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Open Access 01.12.2025 | Research

Patterns of vicarious trauma and vicarious posttraumatic growth among oncology nurses: a latent profile analysis

verfasst von: Dandan Chen, Yi Zhou, Jinghan Xu, Yunxian Zhou

Erschienen in: BMC Nursing | Ausgabe 1/2025

Abstract

Background

Vicarious trauma (VT) and vicarious posttraumatic growth (VPTG) are potential psychological responses of oncology nurses to indirect exposure to traumatic events in long-term clinical practice. However, limited research has examined the concurrent patterns of VT and VPTG. This study aimed to identify the coexisting patterns of VT and VPTG among oncology nurses and explore the specific predictors of these subgroups.

Methods

The Medics’ Vicarious Trauma Scale and Posttraumatic Growth Inventory were utilized to assess self-reported VT and VPTG among 401 Chinese oncology nurses across multiple hospitals in Zhejiang Province, China. Latent profile analysis was conducted to explore potential patterns of VT and VPTG, and multinomial logistic regression was applied to investigate factors influencing these profiles.

Results

The latent profile analysis results indicated that a three-class profile best fit the data, characterized by the following patterns: mild VT - high VPTG (45.9%), mid VT - mid VPTG (30.2%), and mild VT - mild VPTG (23.9%). Variations in VT and VPTG patterns were associated with age, fertility status, job satisfaction, and social support.

Conclusion

These findings enhance understanding of the coexisting patterns of VT and VPTG and provide valuable insights for clinical administrators to implement tailored managerial and supportive interventions for oncology nurses.
Hinweise
Dandan Chen and Yi Zhou contributed equally to this work.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Introduction

