Supervisor(s):Chinese Academy of Sciences Sponsor(s):Chinese Psychological Society; Institute of Psychology, Chinese Academy of Sciences ISSN:0439-755X CN:11-1911/B
Acta Psychologica Sinica is a scholarly journal sponsored by Chinese Psychological Society and Institute of Psychology, Chinese Academy of Sciences, co-sponsored by Department of Psychology, Chinese University of HongKong, published monthly by the Science Press.
It is to publish original empirical studies and theoretical papers in the broad field of psychology including cognitive and experimental psychology, developmental and educational psychology, physiological and medical psychology, management social psychology, psychological measure, psychological history and method et al.
Editor-in-chief ZHANG Kan, Institute of Psychology, Chinese Academy of Sciences, China Associate Editors FUNG Helene Hoi Lam, Department of Psychology, Chinese University of Hong Kong, China HAU Kit-Tai, Department of Educational Psychology, Chinese Univ
The plasticity of executive function (EF) has been discussed as a core topic in recent cognitive development research. However, inhibition training research remains inadequate. According to dimensional overlap theory, inhibition has two types: interference and response. The neural networks of the brain that respond to conflicts do not mature until early adulthood. By conducting a comparison of the plasticity of response inhibition between adolescents and adults, the applicable age group for response inhibition training is explored. Introducing online feedback as reinforcement improves the training effects and helps individuals to balance further accuracy and speed. Therefore, we added online feedback in the training groups but used the original Stop Signal task in the active control groups to investigate the training and transfer effects of this task with online feedback.This study included 194 participants (134 adults and 60 adolescents) that were divided into five groups: adult training group (
N = 47), adult active control group (
N = 45), adolescent training group (
N = 30), adolescent active control group (
N = 30), and passive control group (
N = 42). The response inhibition training consisted of nine sessions, and it was held three times a week. In each training session of the adult and adolescent training groups, participants were guided to finish eight blocks (100 trials in each block) of the Stop Signal task with online feedback. In the adult and adolescent active control groups, participants completed the same amount of the Stop Signal task without online feedback. The passive control group received no training. The participants’ inhibition, working memory, and fluid intelligence were measured before and after training through six tasks (e.g., Inhibition: Stop Signal task, Go/No-go task, and Stroop task; Working memory: 2-back Task and 3-back Task; and Fluid intelligence: Raven’s Standard Progressive Matrices). A 9 (all training sessions) × 2 (training group, active control group) × 2 (adult, adolescent) repeated measure ANOVA was used to test the training effects. Both age groups exhibited improved performances with the continuation of the training sessions. However, the adults performed significantly faster and more accurate than the adolescents. Next, four 2 (pretest, posttest) × 5 (all five groups) repeated measure ANOVA were conducted to test the transfer effects. The transfer effect results revealed that (1) on the Go/No-go task, both training groups showed significant improvement; (2) on the Stroop task, only the adolescent training group showed significant improvement; (3) on the 2-back task, both training groups and the adult active control group improved significantly; (4) on the 3-back task, only the adolescent training group gained significant transfer effects; and (5) on the Raven’s Standard Progressive Matrices, no group showed significant improvement. To sum up, the results suggest that the Stop Signal training task with online feedback has produced training effects on both age groups, and the transfer effects are influenced by the age difference of cognitive plasticity and the nature of the task. Thus, adding online feedback to computerized training can effectively improve the training and the transfer effects. Finally, inhibition training has a more formative effect on the pre-adult age.
In the last few years, marketing scholars have been showing increasing interest in examining how crowding affects consumers’ emotions and behaviors. As a result, empirical literature on crowding has been growing rapidly. However, the crowding literature in Marketing has reported many inconsistent findings which need to be reconciled. The current meta-analysis paper aims to find out the reasons for heterogeneity in the findings of previous studies on crowding. In this meta-analysis, the authors analyzed 149 effect sizes from 38 Eastern and Western empirical studies and 81 samples. Each author independently coded the data and discrepancies were resolved through discussion. Based on the measures of crowding used in each individual empirical paper, the authors coded two types of crowding, namely, social crowding and spatial crowding. First, the authors analyzed the effects of social crowding and spatial crowding on consumers’ emotional reactions and shopping reactions. Next, the authors examined the potential moderation effects of several contextual and methodological factors, including types of shopping environment, the reality of research context, and sources of research samples (Western countries vs. Eastern countries, students vs. non-students). This meta-analysis work obtained many interesting findings. First, this paper documented that social crowding significantly increased consumers’ negative emotions, but dramatically decreased consumers’ dominance. Social crowding was found to be positively correlated with the approach-related shopping responses (ρ = 0.208,
N = 28624), and negatively correlated with consumer attitudes and willingness to shop (ρ = −0.135,
N = 10094). Second, this paper documented that spatial crowding had a significant negative effect on avoidance-related shopping responses (ρ = −0.409,
N = 3223), but had no significant influence on the approach-related shopping responses. Furthermore, moderation analyses showed that some of the aforementioned main effects were significantly moderated by types of shopping environment (utilitarian vs. hedonic), the reality of the context (virtual vs. real), and sources of research samples (Western countries vs. Eastern countries, students vs. non-students). To summarize, this paper makes several important theoretical advances. First, drawing on several psychological theories on individuals’ reactions to the crowding environment, this paper builds a relatively unified research framework on consumers’ reactions to crowding. More importantly, this paper also tests this framework via meta-analyzing the effects of social crowding and those of spatial crowding on consumers’ emotional reactions and shopping-related behavioral responses, respectively. The results suggest that the overall influence of crowding on individuals’ emotion and behavior is not as large as that reported in previous studies. Second, by examining the moderation effects of several situational and methodology-related factors, this paper is able to explain why prior literature on crowding has reported inconsistent findings. Finally, this meta-analysis work also puts forth several intriguing and testable future research hypotheses. In addition to advancing theory, the current paper’s findings also have practical implications. Companies and managers should consider reducing consumers’ spatial crowding perceptions of the shopping environment. However, it is not wise for firms to universally adopt a policy of decreasing consumers’ perceptions of pedestrian volume.
