Pilot turning behavior cognitive load analysis in simulated flight.

Background: To identify the cognitive load of different turning tasks in simulated flight, a flight experiment was designed based on real "preliminary screening" training modules for pilots. Methods: Heart Rate Variability (HRV) and flight data were collected during the experiments using a flight simulator and a heart rate sensor bracelet. The turning behaviors in flight were classified into climbing turns, descending turns, and level flight turns. A recognition model for the cognitive load associated with these turning behaviors was developed using machine learning and deep learning algorithms. Results: pnni_20, range_nni, rmssd, sdsd, nni_20, sd1, triangular_index indicators are negatively correlated with different turning load. The LSTM-Attention model excelled in recognizing turning tasks with varying cognitive load, achieving an F1 score of 0.9491. Conclusion: Specific HRV characteristics can be used to analyze cognitive load in different turn-ing tasks, and the LSTM-Attention model can provide references for future studies on the selection characteristics of pilot cognitive load, and offer guidance for pilot training, thus having significant implications for pilot training and flight safety.

Example-based learning in heuristic domains: can using relevant content knowledge support the effective allocation of intrinsic, extraneous, and germane cognitive load?

Introduction: Worked examples support initial skill acquisition. They often show skill application on content knowledge from another, "exemplifying" domain (e.g., argumentation skills have to be applied to some contents). Although learners' focus should remain on the skill, learners need to understand the content knowledge to benefit from worked examples. Previous studies relied on exemplifying domains that are familiar and contain simple topics, to keep learners' focus on skill acquisition. Aim: We examined whether using a relevant exemplifying domain would allow learners to acquire both skills and content knowledge simultaneously, or whether relevant content distracts from the main learning goal of skill acquisition. Methods and results: In a training study with 142 psychology students, we used example-based learning materials with an exemplifying domain that was either relevant or irrelevant for participants' course outcomes. We assessed cognitive load, declarative knowledge about skills and course-related content knowledge, and argumentation quality. Incorporating relevant content knowledge in worked examples did not reduce learning outcomes compared to a condition using an irrelevant exemplifying domain. Discussion: Contrary to previous research, the results suggest that worked examples with a relevant exemplifying domain could possibly be an efficient teaching method for fostering skills and content knowledge simultaneously.

Which ERP components are effective in measuring cognitive load in multimedia learning? A meta-analysis based on relevant studies.

The open and generative nature of multimedia learning environments tends to cause cognitive overload in learners, and cognitive load is difficult for researchers to observe objectively because of its implicit and complex nature. Event-related potentials (ERP), a method of studying potential changes associated with specific events or stimuli by recording the electroencephalogram (EEG), has become an important method of measuring cognitive load in cognitive psychology. Although many studies have relied on ERP output measurements to compare different levels of cognitive load in multimedia learning, the results of the effect of cognitive load on ERP have been inconsistent. In this study, we used a meta-analysis of evidence-based research to quantitatively analyze 17 experimental studies to quantitatively evaluate which ERP component (amplitude) is most sensitive to cognitive load. Forty five effect sizes from 26 studies involving 360 participants were calculated. (1) The results of the studies analyzed in subgroups indicated high level effect sizes for P300 and P200 (2) Analyses of moderating variables for signal acquisition did not find that different methods of signal acquisition had a significant effect on the measurement of cognitive load (3) Analyses of moderating variables for task design found that a task system with feedback was more convenient for the measurement of cognitive load, and that designing for 3 levels of cognitive load was more convenient for the measurement of cognitive load than for 2 levels of cognitive load. (4) Analyses of continuous moderating variables for subject characteristics did not find significant effects of age, gender, or sample size on the results.

Electromyographically controlled prosthetic wrist improves dexterity and reduces compensatory movements without added cognitive load.