Cancer is a major life-threatening disease worldwide. A recent report indicated an increase in the incidence of malignant tumors and a substantial disease burden in China, with 4.82 million new cases reported in 2022 [1]. Nursing plays a critical role in oncology care, encompassing not only clinical expertise but also the emotional support of patients and their families. Due to the complex and prolonged nature of cancer treatment, oncology nurses often develop close and enduring relationships with patients [2]. Throughout these extended interactions, the pain, negative emotions and hardships faced by patients can significantly affect the emotional health and cognitive functioning of oncology nurses [3]. In addition, oncology nurses might encounter moral distress due to institutional restrictions on the extent of care they are allowed to offer [4]. These stressors may result in trauma akin to that experienced by patients, leading to vicarious trauma (VT). Moreover, oncology nurses may experience greater trauma compared to other healthcare professionals [5].
VT refers to psychological trauma that alters an individual’s cognitive schema, often occurring in clinical settings or via exposure to social media [4]. Empathy is a key factor influencing the development of VT [4]. VT can manifest as short-term emotional changes or a long-term shift in one’s belief system, potentially leading to an identity crisis or contemplation of giving up clinical work [4, 6, 7]. Empirical studies suggest that oncology nurses frequently experience mild to moderate VT [8, 9]. While the intensity of VT is typically lower than that of direct trauma exposure, its detrimental effects are often overlooked. Over time, VT can evolve into anxiety, depression, and post-traumatic stress disorder, negatively impacting the quality of life of oncology nurses [10, 11].
Despite the adverse consequences of VT, nurses persistently adapt to it. One study found that when nurses derive new meaning from their VT experiences and use them as catalysts for personal and professional growth, it can lead to positive changes in their interpersonal relationships, self-perception and attitudes toward life [4]. The positive psychological transformation following indirect exposure to trauma, as opposed to direct exposure, is termed vicarious posttraumatic growth (VPTG) [12]. Previous quantitative surveys investigating VPTG among nurses in various departments (such as obstetrics, neonatal intensive care and emergency) using the PTG Inventory (PTGI) found that the levels of VPTG tends to fall within a moderate range (54.09 to 66.11) [13, 14, 15]. Vishnevsky et al. conducted a qualitative study that highlighted the personal growth and wisdom gained by oncology nurses through patient care, providing empirical support for VPTG in this group [16]. However, there is limited quantitative research specifically on VPTG among oncology nurses.
Existing research emphasizes the complexity of the VT-VPTG relationship. According to the affective–cognitive processing model proposed by Joseph et al. [17], a certain degree of posttraumatic stress symptoms, such as intrusive thoughts and avoidance behaviors, is essential for fostering posttraumatic psychological growth. Similarly, Tedeschi et al. propose that the psychological stress induced by traumatic events challenges an individual’s core beliefs, initiating cognitive processes that facilitate the development of PTG [18]. These perspectives suggest that VT may not only precede VPTG but also coexist with it. Moreover, both theories highlight that excessive levels of post-traumatic stress can disrupt cognitive processing, impeding the development of posttraumatic psychological growth. Empirical research among healthcare workers supports this complexity, showing positive correlations [19, 20, 21], no associations [15], and inverted-U curvilinear relationships between VT and VPTG [22]. These mixed findings underscore the need for further investigation.
Most previous studies have primarily used variable-centered approaches (e.g., regression analyses, path models), which assume a homogeneous distribution of psychological states [19, 20, 21]. However, research suggests that psychological states are actually heterogeneous [23], meaning these methods may fail to capture individual differences. In contrast, latent profile analysis (LPA) is a person-centered approach that classifies individuals into distinct latent groups based on similar patterns of observed variables [23], allowing for a more nuanced understanding of these differences in vicarious psychological changes.
To date, only two LPA studies have examined vicarious psychological changes among healthcare workers [24, 25]. One study identified six post-traumatic stress symptom profiles among healthcare staff, such as “no symptom,” “low symptom,” “moderate symptom,” and “high symptom” [25]. Another study on Japanese public health nurses classified individuals into four groups based on empathy and secondary traumatic stress, such as “the highest secondary traumatic stress and personal distress,” “moderate secondary traumatic stress,” and “the lowest secondary traumatic stress and personal distress” [24]. To the best of our knowledge, no studies have employed LPA to examine the combined patterns of VT and VPTG among Chinese oncology nurses, limiting a comprehensive understanding of their complex relationship. To fill this gap, we aim to apply LPA to identify patterns of VT and VPTG in this population.
In addition to identifying these patterns, it is essential to investigate the specific predictors of these unique profiles, to inform targeted psychological interventions. Previous studies have explored factors influencing VT and VPTG separately. Regarding demographic information and individual resources, being female [26], having a personal trauma history [26], having low work ability [9], having lower or higher years of experience [9], being unmarried [9], and having low social support [27], were shown as risk factors for VT. For higher VPTG, older age [12], being male [12, 26], being married [28], having longer years of experience [28], and having high work ability [27] were found to play an important role. However, the role of these factors in the specific patterns of VT and VPTG among oncology nurses remains unclear. Understanding these predictors will help tailor interventions aimed at improving the mental health and well-being of oncology nurses.
Accordingly, this study aimed to (1) apply LPA to identify heterogeneous profiles of VT and VPTG among oncology nurses and (2) examine the socio-demographic factors associated with these profiles.

Method

Participants and procedure

A cross-sectional online survey was conducted in the oncology departments of multiple hospitals in Zhejiang Province, China, between October 2023 and November 2023. Nurses with a minimum of six months experience of working with cancer patients were eligible to participate. To ensure that the observed VT and VPTG arise from professional exposure rather than personal trauma, participants who were currently experiencing or had not yet recovered from specific traumatic events were excluded. These events, based on the Trauma History Screen scale and informed by prior literature and nurses’ occupational characteristics, included: personal or family member suffering from a significant illness (physical or psychological) or a major accident (such as a car accident or fire), tense family relationships (such as separation or divorce), the death of a family member, experiencing a serious medical error, and encountering severe workplace violence (including physical assaults like beatings or psychological violence like verbal abuse) [29, 30, 31].
The questionnaires were distributed to oncology nurses by personnels of the nursing department through WeChat (a popular social media in China) and were implemented online via Questionnaire Star (an online survey platform in China). Participation in this survey was anonymous and voluntary, which may help reduce social desirability bias. However, the self-reported nature of the online survey introduces potential self-selection bias and response biases (such as recall bias), which cannot be entirely ruled out. Electronic informed consent was obtained from all participants. Each IP address was restricted to submitting only one response. A total of 445 questionnaires were distributed. To ensure data quality, those completed in less than 116 s (averaging less than 2 s per item across 58 items) or with the same answers for all items were excluded [32, 33]. This resulted in 401 valid questionnaires, yielding a valid response rate of 89.1%. The study was approved by the Ethics Committee of the Zhejiang Chinese Medical University (20230922-6).
The sample size for this study was calculated using G*Power software. Based on a medium effect size of 0.15, α of 0.05, and a power of 0.95 (using G*Power version 3.1), the minimum sample size was 172 nurses. Accounting for a 20% inefficiency rate, the required sample size was 207. Furthermore, Nylund-Gibson et al. suggest that a minimum sample size of 300 cases is necessary for LPA to prevent difficulties in detecting smaller potential profiles [34]. A total of 401 participants met the sample size requirement for this study.

