Healing Through Loss: Exploring Nurses’ Post-Traumatic Growth After Patient Death

Article information

Psychiatry Investig. 2025;22(1):40-46
Publication date (electronic) : 2025 January 15
doi : https://doi.org/10.30773/pi.2024.0253
1Department of Psychiatry, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea
2Department of Psychiatry, GangNeung Asan Hospital, University of Ulsan College of Medicine, Gangneung, Republic of Korea
3Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
Correspondence: Junseok Ahn, MD Department of Psychiatry, Ulsan University Hospital, University of Ulsan College of Medicine, 877 Bangeojinsunhwando-ro, Dong-gu, Ulsan 44033, Republic of Korea Tel: +82-52-250-8997, Fax: +82-52-250-7078, E-mail: jsahn@uuh.ulsan.kr
Correspondence: C. Hyung Keun Park, MD, PhD Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Republic of Korea Tel: +82-2-3010-1657, E-mail: hkpark@gmail.com
Received 2024 August 6; Revised 2024 September 27; Accepted 2024 October 17.

Abstract

Objective

This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required.

Methods

An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited. We obtained information on the participants’ demographic and clinical characteristics. For symptoms rating, we used the following scales: the Post-traumatic Growth Inventory (PTGI), Stress and Anxiety to Viral Epidemic-9 (SAVE-9), Patient Health Questionnaire (PHQ-9), Pandemic Grief Scale (PGS), and Utrecht Grief Rumination Scale (UGRS), and Grief Support in Healthcare Scale (GSHCS). Pearson’s correlation coefficients, linear regression, and mediation analysis were employed.

Results

PTGI scores were significantly correlated with the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS scores (r=0.46, p<0.01). The linear regression analysis revealed the factors significantly associated with PTGI scores: SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS (β=0.34, p<0.001). The mediation analysis revealed that nurses’ stress and anxiety about COVID-19 and grief rumination had a direct impact on PTG, with grief support serving as a significant mediator.

Conclusion

PTG was promoted by increases in the medical staff’s anxiety and stress related to COVID-19, grief rumination, and grief support. For the medical staff’s experience of bereavement to result in meaningful personal and professional growth, family members, colleagues, and other associates should provide thoughtful support.

INTRODUCTION

When encountering challenging situations, individuals often reinterpret their lives, reassess their goals and priorities, find meaning in their relationships, and cultivate greater gratitude for life, thereby shifting their attitudes in a more positive direction. Tedeschi and Calhoun [1] termed the positive psychological changes that foster new perspectives on life following challenging events as post-traumatic growth (PTG). The process of PTG arises from individuals’ cognitive restructuring as they seek to attribute meaning to the traumatic experience and adapt to a new reality. They also argued that PTG does not stem directly from the trauma itself, but rather from the individual’s struggle to cope with it [1]. They identified five domains of PTG: improved relationships with others, the emergence of new possibilities, the development of personal strength, enhanced appreciation of life, and spiritual change [2].

Since the discovery and rapid spread of coronavirus disease-2019 (COVID-19), frontline healthcare workers (FLHCWs) have faced unprecedented challenges. They confronted the risks of virus exposure and infection, often witnessing their colleagues, loved ones, and patients succumb to the disease. Many FLHCWs experienced feelings of helplessness and overwhelming emotions regarding the conditions and treatment of the patients under their care. They endured numerous work-related challenges, including managing more severe cases than usual, being reassigned to unfamiliar departments without adequate training, navigating interpersonal conflicts, and facing shortages of necessary supplies and training. Additionally, they had to contend with the physical discomforts associated with personal protective equipment while continuously adapting to an uncertain environment marked by rapidly evolving viral variants, changing treatment protocols, and fluctuating policies [3]. Among the various challenges faced, FLHCWs particularly wished to avoid witnessing the deaths of patients in their care.

