Professional Quality of Life Factors and Relationships in Nursing and Psychiatric Nursing Students: An Exploratory Study

A Correlational Study of Burnout and Mitigating Psychological Factors in Undergraduate Nursing Students

BACKGROUND

Evidence indicates that many nursing students exhibit signs of burnout and consider leaving nursing during nursing school. However, there is scant literature on the extent of this problem or mitigating factors.

METHOD

Undergraduate nursing students (n = 129) participated in a correlational study examining patterns of burnout and Psychological Capital (PsyCap), a four-pronged construct that captures hope, efficacy, resilience, and optimism. Burnout and PsyCap were measured using the Maslach Burnout Survey (MBI-GS) and the PsyCap Questionnaire (PCQ-24). Burn-out prevalence was calculated. Correlations were assessed using MBI-GS subscales and the PCQ-24. Bivariate regressions were used to assess the effects of PsyCap on burnout dimensions.

RESULTS

High levels of exhaustion were identified, with 38.8% of the participants scoring in the overex-tended range, the first stage of burnout. Moderate PsyCap levels were found to be protective against burnout.

CONCLUSION

Strategies to increase PsyCap in nursing students may enhance well-being and reduce dropout. [J Nurs Educ. 2025;64(X):XXX-XXX.].

Prevalence and related factors of compassion fatigue among registered nurses and nursing students during the internship: a systematic review and meta-analysis

BACKGROUND

Compassion fatigue impacts nurses' well-being and work efficiency. Extensive research has explored its prevalence, but evidence regarding related factors is broadly categorized and lacks descriptive data. There's also a lack of systematic reviews on compassion fatigue among nursing students during internships.

OBJECTIVES

To synthesize evidence on the levels and factors of compassion fatigue among nurses and nursing students during internships.

METHODS

This systematic review is registered with PROSPERO (ID CRD42023444173). Literature searches were conducted in five databases (Cochrane Library, PubMed, EMBASE, CNKI, and WanFang) up to November 30, 2022, with updates planned until January 17, 2024, if necessary. Inclusion criteria covered studies reporting data on the prevalence and related factors of compassion fatigue or its dimensions, burnout and secondary traumatic stress, among registered nurses or nursing students during internships. Independent study selection, quality assessment, and data extraction were performed. The Agency for Healthcare Research and Quality tool was used for critical appraisal of study quality. Random-effects model analyses were conducted using Stata 17.0 to pool data on prevalence rates and mean scores of compassion fatigue. When comprehensive data on compassion fatigue were unavailable, its dimensions were analyzed for both prevalence and mean scores.

RESULTS

Our review included 196 studies (73,034 nurses and 4,551 nursing students). For nurses, pooled mean scores for burnout and secondary traumatic stress were 26.81 (95% CI 26.28 to 27.35) and 25.88 (95% CI 25.39 to 26.37), respectively. For nursing students during internships, pooled mean scores were 29.16 (95% CI 26.95 to 31.37) and 25.64 (95% CI 20.95 to 30.34), respectively. Subgroup analyses revealed that post-COVID-19 pandemic, nurses exhibited higher compassion fatigue, especially in ICU or emergency departments. Evidence from 93 studies suggested that nurses' burnout and secondary traumatic stress are both influenced by work environment, social support, job satisfaction, workload, and psychological capital (moderate to low-certainty evidence). For nursing students, psychological capital plays a significant role (moderate to low-certainty evidence).

CONCLUSIONS

Both registered nurses and nursing students experience moderate compassion fatigue. Work environment, social support, job satisfaction, workload, and psychological capital are key factors associated with burnout and secondary traumatic stress in registered nurses. For nursing students, psychological capital plays a similarly significant role. Given that this is the first systematic review to explore these factors among nursing students, further research is essential to deepen understanding and develop effective interventions.

Development and validation of a machine learning-based predictive model for compassion fatigue in Chinese nursing interns: a cross-sectional study utilizing latent profile analysis

BACKGROUND

Compassion fatigue is a significant issue in nursing, affecting both registered nurses and nursing students, potentially leading to burnout and reduced quality of care. During internships, compassion fatigue can shape nursing students' career trajectories and intent to stay in the profession. Identifying those at high risk is crucial for timely interventions, yet existing tools often fail to account for within-group variability, limiting their ability to accurately predict compassion fatigue risk.

OBJECTIVES

This study aimed to develop and validate a predictive model for detecting the risk of compassion fatigue among nursing students during their placement.

DESIGN

A cross-sectional study was used to capture the prevalence and associations of compassion fatigue among nursing interns, as it allows for timely assessment of key influencing factors without requiring long-term follow-up.

METHODS

A convenience sampling strategy was used to recruit 2256 nursing students from all ten public junior colleges in Hunan province in China between December 2021 and June 2022. Participants completed questionnaires assessing compassion fatigue, professional identity, self-efficacy, social support, psychological resilience, coping styles, and demographic characteristics. Predictors were selected based on prior literature and theoretical frameworks related to compassion fatigue in nursing. Latent profile analysis was used to classify compassion fatigue levels, and potential predictors were identified through univariate analysis and least absolute shrinkage and selection operator (LASSO) regression. Eight machine learning algorithms were applied to predict compassion fatigue, with performance assessed through cross-validation, calibration, and discrimination metrics. The best-performing model was further validated to ensure robustness.