Measures

Demographic characteristics

A self-designed questionnaire was used to collect socio-demographic information including age, gender, years of experience, job title, level of education, marital status, fertility status, social support, and job satisfaction.

Medics’ vicarious trauma scale

The scale was developed by a team led by psychologist Xiao Zhou at Zhejiang University, which includes 29 items across three dimensions: negative emotional experiences, avoidance and somatization responses, and negative cognition and vigilance [35]. Responses are rated on a 5-point scale, ranging from 1 (strongly disagree) to 5 (strongly agree), with higher scores indicating more severe VT [35]. The theoretical score range for VT is 29 to 145, and scores can be divided into three categories using equal intervals: low (29–67), mid (68–106), and high (107–145). This scale was used in a survey of 572 medical staff from 18 provinces and municipalities in China by Zhang et al., who found an overall Cronbach’s α coefficient of 0.97, with dimension-specific coefficients of 0.90, 0.97, and 0.93, respectively [35]. The test-retest reliability was 0.8. Confirmatory factor analysis further supported the scale’s good construct validity [35]. The scale also demonstrated satisfactory criterion validity, with coefficients of 0.658 and 0.663 [35]. In the current study, the overall Cronbach’s α coefficient for the scale was 0.957, with dimension-specific coefficients ranging from 0.898 to 0.923.

VPTG inventory

The Chinese - Posttraumatic Growth Inventory (C-PTGI), originally developed by Tedeschi and Calhoun [36], and translated and revised into Chinese by Wang et al. [37], was employed. In line with prior research [26, 38], the C-PTGI was adapted to reflect VPTG, to ask participants whether changes had occurred as a result of their clinical work with cancer patients. The questionnaire comprises 20 items across five dimensions (relating to others; new possibilities; personal strength; spiritual change; appreciation of life). Respondents answer each item on a 6-point Likert scale ranging from 0 (I did not experience this) to 5 (I experienced this change to a very great degree). Total scores range from 0 to 100, with scores between 60 and 65 indicating moderate growth, and scores of 66 or above reflecting high-level growth [37]. The overall Cronbach’s α coefficient is 0.965, with dimension-specific coefficients ranging from 0.789 to 0.823 in this study.

Statistical methods

LPA was conducted to identify subgroups of nurses based on their levels of VT and VPTG. When determining the most appropriate number of latent classes, several factors merit consideration, including theoretical considerations and the statistical fit of potential solutions [39]. The optimal number of profiles was determined by various statistical indicators [40]: (1) Akaike’s information criteria (AIC) (2), Bayesian information criteria (BIC) (3), sample size adjusted Bayesian information criteria (ABIC) (4), Lo-Mendell-Rubin likelihood ratio test (LMRLRT), and (5) bootstrap likelihood ratio test (BLRT). For AIC, BIC, and ABIC, lower values signify a better fit of the model. A significant p-value in the LMRLRT or BLRT suggests that a model with k profiles fits the data better than one with k-1 profiles. Additionally, entropy is used as an indicator of classification accuracy, with values closer to 1 indicating higher accuracy.
Simulation studies have demonstrated that BIC, ABIC, and BLRT are the most informative indicators for determining the correct number of classes [41, 42, 43, 44]. Conversely, AIC and LMRLRT are less dependable, and may result in the selection of an incorrect number of classes [42, 44, 45]. The sample size is also a critical factor in model selection, with each profile needing to account for at least 5% of the sample [46]. Finally, the substantive meaningfulness of the profiles should also be considered.
After identifying the latent profiles, comprehensive descriptions of each profile were provided. The chi-squared test or Fisher’s exact test was used to compare frequencies and percentages for categorical variables. Subsequently, multinomial logistic regression was then used to examine the influence of demographic variables on the profiles.
Latent profile analysis was conducted using Mplus version 7.0 and multinomial logistic regressions were conducted with IBM SPSS Statistics version 20.0. A two tailed P < 0.05 was considered to be statistically significant in all analyses.

