Communications Psychology最新文献

Light exposure can modulate cognitive function, yet its effects outside of controlled laboratory settings remain insufficiently explored. To examine the relationship between real-world light exposure and cognitive performance, we assessed personal light exposure and measured subjective sleepiness, vigilance, working memory, and visual search performance over 7 days of daily life, in a convenience sample of UK adults (n = 58) without significant circadian challenge (shiftwork or jet-lag). A subset of participants (n = 41) attended an in-lab session comprising a battery of pupillometric and psychophysical tests aimed to quantify melanopsin-driven visual responses. We find significant associations between recent light exposure and subjective sleepiness. Recent light exposure was also associated with reaction times for both psychomotor vigilance and working memory tasks. In addition, higher daytime light exposure and an exposure pattern with reduced fragmentation were linked to improved cognitive performance across visual search, psychomotor vigilance, and working memory tasks. Higher daytime light exposure and earlier estimated bedtimes were associated with stronger relationships between recent light exposure and subjective sleepiness. These results provide real world support for the notion that intra- and inter-individual differences in light exposure meaningfully influence aspects of cognition, with beneficial effects of short-term bright light and of habitual light exposure patterns characterized by brighter daytimes, earlier rest phase, and greater intra- and inter-daily stability.

The pleasurable urge to move to music, termed "groove," is thought to arise from the tension between top-down metric expectations or predictions and rhythmic complexity. Specifically, groove ratings are highest for moderately complex rhythms, balancing expectation and surprise. To test this, meter and rhythmic complexity need to be manipulated independently to assess their impact on groove. Thus, we compared Western listeners' ratings for musical clips of varying rhythmic complexity composed in either the most common Western meter (4/4) or less common meters (e.g., 7/8). In several behavioral studies (Experiment 1, N = 143; Experiment 2, N = 120; Experiment 3, N = 120), we used Bayesian regression to show that groove is greatest for moderately complex rhythms, but only in 4/4. In non-4/4 meters, simpler rhythms elicited the greatest groove. This provides support for the theory that bottom-up rhythmic features interact with meter in a way that shapes the pleasurable urge to move to music.

Understanding how individuals perceive and recall information in their natural environments is critical to understanding potential failures in perception (e.g., sensory loss) and memory (e.g., dementia). Event segmentation, the process of identifying distinct events within dynamic environments, is central to how we perceive, encode, and recall experiences. This cognitive process not only influences moment-to-moment comprehension but also shapes event specific memory. Despite the importance of event segmentation and event memory, current research methodologies rely heavily on human judgements for assessing segmentation patterns and recall ability, which are subjective and time-consuming. A few approaches have been introduced to automate event segmentation and recall scoring, but validity with human responses and ease of implementation require further advancements. To address these concerns, we leverage Large Language Models (LLMs) to automate event segmentation and assess recall of written narratives, employing chat completion and text-embedding models, respectively. We validated these models against human annotations and determined that LLMs can accurately identify event boundaries, and that human event segmentation is more consistent with LLMs than among humans themselves. Using this framework, we advanced an automated approach for recall assessments which revealed semantic similarity between segmented narrative events and participant recall can estimate recall performance. Our findings demonstrate that LLMs can effectively simulate human segmentation patterns and provide recall evaluations that are a scalable alternative to manual scoring. This research opens avenues for studying the intersection between perception, memory, and cognitive impairment using methodologies driven by artificial intelligence.

Sensorimotor processing in the human brain is largely lateralized, with the corpus callosum integrating these processes into a unified experience. Following complete callosotomy, this integration breaks down, resulting in disconnection syndromes. We asked how much of the corpus callosum is sufficient to support functional unity-the absence of disconnection syndrome-by comparing three complete callosotomy patients with one retaining only the splenium. Using lateralized tasks across visual, tactile, visuospatial, and language domains, we predicted domain-specific deficits in the splenium-only patient based on established anatomical models of callosal topography. Strikingly, while complete callosotomy patients exhibited disconnection syndromes, the splenium patient demonstrated functional unity across all domains-as if his entire corpus callosum were intact. Our findings highlight the brain's remarkable capacity to maintain behavioral integration through minimal preserved pathways, highlighting how the structure-dependent reorganizational capacity of the human brain may allow to preserve functional unity.

