Person-specific priorities in solitude.

OBJECTIVE: People value solitude in varying degrees. Theories and studies suggest that people's appreciation of solitude varies considerably across persons (e.g., an introverted person may value solitude more than an extraverted person), and solitude experiences (i.e., on average, people may value some functions of solitude, e.g., privacy, more than other functions, e.g., self-discovery). What are the unique contributions of these two sources? METHOD: We surveyed a quota-based sample of 501 US residents about their perceived importance of a diverse set of 22 solitude functions. RESULTS: Variance component analysis reveals that both sources contributed to the variability of perceived importance of solitude (person: 22%; solitude function: 15%). Crucially, individual idiosyncratic preferences (person-by-solitude function interaction) had a substantial impact (46%). Further analyses explored the role of personality traits, showing that different functions of solitude hold varying importance for different people. For example, neurotic individuals prioritize emotion regulation, introverted individuals value relaxation, and conscientious individuals find solitude important for productivity. CONCLUSIONS: People value solitude for idiosyncratic reasons. Scientific inquiries on solitude must consider the fit between a person's characteristics and the specific functions a solitary experience affords. This research suggests that crafting or enhancing positive solitude experiences requires a personalized approach.

Parametric g-formula for Testing Time-Varying Causal Effects: What It Is, Why It Matters, and How to Implement It in Lavaan.

Psychologists leverage longitudinal designs to examine the causal effects of a focal predictor (i.e., treatment or exposure) over time. But causal inference of naturally observed time-varying treatments is complicated by treatment-dependent confounding in which earlier treatments affect confounders of later treatments. In this tutorial article, we introduce psychologists to an established solution to this problem from the causal inference literature: the parametric g-computation formula. We explain why the g-formula is effective at handling treatment-dependent confounding. We demonstrate that the parametric g-formula is conceptually intuitive, easy to implement, and well-suited for psychological research. We first clarify that the parametric g-formula essentially utilizes a series of statistical models to estimate the joint distribution of all post-treatment variables. These statistical models can be readily specified as standard multiple linear regression functions. We leverage this insight to implement the parametric g-formula using lavaan, a widely adopted R package for structural equation modeling. Moreover, we describe how the parametric g-formula may be used to estimate a marginal structural model whose causal parameters parsimoniously encode time-varying treatment effects. We hope this accessible introduction to the parametric g-formula will equip psychologists with an analytic tool to address their causal inquiries using longitudinal data.

Does dispositional preference for solitude predict better psychological outcomes during times of social distancing? Beliefs and reality.

OBJECTIVE: People value solitude for themselves. Yet little is known about how people perceive dispositional preference for solitude in others. Does dispositional preference for solitude represent a protective factor from psychological distress during times of social distancing? And do laypeople have accurate beliefs about the role of preference for solitude? METHOD: To answer these questions, we conducted four studies (three preregistered, Ntotal  = 1418) at the early and a later stage of the COVID-19 pandemic using experimental, longitudinal, and experience sampling designs. RESULTS: People expected targets with a higher solitude preference to be more resilient (e.g., less lonely, more satisfied with life) during social distancing, and consequently prioritize them less when allocating supportive resources for maintaining social connections (Studies 1 and 2). Compared to these beliefs, the actual difference between individuals with higher versus lower solitude preference was smaller (Study 2) or even negligible (Study 3). Did people form more calibrated beliefs two years into the pandemic? Study 4 suggested no. CONCLUSIONS: Together, these studies show that people overestimate the role of preference for solitude in predicting others' psychological experience. As a result, solitude-seeking individuals may miss out on supportive resources, leading to higher risks for mental health issues.

Intensity, intent, and ambiguity: Appraisals of workplace ostracism and coping responses.

Using both correlational and experimental designs across four studies (N = 1251 working individuals), the current project aimed to contribute to the understanding of workplace ostracism by studying two research questions. First, we tested whether the subjective experience of targets reflects the current theorizing of ostracism. Second, drawing from the transactional theory of stress and coping, we investigated whether this subjective experience impacts targets' coping responses. Findings based on exploratory and confirmatory factor analyses supported the current theorizing of workplace ostracism such that perceived intensity, intent, and ambiguity were reflected in how targets appraised being ostracized at work. The appraisals were also related to coping responses. Perceived intensity predicted more approach-oriented (e.g., confrontation) and less avoidance-oriented coping responses (e.g., minimization). While attributions of intent also predicted some coping responses (e.g., instrumental support seeking), the explanatory power of perceived ambiguity was lower than the other two appraisals. Although these researcher-defined dimensions may be reflective of targets' experience, we propose that predictions made based on these dimensions need further refinement. The theoretical and practical significance of these findings are discussed in relation to how workplace ostracism is typically studied in the literature.

