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Running head: Ecological momentary assessment of social exclusion
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An Ecological Momentary Assessment Study to investigate individuals’ reactions to
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perceived social exclusion
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Luca Pancani,a Daniel Waldeck,b Ian Tyndall, c & Paolo Rivaa
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a Department of Psychology, University of Milano-Bicocca, IT
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b Department of Psychology, Coventry University, UK
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c Department of Psychology, University of Chichester, UK
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Ecological momentary assessment of social exclusion
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Abstract
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Most psychological research on social exclusion mainly focused on maximizing internal validity
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(e.g., controlling for confounding variables). However, maximizing external validity to produce
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generalizable knowledge about real-world experiences becomes increasingly essential. In the
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present study (N=89), we adopted an ecological momentary assessment (EMA) design to track
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exclusionary experiences and their impact on psychological distress over 15 consecutive days. We
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tested the mediating effects of positive and negative emotions on the link between daily
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exclusionary experiences and psychological distress, examining the moderating role of experiential
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avoidance (EA). Results confirmed a large effect of social exclusion on distress mediated by
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positive and negative emotions. However, EA did not moderate the exclusion-distress link but was,
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unexpectedly, found to moderate the exclusion-positive emotions relationship. Specifically, this
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relationship was stronger for low (vs. high) levels of EA, indicating that adopting EA in response to
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perceived exclusion may provide a protective function from blunted positive emotions. The present
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study suggests the usefulness of investigating the occurrence and reactions to the daily experiences
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of social exclusion, going beyond the sole reliance on experimental manipulations, especially to
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explore the role of individual differences in working towards a more integrated theoretical model of
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exclusion.
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Keywords: Social Exclusion; Ecological Momentary Assessment; Experiential Avoidance;
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Personality, Coping.
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Ecological momentary assessment of social exclusion
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Introduction
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Social exclusion has been broadly defined as the experience of being kept apart from
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others physically (e.g., social isolation) or emotionally (e.g., being ignored or told one is not
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wanted; Riva & Eck, 2016). Exposure to social exclusion experiences can occur multiple times
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throughout the day in various contexts (e.g., ignored by family members, work colleagues, or
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social media posts receive no comments or likes; Nezlek et al., 2012; Rudert et al., 2020).
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According to the Temporal Need Threat Model of Ostracism (Williams, 2009), individuals
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experience immediate psychological distress with an increase in negative emotions (and
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decrease in positive ones) and threats of satisfaction of fundamental needs (i.e., belonging,
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control, self-esteem, and meaningful existence). Since its introduction, hundreds of
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experimental studies have replicated these findings through the Cyberball paradigm (e.g.,
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Williams et al., 2000; Hartgerink et al., 2015). Following this short-term reaction, Williams
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(2009) argues that how a person copes with their ostracism depends on how they appraise the
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meaning, context, and importance of the experience (i.e., the reflective stage). Moreover, at
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this stage, individual differences are purported to influence how quickly people cope with their
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ostracism experience. Indeed, several moderators of the short-term effects of ostracism have
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been reported, including social anxiety (Zadro et al., 2006), fear of social pain (Riva et al.,
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2014), attachment style (Yaakobi & Williams, 2016), cultural values (Yaakobi, 2021), and a
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tendency to ruminate (Wesselmann et al., 2013). Although people might experience prolonged
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and repeated episodes of exclusion (entering the so-called resignation stage; Williams, 2009;
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see also Riva et al., 2017), when such experiences remain short-term, their adverse effects do
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not typically persist for long (Williams, 2009).
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Over the last 20 years, numerous experimental studies on ostracism and rejection with high
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internal validity have been conducted. However, research that points to external validity and
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Ecological momentary assessment of social exclusion
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considers the unfolding of exclusion in real life is lacking. Given that much work in the social
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exclusion literature has examined potential moderating effects of individual differences in the
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laboratory, methods are needed to allow for tests of such moderation effects that are externally valid
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and generalizable. The present study aims to address this knowledge gap using the Ecological
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Momentary Assessment (EMA) paradigm to examine real-world experiences of social exclusion
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and possible moderators of its consequences rather than artificially induced exclusionary events in
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the laboratory.
