Introduction: The birth of a child typically transcends parents’ daily lives and is frequently described as a spiritual experience. Yet, little is known about medium- or long-term effects of becoming parents on individuals’ spirituality. Spirituality is commonly conceptualised more broadly than religiosity and can refer to an ori- entation towards something divine, no matter whether this is a religious being or a non-religious entity. Its lifespan development and responsiveness to life events are not yet systematically understood, and existing evidence often does not allow for causal conclusions. Addressing this research gap, our study seeks to provide robust causal insights on the medium-term stability and change of spirituality following childbirth.Methods: Using longitudinal pre- and post-birth spirituality data from the Swiss Household Panel (SHP), we compared participants who had become parents for the first time between 2015 and 2018 with propensity score (PS)-matched child- less and multiparous parent controls.Results: Across multiple robustness conditions regarding covariate selection, manifest and structural equation modelling analyses suggested a high average medium-term stability in spirituality (r ≥ 0.87; ρ ≥ 0.95) and no average spiritual change following childbirth among the first-time parents (N = 138) compared to the matched controls.Discussion: Given this high average stability, future research should focus on differential trajectories rather than average effects to better understand which individual and situational characteristics influence the development of spirituality following life events.

The authors causally identify the effects of intense survey participation on key labor market outcomes by randomly excluding individuals willing to sign up for a high-intensity survey with a focus on job search and well-being. Using administrative data, they find that, on average, survey participation had no effect on labor market outcomes during the year after signing up. They also demonstrate that an alternative selection-on-observables approach would yield misleading results. These findings underscore the value of experiments in examining effects of survey participation.

In the present study we examined whether spatial indicators of neighborhood structure proxied by the social composition of the local population predict numeracy competencies of children in early childhood educational institutions. Additionally, we investigated whether the impact of neighborhood structure differs between early childhood education institutions in urban and rural areas. We used data from 189 children attending early childhood educational institutions in two federal states in Germany along with spatial data on social welfare and foreigner proportions as found in the neighborhoods surrounding early childhood educational institutions. Although we had limited information on children’s individual characteristics, we addressed the associated problem of selection bias partially by using growth modeling. It allowed us to consider the first measurement occasion when modeling the second one to examine the impact of neighborhood structure on children’s competencies. The results indicated that, in contrast to children who live in rural areas, a substantial amount of variance in children’s competencies in urban areas is explained by foreigner proportion. We concluded that it is useful to consider spatial aspects when predicting children’s competencies. Besides, it appears reasonable to include the neighborhood perspective into theoretical models of children’s academic development.

INTRODUCTION:Proactive coping is an important construct in health and well-being research. Yet, not much is known about its temporal stability and how life events affect it. Conceptualizations of coping have mainly focused on either (i) stable, trait-like characteristics, (ii) state-like, context-dependent features, or (iii) process-oriented aspects of coping. This preregistered study integrates these approaches to investigate the variability and stability of five dimensions of proactive coping. It further examines whether proactive coping is sensitive to an exemplary life event: unemployment. METHODS:The study uses monthly panel data of two cohorts of initially employed German job seekers (N1 = 1540; N2 = 909). It utilizes a latent-state-trait model with autoregressive effects. RESULTS:Proactive coping was highly stable over time. This stability was largely driven by dispositional (trait) differences. Situation-specific factors had a very small effect. Similarly, the effects of previous situations were overall small; however, they were larger on the early and late occasions of measurement. Furthermore, no effects of unemployment were found. The results were largely similar in the two cohorts. CONCLUSION:Proactive coping is highly stable over time and across episodes of employment and unemployment. However, it also contains a dynamic component, which suggests it can be affected by situational influences.