Many researchers and policymakers assume that interventions targeting trust in science will be key for promoting health-related behaviors, including in the context of curbing the spread of disease. One central finding from the past pandemic is that trust in science predicted health-related protection intentions and behaviors, such as social distancing and vaccination. Yet, it is unclear whether the observed correlation between trust in science and protection intentions does indeed imply causation. Across our studies (total N = 5311), we successfully replicated this correlation. However, when experimentally manipulating self-reported trust in science, we found no evidence for causal effects on protection intentions. This absence of meaningful effects was confirmed by equivalence tests, an internal meta-analysis (N = 3761), and a machine learning algorithm. These results question the causal importance of short-term changes in trust in science for protection intentions. Drawing the right lessons from the COVID-19 pandemic will be essential for effective future policy responses.

Older adults prioritize emotional well-being in their relationships, but communication of emotion may differ during in-person and phone contact. Older adults (N = 266, aged 65-90) completed ecological momentary assessments (EMA; n = 4,627) reporting their social encounters via different modes of social contact and positive and negative mood every 3 hours. Participants wore a device with the Electronically Activated Recorder (EAR) app which recorded 30 seconds every 7 minutes (n = 104,746 sound files). Linguistic Inquiry and Word Count (LIWC) extracted linguistic features reflecting verbal communication of emotion from the sound file transcriptions. Multilevel models revealed that in-person and phone contact were associated with communicating more positive emotions, and in-person contact was associated with communicating more negative emotions. There was no statistically significant evidence that the association between communicating positive emotions and more positive and less negative mood varied by form of communication. Participants who had less in-person contact on average experienced a greater increase in positive mood when they communicated positive emotions. This study emphasizes the emotional benefits of social contact, particularly for communicating positive feelings. Findings highlight the role of in-person contact in older adults' daily lives, allowing for the verbal communication of negative emotions.

Children incorporate items found in their environment into their play, transforming everyday objects and materials into an opportunity for exploration. Termed loose parts, these versatile, natural, or manufactured materials (e.g., cardboard, pipes, buttons, sticks) are widely recommended for supporting children's early STEM learning. Limited empirical work has documented children's indoor STEM behaviours with loose parts. Using a within-subjects experimental design, we examined children's early STEM behaviours and engagement (N = 60; 32 females, 28 males; Mage = 58.6 months, SD = 10.9) during unstructured solitary play with loose parts and toys that have limited function and affordance (e.g., toy percussion instruments; control). We conducted observations of children's STEM behaviours. Children's cognitive functioning, executive function, and home learning environment were also assessed via standardized measures and parent reports. Children demonstrated significantly more STEM behaviours with loose parts than in the control condition. There was no credible evidence that these behaviours differed by sex. Cognitive functioning predicted STEM Engagement Score with loose parts, with children's verbal comprehension being the strongest predictor in the control condition. Children's executive function and parents' attitudes regarding play and engagement in play activities at home predicted constructing structures, which were the most common STEM behaviours. This study thus demonstrates that loose parts may offer a powerful opportunity for STEM-related early learning; however, children's cognitive capacities and home experiences should be considered, rather than assuming uniform benefits.

Psychological variability is central to understanding behavioural interventions. Over the past 15 years, many behaviourally informed public policies have proven effective; however, they often yield highly heterogeneous outcomes, and the reasons for this variability remain unclear. We posit that these mixed results are due to researchers and policy makers designing interventions around behavioural strategies that perform well on average, overlooking how individuals differ in their responses. We review discoveries from the psychology of poverty to show how variations in traits such as conformism, present orientation, personal agency, and social vigilance correspond with levels of resource availability. We then demonstrate how these psychological differences systematically shape individual reactions to behavioural policy tools such as default options, self-regulation devices, information campaigns, social-belonging interventions, and social norms. Ultimately, we argue that an applied behavioural science of poverty is essential for crafting interventions that are both effective and equitable.

Acute stress triggers a cascade of physiological and psychological changes, including heightened perspiration, cortisol levels, and anxiety. Currently, little is known about the effects of acute stress on the quality of higher-order decision-making, with existing studies unable to disentangle decision-making capacity from subjective preferences. To address this gap, we conducted a within-participants laboratory experiment in which university students (n = 42) made objective decisions of varying complexity (computational hardness) under both acutely stressful and control conditions. We find that higher cortisol levels, induced via the Trier Social Stress Test, leads to lower decision quality and a higher incidence of experienced time pressure. Among cortisol responders, the deterioration in decision quality was independent of the level of computational hardness, whilst among the full sample it was concentrated among trials with higher levels of computational hardness. Post-hoc, we find that the most substantial deficits in decision quality occurred when acute stress was accompanied by time pressure, with gaze-tracking analyses offering tentative evidence that changes in attention allocation may be one mechanism for this effect. Our results demonstrate that acute stress impairs the capacity to decide correctly, and highlights the importance of computational hardness and time pressure as potential moderators of this effect.