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Experiential Avoidance
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One moderator of the shorter-term effects of social exclusion that has received recent
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empirical attention is experiential avoidance (EA). EA is one of the key processes in the
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overarching construct of psychological inflexibility within the Acceptance and Commitment
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Therapy (ACT) model of behavior change (Hayes et al., 2006, 2012). EA is described as
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efforts to alter the frequency or form of unwanted thoughts, memories, and bodily sensations,
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even when it leads to a personal detriment. In the short term, avoiding the experience of
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uncomfortable and distressing private events might be adaptive. This might happen, for
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instance, when someone attempts to suppress their thoughts and feelings when ghosted, rather
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than over-reacting to such feelings (e.g., accusing the other person of ostracism, ignoring them
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in retaliation; see Pancani et al., 2021). However, the chronic use of EA when dealing with
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daily stressors (e.g., social exclusion) is purported to exacerbate psychological distress (e.g.,
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Hayes et al., 1996). Indeed, research has shown that attempts to suppress unwanted thoughts
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(i.e., one type of EA strategy) can lead to paradoxical effects whereby the frequency and
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intensity of the thought increase (e.g., Wenzlaff & Wegner, 2000). It is worth noting here that
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some ostracism researchers posit that individuals with avoidant attachment styles report less
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psychological distress following social exclusion because they employ suppression and denial
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mechanisms to protect themselves (e.g., Shaver & Mikulincer, 2013; Yaakobi, 2022; Yaakobi
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Ecological momentary assessment of social exclusion
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&Wlliams, 2016;). However, importantly, while the mechanism might appear similar on the
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surface, EA from an ACT perspective is not linked to putative attachment styles but is a
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contextual emotion regulation behavior shaped via a history of negative reinforcement.
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Some researchers have explored whether EA is a moderator of the emotional effects of
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ostracism. For instance, Waldeck et al. (2020) found that participants who were ostracized in
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Cyberball coped with their ostracism more quickly in the short term when low (vs. high) in EA.
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Furthermore, Tyndall et al. (2018) found that EA appeared to moderate the relationship between
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perceived ostracism and psychological distress in the long term. Thus, at high EA levels (i.e., more
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inflexible), there was a significant positive relationship between ostracism and distress, which was
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not significant at low levels. As such, people appeared to recover more quickly from their ostracism
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when lower in EA. Such findings are promising as reducing reliance on EA as a coping strategy is a
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key target within ACT’s model of behavior change and offers a potential route for effective
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intervention for those who suffer exclusion daily. Indeed, emerging literature suggests that even
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brief exposure to acceptance and mindfulness-based interventions can help people cope more
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readily with their ostracism experience (e.g., Hochard et al., 2021). Although the above results are
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encouraging, little is known about the role of EA in coping with episodes of exclusion in the short
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term, and research needs to examine it in a more ecological context when dealing with the
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psychological distress resulting from daily experiences of social exclusion.
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The present research
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The present study focused on the association between perceived social exclusion and
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psychological distress in everyday life, testing possible mediating effects of positive and negative
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emotions. Moreover, we explored whether the participants’ tendency to avoid uncomfortable and
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distressing internal experiences could moderate the relationships among social exclusion, emotions,
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and psychological distress. As noted above, as an innovative factor, we adopted an Ecological
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Momentary Assessment design (EMA; for an overview, see: Shiffman et al., 2008) that allows the
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Ecological momentary assessment of social exclusion
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collecting of real-time data repeatedly over time and in natural environments. Thus, compared with
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cross-sectional designs, these advantages make the EMA methodology more reliable for
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investigating the relationship between psychological dimensions that can rapidly change over time,
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such as social exclusion and psychological distress.
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As reported in several studies (Chung, 2018; Riva et al., 2017), we hypothesized a positive
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relationship between perceived social exclusion and psychological distress. Following Williams
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(2009), we also hypothesized that affective reactions mediate this link. Specifically, a higher
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perception of social exclusion would decrease positive emotions and increase negative ones, which
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would lead to higher psychological distress. Indeed, the immediate (reflexive) emotional response is
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posited to precede the subsequent reflective stage (Williams, 2009). Further, as experiential
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avoidance (EA) strategies include attempts to avoid or reduce the intensity of emotional responses
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to stress (Hayes et al., 2012), we hypothesized that EA would moderate the exclusion-distress
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relationship. Specifically, having low levels of EA should act as a buffer against the distress
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associated with ostracism (e.g., Tyndall et al., 2018). As such, we have positioned EA as a
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response-focused rather than an antecedent emotion regulation strategy in this study (see Gross,
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1998), meaning that it can intervene when the individual reflects on the meaning of the perceived
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exclusionary episode (i.e.,, William’s reflective stage).
