Literature DB >> 33270780

Status, rivalry and admiration-seeking in narcissism and depression: A behavioral study.

Anna Szücs1,2, Katalin Szanto1, Jade Adalbert3, Aidan G C Wright4, Luke Clark3, Alexandre Y Dombrovski1.   

Abstract

Humans seek admiration to boost their social rank and engage in rivalry to protect it when fearing defeat. Traits such as narcissism and affective states such as depression are thought to influence perception of rank and motivation for dominance in opposite ways, but evidence of the underlying behavioral mechanisms is scant. We investigated the effects of dimensionally-assessed narcissism and depression on behavioral responses to social defeat in a rigged video game tournament designed to elicit rivalry (stealing points from opponents) and admiration-seeking (paying for rank). We tested an undergraduate sample (N = 70, mean age = 21.5 years) and a clinical sample of predominantly depressed elderly (N = 85, mean age = 62.6 years). Both rivalry and admiration-seeking increased with time on task and were particularly enhanced in individuals high in narcissism. Participants engaged in more rivalry when pitted against high-ranked opponents, but depression partially mitigated this tendency. Our findings provide behavioral evidence that narcissism manifests in increased rivalry and admiration-seeking during social contests. Depression does not suppress general competitiveness but selectively inhibits upward-focused rivalry.

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Year:  2020        PMID: 33270780      PMCID: PMC7714187          DOI: 10.1371/journal.pone.0243588

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

As primates whose survival and reproduction depend on our standing in a group, we integrate social comparisons, victories, and defeats into an implicit estimate of our social status or rank. Thus, we learn our place and decide how to best improve or maintain it [1-3]. Our implicit rank, i.e. the hierarchical rank manifested through our behavior, is recalibrated following unexpected outcomes of social comparisons against others [4]. Consistently, we tend to avoid confrontations with superiors without a reasonable probability of success [5] and prefer same-level comparisons, which give a better chance of increasing our status while remaining reasonably safe [6]. Individuals, as well as firms, political parties, and sports teams act more competitively when facing similarly-ranked counterparts than stronger ones [7-10]. When threatened with social defeat, people tend to engage in self-enhancement, which aims to increase social rank, and in self-protection, which aims to avoid further losses by fleeing or fighting back [11]. These competitive behaviors are subject to marked individual differences [12], and can sometimes reach irrational and socially disadvantageous extremes [13,14]. This paper explores behavioral responses to social defeat in narcissism and depressive states, linked by prior self-report and interview studies to opposite patterns of dominant and submissive behaviors [15]. In narcissism, implicit rank is inflated [16] and also closely monitored [17], which may confer certain fitness advantages. Fierce protection of one’s dominant status [18] may improve access to resources, and self-inflation improves mating chances [19,20]. These strategies, however, can backfire when affiliation- rather than dominance-driven responses are called for [21], for example during prolonged periods of adversity [22]. The prospect of losing status elicits intense emotions in highly narcissistic individuals [23,24], and leads to counteroffensives to reassert dominance [25]. Back and colleagues termed narcissistic self-enhancement admiration-seeking (seeking status through self-promotion), and narcissistic self-protection rivalry (antagonizing those perceived as threatening) [26]. Whereas healthy rivalry is attuned to the social rank of the opponent, highly narcissistic persons may engage in indisciminate rivalry [27], often despite dire moral and financial consequences, and without explicit provocation [28]. At the same time, admiration-seeking takes a comparative form in more narcissistic individuals [29], and is mostly directed towards high-status others [27]. In contrast, depression is thought to shift priorities from achieving dominance to preventing conflict [15,30]. Animals subordinated by aggressive conspecifics become socially avoidant and lack vigor in seeking rewards, a state mediated by plasticity in the mesostriatal pathway and reversed by antidepressants [31,32]. Consistently, subordinate mice display lower anxiety in situations of chronic social defeat than dominant mice [33]. In humans, depressive states appear to deflate one’s implicit rank [34], decrease social comparisons and increase submissive behavior when these characteristics are measured by self-reports [35]. Conversely, assertively renegotiating one’s role in key relationships is thought to be one mechanism of change in interpersonal therapy for depression [36]. These findings suggest that behavioral and neural plasticity induced by social defeat constitute one component of human depressive states. Thus depressive symptoms are expected to inhibit both rivalry and admiration-seeking in competitive environments. In summary, while self-report studies describe broadly opposing reactions to social defeat in narcissism and depression, this concept’s behavioral manifestations are yet to be tested experimentally. Toward this end, we investigated the effects of dimensionally-measured narcissism and depression on self-protective and self-enhancing behaviors in situations of defeat in a competitive setting. Using a rigged video game tournament paired with a league table, we elicited rivalry (stealing points from opponents), and admiration-seeking (paying to increase one’s rank), in an undergraduate sample and a clinical sample of predominantly depressed older adults. To uncover effects of implicit rank (participants’ hierarchical status inferred from their behavioral choices), our task manipulated the rank of opponents to examine whether rivalry and admiration-seeking were directed upwards or downwards in the social hierarchy. We expected (H1a) both rivalry and admiration-seeking to increase as a reaction to the cumulative experience of defeat throughout the task; (H1b) narcissism to further enhance both behaviors, prompting a more intense reaction to defeat [26]; and (H1c) depression to dampen them, favoring submissive responses to adversity [35]. Participants’ implicit rank was indicated by their level of competitive involvement, i.e. rivalry and admiration-seeking as a function of the opponent’s rank. We hypothesized that (H2a) high-ranked opponents would elicit more rivalry and admiration-seeking than low-ranked opponents, given that high-ranked opponents will be perceived as similar or superior to oneself and thus more threatening [6]. Additionally, (H2b) this effect would be further enhanced by narcissism, which is known to shift implicit rank upward [16], and (H2c) mitigated by depression, which tends to lower implicit rank [34].

Materials and methods

Participants

All procedures were approved by the Behavioural Research Ethics Board of the University of British Columbia for Sample 1 and the Institutional Review Board of the University of Pittsburgh for Sample 2. All participants provided their written, informed consent before starting the experiment. Sample 1 included 70 undergraduate students enrolled at the University of British Columbia, Vancouver, Canada (mean age 21.5 years), who participated (in individual sessions) for course credit. Sample 2 included 85 adults aged 50 or older (mean age 62.6 years) participating in the Longitudinal Research Program in Late-life Suicide, in Pittsburgh, United States, a larger ongoing study [37]. Correlates of the present experimental task with suicidal behavior in Sample 2 will be reported elsewhere. Participants from Sample 2 were originally recruited as 25 healthy subjects with no lifetime history of psychiatric disorder and 60 subjects with clinical levels of depression, scoring 14 or higher on the Hamilton Rating Scale for Depression (HRSD) upon study recruitment. The present study treated depression as a continuous variable in both samples. Significant effects were nevertheless tested in a categorical sensitivity analysis in Sample 2 (Fig C in S1 Appendix). Sample characteristics can be found in Table A of S1 Appendix.

Behavioral task

We used a rigged video game tournament to elicit rivalry and admiration-seeking behaviors under a threat of social defeat (Fig 1; the task is freely available at https://github.com/aszucs/cobra_task_v1).
Fig 1

Task description.

Each of the 24 trials has the following steps: (A), new opponent is displayed with name and league rank (participants are told that these opponents are all previous players whose performance has been prerecorded); (B), 1st outcome measure: willingness to steal points from the opponent’s future score in order to increase one’s chance of defeating him/her; (C), playing the snake arcade game for 20 seconds, with the goal of gathering as many points (apples) as possible, while one’s score (the number of apples caught) is displayed, as well as a message at 10 seconds informing the participant whether he/she is ahead, behind, or the outcome is close; (D), learning the contest’s outcome, which defines whether the participant will move 5 ranks up or down in the global ranking. These outcomes are rigged towards a 2:1 defeat to victory ratio occurring in a pseudorandom order; (E), 2nd outcome measure: willingness to buy extra rank; (F), learning current rank in the competition. ($ $), each trial starts with a renewed virtual endowment that the participant can choose to spend on extra ranks. Participants are told that their real money payoff will be computed based on their savings from three random trials. Note. The computer version is in color.

Task description.