Results

Participant characteristics

The survey was completed by 401 oncology nurses, with the majority (98.5%) being female (n = 395). Most participants held an education level of bachelor degree (90.3%, n = 362), were aged between 30 and 39 years (41.6%, n = 167) and had intermediate job titles (47.6%, n = 191). Participants with 1 to 5 years and over 15 years of experience represented 24.7% (n = 99) and 28.9% (n = 116), respectively. Nearly two-thirds of respondents (68.8%, n = 276) reported being married, and 63.3% (n = 254) had experienced childbirth. Additionally, approximately half of the nurses reported being satisfied with their current work (50.9%, n = 204) and having moderate social support (47.1%, n = 189). Table 1 indicates that VT scores ranged from 29 to 145, with a mean of 66.32 ± 22.50, while VPTG scores ranged from 0 to 100, with a mean of 68.67 ± 18.88.
Table 1
Scores of VT and VPTG for oncology nurses
Variable
Theoretical score range
Observed score range
Score (Mean ± SD)
VT
29–145
29–145
66.32 ± 22.50
VPTG
0–100
0–100
68.67 ± 18.88
Abbreviation: VT, Vicarious Trauma; VPTG, Vicarious Posttraumatic Growth; SD, Standard Deviation

Latent profile analysis

The fit indices for the five LPA models are displayed in Table 2. According to established methods, BIC, ABIC, and BLRT are the most informative indicators for determining the appropriate number of latent classes. In this study, all BLRT p-values were statistically significant. Furthermore, model fit improved as the number of profiles increased, as evidenced by decreasing AIC and BIC values. Based on these criteria alone, the five-profile solution would appear optimal. However, the smallest class in the five-profile model accounted for less than 5% of the sample.
Table 2
Fit indices for latent profile analysis models
 
AIC
BIC
ABIC
Entropy
LMRLRT
BLRT
Size of smallest class
One-class
61750.758
62142.166
61831.205
    
Two-class
57480.262
58071.368
57601.752
0.972
0.0007
<0.001
32.2%
Three-class
55281.917
56072.722
55444.452
0.972
0.1616
<0.001
23.9%
Four-class
53741.582
54732.085
53945.161
0.965
0.4258
<0.001
17.5%
Five-class
52627.612
53817.813
52872.235
0.975
0.7531
<0.001
3.5%
Abbreviations: AIC, Akaike Information Criterion; BIC, Bayesian Information Criterion; ABIC, Adjusted BIC; LMR, Lo-Mendell-Rubin; BLRT, Bootstrap Likelihood Ratio Test
When compared with the two-class solution, both the three-class and four-class solutions showed lower AIC and BIC values, indicating better fit. All profiles from the three-class model were retained in the four-class model. Nevertheless, the four-class model demonstrated over-extraction, as the newly introduced class was essentially a subdivision of an existing class from the three-class model. This subdivision showed similar item-response mean values for the VT and VPTG indicators as the original class, blurring category distinctions and reducing the model’s ability to capture meaningful differences. Additionally, the new profile lacked a unique theoretical interpretation and did not offer new insights. The entropy value of the three-class model was also higher than that of the four-class model, indicating a clearer classification structure. Consequently, the three-class model was selected for interpretation and further analysis due to its greater efficiency and lower complexity compared to the four-class model.
The three-class patterns were characterized by comparing their means: mild VT and mild VPTG, middle VT and middle VPTG, as well as mild VT and high VPTG. These were named the mild VT - mild VPTG group (n = 96, 23.9%), the mid VT - mid VPTG group (n = 121, 30.2%), and the mild VT - high VPTG group (n = 184, 45.9%), respectively (Figs. 1 and 2).