Wrist function is a top priority for transradial amputees. However, the combined functional, biomechanical, and cognitive impact of using a powered prosthetic wrist is unclear. Here, we quantify task performance, compensatory movements, and cognitive load while three transradial amputees performed a modified Clothespin Relocation Task using two myoelectric prostheses with and without the wrists. The two myoelectric prostheses include a commercial prosthesis with a built-in powered wrist, and a newly developed inexpensive prosthetic wrist for research purposes, called the "Utah wrist", that can be adapted to work with various sockets and prostheses. For these three participants, task failure rate decreased significantly from 66% ± 12% without the wrist to 39% ± 9% with the Utah wrist. Compensatory forward leaning movements also decreased significantly, from 24.2° ± 2.5 without the wrist to 12.6° ± 1.0 with the Utah wrist, and from 23.6° ± 7.6 to 15.3° ± 7.2 with the commercial prosthesis with an integrated wrist. Compensatory leftward bending movements also significantly decreased, from 20.8° ± 8.6 to 12.3° ± 5.3, for the commercial with an integrated wrist. Importantly, simultaneous myoelectric control of either prosthetic wrist had no significant impact on cognitive load, as assessed by the NASA Task Load Index survey and a secondary detection response task. This work suggests that functional prosthetic wrists can improve dexterity and reduce compensation without significantly increasing cognitive effort. These results, and the introduction of a new inexpensive prosthetic wrist for research purposes, can aid future research and development and guide the prescription of upper-limb prostheses.

EEG ß oscillations in aberrant data perception under cognitive load modulation.

Data-driven decision making (DDDM) is becoming an indispensable component of work across various fields, and the perception of aberrant data (PAD) has emerged as an essential skill. Nonetheless, the neural processing mechanisms underpinning PAD remain incompletely elucidated. Direct evidence linking neural oscillations to PAD is currently lacking, and the impact of cognitive load remains ambiguous. We address this issue using EEG time-frequency analysis. Data were collected from 21 healthy participants. The experiment employed a 2 (low vs. high cognitive load) × 2 [PAD+ (aberrant data accurately identified as aberrant) vs. PAD- (non-aberrant data correctly recognized as normal)] within-subject laboratory design. Results indicate that upper ß band oscillations (26-30 Hz) were significantly enhanced in the PAD + condition compared to PAD-, with consistent activity observed in the frontal (p < 0.001, [Formula: see text] = 0.41) and parietal lobes (p = 0.028, [Formula: see text] = 0.22) within the 300-350 ms time window. Additionally, as cognitive load increased, the time window of ß oscillations for distinguishing PAD+ from PAD- shifted earlier. This study enriches our understanding of the PAD neural basis by exploring the distribution of neural oscillation frequencies, decision-making neural circuits, and the windowing effect induced by cognitive load. These findings have significant implications for elucidating the pathological mechanisms of neurodegenerative disorders, as well as in the initial screening, intervention, and treatment of diseases.

The effects of different interruption conditions on mental workload: an experimental study based on multimodal measurements.

Interruptions in the working environment cause extra mental workload for the operators, and this phenomenon has garnered significant research attention. This study designed four interruption conditions based on the perceptual and cognitive perspectives of human information processing, using a 2(perceptual primary task and cognitive primary task)*2(perceptual interruption task and cognitive interruption task) factorial design. Multimodal measurement methods were used to evaluate mental workload in different interruption conditions. The results show that when the primary task and the interruption task are different load types, they generate a higher mental workload than the same load type. It can be attributed to the fact that perceptual tasks and cognitive tasks increase mental workload during switching. In addition, based on the multimodal index data, the prediction model of interruption recovery delay time and the classification model of interruption conditions are established, which provides a basis for rational scheduling of work and preventing mental overload.

This study's results enhance our understanding of interruptions from the perspectives of perception and cognition, providing a more accurate theoretical basis for managing mental workload in interruption conditions. The proposed interruption recovery delay time prediction model and the interruption condition classification model have certain reference values for improving interruption management capabilities.

Understanding, fast and shallow: Individual differences in memory performance associated with cognitive load predict the illusion of explanatory depth.