Each of the 24 trials has the following steps: (A), new opponent is displayed with name and league rank (participants are told that these opponents are all previous players whose performance has been prerecorded); (B), 1st outcome measure: willingness to steal points from the opponent’s future score in order to increase one’s chance of defeating him/her; (C), playing the snake arcade game for 20 seconds, with the goal of gathering as many points (apples) as possible, while one’s score (the number of apples caught) is displayed, as well as a message at 10 seconds informing the participant whether he/she is ahead, behind, or the outcome is close; (D), learning the contest’s outcome, which defines whether the participant will move 5 ranks up or down in the global ranking. These outcomes are rigged towards a 2:1 defeat to victory ratio occurring in a pseudorandom order; (E), 2nd outcome measure: willingness to buy extra rank; (F), learning current rank in the competition. ($ $), each trial starts with a renewed virtual endowment that the participant can choose to spend on extra ranks. Participants are told that their real money payoff will be computed based on their savings from three random trials. Note. The computer version is in color. The snake arcade game (adapted from the classic video game to Python 2.7) served as a basis to the competition and was embedded in a tournament interface programmed in Matlab, version 2016b. Each of the 24 trials was divided into a contest phase, when participants played a round of the snake arcade game against different opponents, and a ranking phase, where they gained or lost status in the tournament’s league standings. Rivalry was measured by the willingness to steal points from the opponent before the contest (henceforth point stealing). Admiration-seeking was measured by the willingness to pay virtual money to increase one’s rank in the league during the ranking phase (henceforth rank buying). Whereas point stealing had a moral cost of being unfair and unsportsmanlike, participants were told that rank buying had a financial cost: they were instructed that their real money payment would be calculated based on the amount of virtual money saved on each trial, whereas their final standing in the game would not impact the payoff. The end-game payoffs were in fact the same for all participants. To emulate a real-life social environment, participants were told they were playing against previous study participants whose performance had been recorded. To support this cover story, they chose an avatar to represent themselves in the game and entered a pseudonym; we instructed them not to use their real name, to preserve confidentiality. As a final step, participants were asked to choose whether they wanted to appear in the tournament’s league table against future participants. Participants were in fact playing against virtual opponents, arranged in a pseudorandom order and paired with predefined outcomes, having an overall 2:1 defeat to victory ratio. To mask the rigged outcomes, two additional manipulations were added during the arcade game: the commands from the original snake game were reduced to only the left/right arrow keys, turning the snake 90 degrees left or right on its own axis of reference; second, fewer apples (points) were available for collection on losing trials. The goal of these manipulations was to enhance the game’s difficulty, and elicit feelings of frustration and helplessness due to poor performance [38]. Finally, virtual monetary endowments and real money payoffs were adapted to each sample: in Sample 1, participants received 5 CAD (Canadian Dollars) as the trial-by-trial endowment and 7.50 CAD as the overall payoff, while in Sample 2, participants received 20 USD (U. S. Dollars) as the trial-by-trial endowment and 25 USD as the payoff. The game recorded four subject-dependent variables. The two main outcome measures were participants’ choices for point stealing (integers ranging from 1: no point stealing to 5: stealing 10 points from opponent) and rank buying (integers ranging from 1: no rank buying to 5: buying 5 extra ranks for half of the trial-by-trial endowment’s amount). Additionally, the game recorded participants’ own rank (recoded for analysis in an increasing order from 1 = worst rank to 200 = best rank) and scores (number of points on the snake arcade game) on each trial. These two additional subject-dependent variables were used as covariates during the analysis of the main outcome measures (see Statistical Analysis below). Scores were additionally employed in quality checks measuring game performance and task engagement (pages 11–13 in S1 Appendix).

Other assessments

At the beginning of the task, participants indicated their video game experience (integers ranging from 1: never played any games including smartphones and tablets to 5: playing every day). After the task, participants answered twelve additional questions about their motivations and impressions of the game that were examined in an exploratory analysis (Fig H in S1 Appendix). Demographic characteristics (age, sex, ethnicity and household income) were collected at baseline. Due to divergence in data collection, household income was coded as an ordinal variable in Sample 1 and as logged amounts in Sample 2. Years of education were only assessed in Sample 2, as Sample 1 comprised undergraduates. Ethnicity and household income were missing in three participants of Sample 1. Narcissism was assessed by the FFNI (Five-Factor Narcissism Inventory) [39] and was treated as a continuous variable, given its dimensional structure corroborated by recent studies [40]. The FFNI’s distribution in our two samples can be found in Fig A in S1 Appendix. As a senstivity analysis testing the generalizability of our findings to the more pathological aspects of narcissism [41,42], we additionally used the BPNI (Brief Pathological Narcissism Inventory), a 28-item version of the Pathological Narcissism Inventory [43]. We used total scores in our main analysis, but investigated whether specific dimensions of narcissism were driving the observed behavioral effects in an exploratory analysis including FFNI subscales agentic extraversion, antagonism, and narcissistic neuroticism. The FFNI was missing in four participants of Sample 2. The BPNI was missing in one participant of Sample 1 and two participants of Sample 2. Depression was assessed by the DASS-21 depression subscale in Sample 1 [44] and the Hamilton Rating Scale for Depression (HRSD) in Sample 2 [45]. Trait dominance was assessed in Sample 2 only by the IPIP-DS (International Personality Item Pool–Dominance Subscale) [46]. We used this measure in an exploratory analysis investigating whether the tendency to thrive for dominance mapped on the behaviors observed with narcissism and depression. See Table B in S1 Appendix for reliability coefficients of all psychometric measures and Fig B in S1 Appendix for their correlations with task-related variables.

Procedure

Participants played the task on a laptop computer in Sample 1 and Windows tablets in Sample 2. After they had given written, informed consent to participate, a research assistant walked them through the task instructions, a practice session, and a survey of their prior video game experience, all of which were built in the task. Participants then played the rigged video game tournament for 24 trials. The test administrator stayed in the room but did not watch participants’ actions after the first two trials. After finishing the task, participants filled out the additional assessments (DASS-21, FFNI and BPNI scales for Sample 1; FFNI, BPNI and IPIP-DS for Sample 2). In Sample 2, the HRSD was administered by a clinician within a week of the task session in the form of a semi-structured interview.

Statistical analysis

We examined how (H1a) defeat and (H2a) opponents’ rank influenced rivalry and admiration-seeking throughout the task, and how (H1b, H2b) narcissism and (H1c, H2c) depression moderated these relationships.

Dependent variable and covariates

All analyses were conducted in R version 3.4. We determined our main analytic approach, dependent variables, variables of interest and covariates at the beginning of data analysis and did not modify them during the subsequent phases of model selection. Point stealing and rank buying were analyzed as continuous, trial-level variables that were person-mean centered around subject means, which resulted in a normal distribution. The person mean-centered scores were then entered as dependent variables in separate linear multi-level models (function lmer, package lme4 [47]). As within-subject centering of choices yielded a variance of 0 in the subject intercept, associations between the subject’s mean and subject-level variables were not tested. Instead, we examined increases in behavior in response to task manipulations, and interactions with subject-level variables modulating these relationships. All reported models include age, sex, education (in Sample 2 only), ethnicity, household income, game experience, and depression as co-variates. Unless specified otherwise, main effects’ significance did not differ without the inclusion of these variables.

Model selection

On each step, model selection was performed using the likelihood-ratio test (function anova, package Stats [48]). To diagnose multicollinearity, variance inflation factors adjusted for degrees of freedom were computed and were <2 for all reported effects of retained models. First, the best-fitting model containing only design variables was selected in both samples. Three experimental condition effects central to our research questions were retained in all models: (H1a) to investigate the effect of defeat, trial (time on task) measured overall exposure length to social defeat whereas most recent outcome (dummy-coded as 1 for victory and 0 for defeat) measured trial-by-trial positive/negative reinforcement on competitive behavior; (H2a) the level of competitive involvement was measured as increases in behavior in response to the oppenent’s rank (an integer between 1 = worst rank and 200 = best rank). All models additionally included an indicator of performance on the snake arcade game (score on the most recent trial) and participants’ current rank. Significant predictors in Sample 1 were retained in models built for Sample 2, even when they were no longer significant in Sample 2. In models predicting rank buying, previous rank-buying choices had to be entered as a covariate, since buying extra rank improved one’s own status in the game (see Fig B in S1 Appendix for correlations). Second, we investigated the effects of narcissism (measured by the FFNI) and depression (measured by the DASS-21 depression subscale in Sample 1 and the HRSD in Sample 2) by adding these psychometric constructs separately to the retained models with design variables, and allowing interactions between them. (H1b, H1c) An interaction effect with trial or outcome would inform us about the psychometric construct’s effect on the behavioral response to defeat, whereas (H2b, H2c) an interaction with opponent’s rank would suggest an effect on the level of competitive involvement. Finally, we evaluated the retained models in a pooled analysis, in an effort to verify our results’ consistency across age groups and levels of psychopathology. Including sample as an independent variable, we ran all selected models described above in a dataset encompassing both samples. The pooled analysis kept all subject-level covariates, which necessitated approximate conversions of household income, education and depression. Household income was recoded as a ranked variable in Sample 2 after conversion of the cut-off values used in Sample 1 from CAD to USD. The DASS-21 depression subscale in Sample 1 and the HRSD in Sample 2 were converted into percentile norms using a software tool developed by Crawford and colleagues in a general population sample [49]. Since percentile norms were not directly available for the HRSD, values of the Carroll Rating Scale for Depression were used instead, which is a self-report version of the HRSD that shares the same items and scoring [50]. Education was assumed to be 13 years in Sample 1.

