Factors Influencing Posttraumatic Growth among Nurses in COVID-19 Isolation Wards in Tertiary Hospitals

Article information

J Korean Acad Fundam Nurs. 2025;32(2):233-242
Publication date (electronic) : 2025 May 31
doi : https://doi.org/10.7739/jkafn.2025.32.2.233
1)Nurse, Department of Nursing, Jeonbuk National University Hospital, Jeonju, Korea
2)Professor, College of Nursing ‧ Research Institute of Nursing Science, Jeonbuk National University, Jeonju, Korea
Corresponding author: Kim, Hyun Kyung College of Nursing, Jeonbuk National University 567 Baekje-daero, Deokjin-gu, Jeonju, 54896, Korea Tel: +82-63-270-3121, Fax: +82-63-270-3127, E-mail: kimhk@jbnu.ac.kr
*This article is a condensed form of the first author's master's thesis from Jeonbuk National University. Year of 2022.
Received 2025 January 24; Revised 2025 May 9; Accepted 2025 May 19.

Abstract

Purpose

This study investigated the factors influencing posttraumatic growth (PTG) among nurses who worked in COVID-19 isolation wards in tertiary hospitals in South Korea.

Method

A cross-sectional descriptive correlation research design was used. In total, 190 nurses who had worked with COVID-19-infected patients participated in the study. Their demographic characteristics, self-disclosure, resilience, social support, and PTG were examined using a structured online questionnaire administered from March 16 to 25, 2022. Data were analyzed using SPSS/WIN 27.0.

Results

The mean scores for self-disclosure, resilience, social support, and PTG were 42.79 (range: 12∼60), 60.92 (range: 0∼100), 46.98 (range: 12∼60), and 45.66 (range: 0∼80), respectively. Self-disclosure (β=.18, p=.003) and resilience (β=.65, p<.001) significantly influenced PTG, explaining 55% of the total variance in this variable.

Conclusion

This study highlights the need to systematically develop and implement effective intervention programs to strengthen nurses' self-disclosure and resilience.

INTRODUCTION

Coronavirus disease 2019 (COVID-19) emerged in China in 2019 and was declared a global pandemic by the World Health Organization in March 2020, marking the longest-running infectious disease epidemic since the outbreak of severe acute respiratory syndrome in 2002 [1]. Healthcare workers (HCWs) may experience severe stress in response to the dangerous situations they face from pathogen exposure and new infectious diseases [2]. Notably, HCWs, especially nurses, are particularly susceptible to developing posttraumatic stress disorder (PTSD) following infectious disease pandemics, as they experience the stress of caring for patients and a high risk of exposure to infection [3]. When working in isolation wards, nurses encounter physical challenges, such as exhaustion and discomfort from personal protective equipment, and psychological challenges, including witnessing the depression experienced by isolated patients [4,5]. The psychological burden of such experiences can be profound, and research suggests that PTSD is highly prevalent among HCWs following infectious disease outbreaks [3].

However, focusing solely on the negative aspects of trauma may lead to an incomplete understanding of trauma responses [6]. Posttraumatic growth (PTG) refers to the positive changes achieved after coping with a traumatic event, transcending trauma recovery to represent inner growth within an individual [7,8]. This growth can enable individuals to adapt and develop resilience beyond their previous capacity [7]. Furthermore, PTG allows nurses who have experienced trauma to demonstrate their proficiency by openly discussing their emotions with colleagues and effectively responding to challenges [9]. Notably, PTG does not occur automatically; rather, it emerges through a complex and painful process of psychological struggle, meaning-making, and adaptation [6,7]. To enhance PTG among nurses caring for COVID-19 patients, it is crucial to identify and actively manage the influencing factors. Specifically, this study aims to explore the relationships between self-disclosure, resilience, social support, and PTG, as these variables are hypothesized to play critical roles in facilitating positive psychological changes following traumatic experiences. By examining these relationships, we can better understand how nurses’ experiences of trauma during the pandemic contribute to their PTG, and how these factors can be leveraged to support their psychological well-being and professional development. This understanding will inform strategies for promoting PTG and mitigating the negative impacts of trauma on nurses.

