Subjects: Psychology >> Cognitive Psychology Subjects: Psychology >> Physiological Psychology submitted time 2026-06-01
Abstract： Impaired inhibitory control is considered one of the core mechanisms underlying the progression of depression. Cognitive models of depression propose that deficits in inhibitory control weaken individuals’ ability to regulate emotional information, thereby sustaining negative affect and exacerbating depressive symptoms. However, because patients with depression exhibit both emotional disturbances and widespread cognitive impairments, explaining inhibitory control deficits solely from an emotion-processing perspective may not fully capture their role in the pathophysiology of depression. Therefore, it is necessary to systematically integrate existing evidence to determine whether inhibitory control impairments in depression are primarily emotion-specific or reflect a more generalized cognitive dysfunction, thereby clarifying the pathways through which inhibitory control contributes to the onset and maintenance of depression. The present study conducted a meta-analysis to synthesize neuroimaging findings from emotional and non-emotional inhibitory control tasks in patients with depression, aiming to identify the characteristics and neural mechanisms of inhibitory control deficits.
Specifically, this study conducted an Activation Likelihood Estimation (ALE) meta-analysis of task-related neural activation differences between patients with major depressive disorder (MDD) and healthy controls (HC) during emotional and non-emotional inhibitory control tasks. Following a systematic literature search and rigorous screening, 19 task-based fMRI studies were included, involving 393 individuals with MDD and reporting 133 activation foci. Based on task type (emotional vs. non-emotional) and the direction of activation difference(MDD > HC vs. MDD < HC), these foci were classified into four datasets: emotional–MDD > HC, emotional–MDD < HC, non-emotional–MDD > HC, and non-emotional–MDD < HC. All coordinates were transformed into Montreal Neurological Institute (MNI) space prior to analysis, with Talairach coordinates reported in the original studies converted to MNI coordinates using GingerALE 2.6.3. Single ALE analyses were performed for each dataset using an uncorrected threshold of p < 0.0001 and a minimum cluster size of 200 mm³. Because the non-emotional–MDD < HC and non-emotional–MDD > HC datasets showed no significant convergent activation, contrast analyses between emotional and non-emotional inhibitory control tasks could not be performed.
The results showed that, during emotional inhibitory control tasks, individuals with MDD exhibited compensatory hyperactivation in the right middle frontal gyrus(34, 38, 32), and decreased activation convergence in the left middle frontal gyrus(–36, 40, 16) and right inferior frontal gyrus(50, 14, 18) relative to HC. By contrast, no significant convergent activation was observed for non-emotional inhibitory control tasks.
This meta-analysis advances our understanding of the pathophysiology of depression by revealing the characteristics of inhibitory control deficits. The findings indicate that depression is characterized by altered recruitment of prefrontal regions during emotional inhibitory control, supporting the view that inhibitory control deficits in depression are closely linked to emotional processing dysfunction. These results highlight a potential pathway through which impaired inhibitory control may contribute to the persistence of depressive symptoms and may inform the development of targeted cognitive and neurobiological interventions.
Subjects: Psychology >> Educational Psychology submitted time 2026-05-31
Abstract： In online learning environments, danmaku (bullet-screen comments) have been increasingly adopted as an interactive teaching tool. However, the underlying mechanisms through which danmaku influences learning outcomes remain underexplored. Drawing on goal contagion theory, this study aimed to investigate effect of the danmaku on online learning engagement and its mechanism of action. Specifically, three progressive experiments were designed to examine whether danmaku containing learning goals, compared with non-learning goal danmaku, would induce higher goal activation, enhance emotional engagement and improve learning outcomes, and whether goal inference would serve as a mediator between danmaku type and learning outcomes. Additionally, the study aimed to rule out attentional distraction as an alternative explanation by using eye-tracking technology.
Three experiments were conducted sequentially. Experiment 1 adopted a between-subjects design, randomly assigning participants to either a learning goal danmaku condition or a non-learning goal danmaku condition. The dependent variable was goal activation level, measured immediately after exposure to the danmaku. Experiment 2 extended the investigation by including measures of emotional engagement and learning outcomes. Participants completed a post-test based on the video content to assess learning outcomes. The mediating role of goal inference—the extent to which viewers inferred the comment sender’s learning intention—was tested using a bootstrapping approach. Experiment 3 incorporated eye-tracking technology to record participants’ dwell time on two predefined areas of interest: the danmaku area and the content area. This allowed the study to directly test whether any observed effects could be attributed to differential allocation of visual attention rather than to goal contagion processes.
The results showed a consistent pattern across the three experiments. In Experiment 1, learning goal danmaku led to significantly higher levels of goal activation compared with non-learning goal danmaku. In Experiment 2, participants in the learning goal danmaku condition reported greater emotional engagement and achieved better learning outcomes on both retention and comprehension measures. Furthermore, goal inference fully mediated the relationship between danmaku type and learning outcomes, indicating that the positive effect of learning goal danmaku operated through the automatic inference of learning intentions. In Experiment 3, eye-tracking data revealed no significant difference between the two groups in dwell time on either the danmaku area or the content area. This finding suggests that the superior performance of the learning goal danmaku condition was not due to increased attention to the comments themselves or to reduced attention to the learning content. Rather, the effect persisted even after attentional distraction was ruled out as a confounding factor.