People are often overconfident about their ability to explain how everyday phenomena and artifacts work (devices, natural processes, historical events, etc.). However, the metacognitive mechanisms involved in this bias have not been fully elucidated. The aim of this study was to establish whether the ability to perform deliberate and analytic processes moderates the effect of informational cues such as the social desirability of knowledge on the Illusion of Explanatory Depth (IOED). To this purpose, the participants' cognitive load was manipulated as they provided initial estimates of causal understanding of national historical events in the standard IOED paradigm. The results showed that neither the social desirability of specific causal knowledge nor the cognitive load manipulations had direct effects on the IOED. However, subsequent exploratory analyses indicated that high cognitive load was related to lower performance on concurrent memory tasks, which in turn was associated with a higher IOED magnitude. Higher analytical processing was also related to lower IOED. Implications for both dual-process models of metacognition and the design of task environments that help to reduce this bias are discussed.

Unanticipated evolution of cardio-respiratory interactions with cognitive load during a Go-NoGo shooting task in virtual reality.

The cardiovascular system interacts continuously with the respiratory system to maintain the vital balance of oxygen and carbon dioxide in our body. The interplay between the sympathetic and parasympathetic branches of the autonomic nervous system regulates the aforesaid involuntary functions. This study analyzes the dynamics of the cardio-respiratory (CR) interactions using RR Intervals (RRI), Systolic Blood Pressure (SBP), and Respiration signals after first-order differencing to make them stationary. It investigates their variation with cognitive load induced by a virtual reality (VR) based Go-NoGo shooting task with low and high levels of task difficulty. We use Pearson's correlation-based linear and mutual information-based nonlinear measures of association to indicate the reduction in RRI-SBP and RRI-Respiration interactions with cognitive load. However, no linear correlation difference was observed in SBP-Respiration interactions with cognitive load, but their mutual information increased. A couple of open-loop autoregressive models with exogenous input (ARX) are estimated using RRI and SBP, and one closed-loop ARX model is estimated using RRI, SBP, and Respiration. The impulse responses (IRs) are derived for each input-output pair, and a reduction in the positive and negative peak amplitude of all the IRs is observed with cognitive load. Some novel parameters are derived by representing the IR as a double exponential curve with cosine modulation and show significant differences with cognitive load compared to other measures, especially for the IR between SBP and Respiration.

Pupillometry and autonomic nervous system responses to cognitive load and false feedback: an unsupervised machine learning approach.

Objectives: Pupil dilation is controlled both by sympathetic and parasympathetic nervous system branches. We hypothesized that the dynamic of pupil size changes under cognitive load with additional false feedback can predict individual behavior along with heart rate variability (HRV) patterns and eye movements reflecting specific adaptability to cognitive stress. To test this, we employed an unsupervised machine learning approach to recognize groups of individuals distinguished by pupil dilation dynamics and then compared their autonomic nervous system (ANS) responses along with time, performance, and self-esteem indicators in cognitive tasks. Methods: Cohort of 70 participants were exposed to tasks with increasing cognitive load and deception, with measurements of pupillary dynamics, HRV, eye movements, and cognitive performance and behavioral data. Utilizing machine learning k-means clustering algorithm, pupillometry data were segmented to distinct responses to increasing cognitive load and deceit. Further analysis compared clusters, focusing on how physiological (HRV, eye movements) and cognitive metrics (time, mistakes, self-esteem) varied across two clusters of different pupillary response patterns, investigating the relationship between pupil dynamics and autonomic reactions. Results: Cluster analysis of pupillometry data identified two distinct groups with statistically significant varying physiological and behavioral responses. Cluster 0 showed elevated HRV, alongside larger initial pupil sizes. Cluster 1 participants presented lower HRV but demonstrated increased and pronounced oculomotor activity. Behavioral differences included reporting more errors and lower self-esteem in Cluster 0, and faster response times with more precise reactions to deception demonstrated by Cluster 1. Lifestyle variations such as smoking habits and differences in Epworth Sleepiness Scale scores were significant between the clusters. Conclusion: The differentiation in pupillary dynamics and related metrics between the clusters underlines the complex interplay between autonomic regulation, cognitive load, and behavioral responses to cognitive load and deceptive feedback. These findings underscore the potential of pupillometry combined with machine learning in identifying individual differences in stress resilience and cognitive performance. Our research on pupillary dynamics and ANS patterns can lead to the development of remote diagnostic tools for real-time cognitive stress monitoring and performance optimization, applicable in clinical, educational, and occupational settings.

