Introduction

Being authentic or “true” to oneself is often touted as central to a good, fulfilling life (e.g., Kierkegaard, 1843/1954; Waterman 1990). Empirical research has examined authenticity both as a psychological trait (i.e., the subjective judgment that one is authentic most of the time, e.g., Kernis & Goldman 2006; Wood et al., 2008) and a psychological state (i.e., the subjective judgment that one is being authentic right now, e.g., Sedikides et al., 2019). Trait and state authenticity can be differentiated in that the former is relatively stable, whereas the latter is highly variable and context-dependent. At least one study found that about 2/3 of the total variability in authenticity occurs within subjects (Lenton et al., 2016), suggesting much of the “action” in authenticity is at the state level.

The current research examines state authenticity and its antecedents. It is important to understand what promotes authenticity, as authenticity is a well-documented contributor of well-being (Rivera et al., 2019; Sedikides et al., 2019). Meanwhile, there is controversy over how judgments of authenticity are made. Whereas authenticity is typically equated with behaving in ways that are consistent with one’s traits or other self-aspects, more recent research suggest that people may use a set of heuristics or cues to inform their judgments of authenticity, which are not necessarily related to self-consistency, for example, social desirability and promotion focus (e.g., Fleeson & Wilt 2010; Jongman-Sereno & Leary, 2016; Kim et al., 2019). This is sometimes referred to as the “state content significance” hypothesis (Fleeson & Wilt, 2010). It suggests that some ways of acting feel more authentic to everyone, regardless of their self-concepts.

Adjoining prior work on “state content significance” hypothesis, this research focuses specifically on how various affective states can be used as cues to inform judgments of authenticity. Past research suggests that positive affective states promote state authenticity (Cooper et al., 2018; Jayawickreme et al., 2021; Lenton et al., 2013; Zhang et al., 2020). Lenton and colleagues (2013), for example, found that people experimentally induced into affectively pleasant states report feeling more authentic compared to those induced into affectively neutral or unpleasant states. However, one limitation of this work is the confounding of affective valence (pleasant vs. unpleasant) and motivational direction (approach vs. avoidance), as most positive affective states are related to approach motivation and most negative affective states are related to avoidance motivation (Elliot et al., 2013; Harmon-Jones & Harmon-Jones, 2021b). Given authenticity has also been linked to approach behaviors (Kim et al., 2019; Schmader & Sedikides, 2018), it is unclear whether the causal link between positive affective states and state authenticity as established in the past work was driven by affective valence, motivational direction, or both.

The goal of the current research is to address this limitation by studying anger. Anger represents a unique affective state in which affective valence and motivational direction diverge: It is unpleasant but high in approach motivation (Carver & Harmon-Jones, 2009; Harmon-Jones & Harmon-Jones, 2021b). Thus, anger represents a potential case for teasing motivational direction and affective valence apart.

Anger as a unique affective state

Anger is a unique affective state. Often viewed as basic and universal, anger is associated with a distinct set of physiological, cognitive and behavioral correlates (Alia-Klein et al., 2020; Ekman & Cordaro, 2011; Izard, 2009). Of relevance to the current work, research suggests anger has a unique experiential profile. Affective states can be characterized based on their standing on broader underlying dimensions, among which are valence (pleasantness vs. unpleasantness, e.g., Russell & Carroll, 1999; Yik et al., 2023) and motivational direction or action tendency (approach vs. avoidance, e.g., Harmon-Jones & Harmon-Jones, 2021a; Harmon-Jones et al., 2013). Positive affective states are, by nature, related to approach motivation. As one example, Shiota and colleagues (2017), proposed that one core feature shared among positive affective states is their relationship with the dopaminergic reward system (i.e., a neural system for the acquisition of resources). Meanwhile, negative affective states are often posited as related to the avoidance motivation (e.g., Hutcherson & Gross, 2011; McNaughton & Corr, 2004; Oaten et al., 2009; Shook et al., 2019). For example, disgust has been theorized as related to disease avoidance (Oaten et al., 2009). Still, accumulating research suggests that not all negative affective states are avoidance related. Anger, as one example, is a notable exception as it is an unpleasant state primarily related to approach motivation (Carver & Harmon-Jones, 2009; Harmon-Jones & Harmon-Jones, 2021b). Most people find anger unpleasant as it is evoked by events or stimuli that are themselves unpleasant, such as goal frustration and perceived injustice (Berkowitz & Harmon-Jones 2004; Gibson & Callister, 2010). At the same time, it has long been acknowledged that anger is tied to approach behaviors, such as aggression (e.g., Blanchard & Blanchard, 1984; Darwin, 1872/1965) or more generally actions against the frustration of goals or intentional harm (Alia-Klein et al., 2020; Carver & Harmon-Jones, 2009; Fischer & Roseman, 2007; Hutcherson & Gross, 2011; Lench, Bench, et al., 2015; Lench, Tibbett, & Bench, 2016). That is, anger initiates approach-related behavioral tendencies so that people can “re-approach” and restore their pre-existing pursuit of positive ends.