Taken together, these findings uncover a non-conscious processing pathway through which learning goal danmaku facilitates online learning performance. From the perspective of goal contagion theory, exposure to goal-relevant danmaku automatically activates learning goals in the observer, which in turn enhances emotional engagement and improves learning outcomes, without relying on deliberate attentional shifts. This study provides both theoretical and empirical support for optimizing danmaku functions in online education platforms.
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Social Psychology submitted time 2026-05-30
Abstract： Prosocial behavior often requires people to incur personal costs to benefit others. Although many studies have focused on the benefits received by others, the effects of self-incurred costs on prosocial behavior remain underexplored. The few studies that have examined self-costs have mainly focused on the trade-off between effort costs and monetary rewards, overlooking the broader neural dynamics through which effort shapes the valuation of benefits to others. Recently, we demonstrated an effort paradox mechanism, whereby effort exerted for oneself both prospectively discounts and retrospectively enhances reward value. We hypothesize that this two-stage relationship between effort and reward may constitute a novel mechanism underlying prosocial behavior. To test this hypothesis, we will combine behavioral experiments with EEG and fMRI to examine the neural dynamics that arise when individuals exert cognitive effort to earn rewards for themselves versus for others. We will further determine whether these neural dynamics are domain-general or domain-specific across different forms of effort and benefit. These findings will clarify the cognitive and neural mechanisms by which prosocial effort shapes reward processing, thereby addressing a key gap in current theories and offering a new perspective on how self-incurred costs and others' benefits are balanced, and on how prosocial behavior can be promoted.
Subjects: Psychology >> Management Psychology submitted time 2026-05-28
Abstract： Algorithmic management has become the primary management model for the gig economy and platform work. Its “rush-games-style” management traps gig workers in an intense and unstable work rhythm, which exacerbates the tension between work and family, and triggers the dilemma of blurring of the work-family interface for gig workers. How to balance work and family has become an important issue of common concern to both managers and gig workers. Based on the dual-process model and dissipative structure theory, this study constructs a moderated mediation model of the impact of algorithmic management on the work-family interface. Specifically, Study 1 relies on the dissipative structural characteristics of the human brain and constructs a linear impact model of algorithmic management on work-family facilitation from the perspective of System 1; Study 2 draws on the dissipative structural characteristics of the individual and constructs a nonlinear impact model of algorithmic management on work-family conflict from the perspective of System 2. The anticipated findings can provide an appropriate theoretical perspective for explaining the impact of algorithmic management on the work-family interface, and offer suggestions for improving gig platforms’ algorithmic management capabilities and helping gig workers better balance work and family relationships.
Subjects: Psychology >> Cognitive Psychology submitted time 2026-05-27
Abstract： Collaborative retrieval refers to the joint recovery of encoded information by two or more individuals through social interaction. Although this process typically yields collaborative inhibition relative to nominal groups, it concurrently generates a post-collaborative facilitation effect that enhances subsequent individual retention. While previous studies have highlighted encoding level as a crucial moderating factor, they have predominantly focused on group-level manipulations rather than on the effects of within-group encoding disparities. By incorporating functional near-infrared spectroscopy (fNIRS), this study investigated how such disparities influence inter-brain synchrony (IBS) and directional neural coupling, thereby revealing the leadership–followership dynamics and information transfer patterns during collaboration.
A total of 160 university students participated in a single-factor between-participants experiment. The study manipulated the encoding composition of dyads across three conditions: differential encoding (semantic + perceptual), homogeneous high-level encoding (semantic + semantic), and homogeneous low-level encoding (perceptual + perceptual), while matched nominal groups served as controls. The experimental stimuli comprised 32 neutral, low-frequency, two-character words balanced for grammatical category and structure. The procedure involved four phases: an encoding phase, distraction task, collaborative (or individual) retrieval phase, and secondary individual retrieval phase. During the collaborative retrieval phase, fNIRS hyperscanning was employed to record neural activity. This study primarily focused on the prefrontal cortex and right temporoparietal junction.
The behavioral results indicated that, compared with nominal groups, homogeneous dyads exhibited collaborative inhibition, whereas differential dyads (semantic + perceptual) effectively eliminated this inhibition and enhanced post-collaborative individual retrieval, particularly benefiting perceptual encoders. In terms of neural activity, the results showed that differential encoding strengthened IBS in the right middle frontal gyrus (BA10) and right angular gyrus (BA39), with this synchrony positively predicting post-collaborative retrieval accuracy. Granger causality results further revealed the directional characteristics of the IBS, demonstrating a significant information flow from semantic encoders to perceptual encoders in the differential condition. This suggests a leader–follower dynamic in which semantic encoders guided the retrieval process.
In summary, the present study demonstrated that differential encoding composition promotes deeper social interaction, effectively eliminating collaborative inhibition and fostering post-collaborative facilitation. Inter-brain synchrony serves as a critical neural mechanism underlying the establishment of a leader–follower dynamic, thereby facilitating the effective transfer of information from semantic to perceptual encoders. These results provide empirical support for the optimization of collaborative memory through within-group encoding disparities. This study offers a novel perspective on the role of encoding levels and contributes to a deeper understanding of complex social–cognitive processes from the perspective of interpersonal neuroscience.