RESULTS

A three-profile model best fits the data, identifying low (55.73%), moderate (32.17%), and severe (12.10%) profiles for compassion fatigue. Generally, an area under the curve (AUC) above 0.700 is acceptable, and above 0.800 indicates good predictive performance. The AUC values for the eight machine learning models ranged from 0.644 to 0.826 for the training set and 0.651 to 0.757 for the test set, indicating moderate to good discriminatory ability. The eXtreme Gradient Boosting (XGBoost) performed best, with AUC values of 0.840, 0.768, and 0.731 in the training, validation, and test sets, respectively. Shapley Additive Explanation (SHAP) analysis interpreted the model by quantifying the contribution of each variable to the prediction, revealing that psychological resilience, professional identity, and social support were the key contributors to the risk of compassion fatigue. A user-friendly, web-based prediction tool for calculating the risk of compassion fatigue was developed.

CONCLUSIONS

The XGBoosting classifier demonstrates excellent performance, and implementing the online tool can help nursing administrators manage compassion fatigue effectively. It holds practical value for nursing education and practice by supporting early detection and intervention. Future research should validate its use across settings, and longitudinal studies could assess its long-term impact.

Mediating effect of moral sensitivity and professional identity between moral courage and compassion fatigue among nursing interns: a cross-sectional study

BACKGROUND

Compassion fatigue in nursing interns contributes to career indecision and worsens the nursing shortage. While work environment and psychological factors are well-studied, the ethical dimension remains unexplored. Understanding these mechanisms, particularly the role of moral courage, is essential for designing interventions to combat compassion fatigue and address the workforce crisis. This study investigates the influence of moral courage on compassion fatigue among Chinese nursing interns, focusing on the mediating roles of moral sensitivity and professional identity.

METHODS

A quantitative, cross-sectional study was conducted in accordance with the STROBE guidelines. We used the convenience sampling method to recruit 467 nursing interns from four public junior colleges in Hunan Province, China in February, 2024. Data were collected using Compassion Fatigue Short Scale, Moral Courage Scale, Revised Moral Sensitivity Questionnaire, and Professional Identity Scale. Data analyses were conducted using SPSS 22.0 and Amos 21.0.

RESULTS

The modified model exhibited a good fit (χ2/df = 3.437, AGFI = 0.928, IFI = 0.984, TLI = 0.976, CFI = 0.984, NFI = 0.977, RMSEA = 0.072). Moral sensitivity positively influenced both moral courage and professional identity, while professional identity negatively impacted compassion fatigue. Importantly, the effect of moral courage on compassion fatigue was entirely mediated by moral sensitivity and professional identity (β = -0.114, P = 0.001).

CONCLUSION

This study suggests that moral courage in nursing interns mitigates compassion fatigue through the combined mediating effects of moral sensitivity and professional identity. Ethics education programs fostering moral courage, moral sensitivity, and professional values in nursing students could be crucial in alleviating compassion fatigue.

Prevalence of Compassion Fatigue and Its Association with Professional Identity in Junior College Nursing Interns: A Cross-Sectional Study

Background: The issue of compassion fatigue among clinical nurses has received considerable attention, particularly during the COVID-19 pandemic. Yet, the current status of compassion fatigue among junior college nursing interns remains unclear. Additionally, professional identity can modulate the impact of compassion fatigue or burnout on psychological well-being; however, whether professional identity still works in this group is also unclear. This study aimed to reveal the current status of compassion fatigue among nursing interns in junior colleges and also investigate the association between compassion fatigue and professional identity. Methods: This cross-sectional survey evaluated the levels of participants' compassion fatigue (The Compassion Fatigue Short Scale) and professional identity (Professional Identity Scale) in 2256 nursing interns. Results: The mean score of compassion fatigue was 44.99, and 19.5% of the participants scored above The Compassion Fatigue Short Scale median scores for compassion fatigue. A moderate negative correlation was detected between compassion fatigue and professional identity. Conclusions: The level of compassion fatigue among nursing interns is low but nearly one in five nursing students is at risk of compassion fatigue. More attention should be paid to nursing interns with a high risk of compassion fatigue. Future studies are warranted to explore which pathways could mediate the relationship between professional identify and comparison fatigue.

Learning and quality of life in undergraduate nursing students: An exploratory study in Chile during the COVID-19 pandemic

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a global pandemic that has modified all social and, especially, learning instances. The purpose of this study was to determine the perception of final-year nursing students at a university in southern Chile regarding the impact of the pandemic on their learning, and consequently on their quality of life, in the context of the COVID-19 pandemic.

MATERIALS AND METHODS

This is a qualitative study. The research was conducted on 14 nursing students who were selected from a university located in the province of Talca, Maule Region, Chile. Data collection was done through semi-structured interviews conducted during July and September 2021. The data were analyzed using the inductive logic of theoretical categorization; this process was assisted by the Nvivo 10 program.

RESULTS

Two mega categories were generated that accounted for the nursing students' experience during the COVID-19 pandemic: objective factors category and subjective factors category. Six subcategories were derived from these two categories: free time, social relationships, learning from practice, physical exercise, eating habits, and emotional state.

CONCLUSION

The research findings indicate that the students, in addition to feeling upset about not being able to do the internship, also feel that they have not been able to acquire all the knowledge necessary for their training and professional development, since the virtual classes fail to deliver adequate learning as they lack the practical component that is so important in their careers. This has repercussions in the physical, social, and psychological areas, affecting their quality of life.