Sleep, resilience, and psychological distress in United States military Veterans

An empirical evaluation of The Resilience Shield model

Background

Resilience refers to the process through which individuals deal with the adversity they experience. Previous research has shown there are multiple factors that contribute to individuals’ resilience, leading to increasing interest in the development of multidimensional resilience models. Once such recently proposed model is The Resilience Shield, which clusters groups of protective factors into different shield layers. The stronger these layers, the better the protection against adversity (Pronk et al. in The Resilience Shield, Pan Macmillan Australia, 2021). While this model was based in part on existing literature, no empirical evaluation has occurred to date. The aim of this study was therefore to evaluate the model fit for each of the modifiable shield layers and the overall model, and to examine whether each of the constructs included contributes to observed resilience scores.

Methods

Participants completed a series of questionnaires via The Resilience Shield website assessing constructs relevant to each resilience shield layer. Data from 3337 participants was analysed using Structural Equation Modelling and regression analyses.

Results

The results showed acceptable fit of the measurement model for the Social, Mind, and Professional Layers, but poor fit for the Body Layer. There was also good fit for the overall model. In addition, all but one of the constructs included in The Resilience Shield survey explained independent variance in either dispositional resilience scores, or dispositional vulnerability scores.

Conclusion

These results broadly support the multidimensional structure proposed by The Resilience Shield model and suggest that (at least in the population in which it was tested) this may be an acceptable model to index individuals’ performance on a range of indicators that contribute to resilience.

Modifiable Resources and Resilience in Racially and Ethnically Diverse Older Women: Implications for Health Outcomes and Interventions

Introduction: Resilience—which we define as the “ability to bounce back from stress”—can foster successful aging among older, racially and ethnically diverse women. This study investigated the association between psychological resilience in the Women’s Health Initiative Extension Study (WHI-ES) and three constructs defined by Staudinger’s 2015 model of resilience and aging: (1) perceived stress, (2) non-psychological resources, and (3) psychological resources. We further examined whether the relationship between resilience and key resources differed by race/ethnicity. Methods: We conducted a secondary analysis on 77,395 women aged 62+ (4475 Black or African American; 69,448 non-Hispanic White; 1891 Hispanic/Latina; and 1581 Asian or Pacific Islanders) who enrolled in the WHI-ES, which was conducted in the United States. Participants completed a short version of the Brief Resilience Scale one-time in 2011. Guided by Staudinger’s model, we used linear regression analysis to examine the relationships between resilience and resources, adjusting for age, race/ethnicity, and stressful life events. To identify the most significant associations, we applied elastic net regularization to our linear regression models. Findings: On average, women who reported higher resilience were younger, had fewer stressful life events, and reported access to more resources. Black or African American women reported the highest resilience, followed by Hispanic/Latina, non-Hispanic White, and Asian or Pacific Islander women. The most important resilience-related resources were psychological, including control of beliefs, energy, personal growth, mild-to-no forgetfulness, and experiencing a sense of purpose. Race/ethnicity significantly modified the relationship between resilience and energy (overall interaction p = 0.0017). Conclusion: Increasing resilience among older women may require culturally informed stress reduction techniques and resource-building strategies, including empowerment to control the important things in life and exercises to boost energy levels.

A cluster analysis of physical activity profiles and resilience in intensive care nurses

Purpose

Limited evidence exists regarding a group of nurses' physical activity patterns and association with resilience. Less is known about the physical activity health paradox in nurses (the positive health effects of leisure time physical activity vs the negative health effects of occupational physical activity). This study aimed to explore the profiles of intensive care nurses' physical activity behaviours and associations with resilience, following a developed study-specific job demands–recovery framework.

Design/methodology/approach

A cross-sectional study was conducted with intensive care unit (ICU) nurses to explore their physical activity profiles and associations with resilience. The Connor-Davidson Resilience Scale 25 (CD-RISC 25) was used to assess resilience, and accelerometry was utilised to record participants' four-day activity (two workdays, two non-workdays). Hierarchical cluster analysis was employed to define groups of nurses by activity behaviours.

