https://orcid.org/0000-0002-9356-2306
Abstract
The mindsets related to individuals’ abilities and personalities can explain why some people are more open to learning from others and improving themselves. A strategic mindset, which involves frequently asking oneself strategy-eliciting questions, has been linked to better academic performance among students. Yet the neuropsychological mechanisms underlying the strategic mindset in the domain of social interaction remain unclear. Here, we investigated the relationships among a strategic mindset, social feedback processing, and self-concept adjustment. Our event-related potential study (n = 41) showed a negative correlation between a strategic mindset and the neural indicator of social conflict (ie the N400 component). Moreover, a strategic mindset selectively responds to positive social feedback, supported by its positive correlations with the amplitude of the late positive potential in response to desirable feedback. Our behavioral study (n = 45) further demonstrated that individuals with a higher level of strategic mindset were more likely to update their self-concept based on conflicting opinions presented by others. We differentiated a strategic mindset from a growth mindset and showed that it explained unique variance in two studies. These findings may have practical implications for interventions aimed at encouraging individuals to ask strategy-eliciting questions and facilitating personal growth.
Introduction
In daily social interactions, individuals often receive feedback from others regarding their character traits and tend to integrate this feedback into their self-concept development. This process involves updating one’s initial beliefs about oneself based on the feedback received. For instance, when someone receives feedback that they are very smart, they may take this information into account and adjust how they perceive their own intelligence accordingly. The ability to adjust one’s self-concept based on social feedback is crucial for personal growth and development.
Strategic mindset, social feedback processing, and self-concept adjustment
Adjusting one’s self-concept based on social feedback involves both normative and adaptive processes. Normativity refers to the social standards and expectations that influence how individuals perceive themselves in relation to others (Festinger 1954; Rosenberg 2017). Adaptivity, conversely, emphasizes the importance of flexibility in responding to social feedback, fostering a willingness to learn from experiences, and facilitating greater personal growth. This adaptive adjustment depends on processing conflicts between personal views and others’ views. The way individuals perceive and interpret this social conflict affects how much they adjust their beliefs and behaviors. On the one hand, the reward-based reinforcement learning model suggests that successful behavioral patterns and correct beliefs are reinforced, while errors call for adjustments. Specifically, the “prediction error”—a difference between the expected and obtained outcome—guides decision-making by signaling the need for behavioral adjustment (Schultz 2006). Although the conflict between one’s self-concept and the views of others is not necessarily considered an error, it can be viewed as a deviation from expectation. A functional magnetic resonance imaging (fMRI) study demonstrated that conflict with group opinion triggers a neuronal response in the rostral cingulate zone and the ventral striatum, which is similar to the “prediction error” signal proposed by neuroscientific models of reinforcement learning (Klucharev et al. 2009; Botvinick et al. 2020). This conflict-related signal amplitude was found to predict subsequent conforming behavioral adjustments (Klucharev et al. 2009). It appears that individuals who are more sensitive to social conflict may be more likely to adjust their subsequent beliefs and behaviors.
On the other hand, it is also possible that individuals may be more inclined to integrate feedback into their self-concept when they perceive minimal conflict between their self-view and others’ perspectives. This phenomenon can be explained by self-verification theory, which suggests that individuals seek feedback that confirms their existing self-concepts in order to maintain coherence and stability, particularly when the feedback is perceived as non-threatening and aligns with their self-perceptions (Sedikides and Gregg 2008; Swann Jr 2012). Such integration is facilitated by reduced cognitive dissonance (Festinger 1954), making it easier to assimilate new information. As a result, individuals are more likely to reflect on and modify their self-concepts, thereby reinforcing their identity (Festinger 1962). From this perspective, individuals who are less sensitive to social conflict may find it easier to incorporate feedback into their self-view, experiencing fewer internal contradictions and less psychological discomfort. This allows them to accept and integrate constructive criticism more readily, leading to more adaptive self-concepts.
We believe that individuals’ mindsets regarding their own abilities and personalities play a crucial role in this adaptive learning process and may help explain why some individuals are more likely to learn from others’ feedback and improve themselves. While a growth mindset, characterized by the belief that personalities and abilities can be developed through effort (Dweck and Leggett 1988; Dweck 2013), encourages openness to feedback, it may not fully capture the nuances of how individuals engage with opportunities for improvement. Recent research highlighted the importance of a domain-general psychological construct—“strategic mindset,” which goes beyond the growth mindset by emphasizing the use of metacognitive strategies, such as the ability to monitor progress and flexibly adjust approaches (Chen et al. 2020). In another study, the authors suggested that “a strategic mindset is less of a metacognitive strategy and more of an individual’s proclivity to accessing and applying those strategies through self-reflection” (McKay 2023). This mindset involves frequently asking oneself strategy-eliciting questions, such as: “What can I do to help myself?” or “Is there a way to do this even better?” (Chen et al. 2020). Unlike a purely growth-oriented approach, a strategic mindset actively fosters adaptability and self-monitoring, leading to more effective learning outcomes. Previous studies showed that the strategic mindset is associated with higher academic scores, greater progress toward goals, and better performance in challenging tasks among students (Chen et al. 2020). Another study extended the strategic mindset construct to entrepreneurship, demonstrating that it mediates the effect of frugality on both innovative behavior and the level of effort enacted toward one’s new venture (Michaelis et al. 2021). However, little is currently known about how the strategic mindset is related to social feedback learning and self-concept adjustment at both behavioral and neural levels.
Event-related potential research on social feedback processing
The exceptional millisecond temporal resolution of the event-related potential (ERP) technique makes it possible to examine how the human brain learns social feedback at the different information processing stages. First, discrepancies between external feedback and internal self-perception can be identified. Individuals then assess whether the feedback is positive or negative, which influences their emotional response and subsequent actions. Our primary focus is on two well-established ERP components involved in feedback processing: the relatively early N400, which is associated with conflict processing, and the late positive potential (LPP), which relates to stimulus significance processing. The N400 is a negative deflection of the ERP that peaks around 400 ms and was originally found to be associated with the processing of information that is semantically incongruent with prior knowledge (Kutas and Hillyard 1980). More recent studies have demonstrated that the N400 is also sensitive to social information that violates our expectations or knowledge about the world (Goto et al. 2013; Huang et al. 2014; Rueschemeyer et al. 2015; Brusa et al. 2021). For instance, a study found that social conflict, in which an individual’s opinion differed from the group opinion, elicited a larger N400 amplitude than a no-conflict condition (Huang et al. 2014). These findings suggest that the N400 may play a significant role in social conflict processing and social feedback learning.
