Stable Individual Trait Research Articles

The daily costs of workaholism: A within-individual investigation on blood pressure, emotional exhaustion, and sleep disturbances.

Workaholism literature has been so far focused on individual differences in workaholic tendencies, considering the construct as a stable individual trait and highlighting its health and well-being consequences. Only recently, research has started inspecting the daily dynamics and potential consequences of state workaholism. In this preregistered study, we aimed at systematically investigating the within-individual fluctuations in workaholism levels and their potential short-term and delayed psychophysiological responses as captured by ambulatory assessment integrating subjective and objective data. Using an intensive longitudinal design over 10 workdays with 114 workers from various occupations (2,534 measurement occasions), we found higher systolic and diastolic blood pressure, emotional exhaustion, and sleep disturbances in workdays characterized by higher-than-usual workaholism symptoms. Moreover, the reactivity to state workaholism, as indexed by afternoon blood pressure, was found as a mediator of the subsequent prolonged activation indexed by bedtime blood pressure. Finally, we found evidence of a buffering effect of evening psychological detachment on the relationship between state workaholism and sleep disturbances. Overall, our results support the conceptualization of workaholism as a multilevel phenomenon that acts as an internal job-related demand by showing the typical strain reactions triggered by well-characterized external demands. This study contributes to the literature by highlighting that transient workaholism symptoms can result in significant short-term stress responses at different levels, providing new, robust, and multisource evidence that underlies the importance of effectively preventing and managing dysfunctional work investment since its early manifestation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Contradictory deviations from maximization: Environment-specific biases, or reflections of basic properties of human learning?

Analyses of human reaction to economic incentives reveal contradictory deviations from maximization. For example, underinvestment in the stock market suggests risk aversion, but insufficient diversification of financial assets suggests risk-seeking. Leading explanations for these contradictions assume that different choice environments (e.g., different framings) trigger different biases. Our analysis shows that variation in the choice environment is not a necessary condition. It demonstrates how certain changes in the incentive structure are sufficient to trigger six pairs of contradictory deviations from maximization even when the choice environment is fixed. Moreover, our analysis shows that the direction of these deviations can be captured by assuming that choice propensities reflect reliance on small samples of past experiences. In order to clarify the underlying processes, we considered distinct models of the reliance on small samples assumption, and compared them to classical models of choice (including prospect theory). The comparison focused on both within-individual, and between-group predictions (based on a preregistered study with 120 new tasks). The results reveal large advantage of "wide sampling" models that (in the static settings we examine) approximate an effort to rely on the most similar past experiences. Surprisingly, we also found that assuming that the parameters reflect stable individual traits impairs predictions; it seems that the number of "most similar past experiences" for each individual varies from task to task. These results suggest that ignoring the predictable impact of the incentive structure can lead to exaggeration of the importance of environment- and individual-specific decision biases. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For?

Human performance shows substantial endogenous variability over time, and this variability is a robust marker of individual differences. Of growing interest to psychologists is the realisation that variability is not fully random, but often exhibits temporal dependencies. However, their measurement and interpretation come with several controversies. Furthermore, their potential benefit for studying individual differences in healthy and clinical populations remains unclear. Here, we gather new and archival datasets featuring 11 sensorimotor and cognitive tasks across 526 participants, to examine individual differences in temporal structures. We first investigate intra-individual repeatability of the most common measures of temporal structures — to test their potential for capturing stable individual differences. Secondly, we examine inter-individual differences in these measures using: (1) task performance assessed from the same data, (2) meta-cognitive ratings of on-taskness from thought probes occasionally presented throughout the task, and (3) self-assessed attention-deficit related traits. Across all datasets, autocorrelation at lag 1 and Power Spectra Density slope showed high intra-individual repeatability across sessions and correlated with task performance. The Detrended Fluctuation Analysis slope showed the same pattern, but less reliably. The long-term component (d) of the ARFIMA(1,d,1) model showed poor repeatability and no correlation to performance. Overall, these measures failed to show external validity when correlated with either mean subjective attentional state or self-assessed traits between participants. Thus, some measures of serial dependencies may be stable individual traits, but their usefulness in capturing individual differences in other constructs typically associated with variability in performance seems limited. We conclude with comprehensive recommendations for researchers.