Self-disclosure alleviates emotional pain by allowing individuals to share their experiences through writing, conversations, and prayer [10]. It can promote personal growth by reducing emotional distress and providing comfort while helping individuals reinterpret themselves, others, and their circumstances from a fresh perspective [11]. Thus, self-disclosure can aid personal adaptation and PTG by fostering deeper emotional processing, enhancing self-awareness, and facilitating meaning-making in response to traumatic experiences [11].

Psychological resilience enables individuals to adapt to adversity and facilitates growth when faced with challenges [12]. Nurses exhibiting high resilience effectively tackle challenges by leveraging internal and external resources and display enhanced capabilities compared to their less resilient counterparts [13]. Resilience also contributes to increased PTG by enhancing emotional regulation, fostering a sense of self-control, and promoting adaptive coping strategies. Individuals with high resilience are more likely to reframe traumatic experiences positively, experience personal transformation, and develop a greater sense of purpose in their professional and personal lives [9].

Social support encompasses the positive resources individuals receive from their relationships with others [14]. It helps manage painful emotions resulting from trauma [15]. A hospital nurse's support network may include supervisors, peers, family members, and close friends, along with feelings of inclusion in meetings and engagement in various activities with others. Social support significantly influences nurses’ ability to effectively cope with stress, which may stem from recurring traumatic incidents in clinical environments [16].

Studies have indicated that self-disclosure encourages PTG among intensive care [16] and general [17] nurses. A recent study on nurses who cared for COVID-19 patients similarly reported that higher levels of self-disclosure were associated with higher PTG levels [18]. Resilience was found to positively affect PTG in nurses at hospitals in Wuhan, China, which was the initial COVID-19 epicenter [19], and at infectious disease hospitals in South Korea [20]. Previous studies on nurses who cared for COVID-19 patients reported that social support affected PTG [21-23].

Nurses working on the front line against infectious diseases require strategies for overcoming work-related trauma. Although several studies [3,7,18,20] have recently investigated PTG and its influencing factors in relation to COVID-19, research specifically addressing nurses working in isolation wards during the pandemic is minimal. The influence of self-disclosure, resilience, and social support on the PTG of nurses who have cared for COVID-19 patients in isolation wards needs to be investigated.

This study aimed to examine the influence of self-disclosure, resilience, and social support on PTG among nurses caring for COVID-19 patients in isolation wards. This study provides directions for developing programs and policies aimed at promoting PTG among nurses working on the front lines in the case of future outbreaks of novel infectious diseases.

METHODS

1. Study Design

This study used a cross-sectional design.

2. Participants

Participants included nurses who had cared for or were currently caring for COVID-19 patients in the isolation wards of tertiary hospitals in South Korea. The selection criteria included working at a tertiary hospital, having worked or currently working in a COVID-19 isolation ward, and consenting to participate in the study. Nurses at the managerial level or those who had temporarily treated COVID-19 patients for surgery, procedures, or examinations were excluded.

The sample size was determined using G*Power 3.1.9.4, with 14 predictor variables designated for regression analysis, a significance level of .05, a power (1-β) of .90, and a medium effect size of .15. The effect size used in this study was determined based on a previous study examining PTG among healthcare workers, which reported a medium effect size of 0.15 [16,17]. In total, 162 participants were eligible for inclusion.

Regarding the dropout rate, while previous studies involving similar populations and variables reported dropout rates ranging from 10∼15%, a slightly higher rate of 20% was adopted herein. This decision was made considering the unique circumstances of the COVID-19 pandemic, where the high workload and psychological burden among nurses could have increased the likelihood of incomplete responses. Additionally, ensuring a sufficient final sample size was crucial for maintaining the statistical power and representativeness of the data. Therefore, a 20% dropout rate was set as a precautionary measure to account for potential nonresponses and missing data. Considering a dropout rate of 20%, online questionnaires were distributed to 203 nurses.