The LPP, a slow positive deflection ERP component, is commonly examined in studies of emotion and emotion regulation. Enhanced LPP amplitudes have been consistently observed in response to motivationally significant and highly emotionally arousing images (Cacioppo et al. 1993; Hajcak and Foti 2020). Sustained LPP activity can be observed for an extended period following stimulus presentation, typically lasting between 600 and 2,000 ms (Schupp et al. 2006). In terms of social feedback processing in this study, we predict that the LPP may reflect the relatively late elaboration of feedback. People generally perceive themselves positively and anticipate receiving more positive feedback than negative (Leary 2007; Hepper et al. 2011). It has been suggested that individuals can cultivate and sustain a positive self-concept due to cognitive processing mechanisms that tend to distort incoming information favorably (Taylor and Brown 1988). Previous studies have found that individuals tend to process feedback with a positive bias; specifically, they adjust their self-evaluations more in response to desirable feedback than to undesirable feedback (Korn et al. 2012). This positively biased processing of social feedback suggests that individuals may be more emotionally and cognitively engaged when processing positive feedback. From this perspective, desirable and undesirable feedback may differ not only in their valence but also in the level of emotional arousal they induce. Desirable feedback is likely more congruent with an individual’s self-concept and, therefore, more emotionally arousing, leading to a larger LPP amplitude.
The current study and hypotheses
In the current research, we used a personality trait rating task and conducted one ERP study (study 1) and one behavioral study (study 2). In both studies, the participants were asked to initially rate how much each trait adjective (including positive and negative traits) applied to themselves. They were also presented with ratings from one of their friends (as they believed) for each of the adjectives to induce social conflict. In study 2, participants attended an additional session where they were asked to rate all the trait adjectives again. This allows us to examine how they updated their self-concept based on the social feedback received in the first session. The objective of study 1 was to examine the correlation between a strategic mindset and social conflict/feedback processing in the brain. The goal of study 2 was to extend these findings by investigating whether a strategic mindset facilitates self-concept adjustment in response to conflicting views.
Specifically, we hypothesized that in study 1, the N400 component would show a response to the social conflict itself (relative to no conflict), while the LPP component would further encode the desirability of the social feedback. Due to the biased favor toward positive feedback, we expect that desirable social feedback would elicit a larger LLP amplitude compared to undesirable feedback. As outlined above, self-concept adjustment based on social feedback can be achieved either by becoming more sensitive to social conflict through a “prediction error” mechanism or by experiencing reduced internal cognitive dissonance when facing conflict. However, it remains unclear how and in which direction a strategic mindset is related to social conflict processing, making it ideal to use ERP to address this question. It is possible that a strategic mindset would be positively correlated with the N400 amplitude, as individuals with this mindset may be more inclined to ask themselves strategy-eliciting questions, making them more sensitive to conflicting views and enabling them to identify areas for improvement in their own thought processes and behaviors. Conversely, it is also reasonable to hypothesize that individuals with a higher level of strategic mindset would exhibit a smaller N400 amplitude when confronted with social conflict, because they may perceive conflicting information as less discordant. Furthermore, it is believed that individuals with a strategic mindset are more inclined to actively seek opportunities for self-improvement, making them more responsive to both favorable and unfavorable social feedback, as both types offer valuable insights for growth. Based on this assumption, we hypothesized that a strategic mindset would correlate with the amplitude of the LPP in response to both desirable and undesirable social feedback conditions.
In study 2, we further hypothesized that individuals with a higher level of strategic mindset would be more likely to adjust their beliefs in response to the conflict between their own and others’ views. Additionally, we hypothesized that a strategic mindset would have unique predictive power beyond the growth mindset construct related to personal growth, specifically in the domain of personality. We examined whether the strategic mindset would significantly predict social conflict sensitivity and self-concept adjustment, after controlling for the growth mindset construct.
Study 1—strategic mindset and social feedback processing
Materials and methods
Participants
Forty-one native Chinese-speaking university Master’s students were recruited to participate in the ERP study. The group consisted of 12 males with a mean age of 29.93 (SD = 9.41). The sample size is comparable to previous ERP studies related to mindset (Moser et al. 2011) and belief updating (Yao et al. 2021). All of the participants reported no history of neurological or psychiatric disorders, had normal or corrected-to-normal vision, and were right-handed. The study was approved by the Ethics and Discipline Committee of the university with which the authors are affiliated (#EC026/2021). All of the participants provided informed consent and received course credit upon completion of the study.
Stimuli
In this experiment, the participants were required to rate how much a series of traits applied to themselves. The trait adjectives were selected from a comprehensive list (Anderson 1968) that has been used in previous studies (Izuma et al. 2008; Korn et al. 2012). These adjectives were translated into Chinese based on the Modern Chinese Dictionary, and their valence was rated in a separate study (Zhou et al. 2013). To further refine the selection, in another study, 176 Chinese adjectives were chosen, with 88 positive adjectives describing socially desirable traits (eg smart) and 88 negative adjectives describing socially undesirable traits (eg lazy). The participants in that study assessed these traits, and the results showed that the positive adjectives were significantly more likable than the negative adjectives (4.88 ± 0.72 vs. 1.65 ± 0.82), but there was no significant difference in the participant’s familiarity with the positive and negative adjectives (3.17 ± 0.35 vs. 3.17 ± 0.35) (Jin 2021). All of the selected words were two-character Chinese adjectives that described different trait concepts and avoided synonyms or antonyms. In the current study, these 176 adjectives were used as the experimental stimuli.
Experimental task and procedure
To ensure that the participants believed they would receive authentic feedback on their traits from a real-life friend, we asked each participant to provide the email address of one friend prior to the experiment. The participants were informed that their friend would receive a study-related questionnaire and that their friend’s responses would be presented to them during the experiment, but they were not provided with specific details about the nature of the experiment. However, in reality, an irrelevant questionnaire was sent to the friend and their responses were not shared with the participants. To prevent any potential interference with the experiment, both the participants and their friends were instructed not to communicate with each other. This procedure ensured the authenticity and effectiveness of the study.
The trait rating task is depicted in Fig. 1, with the stimuli presented using E-prime 3.0 (Psychology Software Tools, Pittsburgh, PA). The design of the ERP study was to investigate the neural responses to social conflict/feedback. For this purpose, participants completed only session 1, in which each trial began with a 0.5-s fixation, followed by the presentation of a randomly selected trait adjective for 1 s. After that, an 8-point Likert scale appeared below the word, and the participant was instructed to rate how much the trait applied to them from 1 (does not apply at all) to 8 (applies very much) by pressing the corresponding key. Then, the participant’s response was highlighted with a blue frame for 0.5 s (“first rating”). Following a jittered blank screen (0.5 to 1 s), the participant was shown a green frame indicating what they believed to be the rating on their trait from a friend for 2 s (“feedback rating”). Actually, the program determined the feedback rating during the experiment using the following criteria: for positive or negative adjectives, in 24 trials, the feedback ratings agreed with the participant’s rating, while in the remaining 64 trials, the feedback ratings were equally likely to be higher or lower than the participant’s rating by −2, −1, +1, or + 2 points (“conflict”), with 16 trials in each type of feedback rating. An adaptive algorithm was implemented to maintain an approximately equal overall ratio of these feedback ratings. If the calculated feedback rating was greater than 8 or less than 1, the positive or negative direction of the point was reversed. For example, in a predetermined +2 conflict trial, if the participant’s first rating was 7, which would result in a feedback rating of 9, the direction of conflict was reversed so the feedback rating would be 5 (ie 7 − 2) instead.