Empirical support for anger as being both unpleasant and approach-related comes from a variety of research areas, such as neuropsychology and animal behavioral studies (e.g., Angus et al., 2015; Harmon-Jones et al., 2009; Harmon-Jones & Sigelman, 2001; see also Harmon-Jones & Harmon-Jones, 2021b). In one study, Hamon-Jones and colleagues (2009) found that when people were put into anger-evoking situations, self-reported anger was positively related to positive affective states as measured by the Positive and Negative Affect Schedule (PANAS, Watson et al., 1988), reflecting the similarity between anger and positive affective states in motivational direction (approach). In the meantime, self-reported anger was negatively correlated with self-reported happiness, suggesting anger was nevertheless perceived as unpleasant. In another study, Harmon-Jones and Sigelman (2001) randomly assigned participants into either an anger-evoking condition or a control condition and found participants in the anger-evoking condition displayed more pronounced relative left frontal activity, the brain activity typically associated with approach motivation (e.g., Harmon-Jones & Allen, 1997, 1998). Moreover, the elevated relative left frontal activity was positively correlated with self-reported anger and a behavioral measure of aggression among participants in the anger-evoking condition (no correlation was found in the control condition; see Angus et al., 2015 for similar findings). These findings are in line with the view that anger activates the brain region responsible for approach motivation and initiates subsequent approach-focused behaviors.

Anger as a causal antecedent of State authenticity

Given that anger is unique in being both negative in valence and approach-focused in motivational direction, how would anger influence state authenticity? One possibility is that anger may lead to less state authenticity, particularly when compared to positive affective states (e.g., amusement). If it is affective valence that is ultimately driving differences in state authenticity, then anger should make people feel less authentic than positive affective states.

Nevertheless, we speculate that anger should make people feel more authentic compared to negative affective states related to avoidance motivation, because anger and state authenticity are similar (or congruent) in motivational direction. To elaborate, just as anger, state authenticity is posited to be related to approach motivation (Schmader & Sedikides, 2018). Though somewhat scant, empirical work seems to support the link: Kim and colleagues (2019), for instance, found a positive correlation between perceived authenticity during a social interaction and the fun-seeking and reward responsiveness dimensions of trait behavioral activation system (BAS; Carver & White 1994). Within romantic relationships, Impett and colleagues (2013) found when people chose to make sacrifice for their partner out of approach goals (e.g., to make their partner happy), they tended to feel more authentic with their decisions. In contrast, when people chose to sacrifice out of avoidant goals (e.g., to avoid conflicts), they tended to feel less authentic (see Neff & Harter 2002 for a similar pattern). It is worth noting that in most, if not all, of these works, approach motivation could be confounded with affective valence, once again highlighting the need for research to disentangle the contribution of affective valence from that of approach motivation. We reason that to the extent there is indeed a link between approach motivation and state authenticity, anger should be more congruent with authenticity than negative affective states relate to avoidance. It should therefore be easier for people to experience authenticity under anger than under other negative affective states.

The current research

In sum, we reason that anger should make people feel less authentic compared to positive affective states, but more authentic compared to negative affective states that predominantly motivate avoidance. To test these ideas, we conducted two experiments where we induced affective states using different paradigms (movie clips, autobiographical recall) and had people report their state authenticity immediately after the induction.

In Study 1, we compared anger with both amusement and fear. Amusement is a positive affective state (e.g., Sauter 2010; Shiota et al., 2017). As the amusement condition corresponded directly to Lenton and colleagues’ positive affective state condition (2013, Experiment 1), including this condition also allowed us to replicate prior work. Fear, on the other hand, is a negative affective state commonly associated with avoidance motivation (e.g., McNaughton & Corr 2004). Comparing anger with fear allowed us to address whether motivational direction matters when affective states have similar valence. Given the proposed roles of affective valence and approach states in state authenticity, we expected that people induced into amusement should feel more authentic than those induced into anger or fear. However, those induced into anger should feel more authentic than those induced into fear. Phrased differently, we expected those induced in amusement should report the highest level of state authenticity, with anger the second and fear the least.

In Study 2, we compared anger with fear and an additional negative affective state commonly considered high in avoidance: disgust (e.g., Hutcherson & Gross 2011; Oaten et al., 2009; Shook et al., 2019). We expected people in the anger condition to report feeling more authentic than those in the fear or disgust condition. In addition, we also measured affective valence and approach motivation, so that we could examine whether these variables mediated any of the observed effects. Although our design was not sufficient in establishing causality (Maxwell & Cole, 2007; Maxwell et al., 2011), we aimed to decouple the relative contributions of approach states and affective valence in any of the observed differences in state authenticity.

Throughout the studies, we adopted a broad approach to operationalize state authenticity and employed two most used measures: first, we used the single-item real-self overlap scale (RSOS, Aron et al., 1992), a pictorial measure to assess rapid, global “feelings” or intuitions of state authenticity. Second, we derived and adapted components of Wood et al.’s (2008) model of trait authenticity: authentic living (i.e., perceptions of acting in line with one’s beliefs about one’s true self) and self-alienation (i.e., perceived disconnection from one’s true self). Previous research suggests authentic living and self-alienation fluctuate meaningfully on a state level as well as on a trait level (Lutz et al., 2022). By operationalizing state authenticity as both intuitive, global feelings (as in RSOS) and cognitive, domain-specific judgments (as reflected in authentic living and self-alienation), we sought to examine if any of our findings were contingent on specific measurement formats or aspects of authenticity judgments. Including both measures also allowed us draw direct comparisons between our findings and previous research where both measures were used (Lenton et al., 2013).