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Method
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Sample Size
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We planned to conduct a multilevel moderated mediation with random slopes in which we
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estimated the relationship between perceived social exclusion and psychological distress being
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mediated by negative and positive emotions. Moreover, we estimated the moderating effect of
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experiential avoidance (i.e., a between-subject variable) on all the relationships estimated in the
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mediation model. Given the complexity of the model, we based our sample size calculation on prior
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simulation studies conducted on EMA methodology and multilevel modeling. Zirkel et al. (2015)
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Ecological momentary assessment of social exclusion
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suggested collecting at least 35 observations per participant; Kreft and de Leeuw (1998)
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recommended the 30/30 rule (i.e., 30 participants with 30 observations each), whereas Hox (1998)
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proposed the 50/20 rule to achieve a good power. Moreover, Maas and Hox (2005) ran a simulation
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study on moderation in multilevel models showing that substantial biases in the estimates related to
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the level-two (i.e., between-subject) variables occur only for 30 level-two units or less. Thus, we
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planned to recruit at least 60 participants asking them to complete up to 45 EMA questionnaires.
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Participants and Procedure
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Eighty-nine participants (52 females; Age: M = 26.82, SD = 7.44) were enrolled with a
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snowball sampling method for the present study. Participants were presented with an initial online
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questionnaire on Qualtrics (2021). Then, the researcher helped participants install an application to
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manage EMA studies, Time2Rate (BLIND REFERENCE), on their smartphones. In our design,
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Time2Rate sent notifications to each participant three times a day for 15 consecutive days. We
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adopted a time-based sampling method in which assessment time systematically varied from day to
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day to cover most waking hours. When tapping on the notification, TimeToRate presented the
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participants with the brief EMA questionnaire. If participants missed the notification, they received
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three reminders (one every 30 minutes). If the last reminder was missed, no other opportunities to
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complete that specific EMA questionnaire were given.
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Measures
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Initial Questionnaire. The questionnaire measured age, gender, and experiential avoidance,
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which was assessed using the Brief Experiential Avoidance Questionnaire (BEAQ; Gámez et al.,
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2014). Participants responded using a 6-point Likert scale from 1 (strongly disagree) to 6 (strongly
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agree), α = .76. Sample items include, “The key to a good life is never feeling any pain” and “I
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would give up a lot not to feel bad.” Higher scores indicate greater levels of experiential avoidance.
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EMA Questionnaire. Each EMA questionnaire included a single question asking participants
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how they felt at that moment. Following the question, six ad hoc items (three for each construct)
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Ecological momentary assessment of social exclusion
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were developed to measure perceived social exclusion and psychological distress on a 5-point
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Likert scale, from 1 (not at all) to 5 (extremely). Specifically, “I feel ignored,” “I feel rejected,” and
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“I feel socially excluded” (α = .88) were used to assess the main components of social exclusion
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(Riva & Eck, 2016). “I feel depressed,” “I feel anxious,” and “I feel stressed out” (α = .73) were
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used to assess the main components of psychological distress (i.e., depression, anxiety, stress;
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Lovibond & Lovibond, 1995). Emotions were measured on the same Likert scale, using two items
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for positive (“happy” and “calm;” r = .58) and negative (“angry” and “sad;” r = .51) valence.
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Results
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The 89 participants completed a total of 3,283 EMA questionnaires, ranging from 5 to 45 (M
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= 36.89, SD = 11.04). Twelve participants had less than 20 repeated measures, 17 participants less
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than 30, and 20 participants less than 35, violating the recommendations of Hox (1998), Kreft and
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de Leeuw (1998), and Zirkel et al. (2015), respectively. However, given that these
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recommendations represent rules of thumb to follow in planning the data collection (not exclusion
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criteria) and a major focus of our study was the effect of a between-subject variable, we prioritized
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level-two units, keeping the number of participants as large as possible to achieve good power.
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Mplus, version 7 (Muthén & Muthén, 2012), was used to run a multilevel moderated
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mediation analysis with random slopes. Specifically, at level 1 (i.e., within-subject), we regressed
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psychological distress on perceived social exclusion, positive emotions, and negative emotions,
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estimating random slopes. Moreover, we estimated the random slope of the effect of perceived
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social exclusion on positive and negative emotions and the correlation between the latter two
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variables. At level 2 (i.e., between-subject), we estimated (a) the fixed effects of all the regression
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coefficients estimated at level 1, (b) the fixed intercept of the three dependent variables, (c) all the
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possible covariances between the coefficients mentioned in the previous two points, (d) the cross-
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level interactions between experiential avoidance and the random intercepts and slopes, and (e) the
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Ecological momentary assessment of social exclusion
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effect of gender (0 = female, 1 = male) and age on each random intercept and slope to control for
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their possible influence. All the predictors were mean-centered.