Experimental task. In session 1 of both study 1 and study 2, participants were first presented with either a positive or negative trait adjective and were asked to rate how much the trait applied to themselves. Participants then received feedback, which they believed was from their friend. The difference between participants’ own rating and the feedback rating they received was conceptualized as conflict and was manipulated during the experiment. In session 2 of study 2, participants were asked to re-rate all the adjectives to assess how much they updated their ratings after receiving feedback.
After the experiment was completed, the participants were debriefed that the feedback ratings were not from their friends. They were asked if they had any doubts about the experiment. All of the participants reported that they had no doubts regarding the authenticity of the feedback ratings.
Measures
Following the trait rating task, the participants were asked to complete the following paper-and-pen self-report scales. The original English items in the scales were translated into Chinese using back-translation (Brislin 1970). Besides the growth mindset of personality, we also controlled for the closeness of the participant to the friend who provided the feedback ratings, which we recognized as an important factor to consider in the social feedback processing.
Strategic Mindset scale
The 6-item Strategic Mindset scale (Chen et al. 2020) was used to measure the general strategic mindset of the participants. An example item is “When you are stuck on something, how often do you ask yourself: ‘What are things I can do to help myself?’”. The responses were recorded on a 5-point Likert scale (1 = never, 5 = most of the time). The Cronbach’s alpha coefficient was 0.86 in Study 1.
Implicit Theories of Personality scale
To measure growth mindset toward personality, the 8-item Implicit Theories of Personality scale (Dweck 2013) was used. The scale items assessed the extent to which the participants believed that personality traits were malleable or fixed (eg “People can’t really change what kind of personality they have. Some people have a good personality and some don’t and they can’t change much”). The responses were given on a 6-point Likert scale ranging from 1 (strongly disagree) to 6 (strongly agree). Cronbach’s alpha coefficient was 0.90 in study 1.
To preliminarily assess the reliability and validity of the translated Chinese scales for Strategic Mindset and Growth Mindset of Personality, we recruited an independent sample of 200 Master’s students in a pilot study (48 females; mean age = 30.37, SD = 8.43). The results indicated that the Strategic Mindset scale significantly correlated with the Metacognitive Strategy-Use scale—an adapted 16-item Chinese translated measure of metacognitive strategies for learning and goal achievement (Chen et al. 2020), with Kendall’s tau correlation, r = 0.21, P < 0.01. Additionally, the Strategic Mindset scale significantly correlated with the Growth Mindset of Personality scale (Kendall’s tau correlation, r = 0.16, P < 0.01). The Cronbach’s alpha coefficients were 0.93 for the Strategic Mindset scale and 0.90 for the Growth Mindset of Personality scale.
We also conducted confirmatory factor analyses using AMOS 26.0 on the translated Chinese version scales. The results revealed a good model fit and validity for the translated scales, with a chi-square ratio (χ2/df) of 2.18 for the Strategic Mindset scale and 1.58 for the Growth Mindset of Personality scale. The comparative fit index (CFI) and Tucker–Lewis index (TLI) were both ≥0.98; the Standardized Root Mean Square Residual (SRMR) were both ≤ 0.03, and the root-mean-square error of approximation (RMSEA) values were both ≤ 0.08. Additionally, for both scales, the composite reliability (CR) values were ≥ 0.7, and the average variance extracted (AVE) values were ≥ 0.5. All factor loadings were greater than 0.8 for the Strategic Mindset scale and greater than 0.7 for the Growth Mindset of Personality scale.
Inclusion of Other in the Self scale
The Inclusion of Other in the Self (IOS) scale (Aron et al. 1992) was used to measure the perceived closeness of the participants to the friend who supposedly provided ratings during the experiment. The participants were presented with seven pairs of circles that ranged from just touching to almost completely overlapping. One circle in each pair was labeled as “self,” and the second circle was labeled as “other.” The participants were instructed to select the pair that best described their relationship with their friend on a 7-point Likert scale (1 = no overlap, 7 = most overlap).
Electroencephalography recording and data analysis
Electroencephalography (EEG) data were recorded using the HydroCel GSN EGI 64-channel system (EGI net station; Electrical Geodesics Inc.) at a sampling rate of 1000 Hz, with the Cz electrode serving as the online reference. The data were preprocessed using EEGLAB v2022.1 (Delorme and Makeig 2004). Prior to analysis, the continuous EEG data were first filtered with a 0.3 to 30 Hz band-pass filter. Bad channels were removed according to a standardized early-stage EEG processing pipeline (PREP) (Bigdely-Shamlo et al. 2015). Independent component analysis (ICA) was then carried out with an optimization algorithm, CUDAICA, which is an implementation of Infomax ICA made on Compute Unified Device Architecture (CUDA) (Raimondo et al. 2012). Components related to eye movement artifacts were then removed using an automatic algorithm - ADJUST (Automatic EEG artifact Detection based on the Joint Use of Spatial and Temporal features) (Mognon et al. 2011). The trials were then epoched from −200 ms prestimulus onset to 1,000 ms poststimulus onset. Epochs with an amplitude exceeding ±80 μV at the electrodes of interest were excluded for further analysis. Eight participants were excluded at this stage, resulting in a final sample size of 33 participants (10 males; mean age = 28.79, SD = 8.29). Finally, the potentials were referenced to the common average and baseline-corrected using a per-stimulus interval of 200 ms prior to the presentation of the stimuli.
The epoched EEG data from each electrode were time-locked to the onset of feedback (ie the simultaneous revelation of the participant’s first rating and the friend’s rating) and were sorted by experimental condition. The N400 was measured as the mean amplitude in a time window of 350 to 550 ms postonset of the feedback. Based on the previous study (Huang et al. 2014), we focused on the N400 responses on the FCz electrode as it showed the largest N400 effect. The LPP was measured as the mean amplitude in a time window of 600 to 1,000 ms postonset of the feedback at the same FCz electrode. As the LPP is observed to be the largest with a central to frontocentral topography, the FCz electrode site is well situated within this region. Inspection reveals similar patterns in the electrodes surrounding FCz.
To assess the relationship between strategic mindset and brain activity during social feedback processing, Kendall’s tau was used to examine the correlation between N400/LPP amplitudes and strategic mindset, considering the non-normality of the data and the small sample size. To account for other variables and evaluate the unique contribution of strategic mindset to conflict sensitivity, regression analysis was conducted by including strategic mindset, growth mindset toward personality, and IOS as predictors, with the amplitudes of N400 and PLL serving as the dependent variable.