Unveiling nuances in data analysis to illuminate marine pilot strain.

Maritime studies, encompassing a range of disciplines, increasingly rely on advanced data analytics, particularly in the context of navigation. As technology advances, the statistical averaging of large datasets has become a critical component of these analyses. However, recent studies have highlighted discrepancies between statistical predictions and observable realities, especially in high-stress environments like port approach procedures conducted by marine pilots. This study analyzed physiological responses recorded during simulation exercises involving experienced marine pilots. The focus was not on the specific outcomes of the simulations but on the potential faults arising from conventional statistical signal processing, particularly mean-centered approaches. A large dataset of signals was generated, including one signal with a dominant characteristic intentionally designed to introduce imbalance, mimicking the uneven distribution of real-world data. Initial analysis suggested that the average physiological response of the pilots followed an S-shaped curve, indicative of a psycho-physiological reaction to stress. However, further post hoc analysis revealed that this pattern was primarily influenced by a single participant's data. This finding raises concerns about the generalizability of the S-curve as a typical stress response in maritime pilots. The results underscore the limitations of relying solely on conventional statistical methods, such as mean-centered approaches, in interpreting complex datasets. The study calls into question the validity of standardizing data interpretations based on dominant characteristic curves, particularly in environments as intricate as maritime navigation. The research highlights the need for a re-evaluation of these methods to ensure more reliable and nuanced conclusions in maritime studies. This study contributes to the ongoing discourse on data interpretation in maritime research, emphasizing the critical need to re-assess conventional statistical signal processing techniques. By recognizing the potential pitfalls in data generalization, the study advocates for more robust analytical approaches to better capture the complexities of real-world maritime challenges.

Cognitive load during driving: EEG microstate metrics are sensitive to task difficulty and predict safety outcomes.

Engaging in phone conversations or other cognitively challenging tasks while driving detrimentally impacts cognitive functions and has been associated with increased risk of accidents. Existing EEG methods have been shown to differentiate between load and no load, but not between different levels of cognitive load. Furthermore, it has not been investigated whether EEG measurements of load can be used to predict safety outcomes in critical events. EEG microstates analysis, categorizing EEG signals into a concise set of prototypical functional states, has been used in other task contexts with good results, but has not been applied in the driving context. Here, this gap is addressed by means of a driving simulation experiment. Three phone use conditions (no phone use, hands-free, and handheld), combined with two task difficulty levels (single- or double-digit addition and subtraction), were tested before and during a rear-end collision conflict. Both conventional EEG spectral power and EEG microstates were analyzed. The results showed that different levels of cognitive load influenced EEG microstates differently, while EEG spectral power remained unaffected. A distinct EEG pattern emerged when drivers engaged in phone tasks while driving, characterized by a simultaneous increase and decrease in two of the EEG microstates, suggesting a heightened focus on auditory information, potentially at a cost to attention reorientation ability. The increase and decrease in these two microstates follow a monotonic sequence from baseline to hands-free simple, hands-free complex, handheld simple, and finally handheld complex, showing sensitivity to task difficulty. This pattern was found both before and after the lead vehicle braked. Furthermore, EEG microstates prior to the lead vehicle braking improved predictions of safety outcomes in terms of minimum time headway after the lead vehicle braked, clearly suggesting that these microstates measure brain states which are indicative of impaired driving. Additionally, EEG microstates are more predictive of safety outcomes than task difficulty, highlighting individual differences in task effects. These findings enhance our understanding of the neural dynamics involved in distracted driving and can be used in methods for evaluating the cognitive load induced by in-vehicle systems.

Augmented reality visualization for ultrasound-guided interventions: a pilot randomized crossover trial to assess trainee performance and cognitive load.