Sensitivity analyses

We conducted four sensitivity analyses: To verify that our findings were truly reflecting behavioral changes arising in response to the task, we assessed the proportion of long-string responders (defined here as participants who repeated the same choice for a given outcome measure throughout the entire task; Table C in S1 Appendix), compared them to the other participants on demographic and psychometric measures (Table D in S1 Appendix) and retested all main findings after excluding participants who engaged in long-string responding on both point stealing and rank buying (Table E in S1 Appendix). Given the well-established role of sex in competitive behaviors [13,51] and the predominance of female participants in both of our samples (resp. 78.6% in Sample 1 and 60.0% in Sample 2; Table A in S1 Appendix), we tested all main findings’ robustness to sex*trial, sex*outcome and sex*opponent’s rank covariates, added simultaneously to our selected models (Table F in S1 Appendix). We subsequently evaluated all main findings for moderation by sex, one interaction at a time (Table G in S1 Appendix). We tested our main findings in the pooled analysis for sample-level differences by letting sample moderate them. We investigated whether the effects found with the FFNI would generalize to the BPNI by substituting BPNI total scores to FFNI total scores in the models in question.

Exploratory analyses

We performed four additional exploratory analyses, in an effort to better situate our main findings within narcissistic dimensions and the task’s general dynamics: To investigate which narcissistic dimensions were driving the effects found with the FFNI total score, we tested them with the three FFNI factors agentic extraversion, antagonism and narcissistic neuroticism in the pooled analysis. We explored how our findings of narcissism and depression would compare to the behavioral effects of the tendency to thrive for dominance by testing interactions of trait dominance, as measured by the IPIP-DS in Sample 2, with trial, outcome and opponent’s rank (page 10 in S1 Appendix). We analyzed performance (scores on the snake arcade game) in linear mixed-effects models having subject-level intercepts as random effect (pages 11–13 in S1 Appendix). This analysis enabled us to test differences between samples (Fig F in S1 Appendix) and the effects of narcissism and depression on task engagement (Table I and Fig G in S1 Appendix). As a final step in the pooled analysis, we looked at correlations of mean point stealing and rank buying behaviors and psychometric constructs with participants’ self-reported motivations and impressions collected at the end of the task (Fig H in S1 Appendix). Our goal was to check whether the observed behaviors and their moderations by psychometric measures was consistent with how participants experienced the task.

Results

For the reader’s convenience, below, we focus on replicated findings illustrated with statistics from the pooled analysis and only describe samplewise models in the main text in the case of inconsistencies. Samplewise findings are further detailed in Figs C and D in S1 Appendix. Table 1 summarizes our main findings.
Table 1

Summary of main findings in the two samples and in the pooled analysis encompassing both.

Effects significant in the pooled analysisSample 1 (N = 70)Sample 2 (N = 85)Pooled (N = 155)
Coefficient (standard error)
(i) Reaction to defeat
Point stealing
Point stealing increases over time.133 (.026)***.115 (.023)***.127 (.017)***
Point stealing increases more over time in participants with higher levels of narcissism.027 (.022).046 (.021)*.043 (.015)**
Rank buying
Rank buying increases over time.107 (.025)***.045 (.023)*.075 (.017)***
Rank buying increases more over time in participants with higher levels of narcissism.057 (.024)*.043 (.021)*.051 (.015)***
(ii) Level of social comparisons
Point stealing
Point stealing increases against high-ranked opponents.068 (.024)**.095 (.022)***.085 (.016)***
Point stealing increases more against high-ranked opponents after having performed well on the arcade game.046 (.021)*.051 (.019)**.032 (.014)*
Point stealing does not increase against high-ranked opponents in highly depressed participants-.031 (.024)-.064 (.019)***-.057 (.014)***
Rank buying
Rank buying increases more over time against high-ranked opponents.059 (.021)**.008 (.020).030 (.014)*

Significant effects are in bold.

*, p < .05

**, p < .01

***, p < .001.

Significant effects are in bold. *, p < .05 **, p < .01 ***, p < .001.

(H1) Reaction to defeat

(H1a) We found no effect of the immediately preceding outcome. However, over the task both point stealing and rank buying increased in reaction to defeat, as evidenced by a main effect of trial (χ1 = 55.33, p < .001 for point stealing; χ1 = 20.11, p < .001 for rank buying; Fig 2).
Fig 2

Models with design variables predicting point stealing and rank buying in the two samples and the pooled analysis.

Estimates of demographic covariates present in the models are not displayed (age, sex, ethnicity, household income, education, game experience, depression); effects significant in the pooled analysis are in bold, significant coefficients within each table appear in darker gray. The significant positive effect of trial (i.e. time on task) on both point stealing and rank buying behaviors can be interpreted as a reaction to the increasing exposure to defeat (given the rigged outcomes). Opponent’s rank and player’s previous score*opponent’s rank were consistent predictors of point stealing across samples, indicating a preference for upward directed rivalry, especially after having performed well on the snake arcade game. The mean of previous rank-buying choices was included as a covariate in the model predicting rank buying since buying extra rank inflated participant’s own rank (see Methods - Statistical Analysis–Model Selection). Points and numbers indicate estimates of fixed effects; horizontal bars represent standard errors. Legend: *, p < .05; **, p < .01; ***, p < .001.

Models with design variables predicting point stealing and rank buying in the two samples and the pooled analysis.

Estimates of demographic covariates present in the models are not displayed (age, sex, ethnicity, household income, education, game experience, depression); effects significant in the pooled analysis are in bold, significant coefficients within each table appear in darker gray. The significant positive effect of trial (i.e. time on task) on both point stealing and rank buying behaviors can be interpreted as a reaction to the increasing exposure to defeat (given the rigged outcomes). Opponent’s rank and player’s previous score*opponent’s rank were consistent predictors of point stealing across samples, indicating a preference for upward directed rivalry, especially after having performed well on the snake arcade game. The mean of previous rank-buying choices was included as a covariate in the model predicting rank buying since buying extra rank inflated participant’s own rank (see Methods - Statistical Analysis–Model Selection). Points and numbers indicate estimates of fixed effects; horizontal bars represent standard errors. Legend: *, p < .05; **, p < .01; ***, p < .001. (H1b) Narcissism predicted greater increases in both point stealing and rank buying over time, as indicated by a significant narcissism*trial effect (χ1 = 7.91, p = .005 for point stealing; χ1 = 11.28, p < .001 for rank buying; Fig 3). This effect was not significant in the model predicting point stealing in Sample 1, but shared a similar pattern in all other cases (Fig C, Panel A in S1 Appendix).
Fig 3

Significant narcissism*trial interactions predicting point stealing (left) and rank buying (right) indicating that more narcissistic individuals tended to increase both behaviors in response to the cumulative experience of defeat. The above effects were robust to subject-level covariates (age, sex, education, ethnicity, household income, game experience and depression). Points are estimates from the corresponding regression model at the indicated values; vertical bars represent 95% confidence intervals. Legend: FFNI, Five-Factor Narcissism Inventory.

Significant narcissism*trial interactions predicting point stealing (left) and rank buying (right) indicating that more narcissistic individuals tended to increase both behaviors in response to the cumulative experience of defeat. The above effects were robust to subject-level covariates (age, sex, education, ethnicity, household income, game experience and depression). Points are estimates from the corresponding regression model at the indicated values; vertical bars represent 95% confidence intervals. Legend: FFNI, Five-Factor Narcissism Inventory. (H1c) Depression did not influence point stealing and rank buying over time.

(H2) Level of competitive involvement

(H2a) With respect to point stealing, our models with design variables indicated that people stole more points when pitted against high-ranked opponents (χ21 = 28.33, p < .001) and even more so when facing a high-ranked opponent after achieving a high score on the previous round (opponent’s rank*previous score: χ21 = 5.42, p = .020). Rank buying was not higher against high-ranked opponents overall, but did increase more against them over time, as evidenced by an opponent’s rank*trial interaction (χ1 = 4.22, p = .040). This effect was not significant in Sample 2. (H2b) No moderation effect was present between opponent’s rank and narcissism in the pooled analysis. Initial narcissism*opponent’s rank*trial and narcissism*opponent’s rank effects predicting rank buying were only found in Sample 1 (resp. χ1 = 4.40, p = .036 and χ1 = 4.75, p = .029; Fig D in S1 Appendix) and were therefore not retained among our main findings. (H2c) A depression*opponent’s rank interaction predicting point stealing (χ1 = 16.79, p < .001; Fig 4) evidenced a consistent loss of sensitivity to opponents’ rank among more depressed participants. After the inclusion of subject-level covariates, this effect fell short of significance when tested separately in Sample 1 (Fig C, Panel B in S1 Appendix), where depression scores were tightly distributed around the population average (Table A in S1 Appendix). In Sample 2, the effect was robust to covariates and remained present when depression was analyzed categorically (χ1 = 9.33, p = .002; Fig C, Panel C in S1 Appendix).
Fig 4

Significant depression*opponent’s rank interaction predicting point stealing.