Results
We first tested the hypothesis that the N400 encodes social conflict and that the LPP reflects the desirability of feedback. Subsequently, we examined how these components correlated with a strategic mindset. Figure 2A displays the ERP grand-average waveforms for the five experimental conditions: (i) positive trait desirable (friend higher rating, average number of trials n = 22); (ii) negative trait desirable (friend lower rating, n = 27); (iii) negative trait undesirable (friend higher rating, n = 29); (iv) positive trait undesirable (friend lower rating, n = 27); and (v) no conflict (n = 35). To examine how conflict affects the N400 amplitude, for the feedback-locked N400 at the FCz electrode, a paired-sample t-test revealed a significantly larger negative N400 in response to the conflict condition (all types of conflict combined, M ± SD, 1.17 μV ± 1.95) than to the no-conflict condition (3.15 μV ± 2.85), t(32) = −4.26, P < 0.001, suggesting that the N400 is sensitive to social conflict. Additionally, to assess whether the N400 encodes trait valence and conflict direction, a repeated-measures analysis of variance (ANOVA) with 2 trait valence (positive vs. negative) × 2 numerical direction of conflict (friend higher rating vs. friend lower rating) on the N400 amplitude revealed a marginally significant main effect of direction, with the friend higher condition eliciting a more negative N400 than the friend lower condition, F(1, 32) = 3.90, P = 0.06 (Fig. 2B). The other effects were not significant, with P-values > 0.61. The paired-sample t-test revealed that there was no significant difference in the amplitude of the N400 between desirable feedback and undesirable feedback, t(32) = −0.51, P = 0.61, suggesting that the desirability of social information cannot be differentiated at an early stage.
ERP results of study 1. A) The ERP grand-average waveforms of five conditions at the FCz electrode; B) the N400 amplitudes (mean ± SE, in μV) for the friend higher, friend lower, and no conflict conditions, as well as the topographical maps for the different wave between conflict and no conflict conditions; (C) the late positive potential (LPP) amplitudes (mean ± SE, in μV) for the desirable, undesirable, and no conflict conditions, as well as the topographical maps for the different wave between desirable and undesirable conditions; D) correlation between strategic mindset the mean N400 amplitude of conflict condition. Since the N400 represents a negative fluctuation, the positive correlation suggests that participants who reported a higher level of strategic mindset tended to exhibit a smaller N400 amplitude; E) correlation between strategic mindset the mean LPP amplitude of desirable condition; F) correlation between strategic mindset the mean LPP amplitude of undesirable condition.
Nevertheless, to assess whether the LPP encodes trait valence and feedback desirability, a repeated-measures ANOVA with 2 trait valence (positive vs. negative) × 2 feedback desirability (desirable vs. undesirable) on the LPP amplitude showed a significant main effect of desirability, F(1, 32) = 5.27, P = 0.03. Undesirable feedback elicited significantly larger LPP amplitudes than desirable feedback, suggesting that the LPP is sensitive to feedback desirability, as demonstrated in Fig. 2C. The other effects were not significant, with P-values > 0.34.
Furthermore, our analysis revealed significant correlations between strategic mindset and neural responses, as shown in Table 1. We found that the mean amplitude of the N400 in the conflict condition was significantly correlated with the strategic mindset, r = 0.27, P = 0.03. Since the N400 represents a negative fluctuation, the positive correlation suggests that participants who reported a higher level of strategic mindset tended to exhibit a smaller N400 amplitude when facing social conflict (Fig. 2D). The correlation between the mean amplitude of the LPP in the desirable condition and strategic mindset was also significant, r = 0.31, P = 0.01 (Fig. 2E). We did not find a significant correlation between the mean amplitude of the LPP in the undesirable condition and strategic mindset, r = 0.18, P = 0.15 (Fig. 2F). The significant correlation between the strategic mindset and IOS measure (r = 0.47, P < 0.01) may suggest that individuals who perceive greater overlap between themselves and others are likely better at considering diverse perspectives, adapting strategies to social contexts, and pursuing shared goals—key components of a strategic mindset.
Means, standard deviations, and Kendall’s tau correlations between variables of interest in study 1 and study 2.
| Variables | M | SD | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|---|---|
| Study 1—ERP study | |||||||
| 1. Strategic mindset | 4.09 | 0.62 | |||||
| 2. Growth mindset of personality | 3.57 | 1.16 | 0.13 | ||||
| 3. Inclusion of other in the self | 5.61 | 1.39 | 0.47a | 0.04 | |||
| 4. Mean amplitude of the N400 (conflict condition) | 1.17 | 1.95 | 0.27b | 0.15 | 0.10 | ||
| 5. Mean amplitude of the LPP (desirable condition) | 3.29 | 2.96 | 0.31a | 0.17 | 0.14 | 0.38b | |
| 6. Mean amplitude of the LPP (undesirable condition) | 4.77 | 3.74 | 0.18 | 0.122 | 0.24 | 0.45 | 0.30b |
| Study 2—Behavioral study | |||||||
| 1. Strategic mindset | 3.04 | 0.48 | |||||
| 2. Growth mindset of personality | 3.54 | 0.76 | 0.13 | ||||
| 3. Inclusion of other in the self | 5.04 | 1.59 | 0.13 | −0.13 | |||
| 4. Regression coefficient of conflict | 0.10 | 0.21 | 0.31b | −0.12 | 0.02 | ||
| Variables | M | SD | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|---|---|
| Study 1—ERP study | |||||||
| 1. Strategic mindset | 4.09 | 0.62 | |||||
| 2. Growth mindset of personality | 3.57 | 1.16 | 0.13 | ||||
| 3. Inclusion of other in the self | 5.61 | 1.39 | 0.47a | 0.04 | |||
| 4. Mean amplitude of the N400 (conflict condition) | 1.17 | 1.95 | 0.27b | 0.15 | 0.10 | ||
| 5. Mean amplitude of the LPP (desirable condition) | 3.29 | 2.96 | 0.31a | 0.17 | 0.14 | 0.38b | |
| 6. Mean amplitude of the LPP (undesirable condition) | 4.77 | 3.74 | 0.18 | 0.122 | 0.24 | 0.45 | 0.30b |
| Study 2—Behavioral study | |||||||
| 1. Strategic mindset | 3.04 | 0.48 | |||||
| 2. Growth mindset of personality | 3.54 | 0.76 | 0.13 | ||||
| 3. Inclusion of other in the self | 5.04 | 1.59 | 0.13 | −0.13 | |||
| 4. Regression coefficient of conflict | 0.10 | 0.21 | 0.31b | −0.12 | 0.02 | ||
Note. M and SD are used to represent mean and standard deviation, respectively.
aindicates P < 0.01.
bindicates P < 0.05.