Does a pandemic context attenuate people's negative perception and meta-perception of solitude?

Solitude-the state of being alone without social interactions-is a common experience in everyday life. Despite that spending time alone can be enjoyable and functional, solitude is often stigmatised: People who engage in solitary activities are perceived negatively (negative perceptions of solitude) and anticipate a negative judgement from others (negative meta-perceptions of solitude). Using the COVID-19 pandemic as a backdrop, we examined whether a pandemic context, in which solitary behaviours were easily attributable to external reasons, would reduce people's negative perceptions and meta-perceptions of solitude. Across three preregistered experiments (total N = 767) conducted during the first wave of the COVID-19 pandemic, we found that the presence (vs. absence) of a pandemic context attenuated both the negative meta-perceptions and the negative perceptions of solitude. Yet, people believed that the pandemic context produced a stronger shift away from the stigmatisation of solitude than it actually did. These findings revealed the limits of contextual cues in mitigating the negative perceptions of being alone-even when these cues were explicit and readily available. The current research sheds light on the potential challenges of destigmatising solitude.

Alone in a Crowd: Is Social Contact Associated with Less Psychological Pain of Loneliness in Everyday Life?

People are often advised to engage in social contact to cope with the experience of loneliness and improve well-being. But are the moments of loneliness actually more bearable when spent in other people's company? In this research, we proposed and tested two conflicting theoretical accounts regarding the role of social contact: social contact is associated with a stronger (the amplifying account) or with a weaker (the buffering account) negative effect of loneliness on psychological well-being. Analyses of three datasets collected using ecological momentary assessments (Nindividuals = 3,035) revealed that the negative association between loneliness and well-being was stronger when participants were with others than alone, consistent with the amplifying account. Further, when participants experienced high levels of loneliness, being with others was associated with the same or with even a lower level of well-being than being alone. These findings suggest that simply spending time with others (vs. alone) is not associated with a reduced burden of loneliness and may even backfire. Supplementary Information: The online version contains supplementary material available at 10.1007/s10902-023-00661-3.

Cynical people desire power but rarely acquire it: Exploring the role of cynicism in leadership attainment.

Do cynical individuals have a stronger desire for power and are they more likely to acquire power at work? The negative consequences of cynicism-for cynics themselves and the people around them-render the examination of these questions particularly important. We first examined the role of cynicism in power motives. Results showed that more cynical individuals have a greater desire for power to avoid exploitation by others (and less so to exploit others; Study 1) and score higher on dominance (but not prestige or leadership) motives (Study 2). The subsequent two studies examined the role of cynicism in power attainment at work. A study of virtual teams (Study 3) showed that more cynical individuals were less likely to emerge as group leaders, and a prospective study of ~9000 employees followed for up to 10 years (Study 4) showed that cynicism predicted a lower likelihood of attaining a leadership position in organizations. Taken together, more (vs. less) cynical individuals have a stronger power-in particular, dominance-motive but they are not more successful at power acquisition. These findings inform the literature on cynicism and power and highlight the importance of cynical worldviews for leadership attainment.

Adjusting for Baseline Measurements of the Mediators and Outcome as a First Step Toward Eliminating Confounding Biases in Mediation Analysis.

Mediation analysis prevails for researchers probing the etiological mechanisms through which treatment affects an outcome. A central challenge of mediation analysis is justifying sufficient baseline covariates that meet the causal assumption of no unmeasured confounding. But current practices routinely overlook this assumption. In this article, we suggest a relatively easy way to mitigate the risks of incorrect inferences resulting from unmeasured confounding: include pretreatment measurements of the mediator(s) and the outcome as baseline covariates. We explain why adjusting for pretreatment baseline measurements is a necessary first step toward eliminating confounding biases. We hope that such a practice can encourage explication, justification, and reflection of the causal assumptions underpinning mediation analysis toward improving the validity of causal inferences in psychology research.

Understated gender disparities due to outcome-dependent selection: Commentary on Mackelprang et al. (2023).

