Acta Psychologica Sinica

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The impact of different types of academic stress on subcomponents of executive function in high school students of different grades

MA Chao, WANG Yanyun, FU Junjun, ZHAO Xin

Acta Psychologica Sinica 2025, 57 (1): 18-35. DOI: 10.3724/SP.J.1041.2025.0018

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This study investigated the roles of four dimensions of academic stress in various executive function components among 985 high school students from grades 10 to 12 using correlation analysis and structural equation modeling. The results revealed that as students progressed through the high school grades, the negative predictive effects of parental stress and teacher stress on various executive function components gradually increased, while the negative predictive effect of social stress gradually decreased. In contrast, self-imposed stress exhibited a positive predictive effect on interference inhibition, response inhibition, and attention switching abilities among high school students, and this positive effect strengthened with advancing grades. These findings indicate that different types of academic stress have varying predictive effects on executive function components, and these effects change as students progress through high school. The conclusions drawn from this study have important implications for educators in effectively developing strategies to cope with academic stress among high school students.

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The influence of cultural differences between China and the West on moral responsibility judgments of virtual humans

YAN Xiao, MO Tiantian, ZHOU Xinyue

Acta Psychologica Sinica 2024, 56 (2): 161-178. DOI: 10.3724/SP.J.1041.2024.00161

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Virtual humans are digital characters created in computer graphics software that take a first-person view of the world and have a social media presence. Compared with real humans, however, are people likely to attribute moral responsibility differently to virtual humans when they do something morally wrong? This important empirical question remains unanswered. Therefore, we addressed this query using Mental Perception Theory. We did so through exploring the influence and mechanism of cultural differences between China and the West on individuals’ moral responsibility judgments of virtual humans versus real humans. Findings revealed that, when virtual humans engaged in immoral behaviors—irrespective of whether real humans or artificial intelligence (AI) controlled them—people in China (vs. the West) attributed more moral responsibility to virtual humans but equal moral responsibility to real humans (Study 1a~1c). Perceived mental capacity, especially perceived experience, mediated the interaction effect of the culture differences (Study 2). Furthermore, compared with Westerners, Chinese people were more likely to punish virtual (vs. real) humans, such as by no longer following their social accounts (Study 3). The current research provided evidence for the cultural differences between Chinese people and Westerners on moral responsibility judgments of virtual humans and contributed to literature on cultural differences and the theory about moral judgments on non-human entities.

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New research paradigms and agenda of human factors science in the intelligence era

XU Wei, GAO Zaifeng, GE Liezhong

Acta Psychologica Sinica 2024, 56 (3): 363-382. DOI: 10.3724/SP.J.1041.2024.00363

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This paper first proposes the innovative concept of “human factors science” to characterize engineering psychology, human factors engineering, ergonomics, human-computer interaction, and other similar fields. Although the perspectives in these fields differ, they share a common goal: optimizing the human-machine relationship by applying a “human-centered design” approach. AI technology has brought in new characteristics, and our recent research reveals that the human-machine relationship presents a trans-era evolution from “human-machine interaction” to “human-AI teaming.” These changes have raised questions and challenges for human factors science, compelling us to re-examine current research paradigms and agendas.
In this context, this paper reviews and discusses the implications of the following three conceptual frameworks that we recently proposed to enrich the research paradigms for human factors science. (1) human-AI joint cognitive systems: This model differs from the traditional human-computer interaction paradigm and regards an intelligent system as a cognitive agent with a certain level of cognitive capabilities. Thus, a human-AI system can be characterized as a joint cognitive system in which two cognitive agents (human and intelligent agents) work as teammates for collaboration. (2) human-AI joint cognitive ecosystems: An intelligent ecosystem with multiple human-AI systems can be represented as a human-AI joint cognitive ecosystem. The overall system performance of the intelligent ecosystem depends on optimal cooperation and design across the multiple human-AI systems. (3) intelligent sociotechnical systems (iSTS): human-AI systems are designed, developed, and deployed in an iSTS environment. From a macro perspective, iSTS focuses on the interdependency between the technical and social subsystems. The successful design, development, and deployment of a human-AI system within an iSTS environment depends on the synergistic optimization between the two subsystems.
This paper further enhances these frameworks from the research paradigm perspective. We propose three new research paradigms for human factors science in the intelligence ear: human-AI joint cognitive systems, human-AI joint cognitive ecosystems, and intelligent sociotechnical systems, enabling comprehensive human factors science solutions for AI-based intelligent systems. Further analyses show that the three new research paradigms will benefit future research in human factors science. Furthermore, this paper looks forward to the future research agenda of human factors science from three aspects: “human-AI interaction,” “intelligent human-machine interface,” and “human-AI teaming.” We believe the proposed research paradigms and the future research agenda will mutually promote each other, further advancing human factors science in the intelligence era.

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Trend analysis of marital satisfaction of mainland Chinese couples in the past 20 years

HOU Juan, JIA Keke, FANG Xiaoyi

Acta Psychologica Sinica 2024, 56 (7): 895-910. DOI: 10.3724/SP.J.1041.2024.00895

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The cognitive mechanism of reducing procrastination by emotion regulation: The mediation role of task aversiveness

TONG Tingting, BAI Youling, FENG Tingyong

Acta Psychologica Sinica 2024, 56 (4): 458-468. DOI: 10.3724/SP.J.1041.2024.00458