All materials, dataset, scripts are available at https://osf.io/m9qzr/?view_only=1d14b61adc1a4d71adc42f52dfcd42b2.

Study 1

Study 1 was a between-subject experiment where we used movie clips to elicit affective states (anger, amusement, and fear), an approach common in the field (Ferrer et al., 2015; Rottenberg et al., 2007).

Methods

Participants

Four hundred and sixty-seven undergraduate students from a large public university in the U.S. participated in the study for course credit. Six participants failed to report taking the study seriously on a modified seriousness check item (Aust et al., 2013) at the end of the survey and were removed from the analyses. This resulted in a final sample of N = 461 (300 female, 152 male, 1 female-to-male transgender, 8 missing; Mage = 19.21 years, SD = 2.96; 62% White or European American, see Table 1 for a more detailed breakdown).

Table 1 Racial Demographics of Participants
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The sample size was not determined a priori. Rather, we tried to recruit as many participants as possible over three semesters to obtain adequate power for the study. A sensitivity test via the software G*Power 3.1 (Faul et al., 2009) revealed that the final sample size would be adequately powered (at p = .05, assuming power of 0.80) to detect a minimum effect size of f2(V) = 0.01 (equivalent to partial η2 = 0.01) or similar.

Procedure and materials

The whole procedure was delivered via Qualtrics software. Upon arrival to the lab, participants were escorted to individual cubicles, each with a computer and a set of headphones. Participants were first given an information sheet in which they were informed that they were going to “watch some video clips and be asked to complete a number of questionnaires related to your personality, beliefs, and attitudes” and that some video clips might be “emotionally disturbing”. Participants then completed a battery of ostensibly unrelated questionnaires, including the Subjective Happiness Scale (Lyubomirsky & Lepper, 1999) that measures dispositional happiness and survey items from the International Personality Item Pool Representation of the NEO PI-R™ (Goldberg et al., 2006) that measures dispositional anger. As in prior research (Lenton et al., 2013), we were interested in whether individual differences in managing happiness/anger moderated the effect of affective states on state authenticity. We found very little evidence of a moderation (see supplemental materials).

After completing the questionnaires, participants were randomly assigned to receive one of the three affective state manipulations (anger, fear, and amusement). Immediately following the manipulation, participants completed manipulation checks and state authenticity measures. They were subsequently debriefed, thanked, and allowed to leave the lab.

Manipulation of Affective States

We manipulated affective states by having participants watch one of the three sets of movie clips that induces anger (vs. fear vs. amusement). Each set was composed of two movie clips that had been validated by previous research (Rottenberg et al., 2007). In total, each set lasted about 7 min. The anger set was composed of a clip from the film “My Bodyguard” and another clip from the film “Cry Freedom”. The fear set was composed of a clip from the film “The Shining” and another clip from the film “The Silence of the Lambs”. The amusement set included a clip from the film “When Harry Met Sally” and another clip from the film “Robin Williams Live”.

As a manipulation check, participants completed the same self-report emotion questionnaire used by Rottenberg and colleagues. The scale presented the participants with 18 affective states (see Rottenberg et al., 2007 for the full list). Participants rated themselves on a scale of 1 to 7 (1 = “Not at all/none”, 4 = “Somewhat/some”, 7 = “Extremely/a great deal”) the extent to which they experienced each affective state at the moment. Anger, fear and amusement each was measured with one single-item.

State Authenticity

State authenticity was measured via two measures presented in randomized order. One measure was RSOS: Participants were presented with 8 pairs of circles (the one on the left representing the “current self” and the one on the right representing the “true self”); each of these pairs differed in how the two circles overlapped with each other. Participants were asked to choose the pair that best represented how close they felt with their true selves. In addition to RSOS, we also adapted Wood and colleagues’ (2008) measure of trait authenticity. This 8-item measure is composed of two subscales (each with four items)Footnote 1: self-alienation (αs > 0.79 for all three conditions) and authentic living (αs > 0.70 all three conditions). The items were reworded to assess psychological state (e.g., “Right now, I don’t know how I really feel inside” for self-alienation, and “Right now, I feel like standing by what I believe in” for authentic living). Participants indicated to what extent they agree with the items on a scale of 1 to 7 (1 = “Strongly disagree”, 7 = “Strongly agree”). RSOS and the adapted authenticity subscales were correlated yet not redundant (|rs| < 0.49 in Study 1; |rs| < 0.47 in Study 2).