What is the gender gap in invited publications in high-impact psychology journals? To answer this critical question, Mackelprang et al. (2023) examined invited publications in five high-impact psychology journals. They first calculated the share of women among authors of the invited publications (35.6%), then compared it with a "base rate" (42.3%; the share of women among associate and full psychology professors at R1 institutions). This comparison was presented as empirical evidence of women being underrepresented in the authorship of publications in these high-impact journals. In this commentary, we show that comparing these two descriptives-either using a difference or a ratio-provides little insight into the actual gender disparity of interest. A fundamental shortcoming of such a comparison is due to outcome-dependent selection. We explain what outcome-dependent selection is and why it is inappropriate. Crucially, we explain why, following such outcome-dependent selection, comparing the share of women in the selected sample with a "base rate" rules out drawing valid inferences about the actual gender gap. We urge researchers to recognize the perils of, and thus avoid, outcome-dependent selection. Finally, we suggest an alternative approach that permits a more accurate understanding of gender disparities in academia. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Data-driven covariate selection for confounding adjustment by focusing on the stability of the effect estimator.

Valid inference of cause-and-effect relations in observational studies necessitates adjusting for common causes of the focal predictor (i.e., treatment) and the outcome. When such common causes, henceforth termed confounders, remain unadjusted for, they generate spurious correlations that lead to biased causal effect estimates. But routine adjustment for all available covariates, when only a subset are truly confounders, is known to yield potentially inefficient and unstable estimators. In this article, we introduce a data-driven confounder selection strategy that focuses on stable estimation of the treatment effect. The approach exploits the causal knowledge that after adjusting for confounders to eliminate all confounding biases, adding any remaining non-confounding covariates associated with only treatment or outcome, but not both, should not systematically change the effect estimator. The strategy proceeds in two steps. First, we prioritize covariates for adjustment by probing how strongly each covariate is associated with treatment and outcome. Next, we gauge the stability of the effect estimator by evaluating its trajectory adjusting for different covariate subsets. The smallest subset that yields a stable effect estimate is then selected. Thus, the strategy offers direct insight into the (in)sensitivity of the effect estimator to the chosen covariates for adjustment. The ability to correctly select confounders and yield valid causal inferences following data-driven covariate selection is evaluated empirically using extensive simulation studies. Furthermore, we compare the introduced method empirically with routine variable selection methods. Finally, we demonstrate the procedure using two publicly available real-world datasets. A step-by-step practical guide with user-friendly R functions is included. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Estimating time-varying treatment effects in longitudinal studies.

Longitudinal study designs are frequently used to investigate the effects of a naturally observed predictor (treatment) on an outcome over time. Because the treatment at each time point or wave is not randomly assigned, valid inferences of its causal effects require adjusting for covariates that confound each treatment-outcome association. But adjusting for covariates which are inevitably time-varying is fraught with difficulties. On the one hand, standard regression adjustment for variables affected by treatment can lead to severe bias. On the other hand, omitting time-varying covariates from confounding adjustment precipitates spurious associations that can lead to severe bias. Thus, either including or omitting time-varying covariates for confounding adjustment can lead to incorrect inferences. In this article, we introduce an estimation strategy from the causal inference literature for evaluating the causal effects of time-varying treatments in the presence of time-varying confounding. G-estimation of the treatment effect at a particular wave proceeds by carefully adjusting for only pre-treatment instances of all variables while dispensing with any post-treatment instances. The introduced approach has various appealing features. Effect modification by time-varying covariates can be investigated using covariate-treatment interactions. Treatment may be either continuous or noncontinuous with any mean model permitted. Unbiased estimation requires correctly specifying a mean model for either the treatment or the outcome, but not necessarily both. The treatment and outcome models can be fitted with standard regression functions. In summary, g-estimation is effective, flexible, robust, and relatively straightforward to implement. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Do targets of ostracism truthfully communicate their emotional reactions to sources?

Ostracism triggers negative emotions such as sadness, anger, and hurt feelings. Do targets of ostracism truthfully share their emotions with the sources of ostracism? Drawing on past research on social-functional accounts of emotions and interpersonal emotion regulation, we investigated the possibility that targets may misrepresent their emotions (i.e., gaming emotions). We conducted three experiments (N = 1058; two pre-registered) using an online ball-tossing game, in which participants were randomly assigned to be included or ostracized. Consistent with the literature, we found that ostracized individuals were more hurt, sad, and angry than included individuals. However, we found little and inconsistent evidence that ostracized (vs included) individuals misrepresented their emotional reactions to the sources. Further, Bayesian analyses offered more support against misrepresentation of emotions. These findings suggest that targets of ostracism truthfully communicated their social pain to the sources.