BACKGROUND: Augmented reality (AR) technology involving head-mounted displays (HMD) represents a significant innovation in medical education, particularly for training in guided invasive procedures. Novice physicians often face challenges in simultaneously identifying anatomical landmarks and performing procedures when learning point-of-care ultrasound (POCUS). Our primary objective was to determine the effectiveness of AR in enhancing physician training for ultrasound-guided interventions using AR visual overlays. The secondary objective was to compare cognitive load between traditional ultrasound training settings and AR-assisted training settings. METHODS: This randomized crossover study, conducted from 2021 to 2022, compared performance and cognitive load of trainees attempting accurate central venous catheter (CVC) placement using an AR-HMD to display ultrasound images (AR-US), compared with standard ultrasound without visual overlay (S-US). We enrolled 47 trainees, including 22 final-year undergraduate medical students and 25 postgraduate physicians (years 1-4) from three hospitals in Taiwan. All participants had basic training in US-guided CVC placement but lacked AR-US experience. Performance and cognitive load were assessed using time measurements and NASA Task Load Index (NASA-TLX), covering the dimensions of Mental-, Physical- and Temporal Demand, and Performance, Effort and Frustration. RESULTS: We found AR technology reduced the time required for critical steps in CVC placement, while minimizing users' neck strain. Female and junior trainees using AR-US identified anatomy and localized veins faster than those using S-US. Using AR-US, female trainees significantly outperformed males in anatomical identification [mean difference (MD): -10.79 s (95% CI: -2.37 to -19.21)]. The NASA-TLX cognitive load assessment showed mental workload trending lower in all dimensions except performance while using AR-US, compared to S-US. Similarly, junior trainees' effort- and frustration scores were lower [MD: -2.73 (95% CI: -5.04 to -0.41) and -2.41 (95% CI: -4.51 to -0.31), respectively], as were female trainees' effort scores [MD: -3.07 (95% CI: -6.10 to -0.03)] when using AR-US, compared to S-US, whereby these differences were statistically significant. CONCLUSIONS: AR technology helped improve trainee performance and reduced cognitive load during ultrasound-guided CVC placement. These findings support the application of AR technology to enhance physician training in ultrasound-guided interventional procedures, suggesting that AR-HMDs could be a valuable tool in medical education. TRIAL REGISTRATION: The trial was registered with Clinicaltrials.gov on 20/09/2023 as a clinical trial, under the identifier NCT06055400.

Music Listening as Exploratory Behavior: From Dispositional Reactions to Epistemic Interactions with the Sonic World.

Listening to music can span a continuum from passive consumption to active exploration, relying on processes of coping with the sounds as well as higher-level processes of sense-making. Revolving around the major questions of "what" and "how" to explore, this paper takes a naturalistic stance toward music listening, providing tools to objectively describe the underlying mechanisms of musical sense-making by weakening the distinction between music and non-music. Starting from a non-exclusionary conception of "coping" with the sounds, it stresses the exploratory approach of treating music as a sound environment to be discovered by an attentive listener. Exploratory listening, in this view, is an open-minded and active process, not dependent on simply recalling pre-existing knowledge or information that reduces cognitive processing efforts but having a high cognitive load due to the need for highly focused attention and perceptual readiness. Music, explored in this way, is valued for its complexity, surprisingness, novelty, incongruity, puzzlingness, and patterns, relying on processes of selection, differentiation, discrimination, and identification.

How is social dominance related to our short-term memory? An EEG/ERP investigation of encoding and retrieval during a working memory task.

Social hierarchies exist in all societies and impact cognitive functions, brain mechanisms, social interactions, and behaviors. High status individuals often exhibit enhanced working memory (WM) performance compared to lower status individuals. This study examined whether individual differences in social dominance, as a predictor of future status, relate to WM abilities. Five hundred and twenty-five students completed the Personality Research Form dominance subscale questionnaire. From this sample, students with the highest and lowest scores were invited to participate in the study. Sixty-four participants volunteered to take part and were subsequently categorized into high- and low-dominance groups based on their dominance subscale questionnaire (PRF_d) scores. They performed a Sternberg WM task with set sizes of 1, 4, or 7 letters while their EEG was recorded. Event-related potential (ERP) and power spectral analysis revealed significantly reduced P3b amplitude and higher event-related synchronization (ERS) of theta and beta during encoding and retrieval phases in the high-than low-dominance group. Despite these neural processing differences, behavioral performance was equivalent between groups, potentially reflecting comparable cognitive load demands of the task across dominance levels. Further, there were similar P3b patterns for each set-size within groups. These findings provide initial evidence that individual differences in social dominance trait correlate with WM functioning, as indexed by neural processing efficiency during WM performance.

