Depression Tendency Individuals' Self-evaluation Bias during Social Comparison with Friend

Depression Tendency Individuals' Self-evaluation Bias during Social Comparison with Friend | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 23 January 2025 V1 Latest version Share on Depression Tendency Individuals' Self-evaluation Bias during Social Comparison with Friend Authors : Rui KOU 0000-0001-8479-6381 [email protected] , Rui Xu , Weiqi He , Ruolei Gu , and Wenbo Luo Authors Info & Affiliations https://doi.org/10.22541/au.173759794.47921212/v1 Published BMC Psychology Version of record Peer review timeline 247 views 160 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Social comparison is an important process that affects an individual’s self-assessment and subjective well-being. Previous studies have observed abnormal social comparison tendencies among depressed individuals, which may account for their social avoidance behavior. In this study, we asked participants to finish a simple gambling task with a friend, during which they could observe the outcome of their choice and that of their friend’s simultaneously (which were pseudorandomly determined). Behavioral measures and event-related potentials (ERP) elicited by outcome presentation (including the P2, feedback-related negativity, and P3 components) were recorded and analyzed. The whole sample consisted of a depression tendency (DT) group and a non-depressive control group, which were divided according to individual scores on Symptom Checklist-90 and Self-Rating Depression Scale. Compared to the controls, the DT group was generally in a more negative mood both before and after the experiment, as demonstrated by Positive Affect and Negative Affect Scale data. No between-group difference was detected regarding participants’ relationship closeness with their friend (as measured by the Inclusion of Other in the Self Scale) or self-reported outcome satisfaction. In contrast, the influence of depression on the P2 and FRN was significant. Specifically, the P2 elicited by self-win was larger in the controls than the DT group; also, it was sensitive to friend’s outcome in the DT group but not the control group. Finally, the FRN was sensitive to self-outcome in the DT group only when their friends had won. In our opinion, these results could be interpreted according to the relationship between depression and low self-esteem: compared to non-depressive ones, depressed individuals’ self-assessment is more susceptible to other people’s status, indicating more vulnerable self-esteem. Certainly! Apologies for the previous omissions. Below is the complete LaTeX document that includes all the requested sections, arguments, code snippets, and proofs, organized logically into a single cohesive document. “‘latex Depression Tendency Individuals’ Self-evaluation Bias during Social Comparison with Friend Running title: Depression Tendency and Social Comparison with Friend Rui Kou 1,2,3,# , Rui Xu 4,# , Weiqi He 2,3 , Ruolei Gu 5,6,* , Wenbo Luo 2,3,* 1 State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China 2 Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China 3 Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian 116029 4 Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China 5 CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China 6 Department of Psychology, University of Chinese Academy of Sciences, Beijing 100101, China * Corresponding author: Wenbo Luo, E-mail: [email protected] . Ruolei Gu, E-mail: [email protected] Acknowledgment: This study was funded by the National Natural Science Foundation of China (32020103008). Author contributions: WL conceived the experiment; RK performed the experiment, collected the data, and analyzed the data; RK, RX, RG, WQ, and WL wrote the manuscript. Declaration of ethics: All procedures performed in this study were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The local ethics committee approved the experimental protocol. Institutional Review Board Statement : The study was approved by the Ethics Committee of Liaoning Normal University (approval code lnnu2020-0068, approval date of 20 October 2020).Ethic Committee Name: the Ethics Committee of Liaoning Normal University. Approval Code:lnnu2020-0068. Approval Date:20 October 2020 Conflict of interest: The authors have declared that there is no conflict of interest in relation to the subject of