Results

Manipulation check

We conducted a one-way multivariate analysis of variance (MANOVA) to examine the effect of affective state induction on manipulation check. Overall, the effect of affective state induction was significant, F (6, 914) = 151.78, p < .001; Wilk’s Λ = 1.00, partial η2 = 0.50. As presented in Table 2, the effect of our induction was significant on all manipulation check items. Pairwise comparisons with Bonferroni correction revealed significant differences in self-reported anger between the anger condition and the fear condition, mean difference (MD) = 2.89, SE = 0.16, p < .001, g = 2.05, 95% CI [2.51, 3.27], between the anger condition and the amusement condition, MD = 3.57, SE = 0.16, p < .001, g = 2.54, 95% CI [3.19, 3.96], and between fear condition and the amusement condition, MD = 0.68, SE = 0.16, p < .001, g = 0.48, 95% CI [0.30, 1.07]. The analyses also revealed significant differences in self-reported amusement between the amusement condition and the fear condition, MD = 2.12, SE = 0.18, p < .001, g = 1.35, 95% CI [1.69, 2.55], between the amusement condition and the anger condition, MD = 3.32, SE = 0.18, p < .001, g = 2.12, 95% CI [2.89, 3.75], and between the fear condition and the anger condition, MD = 1.20, SE = 0.18, p < .001, g = 0.77, 95% CI [0.77, 1.63]. Finally, for self-reported fear, the analyses revealed significant difference between the fear condition and the anger condition, MD = 0.99, SE = 0.19, p < .001, g = 0.61, 95% CI [0.54, 1.43], between the fear condition and the amusement condition, MD = 2.63, SE = 0.19, p < .001, g = 1.62, 95% CI [2.18, 3.08], and between the anger condition and the amusement condition, MD = 1.64, SE = 0.19, p < .001, g = 1.01, 95% CI [1.20, 2.09].

Table 2 Effect of Affective States in Study 1
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These findings suggested that people did report the highest amount of amusement/fear/anger in the corresponding conditions—though there were also some unintentional effects as well (e.g., relative to the amusement condition, the anger manipulation also made people experience more fear). The unintentional effects and their implications will be discussed in the discussion section.

State authenticity

We then conducted a one-way MANOVA on measures of state authenticity (RSOS, self-alienation and authentic living). The analysis revealed an overall significant effect of manipulation, F (6, 914) = 3.90, p = .001; Wilk’s Λ = 0.05, partial η2 = 0.03. As presented in Table 2, the effect of manipulation was significant on all measures of state authenticity except for authentic living. Pairwise comparisons with Bonferroni correction revealed that on the RSOS measure of state authenticity, people in the amusement condition reported feeling significantly more authentic than those in the anger condition, MD = 0.55, SE = 0.20, p = .02, g = 0.32, 95% CI [0.08, 1.03]. The fear condition did not differ from either the amusement condition, MD = -0.31, SE = 0.20, p = .36, g = 0.18, 95% CI [-0.78, 0.17], or the anger condition, MD = 0.24, SE = 0.20, p = .66, g = 0.14, 95% CI [-0.23, 0.72]. On the self-alienation measure, people in the amusement condition reported feeling significantly less self-alienated than those in either the anger condition, MD = -0.54, SE = 0.16, p = .002, g = 0.39, 95% CI [-0.92, -0.17] or the fear condition, MD = -0.57, SE = 0.16, p = .001, g = 0.42, 95% CI [-0.95, -0.20]. The anger condition did not differ from the fear condition, MD = -0.03, SE = 0.16, p > .99, g = 0.02, 95% CI [-0.40, 0.35]. Overall, differences in self-alienation and the RSOS measure of state authenticity seemed to be driven mostly by the amusement condition making people feel more authentic and less self-alienated than the anger condition.

Discussion

Findings of Study 1 varied depending on the specific measure of state authenticity. On RSOS and self-alienation, we observed that participants in the amusement condition reported more state authenticity than those in the anger condition (and those in the fear condition on self-alienation). Anger, however, did not differ from fear. On authentic living, we failed to observe significant differences. The null finding on authentic living could be because some of the survey items were not well-adapted into measuring state variables (e.g., “Right now, I feel I am true to myself in most situations.”). Besides, in prior research (Lenton et al., 2013, Experiment 1), affective state manipulation had a less reliable effect on this measure.

Still, the general pattern of results seems to point to a main effect of affective valence. Specifically, the lack of difference between the anger condition (an approach-related state) and the fear condition (an avoidance-related state) suggests that when affective states have similar valence, motivational direction may not matter. This suggestion is further backed up by the comparison between amusement and anger, as even amusement is considered relatively low in approach motivation among positive affective states (Domachowska et al., 2016; Gable & Harmon-Jones, 2008). As such, the finding that participants in the amusement (vs. anger) condition reported more state authenticity could indicate that even low approach states could feel more authentic if they are positively valenced. Together, these findings conceptually replicate previous research on the causal role of positive affective states in state authenticity (Lenton et al., 2013), but provide little support for the role of approach motivation in state authenticity.

Nevertheless, before these findings can be discussed further, it is important to address several limitations of the study. First, we compared anger with fear—which is only one out of the many negative affective states that primarily prompt avoidance motivation. Second, findings of Study 1 were similarly based on only one specific type of experimental manipulation (i.e., movie clips). It is possible that our findings may not hold in alternative, more ecologically valid settings. Third, our manipulation of anger (vs. amusement) seemed to have accidentally induced some degree of fear, whereas our manipulation of fear (vs. amusement) seemed to have induced some anger as well. It is not uncommon for movie clips to induce a blend of affective states (e.g., Lobbestael et al., 2008; Rottenberg et al., 2007). Moreover, anger and fear often arise in response to the same stimuli (e.g., a threat, Berkowitz & Harmon-Jones 2004; see also Rohr et al., 2015). In our study, the blend of fear and anger as induced by our manipulation could create ambiguity in how to interpret the findings. It is likely that when anger is induced alongside other negative affective states, its motivational direction (i.e., approach) is offset (Harmon-Jones et al., 2017). This limitation was exacerbated by the fact that we did not measure approach motivation, leaving us unable to verify whether our anger manipulation induced an approach-related state and whether that approach-related state was translated into state authenticity. To address these concerns, we designed Study 2 as a more refined test of the differences between anger and avoidance-related negative affective states.

