the stakes feel high. Both patterns have empirical support, which means something important must be missing from the way the field has framed the question.

Sayalı and her colleagues proposed that the missing ingredient is the interaction between two different kinds of anxiety. State anxiety refers to the transient, situational feeling of tension and apprehension that rises and falls with circumstances. Trait anxiety, by contrast, describes a stable disposition to experience such states frequently and intensely. The team hypothesized that state anxiety would enhance task engagement as task difficulty increased, and that this effect would diminish in people with higher trait anxiety. In other words, a jolt of situational anxiety might push people to try harder on harder tasks, but only up to a point, and the strength of that push would depend on the anxious disposition a person brings to the laboratory with them.

To test this, the researchers ran two online experiments with independent samples. In both, they assessed participants’ self-reported anxiety and manipulated their affective state experimentally, allowing them to examine how induced changes in anxious mood altered engagement with tasks of varying difficulty. The design is notable for its scale and its ecological reach: rather than bringing volunteers into a physical laboratory, the team collected data online, which permitted a much larger second sample and a more diverse participant pool than many effort-based decision studies typically achieve.

The results of the first experiment, conducted with 107 participants, came as a surprise. Contrary to the hypothesis, participants with low trait anxiety reported reduced task engagement when they were under high state anxiety, but this effect appeared only for easy tasks. When the tasks were easy, a spike in situational anxiety seemed to push low-trait-anxious individuals away from the task, prompting disengagement precisely where the effort required was smallest. Meanwhile, this pattern was attenuated in participants with higher trait anxiety, whose engagement was less sensitive to the state anxiety manipulation. The predicted interaction between state and trait anxiety was there, but its direction and its boundary conditions were not what the team expected.

Experiment 2, with a substantially larger sample of 572 participants, put the finding to a replication test. The key interaction partially replicated: the negative effect of state anxiety on engagement was again attenuated in individuals with higher trait anxiety. But there was an important difference in scope. In the second experiment, the negative effect of state anxiety on engagement was observed across all task difficulty levels rather than being restricted to easy tasks. The core signature held, namely that higher trait anxiety blunted the impact of state anxiety on disengagement, yet the first experiment’s restriction of the effect to easy tasks did not generalize to the larger sample.

What does it mean that trait anxiety appears to buffer, or at least dampen, the disengaging effect of state anxiety? The authors draw a provocative conclusion from their data: trait anxiety may reflect a reduced impact of state anxiety on disengagement. On this reading, people high in trait anxiety are not simply people who experience more anxious states; they are people whose engagement with cognitive work is less perturbed by those states when they arise. Someone who lives with a chronically anxious disposition may have, in effect, a decoupling between the transient feeling of anxiety and the motivational machinery that decides whether a task is worth continuing. For low-trait individuals, by contrast, a surge of state anxiety arrives as an unfamiliar signal that can knock them off even a lightly demanding task.

This framing helps explain why the earlier literature seemed contradictory. Studies that measured only state anxiety, or only trait anxiety, or that examined tasks of a single difficulty level, would each capture a different slice of what is fundamentally an interactive system. A study of anxious states in a low-trait sample might find that anxiety increases effort cost and promotes avoidance. A study in a high-trait sample might find that anxiety motivates engagement, because the state manipulation simply has less traction on disengagement in those individuals. Task difficulty adds a further layer, with the first experiment suggesting the disengagement effect may be most visible when the task demands little and the perceived cost-benefit balance is otherwise favorable.

The work also speaks to a broader theoretical conversation about cognitive effort as something the brain evaluates like a cost, weighing the demands of a task against its value. Effort avoidance is a well-documented phenomenon, and it is often amplified in populations with motivational impairments. Anxiety has been a candidate modulator of this cost calculus, but the present findings suggest it cannot be treated as a single dial. The same anxious state can carry different motivational meaning depending on the dispositional context in which it occurs, and the same trait disposition can alter how strongly moment-to-moment mood steers behavior. Any model of effort-based decision making that treats anxiety as a unitary input is likely to be incomplete.

There are, of course, limits to what these two experiments can establish. The manipulations were delivered online, the engagement measures were self-reported, and the partial replication indicates that some details of the phenomenon, such as the role of task difficulty, remain unsettled. The authors are transparent that their hypothesis was not confirmed as stated, and the divergence between the two experiments on the difficulty question is itself informative, showing that the easy-task specificity seen in the smaller sample was not robust. Still, the consistency of the trait anxiety attenuation across both samples gives the central finding considerable weight, and the large second sample lends confidence that the interaction is not a statistical fluke.