Predictor of latent profile membership

The chi-squared test or Fisher’s exact test revealed significant differences between the three profiles regarding fertility status (χ2 = 7.397, p = 0.025), job satisfaction (χ2 = 42.021, p < 0.001), and social support (p < 0.001) (Table 3).
Table 3
Descriptive statistics in the full sample and each latent profile
Variables
Total sample
(n = 401)
Mild VT - mild VPTG groupa
(n = 96)
Mid VT - mid VPTG groupb
(n = 121)
Mild VT - high VPTG groupc
(n = 184)
χ2
P
Age (years)
    
7.727
0.102
 20–29
123 (30.7%)
39 (40.6%)
30 (24.8%)
54 (29.4%)
  
 30–39
167 (41.6%)
35 (36.5%)
58 (47.9%)
74 (40.2%)
  
 >40
111 (27.7%)
22 (22.9%)
33 (27.3%)
56 (30.4%)
  
Gender
     
0.430
 Male
6 (1.5%)
0 (0.00%)
3 (2.5%)
3 (1.6%)
  
 Female
395 (98.5%)
96 (100%)
118 (97.5%)
181 (98.4%)
  
Years of experience
    
11.247
0.081
 1–5
99 (24.7%)
33 (34.4%)
26 (21.4%)
40 (21.7%)
  
 6–10
99 (24.7%)
20 (20.8%)
29 (24.0%)
50 (27.2%)
  
 11–15
87 (21.7%)
21 (21.9%)
33 (27.3%)
33 (17.9%)
  
 >15
116 (28.9%)
22 (22.9%)
33 (27.3%)
61 (33.2%)
  
Job title
     
0.061
 Junior
178 (44.4%)
47 (49.0%)
53 (43.8%)
78 (42.3%)
  
 Intermediate
191 (47.6%)
47 (49.0%)
60 (49.6%)
84 (45.7%)
  
 Associate or chief
32 (8.0%)
2 (2.0%)
8 (6.6%)
22 (12.0%)
  
Level of education
     
0.262
 Associate degree
28 (7.0%)
10 (10.4%)
9 (7.4%)
9 (4.9%)
  
 Bachelor degree
362 (90.3%)
83 (86.5%)
107 (88.4%)
172 (93.5%)
  
 Master degree
11 (2.7%)
3 (3.1%)
5 (4.1%)
3 (1.6%)
  
Marital status
    
3.271
0.195
 Unmarried
125 (31.2%)
37 (38.5%)
36 (29.8%)
52 (28.3%)
  
 Married
276 (68.8%)
59 (61.5%)
85 (70.2%)
132 (71.7%)
  
Fertility status
    
7.397
0.025
 Not given birth
147 (36.7%)
46 (47.9%)
43 (35.5%)
58 (31.5%)
  
 Given birth
254 (63.3%)
50 (52.1%)
78 (64.5%)
126 (68.5%)
  
Job satisfaction
    
42.021
< 0.001
 Dissatisfied
40 (10.0%)
12 (12.5%)
18 (14.9%)
10 (5.4%)
  
 Moderately satisfied
157 (39.1%)
44 (45.8%)
64 (52.9%)
49 (26.7%)
  
 Satisfied
204 (50.9%)
40 (41.7%)
39 (32.2%)
125 (67.9%)
  
Social support
     
< 0.001
 Low
14 (3.5%)
6 (6.2%)
4 (3.3%)
4 (2.2%)
  
 Medium
198 (49.4%)
47 (49.0%)
84 (69.4%)
67 (36.4%)
  
 High
189 (47.1%)
43 (44.8%)
33 (27.3%)
113 (61.4%)
  