Subjects: Psychology >> Developmental Psychology submitted time 2026-05-27
Abstract： Addressing the critical public health need for the prevention and treatment of age-related cognitive decline and related neurodegenerative diseases in the context of population aging, the present study focuses on non-pharmacological interventions as a promising strategy for mitigating cognitive deterioration in older adults. We aim to identify a core unifying neural biomarker underlying heterogeneous interventions and to establish causal evidence for its role through three integrated studies. Study 1 utilizes multimodal data from different types of interventions (including behavioral and neuroimaging data) to propose the novel hypothesis of a “core convergent network”. Based on this framework, we will identify and characterize the shared neural biomarker across different non-pharmacological interventions through multidimensional analyses of functional gradients, intrinsic neural timescales, and brain asymmetry. Studies 2 and 3 employ repetitive transcranial magnetic stimulation (rTMS) to modulate the core brain network identified in Study 1. Combined with task-based functional magnetic resonance imaging and behavioral experiment, these studies will provide dual validation in healthy and pathological aging, thereby establishing a complete research framework from mechanistic investigation to causal verification. The expected outcomes will reveal common patterns of neuroplasticity across intervention types and provide an original theoretical basis for developing precision intervention strategies based on a core unifying neural biomarker in older adults. The findings will have important scientific value for improving healthy aging management and reducing the burden of dementia and related disorders, while supporting national strategic initiatives such as “Active Response to Population Aging” and “Healthy China 2030”.
Subjects: Psychology >> Management Psychology submitted time 2026-05-27
Abstract： As artificial intelligence (AI) becomes increasingly embedded in creative work, organizations face a critical question: how human-AI collaboration should be structured to maximize creativity. Prior research has largely favored a human-first collaboration sequence, arguing that premature exposure to AI-generated content constrains independent thinking and fosters cognitive inertia. However, given the multi-stage nature of the creative process, it remains unclear whether the benefits of a human-first sequence generalizes across different stages. Drawing on the anchoring effect, we argue that in the idea elaboration phase, a human-first collaboration sequence can undermine creativity. Specifically, when individuals elaborate on ideas they initially generated themselves, they develop stronger psychological ownership over those ideas, which increases resistance to subsequent AI-generated structural suggestions. As a result, creators become less willing to incorporate AI input that could improve idea articulateness, ultimately reducing overall creativity. We further propose that trust in AI mitigates this effect by increasing individuals’ receptiveness to AI-generated suggestions.
We tested our hypotheses across three complementary experiments involving diverse creative tasks and samples (N = 741). Study 1 recruited 230 full-time employees to complete a product design elaboration task. Study 2 was a field experiment involving 271 participants who developed marketing plans for newly launched coffee products, including both human-first and AI-first collaboration conditions as well as a no-AI control condition. Study 3, involving 240 full-time employees, replicates the findings while directly testing psychological ownership as the underlying mechanism.
Across the three studies, we find consistent support for our hypotheses. Contrary to the prevailing assumption that human-first collaboration is universally beneficial, we find that in idea elaboration tasks, a human-first collaboration sequence reduces creativity relative to an AI-first sequence. This effect occurs because a human-first sequence heightens psychological ownership over initial ideas, leading individuals to discount or resist AI-generated structural suggestions, which in turn inhibits improvements in idea articulateness and ultimately reduces overall creativity. Moreover, trust in AI attenuates these negative effects by increasing willingness to integrate AI input during idea elaboration.
This research contributes to the literatures on human-AI collaboration and creativity in three ways. First, we challenge the prevailing view that a human-first collaboration sequence is inherently advantageous by demonstrating that its effectiveness is contingent on the creative phase. Second, our findings uncover a cognitive mechanism explaining why collaboration may remain suboptimal even when AI is incorporated into creative work. Third, by shifting attention from whether organizations should use AI to how and when AI should be integrated into creative work, this research provides new insights into how organizations can more effectively harness the complementary strengths of humans and AI in creative problem solving.
Subjects: Psychology >> History of Psychology Subjects: Management Science >> Science ology and Management submitted time 2026-05-25
Abstract： Open science enables the effective sharing and full utilization of scientific resources, reshapes research practice and academic culture, while its overall development remains in an initial stage. Taking psychology science and brain science as examples, this paper examines the grassroots open science movement initiated to enhance research credibility and scientific rigor. Such efforts promote open science practices throughout the entire research workflow, and led interdisciplinary open science actions and cultural construction. The paper further analyzes the driving factors behind the thriving open science in this field and provides suggestions for the development of Chinese open science.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Social Psychology submitted time 2026-05-23
Abstract： In the post-pandemic era, consumers have shown growing concerns for the environment, health, and safety, driving a significant surge in demand for natural products. However, what factors prompt consumers to perceive a product as natural? And how are consumers’ responses shaped after forming such perceptions? Existing literature lacks a systematic synthesis and clear classification of the factors influencing Perceived Product Naturalness (PPN), with inconsistent findings regarding the relative effectiveness of different cues. PPN is defined as consumers’ subjective judgment of whether a product is unprocessed by humans, free of non-natural ingredients, and directly derived from nature.Using a meta-analytic approach, this study synthesizes domestic and international empirical studies conducted over the past 20 years. We compare the relative effectiveness of heuristic cues versus systematic cues in shaping PPN, and further examine their overall impacts on consumer responses as well as the boundary conditions of these effects. A total of 59 articles and 229 effect sizes were included in the analysis. The results show that systematic cues outperform heuristic cues overall; consumer individual characteristics, product attributes, and situational factors all moderate the effectiveness of these cues. These findings provide practical implications for the strategic configuration of natural marketing cues and the guidance of consumer decision-making.