3. Measurements

1) Self-disclosure

Self-disclosure was assessed using the Distress Disclosure Index devised by Kahn and Hessling [10] and translated into Korean and modified by Song and Lee [11]. The instrument comprises 12 items that assess whether individuals who have experienced a painful event disclose their emotions and thoughts to others. Each item is assessed on a 5-point Likert scale ranging from 1 (“ strongly disagree”) to 5 (“ strongly agree”). Higher scores indicate a greater tendency to disclose psychological discomfort to others. The tool's Cronbach's ⍺ value was .93 for the original version [10], .93 for the revised version [11], and .92 for this study.

2) Resilience

Resilience was evaluated using the Korean version of the Connor-Davidson Resilience Scale [24]. The tool comprises 25 items divided into the following categories: personal strength, capacity to withstand negative effects such as stress, self-efficacy, capacity to adapt positively to change, emotional and cognitive regulation, and optimism. Each item is evaluated on a 5-point Likert scale ranging from 0 (“ not at all”) to 4 (“ very much”). Higher scores indicate greater resilience. The Cronbach's ⍺ for the tool was .92 for the original version [12], .93 for the Korean version [24], and .92 for this study.

3) Social support

Social support was assessed using the Multidimensional Scale of Perceived Social Support developed by Zimet et al. [25] and translated by Shin and Lee [26]. The tool comprises 12 items across three subscales (family, friends, and significant others). Each item is evaluated on a 5-point Likert scale ranging from 1 (“ completely disagree”) to 5(“ strongly agree”). Higher scores indicate that participants receive greater social support. The scale's Cronbach's ⍺ value was .95 for the original version [25], .89 for the Korean version [26], and .92 for this study.

4) Posttraumatic growth

We measured PTG using the Posttraumatic Growth Inventory developed by Tedeschi and Calhoun [8] and translated into Korean and modified by Song et al. [27]. The tool comprises 16 items: 6 items related to changes in self-perception, 5 items concerning relating to others, 3 items pertaining to new possibilities, and 2 items regarding spiritual change. Each item is evaluated on a 6-point Likert scale ranging from 1 (“ did not experience”) to 6 (“ experienced to a very great degree”). A higher total score suggests greater PTG. The Cronbach's ⍺ for the instrument was .92 for the original version [8], .92 for the Korean version [27], and .88 for this study.

5) Sociodemographic and job-related characteristics

Items for assessing participants’ sociodemographic factors-gender, age, education, marital status, and religion- were included based on prior studies. Job-related characteristics included hospital location, length of total clinical career, time spent caring for COVID-19 patients in an isolation ward, time currently working in an isolation ward, and time elapsed since working in an isolation ward.

4. Data Collection

Data were collected from March 16 to 25, 2022. The recruitment guide for study participation was disseminated through an online nursing community exclusively accessible to licensed nurses, ensuring that only eligible participants could access the survey link and participate. Additionally, upon securing approval from the head of the nursing department at a tertiary hospital in J province, we posted recruitment notices for the study on the board of the COVID-19 isolation wards. Those willing to participate in the study did so by scanning the QR code. To enhance the representativeness and reliability of the sample, the eligibility criteria were clearly stated in the recruitment materials, and duplicate submissions were restricted to prevent multiple responses from the same participant. Prior to participation, the study's purpose and methodology, as well as assurances of confidentiality and anonymity, were thoroughly explained. Of the 203 questionnaires collected, 190, excluding 13 that responded that they worked in an area without a tertiary hospital, were used for statistical analysis.

5. Data Analysis

The collected data were analyzed using SPSS/WIN 27.0. Descriptive statistics were used to analyze the demographic characteristics, self-disclosure, resilience, social support, and PTG. An independent t-test, one-way analysis of variance, and Scheffé's post hoc test were conducted to compare differences in PTG according to demographic characteristics. Pearson's correlation was used to investigate the relationships between self-disclosure, resilience, social support, and PTG. A multiple linear regression was conducted to determine the factors influencing PTG. Linearity was assessed by examining scatterplots between independent and dependent variables. Data normality was assessed using the Kolmogorov-Smirnov test, and homoscedasticity was evaluated using the Breusch-Pagan test. Multicollinearity between independent variables was determined by assessing the tolerance and variance inflation factors. Additionally, the autocorrelation of the dependent variable was examined using the Durbin-Watson test.