Means, standard deviations, and Kendall’s tau correlations between variables of interest in study 1 and study 2.
| Variables | M | SD | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|---|---|
| Study 1—ERP study | |||||||
| 1. Strategic mindset | 4.09 | 0.62 | |||||
| 2. Growth mindset of personality | 3.57 | 1.16 | 0.13 | ||||
| 3. Inclusion of other in the self | 5.61 | 1.39 | 0.47a | 0.04 | |||
| 4. Mean amplitude of the N400 (conflict condition) | 1.17 | 1.95 | 0.27b | 0.15 | 0.10 | ||
| 5. Mean amplitude of the LPP (desirable condition) | 3.29 | 2.96 | 0.31a | 0.17 | 0.14 | 0.38b | |
| 6. Mean amplitude of the LPP (undesirable condition) | 4.77 | 3.74 | 0.18 | 0.122 | 0.24 | 0.45 | 0.30b |
| Study 2—Behavioral study | |||||||
| 1. Strategic mindset | 3.04 | 0.48 | |||||
| 2. Growth mindset of personality | 3.54 | 0.76 | 0.13 | ||||
| 3. Inclusion of other in the self | 5.04 | 1.59 | 0.13 | −0.13 | |||
| 4. Regression coefficient of conflict | 0.10 | 0.21 | 0.31b | −0.12 | 0.02 | ||
| Variables | M | SD | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|---|---|
| Study 1—ERP study | |||||||
| 1. Strategic mindset | 4.09 | 0.62 | |||||
| 2. Growth mindset of personality | 3.57 | 1.16 | 0.13 | ||||
| 3. Inclusion of other in the self | 5.61 | 1.39 | 0.47a | 0.04 | |||
| 4. Mean amplitude of the N400 (conflict condition) | 1.17 | 1.95 | 0.27b | 0.15 | 0.10 | ||
| 5. Mean amplitude of the LPP (desirable condition) | 3.29 | 2.96 | 0.31a | 0.17 | 0.14 | 0.38b | |
| 6. Mean amplitude of the LPP (undesirable condition) | 4.77 | 3.74 | 0.18 | 0.122 | 0.24 | 0.45 | 0.30b |
| Study 2—Behavioral study | |||||||
| 1. Strategic mindset | 3.04 | 0.48 | |||||
| 2. Growth mindset of personality | 3.54 | 0.76 | 0.13 | ||||
| 3. Inclusion of other in the self | 5.04 | 1.59 | 0.13 | −0.13 | |||
| 4. Regression coefficient of conflict | 0.10 | 0.21 | 0.31b | −0.12 | 0.02 | ||
Note. M and SD are used to represent mean and standard deviation, respectively.
aindicates P < 0.01.
bindicates P < 0.05.
After controlling for growth mindset toward personality and the perceived closeness to their friend in the regression model, strategic mindset still significantly predicted the mean amplitude of the N400 in the conflict condition (Beta = 0.43, t = 2.06, P = 0.048). The regression analysis revealed a significant coefficient for the mean amplitude of the LPP in the desirable condition (Beta = 0.44, t = 2.18, P = 0.04), whereas the coefficient was nonsignificant in the undesirable condition (Beta = 0.09, t = 0.39, P = 0.70) (Table 2). Taken together, study 1 demonstrated a negative correlation between a strategic mindset and sensitivity to social conflict, as well as a positive correlation between a strategic mindset and receptiveness to desirable social feedback (measured by the LPP) at the neural level. In study 2, we expanded on these findings by examining how a strategic mindset relates to the adjustment of one’s self-concept in response to social feedback.
Regression results in study 1 and study 2.
| Predictors | Standardized coefficients (beta) | t-Statistic | P-value |
|---|---|---|---|
| Study 1—DV: Mean amplitude of the N400 (conflict condition) (R 2 = 0.16) | |||
| Strategic mindset | 0.43 | 2.06 | 0.048a |
| Growth mindset of personality | 0.06 | 0.35 | 0.73 |
| Inclusion of other in the self | −0.13 | −0.64 | 0.53 |
| Study 1—DV: Mean amplitude of the LPP (desirable condition) (R 2 = 0.24) | |||
| Strategic mindset | 0.44 | 2.18 | 0.04a |
| Growth mindset of personality | 0.16 | 0.98 | 0.33 |
| Inclusion of other in the self | −0.03 | −0.14 | 0.89 |
| Study 1—DV: Mean amplitude of the LPP (undesirable condition) (R 2 = 0.09) | |||
| Strategic mindset | 0.09 | 0.39 | 0.70 |
| Growth mindset of personality | −0.03 | −0.14 | 0.89 |
| Inclusion of other in the self | 0.25 | 1.16 | 0.26 |
| Study 2—DV: Regression coefficient of conflict (R 2 = 0.13) | |||
| Strategic mindset | 0.36 | 2.37 | 0.02a |
| Growth mindset of personality | −0.13 | −0.87 | 0.39 |
| Inclusion of other in the self | −0.04 | −0.28 | 0.78 |
| Predictors | Standardized coefficients (beta) | t-Statistic | P-value |
|---|---|---|---|
| Study 1—DV: Mean amplitude of the N400 (conflict condition) (R 2 = 0.16) | |||
| Strategic mindset | 0.43 | 2.06 | 0.048a |
| Growth mindset of personality | 0.06 | 0.35 | 0.73 |
| Inclusion of other in the self | −0.13 | −0.64 | 0.53 |
| Study 1—DV: Mean amplitude of the LPP (desirable condition) (R 2 = 0.24) | |||
| Strategic mindset | 0.44 | 2.18 | 0.04a |
| Growth mindset of personality | 0.16 | 0.98 | 0.33 |
| Inclusion of other in the self | −0.03 | −0.14 | 0.89 |
| Study 1—DV: Mean amplitude of the LPP (undesirable condition) (R 2 = 0.09) | |||
| Strategic mindset | 0.09 | 0.39 | 0.70 |
| Growth mindset of personality | −0.03 | −0.14 | 0.89 |
| Inclusion of other in the self | 0.25 | 1.16 | 0.26 |
| Study 2—DV: Regression coefficient of conflict (R 2 = 0.13) | |||
| Strategic mindset | 0.36 | 2.37 | 0.02a |
| Growth mindset of personality | −0.13 | −0.87 | 0.39 |
| Inclusion of other in the self | −0.04 | −0.28 | 0.78 |
aindicates P < 0.05.
Regression results in study 1 and study 2.