Do individual differences in lexical reliance reflect states or traits?

Individual differences in listeners’ reliance on lexical information for speech perception have been established in the literature. However, it is not yet clear whether these individual differences reflect a context-dependent “state” or whether they reflect a stable listener “trait.” To examine this question, listeners completed three measures of lexical processing and one measure of acoustic-phonetic processing at two time points (n = 80 at session 1; n = 41 at session 2). Results to date suggest limited within-session convergence among the three measures of lexical processing, inconsistent with past results. However, strong between-session relationships for two of the three measures of lexical processing and the measure of acoustic-phonetic processing and were found, suggesting that performance in these tasks may reflect stable individual traits. A strong trading relationship between reliance on lexical versus acoustic-phonetic information was only found when both sources of information were available in a given task, suggesting that individual differences in cue use may emerge most strongly when cues conflict in speech input. Collectively, the current results suggest that individuals are stable in their acoustic-phonetic and lexical cue use strategies for a given task, but that an individual’s cue use strategy may be task-dependent.

Similarity and stability of face network across populations and throughout adolescence and adulthood

The ability to extract cues from faces is fundamental for social animals, including humans. An individual's profile of functional connectivity across a face network can be shaped by common organizing principles, stable individual traits, and time-varying mental states. In the present study, we used data obtained with functional magnetic resonance imaging in two cohorts, IMAGEN (N = 534) and ALSPAC (N = 465), to investigate - both at group and individual levels - the consistency of the regional profile of functional connectivity across populations (IMAGEN, ALSPAC) and time (Visits 1 to 3 in IMAGEN; age 14 to 22 years). At the group level, we found a robust canonical profile of connectivity both across populations and time. At the individual level, connectivity profiles deviated from the canonical profile, and the magnitude of this deviation related to the presence of psychopathology. These findings suggest that the brain processes faces in a highly stereotypical manner, and that the deviations from this normative pattern may be related to the risk of mental illness.

Three Theories of Choice and Their Psychology of Losses

Loss aversion has long been regarded as a fundamental psychological regularity, yet evidence has accumulated to challenge this conclusion. We review three theories of how people make decisions under risk and, as a consequence, value potential losses: expected-utility theory, prospect theory, and risk-sensitivity theory. These theories, which stem from different behavioral disciplines, differ in how they conceptualize value and thus differ in their assumptions about the degree to which value is dependent on state and context; ultimately, they differ in the extent to which they see loss aversion as a stable individual trait or as a response to particular circumstances. We highlight points of confusion that have at least partly fueled the debate on the reality of loss aversion and discuss four sources of conflicting views: confusion of loss aversion with risk aversion, conceptualization of loss aversion as a trait or as state dependent, conceptualization of loss aversion as context dependent or independent, and the attention–aversion gap—the observation that people invest more attentional resources when evaluating losses than when evaluating gains, even when their choices do not reveal loss aversion.

Gauging facial feature viewing preference as a stable individual trait in autism spectrum disorder.

Eye tracking provides insights into social processing deficits in autism spectrum disorder (ASD), especially in conjunction with dynamic, naturalistic free-viewing stimuli. However, the question remains whether gaze characteristics, such as preference for specific facial features, can be considered a stable individual trait, particularly in those with ASD. If so, how much data are needed for consistent estimations? To address these questions, we assessed the stability and robustness of gaze preference for facial features as incremental amounts of movie data were introduced for analysis. We trained an artificial neural network to create an object-based segmentation of naturalistic movie clips (14 s each, 7410 frames total). Thirty-three high-functioning individuals with ASD and 36 age- and IQ-equated typically developing individuals (age range: 12-30 years) viewed 22 Hollywood movie clips, each depicting a social interaction. As we evaluated combinations of one, three, five, eight, and 11 movie clips, gaze dwell times on core facial features became increasingly stable at within-subject, within-group, and between-group levels. Using a number of movie clips deemed sufficient by our analysis, we found that individuals with ASD displayed significantly less face-centered gaze (centralized on the nose; p < 0.001) but did not significantly differ from typically developing participants in eye or mouth looking times. Our findings validate gaze preference for specific facial features as a stable individual trait and highlight the possibility of misinterpretation with insufficient data. Additionally, we propose the use of a machine learning approach to stimuli segmentation to quickly and flexibly prepare dynamic stimuli for analysis. LAY SUMMARY: Using a data-driven approach to segmenting movie stimuli, we examined varying amounts of data to assess the stability of social gaze in individuals with autism spectrum disorder (ASD). We found a reduction in social fixations in participants with ASD, driven by decreased attention to the center of the face. Our findings further support the validity of gaze preference for face features as a stable individual trait when sufficient data are used.

