Using job characteristics theory as a framework, we calculated meta‐analytic effect sizes between meaningful work and various outcomes and tested a mediated model of meaningful work predicting proximal and distal outcomes with meta‐analytic structural equation modelling (MASEM). From 44 articles (N = 23,144), we found that meaningful work had large correlations (r = 0.70+) with work engagement, commitment, and job satisfaction; moderate to large correlations (r = 0.44 to −0.49) with life satisfaction, life meaning, general health, and withdrawal intentions; and small to moderate correlations (r = −0.19 to 0.33) with organizational citizenship behaviours, self‐rated job performance, and negative affect. The best MASEM fitting model was meaningful work predicting work engagement, commitment, and job satisfaction and these variables subsequently predicting self‐rated performance, organizational citizenship behaviours, and withdrawal intentions. This meta‐analysis provides estimated effect sizes between meaningful work and its outcomes and reveals how meaningful work relates directly and indirectly to key outcomes.

This is the first paper in a series of two that synthesizes, compares, and extends methods for causal inference with longitudinal panel data in a structural equation modeling (SEM) framework. Starting with a cross-lagged approach, this paper builds a general cross-lagged panel model (GCLM) with parameters to account for stable factors while increasing the range of dynamic processes that can be modeled. We illustrate the GCLM by examining the relationship between national income and subjective well-being (SWB), showing how to examine hypotheses about short-run (via Granger-Sims tests) versus long-run effects (via impulse responses). When controlling for stable factors, we find no short-run or long-run effects among these variables, showing national SWB to be relatively stable, whereas income is less so. Our second paper addresses the differences between the GCLM and other methods. Online Supplementary Materials offer an Excel file automating GCLM input for Mplus (with an example also for Lavaan in R) and analyses using additional data sets and all program input/output. We also offer an introductory GCLM presentation at https://youtu.be/tHnnaRNPbXs . We conclude with a discussion of issues surrounding causal inference.

In recent years, there has been heightened interest in the active role of employees in shaping activities and experiences in their pursuit of optimal functioning (i.e., feeling and performing well), referred to as job-, leisure-, home-, and work-life balance crafting. Various perspectives have emphasized distinct dimensions within the crafting process (i.e., motives, behaviors, life domains, and outcomes) yielding a rich but fragmented theoretical account. With psychological needs satisfaction as the underlying process, we propose an integrative model to account for past conceptualizations of crafting motives and efforts across a person´s various role identities. This integration highlights the importance of recognizing unfulfilled needs, matching needs and crafting efforts, within-and between-level temporal dynamics of the crafting process, and possibilities for spillover and compensation processes across identity domains. Accordingly, the Integrative Needs Model of Crafting explains a) why and how people craft, b) when and why crafting efforts may (not) be effective in achieving optimal functioning, c) the sequential process of crafting over time, and d) how crafting processes unfold across different identity domains.

Positive organizational scholarship has led to a growing interest in the critical role of positive emotions for the lives of both workers and organizations. We review and integrate the different perspectives on positive emotions (i.e., positive valence, positive emotion regulation strategies, and positive adaptive function) and the four main mechanisms (i.e., cognition, affect, behavior, and physiology) that lead to positive organizational outcomes. There is growing evidence that positive emotions influence variables vital for workplace success such as positive beliefs, creativity, work engagement, positive coping, health, teamwork and collaboration, customer satisfaction, leadership, and performance. We additionally review dynamic features of positive emotions (i.e., intraindividual variability, reactivity, inertia, cycles, feedback loops) and their relation to psychological and work outcomes. Finally, we discuss additional questions and future directions for consideration.

Using representative cross-sections from 166 nations (more than 1.7 million respondents), we examined differences in three measures of subjective well-being over the life span. Globally, and in the individual regions of the world, we found only very small differences in life satisfaction and negative affect. By contrast, decreases in positive affect were larger. We then examined four important predictors of subjective well-being and how their associations changed: marriage, employment, prosociality, and life meaning. These predictors were typically associated with higher subjective well-being over the life span in every world region. Marriage showed only very small associations for the three outcomes, whereas employment had larger effects that peaked around age 50 years. Prosociality had practically significant associations only with positive affect, and life meaning had strong, consistent associations with all subjective-well-being measures across regions and ages. These findings enhance our understanding of subjective-well-being patterns and what matters for subjective well-being across the life span.