Subjects: Psychology >> Social Psychology submitted time 2026-05-22
Abstract： Awe is an emotion of wonder and perceived vastness that arises when people encounter stimuli that exceed their existing mental frames. Prior studies suggest that awe can encourage healthier choices, but it remains unclear whether adolescents respond in the same way to awe elicited by nature and awe elicited by non-nature-based stimuli. Drawing on nature connectedness and construal-level perspectives, this study examined how different forms of awe shaped adolescents’ healthy eating preferences and identified presentation strategies that could strengthen these effects.
Five experiments were conducted with adolescent participants (N = 937). In Study 1, video materials were used to induce positive nature-based awe, negative nature-based awe, non-nature-based awe, or a neutral emotional state. Participants then completed a healthy snack-choice task. Nature connectedness and construal level were measured as potential mediators. Studies 2a and 2b tested whether cues related to food naturalness would enhance the effect of positive nature-based awe. Study 2a presented yogurt advertisements that emphasized natural or artificial attributes, whereas Study 2b manipulated packaging color as an indirect cue of naturalness. Healthy eating was assessed using self-reported healthy food preferences and willingness to pay (WTP). Studies 3a and 3b examined whether activating high-level construal would strengthen the effect of non-nature-based awe. Study 3a varied advertising appeals by emphasizing long-term versus immediate health benefits, and Study 3b varied spatial framing by presenting healthy foods in distant versus close-up views. Across experiments, participants completed emotion manipulation checks, food evaluation tasks, and demographic measures.
Consistent with our hypotheses, the results showed that both positive nature-based awe and non-nature-based awe promoted healthier eating, as reflected in healthier snack choices, stronger preferences for healthy foods, and higher WTP. Crucially, the two forms of awe operated through different psychological pathways. Positive nature-based awe increased healthy eating mainly by strengthening adolescents’ connectedness with nature, whereas non-nature-based awe increased healthy eating mainly by promoting a higher construal level. The follow-up experiments further supported these mechanism-specific enhancement strategies. When adolescents experienced positive nature-based awe, emphasizing a food’s natural attributes, rather than artificial attributes, and using natural packaging colors, rather than non-natural colors, increased healthy food evaluations and WTP. When adolescents experienced non-nature-based awe, highlighting long-term health benefits rather than immediate benefits, or presenting healthy foods in distant rather than close-up views, participants reported stronger healthy eating preferences and higher WTP. These patterns indicated that different forms of awe operate through source-specific psychological mechanisms and that matching food cues to the relevant mechanism produces stronger effects than mismatched or neutral presentations.
Overall, these findings suggest that awe is not a uniform emotional driver of healthy eating. Instead, the health-promoting effect of awe depends on its source and on whether food messages fit the psychological process it activates. The study extends research on emotion and dietary decision-making by distinguishing nature connectedness from construal level as two mechanisms linking awe to adolescents’ food choices. It also offers practical implications for nutrition education, school-based health promotion, and public health communication. Awe-based interventions may be more effective when emotional induction is paired with naturalness cues or with higher-level construal framing that matches the type of awe being elicited.
Subjects: Psychology >> Applied Psychology submitted time 2026-05-21
Abstract： With the rapid development of artificial intelligence (AI) technology, human-AI relationships have become increasingly prevalent and consequential in organizations. Human trust in AI lies at the core of human-AI relationships and is critical to the effectiveness of human-AI interactions. Key challenges in research on human trust in AI include how to conceptualize trust, understand dynamic patterns of human-AI relationships, and achieve complementary advantages through human-AI interactions. This study addresses these issues by focusing on the dyadic interaction between humans and AI to explore the dynamic processes of human trust in AI over time. First, drawing on the perspective of technological ethics, this study conceptualizes human trust in AI as a two-dimensional construct comprising instrumental trust and value trust, and further develops a corresponding measurement scale. Second, adopting a dynamic development perspective, the study explores the temporal characteristics and dynamic patterns of human trust in AI, thereby opening the “black box” of trust dynamics in human-AI relationships. Finally, from the perspective of human-AI collaboration, the study investigates the effect of different forms of human trust in AI on employee creativity, offering a nuanced understanding of human-AI relationship development and providing insights into how trust in AI shapes employees’ core competencies in the digital intelligence era.