Affective styles and emotional lateralization: A promising framework for animal welfare research

The growing recognition of animals as individuals has broader implications for farm animal welfare research. Even under highly standardized on-farm conditions, farm animals show heterogeneous but individually consistent behavioural patterns towards various stimuli, based on how they appraise these stimuli. As a result, animal welfare is likely to be highly individual as well, and studying the proximate mechanisms underlying distinct individual behaviour patterns and appraisal will improve animal welfare research. We propose to extend the framework of affective styles to bridge the gap between existing research fields on animal personality and affective states. Affective styles refer to consistent individual differences in emotional reactivity and regulation and can be predicted by baseline cerebral lateralization. Likewise, animals with consistent left or right motor biases—a proxy measure of individual patterns in cerebral lateralization—have been shown to differ in their personality, emotional reactivity, motivational tendencies or coping styles. In this paper, we present the current knowledge of the links between laterality and stable individual traits in behaviour and affect in light of hypotheses on emotional lateralization. Within our suggested framework, we make recommendations on how to investigate affective styles in non-human animals and give practical examples. This approach has the potential to promote a science of affective styles in nonhuman animals and significantly advance research on animal welfare.

The impact of emotional videos and emotional static faces on postural control through a personality trait approach.

During social interactions, perception of emotions affects motor behaviour by triggering responses like freezing or approach and avoidance reactions. It is however difficult to get a clear picture of the relationship between emotion and posture as previous studies showed inconsistent results, due to methodological differences on stimuli and/or the postural measures used. In this study, we thoroughly investigate how the perception of emotions affects postural control and action tendencies, by contrasting two types of stimuli (emotional static faces or emotional videos) expressing different types of basic emotions (happy, fear, angry, sad, disgust and neutral). We also take into account some other contributing factors relying on stable individual traits (e.g., extraversion, neuroticism, conscientiousness, empathy, etc) and emotional state (e.g., anxiety). Our results show that dynamic stimuli have a greater impact than static stimuli on postural control. Moreover, a crucial aspect of our work lay in the modulation of the relationship between emotions and posture, by stable individual traits.

Lexical entrainment reflects a stable individual trait: Implications for individual differences in language processing.

Language use is intrinsically variable, such that the words we use vary widely across speakers and communicative situations. For instance, we can call the same entity refrigerator or fridge. However, attempts to understand individual differences in how we process language have made surprisingly little progress, perhaps because most psycholinguistic instruments are better-suited to experimental comparisons than differential analyses. In particular, investigations of individual differences require instruments that have high test-retest reliability, such that they consistently distinguish between individuals across measurement sessions. Here, we established the reliability of an instrument measuring lexical entrainment, or the tendency to use a name that a partner has used before (e.g., using refrigerator after a partner used refrigerator), which is a key phenomenon for the psycholinguistics of dialogue. Online participants completed two sessions of a picture matching-and-naming task, using different pictures and different (scripted) partners in each session. Entrainment was measured as the proportion of trials on which participants followed their partner in using a low-frequency name, and we assessed reliability by comparing entrainment scores across sessions. The estimated reliability was substantial, both when sessions were separated by minutes and when sessions were a week apart. These results suggest that our instrument is well-suited for differential analyses, opening new avenues for understanding language variability. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Reliability and correlates of intraindividual variability in the oculomotor system.