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The fixed slopes of the model (AIC = 17750.5, sample-size adjusted BIC = 17963.6) are
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displayed in Figure 1, and the effects of the between-subject predictors are reported in Table 1. The
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direct effect of social exclusion on psychological distress was not significant (p = .517). However,
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this effect was significantly mediated by both positive, b = .152, 95% C.I. [.093, .211], p < .001,
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and negative emotions, b = .050, 95% C.I. [.004, .097], p = .035. In other words, higher perceived
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social exclusion led to higher psychological distress through both a decrease in positive emotions
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and an increase in negative ones. Moreover, the mediation effect passing through positive emotions
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was stronger than the negative one, Δb = .102, 95% C.I. [.034, .169], p = .003.
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To explore whether the two mediation paths were responsible for the non-significant direct
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effect of social exclusion on psychological distress, we ran a multilevel model estimating only the
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latter effect, controlling for the influence of age and gender. The results showed that social
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exclusion had a significant and positive effect on psychological distress, b = .269, 95% C.I. [.141,
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.396], p < .001, confirming the full mediation of emotions.
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In the main model, experiential avoidance showed only one significant effect: the cross-level
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interaction with the random slope estimated between perceived social exclusion and positive
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emotions. Higher perception of social exclusion predicted a significant decrease in positive
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emotions for each level of experiential avoidance tested. However, for individuals low in
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experiential avoidance (-1 SD), the effect of perceived social exclusion on positive emotions was
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stronger, b = -.493, 95% C.I. [-.635, .351], p < .001, than what was observed in individuals high in
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experiential avoidance (+1 SD), b = -.355, 95% C.I. [-.521, -.188], p < .001.
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Due to the above cross-level interaction, experiential avoidance significantly moderated the
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indirect effect passing through positive emotions. The mediation was significant and positive for
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each level of experiential avoidance, but the indirect effect weakened as experiential avoidance
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Ecological momentary assessment of social exclusion
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increased. Indeed, for individuals low in experiential avoidance (-1 SD), the indirect effect of
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perceived social exclusion on psychological distress was stronger, b = .179, 95% C.I. [.114, .244], p
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< .001, than what was observed in individuals high in experiential avoidance (+1 SD), b = .126,
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95% C.I. [.061, .190], p < .001.
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Concerning the sociodemographic characteristics, age did not show any significant effect.
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Conversely, gender predicted the random intercepts of psychological distress and positive emotions,
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as well as the random slopes linking perceived social exclusion to psychological distress and
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negative emotions. Specifically, the average level of psychological distress was higher for females,
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M = 2.249, 95% C.I. [2.118, 2.379], p < .001, than males, M = 1.999, 95% C.I. [1.880, 2.118], p <
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.001, whereas positive emotions were significantly lower than the sample mean for females, M = -
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0.201, 95% C.I. [-0.380, -0.022], p = .028, and not significantly different from it for males, M =
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0.176, 95% C.I. [-0.002, 0.354], p = .053. The relationship between perceived social exclusion and
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psychological distress was not significant for females, b = .037, 95% C.I. [-.076, .150], p = .517,
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and positive and significant for males, b = .231, 95% C.I. [.145, .316], p < .001. Conversely, the
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relationship between perceived social exclusion and negative emotions was significant and positive
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irrespectively from gender, but weaker for females, b = .459, 95% C.I. [.328, .589], p < .001, than
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males, b = .678, 95% C.I. [.513, .843], p < .001. Finally, positive and negative emotions correlated
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negatively at both level 1, r = -.213, 95% C.I. [-.249, -.178], p < .001, and level 2, r = -.089, 95%
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C.I. [-.152, -.026], p = .006.
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Discussion
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The literature on social exclusion has typically investigated the consequences of this
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phenomenon from an experimental standpoint, manipulating individuals’ perceived ostracism and
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rejection, or using retrospective surveys. Although these methods have significantly increased the
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knowledge of the phenomenon, less is known about real-life, daily experiences of exclusion.