Multirater assessments are widely used in psychology to seperate what targets report about themselves from what others perceive about them. The Trait–Reputation–Identity (TRI) model provides a prominent modeling approach for this purpose, but applications of the model often yield improper solutions, including negative variances and weak or inadmissible factor loadings. We argue that these problems arise because the original TRI model does not sufficiently distinguish between different rater types and designs. Building on stochastic measurement theory, we show that TRI model components have different meanings depending on whether observers are interchangeable or structurally different raters. For interchangeable observers, the common observer perspective is already represented by an observer-trait factor. Consequently, the reputation effect cannot be modeled as a higher-order factor. Moreover, identity and reputation effects must be estimated in separate models. For structurally different observers, different TRI models can be specified to answer different substantive questions. We derive different design-oriented TRI models, define variance components for trait, reputation, identity, and rater-specific effects, and illustrate the approach with empirical examples. The proposed framework clarifies the interpretation of TRI effects and provides practical guidelines for specifying TRI models.

Despite extensive research, clear conceptual distinctions between prosociality, altruism and helping remain lacking. This systematic review analyzes 1075 empirical studies to examine definitional overlap and theoretical inconsistencies among these constructs. Using AI-assisted extraction and manual coding, over 5000 construct definitions were identified, clustered, and analyzed. Prosociality is most frequently defined as behavior that benefits others, altruism as cost-incurring, selfless action without expectation of return, and helping as immediate, situational support. Proactivity is primarily future-oriented and self-initiated, often outside social contexts. Based on recurring definitional patterns, we propose a nomological network positioning altruism and helping as subdimensions of prosociality. Due to conceptual divergence, proactivity is excluded. The findings clarify the structure of prosocial constructs, provide a foundation for consistent operationalization, and demonstrate the potential of combining AI tools with systematic review methodology. This approach addresses the persistent 'Jingle-Jangle' problem and supports theory-driven construct refinement in psychological and organizational research.

Unemployment is an important life event that generally affects well-being and mental health negatively. However, there is substantial interindividual variation in the size and direction of the impact. We examined this variation by investigating the potential moderation effects of attitudes toward work such as subjective significance of work and willingness to exert. We used a sample of initially employed German job seekers who participated in a longitudinal app-based study for up to 2 years. A dynamic structural equation model was utilized to explore the moderating effects of five attitudes toward work on unemployment-related changes in life satisfaction, happy mood, and depression. We found no significant moderation effects for any of the dimensions, contrary to theoretical considerations. Attitudes toward work neither buffer nor amplify the negative effects of becoming unemployed on the examined outcomes.

Cortisol, a key biomarker of hypothalamus–pituitary–adrenal (HPA) axis activity, is central to early stress regulation and neurodevelopment. While prior studies have linked maternal and infant cortisol to child outcomes, less is known about their synchrony during early infancy, a time of rapid neuroendocrine development. In this longitudinal study, we examined cortisol coupling and the correlation with maternal adverse childhood experiences (ACEs) in 305 mother–infant dyads from São Paulo, Brazil. Salivary cortisol was collected at 1 month (32.3 days) and 6 months postpartum. We assessed intra- and interindividual cortisol dynamics and coupling using bivariate latent change score modeling. Maternal and infant cortisol were positively correlated at baseline (r = 0.319, p < 0.001) and at 6 months (r = 0.208, p = 0.003), suggesting early attunement that diminishes over time. Mothers and infants showed negative self-feedback, where higher baseline cortisol predicted smaller changes (mothers: B = -0.654; infants: B = -0.615; both p < 0.001). Maternal ACEs predicted elevated maternal cortisol at baseline (B = 0.126, p = 0.026) but did not affect the rate of change. These findings reveal early HPA synchrony and gradual decoupling, and highlight the lasting effects of maternal adversity on postpartum stress physiology.