Following errors, participants usually recruit more cognitive resources to change error-related behaviors. This phenomenon is termed the post-error adjustment. Generally, behavioral adjustments in post-error trials behave as slower subsequent responses and improved accuracy. It is worth noting that we cannot successfully perceive every error that we commit in daily life. Several studies found that post-error slowing occurred only after aware errors, suggesting that only aware errors contributed to the phenomenon of post-error adjustment. Moreover, these studies emphasized the role of top-down control in the processing of error awareness. However, a few studies came to the opposite conclusion, finding that the post-error adjustment could be modulated by unaware errors in an implicit manner. These studies emphasized the role of bottom-up control in the processing of error awareness. Notably, previous studies have demonstrated that the post-error adjustment involves both proactive and reactive cognitive control. Proactive control refers to a goal-driven manner that is actively maintained with sustained attention before the occurrence of cognitively demanding events. Reactive cognitive control refers to a bottom-up manner, in which attentional control is mobilized when the goal-related event is reactivated. Thus, whether different control strategies are adopted by aware and unaware errors remains unclear. To investigate the above issue, we recruited 36 participants to execute an error awareness task based on the go/no-go task. However, data from five participants were removed due to poor EEG records or poor behavioral performance. In the go/no-go error awareness task, participants were instructed to withhold their responses in certain circumstances. The first was when a word was presented on two consecutive trials, and the second was when the font color of the word and its meaning were inconsistent. Additionally, the usage of an error signal button might lead to a response bias toward signaling or not signaling an error. If participants tended to signal errors, they might signal their correct responses as errors, increasing the false alarm rates. If participants did not tend to signal errors, aware errors might be classed as unaware errors. In this case, the measurement of unaware errors might be contaminated by potential conscious error trials. Thus, participants were instructed to respond to indicate their perceived response accuracy in both error and correct cases during the rating screen in the current experiment. Since previous studies have found that neural oscillations reveal the processing of proactive and reactive cognitive control, the time-frequency analysis is conducted in this experiment. It has been suggested that the alpha band (8–14 Hz) reflects the trial-by-trial behavioral adjustment. Thus, alpha power is chosen as the neural indicator. As a result, the post-error reaction time indicated two dissociated behavior patterns with speeding up following aware errors and slowing down following unaware errors. However, accuracy in trials following aware and unaware errors was significantly higher than for trials following correct go. At the neural level, power of alpha waves (−500 to 500 ms) was stronger for aware errors than for unaware errors. Moreover, the alpha waves were activated before the subjective report of error awareness for aware errors, but the alpha waves were activated after the subjective report of error awareness for unaware errors. Current behavioral results showed that aware and unaware errors both successfully optimized post-error performance, but the two error types adopted different methods to adjust post-error behaviors. The time-frequency analysis revealed that aware errors led to sustained attention control after responses, but unaware errors led to temporary attention control induced by the subjective report of error awareness. Therefore, these findings might suggest that the adjustments following aware errors were based on a strategy such as proactive control, whereas the adjustments following unaware errors were based on a strategy such as reactive cognitive control.
The current research examines the influence of anticipated communication on creativity and the moderating role of construal levels in this process. Experiment 1 adopted a structured imagination task to explore the main effect of anticipated communication on creativity. The results of Experiment 1 showed that compared with the no anticipated communication group, the anticipated communication group showed higher creativity. Experiment 2 used a creative generation task to measure creativity and examined the moderating role of construal levels. Results of Experiment 2 suggested that when completing abstract and high construal-level tasks, the anticipated communication group showed higher creativity in dimensions of originality and flexibility, but there was no difference in creativity between the two groups in terms of concrete and low construal-level tasks. That is to say, anticipated communication promotes creativity only when creative tasks require abstract and high construal-level thinking. In conclusion, this study, based on previous studies on communication and creativity and construal level and creativity, found that for abstract creative tasks, merely anticipated communication enhances creativity even though the actual communication has not yet occurred.
