Professional and Gender Differences in Job Stress: A Comparison of Economics, Finance, and Accounting Professionals.

OBJECTIVE: The aim of this study was to investigate the differences in the level and sources of job stress among key business professionals such as economists, financiers, and accountants as well as among genders. METHODS: This cross-sectional study used the Job Stress Survey to collect data on job stress among 702 Kazakhstani business professionals who worked in both public and private organizations. RESULTS: Analysis revealed that the degree of severity and frequency of stress was not high for all business professionals. Results showed that financiers experienced higher stress than economists due to limited opportunity for advancement and disagreeable duties. The study also found that men economists and financiers were stressed from conflicts with other departments more than women of these professions. CONCLUSIONS: Our findings provide insights for organizations about the potential ways of preventing and mitigating job stress.

The bifactor structure of the Self-Compassion Scale: Bayesian approaches to overcome exploratory structural equation modeling (ESEM) limitations.

The rapidly expanding self-compassion research is driven mainly by Neff's (2003a, 2003b, 2023) six-factor Self-Compassion Scale (SCS). Despite broad agreement on its six-first-order factor structure, there is much debate on SCS's global structure (one- vs. two-global factors). Neff et al. (2019) argue for an exploratory structural equation model (ESEM) with six specific and one global bifactor (6ESEM + 1GlbBF) rather than two global factors (6ESEM + 2GlbBF). However, ESEM's methodological limitations precluded testing the appropriate 6ESEM + 2GlbBF, relying instead on a model combining ESEM and traditional confirmatory factor analysis (6ESEM + 2CFA). Although intuitively reasonable, this alternative model results in internally inconsistent, illogical interpretations. Instead, we apply recent advances in Bayesian SEM frameworks and Bayes structural equation models fit indices to test a more appropriate bifactor model with two global factors. This model (as does 6CFA + 2GlbBF) fits the data well, and correlations between compassionate self-responding (CS) and reverse-scored uncompassionate self-responding (RUS) factors (∼.6) are much less than the 1.0 correlation implied by a single bipolar factor. We discuss the critical implications for theory, scoring, and clinical application for the SCS that previously were inappropriately based on this now-discredited 6ESEM + 2GlbCFA. In applied practice, we endorse using scores representing the six SCS factors, total SCS, and CS and RUS components rather than relying solely on one global factor. Our approach to these issues (dimensionality, factor structure, first-order and higher order models, positive vs. negatively oriented constructs, item-wording effects, and alternative estimation procedures) has wide applicability to clinical measurement (see our annotated bibliography of 20 instruments that might benefit from our approach). (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The Self-Compassion Scale: Validation and Psychometric Properties within the Exploratory Structural Equation Modeling Framework.

The Self-Compassion Scale (SCS) is one of the several tools for measuring compassionate self-attitude. Despite its popularity, there is an ongoing controversy regarding its factor structure. Previous studies employing exploratory structural equation modeling (ESEM) found support for the single-bifactor (one general and six group factors) model over the competing two-bifactor (two general factors representing compassionate and uncompassionate self-responding and six group factors) model. Here, we replicated and extended previous ESEM studies through examining the validity and dimensionality of different bifactor models in a sample of UK adults. Model fit was examined across two estimators: maximum likelihood and weighted least square mean and variance adjusted. Finally, we investigated whether one or two observed scores of the SCS can better identify cases of depression, anxiety, and mental wellbeing. Both bifactor models showed good fit to the data irrespective of the estimators used, but only the single-bifactor model demonstrated satisfactory convergent and criterion validity and unidimensionality. The total observed SCS score detected depression, anxiety and high mental wellbeing with higher accuracy than any of the two scores. Overall, we propose to use the total score of the SCS in further research and practice.

Cognitive-behavioural pathways from pain to poor sleep quality and emotional distress in the general population: The indirect effect of sleep-related anxiety and sleep hygiene.

OBJECTIVES: Pain can have a negative impact on sleep and emotional well-being. This study investigated whether this may be partly explained by maladaptive sleep-related cognitive and behavioural responses to pain, including heightened anxiety about sleep and suboptimal sleep hygiene. METHODS: This cross-sectional study used data from an online survey that collected information about pain (Brief Pain Inventory), sleep (Pittsburgh Sleep Quality Index; Sleep Hygiene Index; Anxiety and Preoccupation about Sleep Questionnaire) and emotional distress (PROMIS measures; Perceived Stress Scale). Structural equation modelling examined the tenability of a framework linking these factors. RESULTS: Of 468 survey respondents (mean age 39 years, 60% female), 29% reported pain (mean severity 1.12), most commonly in the spine or low back (28%). Pain severity correlated with poor sleep quality, poor sleep hygiene, anxiety about sleep and emotional distress. In the first structural equation model, indirect effects were identified between pain severity and sleep quality through anxiety about sleep (ß = .08, p < .001) and sleep hygiene (ß = .12, p < .001). In the second model, an indirect effect was identified between pain severity and emotional distress through sleep quality (ß = .19, p < .01). Combining these models, indirect effects were identified between pain severity and emotional distress through anxiety about sleep, sleep hygiene and sleep quality. CONCLUSIONS: This study provides data to support the tenability of a theoretically guided framework linking pain, sleep and emotional distress. If upheld by experimental and/or longitudinal study, this framework holds the potential to inform public health initiatives and more comprehensive pain assessment.