Study 2

Study 2 was another between-subject experiment with modifications to address the limitations of Study 1. First, since our focus was on the differences between negative affective states related to approach and avoidance motivation, we no longer included the amusement condition. Instead, we contrasted anger against fear and another negative affective state that is commonly linked to avoidance motivation—disgust (e.g., Hutcherson & Gross 2011; Oaten et al., 2009; Shook et al., 2019). Second, we induced affective states via autobiographical recall (Dunn & Schweitzer, 2005; Göritz & Moser, 2006; Mills & D’Mello, 2014; Strack et al., 1985) Autobiographical recall has been considered as the strongest method to induce anger (Siedlecka & Denson, 2019). Inducing affective states with a different paradigm should also bolster the ecological validity of our work. Finally, we measured approach states along with affective valence right after the affective state induction. This allowed us to examine the potential indirect effects from the manipulations to state authenticity through either affective valence, motivational direction, or both.

Methods

Participants

Four hundred and eighty-three participants were recruited from Mturk in exchange for $1. Fourteen participants reported not taking the study seriously and were removed from subsequent analyses. We removed another 106 participants from the study—38 in the fear condition, 35 in the disgust condition; 33 in the anger conditionFootnote 2—because they failed to follow our instructions (see discussed below). This resulted in a final sample of N = 363 (179 female, 179 male, 1 male-to-female transgender, 2 gender nonconforming, 2 prefer not to say; Mage = 35.76 years, SD = 11.49; 66.1% White or European American, see Table 1).

The sample size of Study 2 was determined a priori. Given the lack of relevant research on differences in state authenticity between negative affective states, we derived expected effect size from the rules of thumb (Cohen, 1988) and expected a small effect of f2 = 0.02. A power analysis via G*power (MANOVA: global effects) revealed that for our study design (3 groups, 5 response variables) to detect such an effect at p = .05 with power of 0.80, we need to recruit a minimum of 411 participants. To account for potential dropouts, we had planned to recruit around 480 participants. We ended up with a smaller sample. A sensitivity test via G*Power revealed that this sample would have enough power (at p = .05, assuming power of 0.80) to detect a minimum effect size of f2(V) = 0.02 (equivalent to partial η2 = 0.02) or similar.

Procedure and materials

The whole procedure was delivered online via Qualtrics software. Participants were first randomly assigned into one of the three affective state manipulations (disgust, fear, anger). The technique was based on autobiographical recall (Dunn & Schweitzer, 2005; Göritz & Moser, 2006; Mills & D’Mello, 2014; Strack et al., 1985). For each condition, participants were shown an emoji of the correspondent affective state and were instructed to “describe in detail the one situation that has made you feel the most disgusted (vs. fearful vs. angry) you have been in your life and describe it such that a person reading the description would feel disgusted (vs. afraid vs. angry) just from hearing about the situation”. They were then given 4 min to type down what they recalled. The first author inspected participants’ responses after data collection was complete and removed those who failed to follow the instructions (e.g., type down “none” or pleasant experiences ostensibly unrelated to the affective states instructed) or were not taking the instructions seriously (e.g., type down “that is great and best”, see OSF for more details).

After the recall task, participants completed the same manipulation check items and state authenticity measures (RSOS, self-alienation, authentic living) as in Study 1. Responses on the self-alienation subscale and authentic living subscale were again collapsed into corresponding composites (αs > 0.92 for all three conditions on self-alienation; αs > 0.78 for all three conditions on authentic living).

We then computed an index of affective valence based on the same self-report emotion scale we used to embed manipulation check.Footnote 3 We subtracted participants’ mean scores on the eleven negative affective states (αs > 0.92 for all three conditions) from their mean scores on seven positive affective states (αs > 0.92 for all three conditions). Higher scores indicated people experiencing more positive (over negative) affective states.

Finally, participants completed a measure of approach states (Greenaway et al., 2015). They rated to what extent they felt four states (energized, powerful, capable, and competitive) that are theoretically high in approach motivationFootnote 4 on a scale of 1 to 7 (1 = “Not at all/none”, 4 = “Somewhat/some”, 7 = “Extremely/a great deal”). Participants’ responses were internally consistent (αs > 0.87 for all three conditions) and were collapsed into composites.

