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This study aims to develop and test a multivariable psychosocial prediction model of subjective well-being in Ukrainian adults (n = 1,248) 1.5 years after the 2022 Russian invasion of Ukraine.

The research design followed the “Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis” checklist. The online survey combined a questionnaire on sociodemographic characteristics and specifics of living in wartime, as well as validated self-reported inventories: The Modified BBC Subjective Well-being Scale, Acceptance and Action Questionnaire – Version 2 and Connor–Davidson Resilience Scale-10.

The initially developed model was tested through regression analysis, which revealed nine variables as predictors of the subjective well-being scores within the sample, explaining 49.3% of its variance. Among them, the strongest were living with a friend and receiving mental health care systematically. They were almost twice as influential as forced displacement abroad and trauma exposure, which predicted lower well-being, and living with a spouse, which forecasted higher well-being scores. Two resilience subscales – adjustment and restoring and resistance – as predictors of better well-being and perceived unsuccess in life and age as predictors of lower well-being were relatively weaker but statistically significant.

The obtained results support the previous evidence on the essential role of accessible mental health services and social support in times of war, as well as the deteriorative effect of trauma exposure and forcible taking refuge on subjective well-being.

This purpose of this study was to investigate the role of nurses’ resilience as an indicator of their mental health on sick leave absenteeism during the COVID-19 pandemic.

This descriptive-analytical study was conducted in 2020 to identify the predictors of absenteeism among 260 nurses working in two training hospitals delivering specialized services in the treatment of COVID-19 patients. Data was collected through the use of standard questionnaires including demographic information, nurses’ resilience, intention for job turnover and absenteeism from the workplace. To predict sick leave absenteeism, regression analyses were implemented.

Study results revealed that the most influencing features for predicting the probability of taking sick leave among nurses were marital status, tenacity, age, work experience and optimism. Logistic regression also depicted that nurses who had less faith in God or less self-control were more likely to take sick leave.

The resilience of nurses working in the COVID-19 pandemic was relatively low, which needs careful consideration to apply for organizational support. Main challenge that most of the health systems face include an inadequate supply of nurses which consequently lead to reduced efficiency, poor quality of care and decreased job performance. Thus, hospital managers need to put appropriate managerial interventions into practice, such as building a pleasant and healthy work environment, to improve nurses’ resilience in response to heavy workloads and stressful conditions.

To the best of the authors’ knowledge, this is the first study to examine such a relationship, thus contributing findings will provide a clear contribution to nursing management and decision-making processes. Resilience is an important factor for nurses who constantly face challenging situations in a multifaceted health-care system.

This study aims to develop and test multivariable psychosocial prediction models of perceived post-traumatic stress disorder (PTSD) and complex post-traumatic stress disorder (CPTSD) symptoms development among trauma-exposed Ukrainian adults (n = 761) after 1.5 years of the 2022 Russian invasion of Ukraine.

This research was designed as a survey in line with the methodology of “Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis” checklist. The survey included a questionnaire on sociodemographic characteristics and specifics of trauma exposure, as well as validated self-reported inventories: The International Trauma Questionnaire, Acceptance and Action Questionnaire – version 2, Connor–Davidson Resilience Scale-10 and the Modified BBC Subjective Well-being Scale.

Regression analysis revealed different prediction models for PTSD and CPTSD symptoms, explaining 18.4% and 41.4% of their variance with five and eight predictors, respectively. Four variables were similar in predicting PTSD and CPTSD: war-relatedness of trauma, living with a friend, perceived physical health and regret for the past. War-relatedness of trauma the respondents were exposed to was among the strongest predictors for PTSD and CPTSD severity. However, living with a friend was almost equally strong in mitigating these mental consequences. Regret for past and lowly rated physical health were assessed as relatively weaker but statistically significant predictors in this study.

Upon the original theoretical framework, two psychosocial prediction models were developed for PTSD and CPTSD symptoms in a non-clinical sample of trauma-exposed Ukrainian adults.

This study aims to identify the effect of soft skills as a driver of audit quality and their moderating role in the relationship between stress and the propensity for auditors to engage in reduced audit quality practices (RAQP).

This study uses a sample of 130 auditors, whose data were collected through an electronic questionnaire. The results were derived from the partial least squares-structural equation modelling method.

The findings show that the propensity to incur RAQP increases when auditors are under job stressors but decreases when individuals have resilience and time management skills. Moreover, the results suggest that the moderating effect of these two soft skills can effectively reduce the auditors’ propensity to engage in dysfunctional actions and judgments in auditing. Emotional intelligence and self-efficacy skills are shown not to affect RAQP.

This study adds to previous research on auditors’ drivers for supplying audit quality, by providing evidence of auditor characteristics as a critical input to audit quality. The results emphasize the importance of researchers including in models the moderating effect of soft skills on the relationship between audit quality and determinants associated with audit firms, clients or the regulatory framework.