Note: VT = vicarious trauma; VPTG = vicarious posttraumatic growth.
a Mild VT – mild VPTG: A profile characterized by low levels of both VT and VPTG.
b Mid VT – mid VPTG: A profile where moderate levels of VT coexist with moderate levels of VPTG.
c Mild VT – high VPTG: A profile where individuals experience low levels of VT but demonstrate significant VPTG
The results of multiple logistic regressions showed that age, job satisfaction, fertility status, and social support significantly predicted the three-class patterns (Fig. 3). Using the Mild VT - mild VPTG group as the reference, the Mid VT - mid VPTG group was less likely to report high social support (OR = 0.412, 95%CI: 0.220–0.770). Conversely, being in the Mild VT - High VPTG group was more likely among individuals who had given birth (OR = 3.660, 95% CI: 1.113–12.036) or reported job satisfaction (OR = 3.811, 95% CI: 1.434–10.126). When the Mild VT - high VPTG group served as the reference, individuals over 40 (OR = 8.087, 95%CI: 1.267–51.620) and those aged 30–39 (OR = 4.527, 95%CI: 1.098–18.662) were more likely to belong to the Mid VT - mid VPTG group compared to those aged 20–29. Moreover, the Mild VT - high VPTG group had a lower likelihood of oncology nurses reporting satisfaction with their job (OR = 0.196, 95%CI: 0.079–0.491) or high social support (OR = 0.328, 95%CI: 0.187–0.575).