Even if all external circumstances are kept equal, the oculomotor system shows intraindividual variability over time, affecting measures such as microsaccade rate, blink rate, pupil size, and gaze position. Recently, some of these measures have been associated with ADHD on a between-subject level. However, it remains unclear to what extent these measures constitute stable individual traits. In the current study, we investigate the intraindividual reliability of these oculomotor features. Combining results over three experiments (> 100 healthy participants), we find that most measures show good intra-individual reliability over different time points (repeatability) as well as over different conditions (generalisation). However, we find evidence against any correlation with self-assessed ADHD tendencies, mind wandering, and impulsivity. As such, the oculomotor system shows reliable intra-individual reliability, but its benefit for investigating self-assessed individual differences in healthy subjects remains unclear. With our results, we highlight the importance of reliability and statistical power when studying between-subject differences.

State-unspecific patterns of whole-brain functional connectivity from resting and multiple task states predict stable individual traits

An increasing number of functional magnetic resonance imaging (fMRI) studies have revealed potential neural substrates of individual differences in diverse types of brain function and dysfunction. Although most previous studies have inherently focused on state-specific characterizations of brain networks and their functions, several recent studies reported on the potential state-unspecific nature of functional brain networks, such as global similarities across different experimental conditions or states, including both task and resting states. However, no previous studies have carried out direct, systematic characterizations of state-unspecific brain networks, or their functional implications. Here, we quantitatively identified several modes of state-unspecific individual variations in whole-brain functional connectivity patterns, called “Common Neural Modes” (CNMs), from a large-scale fMRI database including eight task/resting states. Furthermore, we tested how CNMs accounted for variability in individual cognitive measures. The results revealed that three CNMs were robustly extracted under various dimensions of features used. Each of these CNMs was preferentially correlated with different aspects of representative cognitive measures, reflecting stable individual traits. Importantly, the association between CNMs and cognitive measures emerged from brain connectivity data alone (“unsupervised”), whereas previous related studies have explicitly used both connectivity and cognitive measures to build their prediction models (“supervised”). The three CNMs were also able to predict several life outcomes, including income and life satisfaction, and achieved the highest level of performance when combined with a conventional cognitive measure. Our findings highlight the importance of state-unspecific brain networks in characterizing fundamental individual variation.

Predictors of ccf-mtDNA reactivity to acute psychological stress identified using machine learning classifiers: A proof-of-concept

ObjectiveWe have previously found that acute psychological stress may affect mitochondria and trigger an increase in serum mitochondrial DNA, known as circulating cell-free mtDNA (ccf-mtDNA). Similar to other stress reactivity measures, there are substantial unexplained inter-individual differences in the magnitude of ccf-mtDNA reactivity, as well as within-person differences across different occasions of testing. Here, we sought to identify psychological and physiological predictors of ccf-mtDNA reactivity using machine learning-based multivariate classifiers. MethodWe used data from serum ccf-mtDNA concentration measured pre- and post-stress in 46 healthy midlife adults tested on two separate occasions. To identify variables predicting the magnitude of ccf-mtDNA reactivity, two multivariate classification models, partial least-squares discriminant analysis (PLS-DA) and random forest (RF), were trained to discriminate between high and low ccf-mtDNA responders. Potential predictors used in the models included state variables such as physiological measures and affective states, and trait variables such as sex and personality measures. Variables identified across both models were considered to be predictors of ccf-mtDNA reactivity and selected for downstream analyses. ResultsIdentified predictors were significantly enriched for state over trait measures (X2 = 7.03; p = 0.008) and for physiological over psychological measures (X2 = 4.36; p = 0.04). High responders were more likely to be male (X2 = 26.95; p < 0.001) and differed from low-responders on baseline cardiovascular and autonomic measures, and on stress-induced reduction in fatigue (Cohen's d = 0.38−0.73). These group-level findings also accurately accounted for within-person differences in 90% of cases. ConclusionThese results suggest that acute cardiovascular and psychological indices, rather than stable individual traits, predict stress-induced ccf-mtDNA reactivity. This work provides a proof-of-concept that machine learning approaches can be used to explore determinants of inter-individual and within-person differences in stress psychophysiology.