Subjects: Psychology >> Psychological Measurement submitted time 2026-05-20
Abstract： Item Response Theory (IRT) models are widely used in psychological and educational measurement. Their effectiveness, however, can be undermined by data quality issues, particularly aberrant responding, such as cheating, careless errors, rapid guessing, and hybrid forms involving multiple aberrant response behaviors. Such responses are especially prevalent in online assessments, where the absence of supervision, external distractions, and low participant motivation can introduce substantial measurement noise. Empirical evidence indicates that even 10～15% proportion of aberrant responses can meaningfully distort parameter estimates, while higher proportions (20～30% or more) can lead to severe bias in item and ability parameter estimates, reduce reliability, distort factor structures, and compromise measurement invariance test.
Person-fit statistics (PFS) are widely used to identify aberrant respondents. However, their dependence on full-sample parameter estimates makes them susceptible to the masking effect, in which aberrant responses bias item parameter estimation and, in turn, obscure person misfit, particularly when the proportion of aberrant responses is high. To overcome this limitation, a robust marginal maximum likelihood method has been proposed that incorporates PFS-derived weights into the likelihood function, thereby down-weighting aberrant respondents during parameter estimation. Using the lz statistic, this method can effectively reduce bias while retaining all response data.
Building on this framework, the present study introduces a new robust weighting method, namely Residual-Based Robust Weighting (RRW), which replaces lz with a residual-based person-fit statistic (PFS). Residual-based statistics quantify item-level deviations between observed and expected responses, standardized by their variances and aggregated across items. This finer-grained approach improves sensitivity to subtle and heterogeneous aberrant patterns compared to the aggregated likelihood ratio underlying lz. As a result, RRW assigns lower weights to respondents whose residual patterns deviate substantially from model expectations, while preserving the full contribution of respondents whose responses are consistent with the model.
We evaluated the proposed RRW method through simulation studies and an empirical example, comparing its performance with unweighted estimation and the lz-based RMML approach. Results showed that aberrant responding substantially distorts item parameter estimation, with the unweighted method exhibiting the largest increases in RMSE and bias as aberrance levels rise. The lz-based method improved discrimination estimates to some extent but showed limited effectiveness for threshold parameters. In contrast, RRW consistently achieved lower estimation errors for both discrimination and threshold parameters across most conditions, with its advantages becoming more pronounced under higher aberrance levels. Moreover, RRW maintained stable performance as test length increased, demonstrating strong robustness and applicability in complex testing scenarios.
Empirical results further validated RRW’s superiority: it reduced item parameter estimation error to a certain extent and enhanced ability estimates for non-aberrant respondents, demonstrating its effectiveness in mitigating the adverse impact of aberrant responses in real testing contexts. By improving item parameter accuracy, RRW indirectly increases the precision of ability estimation, providing a practical and robust alternative for IRT applications in complex testing environments. Overall, evidence from both simulation and empirical analyses indicates that the RRW weighted estimation method effectively reduces the negative effects of complex aberrant response patterns on item parameter estimation and shows strong potential for practical implementation.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Management Psychology submitted time 2026-05-19
Abstract： As artificial intelligence (AI) is increasingly adopted and deployed in enterprises, many teams are moving away from traditional goal-setting methods. In AI-enabled contexts, they are instead using stretch goals to stimulate employee and team creativity. However, the emergence of such goals in AI-enabled settings and their effects on creativity remain underexplored and lack empirical testing. Accordingly, this study aims to: (1) uncover how stretch goals emerge in AI-enabled settings; (2) draw on socio-technical systems theory to examine the mediating role of individual exploratory learning between stretch goals and individual creativity, as well as the moderating role of perceived AI usefulness; (3) draw on the same theory to test the mediating role of human-AI collaboration between stretch goals and team creativity, along with the moderating role of human-AI role clarity; and (4) verify the application of the formation mechanism and impact effects of stretch goals. The core conclusions derived from the “environmental stimuli → goal setting → employee behavioral outcomes” framework are then applied to practical scenarios, offering a reference for enterprises seeking to enhance individual and team creativity. The findings aim to fill the research gap concerning stretch goals in AI-enabled contexts and guide managers in leveraging AI to overcome constraints typically associated with stretch goals.
Subjects: Psychology >> Developmental Psychology submitted time 2026-05-19
Abstract： Ability and effort are two important factors children use to explain success and failure. A growing body of research shows that children can infer others’ ability and effort from behavioral and contextual cues (for example, how much time someone takes to complete a task), and that they increasingly prefer hardworking individuals over smart individuals as they grow older. However, prior studies have typically used single-outcome scenarios, leaving open the question of whether children’s reasoning is sensitive to changes of outcomes. The present study investigated whether children’s inferences about ability and effort are sensitive to changes in outcome cues (e.g., exam rankings), whether they prefer smart or hardworking individuals, and how these patterns change with age.
The study involved 120 children aged 4–7 years (M = 6.08, 63 girls) and 100 adults (M = 25.69, 50 women) in China. We employed a two-task paradigm in which participants were shown two characters completing two rounds of exams. In the first exam, both characters achieved identical performance outcomes (i.e., the same ranking), but one completed the task faster than the other. Participants were asked to infer which character was smarter, which worked harder, and to provide comparative evaluations of the two characters. In the second exam, the outcome was manipulated such that the character previously judged as smarter (or more hardworking, depending on the condition) was depicted as performing worse (ranked lower) than the other character. Participants were then asked to make the same inferences and evaluations again. We examined whether these inferences and evaluations changed following the outcome manipulation.