this study. Data availability statement: All the data and code used in this study could be available by contacting the first author, Rui Kou (email: [email protected] ). Abstract Social comparison is an important process that affects an individual’s self-assessment and subjective well-being. Previous studies have observed abnormal social comparison tendencies among depressed individuals, which may account for their social avoidance behavior. In this study, we asked participants to finish a simple gambling task with a friend, during which they could observe the outcome of their choice and that of their friend’s simultaneously (which were pseudorandomly determined). Behavioral measures and event-related potentials (ERP) elicited by outcome presentation (including the P2, feedback-related negativity, and P3 components) were recorded and analyzed. The whole sample consisted of a depression tendency (DT) group and a non-depressive control group, which were divided according to individual scores on Symptom Checklist-90 and Self-Rating Depression Scale. Compared to the controls, the DT group was generally in a more negative mood both before and after the experiment, as demonstrated by Positive Affect and Negative Affect Scale data. No between-group difference was detected regarding participants’ relationship closeness with their friend (as measured by the Inclusion of Other in the Self Scale) or self-reported outcome satisfaction. In contrast, the influence of depression on the P2 and FRN was significant. Specifically, the P2 elicited by self-win was larger in the controls than the DT group; also, it was sensitive to friend’s outcome in the DT group but not the control group. Finally, the FRN was sensitive to self-outcome in the DT group only when their friends had won. In our opinion, these results could be interpreted according to the relationship between depression and low self-esteem: compared to non-depressive ones, depressed individuals’ self-assessment is more susceptible to other people’s status, indicating more vulnerable self-esteem. Keywords: depression, social comparison, friend, event-related potential, P2 Certainly! Apologies for the previous omissions. Below is the complete LaTeX document that includes all the requested sections, arguments, code snippets, and proofs, organized logically into a single cohesive document. “‘latex Introduction Severe expression of depression symptoms has been consistently linked with a tendency to disengage from social interactions (Nezlek, Hampton, & Shean, 2000; Nezlek, Imbrie, & Shean, 1994). This tendency is devastating to depressed individuals’ social functioning, leading to negative social consequences such as impaired affiliation and attachment, increased feelings of loneliness, and lack of social support (Kupferberg, Bicks, & Hasler, 2016; Segrin, 1998). According to the literature, depressed and at-risk individuals’ reduced motivation to interact with other people is largely due to their distorted self-views maintained by social comparison (Swallow & Kuiper, 1988, 1992). Based on this knowledge, investigating the influence of depression on social comparison processes is clinically meaningful and could help understand the development of depressive symptoms (Appel, Crusius, & Gerlach, 2015; Appel, Gerlach, & Crusius, 2016; Feinstein et al., 2013). Social comparison refers to an internal assessment of the self during the process of comparing with others (Festinger, 1954). When there is no objective standard, people may evaluate their abilities by utilizing the comparison between self and others. Even in the situations of irrelevant comparison (i.e., others’ performance has nothing to do with self-outcome), individual assessment of self-outcome would still be affected by that of others (Leng & Zhou, 2014; Yu & Zhou, 2006; H. Zhang et al., 2020). It has long been suggested that the negative self-evaluation associated with depression should be interpreted from a social comparison perspective (Ahrens, 1991; McCarthy & Morina, 2020). Classic studies have revealed that depressed individuals are more prone to be involved in both upward comparison (the information of which supports their negative self-evaluation: see Beck, 1967, 1976) and downward comparison (which might be ego-enhancing and helps alleviate negative affect: see Gibbons, 1986). According to Swallow and Kuiper (1988), depressive individuals are more likely to