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Prior studies have demonstrated that employing adaptive emotion-regulation strategies, such as cognitive reappraisal, can effectively mitigate procrastination. Nevertheless, the cognitive mechanisms that account for the impact of emotion regulation on procrastination still lack clarity. The temporal decision model of procrastination postulates that procrastination is primarily influenced by the tradeoff between task aversiveness and outcome utility. When task aversiveness exceeds outcome utility, individuals are prone to procrastination; conversely, if outcome utility outweighs task aversiveness, they are more likely to take immediate action. Consequently, emotion regulation has the potential to reduce procrastination by either diminishing task aversiveness or enhancing outcome utility.
In order to explore this matter, this study adopts Gross’s emotion regulation theory and the temporal decision model of procrastination. Specifically, the study targets individuals with high levels of procrastination, as indicated by scores above 67.5 on the General Procrastination Scale. These individuals were assigned to the positive reappraisal group (n = 34) and the ineffective strategy group (n = 34), respectively. The longitudinal tracking of both groups took place over a period of 7 days, resulting in a total of 14 data collection points obtained through empirical sampling.
The results showed that: (1) There was no notable disparity between the two groups in task executive willingness during the pre-test (M_{Pre-test of positive reappraisal group} = 2.05, SD = 1.67, M_{Pre-test of ineffective strategy group}= 2.42, SD = 2.17; F(1, 202) = 1.88, p = 0.172), while the positive reappraisal group demonstrated a significantly higher task executive willingness compared to the ineffective strategy group in the post-test (M_{Post-test of positive reappraisal group} = 5.26, SD = 1.97, M_{Post-test of ineffective strategy group}= 2.91, SD = 2.44; F(1, 202) = 57.49, p < 0.001, partial η²= 0.22) (Figure 1a), indicating that positive reappraisal significantly enhanced individuals’ task executive willingness. (2) No significant difference was observed in task aversiveness between the two groups during the pre-test (M_{Pre-test of positive reappraisal group} = − 5.81, SD = 1.65, M_{Pre-test of ineffective strategy group}= −5.56, SD = 1.88; F(1, 202) = 1.06, p = 0.304), while the positive reappraisal group exhibited noticeably lower levels of task aversiveness compared to the ineffective strategy group in the post-test (M_{Post-test of positive reappraisal group} = − 0.77, SD = 3.19, M_{Post-test of ineffective strategy group}= − 3.75, SD = 3.02; F(1, 202) = 46.59, p < 0.001, partial η²= 0.19) (Figure 2a). Additionally, initial outcome utility levels did not differ significantly between the two groups (M_{Pre-test of positive reappraisal group} = 6.94, SD = 2.33, M_{Pre-test of ineffective strategy group}= 6.81, SD = 2.62; F(1, 202) = 0.14, p = 0.714), while the positive reappraisal group demonstrated significantly higher outcome utility compared to the ineffective strategy group in the post-test (M_{Post-test of positive reappraisal group} = 7.69, SD = 1.90, M_{Post-test of ineffective strategy group}= 6.68, SD = 2.69; F(1, 202) = 9.58, p = 0.002, partial η²= 0.05) (Figure 3a). (3) Mediation analysis indicated that the reduction of task aversiveness mediated the influence of emotion regulation on the degree of improvement in procrastination (that is, the increase in task executive willingness)(b = 0.44, 95% CI = [0.765, 1.561]) (Figure 4), whereas the increase of outcome utility did not mediate the impact of emotion regulation on the degree of improvement in procrastination (that is, the increase in task executive willingness) (b = 0.06, 95% CI = [− 0.013, 0.367]).
These findings suggest that emotion regulation primarily enhances individuals’ task executive willingness by diminishing task aversiveness, consequently mitigating procrastination behavior. This provides a robust theoretical basis for interventions that aim to address procrastination by focusing on emotion regulation.

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Cognitive outsourcing based on generative artificial intelligence: An Analysis of interactive behavioral patterns and cognitive structural features

WANG Fancong, TANG Xiaoyu, YU Shengquan

Acta Psychologica Sinica 2025, 57 (6): 967-986. DOI: 10.3724/SP.J.1041.2025.0967

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Humans can enhance task efficiency and quality by delegating part of their cognitive tasks to generative artificial intelligence (AI), a process referred to as cognitive outsourcing. However, individuals’ effectiveness in using AI varies. To identify the key characteristics and inherent requirements of effective cognitive outsourcing, this study designed a cognitive outsourcing activity for graduate students. Participants wrote articles on open-ended topics with the assistance of a generative AI system and were divided into high-performance and low-performance groups based on their article scores. Differential analysis of knowledge pre-tests revealed that the high-performance group exhibited significantly higher prior domain knowledge compared to the low-performance group. Through lag sequential analysis and epistemic network analysis of interaction process data, differences in interactive behavioral patterns and cognitive structural features between the two groups were identified: participants in the high-performance group demonstrated more diversified behavioral transitions, forming a pattern characterized by “rapid and autonomous task comprehension and planning, efficient and precise human-computer interaction, selective information extraction and deep processing”; the cognitive structure of the high-performance group was balanced and comprehensive, primarily engaging with higher-level cognitive processing, while the low-performance group's cognitive structure was unbalanced and fragmented, primarily engaging with lower-level cognitive processing. In conclusion, effective cognitive outsourcing is a multifaceted process that necessitates active participation and profound cognitive processing. It demands proficient integration between internal cognitive frameworks and external technological tools.

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Perceived opacity leads to algorithm aversion in the workplace

ZHAO Yijun, XU Liying, YU Feng, JIN Wanglong

Acta Psychologica Sinica 2024, 56 (4): 497-514. DOI: 10.3724/SP.J.1041.2024.00497

Abstract （664）

With algorithms standing out and influencing every aspect of human society, people's attitudes toward algorithmic invasion have become a vital topic to be discussed. Recently, algorithms as alternatives and enhancements to human decision-making have become ubiquitously applied in the workplace. Despite algorithms offering numerous advantages, such as vast data storage and anti-interference performance, previous research has found that people tend to reject algorithmic agents across different applications. Especially in the realm of human resources, the increasing utilization of algorithms forces us to focus on users' attitudes. Thus, the present study aimed to explore public attitudes toward algorithmic decision-making and probe the underlying mechanism and potential boundary conditions behind the possible difference.
To verify our research hypotheses, four experiments (N = 1211) were conducted, which involved various kinds of human resource decisions in the daily workplace, including resume screening, recruitment and hiring, allocation of bonuses, and performance assessment. Experiment 1 used a single-factor, two-level, between-subjects design. 303 participants were randomly assigned to two conditions (agent of decision-making: human versus algorithm) and measured their permissibility, liking, and willingness to utilize the agent. Experiment 1 was designed to be consistent with Experiment 2. The only difference was an additional measurement of perceived transparency to test the mediating role. Experiment 3 aimed to establish a causal chain between the mediator and dependent variables by manipulating the perceived transparency of the algorithm. In Experiment 4, a single-factor three-level between-subjects design (non-anthropomorphism algorithm versus anthropomorphism algorithm versus human) was utilized to explore the boundary condition of this effect.
As anticipated, the present research revealed a pervasive algorithmic aversion across diverse organizational settings. Specifically, we conceptualized algorithm aversion as a tripartite framework encompassing cognitive, affective, and behavioral dimensions. We found that compared with human managers, participants demonstrated significantly lower permissibility (Experiments: 1, 2, and 4), liking (Experiments: 1, 2, and 4), and willingness to utilize (Experiment 2) algorithmic management. And the robustness of this result was demonstrated by the diversity of our scenarios and samples. Additionally, this research discovered perceived transparency as an interpretation mechanism explaining participants' psychological reactions to different decision-making agents. That is to say, participants were opposed to algorithmic management because they thought its decision processes were more incomprehensible and inaccessible than humans (noted in Experiment 2). Addressing this “black box” phenomenon, Experiment 3 showed that providing more information and principles about algorithmic management positively influenced participants' attitudes. Crucially, the result also demonstrated the moderating effect of anthropomorphism. The result showed that participants exhibited greater permissibility and liking for the algorithm with human-like characteristics, such as a human-like name and communication style, over more than a mechanized form of the algorithm. This observation underlined the potential of anthropomorphism to ameliorate resistance to algorithmic management.
These results bridge the gap between algorithmic aversion and decision transparency from the social-psychological perspective. Firstly, the present research establishes a three-dimensional (cognitive, affective, and behavioral) dual-perspective (employee and employer) model to elucidate the negative responses toward algorithmic management. Secondly, it reveals that perceived opacity acts as an obstacle to embracing algorithmic decision-making. This finding lays the theoretical foundation of Explainable Artificial Intelligence (XAI) which is conceptualized as a “glass box”. Ultimately, the study highlights the moderating effect of anthropomorphism on algorithmic aversion. This suggests that anthropomorphizing algorithms could be a feasible approach to facilitate the integration of intelligent management systems.