6. Ethical Considerations

After obtaining approval from the institutional review board (IRB no. JBNU 2022-02-008-001) of the authors’ affiliated institution, data were gathered through an online survey. The survey included a consent form on the first page, detailing the study's purpose, how personal information would be gathered, confidentiality assurances, and the option for participants to withdraw freely. Therefore, only those who voluntarily consented were enrolled. Moreover, responses were automatically processed upon completion of the questionnaire using a computerized system to ensure participant anonymity.

RESULTS

1. General Characteristics and Differences in PTG

The mean age of participants was 27.92±4.29 years, and most were women (94.7%). Most participants held a bachelor's degree (97.4%), and 87.9% were unmarried. About 41.1% of the participants reported having a religion. Regarding workplace location, ‘ City’ accounted for the largest proportion (40.5%). Participants had a total clinical career length of approximately 4.20 years, with an average of 9.35 months spent caring for COVID-19 patients in isolation wards. Currently, 84.2% of participants were working in COVID-19 isolation wards. For those not currently working in an isolation ward, the average elapsed period from cessation of work there was 3.89 months.

PTG was significantly different in relation to gender, marital status, religion, and length of total clinical career. Higher levels of PTG were observed among women than men, married than unmarried individuals, and those with a religion than those without. Participants with five or more years of total clinical career had higher scores than those who had been engaged in nursing for less than five years (Table 1).

General Characteristics and Differences in Posttraumatic Growth (N=190)

2. Levels of Self-disclosure, Resilience, Social Support, and PTG

Participants’ mean self-disclosure score was 42.79±8.40 out of 60. The mean resilience score was 60.92±13.56 out of 100. The mean social support score was 46.98±7.75 out of 60. Finally, the mean score for PTG was 45.66±10.87 out of 80 (Table 2).

Levels of Self-Disclosure, Resilience, Social Support, and Posttraumatic Growth (N=190)

3. Correlations between self-disclosure, resilience, social support, and PTG

Self-disclosure was significantly correlated with resilience (r=.28, p<.001), social support (r=.55, p<.001), and PTG (r=.38, p<.001). Resilience was significantly correlated with social support (r=.48, p<.001) and PTG (r=.71, p<.001). Furthermore, social support was significantly correlated with PTG (r=.43, p<.001) (Table 3).

Correlations Between Self-Disclosure, Resilience, Social Support, and Posttraumatic Growth (N=190)

4. Factors Influencing PTG

We conducted a multiple regression analysis, employing the enter method to identify PTG predictors. The regression model encompassed variables that had significant relationships with PTG in the univariate analysis, including gender, marital status, religion, length of total clinical career, self-disclosure, resilience, and social support. Gender, marital status, religion, and length of total clinical career were recoded into dummy variables. Scat-terplots showed linearity between independent and dependent variables. The autocorrelation of the errors, as determined by the Durbin-Watson test, was measured as 1.90, which is close to 2, indicating the absence of autocorrelation. The tolerance values ranged from 0.55 to 0.92, all exceeding 0.10, and the variance inflation factor values ranged from 1.00∼1.82, all below 10, indicating no multi-collinearity among the independent variables.

Multiple regression analysis indicated that resilience (B=0.52, p<.001) and self-disclosure (B=.23, p=.003) significantly explained participants’ PTG. The model accounted for approximately 55.0% of the variance in PTG (F=33.49, p<.001). The standardized residuals satisfied the assumption of normality according to the Kolmogorov-Smirnov test (Z=0.61, p=.846) and the assumption of equal variance based on the Breusch-Pagan test (x2=6.63, p =.469), confirming a good fit of the regression model (Table 4).

Factors Influencing Posttraumatic Growth (N=190)

DISCUSSION

We examined the influence of self-disclosure, resilience, and social support on the PTG of nurses working in COVID-19 isolation wards in tertiary hospitals in South Korea while investigating the main influencing factors.