Temporal Stability of Sexual Excitation and Sexual Inhibition in Women.

The dual control model of sexual response proposes two factors, sexual excitation (SE) and sexual inhibition (SI), that aim to predict sexual behavior and response. While SE and SI are described as stable traits that influence sexuality-related outcomes such as sexual function or sexual risk taking, only a few studies have presented data on the stability of these factors. The aim of this study was to evaluate the temporal stability of SE and SI, and to investigate whether changes in sexual function or partnership status influence SE and SI in a longitudinal sample of women. To address these research questions, the Sexual Excitation/Sexual Inhibition Inventory for Women (SESII-W) was administered five times over the course of 4years. The SESII-W includes two main scales of SE and SI which consist of five (Arousability, Partner characteristics, Sexual power dynamics, Smell, and Setting) and three subscales (Concerns about sexual function, Arousal contingency, Relationship importance), respectively. Data from 553 women (Mage = 31.38years, SD = 10.25, range = 18-67) who participated in at least two assessment points were included in this study. Bivariate correlations between baseline and the fifth follow-up assessment indicated a high temporal stability of SE and SI in women (.47 < r < .71). A series of generalized linear models were conducted to investigate the impact of time, changes in sexual function, partnership status, and changes in partnership status on SE and SI. Partner characteristics (SE) that showed small increases over time. Across different subscales, improvements in sexual function were associated with higher SE and lower SI. Changes in partnership status and partnership status itself were predictors of one SE- and three SI-related scales. This study suggests a relatively high temporal stability of SE and SI in women and supports the dual control model's assertion that both factors are stable individual traits. Certain life events such as a new partnership or sexual difficulties may, however, impact time stability of both factors.

Attention and choice across domains.

When people are faced with a decision, they tend to choose the option that draws their attention. In recent years, correlations between attention and choice have been documented in a variety of domains. This leads to the question of whether there is a general, stable relationship between attention and choice. Here, we examined choice behavior in tasks with and without risk and social considerations, using food or monetary rewards, within a single experiment. This allowed us to test the consistency of the decision-making process across domains. In the aggregate, we identified remarkable consistency in the attention-choice link. At the individual level, subjects with strong attentional effects in one task were likely to have strong attentional effects in the others. The strength of these effects also correlated with individuals' degree of tunnel vision. Thus, the attention-choice relationship appears to be a stable individual trait that is linked to more general attentional constraints. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Unequal involvement, unequal attainment? A theoretical reassessment and empirical analysis of the value of motivation in the labor market

Inequality has often been explained by stable individual traits or by the structural features of labor markets. This study argues that we also should consider task involvement when we account for labor market inequality. Three mechanisms derived from experimental research link task involvement to performance: individuals involved in tasks are more focused on the work process, are more dedicated to mastery and problem-solving, and have stronger product quality perseverance. Despite the significance of task involvement as a motivation, its potential implication for labor market inequality is so far rather unacknowledged. We aim to develop its theoretical implications in the labor market context and test the expectation that task involvement is related to wage attainment by analyzing representative data for Sweden (LNU) and Europe (ESS). We theoretically locate our account within relational sociology, emphasizing that wage inequality is determined by interactions between worker attributes and the features of work organizations.

Predicting future learning from baseline network architecture

Human behavior and cognition result from a complex pattern of interactions between brain regions. The flexible reconfiguration of these patterns enables behavioral adaptation, such as the acquisition of a new motor skill. Yet, the degree to which these reconfigurations depend on the brain's baseline sensorimotor integration is far from understood. Here, we asked whether spontaneous fluctuations in sensorimotor networks at baseline were predictive of individual differences in future learning. We analyzed functional MRI data from 19 participants prior to six weeks of training on a new motor skill. We found that visual-motor connectivity was inversely related to learning rate: sensorimotor autonomy at baseline corresponded to faster learning in the future. Using three additional scans, we found that visual-motor connectivity at baseline is a relatively stable individual trait. These results suggest that individual differences in motor skill learning can be predicted from sensorimotor autonomy at baseline prior to task execution.