FLHCWs involved in treating patients with COVID-19, especially nurses, are particularly vulnerable to negative psychological outcomes such as trauma exposure, frustration, anger, and depression, potentially leading to post-traumatic stress disorder (PTSD). If these issues are not properly identified and treated, they can result in long-term difficulties. However, not all nurses exhibited maladaptive responses during the pandemic; indeed, work-related traumatic events can sometimes facilitate positive changes. A previous study found that nurses caring for patients with COVID-19 displayed higher scores on PTG metrics, consistent with research highlighting the coexistence of PTSD symptoms and PTG [4]. Therefore, this study aimed to identify the factors that may enhance PTG among nursing professionals who experienced the death of a patient during the COVID-19 pandemic. Moreover, it sought to explore how their grief reactions and the availability of grief support may influence their PTG.

METHODS

Participants and procedure

We conducted an online survey from November 16 to 18, 2023, targeting nurses at Ulsan University Hospital who had experienced patient deaths attributable to COVID-19 in the past year. We collected demographic information from participants, including age, sex, years of employment, shift patterns, religion, marital status, and any past psychiatric history. Additionally, participants responded to questions regarding their experiences with patient deaths, such as “Was the death related to COVID-19?” and “Was the death of the patients expected?” The e-survey was designed following the Checklist for Reporting Results of Internet E-Surveys guidelines. The research protocol was approved by the Institutional Review Board of Ulsan University Hospital (IRB No. 2023-10-022).

Measures

Post-traumatic Growth Inventory

The Post-traumatic Growth Inventory (PTGI) was developed to measure the extent of positive changes and growth that an individual may experience following a traumatic event [1]. It consists of 21 items divided into five subscales: relating to others (7 items), new possibilities (4 items), personal strength (3 items), spiritual change (2 items), and appreciation of life (5 items). Each item is rated on a 6-point Likert scale, from 0 (“I did not experience this change as a result of the crisis”) to 5 (“I experienced this change to a very great degree as a result of the crisis”). Total scores range from 0–105, with higher scores indicating greater positive change. The PTGI exhibits strong internal consistency and discriminant validity. In our study, we utilized the original Korean version of the scale [5], which yielded a Cronbach’s alpha of 0.94.

Stress and Anxiety to Viral Epidemic-9

The Stress and Anxiety to Viral Epidemic-9 (SAVE-9) scale is a self-report rating tool designed to assess work-related stress and anxiety specific to viral epidemics [6]. It includes nine items, each rated on a 5-point Likert scale (0: never; 4: always). Total scores range from 0 to 36, reflecting the level of work-related stress or viral anxiety. For our study, we employed the original Korean version, yielding a Cronbach’s alpha of 0.795.

Patient Health Questionnaire-9

The Patient Health Questionnaire-9 (PHQ-9) is a self-assessment tool for evaluating the severity of depressive symptoms [7], consisting of nine items rated on a 4-point Likert scale (0: not at all; 3: nearly every day). Scores range from 0 to 27, with higher scores indicating more severe depressive symptoms. Score interpretation is as follows: 5–9=mild depression, 10–14=moderate depression, 15–19=moderately severe depression, and ≥20=severe depression. We utilized the original Korean version in our study, and Cronbach’s alpha for our sample was 0.84 [8].

Pandemic Grief Scale

The Pandemic Grief Scale (PGS) is a self-reported tool that measures dysfunctional grief reactions related to COVID-19 losses [9]. It comprises five items scored on a 4-point Likert scale (0: not at all; 3: nearly every day). Total scores range from 0 to 15, with higher scores indicating greater levels of dysfunctional grief. In this study, we employed the validated Korean version of the scale [10], which yielded a Cronbach’s alpha of 0.866.

Utrecht Grief Rumination Scale

The Utrecht Grief Rumination Scale (UGRS) is a self-reported tool designed to measure grief-related rumination [11], consisting of 15 items rated on a 6-point Likert scale (1: never; 5: very often). Total scores range from 15 to 75, with higher scores indicating greater levels of grief rumination. We used the validated Korean version of the scale [12], and Cronbach’s alpha for our sample was 0.941.