| Predictors | Standardized coefficients (beta) | t-Statistic | P-value |
|---|---|---|---|
| Study 1—DV: Mean amplitude of the N400 (conflict condition) (R 2 = 0.16) | |||
| Strategic mindset | 0.43 | 2.06 | 0.048a |
| Growth mindset of personality | 0.06 | 0.35 | 0.73 |
| Inclusion of other in the self | −0.13 | −0.64 | 0.53 |
| Study 1—DV: Mean amplitude of the LPP (desirable condition) (R 2 = 0.24) | |||
| Strategic mindset | 0.44 | 2.18 | 0.04a |
| Growth mindset of personality | 0.16 | 0.98 | 0.33 |
| Inclusion of other in the self | −0.03 | −0.14 | 0.89 |
| Study 1—DV: Mean amplitude of the LPP (undesirable condition) (R 2 = 0.09) | |||
| Strategic mindset | 0.09 | 0.39 | 0.70 |
| Growth mindset of personality | −0.03 | −0.14 | 0.89 |
| Inclusion of other in the self | 0.25 | 1.16 | 0.26 |
| Study 2—DV: Regression coefficient of conflict (R 2 = 0.13) | |||
| Strategic mindset | 0.36 | 2.37 | 0.02a |
| Growth mindset of personality | −0.13 | −0.87 | 0.39 |
| Inclusion of other in the self | −0.04 | −0.28 | 0.78 |
| Predictors | Standardized coefficients (beta) | t-Statistic | P-value |
|---|---|---|---|
| Study 1—DV: Mean amplitude of the N400 (conflict condition) (R 2 = 0.16) | |||
| Strategic mindset | 0.43 | 2.06 | 0.048a |
| Growth mindset of personality | 0.06 | 0.35 | 0.73 |
| Inclusion of other in the self | −0.13 | −0.64 | 0.53 |
| Study 1—DV: Mean amplitude of the LPP (desirable condition) (R 2 = 0.24) | |||
| Strategic mindset | 0.44 | 2.18 | 0.04a |
| Growth mindset of personality | 0.16 | 0.98 | 0.33 |
| Inclusion of other in the self | −0.03 | −0.14 | 0.89 |
| Study 1—DV: Mean amplitude of the LPP (undesirable condition) (R 2 = 0.09) | |||
| Strategic mindset | 0.09 | 0.39 | 0.70 |
| Growth mindset of personality | −0.03 | −0.14 | 0.89 |
| Inclusion of other in the self | 0.25 | 1.16 | 0.26 |
| Study 2—DV: Regression coefficient of conflict (R 2 = 0.13) | |||
| Strategic mindset | 0.36 | 2.37 | 0.02a |
| Growth mindset of personality | −0.13 | −0.87 | 0.39 |
| Inclusion of other in the self | −0.04 | −0.28 | 0.78 |
aindicates P < 0.05.
Study 2—strategic mindset and self-concept adjustment
Materials and methods
Participants
To determine the necessary sample size for the correlation between the strategic mindset and conflict sensitivity, we conducted a power analysis using the pwr package in R (Champely et al. 2018). We used a large effect size (r) of 0.5, an alpha level of 0.05, and a power level of 0.9. The result of the power analysis indicated that a sample size of 38 participants is required. Forty-five native Chinese-speaking undergraduate students (9 males; mean age = 21.89 years old, SD = 2.96) were recruited. All of the participants were right-handed and had normal or corrected-to-normal vision. The study was approved by the Ethics and Discipline Committee of the university with which the authors are affiliated. All of the participants provided informed consent and were paid approximately 10 US dollars to compensate them for their time.
Experimental task and measures
The aim of our behavioral study was to examine how participants update their self-concept in response to the conflict between their own and others’ views. For this purpose, following session 1 (the same as the one in study 1), the participants were unexpectedly instructed to begin an additional session 2. During session 2, participants were asked to rate how much the trait adjectives applied to themselves a second time, without receiving any feedback ratings (“second rating”). The same adjectives as those presented during session 1 were shown in a new randomized order. At the debriefing, none of the participants reported any doubts regarding the authenticity of the feedback ratings.
All of the self-report scale measures were identical to those used in study 1 but were administered in an electronic format in the laboratory. In study 2, the Cronbach’s alpha for the “Implicit Theories of Personality scale” was 0.85, while the “Strategic Mindset Scale” had a Cronbach’s alpha of 0.27. Given the low internal consistency of the Strategic Mindset Scale, we conducted a further examination of the interitem correlations among the six items. The Kendall’s tau correlation coefficients ranged from −0.17 to 0.36, with a median of 0.13. Several factors might explain the discrepancy in internal consistency between study 1 and study 2. Study 1 used a paper-and-pen questionnaire, while study 2 employed an electronic format. The tactile engagement and context provided by paper-and-pen formats might facilitate more thoughtful and consistent responses, potentially enhancing internal consistency. Additionally, participants in study 1 were postgraduate students, whereas study 2 participants were undergraduate students. The difference in educational level might influence how participants interpret and respond to the items, potentially impacting the reliability of their responses. Furthermore, poststudy interviews with several participants from study 2 revealed that they approached the experiment with a high level of seriousness and made deliberate efforts to differentiate their responses for each item. Lastly, previous research has shown that Cronbach’s alpha coefficient may not be reliable for small sample sizes. A robust estimate of the population coefficient alpha depends not only on the sample size but also on the largest eigenvalue of the sample dataset Charter (1999).
Data analysis
The feedback ratings for each participant were classified based on the desirability of the feedback received. Desirable feedback was defined as feedback ratings that were considered better than the participant’s first rating. For a positive trait adjective, desirable feedback indicated that the feedback rating was higher than the first rating. For a negative trait adjective, desirable feedback indicated that the feedback rating was lower than the first rating. Conversely, undesirable feedback was defined as feedback ratings that were considered worse than the participant’s first rating. For a positive trait adjective, undesirable feedback indicated that the feedback rating was lower than the first rating. For a negative trait adjective, undesirable feedback indicated that the feedback rating was higher than the first rating.
To evaluate the extent to which the participants modified their self-concept upon receiving social feedback, we computed an “update” score by subtracting each participant’s first rating from their second rating (ie update = second rating − first rating). We expected the participants to adjust their ratings towards the feedback rating, such that they would update their ratings in a “better” direction for desirable feedback and in a “worse” direction for undesirable feedback. However, the critical test for positively biased updating involved comparing the absolute change toward desirable feedback with the change toward undesirable feedback. Therefore, we classified the trials into four conditions based on trait valence and desirability: positive–desirable, positive–undesirable, negative–desirable, and negative–undesirable. For each participant, we computed the mean of all signed updates within each condition and then calculated the absolute mean updates, which reflected the absolute degree of adjustment made by the participants after receiving different types of social feedback. Trials with zero “conflict” (ie feedback rating = first rating) were excluded from the analysis because they did not provide a clear direction of social influence.
For all the participants, to assess the effect of conflict on the update, a mixed-effects regression model was used with “update” as the dependent variable and “conflict” as one of the predictors. Because the first rating and valence of the trait may also influence the update, the regression model is represented as update ~ (conflict + first rating) × valence + (1 + (conflict + first rating) | subject). For each participant, the regression analysis was conducted with the fixed effect only: update ~ (conflict + first rating) × valence. We extracted the regression coefficient of “conflict” for each participant. The coefficient indicated the extent to which the participant updated their ratings based on the conflict between their initial rating and their friend’s rating, after controlling for the first rating and trait valence. This can be considered as the index of sensitivity to conflict for each participant. Kendall’s tau was performed to examine the relationship between the regression coefficient of “conflict” and strategic mindset. Similar to study 1, regression analysis was conducted to account for other variables (growth mindset of personality and IOS) and evaluate the unique contribution of strategic mindset to self-concept adjustment.
Results
We first examined how participants adjust their self-concept based on social feedback, and then we investigated the relationship between this adjustment and strategic mindset. In session 1, the participants gave themselves significantly higher ratings for the positive trait adjectives than for the negative trait adjectives, indicating that they believed positive traits were more applicable to them (M = 5.19, SD = 0.80 vs. M = 4.24, SD = 0.87), t(44) = 4.87, P < 0.001. After receiving their friends’ ratings, the participants changed their ratings on average to align with the feedback. They significantly decreased their ratings when the friends’ ratings were lower than their first rating [mean updates = −0.44, SD = 0.25, one-sample t-test against 0 t(44) = −11.80, P < 0.001] and increased when the friends’ ratings were higher than their first rating [mean updates = 0.28, SD = 0.27, one-sample t-test against 0 t(44) = 7.02, P < 0.001]. Participants slightly reduced their ratings when their friends’ ratings matched their initial rating [mean updates = −0.11, SD = 0.23, one-sample t-test against 0 t(44) = −0.31, P = 0.003].