Factor structure of suggestibility revisited: new evidence for direct and indirect suggestibility

&lt;b&gt;Background&lt;/b&gt;&lt;br /&gt; Yielding to suggestions can be viewed as a relatively stable individual trait, called suggestibility. It has been long proposed that there are two kinds of suggestible influence, and two kinds of suggestibility corresponding to them: direct and indirect. Direct suggestion involves overt unhidden influence, while indirect suggestion concerns influence that is hidden, and the participant does not know that the suggestibility is being measured. So far however, empirical evidence for the existence of the two factors has been scarce. In the present study, more sophisticated and reliable tools for measuring suggestibility were applied than in the previous research, in the hope that better measurement would reveal the factor structure of suggestibility. Two tests of direct suggestibility were used: the Harvard Group Scale of Hypnotic Susceptibility, Form A, measuring hypnotic susceptibility, and the Barber Suggestibility Scale, measuring non-hypnotic direct imaginative suggestibility. Three tests served to measure indirect suggestibility: the Sensory Suggestibility Scale, measuring indirect suggestibility relating to perception; the Gudjonsson Suggestibility Scale, measuring the tendency to yield to suggestive questions and changing answers after negative feedback; and the Emotional Dialogs Tests, measuring the tendency to perceive nonexistent aggression.&lt;br /&gt; &lt;br /&gt; &lt;b&gt;Participants and procedure&lt;/b&gt;&lt;br /&gt; In sum, 115 participants were tested, 69 women, 49 men, mean age 22.20 years, SD = 2.20. Participants were tested in two sessions, lasting for a total of four hours.&lt;br /&gt; &lt;br /&gt; &lt;b&gt;Results&lt;/b&gt;&lt;br /&gt; Confirmatory factor analyses confirmed the existence of two uncorrelated factors of suggestibility: direct and indirect.&lt;br /&gt; &lt;br /&gt; &lt;b&gt;Conclusions&lt;/b&gt;&lt;br /&gt; Suggestibility may indeed involve two factors, direct and indirect, and failure to discover them in previous research may be due to methodological problems.

The Creative Stereotype Effect.

Because of its fundamental relevance to scientific innovation, artistic expression, and human ingenuity, creativity has long been the subject of systematic psychological investigation. Concomitantly, the far-reaching effects of stereotypes on various cognitive and social processes have been widely researched. Bridging these two literatures, we show in a series of two studies that stereotypes related to creativity can both enhance and diminish individuals’ performance on a divergent thinking task. Specifically, Study 1 demonstrated that participants asked to take on a stereotypically uninhibited perspective performed significantly better on a divergent thinking task than those participants who took on a stereotypically inhibited perspective, and a control group. Relatedly, Study 2 showed that the same effect is found within-subjects, with divergent thinking significantly improving when participants invoke an uninhibited stereotype. Moreover, we demonstrate the efficacy of Latent Semantic Analysis as an objective measure of the originality of ideas, and discuss implications of our findings for the nature of creativity. Namely, that creativity may not be best described as a stable individual trait, but as a malleable product of context and perspective.

The Role of Entrepreneurship in the Context of Career Trajectories: Moving Back into Wage Employment or into Unemployment?

AbstractThis study investigates patterns of movement from self‐employment to wage employment or to unemployment inBelgium. Non‐parametric techniques and complimentary log–log analyses are used to determine the significance of stable individual traits (e.g. gender) and of time‐dependent characteristics (e.g. family and organizational context, labour market mobility) in moving back to wage employment or to unemployment. Evidence is provided on the possibility of entrepreneurship acting as a ‘steppingstone’ between long‐term unemployment and paid work. Yet, significant relationships also emerge between ex‐ante time spent in unemployment and the possibility of continued unemployment upon self‐employment exit.