Grief Support in Healthcare Scale

The Grief Support in Healthcare Scale (GSHCS) is a selfreported tool that evaluates the support available to healthcare workers (HCWs) in times of grief [13]. It is composed of 15 items rated on a 5-point Likert scale (1: strongly disagree; 5: strongly agree). In our study, we utilized a 10-item version of the GSHCS, excluding items 11–15, which are not applicable in South Korea [14], and the Cronbach’s alpha for our sample was 0.918.

Statistical analysis

We summarized participants’ demographic profiles and rating scale scores as means±standard deviations. First, we calculated Pearson’s correlation coefficients to examine the associations between PTG and years of employment, duration since experiencing patient deaths, and rating scale scores for psychological states. Second, we conducted linear regression analysis using the “enter” method to identify predictor variables for PTG among clinical variables and rating scale scores. Finally, we applied the bootstrap method with 2,000 resamples and employed mediation analysis to explore the mechanisms underlying the relationships between significant predictor variables identified in the linear regression analysis and PTG. A two-tailed p-value of 0.05 was considered statistically significant. We utilized Jeffreys’s Amazing Statistics Program (JASP) Version 0.17.3 (JASP Team, Amsterdam, Netherlands) for the statistical analyses.

RESULTS

A total of 211 nursing professionals participated in this study, all of whom had experienced the death of a patient (Table 1). The participants’ mean age was 41.1±10.2 years, with an average of 7.7±6.7 years of employment. The mean duration since they experienced a patient’s death was 5.2±5.0 months. Among the participants, 92.4% were female, 66.4% were single, 30.8% identified with a religion, and 88.2% worked in shifts. Regarding the patient deaths, 75.4% reported that these were not related to COVID-19, and 41.2% indicated that the deaths were unexpected.

Baseline demographic and clinical characteristics of the participants (N=211)

Pearson’s correlation analysis revealed a significant correlation between the PTGI score and the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS (r=0.46, p<0.01) scores (Table 2). Con-versely, the PTGI score did not correlate significantly with years of employment or the time elapsed since experiencing patient deaths. The SAVE-9 score was significantly correlated with the PHQ-9 (r=0.42, p<0.01), PGS (r=0.27, p<0.01), UGRS (r=0.28, p<0.01), and GSHCS scores (r=0.23, p<0.01).

Pearson correlation coefficients of research variables for all participants (N=211)

Linear regression analysis employing the “enter” method indicated that the PTGI score could be predicted by the SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS scores (β=0.34, p<0.001) (Table 3). Mediation analysis was employed to explore the mechanisms underlying the relationships between the significant predictor variables identified in the linear regression analysis and PTG. The results showed that nursing professionals’ responses to work-related COVID-19 stress and anxiety, as well as grief rumination, directly influenced their PTG, with grief support for HCWs serving as a mediating factor (Table 4 and Figure 1).

Linear regression analysis of the variables affecting post-traumatic growth among nursing professionals (N=211)

Mediation analysis of the pathways by which stress/anxiety due to COVID-19 and grief rumination affect post-traumatic growth

Figure 1.

The mediation model: the effect of COVID-19-related stress and anxiety and grief rumination (independent variables) on post-traumatic growth (outcome) is mediated by grief support (mediator).

DISCUSSION

This study investigated the factors influencing PTG in nurses who experienced patient deaths during the COVID-19 pandemic. We examined several variables, including work experience, time elapsed since the patient’s death, stress and anxiety due to COVID-19 (measured by the SAVE-9), depression (as indicated by the PHQ-9), dysfunctional grief responses (PGS), grief rumination (UGRS), and grief support (GSHCS). The linear regression analysis identified stress and anxiety due to COVID-19, grief rumination, and grief support as significant predictors of PTG. Notably, higher levels of stress and anxiety due to COVID-19 and grief rumination directly impacted PTG, with greater levels further promoting PTG. Additionally, grief support was found to mediate this relationship.