anticipate further negative self-evaluative consequences under the influence of unfavorable social comparison, leading to social withdrawal and self-imposed isolation that play important roles in the etiology and maintenance of depression. To our knowledge, previous findings supporting the above idea have been predominantly derived from observations on social comparison with other people in general or with strangers (e.g., an anonymous opponent) (Hedley & Young, 2006; Hwnag, 2019; Sheeran, Abrams, & Orbell, 1995; Tabachnik, Crocker, & Alloy, 1983). In contrast, the current study focuses on comparisons with close relations (more specifically, friends), seeing that comparing with familiar others who show similar ability with oneself provides the most useful information for self-evaluation (Festinger, 1954; Swallow & Kuiper, 1988). Some recent studies on social media have indicated a negative relationship between depression and self-esteem during the browsing of social networking sites; however, these results were about online connections rather than real friendship in daily life (Alfasi, 2019; Appel et al., 2016). This study utilized the event-related potential (ERP) technique for three reasons. First, unlike behavioral approaches (e.g., self-reports), neuroscience methods including the ERP are insensitive to demand characteristics and social desirability bias. Also, social comparison represents characteristics of unconsciousness and spontaneity, which are beyond the reach of self-reports (Festinger, 1954). Third, social comparison could be unfolded into different stages that overlap in the time domain (Mussweiler, 2003), which should be better captured by the ERP technique owing to its outstanding exquisite temporal resolution (Amodio, Bartholow, & Ito, 2014). In light of previous relevant research (Kou, Zhang, Lv, & Luo, 2022; Luo et al., 2015; H. Zhang et al., 2021; H. Zhang et al., 2020), we were most interested in three ERP indexes. The first one is the P2 component that emerges approximately 200 ms post-stimulus, indicating an early stage of attention processing (Carretié, Mercado, Tapia, & Hinojosa, 2001; Potts, Patel, & Azzam, 2004). An enhanced P2 amplitude indicates increased attention to stimuli with intrinsic personal relevance (e.g., self-referential information: see Hu, Wu, & Fu, 2011; L. Wu, Gu, Cai, Luo, & Zhang, 2014; L. Wu, Gu, & Zhang, 2016). Following the P2, the feedback-related negativity (FRN) is a negative-going wave peaking at a latency of approximately 250-300 ms (Gehring & Willoughby, 2002; Miltner, Braun, & Coles, 1997), which differentiates between unfavorable and favorable outcomes (Hajcak, Moser, Holroyd, & Simons, 2007; Holroyd, Hajcak, & Larsen, 2006). Finally, the P3 component (reaching its maximum after 300 ms post-stimulus) has been associated with various cognitive functions in previous studies (Polich, 2007; Polich & Criado, 2006) and is proposed to reflect the emotional significance and emotion regulation process of the ongoing event in decision-making tasks (Gu, Ao, Mo, & Zhang, 2020; Lewis, Lamm, Segalowitz, Stieben, & Zelazo, 2006; Polezzi, Sartori, Rumiati, Vidotto, & Daum, 2010). According to Luo et al. (2015), the above three ERP components represent three stages of social comparison from the perspective of brain activity, that is, whether an individual’s self-outcome deviates from any other-outcome (P2), whether s/he belongs to the majority or the minority according to that outcome (FRN), and the distance between different persons’ outcome levels (P3) (see also Hu & Mai, 2021; Lin et al., 2021; Pfabigan et al., 2018; Qi, Wu, Raiha, & Liu, 2018; Uusberg, Peet, Uusberg, & Akkermann, 2018; Valt, Sprengeler, & Stürmer, 2020; Y. Wu, Zhang, Elieson, & Zhou, 2012). In addition, these components are sensitive to abnormalities in social information processing among depressed individuals; for instance, the FRN elicited by social reward (e.g., a smiling face) is negatively correlated with individual depression level, indicating social anhedonia associated with depression (D. Zhang et al., 2020; D. Zhang, Xie, He, Wei, & Gu, 2018). Nevertheless, it remains unclear whether these components would be modulated by individual depression level during social comparison with one’s friends. In this study, we investigated the potential effect of depression tendency (DT), which is defined as having one or more mild depressive symptoms