To examine how trait valence and feedback types influence participants’ absolute rating updates, we conducted a 2 trait valence (positive vs. negative) × 3 feedback desirability (desirable vs. undesirable vs. no-conflict) repeated-measures ANOVA on the absolute mean updates. Results revealed a significant main effect of valence, F(1, 44) = 7.98, P = 0.007, indicating that the participants updated their scores more for negative traits than for positive traits. The main effect of desirability was significant, F(2, 66.24) = 11.51, P < 0.001. The interaction effect was also significant, F(2, 88) = 5.31, P = 0.007. Pairwise comparisons showed that for the negative traits, the participants updated their ratings significantly more after receiving desirable feedback compared with undesirable feedback (M = 0.62, SD = 0.42 vs. M = 0.39, SD = 0.38), P = 0.012, suggesting the positively biased processing of social feedback. This biased updating was not found for positive traits (M = 0.39, SD = 0.31 vs. M = 0.39, SD = 0.27), P = 0.90 (Fig. 3A). The absolute mean updates for positive traits in the no-conflict condition were significantly lower than those in the other two conditions; for negative traits, the updates were also significantly lower than in the desirable condition, with P-values < 0.001.
![Behavioral results of study 2. A) Participants changed their ratings more after receiving desirable feedback than after receiving undesirable feedback, particularly for negative traits but not for positive traits; B) correlation between strategic mindset and the regression coefficient of conflict [update ~ (first rating + conflict) × valence], demonstrating that a higher level of strategic mindset was associated with a greater sensitivity to conflict.](https://oup.silverchair-cdn.com/oup/backfile/Content_public/Journal/cercor/35/3/10.1093_cercor_bhaf061/2/m_bhaf061f3.jpeg?Expires=1747876281&Signature=ozY3f6t4WJh~gYZ-mShBjB9ko~tQCmAb4gBz87FZUWAsvPh7BDWtg~fbwgJTdTN--eL-0pz-Np4Jlm44K3vigHbveAVCHHJrFyO7LR9yAwf5L81wi-uCEpl8es9XFUZWASUEufyHoDCQEdfHgzc4ijhoakIzxKSGJKuqme0habsNtWCcdoLzAkzzNI9lm6rm7PqpijOWESphuqb4kjFZMkAGoctApblBUDdLG7x0mEj61eCeyGEBX8jAuoDfObw9WWvQRalxj5AAGvULWSHi4wjSXVzU5hr-IzqMI61ha1eXsQ~iSgWOqFS-n75cjfSmkXT2ILzAIgJAmSHxC~hefA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA)
Behavioral results of study 2. A) Participants changed their ratings more after receiving desirable feedback than after receiving undesirable feedback, particularly for negative traits but not for positive traits; B) correlation between strategic mindset and the regression coefficient of conflict [update ~ (first rating + conflict) × valence], demonstrating that a higher level of strategic mindset was associated with a greater sensitivity to conflict.
To quantify the extent to which participants update their ratings based on conflicts, for all participants, the mixed-effects regression with the update as the dependent variable and social conflict as one of the predictors showed a significant coefficient of conflict (B = 0.13, SE = 0.02, P < 0.001), suggesting that the participants updated their ratings based on the conflict between their first ratings and their friends’ ratings. Additionally, both the valence of the trait and the first rating significantly predicted the participants’ update (P-values < 0.001). For each participant, we found that the conflict coefficient extracted from the regression model significantly correlated with the participant’s strategic mindset (r = 0.31, P = 0.03), as shown in Table 1 and Fig. 3B. After controlling for growth mindset toward personality and the perceived closeness to their friend in the regression model, strategic mindset still significantly predicted conflict sensitivity (Beta = 0.36, t = 2.37, P = 0.02), as shown in Table 2. Additionally, we conducted separate regression analyses using each item of the Strategic Mindset Scale as independent variables. The results indicated that item 3 and item 6 were significantly correlated with the conflict coefficient (P-values < 0.05). Taken together, these results suggested that the tendency of the participants to update their beliefs based on conflicting opinions with others was positively associated with their reported use of a strategic mindset.
Discussion
In this research, consisting of one ERP and one behavioral study, we showed that a strategic mindset was significantly associated with social feedback processing at the neural level and self-concept adjustment at the behavioral level.
Strategic mindset is linked to feedback processing in the brain
In our ERP study, we were able to investigate the processing of social feedback on a millisecond temporal scale. Our results revealed a dissociable effect at the early and late stages of information processing. Specifically, we found that the N400, measured in the time window of 350 to 550 ms following feedback presentation, responded to the discrepancy between the individual’s self-concept and the social feedback received (ie social conflict), regardless of its desirability. This result is consistent with previous research showing that the N400 is sensitive to social conflict and its numerical direction (Huang et al. 2014). In contrast, the later component, LPP, measured in the time window of 600 to 1,000 ms after feedback presentation, encoded the desirability of the feedback, suggesting that the LPP may reflect an in-depth elaboration of social feedback. The results expand our understanding of the LPP’s function by highlighting its role in processing emotional-salient social information. Our findings suggest that the brain can rapidly differentiate between desirable and undesirable feedback after the initial processing of social conflict.
Importantly, as a novel contribution, our research establishes a link between strategic mindset and social feedback learning at the neural level. A strategic mindset requires asking oneself strategic, thought-provoking questions to identify effective ways to facilitate personal growth. We find a significant negative correlation between strategic mindset and social conflict processing as reflected in the N400. This finding indicates that individuals who frequently adopt a strategic mindset in their daily lives may perceive conflicting information as less discordant with their own views, resulting in a smaller N400 amplitude. The strategic mindset, characterized by planning, goal-directed behavior, and adaptive thinking, may facilitate more efficient processing of conflicting information, thereby reducing cognitive dissonance. As a result, the cognitive load associated with reconciling differing opinions is diminished, which is a crucial factor in promoting behavioral or belief adjustments.
Furthermore, participants with a higher level of strategic mindset were more sensitive to desirable social feedback encoded by the LPP, but this effect did not manifest when presented with undesirable social information. It is possible that without a clear goal of self-improvement in the context of this study, individuals with a strategic mindset may be more motivated to update their self-concepts in self-affirming ways when confronted with contradictory social information. This positive outlook can enhance their attention to and processing of supportive feedback, as evidenced by the significant correlation with LPP amplitudes in the desirable condition. Conversely, while undesirable feedback can also offer valuable insights for personal growth, it may be perceived as a threat to self-esteem (Leitner et al. 2014). Consequently, individuals might respond differently to such feedback: Some might reconsider their self-concepts, while others may choose to disregard threatening information to protect their self-views. This variability could potentially explain the absence of a correlation between strategic mindset and LPP amplitudes in response to undesirable feedback. The tendency to adopt a self-affirming perspective can be generally beneficial for mental health, especially during challenging times. In an era where media-driven social feedback and comparisons are common, individuals often face unrealistic standards and expectations that can harm their self-esteem. Those with a strategic mindset might not only mitigate the potential psychological distress caused by negative social feedback but also foster a greater sense of agency and self-worth. Further research is needed to fully understand the dynamic interplay between the strategic mindset and the adaptive value of being more sensitive to desirable social feedback.