Previous studies suggest that PTG is influenced by several factors. First, the type of trauma can itself be significant. One study reported that PTG is higher in cases of illness compared to accidental events, as accidents are not repetitive and tend to be short-term, unlike illnesses [2,15]. Additionally, individuals who experience trauma firsthand receive more support and show higher levels of PTG compared to their families who experience indirect trauma [2]. Second, age can influence PTG. A meta-analysis reported that individuals younger than 60 years experience more PTG than those older than 60 years. This tendency may relate to younger individuals’ greater adaptability to changes in perspective and acceptance of life’s challenges [16]. This finding is consistent with the results of most previous studies [2,17]. Third, the time elapsed since the trauma can affect PTG. A meta-analysis found that PTG levels are more pronounced within the first 6 months post-trauma, although other research contradicts these findings; they indicate that deeper rumination, often occurring after 6 months, is possible, increasing the likelihood of PTG. Some studies report higher PTG levels 12 months post-trauma compared with 6 or 24 months later. These findings suggest an inverted U-shaped relationship between trauma duration and PTG; however, more longitudinal studies are needed to clarify this relationship [2]. Fourth, the severity of the trauma can influence PTG levels. According to McFarland and Alvaro [18], severe negative events lead to greater self-improvement perceptions than mild negative events. However, the positive correlation between trauma severity and PTG levels is still debated. Fifth, coping strategies for trauma can affect PTG. Coping strategies significantly promote growth by fostering a more positive perception of potentially threatening situations, influencing behavior, enhancing individual adaptive capacity, and helping individuals attribute meaning to experienced events. Religious coping strategies, in particular, have a strong correlation with PTG, where a sense of belonging may serve as a mediator between coping strategies and PTG [19]. Finally, social support is critical for fostering PTG. A meta-analysis of studies examining the relationship between social support and PTG found a moderate positive correlation (r=0.418) between them, reporting that the influence of social support on PTG is both immediate and long-lasting [20].

To the authors’ knowledge, this study is the first to examine the direct relationship between stress and anxiety due to COVID-19 on one hand with PTG on the other. The results indicate that higher stress and anxiety due to COVID-19 directly influences PTG, with higher levels further promoting PTG. However, previous research has not consistently found a positive correlation between trauma severity and PTG. In our study, the average SAVE-9 score of 17.5 (±9.3) fell below the clinical cut-off score of 22, which suggests a level of concern that may require clinical attention [6]. Further research is necessary to determine if the same results would be obtained with an average SAVE-9 score exceeding 22.

The bereavement experience after experiencing the loss of a close person incurs significant emotional distress. To enable growth through a traumatic event, an individual must reassess and reconstruct core beliefs about oneself, others, and the world. According to Tedeschi and Calhoun [21], the reconstruction process that occurs after trauma involves repeated reflection on the traumatic event, helping individuals understand the reasons behind their experiences and their broader impacts, ultimately promoting PTG.

Our results confirmed that higher levels of grief rumination promote PTG, a conclusion reached by most previous studies. One study indicated that the more individuals ruminate about the event shortly after the trauma, the greater the degree of PTG [22]. Taku et al. [23] categorized rumination into four types—intrusive rumination soon after the event, deliberate rumination shortly after the event, recent intrusive ru-mination, and recent deliberate rumination—to investigate their impact on PTG. They found that both intrusive and deliberate rumination have a positive correlation with PTG. However, intrusive rumination shortly after the event helps trigger deliberate cognitive processing, leading to PTG, whereas recent intrusive rumination does not show a significant relationship with PTG. Moreover, recent deliberate rumination shows the strongest positive correlation with PTG. In other words, the process of continuous reconstruction of individual perspectives, understanding of the world, and discovering meaning contribute to PTG. Several studies have also confirmed the positive correlation between deliberate rumination and PTG [24,25]. Ultimately, for those who have experienced bereavement, the process of grief rumination is necessary to achieve PTG. Rather than persisting in intrusive rumination, which can evoke negative thoughts and emotions over time, reconstructing one’s perspective and discovering meaning through deliberate rumination may be more helpful.