In this study, the overall mean PTG score of nurses working in COVID-19 isolation wards in tertiary hospitals was 45.66 out of 80 (2.85 out of 5 per item). This finding is similar to those of previous studies [7,23] that have used the same measurement tools. For example, PTG scores ranging from 46.54 to 47.73 have been reported in studies on nurses caring for COVID-19 patients in nationally designated infectious disease hospitals. Our score was higher than the PTG level observed in general nurses at three hospitals of varying levels, including tertiary, general, and specialized hospitals, which was 40.13 [28]. These results suggest that nurses working in COVID-19 isolation wards may have unique experiences that contribute to higher PTG compared to those in general hospitals. During the pandemic, they faced prolonged exposure to high-risk situations, direct involvement in critical patient care, and the challenge of adapting to rapidly evolving protocols, which could foster a stronger sense of professional achievement, personal growth, and resilience, thus contributing to higher PTG.

However, the PTG score in this study was lower than those observed among firefighters [29] and police officers [30]. This difference may be attributed to the distinct nature of trauma exposure in each profession. Firefighters and police officers often face critical incidents involving immediate physical danger and high-stakes decision-making in emergency situations. Conversely, nurses in COVID-19 isolation wards experienced prolonged exposure to patient suffering, repeated losses, and ongoing ethical dilemmas related to life-sustaining treatments. The cumulative effect of these stressors, combined with physical exhaustion and workplace constraints, likely contributed to the differences in PTG scores between these professions.

Nurses caring for COVID-19 patients often felt pride in their contribution to national infection control efforts and willingly supported the operation of isolation wards [4,31]. However, despite feeling satisfied upon witnessing patients’ recovery under challenging circumstances, they experienced difficulties that limited their ability to achieve PTG. These challenges stemmed from various factors, including the absence of clear guidelines on infectious disease response, discomfort from wearing personal protective equipment, sudden workplace changes, additional non-nursing duties, and physical strain [4,31].

To facilitate nurses’ personal development following traumatic events such as the COVID-19 pandemic, it is imperative to establish structured PTG programs in collaboration with national institutions, such as the National Trauma Center, to effectively support healthcare workers in responding to infectious disease situations [23]. Additionally, strengthening infection control policies, securing sufficient personnel, and providing financial incentives for nurses working in infectious disease wards are necessary strategies for enhancing their psychological well-being and professional sustainability [31]. Furthermore, struc tured resilience training programs have been empirically validated to promote PTG among nurses and should be actively implemented [32].

We identified resilience as the most influential factor for PTG. Resilience is a psychosocial trait that enables individuals to adapt and grow when faced with adversity [12]. People with low resilience experience more negative emotions (e.g., excessive stress, helplessness, and low self-control) and use negative coping methods (e.g., avoidance) [9]. Conversely, resilient individuals have greater self-control, overcome stress, and experience more positive emotions [9].

The average resilience score among nurses who had worked in COVID-19 isolation wards in tertiary hospitals in South Korea was 60.92 out of 100, equivalent to a score of 2.44 out of 4 per item. This aligns closely with the resilience scores reported in previous studies using the same assessment tools. For instance, similar scores of 57.54 out of 100 [20] were observed among nurses caring for COVID-19 patients in infectious disease hospitals. Another study on nurses in negative pressure isolation wards at a dedicated COVID-19 hospital reported a resilience score of 63.55 out of 100 [33].

These findings are consistent with previous results demonstrating that resilience significantly influences PTG among nurses caring for COVID-19 patients in infectious disease hospitals [20]. Resilience can be strengthened through programs that emphasize composure, patience, self-trust, meaning-making, and positive emotions and by implementing emotional coaching programs [9]. While structured programs have been validated as effective interventions for enhancing resilience, additional strategies should be considered. Research suggests that fostering a supportive work environment, encouraging peer discussion, and integrating resilience-building elements into daily nursing practice can significantly contribute to PTG [9,16]. Leadership support and workplace policies promoting psychological well-being also play crucial roles in sustaining long-term resilience [31]. These diverse approaches, in conjunction with structured programs, can provide comprehensive support for nurses facing traumatic experiences.