that do not meet the diagnostic criteria for depression (Kou et al., 2022). Participants with DT and normal controls were recruited to finish a simple decision-making task, in which they compared their task performance with that of a friend (H. Zhang et al., 2021; H. Zhang et al., 2020), so as to collect their behavioral and ERP data. By analyzing the P2, FRN, and P3 component during the task, we aimed to find out whether DT individuals would show deficits in any specific stage of social comparison with their friends. Materials and Methods Participants A priori power analysis using G*Power (Faul, Erdfelder, Buchner, & Lang, 2009; Faul, Erdfelder, Lang, & Buchner, 2007) revealed that 36 participants would ensure 95% statistical power when the effect size was supposed to be 0.25 (Vazire, 2016). Two hundred new college students at a local University finished the Chinese version of the Symptom Checklist-90 (SCL-90: Derocatis, Lipman, & Covi, 1973) and Self-Rating Depression Scale (SDS: Zung, 1965) during a mental health assessment. An SDS index was generated from original data by dividing the sum of raw score by the maximum possible score of 80 (Zung, 1965). According to the results of these questionnaires, the students whose SCL-90 depression dimension ≥ 1.5 and SDS index > 0.5 were considered as DT individuals, while those whose SCL-90 depression dimension < 1.5 and SDS index ≤ 0.5 were consider as non-depressive controls (Gabrys & Peters, 1985; Masal, Koccedil, & Takunyaci, 2013). The students who met the above criteria were randomly invited to complete the SDS again (the SCL-90 was not tested again because it requires a long time to finish). Finally, 20 students in the DT group (11 female) and 20 in the control group (10 female) who scored no significant difference between the two screenings participated in the formal experiment. The between-group difference in SDS index was significant according to the second screening (0.51 ± 0.09 vs. 0.41 ± 0.07 [mean ± standard deviation], t (38) = 3.517, p = 0.001; see Figure 1 ), but no age difference was found (20.25 ± 0.96 vs. 20.85 ± 1.26; t (38) = 1.683, p = 0.101). All participants were right-handed, with normal visual acuity, routine visual acuity or corrected visual acuity, reported no red-green blindness, no brain injury, and no diagnosed psychological or psychiatric disorders. Informed consent was obtained from each participant and the study followed the guidelines of the ethics committee. Two weeks before the formal experiment, the same sample had participated in another research focusing on self-evaluation, the results of which have been reported elsewhere (Kou et al., 2022). Figure 1. The SDS score (generated by dividing the sum of raw score by the maximum possible score of 80) in two groups according to the second screening. DT: depression tendency. Tasks and Procedures On the experimental day, each participant was asked to bring a close friend of the same gender (no romantic partner) to the laboratory. A recent photo of that friend with blue background (frontal view; 25 mm × 35 mm) was also required. Each participant was first asked to finish the Chinese version of the Positive Affect and Negative Affect Scale (PANAS), which consists of 10 words for positive affect and 10 words for negative affect, to assess their emotional state at the moment using a five-point scoring method (Watson, Clark, & Tellegen, 1988). S/he also completed the Inclusion of Other in the Self (IOS) Scale, which is a single-item pictorial questionnaire (7-point), to measure the degree of relationship closeness between her/himself and that friend (Aron, Aron, & Smollan, 1992). Each participant then stayed in an electrically shield room for electroencephalogram (EEG) recording, sitting at a comfortable chair approximately 70 cm from the computer screen. Her/his friend sat in another room finishing the same task without EEG recording (see Figure 2 ). After the formal task (see below), each participant was asked to complete the PANAS again, as well as a questionnaire regarding the level of satisfaction on a seven-point scale (1= very dissatisfied; 7 = very satisfied) about each type of outcome during the task. Approximately 1.5 hours were spent on the whole experiment for each participant. Figure 2. Experimental schematic diagram. Before the formal task, each participant was given written instructions about the rules and was reminded of