By contrast to participants high on trait dominance, more depressed individuals failed to adjust point stealing to their opponents’ rank. Points are estimates from the corresponding regression model at the indicated values; vertical bars represent 95% confidence intervals.

Significant depression*opponent’s rank interaction predicting point stealing.

By contrast to participants high on trait dominance, more depressed individuals failed to adjust point stealing to their opponents’ rank. Points are estimates from the corresponding regression model at the indicated values; vertical bars represent 95% confidence intervals.

Sensitivity analyses

(a) The proportion of long-string responders was consistent across samples. Long-string responders on both outcome measures represented respectively 12 and 13% of participants in Sample 1 and 2 (Table C in S1 Appendix). They did not differ from other subjects, with the exception of none being African-American in Sample 2 vs. 18.7% in the rest of the sample (Table D in S1 Appendix). Excluding long-string responders from the analysis did not change any of our main findings (Table E in S1 Appendix). (b) Including sex*trial, sex*outcome and sex*opponent’s rank did not influence our main findings either in the pooled analysis, or in the individual samples, with the exception of the main effect of trial on rank buying that lost significance in Sample 2 but maintained comparable effect magnitude to the principal model (Table F in S1 Appendix). Interaction effects with sex were not significant in models predicting point stealing (Table G in S1 Appendix). With respect to rank buying, negative sex*trial and sex*trial*opponent’s rank effects emerged in the pooled analysis (resp. χ21 = 6.72, p = .010 and χ21 = 7.96, p = .0047), the former being only significant in Sample 1 (χ21 = 7.22, p = .007) and the latter in Sample 2 (χ21 = 4.71, p = .030). Sex did not moderate the effects of narcissism or depression. (c) Our main findings did not generally differ across samples in the pooled analysis, with the following exceptions: a sample*opponent’s rank interaction predicting point stealing (χ21 = 4.70, p = .030) and a sample*trial interaction predicting rank buying (χ21 = 5.10, p = .024) indicated similar effect directions in both samples, but a greater effect magnitude, respectively, in Sample 2 for opponent’s rank predicting point stealing and in Sample 1 for trial predicting rank buying. (d) Similar narcissism*trial effects were found with the BPNI as with the FFNI in the pooled analysis (χ1 = 7.65, p = .006 for point stealing; χ1 = 4.33, p = .038 for rank buying; Table 2). In the individual samples, this effect did only reach significance for point stealing in Sample 1 (χ1 = 3.97, p = .046).
Table 2

Effects of BPNI narcissism and of lower-level FFNI dimensions in the pooled analysis.

Main effects of interest for narcissism, as measured by the FFNIFFNIBPNI
Coefficient (standard error)
Reaction to defeat (narcissism*trial interaction)
Point stealing
TOTAL SCORE.043 (.015)**.043 (.016)**
Agentic extraversion.041 (.015)**-
Antagonism.024 (.015)
Narcissistic neuroticism.018 (.015)
Rank buying
TOTAL SCORE.063 (.017)***.032 (.016)*
Agentic extraversion.031 (.015)*-
Antagonism.035 (.015)*
Narcissistic neuroticism.015 (.015)

FFNI, Five-Factor Narcissism Inventory; BPNI, Brief Pathological Narcissism Inventory

*, p < .05

**, p < .01

***, p < .001.

FFNI, Five-Factor Narcissism Inventory; BPNI, Brief Pathological Narcissism Inventory *, p < .05 **, p < .01 ***, p < .001.

Exploratory analyses

(a) With respect to FFNI subscales, agentic extraversion was associated with both point stealing and rank buying (resp. χ1 = 7.28, p = .007 and χ1 = 4.28, p = .039), antagonism with rank buying (χ1 = 5.54, p = .019) and narcissistic neuroticism with none of the behaviors. (b) In Sample 2, where the IPIP-DS was administered, trait dominance behaved similarly to narcissism and opposedly to depression (Table H and Fig E in S1 Appendix): it increased point stealing and rank buying over time, as indicated by a trait dominance*trial interaction (χ1 = 7.45, p = .006 for point stealing; χ1 = 5.90, p = .015 for rank buying), and increased the tendency to engage in point stealing against high-ranked opponents, as evidenced by a positive trait dominance*opponent’s rank interaction predicting point stealing (χ1 = 10.90, p = .001). (c) Task performance, as measured by scores on the snake arcade game increased with time (χ1 = 104.95, p < .001), albeit less steeply in Sample 2 (trial*sample interaction in the pooled analysis: χ1 = 12.44, p < .001). Narcissism further accentuated performance over time (χ = 7.65, p = .006). This effect was driven by agentic extraversion (χ = 8.98, p = .003) and to a lesser extent by antagonism (χ = 4.12, p = .042). Antagonism however also predicted lower scores overall (χ21 = 4.37, p = .037). Depression predicted lower scores overall (χ1 = 4.53, p = .033), without influencing improvement over time. For further details, see pages 11–13 in S1 Appendix. (d) Correlations of mean behaviors and psychometric measures with participants’ self-reported feedback can be found in Fig H in S1 Appendix. Mean point stealing and rank buying respectively correlated at .24 and .26 with striving for status (question M5) and at .31 and .20 with striving for victory (question M8). Seeking to outperform others (question M3) and avoiding being worse than everyone else (question M4) additionally correlated with mean point stealing at respectively .25 and .17. Judging one’s own performance favorably correlated with rank buying at .20 (question A4). It also had a positive correlation with agentic extraversion at .23 and a negative one with narcissistic neuroticism at -.16. Depression negatively correlated with enjoyment of the task at -.26 (question A3) and with believed fairness of opponents at -.23 (question A2), whereas agentic extraversion positively correlated with striving for status at .27 (question M5), striving for victory at .20 (question M8), seeking to outperform others at .24 (question M3) and seeking revenge at .17 (question M6). Antagonism correlated with seeking revenge at .26 (question M6) and striving for victory at .16 (question M8).