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The application of artificial intelligence methods in examining elementary school students’ academic cheating on homework and its key predictors

ZHAO Li, ZHENG Yi, ZHAO Junbang, ZHANG Rui, FANG fang, FU Genyue, LEE Kang

Acta Psychologica Sinica 2024, 56 (2): 239-254. DOI: 10.3724/SP.J.1041.2024.00239

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Background. Academic cheating has been a challenging problem for educators for centuries. It is well established that students often cheat not only on exams but also on homework. Despite recent changes in educational policy and practice, homework remains one of the most important academic tasks for elementary school students in China. However, most of the existing studies on academic cheating for the last century have focused almost exclusively on college and secondary school students, with few on the crucial elementary school period when academic integrity begins to form and develop. Further, most research has focused on cheating on exams with little on homework cheating. The present research aimed to bridge this significant gap in the literature. We used advanced artificial intelligence methods to investigate the development of homework cheating in elementary school children and the key contributing factors so as to provide the scientific basis for the development of early intervention methods to promote academic integrity and reduce cheating.

Method. We surveyed elementary school students from Grades 2 to 6 and obtained a valid sample of 2, 098. The questionnaire included students’ self-reported cheating on homework (the dependent variable). The predictor variables included children’s ratings of (1) their perceptions of the severity of consequences for being caught cheating, (2) the extent to which they found cheating to be acceptable, and the extent to which they thought their peers considered cheating to be acceptable, (3) their perceptions of the effectiveness of various strategies adults use to reduce cheating, (4) how frequently they observed their peers engaging in cheating, and (5) several demographic variables. We used ensemble machine learning (an emerging artificial intelligence methodology) to capture the complex relations between cheating on homework and various predictor variables and used the Shapley importance values to identify the most important factors contributing to children’s decisions to cheat on homework.

Results. Overall, 33% of elementary school students reported having cheated on homework, and the rate of such self-reported cheating behavior increased with grade (see Figure 1). The best models with the ensemble machine learning accurately predicted the students’ homework cheating with a mean Area Under the Curve (AUC) value of 80.46% (see Figure 2). The Shapley importance values showed that all predictors significantly contributed to the high performance of our computational models. However, their importance values varied significantly. Children’s cheating was most strongly predicted by their own beliefs about the acceptability of cheating (10.49%), how commonly and frequently they had observed their peers engaging in academic cheating (3.83%), and their achievement level (3.26%). Other predictors (1%-2%), such as children’s beliefs about the severity of the possible consequences of cheating (e.g., being punished by one’s teacher), whether cheating is considered acceptable by peers in general and demographic characteristics, though significantly, were not important predictors of elementary school children’s homework cheating (see Figure 3 for details).

Conclusion. This study for the first time examined elementary school students’ homework cheating behavior. We used machine learning integration algorithms to systematically investigate the key factors contributing to elementary school students' homework cheating. The results showed that homework cheating already exists in the elementary school period and increases with grade. Advanced machine learning algorithms revealed that elementary school students' homework cheating largely depends on their acceptance of cheating, their peers' homework cheating, and their own academic performance level. The present findings advance our theoretical understanding of the early development of academic integrity and dishonesty and form the scientific basis for developing early intervention programs to reduce academic cheating. In addition, this study also shows that machine learning, as the core method of artificial intelligence, is an effective method that can be used to analyze developmental data analysis.

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The Influence Relationship among Variables and Types of Multiple Influence Factors Working Together

WEN Zhonglin, WANG Yifan, MA Peng, MENG Jin, LIU Xiqin

Acta Psychologica Sinica 2024, 56 (10): 1462-1470. DOI: 10.3724/SP.J.1041.2024.01462

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The investigation of relationships among variables is the main focus of empirical research in psychology and other social science disciplines. Many empirical studies based on questionnaire surveys involve the influence relationship between variables. However, the lack of a universally accepted definition for this concept has led to ambiguity, and it is often conflated with causal or correlational relationships, which may cause problems for studies on mediating effects. This article defines the influence relationship as a directional correlation, clarifying relationships among correlation, influence and causation in terms of denotation and connotation. We propose several ways to identify evidence for modeling the influence relationship. Our discussion involves the joint effects of multiple factors influencing a dependent variable. The paper provides theoretical support for studying relationships between variables in questionnaire research.

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The influence of perceived robot threat on workplace objectification

XU Liying, WANG Xuehui, YU Feng, PENG Kaiping

Acta Psychologica Sinica 2024, 56 (2): 210-225. DOI: 10.3724/SP.J.1041.2024.00210

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With buzzwords such as “tool man”, “laborer” and “corporate slave” sweeping the workplace, workplace objectification has become an urgent topic to be discussed. With the increasing use of artificial intelligence, especially robots in the workplace, the workplace effects produced by robots are also worth paying attention to. Therefore, the present paper aims to explore whether people’s perception of robots’ threat to them will produce or aggravate workplace objectification. On the basis of reviewing the related research on workplace objectification and robot workforce, and combined with intergroup threat theory, this paper elaborates the realistic threat to human employment and security caused by robot workforce, as well as the identity threat to human identity and uniqueness. From the perspective of compensatory control theory, this paper proposes the deep mechanisms and boundary conditions of how perceiving robot threat will reduce people's sense of control, thereby stimulating the control compensation mechanism, which in turn leads to workplace objectification.

This research is composed of eight studies. The first study includes two sub-studies, which investigate the relationship between perceived robot threat and workplace objectification through questionnaires and online experiments. This study tries to find a positive correlation and a causal association between perceived robot threat and workplace objectification. As predicted, results showed that workplace objectification was positively correlated with perceived robot realistic threat (r = 0.15, p < 0.001) and perceived robot identity threat (r = 0.18, p < 0.001) (Study 1a). In Study 1b, workplace objectification in high perceived robot threat condition (M = 3.54, SD = 1.01) was significantly more than in low perceived robot threat condition (M = 3.32, SD = 0.92), F(1, 399) = 4.94, p = 0.027, η2 p = 0.01.

The second study comprises three sub-studies, which explore why perceived robot threat increases workplace objectification. This study aims to verify the mediating effect of control compensation (i.e., sense of control), to explain the psychological mechanism behind the effect of perceived robot threat on workplace objectification, and to repeatedly verify it through different research methods. In Study 2a, workplace objectification was positively correlated with perceived robot realistic threat (r = 0.12, p = 0.017) and perceived robot identity threat (r = 0.18, p < 0.001). In addition, a bootstrapping mediation analysis (model 4, 5000 iterations) showed that the effect of perceived robot identity threat on workplace objectification was mediated by sense of control, b = 0.02, 95%CI = [0.002, 0.038]. In Study 2b, workplace objectification in high perceived robot threat condition (M = 2.85, SD = 0.90) was significantly more than in low perceived robot threat condition (M = 2.64, SD = 0.65), F(1, 295) = 5.49, p = 0.020, η2 p = 0.02. Furthermore, a bootstrapping mediation analysis (model 4, 5000 iterations) showed that the effect of perceived robot identity threat on workplace objectification was mediated by sense of control, b = 0.11, 95% CI = [0.020, 0.228]. In Study 2c, a one-way ANOVA revealed that perceived robot threat influenced workplace objectification, F(2, 346) = 3.68, p = 0.026, η2 p = 0.02. Post-hoc pairwise comparison using Bonferroni showed that workplace objectification in perceived robot identity threat condition (M = 3.11, SD = 0.82) was significantly more than in control condition (M = 2.85, SD = 0.72), p = 0.028. Additionally, a bootstrapping mediation analysis (model 4, 5000 iterations) showed that the effect of perceived robot identity threat on workplace objectification was mediated by sense of control, b = 0.116, 95% CI = [0.027, 0.215].