her/his right to discontinue participation at any time. S/he also finished a short practice to get familiar with the stimuli in the task. Each participant was told that s/he would be paid ¥30 (about US $4) as a basic payment for their participation, and her/his task performance would determine how much s/he would be awarded or penalized on top of this basic payment. The formal task design was adapted from our previous studies (H. Zhang et al., 2021; H. Zhang et al., 2020). This gambling task began by displaying the photo of each participant’s friend, which functioned as a cue to remind the participant that s/he was playing the task with her/his friend simultaneously (see Figure 3a ). Each participant pressed the space button when s/he saw the photo, in order to start the formal task. At the beginning of each trial (see Figure 3b ), a white fixation point appeared on a black screen for 500 ms. Then two gray cards (1.9º × 1.9º) appeared on the left and right side of that fixation point, and the participant should choose the left or right card by pressing the ”F” or ”J” button on the keyboard (with her/his left or right forefinger) to finish gambling. The selected card was highlighted by a thick red (or blue) frame for 500 ms. After an interval of 500 − 1000 ms (jitter), the outcome of the participant’s choice (self-outcome) and that of her/his friend’s choice (friend-outcome) appeared on two sides of the fixation point for 1000 ms, which were framed by different colors (red/blue: counterbalanced across participants). Each outcome was either a gain (indexed by the symbol ”+”: final payment increased for ¥0.5) or a loss (indexed by the symbol ”−”: final payment decreased for ¥0.5). According to the cover story, laboratory computers in different rooms were connected via a local area network, therefore s/he could observe the outcome of her/his friend’s choice in real time; however, there was no way for her/him or the friend to affect each other’s outcome. Unbeknownst to each participant, the outcomes were actually provided pseudorandomly regardless of her/his choice or the friend’s choice, such that each participant received an equal number of trials for each kind of outcome throughout the task. Finally, an empty screen lasting for 500 ms indicated the end of the current trial. The formal task consisted of eight blocks, each of which had 64 trials. Stimulus presentation and behavioral data acquisition were conducted by the E-prime 2.0 software package (Psychology Software Tools, Pittsburgh, PA, USA). Figure 3. An illustration of a single trial in the formal task. ERP recording and analysis Brain Products EEG Record System (Brain Product, Herrsching, Germany) was used to record the data. The EEG was recorded (bandpass 0.016 − 70 Hz, sampling rate = 500 Hz) with two scanned amplifiers, using a 64-channel electrode elastic cap with Ag/AgCl (tin) electrodes according to the extended international 10-20 system. All electrodes were referenced to the vertex first. The vertical electrooculograms and the horizontal electrooculograms were installed at 1.5 cm below the right eye and 1.5 cm outside the left eye, respectively. All interelectrode impedances were lower than 5 kΩ. EEGLAB 14.1.1 toolbox under the MATLAB 2015a environment was used to analyze the offline EEG data (Delorme & Makeig, 2004). Data were first re-referenced off-line to the average of the left and right mastoids, then were digitally filtered with a bandpass 0.1 − 30 Hz. A notch-pass filter of 50 Hz was also applied. The data were then segmented into epochs from 200 ms before to 800 ms after outcome onset, with the time window of -200 − 0 ms served as baseline. The independent component analysis (ICA) method was used to remove eye movement artifacts (Debener, Thorne, Schneider, & Viola, 2010). Epochs containing artifacts exceeding ± 70 μV were excluded from data analysis. According to previous ERP studies focusing on social comparison (Gu, Wu, Jiang, & Luo, 2011; Liu, Hu, Shi, & Mai, 2018), we calculated the average over the three midline electrode locations (i.e., Fz, Cz, and Pz) to measure the P2, FRN, and P3 (see also Burnside & Ullsperger, 2020; Takayoshi, Onoda, & Yamaguchi, 2018; Wang, Liu, & Shi, 2020). Time windows for data analysis were selected based on visual observation of the grand average waveforms (see Figure 5 ), which was 200 − 280 ms for P2 mean amplitude, 280 – 340 ms for FRN mean amplitude, and 