Discussion

To our knowledge, this study is the first to explore the heterogeneous patterns of VT and VPTG levels among oncology nurses. The findings revealed three heterogeneous patterns labeled as mild VT - mild VPTG group (n = 96, 23.9%), mid VT - mid VPTG group (n = 121, 30.2%) and mild VT - high VPTG group (n = 184, 45.9%). Additionally, the study found that age, fertility status, job satisfaction, and social support played significant roles in differentiating these patterns of VT and VPTG.
Currently, there are no other similar LPA studies investigating the categories of VT combined with VPTG. Given the similarities between VT and post-traumatic stress disorder (PTSD), as well as between VPTG and PTG, the relationship between VT and VPTG may have certain comparability to the relationship between PTSD and PTG, exhibiting various patterns. A study involving 612 breast cancer patients also identified three patterns: mild PTSD - mild PTG, high PTSD - high PTG, and mild PTSD - high PTG [47]. Similarly, Zhou et al. found similar patterns in children and adolescents exposed to an earthquake [48]. This suggests that the patterns of response in post-traumatic groups are similar across different types of traumatic events. Notably, the mid VT - mid VPTG group in our study differs from high PTSD - high PTG in other studies due to lower intensity of VT responses compared to direct exposure trauma, and numerous studies showed that VT and VPTG in nurses were generally low to moderate [8, 9, 12]. In both the mild VT - mild VPTG group and mid VT - mid VPTG group, VT and VPTG severity were reflective of each other and positively associated. The reasons behind these patterns are multifaceted. Numerous studies suggest that the PTG model is applicable to explain the development of VPTG, and only when VT reaches a level that challenges existing cognitive schemas does it stimulate VPTG [12, 49]. Hence, low VT levels are insufficient to trigger VPTG, whereas moderate VT stress prompts cognitive re-evaluations and adaptive changes, and this level of VT is not severe enough to result in high levels of VPTG [18]. Besides, for the mild VT - mild VPTG group, oncology nurses may have a low perception of traumatic situations, possibly due to their tendency towards a detached perspective when offering care, characterized by low emotional involvement and empathy [50]. Furthermore, the mild VT - mild VPTG group reflects a state similar to the “resilience” as defined by O’Leary and Ickovics [51], which refers to individuals returning to their baseline psychological state after facing challenges. Since this is a cross-sectional study, it only captures a snapshot of the mild VT - mild VPTG pattern at a single point in time. Longitudinal studies would be essential to better understand the dynamic processes involved in resilience.
In this study, the majority of participants belonged to the mild VT - high VPTG group. Due to the lack of similar LPA studies examining VT-VPTG patterns, comparisons with existing literature are limited. The relative predominance of this group suggests a negative association between VT and VPTG among many participants. Previous regression-based studies to explore the VT-VPTG relationship have yielded different findings [38, 52]. For instance, research among substance abuse treatment providers in the United States and emergency room physicians and nurses in Israel found an overall positive correlation between VT and VPTG [38, 52]. These differences may be culturally driven, as Chinese culture prioritizes collectivism and interpersonal harmony, whereas Western societies emphasize individualism. Consequently, Chinese nurses are more likely to seek social support and maintain harmonious relationships, which helps alleviate distress and promote growth, rather than relying solely on individual coping mechanisms [53]. Additionally, this highlights an encouraging phenomenon that most Chinese oncology nurses not only returned to their baseline psychological state but also experienced progress beyond their previous conditions. Despite working in challenging environments, with heavy patient loads and limited resources, Chinese oncology nurses seem to exhibit an internal drive for psychological growth, which helps them cope with the intense pressures and emotional demands of their work. However, it is important to recognize that the cognitive adaptation model suggests that PTG and VPTG, when used as a coping mechanism, might be influenced by positive illusions [54]. This raises the possibility that the observed growth could be illusory and temporary, emphasizing the need for longitudinal studies to further explore the causal relationship and dynamic changes between VT and VPTG in different cultural contexts.
This study also examined the impact of demographic variables on the three-class patterns. Compared to the mild VT - high VPTG group, individuals aged 40 and older, and those between 30 and 39, were more likely to be classified in the mid VT - mid VPTG group. Although older nurses have extensive clinical experience, they also experience accumulated work-related stress and burnout risk. As age increases, cognitive processing of traumatic events may diminish, making it harder to adopt new or creative solutions for psychological growth [55]. Clinical managers and hospital policymakers should prioritize the mental health of older nurses, encouraging them to participate in cognitive behavioral therapy and stress management training (such as meditation and progressive muscle relaxation) to reduce negative psychological reactions.
The effect of gender on VT and VPTG patterns was not analyzed in this study due to the extremely low proportion of male oncology nurses (1.5%). This limitation reflects the demographic reality of the nursing profession, where the workforce is predominantly female. However, previous research on VT or VPTG has highlighted significant but inconsistent gender differences [53, 56, 57]. These differences are partly attributed to variations in coping strategies and rumination tendencies [58]. Women are more likely to adopt emotion-focused coping strategies, while men tend to favor problem-focused coping strategies, with the former potentially being more closely associated with the development of VT or VPTG [57]. Furthermore, women tend to engage more in rumination, a process regarded as essential for facilitating PTG [18]. Research also suggests that intrusive rumination is positively associated with psychological trauma, whereas deliberate rumination promotes PTG [18]. In addition, male nurses within the context of Chinese culture may encounter unique challenges, such as heightened occupational bias, increased gender role expectations in professional interactions, and lower levels of social support [59]. These factors could contribute to higher VT and lower VPTG among male nurses. Future research should seek to include a larger male sample to explore the complex relationship between gender and VT-VPTG patterns.
The results showed that oncology nurses satisfied with their work were likely to enter the mild VT - high VPTG group. Job satisfaction reflects a positive work environment that fosters emotional resilience, buffers the impact of VT, and promotes growth after trauma. Such environments also enhance empathy and emotional involvement, crucial for quality patient care [60]. In addition, childbirth is a significant life event that requires considerable physical, emotional, and psychological strength. Nurses who have undergone this experience may develop enhanced coping mechanisms and higher accomplishment, which can help oncology nurses achieve growth [61, 62]. Hospital administrators should focus on implementing recognition and reward mechanisms, and creating a supportive work environment to effectively improve nurse job satisfaction and sense of fulfillment, and thereby promote positive psychological change.
Compared to the Mid VT - mid VPTG group, oncology nurses in the Mild VT - mild VPTG or Mild VT - high VPTG groups receive higher social support. Notably, these groups with higher social support share a common trait: lower levels of VT. This phenomenon can be explained through the buffering effect model of social support, which suggests that social support functions as a shield that helps individuals cope with the traumatic experiences associated with patient care, thereby reducing the impact of VT [63]. However, the influence of social support on VPTG among oncology nurses is inconsistent. Tedeschi and Calhoun propose that social support can facilitate emotional regulation (including cognitive reappraisal and expressive suppression), which then influences VPTG [18, 64]. On the one hand, when cognitive reappraisal is adopted among oncology nurses, it engages in positive cognitive processing that facilitates PTG. On the other hand, expressive suppression as an emotional regulation strategy is more prevalent among Chinese oncology nurses due to traditional cultural norms, where the expression of negative emotions is often deemed inappropriate, unwelcome or a sign of personal weakness [65]. While this suppression may reduce the overt manifestation of VT symptoms by limiting the expression of distress or vulnerability, it may simultaneously impede the process of VPTG [66]. Clinical managers should strengthen support for oncology nurses through both family and professional resources, such as peer support groups and Balint groups. Given China’s cultural tendency toward expressive suppression, clinical training should include emotional expression skills training to enhance nurses’ psychological well-being.