The implications reach beyond the laboratory. If momentary anxiety differentially disrupts engagement depending on a person’s trait anxiety, then interventions aimed at keeping anxious people on task may need to be tailored to disposition rather than applied uniformly. Educational settings, workplaces, and clinical contexts all involve cognitively demanding work performed under emotionally loaded conditions, and the assumption that anxiety always undermines effort may lead well-intentioned support strategies astray for some individuals. For the researchers themselves, the study is a reminder of why hypothesis-driven science matters even when the hypothesis fails: the team predicted an interaction, found one with a different shape, and in doing so uncovered a candidate redefinition of trait anxiety, not as the tendency to feel anxious more often, but as the tendency for those feelings to matter less when it comes time to decide whether to keep working.

Subject of Research: The interaction between state and trait anxiety in cognitive effort evaluation and task engagement

Article Title: Anxiety state-related task disengagement varies with trait anxiety

Article References: Sayalı, C., Heling, E., & Cools, R. (2026). Anxiety state-related task disengagement varies with trait anxiety. Communications Psychology. https://doi.org/10.1038/s44271-026-00545-1

Image Credits: AI Generated

DOI: 10.1038/s44271-026-00545-1

Keywords: anxiety, trait anxiety, state anxiety, cognitive effort, task engagement, effort avoidance, motivation, cognitive control, psychology, decision making, affective state, task difficulty

Planning is one of the most computationally demanding things the human mind does. To decide on a course of action, people must mentally simulate future states of the world, evaluate the consequences of each possible move, and compare the expected values of different sequences of choices. In a perfectly predictable environment, this simulation can be carried out with confidence: if you take action A, outcome B will follow. But the real world is stochastic. Outcomes are corrupted by noise, the rules governing them shift over time, and sometimes our own actions fail to produce the effects we intend. Each of these forms of randomness, the authors note, makes exact planning exponentially harder, because the decision-maker must average over many possible futures rather than tracing a single one. The theoretical optimal solution to such problems quickly becomes intractable, which raises a fundamental question that has lingered in cognitive science: how do people balance the cognitive cost of planning against its potential benefits when the environment is uncertain?

To answer this question, the team designed a laboratory planning task in which participants encountered one of three distinct forms of stochasticity that are commonly found in real-world environments. The first was reliability, meaning the degree to which outcomes consistently reflect the underlying value of an action. The second was volatility, meaning the rate at which the environment’s structure changes over time. The third was controllability, meaning the extent to which a person’s own actions reliably determine what happens next. These three manipulations capture, in simplified form, the kinds of unpredictability people face when navigating unreliable transportation systems, volatile financial markets, or social situations where other people’s behavior only partially responds to our own. By varying each form of stochasticity independently, the researchers could ask whether different types of randomness affect planning in different ways, or whether the brain responds to all of them with a common strategy.

The central behavioral measure was deceptively simple: the time participants took to make their first choice in each planning episode. First-choice response times are widely used as a proxy for planning depth, because a longer deliberation typically reflects more mental simulation of future possibilities. Across all three manipulations, the researchers found a robust and consistent pattern. As stochasticity increased, people reduced their planning effort, as indexed by faster first-choice response times. In other words, whether the randomness came from unreliable outcomes, a shifting environment, or diminished control over events, the response was the same: participants spent less time deliberating. This consistency across three conceptually distinct sources of uncertainty is one of the study’s most important contributions, suggesting that the brain may treat different forms of environmental randomness through a common computational lens when deciding how much to think.

To understand what was happening inside the mind during these decisions, the team went beyond response times and built a family of computational cognitive models designed to account for participants’ choices. This modeling approach is a hallmark of the Ma laboratory’s work on resource-rational cognition, the idea that the brain optimizes not for perfect performance but for the best performance achievable given limited time, energy, and neural machinery. The models allowed the researchers to distinguish between competing hypotheses about how people cope with stochasticity. One possibility is that people perform something close to the correct calculation, computing expected values by averaging over possible outcomes weighted by their probabilities. Another possibility is that people adopt a much simpler strategy, one that sacrifices accuracy in exchange for a dramatic reduction in mental effort.

The modeling results pointed decisively toward the simpler strategy. Rather than calculating expected values optimally, people behaved as if the world were deterministic, a phenomenon the authors call determinizing. Under this scheme, the planner ignores the probability distribution over outcomes and plans as though each action leads to a single, certain result. Determinizing is computationally cheap: it converts a difficult problem of averaging over many futures into an easy problem of following one imagined path. The cost, of course, is accuracy, because in a genuinely stochastic world the single imagined path will sometimes be wrong. But the benefit is a substantial saving of cognitive effort, and the study suggests that when randomness rises, the brain judges that saving to be worth the loss in precision. This finding connects to a broader theme in recent cognitive science, in which people construct simplified mental representations to make planning tractable, rather than brute-forcing optimal solutions their neural hardware cannot afford.

