The effects of secondary stressors, social identity, and social support on perceived stress and resilience: Findings from the COVID-19 pandemic

"It's that feeling that you can't get away": Motherhood, gender inequality and the stress process during extreme events

The impacts of extreme events can intersect with pre-disaster systemic inequalities and deficiencies, exacerbating distress. This paper contributes to the existing literature by exploring the psychosocial processes through which stressors become traumatic during an extreme event. It does so by focusing on how mothers of children and/or adolescents in the United Kingdom experienced the COVID-19 pandemic. First, qualitative interviews (N = 15) showed that participants experienced a cluster of stressors stemming from their workplaces, partners, children's behaviours and homeschooling, which caused a sense of overload and captivity, reducing their quality of life. However, individual, interpersonal and collective forms of coping were reported. Second, quantitative survey data (N = 621) showed that the relationship between stressors and perceived stress was mediated by feelings of overload due to excessive identity-related tasks and caregiving responsibilities. Moreover, community identification was associated with reduced overload and perceived stress. Overall, during extreme events, people can experience distress due to being overloaded by and trapped in particular identities and identity-related tasks, unable to perform other aspects of their social selves. We argue that social psychological analyses can be useful in tracing the complex impacts of extreme events across a range of systems and levels of analysis.

Risk perception and quality of working life of nurses in infectious disease department in China: The chain-mediating effects of psychological resilience and social support

AIM

To determine whether social support and psychological resiliency are significant mediators of the associations between risk perception and quality of working life in Chinese nurses working with infectious diseases.

DESIGN

A cross-sectional study.

METHODS

A cross-sectional survey of 879 nurses in infectious diseases department of specialty or general hospitals in China completed online questionnaires on the nurses' risk perception questionnaire, quality of working life, psychological resilience and the social support rating scale.

RESULTS

Our study observed that risk perception directly negatively influences the quality of working life of infectious disease nurses, while psychological resilience and social support positively chain mediate this relationship.

CONCLUSION

Critical elements impacting the quality of working life of infectious disease nurses are risk perception, psychological resilience and social support. Managers may think about decreasing the level of risk perception and enhancing the quality of working life of infectious disease nurses by enhancing their psychological resilience and providing support.

PUBLIC CONTRIBUTION

The quality of working life of infectious disease nurses should be a priority for nursing management; it is critical to maintain their health and well-being, raise the quality of care and lower turnover. Managers should create resilience-building programmes and support tools to assist nurses properly perceive risks and adopt protective strategies to deal with them to improve the quality of working life for nurses.

The impact of stress and well-being during the COVID-19 pandemic on mental health in U.S. veterans

The COVID-19 pandemic disrupted life around the globe and negatively impacted mental health (MH), including among military veterans. Building on previous research with U.S. veterans, the present study examined the association between a broad array of pandemic stressors and well-being on MH outcomes. A total of 372 veterans (51.3% women) from all service eras completed measures of posttraumatic stress disorder and depression during early (timepoint 1 [T1]) and peri-pandemic (timepoint 2 [T2]) periods. Pandemic-related stressors and well-being (satisfaction in life domains) were assessed at the peri-pandemic timepoint (T2). Logistic regression analyses were used to investigate associations between stressors and well-being with the likelihood of a probable MH diagnosis at T2 controlling for T1 MH status. More negative physical and MH impacts of the pandemic in addition to fewer positive consequences and lower satisfaction with paid work, finances, health, romantic relationships, and social life were associated with a higher likelihood of a probable T2 MH diagnosis. COVID infection was associated with lower odds of a probable T2 MH diagnosis. There were significant indirect effects, such that physical and MH impacts of the pandemic were associated with T2 MH via well-being. Overall, these findings highlight the role of stress and well-being on MH during a global pandemic. Interventions to address well-being may be important to address veteran MH during other periods of stress. Future research should examine the generalizability of study findings and further investigate factors that contribute to veterans' MH resilience during stressful life experiences.