Do cues of infectious disease shape people's affective responses to social exclusion?

Social exclusion triggers aversive reactions (e.g., increased negative affect), but being excluded may bring substantial benefits by reducing pathogen exposure associated with social interactions. Is exclusion less aversive when cues of infectious diseases are salient in the environment? We conducted two preregistered experiments with a 2 (belonging status: included vs. excluded) × 2 (disease salience: low vs. high) design, using scenarios (Study 1, N = 347) and a well-validated exclusion paradigm, Cyberball (Study 2, N = 519). Positive affect and negative affect were measured as the key outcomes. Across the 2 studies, we found little evidence that disease salience moderated the effect of exclusion (vs. inclusion) on positive affect. At the same time, we observed consistent evidence that disease salience moderated the effect of exclusion (vs. inclusion) on the other affective component: negative affect. Concretely, disease salience increased participants' negative affect in inclusion conditions; in exclusion conditions, the effect of disease salience on negative affect was negligible or nearly zero. Using a novel and robust approach of mediation analysis (interventional indirect effects), we further showed that the motive of disease avoidance rivals the motive of affiliation in shaping people's experiences of social interactions. These findings suggest that cues of disease salience alter people's affective experience with inclusion but not exclusion. The current research represents an important step toward understanding people's affective responses to social exclusion and inclusion in complex social situations involving multiple, and potentially conflicting motives. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Estimating social influence in a social network using potential outcomes.

Social influence occurs when an individual's outcome is affected by another individual's actions. Current approaches in psychology that seek to examine social influence have focused on settings where individuals are nested in predefined groups and do not interact across groups. Such study designs permit using standard estimation methods such as multilevel models for estimating treatment effects but restrict social influence to originate only from individuals within the same group. In more general settings, such as social networks where an individual is free to interact with any other individual, the absence of discernible clusters or scientifically meaningful groups precludes existing estimation methods. In this article, we introduce a new class of methods for assessing social influence in social networks in the context of randomized experiments in psychology. Our proposal builds on the potential outcomes framework from the causal inference literature. In particular, we exploit the concept of (treatment) interference, which occurs between individuals when one individual's outcome is affected by other individuals' treatments. Estimation proceeds using randomization-based approaches that are established in other disciplines and guarantee valid inference by construction. We compared the proposed methods with standard methods empirically using Monte Carlo simulation studies. We illustrated the method using publicly available data from an experiment assessing the effects of an anticonflict intervention among students' peer networks. The R scripts used to implement the proposed methods in the simulation studies and the applied example are freely available online. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Low Self-Control: A Hidden Cause of Loneliness?

Loneliness has been associated with multiple negative outcomes. But what contributes to loneliness in the first place? Drawing from the literature on the importance of self-regulatory ability for successful social functioning, the present research explored the role of low self-control as a factor leading to loneliness. A set of four studies (and three additional studies in Supplementary Online Materials) using cross-sectional, experimental, daily diary, and experience sampling methods showed that lower self-control is associated with higher loneliness at both trait and state levels. Why does low self-control contribute to loneliness? Self-control failures that have negative implications for others lead to higher risks for being ostracized by others, which predicts increased feelings of loneliness over time. These results suggest that low self-control, which is often associated with negative intrapersonal outcomes, can have important interpersonal consequences by evoking ostracism, and consequently, loneliness.

Nonlinear effect of social interaction quantity on psychological well-being: Diminishing returns or inverted U?

Social contact is an important ingredient of a happy and satisfying life. But is more social contact necessarily better? Although it is well-established that increasing the quantity of social interactions on the low end of its spectrum promotes psychological well-being, the effect of interaction quantity on the high end remains largely unexplored. We propose that the effect of interaction quantity is nonlinear; specifically, at high levels of interaction quantity, its positive effects may be reduced (Diminishing Returns Hypothesis) or even reversed (Inverted U Hypothesis). To test these two competing hypotheses, we conducted a series of six studies involving a total of 161,836 participants using experimental (Study 1), cross-sectional (Studies 2 and 3), daily diary (Study 4), experience sampling (Study 5), and longitudinal survey designs (Study 6). Consistent evidence emerged across the studies supporting the Diminishing Returns Hypothesis. On the low end of the interaction quantity spectrum, increasing interaction quantity enhanced well-being as expected; whereas on the high end of the spectrum, the effect of interaction quantity was reduced or became nearly negligible, but did not turn negative. Taken together, the present research provides compelling evidence that the well-being benefits of social interactions are nearly negligible after moderate quantities of interactions are achieved. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Association Between Dispositional Mindfulness and Need Threat Following Ostracism in Spanish Adolescents: The Moderating Role of Age.