Application of cognitive load theory in reading English academic articles on medical education among Chinese undergraduate medical students.

Reading English academic articles is the cornerstone of innovative medical education and scientific research. However, limited by both language and professional knowledge, many nonnative English-speaking undergraduate medical students have a fear of reading English academic articles. The purpose of this study was to explore whether cognitive load theory can be a useful guiding strategy to promote English medical education article reading among Chinese undergraduates, while also evaluating students' attitudes toward the reading activities and cognitive load entailed in the last article they read. In the reading activities, students needed to read 19 English academic articles that are closely related to their courses. A questionnaire was administered after the students finished reading the 19th article to determine their attitudes toward reading English medical education articles and the cognitive load involved in reading the 19th article. The results showed that students' overall perceptions of reading English medical education articles were positive. Most students felt that their ability to read English academic articles and related skills had improved. The mean scores for students' intrinsic and germane cognitive loads in reading the 19th article were 6.44 ± 1.81 and 6.92 ± 2.05, respectively. The mean score for the extraneous cognitive load was 2.31 ± 2.63. In conclusion, the cognitive load theory can serve as the basis for an effective strategy to guide English medical education article reading activities among undergraduates in China. Meanwhile, students' attitudes toward the reading activities were favorable, and they read the latest article within an acceptable cognitive load.NEW & NOTEWORTHY Many nonnative English-speaking undergraduates have a fear of reading English academic articles. This study was performed to explore whether cognitive load theory can be a useful guiding strategy to promote English article reading among Chinese medical undergraduates. The results showed that cognitive load theory can serve as the basis for an effective strategy to guide English medical education article reading activities among undergraduates in China, and students' attitudes toward the reading activities were favorable.

Error monitoring under working memory load: An electrocortical investigation.

Error monitoring is essential for detecting errors and may facilitate behavioral adjustments that can reduce or prevent future errors. At times, error monitoring must occur while individuals are engaged in other, cognitively demanding tasks that might consume processing resources necessary for error monitoring. Here, we set out to determine whether concurrent working memory (WM) load interferes with error monitoring, as measured using event-related potentials, the error-related negativity (Ne/ERN), and error positivity (Pe). Fifty-four participants (n = 33 female) completed an arrowhead flanker task, with trials presented under low (2 letter) or high (6 letter) WM load. Participants were required to hold letter strings in memory and to recall these letters at the end of a set of flanker trials. Results showed that WM load reduced the Pe but did not affect the Ne/ERN. Therefore, WM load appeared to attenuate later, more elaborated stages of error processing, though initial error detection was unaffected. Additionally, high WM load slowed reaction times overall, but did not lead to a significant increase in errors. As such, slower responses may have helped participants maintain comparable accuracy for low-load versus high-load trials. Overall, results indicate that WM load interferes with the evaluation of error significance, which could interfere with behavioral adaptations over time.

Effects of adaptive scaffolding on performance, cognitive load and engagement in game-based learning: a randomized controlled trial.