Results

Manipulation checks

We repeated the analytic procedure in Study 1 for manipulation check. The overall effect of affective state induction was significant, F (6, 718) = 26.42, p < .001; Wilk’s Λ = 0.36, partial η2 = 0.18. As presented in Table 3, the effect of our manipulation was once again significant on all manipulation check items. Pairwise comparisons revealed significant differences in self-reported disgust between the fear condition and the disgust condition, MD = -1.86, SE = 0.26, p < .001, g = 0.93, 95% CI [-2.48. -1.24], between the fear condition and the anger condition, MD = -1.26, SE = 0.26, p < .001, g = 0.63, 95% CI [-1.88, -0.64], but not between the anger condition and the disgust condition—though the difference is trending towards conventional level of significance, MD = -0.60, SE = 0.26, p = .057, g = 0.30, 95% CI [-1.22, 0.01]. The analyses also revealed significant differences in self-reported anger between the anger condition and the disgust condition, MD = 1.11, SE = 0.26, p < .001, g = 0.54, 95% CI [0.49, 1.74], between the anger condition and the fear condition, MD = 1.32, SE = 0.26, p < .001, g = 0.65, 95% CI [0.68, 1.95], but not between the fear condition and the disgust condition, MD = -0.20, SE = 0.26, p > .99, g = 0.10, 95% CI [-0.84, 0.43]. Finally, the analyses revealed significant differences in self-reported fear between the fear condition and the anger condition, MD = 0.77, SE = 0.26, p = .009, g = 0.38, 95% CI [0.15, 1.40], between the fear condition and the disgust condition, MD = 0.99, SE = 0.26, p = .001, g = 0.49, 95% CI [0.36, 1.61], but not between the anger condition and the disgust condition, MD = 0.21, SE = 0.26, p > .99, g = 0.10, 95% CI [-0.41, 0.83].

Table 3 Effect of Affective States in Study 2
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These findings indicated that people did report more disgust/anger/fear in the corresponding conditions, except that the difference in self-reported disgust did not reach conventional level of significance between the anger condition and the disgust condition. Besides, participants in the anger condition and in the disgust condition had rather similar ratings on self-reported fear, suggesting that the effects of anger and disgust manipulations were quite similar, or that experiences leading to anger and disgust may have similar affective profiles. Exploratory analyses revealed that this similarity in affective profiles might have at least been partially driven by some participants in the disgust condition recalling moral (vs. physical) events (see supplemental materials).Footnote 5

State authenticity

Turning to measures of state authenticity, we once again conducted a one-way MANOVA. Multivariate analysis revealed that affective state manipulation did not have a significant overall effect, F (6, 718) = 1.15, p = .33, Wilk’s Λ = 0.02, partial η2 = 0.01. As presented in Table 3, significant differences between conditions only emerged predicting the RSOS measure of state authenticity. Simple effect analyses revealed that people in the anger condition reported experiencing less authenticity than those in the disgust condition, though this difference did not reach conventional level of significance, MD = -0.52, SE = 0.22, p = .06, g = 0.30, 95% CI [-1.06, 0.02]. The fear condition did not differ from either the disgust condition, MD = -0.08, SE = 0.23, p > .99, g = 0.05, 95% CI [-0.63, 0.46], or the anger condition, MD = 0.44, SE = 0.23, p = .16, g = 0.25, 95% CI [-0.11, 0.98]. Overall, the observed effect on the RSOS measure of state authenticity seemed to be driven mostly by people in the anger condition reporting slightly less state authenticity than those in the disgust condition. The pattern was against our prediction.

Affective valence and approach states as mediators

We proceeded by examining affective valence and approach states as potential mediators of observed differences. Table 4 presented simple correlations among affective valence, approach states and state authenticity measures. Affective valence was negatively correlated with self-alienation and positively correlated with authentic living and the RSOS measure of state authenticity. Approach states, on the other hand, were positively correlated with all authenticity measure (including self-alienation). And more importantly, it was correlated with affective valence, r = .51, p < .001. This could suggest the two variables were mutually confounded. Therefore, when analyzing one of these variables, we controlled for the other.

Table 4 Simple Correlations Among Measured Variables in Study 2
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We then conducted a one-way analysis of covariance (ANCOVA) to examine the effect of affect states induction on affective valence, controlling for approach states. As presented in Table 3, the analysis revealed a significant effect of affective state induction: participants in the anger condition reported feeling significantly less pleasant (vs. unpleasant) than those in either the fear condition, MD = -0.76, SE = 0.21, p = .001, g = 0.48, 95% CI [-1.26, -0.27] or the disgust condition, MD = -0.61, SE = 0.20, p = .009, g = 0.38, 95% CI [-1.09, -0.12]. Participants in the disgust condition did not differ from those in the fear condition, MD = -0.16, SE = 0.21, p > .99, g = 0.10, 95% CI [-0.65, 0.34].

We similarly performed a one-way ANCOVA to examine the effect of affective state induction on approach states, controlling for affective valence. Once again, the effect of affective state induction was significant (see Table 3): participants in the anger condition reported experiencing more approach states, relative to those in the fear condition, MD = 0.58, SE = 0.19, p = .007, g = 0.40, 95% CI [0.12, 1.03]. Though these participants also reported experiencing more approach states than those in the disgust condition, the difference was not significant, MD = 0.27, SE = 0.19, p = .44, g = 0.19, 95% CI [-0.18, 0.72], and neither was the difference between the disgust condition and the fear condition, MD = 0.30, SE = 0.19, p = .32, g = 0.21, 95% CI [-0.15, 0.75]. Together, these results suggest that our anger manipulation produced a rather unpleasant state that was high in approach motivation (compared to fear). These patterns are consistent with existing accounts of anger (Alia-Klein et al., 2020; Carver & Harmon-Jones, 2009; Harmon-Jones & Harmon-Jones, 2021b).