Three main findings emerged. First, children as young as 4 years old inferred that the character who finished the task faster as smarter, whereas their inferences about effort showed notable developmental changes. Four-year-olds were unable to infer who was more hardworking; beginning around age 5.5 years, however, children inferred the character who took longer to finish the task as more hardworking. Second, children’s inferences of smartness were sensitive to outcome information, whereas their inferences about effort were less likely to change in response to outcome information. Third, their evaluations also showed developmental change, with older children increasingly favoring the hardworking character. In contrast, adults’ inferences about both smartness and effort remained stable despite changes in outcomes.
These findings indicate that children’s conceptions of smart and effort, as well as their sensitivity to outcome, follow distinct developmental trajectories. Children demonstrate early competence in inferring smartness and these inferences are sensitive to outcomes, whereas their conceptualization of effort develops relatively later and becomes more process-oriented and less outcome-dependent with age. These findings contribute to our understanding of achievement-related cognition and suggest that educators could support children’s appreciation of effort by emphasizing process rather than outcome, particularly in early childhood.
Subjects: Psychology >> Cognitive Psychology submitted time 2026-05-19
Abstract： Whether bilinguals share the same neural mechanisms for processing their native language (L1) and second language (L2) is a long-standing question of debate. Extensive neuroimaging evidence has accumulated, yet substantial inconsistencies remain. These largely stem from linguistic distance between bilinguals’ L1 and L2, as well as differences in experimental task demands.
The present study used an activation likelihood estimation (ALE) meta-analysis to examine how linguistic distance and task demands affect brain activation during bilingual lexical processing. Seventy-four studies met the inclusion criteria and were classified into six groups according to task type (phonological, semantic, language switching) and language distance (Chinese–English bilinguals vs. alphabetic bilinguals): 18 on phonological processing in Chinese–English bilinguals, 12 on phonological processing in alphabetic bilinguals, 12 on semantic processing in Chinese–English bilinguals, 13 on semantic processing in alphabetic bilinguals, 9 on language switching in Chinese–English bilinguals, and 14 on language switching in alphabetic bilinguals. We carried out ALE meta-analyses using GingerALE 3.0.2. All coordinates were converted to Talairach space. To visualize the activation patterns, we projected the coordinates onto a standard brain template using BrainNet Viewer and xjview.
Results showed that during phonological tasks, Chinese–English bilinguals with a large language distance recruited greater L2-related activation in the left inferior parietal lobule, extending into the supramarginal gyrus, which is responsible for grapho-phonological conversion; whereas bilinguals of alphabetic languages with a small language distance shared the same neural mechanisms for their L1 and L2. During semantic tasks, Chinese–English bilinguals showed greater activation in the left middle frontal gyrus and left precuneus for L1 processing to support grapho-to-meaning conversion; whereas alphabetic bilinguals recruited the middle part of the left superior temporal gyrus more for their L1 to achieve phonology-to-meaning conversion, and for their L2 they activated language control brain regions including the left middle frontal gyrus/inferior frontal gyrus, insula, and inferior parietal lobule. Further comparison of brain activation between the two types of bilinguals during language switching tasks also revealed that alphabetic bilinguals with a small language distance required greater involvement of executive control brain regions, including the left inferior frontal gyrus, middle frontal gyrus, and inferior parietal lobule.
In sum, the current meta-analysis demonstrated that differences in brain activation between bilinguals' L1 and L2 processing reflect underlying cognitive processes jointly driven by linguistic distance and task demands. These findings not only support the specific computational demands hypothesis but also provide bilingual perspectives for understanding the universality and specificity of language processing.
Subjects: Psychology >> Social Psychology submitted time 2026-05-18
Abstract： With the growing integration of pets into urban life, pet-related injuries have become more common. These incidents often involve ambiguous causes, leading to public disagreement over responsibility. Psychologically, how people assign blame in ambiguous situations is not well understood. We propose that pet contact influences responsibility attribution, hypothesizing that more pet contact would result in less blame being assigned to the pet party diad (the pet and its owner), especially when the cause of the incident is unclear, and that this effect would occur through reduced perceived pet harmfulness. This reduction in perceived harmfulness was also expected to subsequently decrease support for victim compensation, extending the attributional chain to behavioral intentions.
Four studies were conducted with Chinese adults recruited online and locally. Study 1 (N = 156) was a cross-sectional survey measuring self-reported pet contact and responsibility attribution across two types of pet injury scenarios: clear and ambiguous. Study 2 (N = 189) experimentally manipulated pet contact via an imagination task. Study 3 (N = 210) used video priming. Study 4 (N = 156) employed real interactions in a real pet store versus a real store. Measures included pet contact frequency, perceived harmfulness, responsibility attribution to the pet party, and support for victim compensation. The analyses used ANOVA, linear mixed models, and mediation analysis, controlling for pet ownership, age, gender, and pet liking.