Within this determinizing framework, the researchers identified a second, subtler signature of reduced effort. As stochasticity increased, people decreased their sensitivity to values, a pattern the authors describe as policy compression. In a fully sensitive policy, small differences in the value of different options translate into large differences in choice behavior, reflecting careful, fine-grained evaluation. When sensitivity to values decreases, choices become less discriminating, as though the planner is working from a coarser, more compressed summary of the decision landscape. Policy compression is a form of lossy compression of a behavioral policy: the brain retains the broad shape of what is worth doing but discards the fine distinctions that would require more computation to resolve. Consistent with the response time findings, this compression deepened as environmental randomness grew, providing converging evidence at both the level of deliberation time and the level of choice structure that planning effort was being actively withdrawn.

The study also carries a methodological warning for the field. The authors emphasize that their results reveal the limitations of studying stochasticity solely through single-shot decisions, the brief one-off gambles that dominate much of the decision-making literature. In a single-shot choice, the computational burden of planning is minimal, and the effects of stochasticity on effort may be invisible. It is only in tasks that require genuine multi-step planning, where the decision-maker must simulate sequences of future actions, that the withdrawal of effort under uncertainty becomes measurable. This suggests that conclusions about how humans handle uncertainty drawn from simple gambling paradigms may not generalize to the richer, sequential decisions that fill everyday life, from choosing a commute route to planning a career move. The planning task developed here offers a template for probing those richer decisions under controlled variation in environmental structure.

The broader implications of the work extend beyond the laboratory. If people systematically reduce planning effort as their environments become less reliable, more volatile, or less controllable, then the cognitive consequences of living in unstable conditions may be more nuanced than commonly assumed. It is tempting to interpret poor planning under uncertainty as a failure of attention or motivation, but this study reframes it as a potentially rational allocation of a scarce cognitive resource: when the expected payoff of careful planning falls because randomness will erode the value of any plan anyway, the brain sensibly stops paying for it. At the same time, the finding raises questions about contexts where reduced deliberation is harmful, such as volatile but high-stakes environments where careful planning remains valuable despite the noise. Understanding when determinizing serves us well and when it leads us astray is a natural next step. The research was funded by the National Science Foundation and the National Institutes of Health, and the authors acknowledge guidance from Marcelo Mattar, Todd Gureckis, and Cristina Savin. As stochasticity shapes everything from economic turbulence to climate variability, this work highlights an often overlooked truth: the mind’s response to an unpredictable world is not to think harder, but to think less.

Subject of Research: How environmental stochasticity affects human planning effort and strategy

Article Title: Environmental stochasticity reduces human planning effort

Article References: Lei, J., Olieslagers, J., Arfaei, N., Lin, D. X., & Ma, W. J. (2026). Environmental stochasticity reduces human planning effort. Nature Communications. https://doi.org/10.1038/s41467-026-78023-9

Image Credits: AI Generated

DOI: 10.1038/s41467-026-78023-9

Keywords: planning, stochasticity, decision-making, cognitive effort, determinizing, policy compression, computational modeling, response times, uncertainty, Nature Communications, resource rationality, human behavior

Temporal interference, first demonstrated in animal models by researchers at Imperial College London, is a fundamentally different approach from conventional transcranial stimulation. Traditional non-invasive methods such as transcranial direct current stimulation or repetitive transcranial magnetic stimulation are limited in how deeply they can reach, because electrical currents applied at the scalp spread broadly and lose focus as they penetrate the brain. Temporal interference gets around this problem with an elegant piece of biophysics. Two kilohertz-frequency electrical fields are applied from electrodes on the scalp, each at a slightly different frequency, for example two thousand hertz and two thousand and ten hertz. Neither frequency on its own is capable of driving neurons to fire, because high-frequency fields oscillate too quickly for neural membranes to follow. But where the two fields overlap inside the brain, their sum produces a beat pattern, an envelope that rises and falls at the small frequency difference between them. It is this slow modulation, delivered at a frequency the brain can respond to, that modulates neuronal activity.

The critical advantage is spatial control. By adjusting the positions and intensities of the scalp electrodes, researchers steer the interference envelope to a chosen target deep within the brain, while regions that receive only one of the two high-frequency fields remain largely unaffected. The technique has been used in animal studies to activate structures such as the hippocampus without overlying cortex involvement, and more recently in human proof-of-concept work targeting the striatum and other subcortical nuclei. The new findings in Translational Psychiatry bring this targeting capability to bear on one of the most consequential circuits in behavioral economics and psychiatry: the network that assigns value to effort.