Finally, we examined whether affective valence and approach states mediated the differences between anger and other conditions on the RSOS measure of state authenticity, given this was the only outcome measure where a significant difference emerged. We used the PROCESS macro (Hayes, 2017, Model 4, with 5, 000 bootstrap samples) for SPSS to estimate the indirect effects. Two dummy codes were created, one comparing the disgust condition with the other two conditions (1 = disgust, 0 = non-disgust) and the other comparing the fear condition with the other two conditions (1 = fear, 0 = non-fear). Doing so allowed the anger condition to be used as criteria. Affective valence and approach states were simultaneously entered into the model as mediators, allowing the indirect effects to be teased apart from one another.

The results are presented in Fig. 1. The analysis revealed significant indirect effects of affective valence (b = 0.14, SE = 0.07, 95% CI [0.03, 0.29] for comparing anger with disgust; b = 0.14, SE = 0.06, 95% CI [0.03, 0.28] for comparing anger with fear). The indirect effects of approach states were not significant (b = 0.002, SE = 0.02, 95% CI [-0.04, 0.04] for comparing anger with disgust; b = -0.02, SE = 0.02, 95% CI [-0.08, 0.02] for comparing anger with fear). These patterns suggested that relative to disgust/fear, anger made participants feel less pleasant, which in turn contributed to participants’ lower state authenticity in this condition.

Fig. 1
figure 1

A Simple Mediation Analysis: Indirect Effects of Comparisons Between Anger and Disgust/Fear Conditions on the RSOS Measure of State Authenticity Through Approach States and Affective Valence

Notes. RSOS = real-self overlap scale of state authenticity. Anger was coded as 0, fear/disgust was coded as 1

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Discussion

Results of Study 2 provided no support for the hypothesis that anger makes people feel more authentic than theoretically avoidance-related affective states (fear/disgust), despite that anger seemed more approach-related (especially compared to fear). The differences in state authenticity (i.e., RSOS) seemed attributable to affective valence rather than approach states: participants induced into anger reported less positive affective states, which explained their lower state authenticity.

Notably, these findings came as a considerable amount (24.8%) of the original sample was removed during data screening. Yet, what we found (e.g., the lack of difference between anger and fear) was remarkably consistent with Study 1 where data exclusion was minor (1.3% of the original sample). Results of mediation analyses also conceptually converged with Study 1 (i.e., comparing anger with amusement) in suggesting that anger is not uniquely related to state authenticity—rather, it seems to only relate to state authenticity because it is a negative affective state. Given these consistencies, it is unlikely that results of Study 2 are a mere matter of data quality (we will discuss this issue again in the General Discussion).

General discussion

Feelings of authenticity are key determinants of well-being (Rivera et al., 2019; Sedikides et al., 2019). It is thus not surprising that researchers have strived to understand what makes people feel authentic. One line of research (Cooper et al., 2018; Jayawickreme et al., 2021; Lenton et al., 2013; Zhang et al., 2020) suggests that authentic feelings can be promoted by a common element of human lives—positive affective experiences. Yet, these efforts were compromised by the confound of affective valence with motivational direction. The goal of current research is to address this limitation by studying anger, an affective state that defies the general rule of valence-approach/avoidance correlation, being negative in valence and approach-related (Alia-Klein et al., 2020; Carver & Harmon-Jones, 2009; (Harmon-Jones & Harmon-Jones, 2021b).

Results of two experiments suggest anger does not seem to be uniquely related to authenticity beyond the relationship that would be expected based on its negative valence. Whereas anger made people feel less authentic compared to amusement, a positive affective state (Study 1), it mostly did not differ from negative affective states that are theoretically avoidance-related (i.e., fear in Studies 1 & 2, and disgust in Study 2). Even when significant differences did emerge, anger seemed to reduce state authenticity (vs. the disgust condition on the RSOS measure, Study 2). This is inconsistent with the view that anger should lead to more state authenticity than negative affective states high in avoidance motivation because anger and authenticity are both approach-related and therefore more congruent. Further, mediation analyses suggested that it was affective valence, not approach states, that was contributing to differences in state authenticity: participants in the anger condition reported feeling more unpleasant which in turn explained their lower state authenticity. Overall, our results merely support the view that anger should lead to less authenticity than positive affective states; there is no reason to believe that anger is any different from negative, avoidance-related affective states in influencing state authenticity.

Our work most closely replicated and built on the work of Lenton and colleagues (2013), which suggested positive affective states facilitate state authenticity. However, as the researchers experimentally manipulated affective valence by inducing people into states of happiness (as a proxy of general positive affective states) and sadness (as a proxy of general negative affective states) respectively, their findings were based on only two discrete affective states. The current study extends this work by showing that the positive affective state, amusement, leads to more state authenticity than the negative affective states of anger and (to a lesser extent) fear. The effect of affective valence on state authenticity is therefore robust across a wider array of affective states.