Findings

Participants (N = 93) were classified as low actives (n = 19), standers (n = 36), sitters (n = 31) and movers (n = 7). During two 12-h shifts, movers had the highest mean level of dynamic standing and the lowest mean level of sitting. During two non-workdays, movers had the highest mean level of walking as well as the lowest mean level of sitting and sleep time.

Originality/value

The uniqueness of this study was that it analysed ICU nurses' physical activity profiles and associations with resilience using identified clusters. However, the small number of participants limited this study's ability to determine significant relationships between resilience and the grouped physical activity profiles.

Resilience and CVD-protective Health Behaviors in Older Women: Examining Racial and Ethnic Differences in a Cross-Sectional Analysis of the Women's Health Initiative

Little is known about the relationship between self-reported psychological resilience (resilience) and health behaviors shown to reduce the risk of cardiovascular disease (CVD). This study examines the associations between resilience and CVD-related risk factors, such as diet, smoking, physical activity, sleep, and alcohol consumption among older American women from diverse backgrounds.

METHODS

A cross-sectional secondary analysis was conducted on 77,395 women (mean age 77 years, Black (N = 4475, 5.8%), non-Hispanic white (N = 69,448, 89.7%), Latina (N = 1891, 2.4%), and Asian or Pacific Islander (N = 1581, 2.0%)) enrolled in the Women's Health Initiative Extension Study II. Resilience was measured using an abbreviated version of the brief resilience scale. Multivariable logistic regression models were used to evaluate the association between resilience and health behaviors associated with risk for CVD, while adjusting for stressful life events and sociodemographic information. To test whether these associations varied among racial/ethnic groups, an interaction term was added to the fully adjusted models between resilience and race/ethnicity.

RESULTS

High levels of resilience were associated with better diet quality (top 2 quintiles of the Healthy Eating Index 2015) (OR = 1.22 (95% Confidence Interval (1.15-1.30)), adhering to recommended physical activity (≥ 150 min per week) (1.56 (1.47, 1.66)), sleeping the recommended hours per night (7-9) (1.36 (1.28-1.44)), and moderate alcohol intake (consuming alcoholic drink(s) 1-7 days per week) (1.28 (1.20-1.37)). The observed association between resilience and sleep is modified by race/ethnicity (p = 0.03).

CONCLUSION

Irrespective of race/ethnicity, high resilience was associated with CVD-protective health behaviors. This warrants further investigation into whether interventions aimed at improving resilience could increase the effectiveness of lifestyle interventions.

Self-Reported Sleep Need, Subjective Resilience, and Cognitive Performance Following Sleep Loss and Recovery Sleep

Objective

Individuals vary in response to sleep loss: some individuals are “vulnerable” and demonstrate cognitive decrements following insufficient sleep, while others are “resistant” and maintain baseline cognitive capability. Physiological markers (e.g., genetic polymorphisms) have been identified that can predict relative vulnerability. However, a quick, cost-effective, and feasible subjective predictor tool has not been developed. The objective of the present study was to determine whether two factors—“subjective sleep need” and “subjective resilience”—predict cognitive performance following sleep deprivation.

Methods

Twenty-seven healthy, sleep-satiated young adults participated. These individuals were screened for sleep disorders, comorbidities, and erratic sleep schedules. Prior to 40 hours of in-laboratory total sleep deprivation, participants were questioned on their subjective sleep need and completed a validated resilience scale. During and after sleep deprivation, participants completed a 5-minute psychomotor vigilance test every 2 hours.

Results

Both subjective resilience and subjective sleep need individually failed to predict performance during sleep loss. However, these two measures interacted to predict performance. Individuals with low resilience and low sleep need had poorer cognitive performance during sleep loss. However, in individuals with medium or high resilience, psychomotor vigilance test performance was not predicted by subjective sleep need. Higher resilience may be protective against sleep loss-related neurobehavioral impairments in the context of subjective sleep need.

Conclusions

Following sleep loss (and recovery sleep), trait resilient individuals may outperform those with lower resiliency on real-world tasks that require continuous attention. Future studies should determine whether the present findings generalize to other, operationally relevant tasks and additional cognitive domains.