People overestimate the intensity and duration of their affective reactions to events in the future. This is called impact bias (Wilson and Gilbert, 2003). Impact bias influences individuals’ satisfaction with their decision making. Few studies have shed light on how to reduce impact bias in affective forecasting based on the dual-process theory. According to the dual-process theory of human thinking, there are two distinct but interacting systems for information processing. System 1 relies on frugal heuristics and produces intuitive responses, while System 2 relies on deliberative analytic processing. System 2 often overrides the input of System 1 when analytic thinking is activated. Thus, we hypothesize that analytic thinking reduces the impact bias in affective forecasting. In experiment 1, a total of 240 undergraduates were assigned to play an ultimatum game as proposers and asked to predict how they would feel when their proposals were accepted or rejected by responders. Randomly, they were told their proposals were accepted or rejected. As soon as they knew the result, they were asked to report how they felt. Before the ultimatum game began, participants were randomly assigned to view pictures of
The Thinker to prime analytic thinking or geometric figures as a control condition. The results showed that analytic thinking reduced impact bias in affective forecasting by reducing the intensity of predicted emotions. In experiment 2, a total of 52 undergraduates took part in a memory test. They were asked to predict how they would feel if their scores on a memory test exceeded 90% or not before the test. As soon as they knew the result that they did not exceed 90%, they were asked to report how they felt. Before taking the memory test, participants were randomly assigned to perform a verbal fluency task with words related to analytic thinking to prime analytic thinking or a task not related to analytic thinking as a control condition. The results showed that analytic thinking reduced impact bias in affective forecasting by reducing the intensity of predicted emotions. In experiment 3, a total of 111 women who had only one child were asked to predict how they would feel if they had the second child. Before predicting their feelings, they were randomly assigned to view pictures of
The Thinker to prime analytic thinking or geometric figures as a control condition. Results showed that analytic thinking reduced the positive affect of having the second child but not the negative affect of having the second child. In sum, the present research shows that analytic thinking reduces impact bias in affective forecasting by reducing the intensity of predicted emotions. It can help us reduce impact bias in affective forecasting when making decisions, and promote satisfaction with those decisions. Limitations and further research are discussed as well.
Judgments of learning (JOLs) are characterized as metacognitive judgments on the likelihood that studied items can be successfully retrieved in a future memory test. Previous studies found that people employ different types of cues to inform their online JOLs. Some of these cues can guide JOLs to accurately reflect memory status but others cannot (and are even misleading in some situations). A widely studied cue for JOL formation is subjective processing experience (e.g., perceptual fluency) while completing a given task, which often confers metacognitive illusions. It has been found that people give higher JOLs to large than to small words, although font size has minimal influence on retention, a phenomenon termed the
font size effect on JOLs. A potential mechanism underlying the effect is perceptual fluency: Large words are perceived more fluently than small ones, and fluent processing experience of large words induces a feeling of knowing, which drives people to offer higher JOLs. The font size effect is important because it spotlights a dissociation between metacognitive judgments and memory itself. The current study aims to explore the influences of encoding strength on the font size effect, and to explore practical techniques to calibrate metacognitive illusions induced by perceptual fluency. Experiment 1 aimed to delineate the role of perceptual fluency in the font size effect. Twenty-six participants first completed a continuous identification (CID) task to measure the difference in perceptual fluency (indexed by response times; RTs) between large (70-pt) and small (9-pt) words, after which they attended a classic learning task. In the learning task, participants studied large and small words one-by-one, for 2 s each, and made item-by-item JOLs. Immediately following the learning task, they completed a distractor task, followed by a free recall test. The results showed that, in the CID task, participants responded much faster to large than to small words, indicating the natural difference in perceptual fluency between large and small words. In addition, perceptual fluency (i.e., RTs in the CID task) significantly correlated with JOLs, reflecting the fluency effect on JOLs. More importantly, perceptual fluency significantly mediated the font size effect on JOLs, supporting the claim that perceptual fluency is responsible for the font size effect. Experiment 2 manipulated study durations to investigate the influence of enhancing encoding strength (through prolonging study duration) on the font size effect. Specifically, three groups of participants studied each word for 2 s, 4 s, and 8 s, respectively, and made item-by-item JOLs. The results demonstrated that prolonging study duration correspondingly decreased the font size effect on JOLs. It is, however, worth highlighting that expanding study time cannot fully eliminate the font size effect because the results still showed a significant font size effect even when the study time was increased to 8 s. Experiment 3 was conducted to further investigate the effectiveness of enhancing encoding strength for calibration of the font size effect. A sentence-making group was instructed to encode each word by generating a sentence to deepen the level of processing (i.e., encoding strength). By contrast, there were no explicit requirements of encoding strategies in the control group (i.e., participants in the control group could use any strategies they liked). In the control group, the classic font size effect on JOLs was successfully replicated; of critical interest, the effect disappeared in the sentence-making group. Such results reflect the power of improving encoding strength to calibrate metacognitive illusions induced by perceptual features. In summary, the current study establishes that perceptual fluency is at least one of the mechanisms underlying the font size effect on JOLs; prolonging study duration reduces but fails to eliminate the font size effect on JOLs; more importantly, directly deepening the level of processing through sentence-making is a valid strategy to calibrate metacognitive illusions induced by perceptual features. Theoretical and practical implications are discussed in the main text.