Study 1 showed that more pet contact predicted less responsibility attribution to the pet party diad in ambiguous scenarios (β = −0.45, p = 0.010), but no effect in clear situations. Study 2 found that the pet contact group attributed less responsibility to pet party diad (p < 0.001) and perceived pets as less harmful, with mediation confirmed (95% CI [−0.25, −0.04]). Study 3 replicated this finding and demonstrated a sequential mediation: from pet contact to lower perceived harmfulness, then to reduced responsibility, and finally to lower support for victim compensation (95% CI [−0.44, −0.10]). Study 4, implemented in a real setting, again supported the sequential mediation (95% CI [−0.60, −0.10]). A mini meta-analysis of Studies 2–4 showed a consistent medium effect (Cohen’s d = −0.44, 95% CI [−0.81, −0.07]).
This research shows that pet contact reduces responsibility attributions by lowering perceived harmfulness, and supports the application of attribution theory to human–animal interactions. The findings highlight how personal experience can systematically shape causal inference in ambiguous contexts. Practically, they help explain public disagreements over pet-related disputes and suggest that pet contact history may unconsciously bias judgments of blame and compensation. Future research should examine boundary conditions such as pet type and negative contact experiences.
Subjects: Psychology >> Social Psychology submitted time 2026-05-17
Abstract：
A reverse mentoring relationship is a developmental workplace relationship in which younger employees provide guidance and support to older employees. In the digital-intelligence era, older employees still possess valuable work experience, contextual judgment, and tacit knowledge. Still, they may face difficulties in adapting to emerging digital tools and platform-based work systems. Existing research has mainly relied on Western frameworks derived from traditional mentoring, leaving the role reversal, power dynamics, and cultural features of reverse mentoring relationships
in Chinese organizations insufficiently specified. This study examined the dimensional structure of the reverse mentoring relationship, developed a measurement scale, and tested its practical effects for older protégés and younger mentors.
Three studies were conducted. Study 1 used grounded theory methods based on semi-structured interviews with 15 participants and open-ended questionnaire responses from 13 participants. Through open, axial, selective, and theoretical coding, 890 valid semantic segments were extracted.
The coding process showed high inter-coder agreement, with an agreement rate of 87.4% and Cohen’s kappa = 0.83. Study 2 developed and validated the reverse mentoring relationship scale using three independent samples: 200 participants for exploratory factor analysis, 492 participants for confirmatory factor analysis and measurement invariance testing, and 249 participants for discriminant validity testing. Study 3 adopted a three-wave matched design, including 240 older protégés and their supervisors and 292 younger mentors, to examine the scale’s practical applicability.
Study 1 identified three dimensions of the reverse mentoring relationship in Chinese organizations: technical support, mental inspiration, and competence recognition. Based on these dimensions, a 15-item scale was developed. In Study 2, exploratory factor analysis extracted three
factors, explaining 61.69% of the total variance. Confirmatory factor analysis supported the three factor model. The second-order three-factor model also showed acceptable fit, indicating that the reverse mentoring relationship is a multidimensional construct. Measurement invariance tests across gender, age, education, position level, traditional mentoring role, relationship type, and organizational ownership supported the scale's cross-group stability. Discriminant validity analysis showed that the new scale was related to, but distinct from, Chen(2014)’s reverse mentoring relationship measure. In Study 3, the reverse mentoring relationship positively predicted older protégés’ task performance and self-efficacy; self-efficacy further predicted task performance. The reverse mentoring relationship also negatively predicted younger mentors’ turnover intention, and positively predicted perceived insider status; perceived insider status negatively predicted turnover intention.
By integrating Chinese cultural characteristics with the context of digital-intelligence transformation, this study clarified the conceptual connotation and structural dimensions of the reverse mentoring relationship. It developed a measurement tool applicable to Chinese organizational contexts in the digital-intelligence era. It not only provides a contextualized refinement and localized extension of existing Western frameworks but also offers a key methodological foundation for future scholars to examine the effects and mechanisms of the reverse mentoring relationship. In addition, it offers new insights and directions for research on talent development mechanisms and management practices in Chinese organizations.
Subjects: Psychology >> Cognitive Psychology Subjects: Mathematics >> Statistics and Probability submitted time 2026-05-17
Abstract： Meta-analysis serves as an essential statistical methodology to synthesize independent empirical findings. It is deeply embedded across various quantitative disciplines. However, researchers routinely confront significant dilemmas regarding model selection throughout the analytical workflow. When managing across-study heterogeneity, researchers face a strict choice between fixed-effects and random-effects frameworks. Similarly, to mitigate the threat of potential publication bias, researchers choose from a diverse array of disparate correction models. At present, the field lacks a unified, standardized criterion for selecting the single optimal model configuration. Consequently, traditional approaches rely on a single chosen model and neglect model uncertainty. This omission causes overconfident statistical inferences, underestimated standard errors, and potentially biased estimates of the true population effect size. In turn, these estimation errors reduce the replicability of empirical findings.