Discussion

We used a rigged video game tournament experiment to elicit rivalry and admiration-seeking behaviors and investigate the level of social comparisons under the threat of defeat. We observed an increase of both behaviors with time on task, which was further enhanced by narcissism. In contrast, depression did not inhibit these behaviors, against our prediction. With respect to the level of competitive engagement, we observed no consistent effect of narcissism but found that upward-focused rivalry was inhibited by depression. Taken together, our findings are consistent with the maintainance of social status constituting a general human motivation [52], and further suggest that this goal is moderated by narcissism and depression on two distinct levels: while narcissism primarily increases the intensity of rivalry and admiration-seeking, depression influences rivalry’s objective, by inhibiting upward-focused ambitions. Experimentally corroborating the rivalry/admiration theory [26], more narcissistic persons were more intensely motivated to protect and promote their implicit rank in the face of social defeat (Fig 3). These behaviors scaled in similar ways with trait dominance as with narcissism (Fig E in S1 Appendix), which was consistent with overlapping dominance-driven motivations between the two constructs, as outlined in the Dominance Behavioral System [15]. Narcissism also correlated with faster improvement in performance on the snake arcade game (Fig G in S1 Appendix), corroborating the higher competitiveness and task engagement found in narcissism [53], especially on tasks where good performance provides the opportunity to self-enhance [54]. The fact that participants high in narcissism started the task with lower rates of rivalry and admiration-seeking than their less narcissistic counterparts (Fig 3) is consistent with these behaviors’ compensatory role. Individuals perceiving themselves as powerful have been found to resort to aggression primarily when feeling incompetent and threatened in their self-view [55], and since narcissism has been linked to overestimating one’s future performance [56], it is likely that more narcissistic participants only resorted to alternative pathways once their own performance appeared insufficient to achieve dominance. Consistent with Back and colleagues’ theory [26], we observed that rivalry and admiration-seeking behaviors were mostly driven by the grandiose dimensions of narcissism (the FFNI dimensions agentic extraversion, and to a lesser extent antagonism; Table 2). Whereas these behaviors also occured in more pathological forms of narcissism, as measured by the BPNI, they had no association with narcissistic neuroticism on the FFNI. In Back’s conceptualization, admiration-seeking roughly corresponds to agentic extraversion and rivalry to antagonism [25]. However, in our study, antagonism only enhanced rank buying, our behavioral measure of admiration-seeking (Table 2). Rivalry in our paradigm did not, in fact, include components of reactive anger, a core facet of FFNI antagonism [39], since point stealing occurred before playing against a given opponent. Further, based on the instructions, opponents were presented as previous participants and therefore were not handicapped by point stealing in real time. On the other hand, rank buying took place right after learning the trial’s outcome and thus likely acquired a reactive component. This is also corroborated by the increase of rank buying against high-ranked opponents over time (Table 1). It nevertheless remains unclear whether a similar pattern would occur with self-reported rivalry, since FFNI antagonism and rivalry measured by the Narcissistic Admiration and Rivarly Questionnaire (NARQ) are not fully overlapping constructs [25,26]. Rivalry in our paradigm matches Back’s definition, namely a willingness to surpass and devalue others in a socially insensitive way [25], and is consistently correlated with the self-reported motivation of outperforming others (Fig H in S1 Appendix). However, revenge-orientation has a strong association with rivalry in prior research [26], and it is likely that our behavioral measure of rivalry does not capture the constructs’ more antagonistic aspects. Consistently with our second hypothesis with respect to the level of competitive involvement, rivalry was preferentially upward-focused (Fig 2). Although our paradigm did not test participants’ preferred level of social challenges, which may have reflected their implicit rank more directly [6], a strong performance on the previous trial further accentuated rivalry against high-ranked opponents, supporting an upward shift in implicit rank and an increase in assertiveness after positive prediction errors about one’s capability [3,4]. In contrast, depression inhibited upward-directed rivalry (Fig 4). This was not explained by a lack of engagement in the task, as indicated by intact performance improvement in more depressed individuals (Table I in S1 Appendix). Nor was it due to decreased competitiveness, since depression did not inhibit point stealing. Depressed individuals exhibited rivalry in a manner insensitive to others’ rank and were not selectively motivated to dominate high-status others, conversely to participants high in trait dominance, whose competitiveness primarily manifested against high-ranked opponents. This is consistent with prior research, finding depression to correlate positively with performance-avoidance goals, i.e. trying not to underperform compared to others, and negatively with performance-approach goals, i.e. aiming to outperform others [57]. Further, depressive individuals’ insecurity about their own social rank has been found to prompt competitiveness primarily out of fear of inferiority and of subsequent rejection [58], contrasting with individuals perceiving themselves as powerful, who tend to pay little attention to low-power others [59]. Thus, the observed behavioral patterns align with the social competition hypothesis of depression, stating that by down-regulating dominance motivations, depression grants survival to presumably weaker individuals in a hostile environment [30]. The strengths of our study include the nuanced and novel experimental assessment of competitive behavior dynamics and sensitivity to social hierarchy. Our findings’ consistency across two very different samples in terms of age and psychopathology and their robustness to sex differences and other demographic covariates add to their generalizability. As limitations, we note the moderate sizes of each individual sample and the absence of a trait dominance measure in Sample 1. In addition, the weaker manipulation effects in Sample 2 could be due to older adults’ lower cognitive functioning and/or relative inexperience with the video game interface. The competition was limited to the duration of the task (participants did not have access to the league table once they finished playing) and did not take place in real time (opponents were said to be past players), which may have taken away some of participants’ motivation to perform well. It is further possible that some participants did not believe in the deceptive elements incorporated in the task and therefore experienced less affective involvement in the competition. Our participants were not specifically sampled for high/pathological levels of narcissism, since most of the conceptual frameworks relevant to our paradigm have focused on normally distributed subclinical narcissistic traits [3,26,60]. Future research should nonetheless explore how our behavioral findings map on narcissism’s most pathological forms, namely narcissistic personality disorder. Finally, although the admiration and rivalry framework developed by Back and colleagues heavily informed our thinking when building our paradigm [26], the NARQ was not used in the current study. This inventory should be included in future works to calibrate our behavioral measures of rivalry and admiration to self-report items. Our approach captured behaviors that map on narcissistic and depressive semiology, such as narcissistic dominance-striving or depressive dominance-inhibition, and dissected how these tendencies are expressed in social defeat. The decisional biases highlighted by our findings are likely reflected in everyday behavior in both general and clinical populations. The fact that social defeat and status can be successfully manipulated experimentally trial-by-trial in real time opens the way for the study of their physiological and neural correlates, going beyond the classic bargaining games predominantly employed to date.

All supplemental figures and tables.