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Ecological momentary assessment of social exclusion
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Recently, Bernstein et al. (2021) made an effort in this direction, adopting an EMA methodology
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and finding that daily life exclusion worsened mood and threatened basic needs. However, the
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present study is the first to investigate whether individual differences moderated the immediate
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processes following daily exclusion using an EMA design, a methodology characterized by high
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ecological validity. Consistent with previous research (e.g., Riva et al., 2017; Waldeck et al., 2017),
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perceived exclusion was positively associated with psychological distress. However, we detected
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that positive and negative emotions fully mediated the exclusion-distress relationship. This finding
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supports literature reporting links between ostracism and affect (e.g., Howard et al., 2020; Spoelma
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et al., 2021; Williams, 2009). Indeed, according to Williams (2009), there is an immediate
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emotional impact following the detection of exclusion. Our data shows that such an immediate
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reaction accounts for the psychological distress resulting from the perception of exclusion.
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However, in contrast to our predictions, EA was not found to be a moderator of the
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exclusion-distress relationship. This was surprising given that EA has been shown to moderate the
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distress associated with ostracism (Tyndall et al., 2018), at least in the long-term. As such, the
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benefits of psychological flexibility (i.e., low levels of EA) may not be as evident following daily
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exclusion.
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We also unexpectedly noticed that EA was a moderator of the link between perceived
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exclusion and positive emotions. Therefore, people appeared to be somewhat partially protected
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from the distress associated with exclusion due to less of a negative impact on their positive
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emotions (e.g., maintaining one’s enjoyment in activities) if higher in EA (vs. low). As such,
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attempts to avoid the initial pain of ostracism (e.g., thought suppression, distraction) seem to benefit
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how people maintain their positive mood in coping with their exclusion. Indeed, there is evidence to
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suggest that short-term avoidance strategies (e.g., distraction) can help people endure painful events
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(e.g., Brown et al., 2022). Moreover, as people are hard-wired to detect ostracism quickly
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(Williams, 2009), an adaptive response arguably would be to attempt to down-regulate the negative
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Ecological momentary assessment of social exclusion
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impact (i.e., adopt EA strategies). This unexpected result might derive from the robust ecological
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validity of the EMA methodology, that could have uncovered new real-life effects that experimental
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approaches might conceal. However, further research is needed to explore the mechanism in which
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high levels of EA provide some protective function in the short-term. Still, in the long-term, the
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reverse effect might occur (i.e., psychological inflexibility maintains distress from exclusion). Such
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a mechanism would appear to fits with some perspectives from the psychological inflexibility
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model, which discusses whether and when EA is harmful in the moment (Levin et al., 2018).
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It was also found that men (vs. women) appeared to be more distressed due to their
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perceived exclusion. Although such findings are partially consistent with some studies (e.g., Hitlan
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et al., 2006), the literature is still mixed regarding potential sex differences in responses to social
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exclusion (e.g., Benenson et al., 2003; Waldeck et al., 2017).
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Limitations and Future Directions
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Some limitations reduce our ability to make firm conclusions. First, as noted above, 12
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participants had less than 20 repeated measures. A low number of measurements might negatively
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impact data reliability, affecting the estimation of random slopes and reducing power (e.g., Zirkel et
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al., 2015); thus, caution is warranted in interpreting our data as some assumptions were violated.
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Although post-hoc power analysis might seem an easy solution, such technique is strongly
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discouraged by statisticians (e.g., Gelman, 2019; Levine & Ensom, 2001). Indeed, post-hoc power
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is unrelated to a priori power and it only represents an alternative way to express p-values (Hoenig
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& Heisey, 2001; Lakens, 2022). Second, our sample consisted of young individuals, and females
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were overrepresented. Future studies might consider a more heterogeneous sample, especially in
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terms of age, to investigate the replicability of our findings. For instance, extant studies have shown
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that older adults are particularly vulnerable to rejection and ostracism (Hawkley et al., 2011). Our
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EMA design might provide crucial information about how to help them cope with exclusion. Third,
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as the moderation effect was small in magnitude and resulted from an exploratory analysis, the
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Ecological momentary assessment of social exclusion
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results may be subject to Type 1 errors. Moreover, considering possible power issues deriving from
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not excluding participants with too few measurements, the results might be subject to Type 2 errors.
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We recommend that future researchers examine the replicability of these findings using EMA and
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various methodologies (e.g., longitudinal, experimental) and use qualitative approaches to explore
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how people with different personality traits experience (and cope) with exclusion.