The third study also consists of three sub-studies. Based on the three compensatory control strategies proposed by the control compensation theory, in addition to affirming nonspecific structure, this study tries to further explore the moderating effect of personal agency, external agency, and specific structure. As predicted, personal agency played a moderating role in the effect of perceived robot identity threat on workplace objectification. Specifically, in low personal agency condition, perceived robot identity threat had a significant effect on workplace objectification (b = 0.57, SE = 0.17, t = 3.30, p = 0.001), while this effect was not significant in high personal agency condition (b = −0.10, SE = 0.16, t = −0.62, p = 0.536) (Study 3a). In addition, external agency also significantly moderated the relationship between perceived robot identity threat and workplace objectification. Specifically, in low external agency condition, perceived robot identity threat had a significant effect on workplace objectification (b = 0.18, SE = 0.06, t = 2.63, p = 0.004), while this effect was not significant in high personal agency condition (b = 0.01, SE = 0.06, t = 1.10, p = 0.920) (Study 3b). Similarly, Study 3c revealed that specific structure also significantly moderated the relationship between perceived robot identity threat and workplace objectification. Specifically, in low external agency condition, perceived robot identity threat had a significant effect on workplace objectification (b = 0.24, SE = 0.07, t = 3.64, p < 0.001), while the effect was not significant in high personal agency condition (b = −0.02, SE = 0.07, t = −0.27, p = 0.784).

The main findings of this paper can be summarized as follows. First, perceived robot threat, especially identity threat, leads to an increase in workplace objectification. Second, the sense of control plays a mediating role in the effect of perceived robot threat (mainly identity threat) on workplace objectification. Specifically, the higher the perceived robot identity threat, the lower the sense of control, and the more serious the workplace objectification. Third, the other three strategies proposed by compensatory control theory, namely strengthening personal agency, supporting external agency and affirming specific structure, can moderate the effect of perceived robot threat on workplace objectification.

The main theoretical contributions of this paper are as follows. First, it reveals the negative influence of robots on interpersonal relationships and their psychological mechanism. Second, it extends the applicability of compensatory control theory to the field of artificial intelligence by proposing and verifying that perceived robot threat increases workplace objectification through compensatory control. Third, the relationship between different compensation control strategies is discussed, and the moderating model of perceived robot threat affecting workplace objectification is proposed and verified. The main practical contributions are twofold. First, it provides insights into the anthropomorphic design of robots. Second, it helps us to better understand, anticipate and mitigate the negative social impact of robots.

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The “far dog, near cat” effect in stray animal charity rescue and its mechanism

LIU Wumei, WANG Lu

Acta Psychologica Sinica 2024, 56 (6): 777-798. DOI: 10.3724/SP.J.1041.2024.00777

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While past pro-social research has focused on charitable donations to humans, we know little about charitable assistance for stray animals. However, investigating the factors that promote human’s assistance to stray animals is of great practical importance. Currently, an increasing number of organizations and platforms are involving themselves in rescuing stray animals. When these organizations and platforms present animal rescue information, the information ad contains both animal type and spatial distance. Therefore, to address this research gap, this paper aims to study how animal type and spatial distance jointly influence consumers’ willingness to rescue stray animals, as well as the mechanisms and boundary conditions.

We propose a novel “far dog, near cat” effect. Specifically, we predict that under the near spatial distance, rescuing cat (versus rescuing dog) increases consumers’ rescuing willingness, whereas under the far spatial distance, rescuing dog (versus rescuing cat) increases consumers’ rescuing willingness. To test this effect, we conducted a total of nine experiments (N = 2848), including one implicit association test, one field experiment, one laboratory experiment, and six online experiments in different scenarios. We determined sample size of each experiment using G*power calculator.

Overall, this study found that cats were more compatible with proximal spatial distance, while dogs were more compatible with distal spatial distance (Experiment 1a, 1b). Therefore, presenting a stray cat (vs. a stray dog) in the proximal spatial-distance ad triggered consumers’ higher willingness to rescue the animal, while presenting a stray dog (vs. a stray cat) in the distal spatial-distance ad triggered consumers’ higher willingness to rescue the animal (Experiments 2-5). We further found that processing fluency mediated the “far dog, near cat” effect (Experiments 4-5). In addition, we found that the “far dog, near cat” effect was moderated by consumers’ thinking styles such that the "far dog, near cat" effect was evident when consumers adopted affective thinking style and disappeared when consumers adopted cognitive thinking style (Experiment 6).

Study 1a recruited 188 university students (76.1% female, M_age = 23.31 years, SD = 2.43 years) and conducted a 2 (animal type: cat vs. dog) × 2 (spatial distance: near vs. far) repeated-measures ANOVA with average response time as the dependent variable. The results showed a significant interaction effect, F(1, 186) = 16.08, p < 0.001, η²_p = 0.080. Further simple effects analysis revealed that participants responded faster to words indicating near spatial distance when viewing cats compared to dogs (M_cat = 819.86 ms, SD = 182.05 vs. M_dog = 908.99 ms, SD = 279.29), F(1, 186) = 6.72, p = 0.010, η²_p = 0.035. Additionally, participants responded faster to words indicating far spatial distance when viewing dogs compared to cats (M_cat = 961.97 ms, SD = 362.12 vs. M_dog = 862.05 ms, SD = 294.54), F(1, 186) = 4.31, p = 0.039, η²_p = 0.023. A similar analysis with average accuracy rate as the dependent variable also showed a significant interaction effect, F(1, 186) = 4.75, p = 0.031, η²_p = 0.025. Further simple effects analysis showed that compared to seeing cats, participants had a higher accuracy rate for far spatial distance words when seeing dogs (M_cat = 0.94 (94%), SD = 0.12 vs. M_dog = 0.98 (98%), SD = 0.07), F(1, 186) = 4.68, p = 0.032, η²_p = 0.025; whereas the accuracy rate for near spatial distance words was higher when seeing cats compared to dogs, but this difference was not significant (M_cat = 0.98 (98%), SD = 0.07 vs. M_dog = 0.97 (97%), SD = 0.08), F(1, 186) = 0.58, p = 0.448.