(PDF) Click here for additional data file. 5 Oct 2020 PONE-D-20-25628 Status, rivalry and admiration-seeking in narcissism and depression: a behavioral study PLOS ONE Dear Dr. Dombrovski, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Both reviewers were positive on the manuscript each providing enumerating lists of changes that I will not belabor here. I would, for instance, like to see more streamlining/efficiency as noted by Reviewer 2; I prefer less philosopshizing and more science in research along with not trying to oversell/step the data. Conservative approaches to conclusions and analyses are preferable given the state of modern social psychology. Please submit your revised manuscript by Nov 19 2020 11:59PM. 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The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: I Don't Know Reviewer #2: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: This is Nick Holtzman at Georgia Southern University. I sign all my reviews. I learned a lot from this paper, and it is clear that the authors are dedicated scholars with technical skills. I do have some critiques, concerns, questions, and edits; I hope these comments prove useful and constructive. The comments are roughly in descending order of importance, and I provide a general recommendation at the end. 1. The main concern is about pre-registration. Although the sensitivity analyses and the replication across samples appears convincing of the general pattern, it is conceivable that the pattern could have been teased out through taking the garden of forking paths (as Andrew Gelman calls it). Because pre-registration is no longer possible for this study, it seems that the only way to convince readers that the garden of forking paths was not traveled is to explicitly state which analyses were conducted. If the authors only conducted the present set of analyses, then please indicate that. If other analyses were conducted but were not presented, then please indicate which ones were conducted. Because this paper was not pre-registered—and especially given the small sample sizes—it is necessary to allay any concerns about p-hacking. This is further complicated by the large number of covariates in the model (see lines 223-224). It’s not that covariates are a problem by themselves; it’s that the possibility of p-hacking and alternative covariates is especially problematic in small samples. 2. One oddity in the results is that, in the undergraduate sample, the association between depression and narcissism was positive. This usually doesn’t happen in younger samples (e.g., see the fascinating SPPS paper by Patrick Hill and Brent Roberts). I attribute this to statistical error, but it may have constrained the ability to tease out fully clear differential results for narcissism and depression. (You can imagine an extreme case where narcissism and depression are correlated .80, and thus it would be nearly impossible to get differential results for the two constructs). 3. From a measurement standpoint, I was confused about the chosen measures and why Admiration and Rivalry weren’t assessed directly. I bet that if Mitja Back read this, he would say the same thing. Maybe one of the measures the authors did use could be converted to admiration and rivalry—I’m not sure. This would clearly require a lot of additional analyses, but it would make the line of reasoning straightforward. 4. The phrase “implicit rank” carries a measurement connotation of the implicit association test, which has seen better days. Is this necessarily implicit? If the idea is about self-perceived rank, then that phrase could be used instead. 5. Please unpack the terse verbiage in H2a and H2b; two things would help me understand this more readily: first, eliminating the dashes between words like upward-focused (which needs to be explained), and second, providing an example to make it more concrete. 6. In the participants section, use “included” instead of “was composed of”, the latter of which involves passive voice. 7. On line 136-137, specify what type of payment. There is an imaginary currency and a real currency at play, so please be more specific in this sentence. 8. Line 151: Spelling error on difficulty. 9. I was confused about rankings, specifically in line 162. Usually, being #1 is best, but here, being #200 is best, right? Also the wording is confusing to me, because “highest” implies best or most superior, but usually that is a word that belongs to the first-ranked individual. One way to simplify this and retain the numbers used in analytics, would simply be to say “best” and “worst”. 10. Please cite the authors of the statistics packages in R (e.g., on line 228). 11. I am not sure what line 240-241 means where the authors write that “significant predictors … were maintained … even when non-significant.” Please clarify. 12. The phrase “stereotypical response rates” is new to me. Is this a common phrase in the literature that I’ve missed? I am accustomed to seeing a phrase like “long-string analysis” (Curran, 2016, JESP). Either an explanation of the phrase or switching the phrase would be welcomed. 13. On line 509, I’m not sure what the dash means after dominance. 14. Figure 2 must have taken a long time to create, and it looks excellent. Nice work. 15. Figures 3 & 4 could be improved slightly by making sure the bars do not overlap. There is a setting for this in R so that you can stagger and space the bars. 16. There are a couple of papers that are pertinent that could be cited to round out the literature review: a. Wallace and Baumiester had a paper on perceived opportunity for glory in narcissists. b. Fast and Chen had a paper: https://doi.org/10.1111/j.1467-9280.2009.02452.x 17. In general, I would recommend pulling Chen’s papers from the literature to see if there are any other hints that would be helpful. Her work is highly relevant here. All told, my main recommendation is for the authors to consider whether their results will hold up in the long run. This will require some reflection on the analytic path that they authors took. I think it is necessary to be explicit about whether any other analytic paths were taken, and if the number of paths is numerous, then it is probably best to hedge on the conclusiveness of this project. That being said, to the editor, I would recommend soliciting a response from the authors involving a reflection on pre-registration, an honest self-assessment of analytic paths taken, and whether the authors think this set of results will hold. Reviewer #2: Title: “Status, rivalry and admiration-seeking in narcissism and depression: A behavioral study” I was excited to review this manuscript because it concerned an extremely interesting research question. I was impressed that the authors used an interesting procedure to capture the dynamics surrounding status while engaging in a competitive video game task. I think the manuscript has the potential to make a small but interesting contribution to the literature. Below are my specific suggestions and concerns regarding the manuscript: 1. My broad reaction is that the authors may be trying to do so much with this manuscript that it may be difficult for readers to extract the most meaningful information. As a result, my advice for the authors would be for them to streamline the manuscript so that it is more focused. As it currently stands, the manuscript is a bit messy and confusing because the authors have so much happening in the manuscript that it is hard to follow. For example, the authors included analyses concerning trait dominance even though the Introduction does not really provide a strong rationale for doing so since it was focused largely on narcissism and depression. Further, the authors only collected a measure of trait dominance in Sample 2 but not Sample 1 which suggests that they did not anticipate trait dominance being a central feature of this work. The authors should either drop trait dominance from their analyses (and maybe include a footnote regarding the analyses concerning trait dominance for Sample 2) or revise the Introduction so that it gives a bit more attention to trait dominance. 2. I think the results concerning narcissism were the most interesting in the manuscript but it is hard to follow everything because there are so many different conceptualizations of narcissism included in the manuscript. My advice would be to simplify things. For the FFNI, it probably makes the most sense to focus on the three-dimensional model (i.e., extraversion, antagonism, and neuroticism). If the authors think it is important to also report the results for the total FFNI score and the grandiose and vulnerable dimensions, then it may be better to do that in a footnote. 3. It may be helpful for the authors to provide a bit more information concerning the rationale for their hypotheses. I think the authors have very interesting ideas but it may be helpful for readers if they provide a little more information to clarify their logic for some of the predictions. 4. The Results section was difficult to follow. I think the authors could make it far more readable by streamlining the number of variables they are including in their analyses so I hope they consider that approach. 5. I was a bit confused by the operationalization of “social comparison” in the manuscript. If I am understanding it correctly, the authors used increases in point-stealing and rank-buying in conjunction with the rank of the opponent to capture “social comparison.” I think the construct that is being captured by the authors is interesting but I am not quite sure that it is really social comparison. 6. The rigged video game tournament is certainly an interesting approach for capturing these sorts of dynamics. I applaud the authors for their efforts to use this sort of approach. However, I think that some of the limitations of this approach deserve a bit more attention in the Discussion. The fact that point-stealing took place before playing an opponent whereas rank-buying took place after playing an opponent is an issue. The authors acknowledge that issue briefly but I think it deserves more attention. Also, the issue that participants would never see the leader board again after their session makes it a bit odd and may be a somewhat weak situation with regard to motivating individuals to consider point-stealing or rank-buying. 7. The pattern of results for FFNI antagonism were surprising. The authors briefly address this issue in the Discussion but it may warrant a bit more attention and consideration from the authors. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 19 Nov 2020 # Editorial comments E-C1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf A: We have formatted the manuscript according to the guidelines. E-C2. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information. A: We have included the caption for our Supporting Information file (S1 Appendix) at the end of the manuscript and formatted all references to supplemental Tables/Figures according to the guidelines. # Reviewer 1 R1-C1. The main concern is about pre-registration. Although the sensitivity analyses and the replication across samples appears convincing of the general pattern, it is conceivable that the pattern could have been teased out through taking the garden of forking paths (as Andrew Gelman calls it). Because pre-registration is no longer possible for this study, it seems that the only way to convince readers that the garden of forking paths was not traveled is to explicitly state which analyses were conducted. If the authors only conducted the present set of analyses, then please indicate that. If other analyses were conducted but were not presented, then please indicate which ones were conducted. Because this paper was not preregistered—and especially given the small sample sizes—it is necessary to allay any concerns about p-hacking. This is further complicated by the large number of covariates in the model (see lines 223-224). It’s not that covariates are a problem by themselves; it’s that the possibility of p-hacking and alternative covariates is especially problematic in small samples. A: We agree that preregistration would have been desirable for this study employing a new behavioral experiment. To be fully transparent, the paradigm was developed in the context of a NIMH grant supplement (R01MH085651S1) exploring how frustrated dominance experimentally instantiated, as threat of social defeat can lead to detrimental decisions in people with specific vulnerability factors, such as narcissistic personality traits. The wider aim of the project is to investigate a potential pathway to late-life suicidal behavior in older adults. The present manuscript constitutes the first report validating the experimental paradigm, hence the inclusion of the undergraduate sample. If we understand the reviewer correctly, the