During the peak of the COVID-19 pandemic, HCWs were extremely busy caring for patients under unprecedented, uncertain circumstances. Hence, they often did not have sufficient time or capacity to engage in adequate meaningfully in grief rumination after experiencing patient deaths. However, in the current situation where the momentum of COVID-19 has subsided, it becomes crucial for HCWs experiencing patient deaths to utilize these traumatic events as opportunities for personal growth by engaging in sufficient grief rumination processes.

Further, the results confirmed that grief support mediates the relationship between COVID-19-related stress and anxiety, grief rumination, and PTG. This finding aligns with the conclusion of most studies investigating the relationship between social support and PTG. For example, Tureluren et al. [26] pointed out a significant correlation between social support from meaningful acquaintances, friends, and family and personal growth among young adults who had experienced bereavement. This is because social support provides opportunities for self-disclosure, helps manage negative emotions, and promotes finding meaning in traumatic events. A metaanalysis studying the relationship between social support and PTG showed a moderate positive correlation (r=0.418) between social support and PTG. Social support has both immediate and long-lasting effects on PTG. Initially, it provides a sense of belonging, and over time, it serves as a platform for narrative reconstruction, thereby facilitating the cognitive processing process [20]. In Tedeschi and Calhoun’s PTG model [21], individuals who have experienced a traumatic event reconstruct their perspectives and discover new meanings through disclosure and support, leading to PTG. In other words, the disclosure process mediates the relationship between cognitive engagement and PTG [19].

Richardson27 studied the spouses of firefighters who died in the line of duty during the 9/11 attacks in the US to examine the relationship between social support and PTG. The results demonstrated that both informal and formal types of social support enhanced PTG, with informal meetings among widows who shared similar experiences being the most commonly utilized form of social support. This suggests that grief support not only mediates the relationship between cognitive engagement and PTG but also has a positive effect by normalizing individual situations and emotions through shared trauma experiences. Hence, social support is essential for individuals who have experienced loss to achieve PTG, especially when it comes from individuals who have had similar experiences.

Usually, the family or friends of HCWs may not fully grasp the complexities of relationships between the HCWs and their patients. Therefore, efforts to show more interest in and initiate conversations about these relationships could positively influence the HCWs’ bereavement experiences after patient death. Additionally, at the hospital level, HCWs who have experienced patient death could be organized into groups to receive support from colleagues with similar experiences, freely share their experiences, and engage in a thorough grieving process, thus facilitating PTG. The hospital could support such groups by covering the costs or providing venues for their meetings.

This study has several limitations. First, the study participants were limited to nurses at a university hospital in Ulsan, South Korea, which may restrict the generalizability of the findings to other populations. Future research should analyze a larger and more diverse sample, including various regions and types of hospitals. Second, the study relied on self-reported measures, which could have introduced social-desirability bias in the responses of participants, potentially leading to information bias. However, the fact that the surveys were conducted anonymously likely mitigated this risk. Finally, the cross-sectional design of this study makes it challenging to infer causality between variables, only allowing for the identification of correlations. Future studies should consider longitudinal research designs to elucidate the causal relationships between PTG and other factors.

This study demonstrates that PTG is facilitated by increases in anxiety and stress among HCWs due to COVID-19, grief rumination, and grief support. Specifically, COVID-19-related stress and anxiety and grief rumination directly affect PTG, with grief support acting as a mediator in this relationship. To ensure that HCWs can leverage their bereavement experiences after patient death for meaningful personal and professional growth, it is vital for family members, colleagues, and other associates to provide more attentive support and care.