Previous studies have applied a variable-centered approach to conduct extensive investigations of preservice early childhood teachers’ (PECTs’) epistemic beliefs in the domain of mathematics (application-related beliefs, process-related beliefs, static orientation), enjoyment of mathematics, mathematics anxiety, mathematical content knowledge, and mathematics pedagogical content knowledge. However, person-centered approaches, which have been fruitfully applied to other constructs and domains concerning pre- and inservice teachers, have not yet been applied to the aforementioned constructs. We addressed this research gap by investigating relationships between mathematics-related beliefs, emotions, and knowledge in terms of the well-established control-value theory in combination with a mixture distribution path analysis. About 1,851 PECTs took part in the study. Participants worked on tests and questionnaires during regular class time in teacher education. The results yielded two latent classes with structural differences in the coefficients of the path model, which we termed the application and static learning classes. In Class 1, higher levels of application-related beliefs were in line with lower levels of anxiety and higher levels of knowledge. In Class 2, higher levels of static orientation were in line with lower levels of enjoyment and higher levels of anxiety and knowledge. These novel results indicate two pathways for learning, with implications for research and practice. For research, the results are interesting with regard to static orientation and show the need for further research. For practice, they indicate the need to respect individual differences even during teacher education.

Neuropsychological assessment has to consider the subjective and objective functional deficits of help-seeking individuals in several cognitive domains. Due to time constraints in clinical practice, several web-based approaches have been developed. The current study examined whether functional deficits in the mnestic and attentive domain can be predicted based on an unsupervised self-administered online assessment neuropsychological online screening (NOS): This screening includes self-reports and psychometric memory tests (face-name association, visual short-term memory). Data of help-seeking individuals (n = 213, mean age: 48.2 years) running an extensive in-person assessment were analyzed. A functional deficit in at least one cognitive domain was detected in 48 individuals. This classification was supported by the preceding online screening (sensitivity = 0.75, specificity = 0.80), and a linear regression model identified two significant predictors (free recall performance, form discrimination in visual short-term memory). The predictive quality was enhanced for individuals with selective deficits in the mnestic domain (n = 23: sensitivity = 0.78 and specificity = 0.78) as compared to the attentive domain (n = 25: sensitivity = 0.68 and specificity = 0.75). Our results show that a neuropsychological in-person assessment cannot be replaced by an unsupervised self-administered online test. However, a specific pattern of results in the online test might indicate the necessity of an extensive assessment in help-seeking individuals.

This pre-registered study examines the longitudinal relationships between well-being, hair cortisol (a biomarker linked to poor health), and self-reported health. Accumulated cortisol output over three months was determined quarterly over the course of one year using hair samples. Well-being was assessed as affective well-being (via experience sampling), cognitive well-being (i.e., life satisfaction), and eudaimonic well-being (via the Ryff Scales of Psychological Well-Being). Self-reported health was measured using one item on the current state of health. The longitudinal analyses allowed for disentangling initial between-person differences from within-person changes and were based on a large panel study of working-age people (N = 726). The results indicate that hair cortisol levels were generally not associated with any of the examined well-being facets, regardless of the level of analysis. Further, deviations from well-being trait levels were not linked to subsequent within-person changes in hair cortisol (and vice versa), challenging the notion that cortisol output is a key physiological pathway through which well-being improves health. In contrast, self-reported health was positively correlated with affective, cognitive, and eudaimonic well-being at both the trait and within-person levels, whereas deviations from well-being trait levels were generally not associated with subsequent within-person changes in self-reported health, and vice versa.

There is considerable interest in studying the impact of major life events (e.g., marriage, job loss) on people’s lives. This line of research is inherently causal: Its goal is to study whether life events cause changes in the examined outcomes. However, because major life events cannot be randomly assigned, studies in this area necessarily rely on longitudinal observational data. In this article, we provide guidelines for researchers interested in studying life events in an explicitly causal framework. Although focused on life-event studies for substantive context, many recommendations also apply to longitudinal observational studies more broadly. We begin by emphasizing the importance of clearly specifying the causal estimand and describe conditions in which the defined causal estimand can be identified. Then, we discuss the features and challenges of the two main analytical approaches to causal inference in life-event studies: difference-in-difference designs with a (matched) comparison group that attempt to separate event-related changes from normative changes and within-person designs that control for all time-invariant person-level confounders. We describe how the desired causal effect can be estimated in these designs and provide recommendations for when to apply each modeling strategy. In addition, we present methods for conducting sensitivity analysis, probing the robustness of the estimated causal effects, and evaluating the generalizability of the results. We conclude by describing how new specialized panel studies can be designed to examine the impact of various life events in more controlled settings.