To resolve these deep-seated methodological vulnerabilities, Bayesian Model Averaging (BMA) offers an innovative and mathematically rigorous paradigm that operates within the broader Bayesian statistical framework. Instead of an arbitrary, ex-ante selection of a single statistical model, BMA directly accommodates model uncertainty. It embeds all theoretically plausible candidate models into a single, cohesive model space. Specifically, BMA treats the model itself as a random variable within a probability space. This formulation effectively manages uncertainty in both the effect size and heterogeneity. By establishing prior probabilities for each model configuration, BMA leverages empirical data to calculate posterior model probabilities. This process quantifies the precise degree of empirical data support that each individual model receives. Ultimately, the final effect size is a weighted average across all models, where posterior probabilities directly determine individual model weights. This approach avoids the inherent biases of single-model selection. It yields a continuous measure of cumulative evidence rather than a binary accept-reject decision.
Researchers operationalize this rigorous approach in meta-analysis as robust Bayesian meta-analysis (RoBMA). RoBMA inherits the core model-averaging principles of BMA. It systematically incorporates multiple publication bias correction models, such as selection models and PET-PEESE (precision-effect test and precision-effect estimate with standard error), into the Bayesian inference framework. It avoids a forced selection of a single optimal model. Instead, the framework weights competing hypotheses within the model space based directly on empirical data. This mechanism provides rigorous quantitative evidence, specifically inclusion Bayes factors (BF), to evaluate 3 critical hypotheses concurrently to govern the validity of literature synthesis. These hypotheses test whether a true population effect exists, whether study-level heterogeneity is present, and whether publication bias contaminates the literature. RoBMA constructs a multi-dimensional model space to map every possible combination of these 3 dimensions (e.g., presence vs. absence of an effect, presence vs. absence of heterogeneity, and presence vs. absence of publication bias). As a consequence, the framework outputs model-averaged posterior estimates that fully incorporate model uncertainty, delivering an exceptionally robust and reliable evaluation of the primary effect size.
Beyond its conceptual and theoretical advantages, the practical execution of BMA-based meta-analysis has become highly viable due to contemporary computational breakthroughs and software integration. This paper comprehensively outlines the concrete, accessible pathways for applied researchers to deploy these advanced statistical techniques in real-world research scenarios. Specifically, the open-source statistical software JASP seamlessly executes the entire analytical pipeline, which provides an intuitive and user-friendly graphical user interface (GUI) for point-and-click execution. For researchers who require scriptability and reproducibility, specialized open-source packages make the methodology fully available into the R programming language. These programming tools facilitate automated reporting and extensive sensitivity analyses. They effectively lower the technical barriers to advanced Bayesian inference for non-statisticians. This paper effectively bridges the historical divide between intricate Bayesian theory and practical application. It delivers a definitive roadmap for researchers to maximize transparency and credibility in meta-analytic conclusions. Therefore, this methodology offers broad applicability for enhancing the robustness of evidence synthesis across psychological science and various other disciplines.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Educational Psychology Subjects: Psychology >> Developmental Psychology submitted time 2026-05-15
Abstract： The school climate serves as a pivotal microenvironment for the development of adolescents’ social behaviors and constitutes a critical component of school bullying intervention and governance. Previous research has indicated that adverse peer relationships are a key school environmental risk factor for predicting bullying and victimization, whereas bystander defending behaviors constitute one of the critical school environmental protective factors in terminating bullying events. However, traditional studies have mostly adopted a static perspective to focus on the predictive effects of a limited number of variables on bystander defending behaviors, thus failing to address the scientific question regarding the complex psychological mechanisms underlying why bystanders make divergent behavioral choices in real-world contexts. Furthermore, theoretically driven variable selection and linear analytic approaches have also constrained the discovery of potential pathways, failing to illuminate the intrinsic psychological processes underlying the bystanders’ behavioral decision-making. To address these gaps, the present study attempts to adopt a dynamic perspective of situational interactions, focusing on constructing a three-stage psychological decision-making framework that illustrates how school climate, interpersonal interactions, and bystanders’ personal traits shape bystander defending behaviors through the psychological processes of event identification, emotional experience, and risk-benefit trade offs. These results may provide innovative insights for developing a scientifically sound and comprehensive model of school bullying governance.
Subjects: Psychology >> Educational Psychology submitted time 2026-05-15
Abstract： Creativity is a neutral cognitive capacity that can generate constructive outcomes, but it may also lead to negative social consequences. The latter includes negative creativity and malevolent creativity. Both are grounded in the cognitive basis of novelty and appropriateness and both involve negative social value in their outcomes, yet they differ in motivational orientation: negative creativity is primarily self-serving, with harm occurring mainly as a byproduct, whereas malevolent creativity takes harming others, organizations, or society as its core objective. This review systematically clarifies the conceptual boundaries and measurement challenges of negative creativity and malevolent creativity. It further argues that the evolution from negative creativity to malevolent creativity is neither linear nor inevitable, but is dynamically driven by cognitive control failure, situational triggers, motivational reinforcement, moral disengagement, and insufficient social regulation, which may operate independently or in combination. Building on this analysis, this review proposes the Cognitive-Motivational-Development (CMD) intervention model. Through cognitive evaluation training, motivational value reconstruction, and developmental ecological support, the model aims to provide upstream guidance for children’s negative creativity. This framework offers both theoretical and practical implications for understanding the developmental mechanisms underlying the negative side of creativity and for promoting healthy creative development in childhood.
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