Notes

Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author upon reasonable request.

Conflicts of Interest

C. Hyung Keun Park, a contributing editor of the Psychiatry Investigation, was not involved in the editorial evaluation or decision to publish this article. All remaining authors have declared no conflicts of interest.

Author Contributions

Conceptualization: YongHan Kim, Seockhoon Chung, Junseok Ahn. Data curation: Seockhoon Chung, Junseok Ahn, C. Hyung Keun Park. Funding acquisition: Junseok Ahn. Investigation: YongHan Kim, Joon-Ho Ahn, Seockhoon Chung, Junseok Ahn, Jangho Park. Methodology: Young Rong Bang, Jin Yong Jun, Youjin Hong. Writing—original draft: YongHan Kim, Seockhoon Chung, Junseok Ahn. Writing—review & editing: all authors.

Funding Statement

This research was funded by the Choi Shin-Hai Neuropsychiatry Research Fund (2023) of the Korean Foundation of Neuropsychiatry Research.

Acknowledgements

We would like to thank the shift-working nursing professionals at Ulsan University Hospital for their efforts in caring for patients with serious conditions.

References

1. Tedeschi RG, Calhoun LG. The posttraumatic growth inventory: measuring the positive legacy of trauma. J Trauma Stress 1996;9:455–471.
2. Wu X, Kaminga AC, Dai W, Deng J, Wang Z, Pan X, et al. The prevalence of moderate-to-high posttraumatic growth: a systematic review and meta-analysis. J Affect Disord 2019;243:408–415.
3. Arnetz JE, Goetz CM, Arnetz BB, Arble E. Nurse reports of stressful situations during the COVID-19 pandemic: qualitative analysis of survey responses. Int J Environ Res Public Health 2020;17:8126.
4. Chen R, Sun C, Chen JJ, Jen HJ, Kang XL, Kao CC, et al. A large-scale survey on trauma, burnout, and posttraumatic growth among nurses during the COVID-19 pandemic. Int J Ment Health Nurs 2021;30:102–116.
5. Song S, Lee HS, Park JH, Kim KH. [Validity and reliability of the Korean version of the posttraumatic growth inventory]. Kor J Psychol Health 2009;14:193–214. Korean.
6. Chung S, Kim HJ, Ahn MH, Yeo S, Lee J, Kim K, et al. Development of the stress and anxiety to viral epidemics-9 (SAVE-9) scale for assessing work-related stress and anxiety in healthcare workers in response to viral epidemics. J Korean Med Sci 2021;36e319.
7. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001;16:606–613.
8. Park SJ, Choi HR, Choi JH, Kim K, Hong JP. [Reliability and validity of the Korean version of the patient health questionnaire-9 (PHQ-9)]. Anxiety Mood 2010;6:119–124. Korean.
9. Lee SA, Neimeyer RA. Pandemic grief scale: a screening tool for dysfunctional grief due to a COVID-19 loss. Death Stud 2022;46:14–24.
10. Kim JH, Park CHK, Ahmed O, Hong Y, Chung S, Park J, et al. Validation of the healthcare workers’ version of the pandemic grief scale among frontline nursing professionals during the COVID-19 pandemic in Korea. Front Psychiatry 2023;14:1121546.
11. Eisma MC, Stroebe MS, Schut HA, Van Den Bout J, Boelen PA, Stroebe W. Development and psychometric evaluation of the Utrecht grief rumination scale. J Psychopathol Behav Assess 2014;36:165–176.
12. Kim JH, Chung S. Validation of the Korean version of the Utrecht grief rumination scale and its relationship with COVID-related hypochondriasis among healthcare workers who witnessed patient deaths. Brain Behav 2023;13e3203.
13. Anderson KA, Ewen HH, Miles EA. The grief support in healthcare scale: development and testing. Nurs Res 2010;59:372–379.
14. Ahn J, Bang YR, Cho E, Ahmed O, Kim JH, Hong Y, et al. Validation of the grief support in healthcare scale among frontline nursing professionals working in COVID-19 inpatient wards in Korea. Front Psychiatry 2023;14:1097022.
15. Harms L, Talbot M. The aftermath of road trauma: survivors’ perceptions of trauma and growth. Health Soc Work 2007;32:129–137.
16. Sawyer A, Ayers S, Field AP. Posttraumatic growth and adjustment among individuals with cancer or HIV/AIDS: a meta-analysis. Clin Psychol Rev 2010;30:436–447.
17. Andysz A, Najder A, Merecz-Kot D, Wójcik A. Posttraumatic growth in women after breast cancer surgery-preliminary results from a study of Polish patients. Health Psychol Rep 2015;3:336–344.
18. McFarland C, Alvaro C. The impact of motivation on temporal comparisons: coping with traumatic events by perceiving personal growth. J Pers Soc Psychol 2000;79:327–343.
19. Henson C, Truchot D, Canevello A. What promotes post traumatic growth? A systematic review. Eur J Trauma Dissoc 2021;5:100195.
20. Ning J, Tang X, Shi H, Yao D, Zhao Z, Li J. Social support and posttraumatic growth: a meta-analysis. J Affect Disord 2023;320:117–132.
21. Tedeschi RG, Calhoun LG. Posttraumatic growth: conceptual foundations and empirical evidence. Psychol Inq 2004;15:1–18.
22. Calhoun LG, Cann A, Tedeschi RG, McMillan J. A correlational test of the relationship between posttraumatic growth, religion, and cognitive processing. J Trauma Stress 2000;13:521–527.
23. Taku K, Cann A, Tedeschi RG, Calhoun LG. Intrusive versus deliberate rumination in posttraumatic growth across US and Japanese samples. Anxiety Stress Coping 2009;22:129–136.
24. Hirooka K, Fukahori H, Taku K, Togari T, Ogawa A. Quality of death, rumination, and posttraumatic growth among bereaved family members of cancer patients in home palliative care. Psychooncology 2017;26:2168–2174.
25. Zhou X, Wu X. The relationship between rumination, posttraumatic stress disorder, and posttraumatic growth among Chinese adolescents after earthquake: a longitudinal study. J Affect Disord 2016;193:242–248.
26. Tureluren E, Claes L, Andriessen K. Personal growth in bereaved students: associations with support, grief, and distress. Death Stud 2023;47:307–314.
27. Richardson KM. The surviving sisters club: examining social support and posttraumatic growth among FDNY 9/11 widows. J Loss Trauma 2016;21:1–15.