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Conclusion
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Daily encounters of social exclusion can be distressing experiences. We provide further
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evidence on this topic by employing an EMA methodology, finding that positive and negative
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emotions fully mediate the link between social exclusion and psychological distress. Our adoption
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of EMA design in this research domain represents a methodological advance insofar as the internal
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validity of numerous laboratory investigations of social exclusion has been shown. Still,
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ecologically valid methods are necessary to further our understanding of the real-world effects of
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perceived ostracism (see also Bernstein et al., 2021). Therefore, we argue that the EMA design
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might have revealed effects (i.e., the moderating role of EA) that could not be observed using other
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methods. Indeed, we found new evidence that adopting experiential avoidance strategies may
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ironically provide a partial buffer in coping with the initial impact of exclusionary events by
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maintaining positive emotions. These results extend existing literature showing that EA can
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moderate distress from ostracism; however, future research is needed to replicate further and
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explore these effects.
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Ecological momentary assessment of social exclusion
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References
1
Benenson, J. F., Markovits, H., Hultgren, B., Nguyen, T., Bullock, G., & Wrangham, R. (2013).
2
Social exclusion: More important t human females than males. PLoS one, 8(2), e55851.
3
Bernstein, M. J., Neubauer, A. B., Benfield, J. A., Potter, L., & Smyth, J. M. (2021). Within-person
4
effects of inclusion and exclusion on well-being in daily life. Personal Relationships, 28,
5
940-960.
6
Brown, P., Powell, W., Dansey, N., Al-Abbadey, M., Stevens, B., & Powell, V. (2022). Virtual
7
reality as a pain distraction modality for experimentally induced pain in a chronic pain
8
population: A exploratory study. Cyberpsychology, Behavior, and Social Networking, 25(1),
9
66-71.
10
Carter‐Sowell, A. R., Chen, Z., & Williams, K. D. (2008). Ostracism increases social
11
susceptibility. Social Influence, 3, 143-153.
12
Chung, Y. W. (2018). Workplace ostracism and workplace behaviors: A moderated mediation
13
model of perceived stress and psychological empowerment. Anxiety, Stress, & Coping,
14
31(3), 304–317. https://doi.org/10.1080/10615806.2018.1424835
15
Gámez, W., Chmielewski, M., Kotov, R., Ruggero, C., Suzuki, N., & Watson, D. (2014). The Brief
16
Experiential Avoidance Questionnaire: Development and initial validation. Psychological
17
Assessment, 26, 35–45. https://doi.org/10.1037/a0034473
18
Gelman, A. (2019). Don't calculate post-hoc power using observed estimate of effect size. Annals of
19
Surgery, 269(1), e9-e10. doi: 10.1097/SLA.0000000000002908
20
Gross, J. J. (1998). Antecedent- and response-focused emotion regulation: Divergent consequences
21
for xperience, expression, and physiology. Journal of Personality and Social Psychology,
22
74(1), 224-237.
23
Hales, A. H., Kassner, M. P., Williams, K. D., & Graziano, W. G. (2016). Disagreeableness as a
24
cause and consequence of ostracism. Personality and Social Psychology Bulletin, 42, 782-
25
797.
26
Ecological momentary assessment of social exclusion
15
Hartgernik, C. H., Van Beest, I., Wicherts, J. M., & Williams, K. D. (2015). The ordinal effects of
1
ostracism: A meta-analysis of 120 Cyberball studies. PLoS one, 10(5), e0127002.
2
Hawkley, L. C., Williams, K. D., & Cacioppo, J. T. (2011). Responses to ostracism across
3
adulthood. Social Cognitive and Affective Neuroscience, 6, 234-243.
4
Hayes, S. C., Luoma, J. B., Bond, F. W., Masuda, A., & Lillis, J. (2006). Acceptance and
5
commitment therapy: Model, processes, and outcomes. Behavior Research and Therapy, 44,
6
1-25. doi.org/10.1016/j.brat.2005.06.006
7
Hayes, S. C., Wilson, K. G., Gifford. E. V., Follette, V. M., & Strosahl, K. (1996). Experiential
8
avoidance and behavioral disorders: A functional diagnostic approach to diagnosis and
9
treatment. Journal of Consulting and Clinical Psychology, 64, 1152-1168.
10
doi.org/10.1037/0022-006X.64.6.1152
11
Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (2012). Acceptance and commitment therapy: The
12
process and practice of mindful change, (2nd ed). Guilford Press.
13
Hochard, K. D., Hulbert-Williams, L., Ashcroft, S., & McLoughlin, S. (2021). Acceptance and
14
values clarification versus cognitive restructuring and relaxation: A randomized controlled
15
trial of ultra-brief non-expert-delivered coaching interventions for social resilience. Journal
16
of Contextual Behavioral Science, 21, 12-21.