This research examines the factor structure and psychometric properties of two well-known Dark Triad personality trait questionnaires: the Short Dark Triad (SD3) and the Dirty Dozen (DD). By analyzing data from 11 (SD3) and 5 (DD) carefully selected studies in the United States and Canada, this meta-analysis uncovers unexpected correlations among questionnaire items, challenging existing assumptions. The study employs a two-stage structural equation modeling approach to evaluate various measurement models. Conventional models, such as the correlated factor and orthogonal bifactor models, fail to explain the irregular correlations. For Dirty Dozen items, a bifactor-(S·I-1) model is more suitable than the orthogonal bifactor model, significantly affecting interpretation. On the other hand, the complex structure of the SD3 necessitates item revision to enhance reliability, discriminant validity, and predictive validity. These findings emphasize the need for refining and clarifying concepts in item revision. Furthermore, the research highlights the overlap between Machiavellianism and psychopathy, particularly in relation to revenge-related items, suggesting the need for differentiation between these traits or the identification of distinct core characteristics.

Rating scales are susceptible to response styles that undermine the scale quality. Optimizing a rating scale can tailor it to individuals' cognitive abilities, thereby preventing the occurrence of response styles related to a suboptimal response format. However, the discrimination ability of individuals in a sample may vary, suggesting that different rating scales may be appropriate for different individuals. This study aims to examine (1) whether response styles can be avoided when individuals are allowed to choose a rating scale and (2) whether the psychometric properties of self-chosen rating scales improve compared to given rating scales. To address these objectives, data from the flourishing scale were used as an illustrative example. MTurk workers from Amazon's Mechanical Turk platform (N = 7042) completed an eight-item flourishing scale twice: (1) using a randomly assigned four-, six-, or 11-point rating scale, and (2) using a self-chosen rating scale. Applying the restrictive mixed generalized partial credit model (rmGPCM) allowed examination of category use across the conditions. Correlations with external variables were calculated to assess the effects of the rating scales on criterion validity. The results revealed consistent use of self-chosen rating scales, with approximately equal proportions of the three response styles. Ordinary response behavior was observed in 55-58% of individuals, which was an increase of 12-15% compared to assigned rating scales. The self-chosen rating scales also exhibited superior psychometric properties. The implications of these findings are discussed.

This study examined whether the six trait-like dimensions of psychological well-being (e.g., autonomy and environmental mastery) moderate the effects of unemployment on various facets of subjective well-being (i.e., life satisfaction, satisfaction with life domains, and experienced mood). Further, re-employment expectations during unemployment were investigated as a moderator in this context. The study is based on monthly panel data (N-observations > 23,000) of two samples of initially employed German jobseekers, who either registered as jobseekers due to (i) mass layoffs or plant closures (N = 552) or (ii) other reasons (N = 988). The results indicate substantial interindividual differences in unemployment-related changes across all examined subjective well-being facets. However, dimensions of psychological well-being did generally not moderate these changes. Only in one unemployment context, environmental mastery was positively related to unemployment-related mood changes. Good re-employment expectations were related to increases in several well-being facets (e.g., leisure satisfaction) compared to being employed, whereas poor re-employment expectations were associated with particularly detrimental effects of unemployment in terms of life satisfaction. Overall, the study provides further evidence that (perceived) contextual features of unemployment seem to be particularly relevant for how individuals experience unemployment, whereas internal (coping) resources only seem to play a negligible role.