BACKGROUND: While game-based learning has demonstrated positive outcomes for some learners, its efficacy remains variable. Adaptive scaffolding may improve performance and self-regulation during training by optimizing cognitive load. Informed by cognitive load theory, this study investigates whether adaptive scaffolding based on interaction trace data influences learning performance, self-regulation, cognitive load, test performance, and engagement in a medical emergency game. METHODS: Sixty-two medical students from three Dutch universities played six game scenarios. They received either adaptive or nonadaptive scaffolding in a randomized double-blinded matched pairs yoked control design. During gameplay, we measured learning performance (accuracy, speed, systematicity), self-regulation (self-monitoring, help-seeking), and cognitive load. Test performance was assessed in a live scenario assessment at 2- and 6-12-week intervals. Engagement was measured after completing all game scenarios. RESULTS: Surprisingly, the results unveiled no discernible differences between the groups experiencing adaptive and nonadaptive scaffolding. This finding is attributed to the unexpected alignment between the nonadaptive scaffolding and the needs of the participants in 64.9% of the scenarios, resulting in coincidentally tailored scaffolding. Exploratory analyses suggest that, compared to nontailored scaffolding, tailored scaffolding improved speed, reduced self-regulation, and lowered cognitive load. No differences in test performance or engagement were found. DISCUSSION: Our results suggest adaptive scaffolding may enhance learning by optimizing cognitive load. These findings underscore the potential of adaptive scaffolding within GBL environments, cultivating a more tailored and effective learning experience. To leverage this potential effectively, researchers, educators, and developers are recommended to collaborate from the outset of designing adaptive GBL or computer-based simulation experiences. This collaborative approach facilitates the establishment of reliable performance indicators and enables the design of suitable, preferably real-time, scaffolding interventions. Future research should confirm the effects of adaptive scaffolding on self-regulation and learning, taking care to avoid unintended tailored scaffolding in the research design. TRIAL REGISTRATION: This study was preregistered with the Center for Open Science prior to data collection. The registry may be found at https://osf.io/7ztws/ .

Taste or health: The impact of packaging cues on consumer decision-making in healthy foods.

According to the theory of dietary regulation, consumers frequently encounter conflicts between healthiness and tastiness when selecting healthy foods. This study explores how packaging cue that highlight "tasty" versus "healthy" affect consumers' intentions to purchase healthy food. After an Implicit Association Test (IAT) confirmed a perceived lack of tastiness in health foods in the Preliminary study, Study 1 analyzed pricing and packaging details of the top 200 most-popular items in each of the ten healthy food categories on a major online shopping platform. Results showed that products with taste-focused cues commanded higher prices, indicating stronger consumer acceptance of healthy foods marketed as delicious. To address the causality limitations of observational studies, Study 2 used an experimental design to directly measure the impact of these cues on purchase intentions and perceptions of energy, healthiness, and tastiness. Findings revealed that taste-focused cues significantly boosted purchase intentions compared to health-focused cues, although they also diminished the perceived healthiness of the products. Moreover, in the control group exposed to unhealthy food options, health-emphasized packaging also increased purchase intentions, indicating that consumers seek a balance between healthiness and tastiness, rather than prioritizing health alone. Study 3 further explored the impact of cognitive load over these cue influences, revealing a heightened inclination among consumers to purchase healthy products with taste-focused cue under high cognitive load state. These insights have direct implications for food packaging design, suggesting that emphasizing a balance of taste and health benefits can effectively enhance consumer engagement. The study, which conducted in China, also opens avenues for future research to explore similar effects, maybe in different cultural contexts, different consumer groups, and under varied cognitive conditions.

Gaze cueing improves pattern recognition of histology learners.

Experts perceive and evaluate domain-specific visual information with high accuracy. In doing so, they exhibit eye movements referred to as "expert gaze" to rapidly focus on task-relevant areas. Using eye tracking, it is possible to record these implicit gaze patterns and present them to histology novice learners during training. This article presents a comprehensive evaluation of such expert gaze cueing on pattern recognition of medical students in histology. For this purpose, 53 students were randomized into two groups over eight histology sessions. The control group was presented with an instructional histology video featuring voice commentary. The gaze cueing group was presented the same video, but with an additional overlay of a live recording of the expert's eye movements. Afterward, students' pattern recognition was assessed through 20 image-based tasks (5 retention, 15 transfer) and their cognitive load with the Paas scale. Results showed that gaze cueing significantly outperformed the control group (p = 0.007; d = 0.40). This effect was evident for both, retention (p = 0.003) and transfer tasks (p = 0.046), and generalized across different histological contexts. The cognitive load was similar in both groups. In conclusion, gaze cueing helps histology novice learners to develop their pattern recognition skills, offering a promising method for histology education. Histology educators could benefit from this instructional strategy to provide new forms of attentional guidance to learners in visually complex learning environments.