17
Hoenig, J. M., & Heisey, D. M. (2001). The abuse of power: The pervasive fallacy of power
18
calculations for data analysis. The American Statistician, 55(1), 19-24. doi:
19
10.1198/000313001300339897
20
Hox, J. J. (1998). Multilevel modeling: When and why. In I. Balderjahn, R. Mathar, & M. Schader
21
(Eds.), Classification, data analysis, and data highways (pp. 147–154). Springer-Verlag.
22
Howard, M. C., Cogswell, J. E., & Smith, M. B. (2020). The anteedents and outcomes of workplace
23
ostracism: A meta-analysis. Journal of Applied Psychology, 105(6), 577-596.
24
Kreft, I., & de Leeuw, J. (1998). Introducing multilevel modeling. Sage.
25
Ecological momentary assessment of social exclusion
16
Lakens, D. (2022). Improving Your Statistical Inferences. Retrieved from
1
https://lakens.github.io/statistical_inferences/. https://doi.org/10.5281/zenodo.6409077
2
Levin, M. E., Krafft, J. B., & Potts, S. (2018). When is experiential avoidance harmful in the
3
moment? Examining experiential avoidance as a moderator. Journal of Behavior Therapy
4
and Experimental Psyciatry, 61, 158-163.
5
Levine, M., & Ensom, M. H. H. (2001). Post hoc power: An idea whose time has passed?
6
Pharmacotherapy, 21(4), 405-409. doi: 10.1592/phco.21.5.405.34503
7
Lovibond, S. H., & Lovibond, P. F. (1995). Manual for the depression anxiety stress scales. (2nd
8
Ed.) Psychology Foundation of Australia.
9
Maas, C. J. M., & Hox, J. J. (2005). Sufficient sample sizes for multilevel modeling. Methodology,
10
1(3), 86–92. https://doi.org/10.1027/1614-1881.1.3.86
11
Muthén, L. K., & Muthén, B. O. (2012). Mplus user’s guide, 7th ed. Muthén & Muthén.
12
Nezlek, J. B., Wesselmann, E. D., Wheeler, L., & Williams, K. D. (2012). Ostracism in everyday
13
life. Group Dynamics: Theory, Research, & Practice, 16, 91-104.
14
Pancani, L., Mazzoni, D., Aureli, N., & Riva, P. (2021). Ghosting and orbiting: An analysis of
15
victims’ experiences. Journal of Social and Personal Relationships.
16
Qualtrics. (2021). Qualtrics. Provo, UT. Retrieved from http://www.qualtrics.com
17
Ren, D., Wesselmann, E. D., & Williams, K. D. (2013). Interdependent self‐construal moderates
18
coping with (but not the initial pain of) ostracism. Asian Journal of Social Psychology, 16,
19
320-326.
20
Riva, P., & Eck, J. (2016). Social exclusion: Psychological approaches to understanding and
21
reducing its impact. Springer.
22
Riva, P., Montali, L., Wirth, J. H., Curioni, S., & Williams, K. D. (2017). Chronic social exclusion
23
and evidence for the resignation stage: An empirical investigation. Journal of Social and
24
Personal Relationships, 34(4), 541–564.
25
Riva, P., Williams, K. D., & Gallway, M. (2014). The relationship between fear of social and
26
Ecological momentary assessment of social exclusion
17
physical threat and its effects on social distress and physical pain perception. PAIN, 153(3),
1
485-493.
2
Rudert, S. C., Keller, M. D., Hales, A. H., Walker, M., & Greifeneder, R. (2020). Who gets
3
ostracized? A personality perspective on risk and protective factors of ostracism. Journal of
4
Personality and Social Psychology, 118, 1247-1268.
5
Shaver, P. R., & Mikulincer, M. (2013). Attachment orientation and reactions to ostracism in close
6
relationships and groups. In C. N. De Wall (Ed.), The Oxford Handbook of Social Exclusion
7
(pp. 238-247). Oxford University Press.
8
Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological Momentary Assessment. Annual
9
Review of Clinical Psychology, 4, 1–32.
10
Spoelma, T. M., Chawla, N., & Ellis, A. P. (2021). If you can’t join ’em, report ’em: A model of
11
ostracism and whistleblowing in teams. Journal of Business Ethics, 173(2), 345-363.