340 − 440 ms for P3 mean amplitude. Statistics Behavioral and ERP data were statistically analyzed using SPSS software (version 20.0, SPSS Inc., Chicago, IL, USA). A mixed three-way repeated measure analysis of variance (ANOVA) was applied on the data with one between-subjects factor (DT vs. control) and two within-subject factors (self-outcome: win vs. loss; friend-outcome: win vs. loss). The significance level was set at 0.05 for all the analyses. Partial eta-squared ( η p 2 ) values were conducted to examine the effect size in ANOVA models, such that 0.05 represents a small effect, 0.1 represents a medium effect, and 0.2 represents a large effect (Cohen, 1973). Greenhouse-Geisser correction of the ANOVA assumption of sphericity was applied when appropriate. For brevity, only significant results were reported below. Certainly! Apologies for the previous omissions. Below is the complete LaTeX document that includes all the requested sections, arguments, code snippets, and proofs, organized logically into a single cohesive document. “‘latex Behavioral data IOS questionnaire. No between-group difference was found on the IOS score according to a one-way ANOVA ( F (1, 38) = 0.158, p = 0.693, η p 2 = 0.004). PANAS. Independent-sample t -tests revealed that the PANAS negative affect score (calculated as mean value), but not positive affect score, showed significant between-group difference both before ( t (32) = 5.27, p < 0.001) and after the formal experiment ( t (38) = 3.13, p = 0.003); that is, negative affect score was higher in the DT group than the control group (before the experiment: 2.86 ± 0.71 vs. 1.83 ± 0.42; after the experiment: 2.40 ± 0.69 vs. 1.83 ± 0.42). Please note that six participants (all in the DT group) did not complete the PANAS before the experiment due to an unintentional omission by the experimenters. Excluding these participants from data analysis on the PANAS score after the experiment does not affect our major findings (negative score: DT vs. control = 2.54 ± 0.71 vs. 1.83 ± 0.42, t (32) = 3.64, p = 0.001; positive score: p = 0.846). Self-reported satisfaction. A mixed three-way repeated measure ANOVA (see the Statistics) was performed on the satisfaction level, which showed that the main effect of self-outcome ( F (1, 38) = 63.79, p < 0.001, η p 2 = 0.627) and the interaction of self-outcome × friend-outcome ( F (1, 38) = 24.20, p < 0.001, η p 2 = 0.389) were significant. A simple effect analysis on this interaction indicated that the satisfaction level was higher for friend-win than friend-loss in the self-win condition ( p < 0.001), but not in the self-loss condition (see Figure 4 ). Figure 4. A bar graph showing the interaction of self-outcome × friend-outcome regarding self-reported satisfaction score in the whole sample. Gambling performance. These behavioral data were not analyzed seeing that the outcomes of the gambling task were predetermined and there was no optimal strategy. ERP data P2 amplitude. A three-way ANOVA on the P2 amplitude showed that the main effect of self-outcome was significant ( F (1, 118) = 119.40, p < 0.001, η p 2 = 0.503), indicating that the P2 was larger for self-win (6.64 ± 3.86 μV) than self-loss (5.30 ± 3.43 μV). Also, the interaction of self-outcome × group was significant ( F (1, 118) = 7.30, p = 0.008, η p 2 = 0.058): in the self-win condition, the group effect was significant, indicating that the P2 was larger among the controls (7.20 ± 3.99 μV) than among the DT group (6.07 ± 3.65 μV; p = 0.025); in the self-loss condition, this between-group difference was non-significant ( p = 0.367). There was a significant interaction effect of self-outcome × friend-outcome ( F (1, 118) = 17.22, p < 0.001, η p 2 = 0.127): in the self-win condition, the P2 was larger for friend-win (6.98 ± 4.12 μV) than friend-loss (6.29 ± 3.60 μV; p < 0.001); in the self-loss condition, this effect was non-significant ( p = 0.074; see Figure 5 & 6 ). Finally, there was a significant interaction effect of group × friend-outcome ( F (1, 118) = 8.94, p = 0.003, η p 2 = 0.070): a simple effect analysis showed that the P2 was larger for friend-win (5.86 ± 3.56 μV) than friend-loss (5.32 ± 3.35 μV) in the DT group ( p = 0.001), but not in the control group ( p = 0.467). FRN amplitude. A three-way ANOVA on the FRN amplitude showed that the main effect of self-outcome was significant ( F (1, 118) = 54.64, p < 0.001, η p 2 = 0.316), indicating that the FRN was larger (i.e., more negative-going) for self-loss (3.97 ± 2.76 μV) than self-win (5.56 ± 3.47 μV). Also, there was a significant interaction effect of self-outcome × friend-outcome × group ( F (1, 118) = 6.33, p = 0.013, η p 2 = 0.051). To explain this three-way interaction effect, we found that the self-outcome × friend-outcome interaction was significant in the DT group ( p self-win) was significant for friend-win but not friend-loss in the DT group (see Figure 5 & 6 ). Figure 5. Upper panels: Grand-average ERP waveforms elicited by outcome onset at the electrode site Cz. The time windows for analyzing the P2, FRN, and P3 were marked in gray line rectangles. Lower panels: Topographical scalp distribution of each ERP component for each condition. DT: depression tendency; FRN: feedback-related negativity. Figure 6. Bar graphs showing the interactions of (a) self-outcome × depression tendency (DT), (b) self-outcome × friend-outcome, and (c) friend-outcome × DT on the P2 amplitude; (d) the interaction of self-outcome × friend-outcome × DT on the FRN amplitude. P3 amplitude. A three-way ANOVA on the P3 amplitude found that only the main effect of self-outcome was significant ( F (1, 118) = 32.60, p < 0.001, η p 2 = 0.216), indicating that the P3 was larger for self-win (6.70 ± 4.13 μV) than self-loss (5.60 ± 3.64 μV). Potential relationship between behavioral and ERP data. . We also explored the potential relationship between IOS score and P2 amplitude by calculating their two-tailed Pearson correlation, which showed no significance for either friend-loss or friend-win in the whole sample ( p ≥ 0.082), the DT group ( p ≥ 0.196), or the control group ( p ≥ 0.225). Discussion It has long been suggested that dysfunctional social comparison plays an important role in depressed individuals’ daily life (Swallow & Kuiper, 1988). This study asked a DT group and a control group to finish a simple gambling task, in which participants could compare their decision outcome with that of a friend’s. Behavioral measures and ERP data were collected to investigate the potential influence of depression on social comparison. According to the results, PANAS negative (but not positive) affect score was higher in the DT group than the control group both before and after the experiment, indicating that the DT participants were generally in a more negative mood than the controls (which should not be surprising). Although self-reported satisfaction score was insensitive to individual DT level, we found significant group effects on the ERP components P2 and FRN (but not the P3 component: see below), supporting our idea that the ERPs could reflect underlying cognitive and affective processes beyond participants’ introspection (see also Amodio et al., 2014). In contrast, no group effect was found on the IOS score, indicating that the degree of relationship closeness between participants and their friends had been controlled between groups and therefore should not have confounding influence on our results. According to participants’ self-reports, their satisfaction level was higher for friend-win than friend-loss, but only when they received a winning outcome for themselves. This result was consistent with our previous findings (H. Zhang et al., 2021; H. Zhang et al., 2020) and was in line with the classic self-evaluation maintenance model that the success of a close other could be perceived as a threat when it causes one’s own performance to pale by comparison (Tesser, Millar, & Moore, 1988). In short, we believe that the results of self-reported outcome satisfaction were reasonable, indicating that the participants treated decision outcome seriously. Regarding the ERP data, we first found that the P2 amplitude was larger for self-win than self-loss. Further, the P2 elicited by self-win was larger in the controls than the DT group. As mentioned in the Introduction, the P2 amplitude may indicate the amount of attention devoted to stimuli with intrinsic personal relevance (see also Cao, Gu, Bi, Zhu, & Wu, 2015; H. Wu et al., 2016). Paying attention to one’s own success is an important strategy for protecting self-esteem, which is good to maintain mental health in everyday life (Sedikides & Gregg, 2008; D. Zhang et al., 2022). In our opinion, the P2 results indicate that the controls allocated more attentional resources on self-win than did the DT participants. In