Another factor influencing PTG was self-disclosure. Herein, the mean self-disclosure score was 42.79 out of 60. This score was higher than the 38.82 previously reported among nurses who cared for COVID-19 patients in infectious disease hospitals [18] and similar to the 43.80 reported among intensive care nurses in general hospitals [16]. The formal and structured nature of the organizational culture in tertiary hospitals may make it difficult for nurses to share their traumatic experiences and emotions openly. Addressing this issue requires fostering an empathetic and understanding organizational culture that encourages open communication and emotional expression. Self-disclosure significantly influenced PTG, which was similar to the results of another study [16] targeting intensive care nurses at a general hospital that found that obtaining positive feedback or advice from others through self-disclosure positively affected PTG. Nurses working in COVID-19 isolation wards commonly experience infection risk, anxiety about transmission, difficulty in patient care, and stress [5,34]. Encouraging self-disclosure about these experiences could help reduce negative emotions, enable nurses to confront their feelings, and foster more objective perspectives of their challenges, thereby promoting PTG.

To support self-disclosure among nurses, targeted programs and strategies are necessary. These could include self-disclosure training and mindfulness programs [35] designed to create a safe environment for emotional sharing. Organizational interventions aimed at normalizing emotional expression and fostering open dialogue within healthcare teams may enhance the positive effects of self-disclosure.

Social support was also examined in relation to PTG. The mean social support score in our sample was 46.98 out of 60 (3.92 out of 5 per item). This was slightly lower than the score of 50.81 measured using the same tool in a previous study [33] of COVID-19 isolation ward nurses. The score for support from significant others, a subcomponent of social support, was the highest, consistent with that of a previous study [33]. Support from supervisors, colleagues, and close acquaintances, coupled with a sense of belonging, had important effects on nurses experiencing repeated traumatic events in clinical settings [16].

Although social support did not significantly influence PTG in this study, this finding has significant implications. It contrasts with studies conducted among general hospital [17] and intensive care [16] nurses, in which social support was found to positively affect PTG. However, it aligns with the results of research involving nurses caring for COVID-19 patients in hospitals dedicated to infectious diseases [7]. These results suggest that the unique circumstances of the pandemic, including the fear of infection transmission and strict infection control measures, led many nurses to limit interactions with their families, reside separately, and experience heightened social isolation [5,34]. Consequently, mental and material support from their usual social networks may have been significantly reduced. To address this issue, fostering peer and organizational support can play a critical role during infectious disease outbreaks. Developing strategies to strengthen professional support systems and foster a sense of belonging within healthcare teams may help mitigate the effects of social isolation.

However, it is also important to consider that social support may not always have a direct effect on PTG but may instead play an indirect role through intermediary psychological mechanisms. Previous research has indicated that resilience is a critical determinant influencing PTG among nurses caring for COVID-19 patients, suggesting that psychological adaptability may serve as a pivotal pathway for PTG [9]. This perspective raises the possibility that, rather than directly facilitating PTG, social support may operate as a resource that enhances resilience, subsequently fostering growth. To gain a more comprehensive understanding of this relationship, future studies should explore whether social support functions as a mediator or moderator in the association between resilience and PTG. Investigating these mechanisms could provide deeper insights into the underlying psychological processes driving PTG among nurses in high-stress environments.

Despite its strengths, our study has some limitations. First, data were collected through an online survey, making it impossible to directly verify participants’ personal information. Second, we used convenience sampling, which might have led to selection bias. Nevertheless, this study is meaningful, as it includes nurses nationwide rather than from specific regions or medical institutions. Our findings offer insights for developing and implementing programs that can improve PTG by identifying the factors affecting nurses’ PTG.