Study 1b involved 200 participants from the Credamo survey platform (M_age = 30.14 years, SD = 8.96 years, 68.5% female). The results indicated that participants who saw cat-related content chose images with closer spatial distances compared to those who saw dog-related content (M_cat= 1.24, SD = 0.90 vs. M_dog= 5.23, SD = 4.31), F(1, 198)= 82.26, p < 0.001, η²_p = 0.294. Similarly, the chosen images of participants in the cat group showed closer spatial distances between people and animals compared to those chosen by the dog group (M_cat= 1.63, SD = 0.96 vs. M_dog= 3.17, SD = 1.45), F(1, 198)= 78.41, p < 0.001, η²_p = 0.284.。

Study 2 had 310 participants (M_age = 20.51 years, SD = 1.81 years, 53.2% female) and conducted a 2 (animal type: stray cat vs. stray dog) × 2 (spatial distance: near vs. far) ANOVA, revealing a significant interaction effect on the willingness to participate in animal rescue activities, F(1, 306) = 8.57, p < 0.001, η²_p = 0.027. Further simple effects analysis indicated that at a close spatial distance, participants were significantly more willing to spend time on animal rescue activities for stray cats than for stray dogs (M_dog = 52.12, SD = 34.93 vs. M_cat = 63.28, SD = 38.87), F(1, 306) = 4.25, p = 0.040, η²_p = 0.014. Conversely, at a far spatial distance, participants' willingness to spend time on animal rescue activities was significantly higher for stray dogs than for stray cats (M_dog = 63.12, SD = 31.94 vs. M_cat = 51.04, SD = 32.65), F(1, 306) = 4.33, p = 0.038, η²_p = 0.014. When willingness to purchase animal food was used as the dependent variable, a 2 (animal type: cats vs. dogs) × 2 (spatial distance: close vs. far) factorial between-subjects analysis of variance showed a significant interaction effect, F (1, 306) = 10.88, p = 0.001, η²_p = 0.034. Further simple effects analysis revealed that at a close spatial distance, participants' willingness to purchase food was significantly higher for stray cats than for stray dogs (M_dog = 4.39, SD = 1.24 vs. M_cat = 4.79, SD = 1.14), F(1, 306) = 4.45, p = 0.036, η²_p = 0.014. However, at a far spatial distance, participants' willingness to purchase food was significantly higher for stray dogs than for stray cats (M_dog = 4.89, SD = 1.15 vs. M_cat = 4.37, SD = 1.39), F(1, 306) = 6.47, p = 0.011, η²_p = 0.021.

Study 3 recruited 317 participants (M_age = 31.45 years, SD = 8.48 years; 56.5% female) and used willingness to help as the dependent variable in a 2 (type of animal: stray cats vs. stray dogs) × 2 (spatial distance: near vs. far) factorial between-subjects ANOVA. The results indicated a significant interaction effect, F(1, 313) = 33.29, p < 0.001, η²_p = 0.096. Further simple effects analysis revealed that at a near spatial distance, participants' willingness to help stray cats was significantly higher than their willingness to help stray dogs (M_dog = 5.33, SD = 1.00 vs. M_cat = 5.79, SD = 0.98), F(1, 313) = 7.30, p = 0.007, η²_p = 0.023. Conversely, at a far spatial distance, participants' willingness to help stray dogs was significantly higher than their willingness to help stray cats (M_dog = 5.79, SD = 1.09 vs. M_cat = 4.87, SD = 1.16), F(1, 313) = 7.30, p < 0.001, η²_p = 0.087.

As a supplementary experiment to Experiment 3, 306 participants took part in study 3S on the Credamo platform (M_age = 30.95 years, SD = 8.01 years, 71.2% female). This experiment also focused on the willingness to adopt as the dependent variable, using the same 2 (type of animal: stray cats vs. stray dogs) × 2 (spatial distance: near vs. far) between-subjects factorial design. The results showed a significant interaction effect, F(1, 302) = 13.48, p < 0.001, η²_p = 0.043. Further analysis of simple effects indicated that at a near spatial distance, participants' willingness to adopt stray cats was significantly higher than their willingness to adopt stray dogs (M_dog = 5.67, SD = 0.84 vs. M_cat = 5.97, SD = 0.63), F(1, 302) = 4.13, p = 0.043, η²_p = 0.013. However, at a far spatial distance, participants' willingness to adopt stray dogs was significantly higher than their willingness to adopt stray cats (M_dog = 6.08, SD = 0.61 vs. M_cat = 5.65, SD = 1.20), F(1, 302) = 10.17, p = 0.002, η²_p = 0.033.

Study 4 was a pre-registered study involving 300 college students (M_age = 22.94 years, SD = 3.34 years, 64.7% female). It utilized a 2 (type of animal: stray cats vs. stray dogs) × 2 (spatial distance: near vs. far) between-subjects factorial design, with donation amount as the dependent variable. The results showed a significant interaction effect between the type of animal and spatial distance, F(1, 296) = 9.51, p = 0.002, η²_p = 0.031. Further simple effects analysis revealed that at a close spatial distance, participants donated significantly more to stray cats than to stray dogs (M_dog = 45.70, SD = 28.43 vs. M_cat = 56.93, SD = 34.50), F(1, 296) = 4.79, p = 0.029, η²_p = 0.016. Conversely, at a far spatial distance, donations were significantly higher for stray dogs than for stray cats (M_dog = 52.47, SD = 32.15 vs. M_cat = 41.54, SD = 29.12), F(1, 296) = 4.72, p = 0.031, η²_p = 0.016. Additionally, using donation amount as the dependent variable, type of animal as the independent variable, spatial distance as a moderator, and processing fluency as a mediator, a moderated mediation analysis was conducted using PROCESS (Model 8, 5,000 bootstraps; Hayes, 2018). The results indicated that processing fluency mediated the interaction between animal type and spatial distance on the donation amount (indirect effect = -3.64, SE = 1.79, 95% CI = [-7.6767, -0.6922], not including 0). Further analysis showed that the indirect effect of processing fluency was significant at a close spatial distance (indirect effect = 1.86, SE = 1.03, 95% CI = [0.2001, 4.2033], not including 0) and also significant at a far spatial distance (indirect effect = -1.78, SE = 1.13, 95% CI = [-4.4359, -0.0556], not including 0).

Study 4S, serving as a supplementary study to study 4, had 280 participants (M_age = 41.84 years, SD = 15.64 years, 58.9% female). The study conducted a 2 (animal type: stray cat vs. stray dog) × 2 (spatial distance: near vs. far) analysis of variance with the intention to help as the dependent variable. The results showed a significant interaction F (1, 276) = 9.42, p = 0.002, η²_p = 0.033. Further analysis of simple effects revealed that at a closer spatial distance, participants were more willing to assist stray cats over stray dogs (M_dog = 4.32, SD = 1.47 vs. M_cat = 4.93, SD = 1.64), F (1, 276) = 3.87, p = 0.050, η²_p = 0.014; whereas at a farther spatial distance, the preference shifted towards helping stray dogs rather than cats (M_dog = 4.94, SD= 1.58 vs. M_cat = 4.30, SD = 1.84), F (1, 280) = 5.87, p = 0.016, η²_p = 0.021. Additionally, with the willingness to help as the dependent variable, type of animal as the independent variable, spatial distance as a moderating variable, and processing fluency as a mediating variable, a moderated mediation analysis was conducted using PROCESS (Model 8, 5,000 bootstraps; Hayes, 2018). The results showed that processing fluency mediates the effect of the interaction between type of animal and spatial distance on the willingness to help (indirect effect = 0.13, SE = 0.08, 95% CI = [0.0036, 0.3206], not including 0).