Article information Continued

Figure 1.

The mediation model: the effect of COVID-19-related stress and anxiety and grief rumination (independent variables) on post-traumatic growth (outcome) is mediated by grief support (mediator).

Table 1.

Baseline demographic and clinical characteristics of the participants (N=211)

Variable Value
Female 195 (92.4)
Age (years) 41.1±10.2
Years of employment (years) 7.7±6.7
Duration from patient’s death (month) 5.2±5.0
Marital status
 Single 140 (66.4)
 Married, with kids 52 (24.6)
 Married, without kids 19 (9.0)
Religion (Yes) 65 (30.8)
Shift-working (Yes) 186 (88.2)
Psychiatric history
 Have you experienced or have you been treated for depression, anxiety, or insomnia? (Yes) 20 (9.5)
 Currently, do you think that you are depressed or anxious, or do you need help regulating your mood state? (Yes) 7 (3.3)
Death of patients
 Was the death related to COVID-19
  Yes 24 (11.4)
  No 159 (75.4)
  Uncertain 28 (13.3)
 Was the patient’s death expected?
  Yes 108 (51.2)
  Partially 16 (7.6)
  No 87 (41.2)
COVID-19-related
 Did you experience taking care of infected patients? (Yes) 181 (85.8)
 Did you experience being infected? (Yes) 180 (85.3)
 Did you experience being quarantined? (Yes) 180 (85.3)
 Did you get vaccinated? (Yes) 211 (100)
Symptoms rating
 Post-traumatic Growth Inventory 13.3±11.0 (0–641)
 Stress and Anxiety to Viral Epidemics-9 17.5±9.3 (0–33)
 Patient Health Questionnaire-9 2.7±3.5 (0–18)
 Pandemic Grief Scale 1.3±1.8 (0–8)
 Utrecht Grief Rumination Scale 22.3±7.6 (15–54)
 Grief Support in Health Care Scale 28.2±7.5 (10–44)