12
Tyndall, I., Waldeck, D., Riva, P., Wesselmann, E. D., & Pancani, L. (2018). Psychological
13
flexibility and ostracism: Experiential avoidance rather than cognitive fusion moderates
14
distress from perceived ostracism over time. Journal of Contextual Behavioral Science, 7,
15
72-80.
16
Waldeck, D., Bissell, G., & Tyndall, I. (2020). Experiential avoidance as a moderator for coping
17
with a brief episode of ostracism: A pilot study. Journal of Contextual Behavioral
18
Science, 17, 68-72.
19
Waldeck, D., Tyndall, I., Riva, P., & Chmiel, N. (2017). How do we cope with ostracism?
20
Psychological flexibility moderates the relationship between everyday ostracism experiences
21
and psychological distress. Journal of Contextual Behavioral Science, 6, 425-432.
22
Wenzlaff, R. M., & Wegner, D. M. (2000). Thought suppression. Annual Review of Psychology, 51,
23
59-91.
24
Wesselmann, E. D., Ren, D., Swim, E., & Williams, K. D. (2013). Rumination hinders recovery
25
from ostracism. International Journal of Developmental Science, 7, 33-39.
26
Ecological momentary assessment of social exclusion
18
Williams, K. D., Cheung, C. K., & Choi, W. (2000). Cyberostracism: Effects of being ignored over
1
the Internet. Journal of Personality and Social Psychology, 79, 748-762.
2
Williams, K. D. (2009). Ostracism: A temporal need-threat model. In M. P. Zanna (Ed.), Advances
3
in experimental social psychology (Vol 41, pp. 275-314). Elsevier Academic Press.
4
Yaakobi, E. (2021). Can cultural values eliminate ostracism distress?. International Journal of
5
Intercultural Relations, 80, 231-241.
6
Yaakobi, E. (2022). Avoidant individuals are more affected by ostracism attribution. Journal of
7
Research in Personality, 96. 104184. doi.org/10.1016/j.jrp.2021.104184
8
Yaakobi, E., & Williams, K. D. (2016). Ostracism and attachment orientation: Avoidants are less
9
affected in both individualistic and collectivistic cultures. British Journal of Social
10
Psychology, 55, 162-181.
11
Zadro, L., Boland, C., & Richardson, R. (2006). How long does it last? The persistence of ostracism
12
in the socially anxious. Journal of Experimental Social Psychology, 42, 692-697.
13
Zirkel, S., Garcia, J. A., & Murphy, M. C. (2015). Experience-sampling research methods and their
14
potential for education research. Educational Researcher, 44, 7–16.
15
Ecological momentary assessment of social exclusion
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Table 1 – Effects of the between-subject predictors on random intercepts and slopes.
1
b
95% C.I.
p-value
Fixed intercept: Psychological Distress
Age
–.002
–.014, .010
.736
Gender
–.250
–.424, –.075
.005
Experiential avoidance
.127
–.028, .281
.108
Fixed intercept: Positive Emotions
Age
.009
–.007, .025
.278
Gender
.377
.127, .626
.003
Experiential avoidance
–.111
–.314, .092
.285
Fixed intercept: Negative Emotions
Age
.009
–.004, .022
.158
Gender
–.093
–.247, .061
.237
Experiential avoidance
.055
–.080, .191
.424
Fixed slope: Social Exclusion → Psychologial Distress
Age
.000
–.013, .011
.995
Gender
.193
.059, .327
.005
Experiential avoidance
–.001
–.113, .112
.991
Fixed slope: Social Exclusion → Positive Emotions
Age
.001
–.012, .013
.933
Gender
–.117
–.319, .085
.255
Experiential avoidance
.142
.009, .276
.037
Fixed slope: Social Exclusion → Negative Emotions
Age
–.008
–.018, .002
.115
Gender
.219
.020, .419
.031
Experiential avoidance
–.093
–.226, .039
.167
Fixed slope: Positive Emotions → Psychologial
Distress
Age
.003
–.004, .010
.447
Gender
.034
–.048, .117
.415
Experiential avoidance
.019
–.055, .093
.618
Fixed slope: Negative Emotions → Psychologial
Distress
Age
.003
–.005, .011
.479
Gender
.088
–.015, .192
.095
Experiential avoidance
.076
–.049, .201
.233
2
Ecological momentary assessment of social exclusion
20
Figure 1 – The diagram of the model: fixed slopes coefficients and 95% confidence intervals (in
1
parentheses) are reported.
2
3
Note. Solid lines represent significant effects at level p < .001, dotted lines represent non-
4
significant effects.
5