Study 5 involved 308 participants (M_age = 30.95 years, SD = 10.53 years, 57.1% female) using adoption intention as the dependent variable, and conducted a 2 (animal type: stray cats vs. stray dogs) × 2 (spatial distance: near vs. far) between-subjects factorial ANOVA. The results showed a significant interaction effect, F(1, 304) = 51.49, p < 0.001, η²_p = 0.145. Further simple effects analysis revealed that at a close spatial distance, participants' willingness to adopt stray cats was significantly higher than for stray dogs (M_dog = 5.44, SD = 1.20 vs. M_cat = 6.25, SD = 0.65), F(1, 304) = 30.26, p < 0.001, η²_p = 0.091; whereas at a far spatial distance, participants' willingness to adopt stray dogs was significantly higher than for stray cats (M_dog = 6.25, SD = 0.65 vs. M_cat = 5.46, SD = 0.98), F(1, 304) = 21.68, p < 0.001, η²_p = 0.067. Additionally, using adoption willingness as the dependent variable, type of animal as the independent variable, processing fluency as the mediator, and spatial distance as the moderator, a moderated mediation analysis was conducted using PROCESS (Model 8, 5,000 bootstraps; Hayes, 2018). The results indicated that processing fluency mediated the interaction between animal type and spatial distance on adoption willingness (indirect effect = -0.24, SE = 0.10, 95% CI = [-0.4701, -0.0745], not including 0). The mediating effect of processing fluency was significant at a close spatial distance (indirect effect = 0.10, SE = 0.06, 95% CI = [0.0027, 0.2320], not including 0) and also significant at a far spatial distance (indirect effect = -0.14, SE = 0.07, 95% CI = [-0.2992, -0.0266], not including 0).

Study 6 aimed to examine the moderation of thinking styles, recruiting a total of 639 participants (M_age = 31.29 years, SD = 8.77 years, 65.9% female). The study used adoption intention as the dependent variable to conduct a 2 (animal type: stray cats vs. stray dogs) × 2 (spatial distance: near vs. far) × 2 (thinking style: affective vs. cognitive) three-factor between-subjects ANOVA. The results indicated a significant three-way interaction, F(1, 631) = 23.26, p < 0.001, η²_p = 0.036. Further simple effect analyses revealed that, after priming a cognitive thinking style, the interaction between animal type and spatial distance was not significant, F(1, 631) = 1.56, p = 0.180. When the spatial distance was near, participants' adoption intentions for stray cats and dogs were similar (M_dog = 5.66, SD = 1.28 vs. M_cat = 5.92, SD = 0.80), F(1, 631) = 2.98, p = 0.085. Similarly, when the spatial distance was far, participants' adoption intentions were also similar for both animal types (M_dog = 5.60, SD = 1.02 vs. M_cat = 5.58, SD = 0.92), F(1, 631) = 0.03, p = 0.865. After priming an affective thinking style, the interaction between animal type and spatial distance was significant, F(1, 631) = 57.50, p < 0.001, η²_p = 0.083. Specifically, when the spatial distance was near, participants' adoption intention for stray cats was significantly higher than for stray dogs (M_dog = 5.60, SD = 0.90 vs. M_cat = 6.25, SD = 0.56), F(1, 631) = 19.02, p < 0.001, η²_p = 0.029. Conversely, when the spatial distance was far, participants' adoption intention for stray dogs was significantly higher than for stray cats (M_dog = 6.30, SD = 0.39 vs. M_cat = 5.24, SD = 1.22), F(1, 631) = 51.37, p < 0.001, η²_p = 0.075. Additionally, with adoption intention as the dependent variable, animal type as the independent variable, processing fluency as the mediating variable, spatial distance as the first-level moderator, and thinking style as the second-level moderator, a moderated mediation analysis was conducted using PROCESS (Model 12, 5000 bootstraps; Hayes, 2018). The results showed that processing fluency mediated the effect of the interaction among animal type, spatial distance, and thinking style on adoption intention (indirect effect = -0.16, SE = 0.08, 95% CI = [-0.3334, -0.0157], not including 0). Under a cognitive thinking style: at near spatial distances, the mediating effect of processing fluency was not significant (indirect effect = -0.01, SE = 0.03, 95% CI = [-0.0638, 0.0712], including 0); at far spatial distances, the mediating effect was also not significant (indirect effect = -0.001, SE = 0.03, 95% CI = [-0.0680, 0.0668], including 0). Under an affective thinking style: at near spatial distances, the mediating effect of processing fluency was significant (indirect effect = 0.08, SE = 0.04, 95% CI = [0.0056, 0.1642], not including 0); at far spatial distances, the mediating effect was also significant (indirect effect = -0.08, SE = 0.05, 95% CI = [-0.1879, -0.0007], not including 0).

This paper has significant theoretical contributions and practical implications. Theoretically, this study focuses on stray animals as a novel object of charitable donations and builds the implicit linkage between animal type and spatial distance. Also, this study identifies the “far dog, near cat” effect in stray animal rescue, adding to past pro-social literature in general and donation literature in particular. Practically, the “far dog, near cat” effect we identified in this paper can guide charitable organizations how to present animal-rescue information appropriately.

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Robots abide by ethical principles promote human-robot trust? The reverse effect of decision types and the human-robot projection hypothesis

WANG Chen, CHEN Weicong, HUANG Liang, HOU Suyu, WANG Yiwen

Acta Psychologica Sinica 2024, 56 (2): 194-209. DOI: 10.3724/SP.J.1041.2024.00194

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Asimov's Three Laws of Robotics are the basic ethical principles of artificial intelligent robots. The ethic of robots is a significant factor that influences people’s trust in human-robot interaction. Yet how it affects people's trust, is poorly understood. In this article, we present a new hypothesis for interpreting the effect of robots’ ethics on human-robot trust—what we call the human-robot projection hypothesis (HRP hypothesis). In this hypothesis, people are based on their intelligence, e.g., intelligence for cognition, emotion, and action, to understand robots’ intelligence and interact with them. We propose that compared with robots that violate ethical principles, people project more mind energy (i.e., the level of mental capacity of humans) onto robots that abide by ethical principles, thus promoting human-robot trust.
In this study, we conducted three experiments to explore how presenting scenarios where a robot abided by or violated Asimov’s principles would affect people’s trust in the robot. Meanwhile, each experiment corresponds to one of Asimov’s principles to explore the interaction effect of the types of robot’s decisions. Specifically, all three experiments were two by two experimental designs. The first within-subjects factor was whether the robot being interacted with had abided by Asimov’s principle with a “no harm” core element. The second within-subjects factor was the types of robot’s decision, with corresponding differences in Asimov’s principles among different experiments (Experiment 1: whether the robot takes action or not; Experiment 2: whether the robot obeys human’s order or not; Experiment 3: whether the robot protects itself or not). We assessed the human-robot trust by using the trust game paradigm.
Experiments 1-3 consistently showed that people were more willing to trust robots that abided by ethical principles compared with those who violated. We also found that human-robot projection played a mediating role, which supports the HRP hypothesis. In addition, the significant interaction effects between the type of robot’s decision and robot abided by or violated Asimov’s principle existed in all three experiments. The results of Experiment 1 showed that action robots got more trust than inaction robots when abided by the first principle, whereas inaction robots got more trust than action robots when they violated the first principle. The results of Experiment 2 showed that disobeyed robots got less trust than obeyed robots. The detrimental effect was greater in scenarios where robots violated the second principle than in those who abided. The results of Experiment 3 showed that compared with robots that violated the third principle, the trust-promoting effect of protecting itself versus destroying itself was stronger among those who abided. The above results indicated that the reverse effects of decision types existed in both Experiments 1 and 3. Finally, the cross-experimental analysis showed that: (1) When robots abided by ethical principles, their inaction and disobedience still compromise human-robot trust. When robots violated ethical principles, their obedience incurs the least loss of human-robot trust, while their action and disobedience incur a relatively severe loss of human-robot trust. (2) When the ethical requirements of different robotic laws conflict, there was no significant difference between the importance of not harming humans and obeying human orders in terms of the human-robot trust, and both were more important than protecting robots themselves.
This study helps to understand the impact of robotic ethical decision-making on human-robot trust and the important role of human-robot projection, which might have important implications for future research in human-robot interaction.