We estimate the dynamic impact of two waves of the COVID-19 pandemic on an exceptionally broad range of indicators of worker well-being. Our analyses are based on high-frequency panel data from an app-based survey of German workers and employ an event-study design with individual-specific fixed effects. We find that workers' mental health decreased substantially during the first wave of the pandemic. To a smaller extent, this is also true for life satisfaction and momentary happiness. Most well-being indicators converged to prepandemic levels when infection rates declined. During the second wave of the pandemic, overall worker well-being decreased less than that during the first wave. Life satisfaction does not seem to have changed at all. We conclude that worker well-being adapts to the pandemic. Moreover, subgroup analyses indicate that, in terms of well-being, workers who took part in a job retention scheme fared less well during the pandemic than other employees.

Combining survey data with biological information allows examining complex interrelationships between a person’s physiological status and behavioral or health-related outcomes. Given the increasing importance of online surveys and smartphone-based research, a crucial question is whether biomarker collection can be embedded in online surveys without any face-to-face interaction. The present study addresses this question and investigated participation rates and selective participation in a longitudinal hair collection study that was embedded within an app-based smartphone panel survey on the well-being of German jobseekers. The study further examined the association between participating in the first hair collection wave and panel attrition. The results indicate that the vast majority (81%) of individuals was willing to participate in the first hair collection wave with only a few selection effects. Only older age and higher levels of perceived stress were modestly associated with the stated willingness to participate in the first hair collection wave. The strongest selectivity was induced by the inevitable exclusion of individuals with short hair styles, which led to an underrepresentation of men. Furthermore, respondents’ purported willingness to participate in the first hair collection wave and their actual participation was largely disconnected. This lack of compliance decreased in subsequent collection waves. Notably, participating in the first hair collection wave was positively related to long-term panel participation. Overall, the study underlines the general feasibility of integrating biomarker collections into online surveys.

As the robust maximum likelihood χ2 goodness-of-fit test had been found to yield inflated type-I error rates for certain two-level confirmatory factor analysis (CFA) models, a new correction for the test was implemented in Mplus version 8.7. In this simulation study, we inspected whether the corrected test statistics follow the expected χ2 distributions when applying more complex two-level models for multitrait-multimethod data with varying sample sizes and correlations within trait factors. Investigating rejection rates and probability-probability plots, we found that the new correction markedly and sufficiently reduced previously inflated rejection rates in conditions with within-trait correlations equal to 1, 100 between-level units, and 10 or 20 within-level units. In other conditions, rejection rates were hardly affected or not sufficiently reduced by the new correction. While in most conditions, 2 within-level units did not suffice, 5 within-level units and 250 between-level units were enough to yield correct rejection rates given within-trait correlations did not exceed 0.80. Correlations above 0.80 required larger sample sizes. In planning studies with multilevel CFA models, researchers should be aware that sample size requirements for likelihood-based model fit evaluations can depend on several different factors and might consider conducting Monte Carlo simulations tailored to their specific modeling conditions.

During the COVID-19 pandemic, a sizable proportion of employees conducted home-based telework to contain virus spreading. This situation made it possible to investigate the relationship between telework and job characteristics. Many positive and negative associations between telework and job characteristics have been proposed in the literature, but most studies relied on cross-sectional data as well as narrow samples (e.g. employees voluntarily choosing to telework). Repeated measures designs investigating the association between telework intensity and job characteristics using less selective samples are currently rare. To address this research gap, we collected data at two time points in Germany during the COVID-19 pandemic (n = 479) and investigated if change in telework intensity was associated with change in 19 job characteristics using structural equation modeling. Our analyses showed that-in contrast to several prior cross-sectional studies-telework intensity had a small to moderate association with only two out of the 19 job characteristics: Work scheduling and decision-making autonomy. Hence, the study challenges the previously assumed manifold positive and negative associations between telework intensity and job characteristics and adds to the debate about the role of telework intensity as an antecedent of work design. Future studies should investigate the generalizability of the findings to non-pandemic work contexts.