Strategic mindset facilitates behavioral self-concept adjustment
In the behavioral study, our results indicated that the participants were more likely to update their beliefs when receiving desirable feedback than undesirable feedback, particularly for negative personality traits, showing a self-serving optimistic bias. For instance, if someone views themselves as lazy, but their friend believes they are less lazy, they are very likely to update their self-concept significantly by adjusting their view of themselves as a diligent person. These findings are in line with previous studies that have shown an asymmetry in belief updating, with individuals being more likely to update their beliefs in response to better-than-expected information than worse-than-expected information (Sharot et al. 2011; Korn et al. 2012). This optimism bias is a pervasive human trait that influences various domains, including personal relationships, health, politics, and finance (Weinstein 1980; Puri and Robinson 2007; Fragkaki et al. 2021).
Consistent with our hypothesis that a strategic mindset may promote genuine beliefs and behavioral adjustments, the results showed that individuals with a higher level of strategic mindset were more likely to update their self-concept based on conflicting opinions presented by others. Our results suggest that the strategic mindset may serve as a valuable tool in promoting social feedback learning and self-concept adjustment. This may be because individuals who are inclined to engage in strategic behaviors are more open to learning from the opinions of others and, in turn, more willing to adjust their self-concept and make necessary adaptations.
Strategic mindset vs. growth mindset
Our work also sheds light on the importance of differentiating between a strategic mindset and a growth mindset. In the context of personality, the concept of a growth mindset entails the belief that individuals have the capacity to develop and enhance their personality traits through dedicated effort, continuous learning, and unwavering persistence. In contrast, individuals with a fixed mindset, who believe that their attributes are innate and unchangeable, may perceive negative feedback as threatening. Because they do not feel in control of changing these attributes, they are likely to be less motivated to take action in response to such feedback (Dweck and Leggett 1988; Dweck 2013). However, sometimes merely having a belief that one’s personality can be changed may not be sufficient to trigger real behavior change, and a mindset that actively seeks ways to improve oneself may be necessary.
Our two studies indicated that the strategic mindset and the growth mindset toward personality conceptually differ, as they were lowly to not at all correlated across our studies. It is possible that individuals may hold the belief that their personality traits can be developed but may not necessarily think about effective strategies to improve them. That is, simply possessing the knowledge of a growth mindset does not necessarily translate into practice when needed (Diener and Dweck 1978). Statistically, using regression models, both studies showed a significant and unique contribution of strategic mindset to social conflict processing and self-concept adjustment above and beyond the predictive power of growth mindset towards personality. Conversely, a growth mindset toward personality did not significantly predict these outcomes. These findings highlight the importance of strategic thinking in effectively navigating social feedback learning and suggest that a growth mindset alone may not be sufficient for individuals to adjust their self-concept effectively. Thus, our research findings enrich the literature on the growth mindset that was developed decades ago.
Limitations
There are a few caveats about the present research that need to be mentioned. Firstly, the current research relies on self-report measures to assess strategic mindset, which may introduce biases such as social desirability and variability in interpretation. This could affect the validity and reliability of the results. Future research should consider incorporating objective measures for a more comprehensive understanding of this construct. Secondly, our study represents the first effort to translate the strategic mindset scale into Chinese. While our pilot study and study 1 demonstrated robust reliability for the Chinese version of the Strategic Mindset measure, with Cronbach’s alpha values of 0.93 and 0.86, respectively, participants in study 2 showed less consistency across items, resulting in a low coefficient. Further research with a larger sample size is needed to validate the Chinese translation of the Strategic Mindset scale and to further investigate the relationship between a strategic mindset and self-concept adjustment. Thirdly, as the ERP study aimed to explore the relationship between the strategic mindset and the processing of social conflict and feedback, the lack of session 2 data makes it challenging to evaluate behavioral adjustments at the neural level. Fourthly, the lack of a control condition makes it difficult to determine whether the strategic mindset promotes social feedback processing and behavioral adjustments only when the information is socially relevant to the individual. Future studies could benefit from including control conditions where the feedback is either unrelated to the participants or in the nonsocial domain. Fifthly, the relatively small effect size in the current research calls for replication studies. The conceptual and practical relevance of our findings should also be interpreted with caution. Finally, the correlational nature of the current research does not allow for the establishment of causal relationships. Future studies could consider experimental designs that manipulate the strategic mindset or provide strategic mindset-related training to investigate causal links. Such studies would provide valuable insights into whether the strategic mindset can be intentionally cultivated and how it may impact various outcomes.
Conclusions
In conclusion, our research highlights the significance of a strategic mindset in social feedback processing and self-concept development. The results demonstrated that the strategic mindset holds unique predictive power beyond other factors and could potentially complement the well-documented growth mindset in facilitating personal growth. While a growth mindset encourages persistence, effective strategies are also necessary for pursuing self-improvement. A strategic mindset would encourage individuals to learn from others’ opinions, for example by seeking advice from experts. Future research could utilize our insights to design effective interventions aimed at encouraging individuals to ask themselves strategy-eliciting questions when faced with differing opinions thereby facilitating personal growth and development in educational and work settings.
Acknowledgments
We would like to thank Dr Fai Hong Lui for his supervision of ERP data analysis. This study was not preregistered. O.L.S. presented part of the findings at the 2024 Annual Conference of the Management Psychology Professional Committee of the Chinese Society of Social Psychology and the 6th China Forum on Management Psychology/Organizational Behavior, held on 2024 August 24, in Guilin, China.
Author contributions
Y. Huang and O. L. Siu (conceptualized the research ideas), Y. Huang and Y. Yang (carried out the experimental programming), Y. Yang (collected the data), Y. Huang and Y. Yang (performed the data analysis). All authors discussed and interpreted the results. Y. Huang wrote the original draft. All authors contributed to the final manuscript. Yi Huang (Conceptualization, Formal analysis, Funding acquisition, Methodology, Supervision, Validation, Visualization, Writing—original draft, Writing—review & editing), Yaqi Yang (Data curation, Formal analysis, Investigation, Methodology, Project administration, Visualization, Writing—review & editing), and Oi Ling Siu (Conceptualization, Resources, Supervision, Writing—review & editing).
Funding
This work was supported by the Faculty Research Grant of Lingnan University to Y.H. (SSFRG/23/1/R4).
Conflict of interest statement: None declared.
Data availability
The experimental materials and data can be downloaded from this link: https://osf.io/nvep6/?view_only=61cf797bc5424363a42f0e4cc4b507bf.