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The impacts of music training and music sophistication on empathy

HUA Shan, JIANG Xintong, GAO Yangzhenyu, MU Yan, DU Yi

Acta Psychologica Sinica 2025, 57 (4): 544-558. DOI: 10.3724/SP.J.1041.2025.0544

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Music has long been recognized for fostering social bonds, with potential benefits for prosocial behaviors and empathy. Empathy, a key predictor of prosocial behaviors, encompasses both cognitive and affective components, involving the mentalizing and sharing of others’ emotional states. While musical training has been linked to increased empathy and prosocial behaviors, the influence of musical sophistication—a comprehensive measure of musical experience—on empathy is less well understood. Moreover, the specific components and pathways through which musical experience influences empathy remain unclear, with existing research relying largely on subjective measures and lacking objective behavioral evidence.

To address these gaps, we conducted two studies using musical training and musical sophistication as indicators of musical experience to explore their impact on trait and state empathy through questionnaires and a behavioral experiment.

In Study 1, we examined the relationship between musical training, musical sophistication and empathy in 130 musicians and 121 non-musicians, using standardized measures including the Goldsmiths Musical Sophistication Index (Gold-MSI) and Interpersonal Reactivity Index (IRI). Musicians scored significantly higher than non-musicians in cognitive empathy components (Perspective Taking and Fantasy). After controlling for gender, musical sophistication was positively correlated with cognitive empathy components (Perspective Taking and Fantasy) and an affective empathy component (Empathic Concern). Furthermore, after controlling for gender, openness, psychological states (depression, anxiety, alexithymia), and subjective social status, path analysis revealed that musical sophistication directly influenced cognitive empathy (Fantasy), while musical training indirectly influenced it via the mediating effect of music sophistication.

Study 2 employed a pain empathy paradigm to assess empathic responses in 59 musicians and 61 non-musicians. Musicians demonstrated a higher alignment between ratings of their own and others' pain when observing others in pain, indicating greater empathy. The musicians' empathic response to pain was serially mediated by music sophistication and Fantasy in cognitive empathy. However, musical sophistication alone did not significantly affect pain empathy when the influence of musical training on musical sophistication was controlled.

In summary, both long-term musical training and musical sophistication positively impact cognitive empathy. Specifically, musical training indirectly enhances the cognitive component (Fantasy) of trait empathy by improving musical sophistication, thereby fostering greater empathy for others’ pain. In contrast, musical sophistication has a direct and stable relationship with cognitive empathy. These findings support the “social bonding” hypothesis, highlighting music’s role in developing empathy and interpersonal skills.

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How semantic prosody is acquired in novel word learning: Evidence from the “Double-Date Tree” Effect

WU Shiyu, LI Zan

Acta Psychologica Sinica 2024, 56 (5): 531-541. DOI: 10.3724/SP.J.1041.2024.00531

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Generally, a word’s meaning consists of at least two components. The first is denotative meaning, representing the definitional meaning found in dictionaries and serving as the word’s fundamental meaning. The second component involves semantics that a word “absorbs” from its linguistic context, not constrained by definitions; this is known as semantic prosody, described as a consistent aura of meaning with which a form is imbued by its collocates. While theories and empirical studies have shed light on mechanisms supporting the acquisition of the first word meaning component, the acquisition of the connotative meaning engendered by semantic prosody has been overlooked. It remains unclear whether readers can unconsciously acquire the semantic prosody (or emotional connotations) of a novel word after encountering it consistently in a context with a strong emotional polarity.
Against this backdrop, we conducted a word learning experiment, manipulating context emotionality (negative versus neutral versus positive) and context variability (same-repeated versus varied contexts) as crucial contextual variables. This aimed to address two understudied questions in vocabulary acquisition: (1) Does transfer of affect to a word from its linguistic context take place through reading exposures, facilitating the acquisition of semantic prosody for the word? If so, is such transfer influenced by context variability? (2) Does the acquired semantic prosody for words affect the acquisition of word forms and meanings, and is this acquisition modulated by context variability? This experiment involved two sessions: a reading-and-learning phase and a testing phase. During the reading-and-learning session, participants read emotionally charged passages, simultaneously learning embedded target words. The testing session included an immediate posttest, incorporating four vocabulary tests—valence rating, orthographic choice, definition matching, and definition generation. A total of 196 Chinese speakers participated in the experiment.
Mixed-effects models were utilized to analyze data from the valence rating task and the other three vocabulary knowledge tests. The findings revealed that, within the same-repeated context, manipulating context emotionality (positive versus neutral versus negative) significantly influenced valence ratings, showing significantly higher ratings in the positive condition compared to neutral and negative conditions. Conversely, in the varied context, no significant differences in valence ratings were observed. This result supports the hypothesis of the “Double-Date Tree” effect, emphasizing the effect of repetitive texts compared to multiple texts. However, in the varied context, valence ratings played a role in influencing participants’ performances in the vocabulary tests, leading to better outcomes as valence ratings increased. In the same-repeated context, valence ratings had minimal effect on accuracy in the orthographic choice test and the definition prompting test.
We posit that the effective mechanism for learning the semantic-prosody-engendered connotations of words involves the transfer of affect from their collocations. However, this transfer seems to be contingent on context variability, occurring only in the same-repeated context and not in the varied context. Furthermore, we illustrate that the emotionality of context influences the quality of both orthographic and semantic word learning, with words being better learned in positive contexts as opposed to negative or neutral ones.