A Method to Explore the Best Mixed-Effects Model in a Data-Driven Manner with Multiprocessing: Applications in Public Health Research

In the present study, I developed and tested an R module to explore the best models within the context of multilevel modeling in research in public health. The module that I developed, explore.models, compares all possible candidate models generated from a set of candidate predictors with information criteria, Akaike information criterion (AIC), and Bayesian information criterion (BIC), with multiprocessing. For testing, I ran explore.models with datasets analyzed in three previous studies in public health, which assumed candidate models with different degrees of model complexity. These three studies examined the predictors of psychological well-being, compliance with preventive measures, and vaccine intent during the COVID-19 pandemic. After conducting model exploration with explore.models, I cross-validated the nomination results with calculated model Bayes Factors to examine whether the model exploration was performed accurately. The results suggest that explore.models using AIC and BIC can nominate best candidate models and such nomination outcomes are supported by the calculated model Bayes Factors. In particular, all the identified models are superior to the full models in terms of model Bayes Factors. Also, by employing AIC and BIC with multiprocessing, explore.models requires a shorter processing time than model Bayes Factor calculations. These results indicate that explore.models is a reliable, valid, and feasible tool to conduct data-driven model exploration with datasets collected from multiple groups in research on health psychology and education.

The long-term effects of consecutive COVID-19 waves on mental health

BACKGROUND

Although several studies have documented the impact of the COVID-19 pandemic on mental health, the long-term effects remain unclear.

AIMS

To examine longitudinal changes in mental health before and during the consecutive COVID-19 waves in a well-established probability sample.

METHOD

An online survey was completed by the participants of the COVID-19 add-on study at four time points: pre-COVID-19 period (2014-2015, n = 1823), first COVID-19 wave (April to May 2020, n = 788), second COVID-19 wave (August to October 2020, n = 532) and third COVID-19 wave (March to April 2021, n = 383). Data were collected via a set of validated instruments, and analysed with latent growth models.

RESULTS

During the pandemic, we observed a significant increase in stress levels (standardised β = 0.473, P < 0.001) and depressive symptoms (standardised β = 1.284, P < 0.001). The rate of increase in depressive symptoms (std. covariance = 0.784, P = 0.014), but not in stress levels (std. covariance = 0.057, P = 0.743), was associated with the pre-pandemic mental health status of the participants. Further analysis showed that secondary stressors played a predominant role in the increase in mental health difficulties. The main secondary stressors were loneliness, negative emotionality associated with the perception of COVID-19 disease, lack of resilience, female gender and younger age.

CONCLUSIONS

The surge in stress levels and depressive symptoms persisted across all three consecutive COVID-19 waves. This persistence is attributable to the effects of secondary stressors, and particularly to the status of mental health before the COVID-19 pandemic. Our findings reveal mechanisms underlying the surge in mental health difficulties during the COVID-19 waves, with direct implications for strategies promoting mental health during pandemics.

Exploring the potential impact of group identity on post-traumatic growth in the aftermath of Corona outbreak: function of social-emotional competence as a mediator

Background

This research endeavors to examine the potential effects of human and societal interactions on individuals' post-traumatic growth in the aftermath of the Corona outbreak. To achieve the aforementioned objective, the current research investigates the correlations between post-traumatic growth and group identity, while also examining the potential mediating function of social-emotional competence.

Methods

A cross-sectional design included a representative sample of 2,637 high school students located in the capital territory of Pakistan using convenience sampling method. To explore the associations, correlation and mediation analyzes utilizing the group identification scale, the social-emotional competence scale, and the post-traumatic growth scale was performed with SPSS PROCESS 4 macro and AMOS.

Results

The findings demonstrated that group identification emerged as a substantial predictor substantially associated with post-traumatic growth. Moreover, the relationship linking group identification and post-traumatic growth was found to be partially moderated by social-emotional competence.

Conclusion

The phenomenon of group identification can exert influence on post-traumatic growth through both direct and mediating pathways, with the latter being essentially mediated by social-emotional competence. The aforementioned outcomes possess significant academic and practical implications concerning the promotion of post-traumatic growth and the improvement of psychological well-being after the Corona outbreak.

The Association Between Group Identity and Post-Traumatic Growth in the Post COVID-19 Era: The Mediating Effect of Social-Emotional Competence

Purpose

To investigate the impact of human-society relationships on individual post-traumatic growth (PTG) in the post COVID-19 era, this study examined the association between group identity (GI) and PTG, and explored the mediating role of social-emotional competence (SEC).

Patients and Methods

In this cross-sectional study, we surveyed 1203 high school students in an eastern region of China using the GI Scale, the SEC Scale, and the PTG Scale. We conducted correlation and mediation analyses using SPSS 23.0 and PROCESS software.

Results

The results indicated that GI was a significant positive predictor of PTG (β=0.219, p<0.001), and that the pathway between GI and PTG was partially mediated by SEC (Effect=0.074, 95% CI= [0.045,0.104]).

Conclusion

GI can have both direct and indirect effects on PTG, with the latter mediated by SEC. These findings hold important theoretical and practical implications for promoting PTG and enhancing mental health in the post COVID-19 era.