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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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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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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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 （727）

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 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 Framing Effect of Cross-Period Temporal Choice in the Loss Domain Will Influence the Preference for Debt-Swapping Decisions

MA Jia-Tao, LI Shu, HE Guibing

Acta Psychologica Sinica 2026, 58 (4): 651-666. DOI: 10.3724/SP.J.1041.2026.0651

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Framing effects, which violate the axioms of rational decision-making, represent a robust psychological phenomenon. This study investigates whether framing effects exist in cross-period temporal choice in the loss domain and explores their implications for debt swap policies. The findings reveal two key insights: (1) For a single debt program with a fixed total amount and maturity date, presentation frames significantly influenced debtors’ acceptance level of the debt repayment program. Specifically, low-frequency frames (e.g., annual payments) yielded a significantly higher acceptance level of the debt repayment program compared to high-frequency frames (e.g., weekly payments); (2) For binary-choice debt programs with constant total amounts but varying maturity dates, framing effects again proved significant. Compared to high-frequency frames/conventional timelines, low-frequency frames/compressed timelines made debtors more inclined to accept the initial debt program with higher interest rates and shorter terms. The observed preferences were consistent with predictions of the Graph-Edited Equate-to-Differentiate Model. This study contributes to a deeper understanding of cross-period temporal choice in the loss domain, enriches the “temporal nudge toolbox” with novel interventions, and provides crucial psychological evidence to inform the evaluation of debt swap policies and the optimization of debt management strategies.

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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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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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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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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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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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When AI “possesses” personality: Roles of good and evil personalities influence moral judgment in large language models

JIAO Liying, LI Chang-Jin, CHEN Zhen, XU Hengbin, XU Yan

Acta Psychologica Sinica 2025, 57 (6): 929-946. DOI: 10.3724/SP.J.1041.2025.0929

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At the intersection of technology and morality, a critical question arises: Can large language models (LLMs) simulate good and evil personalities, and does this capacity influence their performance in moral judgment tasks? This study investigated the moral judgment characteristics of LLMs when simulating different good and evil personalities, as well as the similarities and differences between these patterns and those of humans. Across two studies, we analyzed moral judgment data generated by two LLMs—ERNIE 4.0 and GPT-4 (N = 4,832)—alongside responses from human participants (N = 370). The results revealed that: (1) LLMs are capable of successfully simulating varying levels of good and evil personalities; (2) the personality configuration significantly affects the moral judgments made by LLMs; and (3) a personality hierarchy emerges in the alignment between human and LLMs’ responses: good personality plays a more critical role than evil personality (inter-personality hierarchy), and within the good personality, conscientiousness and integrity dimension exerts the strongest influence (intra-personality hierarchy). This research constructed a theoretical model of good and evil personalities in LLMs under moral judgment tasks, contributing to a deeper understanding of how simulated personalities function in AI moral reasoning. The findings provided a theoretical foundation for promoting moral alignment in artificial intelligence systems.

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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

Abstract （439）

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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