Data are presented as mean±standard deviation or number (%).

Table 2.

Pearson correlation coefficients of research variables for all participants (N=211)

Variables Years of employment Duration from patient’s death PTGI SAVE-9 PHQ-9 PGS UGRS
Duration from patient’s death -0.15*
PTGI 0.06 0.05
SAVE-9 -0.04 0.13 0.31**
PHQ-9 -0.04 0.21** 0.31** 0.42**
PGS 0.004 0.06 0.28** 0.27** 0.50**
UGRS 0.01 0.04 0.45** 0.28** 0.53** 0.59**
GSHCS 0.14* 0.08 0.46** 0.23** 0.30** 0.18** 0.31**
*

p<0.05;

**

p<0.01.

PTGI, Post-traumatic Growth Inventory; SAVE-9, Stress and Anxiety to Viral Epidemic-9; PHQ-9, Patient Health Questionnaire-9; PGS, Pandemic Grief Scale; UGRS, Utrecht Grief Rumination Scale; GSHCS, Grief Support in Healthcare Scale

Table 3.

Linear regression analysis of the variables affecting post-traumatic growth among nursing professionals (N=211)

Dependent variable Independent variables β p Adjusted R2 F, p
Post-traumatic growth Years of employment 0.01 0.979 0.32
Duration from patient’s death 0.02 0.862
SAVE-9 0.16 0.014 F=14.7
PHQ-9 -0.02 0.762 p<0.001
PGS 0.03 0.712
UGRS 0.29 <0.001
GSHCS 0.34 <0.001

SAVE-9, Stress and Anxiety to Viral Epidemic-9; PHQ-9, Patient Health Questionnaire-9; PGS, Pandemic Grief Scale; UGRS, Utrecht Grief Rumination Scale; GSHCS, Grief Support in Healthcare Scale

Table 4.

Mediation analysis of the pathways by which stress/anxiety due to COVID-19 and grief rumination affect post-traumatic growth

Effect Standardized estimator S.E. Z-value p 95% CI
Direct effect
 SAVE-9 → PTGI 0.15 0.06 2.71 0.007 0.04 to 0.26
 UGRS → PTGI 0.31 0.07 4.64 <0.001 0.17 to 0.44
Indirect effect
 SAVE-9 → GSHCS → PTGI 0.05 0.02 2.19 0.029 0.01 to 0.10
 UGRS → GSHCS → PTGI 0.09 0.03 3.58 <0.001 0.04 to 0.14
Path coefficients
 SAVE-9 → GSHCS 0.16 0.07 2.40 0.029 0.03 to 0.29
 GSHCS → PTGI 0.33 0.06 5.89 <0.001 0.22 to 0.44
 UGRS → GSHCS 0.27 0.07 4.13 <0.001 0.14 to 0.40
Total effect
 SAVE-9 → PTGI 0.20 0.06 3.65 <0.001 0.09 to 0.31
 UGRS → PTGI 0.39 0.07 5.87 <0.001 0.26 to 0.52

S.E., standard error; CI, confidence interval; SAVE-9, Stress and Anxiety to Viral Epidemic-9; PTGI, Post-traumatic Growth Inventory; UGRS, Utrecht Grief Rumination Scale; GSHCS, Grief Support in Healthcare Scale