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Understanding the Rise of Unique Names: The Emphasis on Uniqueness Matters

BAO Han-Wu-Shuang, CAI Huajian, JING Yiming

Acta Psychologica Sinica 2024, 56 (7): 954-963. DOI: 10.3724/SP.J.1041.2024.00954

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Uncommon personal names have become increasingly popular in many countries and cultures over the past decades. However, little is known about the causes. We propose that the emphasis on uniqueness, manifested both as a cultural value at the macro level and as an individual need at the micro level, may account for the widely observed increase in unique-naming practices. We tested these hypotheses in China. Study 1 found that the increasing cultural emphasis on uniqueness (rather than on independence or competition), as a Granger cause, explained the increasing name uniqueness. Study 2 revealed that the increasing individual need for uniqueness (rather than narcissism or self-esteem) explained the higher preference for unique baby names among younger than older generations. Study 3 showed that, in actual naming practices, younger parents emphasized name uniqueness (rather than modernity, positivity, or other features) more than older cohorts. These findings convergently support our hypotheses, highlighting the importance of identifying specific mechanisms underlying psychological and behavioral changes, rather than assuming the rising individualism as a general explanation.

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Relationship between adolescents’ smartphone stress and mental health: Based on the multiverse-style analysis and intensive longitudinal method

HUANG Shunsen, LAI Xiaoxiong, ZHANG Cai, ZHAO Xinmei, DAI Xinran, QI Mengdi, WANG Huanlei, WANG Wenrong, WANG Yun

Acta Psychologica Sinica 2024, 56 (6): 745-758. DOI: 10.3724/SP.J.1041.2024.00745

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To explore the relationship and mechanisms between smartphone stress and adolescent mental health, Study 1 examined the robust relationship between smartphone stress and adolescent mental health in a sample of 74,182 adolescents using multiverse-style analysis; Study 2 conducted an intensive longitudinal survey over 35 days with 507 adolescents to investigate the mechanisms through which smartphone stress affects their mental health. Study 1 found that more than half of the adolescents reported experiencing stress from smartphones, and there was a robust negative correlation between smartphone stress and mental health, deserving attention from researchers and society. Study 2 identified that intensity/fluctuation of negative emotions and rumination mediate the effect between smartphone stress and mental health, with differences in how these factors affect positive or negative dimensions of mental health. This research extended, for the first time, the “stress-cognition/emotion” theory and the “media use-digital stress-mental health” model in depth and breadth, and provided new perspectives and a basis for promoting youth’s mental health development.

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The influence of positive emotion with varying intensities of approach motivation on false memory and its neural mechanisms: A study based on semantic-related false memory

ZHANG Huan, QIN Xiquan, LIU Yu, LIN Lin, WU Jie

Acta Psychologica Sinica 2025, 57 (3): 349-362. DOI: 10.3724/SP.J.1041.2025.0349

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Emotions can influence false memories. Previous research has primarily focused on the effects of emotional valence and arousal on false memories. To date, the motivational dimension of emotions and its neural mechanisms in influencing false memories remain unclear. This study induced participants to experience positive emotions with varying intensities of approach motivation using the facial-expression-gesture method, and combined it with functional near-infrared spectroscopy (fNIRS) to investigate changes in cortical oxyhemoglobin concentration during the learning of DRM word lists under high, medium, and low intensities of approach motivation positive emotions, as well as the impact of these changes on semantically related false memories. The results showed that the high approach condition produced more false memories. Additionally, in some areas of the left frontal and temporal lobes, the brain activation levels under the high approach condition were significantly higher than those under medium and low approach conditions, indicating that high approach conditions elicit greater brain activation in specific regions. Correlation analysis results indicated that under high approach conditions, the activation levels in the left inferior frontal gyrus and temporal lobe were significantly positively correlated with the rate of false memories; under low approach conditions, the activation levels in the left inferior temporal gyrus were significantly negatively correlated with false memories. These results suggest that positive emotions with different intensities of approach motivation affect the generation of false memories, and the intensity of approach motivation affects the strength of activation in semantically related brain regions, with the left inferior temporal gyrus showing a dissociative effect in the process of false memory generation under different intensities of approach motivation positive emotions.

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Automated scoring of open-ended situational judgment tests

XU Jing, LUO Fang, MA Yanzhen, HU Luming, TIAN Xuetao

Acta Psychologica Sinica 2024, 56 (6): 831-844. DOI: 10.3724/SP.J.1041.2024.00831

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Situational Judgment Tests (SJTs) have gained popularity for their unique testing content and high face validity. However, traditional SJT formats, particularly those employing multiple-choice (MC) options, have encountered scrutiny due to their susceptibility to test-taking strategies. In contrast, open-ended and constructed response (CR) formats present a propitious means to address this issue. Nevertheless, their extensive adoption encounters hurdles primarily stemming from the financial implications associated with manual scoring. In response to this challenge, we propose an open-ended SJT employing a written-constructed response format for the assessment of teacher competency. This study established a scoring framework leveraging natural language processing (NLP) technology to automate the assessment of response texts, subsequently subjecting the system's validity to rigorous evaluation. The study constructed a comprehensive teacher competency model encompassing four distinct dimensions: student-oriented, problem-solving, emotional intelligence, and achievement motivation. Additionally, an open-ended situational judgment test was developed to gauge teachers' aptitude in addressing typical teaching dilemmas. A dataset comprising responses from 627 primary and secondary school teachers was collected, with manual scoring based on predefined criteria applied to 6, 000 response texts from 300 participants. To expedite the scoring process, supervised learning strategies were employed, facilitating the categorization of responses at both the document and sentence levels. Various deep learning models, including the convolutional neural network (CNN), recurrent neural network (RNN), long short-term memory (LSTM), C-LSTM, RNN+attention, and LSTM+attention, were implemented and subsequently compared, thereby assessing the concordance between human and machine scoring. The validity of automatic scoring was also verified.
This study reveals that the open-ended situational judgment test exhibited an impressive Cronbach's alpha coefficient of 0.91 and demonstrated a good fit in the validation factor analysis through the use of Mplus. Criterion-related validity was assessed, revealing significant correlations between test results and various educational facets, including instructional design, classroom evaluation, homework design, job satisfaction, and teaching philosophy. Among the diverse machine scoring models evaluated, CNNs have emerged as the top-performing model, boasting a scoring accuracy ranging from 70% to 88%, coupled with a remarkable degree of consistency with expert scores (r = 0.95, QWK = 0.82). The correlation coefficients between human and computer ratings for the four dimensions—student-oriented, problem-solving, emotional intelligence, and achievement motivation—approximated 0.9. Furthermore, the model showcased an elevated level of predictive accuracy when applied to new text datasets, serving as compelling evidence of its robust generalization capabilities.
This study ventured into the realm of automated scoring for open-ended situational judgment tests, employing rigorous psychometric methodologies. To affirm its validity, the study concentrated on a specific facet: the evaluation of teacher competency traits. Fine-grained scoring guidelines were formulated, and state-of-the-art NLP techniques were used for text feature recognition and classification. The primary findings of this investigation can be summarized as follows: (1) Open-ended SJTs can establish precise scoring criteria grounded in crucial behavioral response elements; (2) Sentence-level text classification outperforms document- level classification, with CNNs exhibiting remarkable accuracy in response categorization; and (3) The scoring model consistently delivers robust performance and demonstrates a remarkable degree of alignment with human scoring, thereby hinting at its potential to partially supplant manual scoring procedures.

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