BACKGROUND: Ostracism -being ignored and excluded- entails risks for adolescent mental health. Less is known about the factors that are negatively associated with the adverse consequences of ostracism. This study explored the association between dispositional mindfulness and need threat following social exclusion using the Cyberball paradigm. Sex and age were included as moderators of the relationship between dispositional mindfulness and need threat. Additionally, the factor structure of the Need Threat Scale (NTS) was analyzed in Spanish adolescents. METHOD: Participants (N = 750, 52.4% female; mean age = 14.51) completed a mindfulness questionnaire, were ostracized in the Cyberball game, and reported their need threat during this game. RESULTS: Dispositional mindfulness was negatively associated with need threat only in older adolescents (>15 years old). Although girls reported higher levels of need threat than boys, sex did not moderate the association between mindfulness and need threat. CONCLUSIONS: This research suggests that dispositional mindfulness is only associated with NTS in older adolescents and girls are more vulnerable to the negative consequence of ostracism.

Leaving the Loners Alone: Dispositional Preference for Solitude Evokes Ostracism.

What are the interpersonal consequences of seeking solitude? Leading theories in developmental research have proposed that having a general preference for solitude may incur significant interpersonal costs, but empirical studies are still lacking. In five studies (total N = 1,823), we tested whether target individuals with a higher preference for solitude were at greater risk for ostracism, a common, yet extremely negative, experience. In studies using self-reported experiences (Study 1) and perceptions of others' experiences (Study 2), individuals with a stronger preference for solitude were more likely to experience ostracism. Moreover, participants were more willing to ostracize targets with a high (vs. low) preference for solitude (Studies 3 and 4). Why do people ostracize solitude-seeking individuals? Participants assumed that interacting with these individuals would be aversive for themselves and the targets (Study 5; preregistered). Together, these studies suggest that seeking time alone has important (and potentially harmful) interpersonal consequences.

Seeking Solitude After Being Ostracized: A Replication and Beyond.

Individuals may respond to ostracism by either behaving prosocially or antisocially. A recent paper provides evidence for a third response: solitude seeking, suggesting that ostracized individuals may ironically engage in self-perpetuating behaviors which exacerbate social isolation. To examine this counterintuitive response to ostracism, we conceptually replicated the original paper in three studies (N = 1,118). Ostracism experiences were associated with preference for solitude across four samples (Study 1), and being ostracized increased participants' desires for solitude (Studies 2 and 3). Extending beyond the original paper, we demonstrated that only the experience of being ostracized, but not ostracizing others or the feeling of conspicuousness, triggered the desire for solitude. Diverging from the original paper, trait extraversion did not moderate the effect of ostracism on solitude desires. Taken together, the current research provides additional and stronger empirical evidence that solitude seeking is a common response to ostracism.

Identity processing in multiple-face tracking.

Research has shown that observers in a multiple-object tracking task are poor at recognizing the identity of successfully tracked objects (Z. W. Pylyshyn, 2004). Employing the same paradigm, we examined identity processing and its relationship with tracking performance for human faces. Experiment 1 showed that although identity recognition was poorer after the target faces were learned in a dynamic display, identification performance was still much higher than the chance level. The experiment also found that on average about two face identities can be correctly traced to their locations. Experiment 2 showed that tracking performance decreased significantly for unique upright faces relative to the unique inverted or identical upright faces, suggesting that upright faces activate some level of mandatory identity processing that interferes and competes with visual tracking for attentional resources. Experiment 3 found that only target faces receive identity processing in the tracking task. Experiment 4 showed that switching face identities during tracking impaired tracking performance. This may indicate that identity encoding is to some extent obligatory during multiple-face tracking. Furthermore, Experiment 5 suggested that attentional resources can be consciously allocated either to maximize identity encoding or tracking, resulting in a tradeoff between the two. The results reveal a bias for face identity processing, which may differ significantly from multiple-object tracking.