Emotional (in)stability: Neuroticism is associated with increased variability in negative emotion after all

Abstract

The personality trait neuroticism is tightly linked to mental health, and neurotic people experience stronger negative emotions in everyday life. But, do their negative emotions also show greater fluctuation? This commonsensical notion was recently questioned by [Kalokerinos et al. Proc Natl Acad Sci USA 112, 15838–15843 (2020)], who suggested that the associations found in previous studies were spurious. Less neurotic people often report very low levels of negative emotion, which is usually measured with bounded rating scales. Therefore, they often pick the lowest possible response option, which severely constrains the amount of emotional variability that can be observed in principle. Applying a multistep statistical procedure that is supposed to correct for this dependency, [Kalokerinos et al. Proc Natl Acad Sci USA 112, 15838–15843 (2020)] no longer found an association between neuroticism and emotional variability. However, like other common approaches for controlling for undesirable effects due to bounded scales, this method is opaque with respect to the assumed mechanism of data generation and might not result in a successful correction. We thus suggest an alternative approach that a) takes into account that emotional states outside of the scale bounds can occur and b) models associations between neuroticism and both the mean and variability of emotion in a single step with the help of Bayesian censored location-scale models. Simulations supported this model over alternative approaches. We analyzed 13 longitudinal datasets (2,518 individuals and 11,170 measurements in total) and found clear evidence that more neurotic people experience greater variability in negative emotion.

Personality Expression in Body Motion Dynamics: An Enactive, Embodied and Complex Systems Perspective

“…Of the personality traits, neuroticism was most predictive of the self-organizing dynamics of body motion (RQA) measures. More neurotic participants were more likely to show unpredictable, unstable, less complex, and more fluctuating/volatile motion dynamics (thus low emotional stability), in line with H2b and the literature (e.g., Mader et al, 2023). These effects were observed when talking about sensory experiences (topic 2) and were most pronounced when participants talked about their socio-emotional life (topic 3).…”

“…Extraversion as most expressible personality factor (e.g., Albright et al, 1988;Kenny et al, 1992;Jiang et al, 2023) captures differences in flexibility, novelty seeking (DeYoung, 2013), and resilience (Oshio et al, 2018), and high scorers were expected (H2a) to show adaptive selforganizing behavior as indicated by more system Entropy (complexity/flexibility), Determinism, Laminarity, and Mean Line. Neuroticism captures more unstable patterns of body motion (Koppensteiner, 2013) and emotion dynamics (Mader et al, 2023). Neuroticism was expected (H2b)…”

Longitudinal within-person variability around personality trajectories.

“…In the present study, even with only the single outcome of health status, sigma proved to have predictive utility above and beyond any associations attributable to intercepts and slopes. This finding corresponds with past research that has examined more short-term, dynamic within-person variability metrics from intensive longitudinal data and found that these metrics are likewise unique predictors of poorer health outcomes, particularly mental health (Anvari et al, 2023;Mader et al, 2023;Ringwald & Wright, 2024). The effects in the present study, as well as in any study in which personality metrics are used to predict an outcome, highlight an important point.…”

Narcissists’ affective well-being: Associations of grandiose narcissism with state affect level and variability.

“…3 Another alternative was proposed by Mestdagh et al (2018), who suggested the use of a relative variability index that takes into account the maximum possible variance given an observed mean. However, this approach was subsequently criticized by Mader et al (2023), who argued that the relative variability index and other corrective indices do not consider the assumed mechanism of data generation and the theoretical possibility of emotional states outside the scale bounds (e.g., extremely positive affective states beyond the upper end of the scale). They suggested a Bayesian-censored location scale model (BCLS) as an alternative modeling approach, which offers the advantages of a MELS model and additionally treats observed affective states as censored variables (i.e., true affective states are assumed to follow an unbounded normal distribution that is censored during the measurement process due to scale bounds).…”