Study limitations

Several limitations of this study should be noted. First, limited by the cross-sectional design of the study, causal relationships between VT, VPTG and their predictors could not be determined. Future research should focus on longitudinal studies. Second, the data were collected from a single province in China, which may affect generalizability. Cultural and systemic differences in healthcare resources and workplace environments may influence VT and VPTG patterns, warranting further exploration in diverse settings. Third, social support, a key variable, was assessed using a simple categorization. While this reduced complexity and participant burden, it lacked rigor. Future research should employ validated scales for a more comprehensive understanding. Additionally, data collection was self-reported, which may introduce response biases such as social desirability or recall bias. The online format may also lead to self-selection bias and made it difficult to clarify questionnaire items, potentially affecting participation rates and data quality. Lastly, the gender distribution was heavily skewed toward females (98.5%), reflecting the predominantly female nursing workforce but limiting the exploration of gender-based differences. Future studies should include more male nurses to better understand gender dynamics.

Conclusion

This study is the first to utilize a person-centered approach to identify patterns of VT combined with VPTG among Chinese oncology nurses. The analysis revealed three-class profiles of VT and VPTG, with the majority of participants classified in the mild VT - high VPTG group. These profiles were influenced by factors such as age, fertility status, job satisfaction, and social support. Our findings contribute to the existing limited literature on the co-occurrence patterns of these two psychological responses and may help to clarify mixed findings observed in prior studies examining the relationship between VT and VPTG. Additionally, this study provides valuable insights for nursing management, offering practical guidance for clinical administrators to develop targeted managerial and supportive interventions.

Acknowledgements

The authors wish to thank all of the participants for their contribution to the research.

Declarations

The study adhered to the Declaration of Helsinki – Ethical principles for medical research involving human participants. The study was approved by the Ethics Committee of the Zhejiang Chinese Medical University (20230922-6). The methods of the current research were carried out in accordance with the relevant guidelines and regulations involving human participants of the above institutional review board. Participation in this survey was anonymous, consensual, and voluntary, with written electronic informed consent obtained from all participants.
Not applicable.

Competing interests

The authors declare no competing interests.

Clinical trial number

Not applicable.
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Glossar
Vicarious Trauma (VT)
A process of experiencing traumatic responses after being exposed to the trauma of others.
Vicarious Posttraumatic Growth (VPTG)
The personal growth and meaning gained through others’ trauma.
Mild VT – mild VPTG
A profile characterized by low levels of both VT and VPTG.
Mid VT – mid VPTG
A profile where moderate levels of VT coexist with moderate levels of VPTG.
Mild VT – high VPTG
A profile where individuals experience relatively low levels of VT but demonstrate significant VPTG.
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Metadaten
Titel
Patterns of vicarious trauma and vicarious posttraumatic growth among oncology nurses: a latent profile analysis
verfasst von
Dandan Chen
Yi Zhou
Jinghan Xu
Yunxian Zhou
Publikationsdatum
01.12.2025
Verlag
BioMed Central
Erschienen in
BMC Nursing / Ausgabe 1/2025
Elektronische ISSN: 1472-6955
DOI
https://doi.org/10.1186/s12912-025-02893-5