The contribution of our work is not limited in illustrating the robustness of previous work. We also addressed a limitation: the natural confound between affective valence and motivational direction. Many of our findings suggest that affective valence is central to state authenticity whereas motivational direction is likely not. For example, the lack of difference between anger and fear/disgustFootnote 6 suggest that approach/avoidance likely does not matter in predicting state authenticity. Findings of Study 2 are especially relevant to this suggestion, as we found evidence that the higher approach states associated with anger (vs. in particular, fear) did not translate into more state authenticity—only affective valence did. This further reinforces the idea that affective valence is potentially more important for state authenticity than motivational direction.

Our findings thus bear implication for the broader literature on authenticity. Scholars have diverged over how judgments of authenticity are made (Rivera et al., 2019). Whereas some could argue judgments of authenticity reflect judgments of whether or not one is living up the self, others suggested judgments of authenticity can be biased or informed by certain cues or heuristics (e.g., Fleeson & Wilt 2010; Jongman-Sereno & Leary, 2016; Kim et al., 2019) that is not necessarily related to self-consistency. Along with Lenton and colleagues’ (2013) work, our findings adjoined the latter perspective in suggesting that people can utilize the valence of affective states as cues to inform judgments of whether or not they are authentic. Moreover, some past work suggested an ostensible link between authenticity and approach motivation (Kim et al., 2019; Schmader & Sedikides, 2018). Based on our findings, approach motivation may only matter to the extent that it reflects or is conflated with affective valence. Still, given we are (to the best of our knowledge) the first study to disentangle the implications of affective valence and approach states (in the case of anger) on state authenticity, follow-up studies are needed on this issue.

Limitations and future directions

We would like to add a couple of caveats for future research. First, we relied exclusively on self-report measures and focused only on experiences or cognitive representations of affective states. We did not examine expression of affective states, which refers to changes in behaviors when people experience a given affective state (e.g., aggressive behaviors under anger, Gross & John 1995, 1997). Expressions of affective states are often correlated with experiences of affective state, but they are not one in the same (see Greenaway & Kalokerinos 2019; Gross et al., 2000, for examples). It will be interesting to see if expressions of anger are uniquely related to state authenticity, as people may deem their feelings inauthentic, but not their behaviors. Given behaviors are publicly observable whereas experiences are private, we speculate that the relationship between state authenticity and anger expressions should be contingent on situational factors exogenous to the experiences per se (e.g., whether the norms of the situation encourage or suppress specific behavioral expressions).

Second, though we found little evidence for a difference in state authenticity between anger and avoidance-related, negative affective states, the difference may still manifest in some circumstances (or among some people). For example, the effect of anger (vs. fear, disgust etc.) on state authenticity might be contingent on the extent to which anger is instrumental to personally important goals. People upregulate experiences of anger when such experiences suit their purposes (Tamir & Ford, 2012). To the extent people consider anger as useful or contributing to attaining personally important goals, they may want to experience more anger and feel more authentic when they are angry.

Third, although it is a strength of the current research to obtain relatively large samples (Ns > 350), both of our samples (student sample in Study 1, Mturk sample in Study 2) are convenience samples and are likely to have a predominant Western background. As already noted by many researchers (e.g., Henrich et al., 2010), findings based on predominantly Western, educated, industrialized, rich and democratic (WEIRD) samples may not generalize to alternative, non-Western groups. Additionally, because our samples came from established participant pools, it is possible that many of them had participated in many research studies before, which could bias the way they responded in the current research. Future research should seek additional sampling strategies to avoid these limitations. Relatedly, some researchers have questioned the quality of MTurk data, particularly when open-ended tasks are used (Webb & Tangney, 2022). We share similar concerns, as we had to screen out a lot of participants in our Mturk sample. While the consistency within our results (and the broader literature) lends confidence to our findings, some low-quality responses could remain in our Mturk dataset (e.g., someone might “pretend” to follow our instructions while being non-serious). To detect such cases, we (and future researchers) may need to incorporate additional quality checks. However, doing so runs the risk of unrepresentative samples (Chmielewski & Kucker, 2020)—in any case, a balance must be achieved. Alternatively, studies with open-ended tasks like autobiographical recall may better be conducted in traditional lab settings.

Finally, it is worth noting that we employed a variety of state authenticity measures, but the results were not entirely consistent. For example, in Study 1, we found significant differences in RSOS measures of authenticity and self-alienation but not in authentic living. While the inconsistency might have something to with scale wording, it might also reflect the heterogeneity inherent in state authenticity as a construct. Affective states may have distinct implications over distinct facets of state authenticity. As research is emerging on how facets of state authenticity are related (e.g., Lutz et al., 2022), we call for more theory building on the structure of state authenticity to shed light on such possibilities.

In conclusion, this research addressed one limitation of past research on the role of affective states in state authenticity: the confound of affective valence and motivational direction. We studied a unique negative affective state related to approach motivation, anger, to discern the relative contribution of affective valence and approach/avoidance motivation. Through contrasting anger against a positive affective state (amusement) and negative, avoidance-related affective states (fear, disgust), this research arrived at the conclusion that past research is correct: as a general rule, negative affective states should make people feel less authentic than positive affective states; anger, despite being unique in being related to approach motivation, is no exception.