It is assumed that bipolarity in happiness and sadness requires mutual exclusion. However, we present psychometric research to show how coendorsements of happiness and sadness do not necessarily constitute evidence against bipolarity. Because individuals have a tendency to endorse emotion terms close to their current state, individuals whose current state is close to the middle of a bipolar continuum would report both happiness and sadness, despite their current state being best represented by a single point. As such, endorsements of happiness (...) and sadness are theoretically expected when individuals’ current state is in the middle of the continuum. Bipolarity however would be violated if endorsements of extreme levels of happiness and sadness can be demonstrated, which has yet to be shown. (shrink)

The growth of positive psychology has birthed debate on the nature of what “positive” really means. Conceptualizations of positive attributes vary across psychological perspectives, and it appears these definitional differences stem from standards for “positive” espoused by three normative ethical frameworks: consequentialism, deontology, and virtue ethics. When definitions of “positive” do not align with one of these ethical schools, it appears researchers rely on preference to distinguish positive attributes. In either case, issues arise when researchers do not make their theoretical (...) alignment explicit, leading to value-laden, often subjective criteria being smuggled into science as a description of what is positive. To foster a deeper critical understanding of the different approaches, we examine how these conceptual definitions of positive attributes (mis)align with their ethical traditions or fail to align with an ethical school. (shrink)

Shaping off-job life is becoming increasingly important for workers to increase and maintain their optimal functioning. Proactively shaping the job domain has been extensively studied, but crafting in the off-job domain has received markedly less research attention. Based on the Integrative Needs Model of Crafting, needs-based off-job crafting is defined as workers’ proactive and self-initiated changes in their off-job lives, which target psychological needs satisfaction. Off-job crafting is posited as a possible means for workers to fulfill their needs and enhance (...) well-being and performance over time. We developed a new scale to measure off-job crafting and examined its relationships to optimal functioning in different work contexts in different regions around the world. Furthermore, we examined the criterion, convergent, incremental, discriminant, and structural validity evidence of the Needs-based Off-job Crafting Scale using multiple methods. The results showed that off-job crafting was related to optimal functioning over time, especially in the off-job domain but also in the job domain. Moreover, the novel off-job crafting scale had good convergent and discriminant validity, internal consistency, and test–retest reliability. To conclude, our series of studies in various countries show that off-job crafting can enhance optimal functioning in different life domains and support people in performing their duties sustainably. Therefore, shaping off-job life may be beneficial in an intensified and continually changing and challenging working life. (shrink)

This article describes some potential uses of Bayesian estimation for time-series and panel data models by incorporating information from prior probabilities in addition to observed data. Drawing on econometrics and other literatures we illustrate the use of informative “shrinkage” or “small variance” priors while extending prior work on the general cross-lagged panel model. Using a panel dataset of national income and subjective well-being we describe three key benefits of these priors. First, they shrink parameter estimates toward zero or toward each (...) other for time-varying parameters, which lends additional support for an income → SWB effect that is not supported with maximum likelihood. This is useful because, second, these priors increase model parsimony and the stability of estimates and thus improve out-of-sample predictions and interpretability, which means estimated effect should also be more trustworthy than under ML. Third, these priors allow estimating otherwise under-identified models under ML, allowing higher-order lagged effects and time-varying parameters that are otherwise impossible to estimate using observed data alone. In conclusion we note some of the responsibilities that come with the use of priors which, departing from typical commentaries on their scientific applications, we describe as involving reflection on how best to apply modeling tools to address matters of worldly concern. (shrink)

Developing self-report Likert scales is an essential part of modern psychology. However, it is hard for psychologists to remain apprised of best practices as methodological developments accumulate. To address this, this current paper offers a selective review of advances in Likert scale development that have occurred over the past 25 years. We reviewed six major measurement journals between the years 1995–2019 and identified key advances, ultimately including 40 papers and offering written summaries of each. We supplemented this review with an (...) in-depth discussion of five particular advances: conceptions of construct validity, creating better construct definitions, readability tests for generating items, alternative measures of precision [e.g., coefficient omega and item response theory information], and ant colony optimization for creating short forms. The Supplementary Material provides further technical details on these advances and offers guidance on software implementation. This paper is intended to be a resource for psychological researchers to be informed about more recent psychometric progress in Likert scale creation. (shrink)