CONCLUSION

This cross-sectional study empirically confirms that self-disclosure and resilience influence the PTG of nurses working with patients with COVID-19. Incorporating resilience-building and self-disclosure facilitation into workplace training may help improve nurses’ long-term psychological well-being in high-stress environments. Based on our results, the following recommendations are pro-posed. First, a systematic program should be developed to enhance the self-disclosure and resilience of nurses caring for patients with emerging novel infections. Second, a lon-gitudinal study of nurses who participated in COVID-19 patient care should be conducted to identify changes in PTG over time.

Notes

CONFLICTS OF INTEREST

The authors declared no conflict of interest.

AUTHORSHIP

Study conception and design acquisition - Im YS and Kim HK; Data collection - Im YS; Data analysis & Interpretation - Im YS and Kim HK; Drafting & Revision of the manuscript - Im YS and Kim HK.

DATA AVAILABILITY

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Article information Continued

Table 1.

General Characteristics and Differences in Posttraumatic Growth (N=190)

Variables Characteristics Categories n (%) or M± SD Posttraumatic growth
M± SD t or F p
Sociodemographic characteristics Gender Men 10 (5.3) 34.00±11.04 -3.60 <.001
Women 180 (94.7) 46.31±10.51
Age (year) <30 139 (73.2) 44.89±10.96 -1.64 .103
≥30 51 (26.8) 47.78±10.42
27.92±4.29
Education College 5 (2.6) 41.60±11.28 -0.85 .380
≥ University 185 (97.4) 45.78±10.87
Marital status Unmarried 167 (87.9) 44.90±10.99 -3.31 .002
Married 23 (12.1) 51.22±8.19
Religion Yes 78 (41.1) 47.83±11.17 2.32 .021
No 112 (58.9) 44.15±10.44
Job-related characteristics Hospital location Capital (Seoul) 49 (25.8) 44.14±9.45 0.66 .519
Metropolitan city 64 (33.7) 46.36±11.10
City 77 (40.5) 46.05±11.54
Length of total clinical career (year) <5 133 (70.0) 44.56±10.47 -2.17 .032
≥5 57 (30.0) 48.25±11.42
4.20±3.81
Time spent caring for COVID-19 patients in an isolation ward (year) <1 116 (61.1) 45.60±10.77 0.44 .642
1∼<2 55 (28.9) 46.45±9.61
≥2 19 (10.0) 43.74±14.72
9.35±6.98
Currently working in an isolation ward Yes 160 (84.2) 45.82±11.02 0.46 .650
No 30 (15.8) 44.83±10.17
Time elapsed since working in an isolation ward (months) (n=30) <4 18 (60.0) 44.94±10.70 0.07 .943
≥4 12 (40.0) 44.67±9.78
3.89±3.58

M=mean; SD=standard deviation.

Table 2.

Levels of Self-Disclosure, Resilience, Social Support, and Posttraumatic Growth (N=190)

Variables M± SD Skewness Kurtosis
Self-disclosure 42.79±8.40 -0.66 -0.13
Resilience 60.92±13.56 -0.48 0.54
Social support 46.98±7.75 -0.91 1.34
Posttraumatic growth 45.66±10.87 -0.18 0.15

M=mean; SD=standard deviation.

Table 3.

Correlations Between Self-Disclosure, Resilience, Social Support, and Posttraumatic Growth (N=190)

Variables Self-disclosure Resilience Social support
r (p) r (p) r (p)
Resilience .28 (<.001)
Social support .55 (<.001) .48 (<.001)
Posttraumatic growth .38 (<.001) .71 (<.001) .43 (<.001)

Table 4.

Factors Influencing Posttraumatic Growth (N=190)

Variables B SE β t p
Gender 4.35 2.50 .09 1.74 .083
Marital status 1.20 1.90 .04 0.63 .530
Religion 2.15 1.13 .10 1.91 .058
Length of total clinical career (year) -2.12 1.40 -.09 -1.52 .130
Self-disclosure 0.23 0.08 .18 3.01 .003
Resilience 0.52 0.05 .65 10.74 <.001
Social support 0.01 0.09 .01 0.11 .910
R2=.56, Adjusted R2=.55, F=33.49, p<.001

SE=standard error;

Dummy variable: gender (women), marital status (married), religion (yes), total clinical career (≥5 years).