The theoretical framework behind the study draws on the effort-based decision-making literature, which models motivation as the outcome of comparing expected reward with expected effort cost. In humans and animals alike, choices between a high-reward, high-effort option and a low-reward, low-effort alternative reveal a stable preference structure, and deviations from that structure are a hallmark of several clinical conditions. Apathy in depression, Parkinson’s disease, and schizophrenia can be understood partly as an overestimation of effort costs, while impulsivity and mania may reflect an underestimation. If the neural machinery that computes effort cost could be nudged in either direction, clinicians would gain a tool not just for measuring motivational dysfunction but for treating it.

Using computational modeling of temporal interference fields, the researchers targeted stimulation toward striatal and frontal regions implicated in effort valuation. The striatum, densely innervated by dopaminergic projections from the ventral tegmental area and substantia nigra, is a central hub in the brain’s reward and motivational circuitry. Phasic dopamine signals track the anticipated value of actions, and tonic dopamine levels appear to shape how much effort an organism is willing to expend per unit of reward. Pharmacological studies in both animals and humans have shown that increasing dopaminergic tone biases choice toward high-effort, high-reward options, whereas dopamine depletion produces the opposite shift, a pattern famously demonstrated in rodent work by Michael Treadway and colleagues at Vanderbilt University. The question the new study posed was whether non-invasive electromagnetic stimulation could produce comparable shifts without drugs or surgery.

The experimental logic followed established paradigms from behavioral economics. Participants performed tasks in which they chose between options differing in the mental effort required and the reward offered. Cognitive effort was manipulated through tasks such as the n-back paradigm, in which participants monitor a stream of stimuli and must remember items from one, two, or three steps back, with the load and thus the effort rising steeply with each increment. By plotting the trade-off point at which a participant finds a higher reward worth the extra cognitive burden, researchers derive an individual measure of effort discounting, the rate at which subjective value declines as required effort climbs. This measure served as the behavioral readout of motivation before, during, and after stimulation.

The results indicate that temporal interference stimulation, applied to the targeted deep circuitry, measurably altered participants’ willingness to invest mental work. Where the stimulation increased activity in effort-valuation circuitry, participants showed a greater tolerance for demanding cognitive tasks, accepting harder options for comparable reward. Conversely, the study examined whether the direction of change depended on stimulation parameters and target placement, consistent with the emerging view that motivation is not a single dial but a distributed computation that can be modulated at multiple nodes. Importantly, the high-frequency carrier fields used in temporal interference are perceptually subtle, and participants were largely unable to distinguish active from control stimulation, a feature that strengthens the double-blind design and reduces placebo confounds that have plagued conventional stimulation research.

The implications extend well beyond the laboratory. Effort-related motivational deficits are among the most disabling and least treatable features of psychiatric illness. Patients with major depression frequently describe that even trivial tasks feel impossibly heavy, a symptom that standard antidepressants addressing mood and anhedonia often leave untouched. Apathy in Parkinson’s disease and in dementia caregivers’ charges erodes quality of life and accelerates functional decline. If deep targeted stimulation can recalibrate the effort-cost calculation, it offers a mechanistically grounded intervention for these conditions, one that could in principle be titrated like any other dose-adjustable therapy. The technique also opens a window onto basic science questions that pharmacology cannot answer with precision: which nodes of the motivational network causally contribute to effort discounting, and how quickly can the computation be shifted?

Significant caveats remain, and the authors and the field are careful to name them. Individual anatomy varies, and steering an interference envelope accurately to a few millimeters of deep tissue in a given person requires individualized modeling based on magnetic resonance imaging. The long-term safety of repeated kilohertz-frequency stimulation is not yet established, and the behavioral effects demonstrated so far are acute and modest in magnitude. Effort-based choices are also shaped by sleep, mood, medication, and learned history, so stimulation is one lever among many rather than a complete account of motivation. Nevertheless, the convergence of field steering physics, computational modeling, and rigorous behavioral economics in a single translational study marks a step change in what non-invasive neuromodulation can claim to do. A technique that began as a demonstration in laboratory animals has now reached the point of altering a fundamental human motivation, the appetite for mental work itself, and with it, the prospect of new therapies for the millions whose capacity to engage with effortful life has been diminished by illness.

Subject of Research: Using temporal interference brain stimulation to alter the motivation for mental effort

Article Title: Changing the motivation for mental work with temporal interference stimulation

Article References: Vural, G., Drexler, S., Keeser, D., & Soutschek, A. (2026). Changing the motivation for mental work with temporal interference stimulation. Translational Psychiatry, 16(1), Article 477. https://doi.org/10.1038/s41398-026-04449-w

Image Credits: AI Generated

DOI: 10.1038/s41398-026-04449-w

Keywords: temporal interference stimulation, mental effort, motivation, cognitive effort, non-invasive brain stimulation, deep brain circuits, effort-based decision making, dopamine, translational psychiatry, neuromodulation, cost-benefit, behavioral neuroscience