addition, the P2 amplitude was sensitive to friend’s outcome in the DT group but not the control group. As verified by correlation analysis, this finding could not be accounted for by between-group difference in interpersonal closeness with friends. We therefore suggest that compared to the controls, DT individuals generally judged their friend’s outcome to be more self-relevant, possibly because their self-evaluation relied more on other people’s performance (Roberts & Monroe, 1994; Sowislo & Orth, 2013). The FRN was also modulated by the group factor, such that its amplitude was sensitive to self-outcome (self-loss > self-win) in the DT group only when their friends had won; in contrast, the self-outcome effect manifested regardless of friend-outcome in the controls. In our opinion, the FRN results could be viewed as another evidence that in contrast to their non-depressive counterparts, DT individuals’ self-evaluation depends too much on close others’ performance, to the extent that they might be unable to evaluate their own performance appropriately. Meanwhile, the P3 amplitude showed no significant between-group difference, possibly reflecting that in contrast to patients with severe depressive symptoms, the emotional processing and emotion regulation function in DT individuals are relatively intact (Joormann & Stanton, 2016; Ritchey, Dolcos, Eddington, Strauman, & Cabeza, 2011). In our opinion, DT individuals’ social comparison tendencies (as reflected by the P2 and FRN data) were manifestations of their low self-esteem. On one hand, one’s social comparison processes could be strongly modulated by her/his self-esteem level, such as devaluing oneself due to other’s success (Alfasi, 2019; Dagnan & Sandhu, 1999). On the other hand, the close relationship between depression and self-esteem has been well established (Roberts & Monroe, 1994). Longitudinal studies have demonstrated that low self-esteem constitutes as one of the key factors in depression ontology, that is, both level and change in adolescent self-esteem predict adult depression (Hilbert et al., 2019; Sowislo & Orth, 2013; Steiger, Allemand, Robins, & Fend, 2014). Indeed, low self-esteem and consequent feelings of inferiority play a crucial role in the onset or recurrence of depression (Appel et al., 2015). However, a significant limitation of our theory is that we did not measure individual level of self-esteem directly. To sum up, our ERP results indicate that DT individuals focus too much on other people’s status when making self-evaluation, which might be harmful to the maintenance of their self-esteem and mental-health. In line with our findings, Swallow and Kuiper (1992) point out that depressed individuals make frequent comparisons with others, particularly following poor performance; as a result, they are more likely to be exposed to unfavorable feedback and evaluate themselves in a more negative way. These abnormalities in social comparison processes may help explain why depression level is negatively correlated with the quality of social life (Nezlek et al., 2000; Rotenberg & Hamel, 1988). In our opinion, the current findings provide insight into the importance of social comparison in developing and maintaining negative self-evaluations in depressed individuals (see also Swallow & Kuiper, 1988), thus would be helpful to depression prevention and intervention. As we mention above, follow-up studies should examine whether self-esteem acts as a mediating variable between depression and social comparison. 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Authors Affiliations Rui KOU 0000-0001-8479-6381 [email protected] Beijing Normal University View all articles by this author Rui Xu China Academy of Chinese Medical Sciences View all articles by this author Weiqi He Liaoning Normal University View all articles by this author Ruolei Gu Beijing Normal University View all articles by this author Wenbo Luo Liaoning Normal University View all articles by this author Metrics & Citations Metrics Article Usage 247 views 160 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Rui KOU, Rui Xu, Weiqi He, et al. Depression Tendency Individuals' Self-evaluation Bias during Social Comparison with Friend. Authorea . 23 January 2025. DOI: https://doi.org/10.22541/au.173759794.47921212/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. 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