concern is that the predictors and models reported here could have been cherry-picked from a larger set. From the start, the study aimed to test manipulation effects and identify effects of narcissism and depression, as an initial step towards understanding the behavioral mechanism underlying their contribution to the suicidal crisis. We have not investigated other psychological constructs besides narcissism, depression and trait dominance; we will report on behavioral correlates of late-life suicidal behavior in a second manuscript, once data collection in Pittsburgh reaches an N of 170 (twice the current N of 85), a sample size estimated sufficient to contrast suicidal and non-suicidal depressed participants. It is true that although frustrated dominance was central to our framework, we did not have a specific a priori hypothesis for trait dominance per se, and we did not assess trait dominance in the Vancouver undergraduate sample for this reason. To focus more on a priori hypotheses, we have now moved the effects of trait dominance from our main findings to the Exploratory analyses section (see also our answer to Reviewer 2’s Comment 1). With respect to the analytic strategy, our models’ structure and the covariates we used were defined from the start, based on our hypotheses. Regarding the covariates, first, we would like to emphasize that the effects of interest did not change when the covariates were omitted. Second, we used a similar set of covariates (with the exception of gaming experience, which is uniquely relevant to the current experiment) to statistically control for confounds as in our other recent papers (1-4). We hope that these references can reassure the reviewer that this is our standard way of dealing with potential confounds. Following the reviewer’s suggestion, we have added a statement in the Methods indicating that: “We determined our main analytic approach, dependent variables, variables of interest and covariates at the beginning of data analysis and did not modify them during the subsequent phases of model selection.” (lines 227-229) (1) Dombrovski, A. Y., Aslinger, E., Wright, A. G. C., & Szanto, K. (2018). Losing the battle: Perceived status loss and contemplated or attempted suicide in older adults. International Journal of Geriatric Psychiatry, 33(7), 907–914. https://doi.org/10.1002/gps.4869 (2) Kenneally, L. B., Szücs, A., Szántó, K., & Dombrovski, A. Y. (2019). Familial and social transmission of suicidal behavior in older adults. Journal of Affective Disorders, 245, 589–596. https://doi.org/10.1016/j.jad.2018.11.019 (3) Szücs, A., Szanto, K., Wright, A. G. C., & Dombrovski, A. Y. (2020). Personality of late‐ and early‐onset elderly suicide attempters. International Journal of Geriatric Psychiatry, 35(4), 384–395. https://doi.org/10.1002/gps.5254 (4) Szanto, K., Galfalvy, H., Kenneally, L., Almasi, R., & Dombrovski, A. Y. (2020). Predictors of serious suicidal behavior in late-life depression. European Neuropsychopharmacology. https://doi.org/10.1016/j.euroneuro.2020.06.005 R1-C2. One oddity in the results is that, in the undergraduate sample, the association between depression and narcissism was positive. This usually doesn’t happen in younger samples (e.g., see the fascinating SPPS paper by Patrick Hill and Brent Roberts). I attribute this to statistical error, but it may have constrained the ability to tease out fully clear differential results for narcissism and depression. (You can imagine an extreme case where narcissism and depression are correlated .80, and thus it would be nearly impossible to get differential results for the two constructs). A: Narcissism was assessed by the Five-Factor Narcissism Inventory (FFNI) in our samples, which is a measure encompassing both grandiose and vulnerable narcissistic dimensions. However, in their article entitled Narcissism, Well-Being, and Observer-Rated Personality Across the Lifespan (https://doi.org/10.1177/1948550611415867), Hill and Roberts use the 40-item version of the Narcissistic Personality Inventory (NPI), which only assesses grandiose narcissism, and even then, much of its content (e.g., Leadership) is notorious for significantly correlating with adaptive functioning. Indeed, much has been written about the challenges of using the NPI given its heterogeneous content (5). We are confident that this explains the discrepancy between their findings and ours in young adults. Grandiose narcissism in our undergraduate sample has a close to zero correlation with depression (see figure in the Response to reviewers.pdf file). (5) Ackerman, R. A., Witt, E. A., Donnellan, M. B., Trzesniewski, K. H., Robins, R. W., & Kashy, D. A. (2011). What does the narcissistic personality inventory really measure? Assessment, 18(1), 67-87. R1-C3. From a measurement standpoint, I was confused about the chosen measures and why Admiration and Rivalry weren’t assessed directly. I bet that if Mitja Back read this, he would say the same thing. Maybe one of the measures the authors did use could be converted to admiration and rivalry—I’m not sure. This would clearly require a lot of additional analyses, but it would make the line of reasoning straightforward. A: Thank you for raising this point. As mentioned in response to the previous comment, our original objective was to relate our behavioral measures to the global construct of narcissism, not specifically to its grandiose dimension. When designing our study protocol, we therefore chose two well-established measures that encompassed both narcissistic dimensions: the Five-Factor Narcissism Inventory (FFNI) and, as a sensitivity measure, the Brief Pathological Narcissistic Inventory (BPNI). However, since the behaviors we capture are most specifically formalized in Mitja Back’s Admiration and Rivalry framework, we nevertheless agree with the reviewer that it is an important direction for future research to test the task with the Narcissistic Admiration and Rivalry Questionnaire (NARQ). We know of no validated method to derive these dimensions from the FFNI or the BPNI. However, since Mitja Back conceptualizes Admiration as approximately similar to FFNI agentic extraversion and Rivalry to FFNI antagonism,6 we have extended the part of the discussion where we elaborate on our findings about these lower-level FFNI dimensions and their possible links to Rivalry and Admiration (please, see our answer to Reviewer 2’s Comment 7 and lines 492-511 in the manuscript for more detail) (6). (6) Back, M. D. (2018). The Narcissistic Admiration and Rivalry Concept. In A. D. Hermann, A. B. Brunell, & J. D. Foster (Eds.), Handbook of Trait Narcissism (pp. 57–67). Springer International Publishing. https://doi.org/10.1007/978-3-319-92171-6_6 R1-C4. The phrase “implicit rank” carries a measurement connotation of the implicit association test, which has seen better days. Is this necessarily implicit? If the idea is about self-perceived rank, then that phrase could be used instead. A: Thank you for bringing up this important point, which helped us realize that our definition of implicit rank needed clarification. In the present case, “implicit” refers to the fact that the rank is inferred from behavior and is not measured directly. “Self-perceived rank” would suggest that participants are conscious about the rank they signal through their actions, which we cannot know for certain. Thus, we opted to keep the term “implicit rank” but added a more precise definition at its first two occurrences, respectively at lines 40-41: “Our implicit rank, i.e. the rank manifested through our behavior, …” and at lines 88-90: “implicit rank (participants’ hierarchical status inferred from their behavioral choices)…” R1-C5. Please unpack the terse verbiage in H2a and H2b; two things would help me understand this more readily: first, eliminating the dashes between words like upward-focused (which needs to be explained), and second, providing an example to make it more concrete. A: Thank you for this suggestion. We have added more thorough explanations to hypotheses H2a and H2b and used a more illustrative language. Per Reviewer 2’s suggestions, we have also added theoretical justifications to our hypotheses and changed the term “level of social comparisons” to “level of competitive involvement,” which describes the measurement underlying these hypotheses more accurately (see our response to Reviewer 2’s Comments 3 and 4 for more detail). Hypotheses H2a and H2b have been clarified as follows: “We hypothesized that (H2a) high-ranked opponents would elicit more rivalry and admiration-seeking than low-ranked opponents, given that high-ranked opponents will be perceived as similar or superior to oneself and thus more threatening [6]. Additionally, (H2b) this effect would be further enhanced by narcissism, which is known to shift implicit rank upward [16], and (H2c) mitigated by depression, which tends to lower implicit rank [34].” (lines 97-102). R1-C6. In the participants section, use “included” instead of “was composed of”, the latter of which involves passive voice. A: Thank you for pointing this out. We have changed both occurrences of “was composed of” to “included” (lines 108 and 110). R1-C7. On line 136-137, specify what type of payment. There is an imaginary currency and a real currency at play, so please be more specific in this sentence. A: We have specified the type of payment: “… participants […] were instructed that their real money payment would be calculated based on the amount of virtual money saved on each trial …” (line 150). R1-C8. Line 151: Spelling error on difficulty. A: We have corrected the spelling error (line 165). R1-C9. I was confused about rankings, specifically in line 162. Usually, being #1 is best, but here, being #200 is best, right? Also the wording is confusing to me, because “highest” implies best or most superior, but usually that is a word that belongs to the first-ranked individual. One way to simplify this and retain the numbers used in analytics, would simply be to say “best” and “worst”. A: Thank you for this suggestion. We have corrected both occurrences of these terms (lines 176 and 253). R1-C10. Please cite the authors of the statistics packages in R (e.g., on line 228). A: All R packages are now duly cited (lines 233 and 243). R1-C11. I am not sure what line 240-241 means where the authors write that “significant predictors … were maintained … even when non-significant.” Please clarify. A: We modified the sentence as follows for clarity: “Significant predictors in Sample 1 were retained in models built for Sample 2, even when they were no longer significant in Sample 2.” (line 256). R1-C12. The phrase “stereotypical response rates” is new to me. Is this a common phrase in the literature that I’ve missed? I am accustomed to seeing a phrase like “long-string analysis” (Curran, 2016, JESP). Either an explanation of the phrase or switching the phrase would be welcomed. A: The term “stereotypical responding/responders” mostly occurs in the learning literature, and usually defines responses driven by the motor set and not by reinforcement (i.e. the adaptation to feedbacks received from the task). We agree that “long-string responding/responders” fits better here. We modified all occurrences of this term in the manuscript and appendix accordingly, and specified how we define “long-string” in this particular task: “… we assessed the proportion of long-string responders (defined here as participants who repeated the same choice for a given outcome measure throughout the entire task; Table C in S1 Appendix), ...” (lines 284-286). R1_C13. On line 509, I’m not sure what the dash means after dominance. A: The dash came with the structure of the phrase: “… self-enhancing/admiration-seeking can also be dominance-[based] not only prestige-based.” However, this sentence has been since removed in an effort to keep the discussion less philosophical and more focused on our findings (see Comment 18). R1-C14. Figure 2 must have taken a long time to create, and it looks excellent. Nice work. A: Thank you! R1-C15. Figures 3 & 4 could be improved slightly by making sure the bars do not overlap. There is a setting for this in R so that you can stagger and space the bars. A: Thank you for this thoughtful suggestion. We have edited Figures 3 and 4 accordingly. R1-C16. There are a couple of papers that are pertinent that could be cited to round out the literature review: a. Wallace and Baumiester had a paper on perceived opportunity for glory in narcissists. b. Fast and Chen had a paper: https://doi.org/10.1111/j.1467-9280.2009.02452.x A: Thank you for suggesting these references. We have included both articles in the Discussion. a. lines 467-470: “Narcissism also correlated with faster improvement in performance on the snake arcade game (Fig G in S1 Appendix), corroborating the higher competitiveness and task engagement found in narcissism [53], especially on tasks where good performance provides the opportunity to self-enhance [54].” b. lines 473-475: “Individuals perceiving themselves as powerful have been found to resort to aggression primarily when feeling incompetent and threatened in their self-view [55], ...” R1-C17. In general, I would recommend pulling Chen’s papers from the literature to see if there are any other hints that would be helpful. Her work is highly relevant here. A: Thank you for this suggestion. We have looked at Chen’s publications and found the book chapter she collaborated on (A Reciprocal Influence Model of Social Power: Emerging Principles and Lines of Inquiry) particularly relevant to our study. We now cite it in our Discussion: “Further, depressive individuals’ insecurity about their own social rank has been found to prompt competitiveness primarily out of fear of inferiority and of subsequent rejection [58], contrasting with individuals perceiving themselves as powerful, who tend to pay little attention to low-power others [59]” (lines 529-532). R1-C18. All told, my main recommendation is for the authors to consider whether their results will hold up in the long run. This will require some reflection on the analytic path that they authors took. I think it is necessary to be explicit about whether any other analytic paths were taken, and if the number of paths is numerous, then it is probably best to hedge on the conclusiveness of this project. That being said, to the editor, I would recommend soliciting a response from the authors involving a reflection on pre-registration, an honest self-assessment of analytic paths taken, and whether the authors think this set of results will hold. A: Having already addressed our research project’s conceptualization and analytical approach in our response to Reviewer 1’s Comment 1, we would like to focus here on responding to how our findings may hold in the long run. As mentioned, our experiment was designed from the start to measure behavioral reactions to social defeat that we expected to be stronger in individuals high in narcissistic traits. Thus, the fact that our task's dynamics aligned with this primary hypothesis in two very different samples seems definitely encouraging about its performance in subsequent studies. At the same time, we acknowledge that our findings' generalizability remains limited at this stage, and agree with the Editor and Reviewers about the tone of our discussion that should be more conservative and less philosophical. We have therefore removed several sections of it that may have been too far-fetched (they are marked in orange with a strikethrough in the manuscript with Track Changes). In addition, we now discuss the experiment's limitations in more detail and explain potential disparities between our behavioral measures of rivalry and admiration-seeking and Back's corresponding psychological constructs (see our answers to Reviewer 2's Comments 6 and 7 as well as lines 547-553 and lines 492-511 in the manuscript). This research article is the first to summarize the behavioral dynamics of our experimental paradigm, and we hope that the above textual changes will encourage other studies to build on our findings, using similar or related behavioral measures. To further facilitate this, we have made the task's code freely available online for other labs (https://github.com/aszucs/cobra_task_v1; mentioned at lines 123-124 in the manuscript). # Reviewer 2 R2-C1. My broad reaction is that the authors may be trying to do so much with this manuscript that it may be difficult for readers to extract the most meaningful information. As a result, my advice for the authors would be for them to streamline the manuscript so that it is more focused. As it currently stands, the manuscript is a bit messy and confusing because the authors have so much happening in the manuscript that it is hard to follow. For example, the authors included analyses concerning trait dominance even though the Introduction does not really provide a strong rationale for doing so since it was focused largely on narcissism and depression. Further, the authors only collected a measure of trait dominance in Sample 2 but not Sample 1 which suggests that they did not anticipate trait dominance being a central feature of this work. The authors should either drop trait dominance from their analyses (and maybe include a footnote regarding the analyses concerning trait dominance for Sample 2) or revise the Introduction so that it gives a bit more attention to trait dominance. A: Thank you for this thoughtful and detailed comment. As acknowledged in our response to Reviewer 1’s Comment 1, we did not have strong starting hypotheses for trait dominance, and did not add this scale to the Vancouver protocol for this reason. We have now removed the effects of trait dominance from our main findings, moving them to the Exploratory analyses section, which seems more adequate. Since PLOS One does not allow footnotes, we added the table and figure illustrating findings with trait dominance to the Appendix (S1 Appendix p. 10). We also simplified the Results’ structure in the subsection of H2 findings (lines 359-379). We hope that these changes helped to improve the Results’ overall flow and clarity. R2-C2. I think the results concerning narcissism were the most interesting in the manuscript but it is hard to follow everything because there are so many different conceptualizations of narcissism included in the manuscript. My advice would be to simplify things. For the FFNI, it probably makes the most sense to focus on the three-dimensional model (i.e., extraversion, antagonism, and neuroticism). If the authors think it is important to also report the results for the total FFNI score and the grandiose and vulnerable dimensions, then it may be better to do that in a footnote. A: Thank you for this suggestion. We simplified our findings by removing the grandiosity and vulnerability subscales and were happy to notice that it did not affect our conclusions as much as we thought it would, while definitely helping to make them more focused. R2-C3. It may be helpful for the authors to provide a bit more information concerning the rationale for their hypotheses. I think the authors have very interesting ideas but it may be helpful for readers if they provide a little more information to clarify their logic for some of the predictions. A: We have detailed the rationale behind our hypotheses, and linked them more explicitly to the concepts outlined in the Introduction: “We expected (H1a) both rivalry and admiration-seeking to increase as a reaction to the cumulative experience of defeat throughout the task; (H1b) narcissism to further enhance both behaviors, prompting a more intense reaction to defeat [26]; and (H1c) depression to dampen them, favoring submissive responses to adversity [35].” (lines 93-97). “We hypothesized that (H2a) high-ranked opponents would elicit more rivalry and admiration-seeking than low-ranked opponents, given that high-ranked opponents will be perceived as similar or superior to oneself and thus more threatening [6]. Additionally, (H2b) this effect would be further enhanced by narcissism, which is known to shift implicit rank upward [16], and (H2c) mitigated by depression, which tends to lower implicit rank [34].” (lines 97-102). R2-C4. The Results section was difficult to follow. I think the authors could make it far more readable by streamlining the number of variables they are including in their analyses so I hope they consider that approach. A: We reduced the number of variables in our main findings by removing trait dominance and simplified the Results’ structure in the subsection reporting findings related to H2 (lines 359-379). For further details, please see our response to Comment 1. R2-C5. I was a bit confused by the operationalization of “social comparison” in the manuscript. If I am understanding it correctly, the authors used increases in point-stealing and rank-buying in conjunction with the rank of the opponent to capture “social comparison.” I think the construct that is being captured by the authors is interesting but I am not quite sure that it is really social comparison. A: We agree with the reviewer and have changed the term “level of social comparisons” to the “level of competitive involvement”. We think that the latter is more accurate, since participants are not choosing their opponents, and the social comparisons are imposed on each trial. What depends on the participants is rather the competitive involvement these comparisons will elicit, as measured by their rivalry and admiration-seeking choices in reaction to the opponent's rank. R2-C6. The rigged video game tournament is certainly an interesting approach for capturing these sorts of dynamics. I applaud the authors for their efforts to use this sort of approach. However, I think that some of the limitations of this approach deserve a bit more attention in the Discussion. The fact that point-stealing took place before playing an opponent whereas rank-buying took place after playing an opponent is an issue. The authors acknowledge that issue briefly but I think it deserves more attention. Also, the issue that participants would never see the leader board again after their session makes it a bit odd and may be a somewhat weak situation with regard to motivating individuals to consider point-stealing or rank-buying. A: Thank you for this suggestion, the task’s design indeed deserved more room in the Discussion. We now discuss in more detail potential behavioral consequences of having the point stealing decision take place before playing the opponent, and link it more clearly to the lack of association of point stealing with antagonism (please, see our answer to Comment 7 below for more detail). We have added other potential weak points of our task’s design to the limitations: “The competition was limited to the duration of the task (participants did not have access to the league table once they finished playing) and the competition did not take place in real time (opponents were said to be past players), which may have taken away some of participants’ motivation to perform well. It is further possible that some participants did not believe in the deceptive elements incorporated in the task and therefore experienced less affective involvement in the competition.” (lines 547-553). R2-C7. The pattern of results for FFNI antagonism were surprising. The authors briefly address this issue in the Discussion but it may warrant a bit more attention and consideration from the authors. A: We now discuss this pattern in more detail and have put it in perspective with the self-reported construct of Rivalry: “In Back’s conceptualization, admiration-seeking roughly corresponds to agentic extraversion and rivalry to antagonism [25]. However, in our study, antagonism only enhanced rank buying, our behavioral measure of admiration-seeking (Table 2). Rivalry in our paradigm did not, in fact, include components of reactive anger, a core facet of FFNI antagonism [39], since point stealing occurred before playing against a given opponent. Further, based on the instructions, opponents were presented as previous participants and therefore were not handicapped by point stealing in real time. On the other hand, rank buying took place right after learning the trial’s outcome and thus likely acquired a reactive component. This is also corroborated by the increase of rank buying against high-ranked opponents over time (Table 1). It nevertheless remains unclear whether a similar pattern would occur with self-reported rivalry, since FFNI antagonism and rivalry measured by the Narcissistic Admiration and Rivarly Questionnaire (NARQ) are not fully overlapping constructs [25,26]. Rivalry in our paradigm matches Back’s definition, namely a willingness to surpass and devalue others in a socially insensitive way [25], and is consistently correlated with the self-reported motivation of outperforming others (Fig H in S1 Appendix). However, revenge-orientation has a strong association with rivalry in prior research [26], and it is likely that our behavioral measure of rivalry does not capture the constructs’ more antagonistic aspects.” (lines 492-509). Submitted filename: Response to reviewers.pdf Click here for additional data file. 24 Nov 2020 Status, rivalry and admiration-seeking in narcissism and depression: a behavioral study PONE-D-20-25628R1 Dear Dr. Dombrovski, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Peter Karl Jonason Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: 26 Nov 2020 PONE-D-20-25628R1 Status, rivalry and admiration-seeking in narcissism and depression: a behavioral study Dear Dr. Dombrovski: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Peter Karl Jonason Academic Editor PLOS ONE
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