xRead - Second Victim Syndrome (March 2026)

BMC Public Health

Huang et al. BMC Public Health

(2024) 24:2330

https://doi.org/10.1186/s12889-024-19738-6

Open Access

RESEARCH

“Learn from Errors”: Post-traumatic growth among second victims

Huanhuan Huang 1 , Tong Liu 1 , Ying Peng 1 , Xingyao Du 1 , Qi Huang 2 , Qinghua Zhao 1 , Mingzhao Xiao 3 , Yetao Luo 4*† and Shuangjiang Zheng 5*†

Abstract Background Second victims, defined as healthcare providers enduring emotional and psychological distress after patient safety incidents (PSIs). The potential for positive transformation through these experiences is underexplored but is essential for fostering a culture of error learning and enhancing patient care. Objective To explore the level and determinants of post-traumatic growth (PTG), applying the stress process model. Methods The study was conducted at a tertiary general hospital in Chongqing, China. A descriptive, cross-sectional study design was used. A total of 474 s victims were included. An online survey was conducted in November 2021 to assess various factors related to the second victim experience. These factors included PSIs (considered as stressors), coping styles, perceived threats, and social support (acting as mediators), as well as the outcomes of second victim syndrome (SVS) and PTG. Statistical description, correlation analysis, and structural equation modeling were utilized for the data analysis. A p-value ≤ 0.05 was considered to indicate statistical significance. Results The participants reported moderate distress (SVS = 2.84 ± 0.85) and PTG (2.72 ± 0.85). The total effects on SVS of perceived threat, negative coping, social support, positive coping, and PSIs were 0.387, 0.359, -0.355, -0.220, and 0.115, respectively, accounting for 47% of the variation in SVS. The total effects of social support, positive coping, and PSIs on PTG were 0.355, 0.203, and − 0.053, respectively, accounting for 19% of the variation in PTG. Conclusions The study provides novel insights into the complex interplay between perceived threats, coping styles, and social support in facilitating PTG among second victims. By bolstering social support and promoting adaptive coping strategies, the adverse effects of PSIs can be mitigated, transforming them into opportunities for resilience and growth, and offering a fresh perspective on managing PSIs in healthcare settings. Keywords Second victim, Patient safety, Post-traumatic growth, Social support, Positive coping

2 School of Public Health, Chongqing Medical University, Chongqing 400016, China 3 Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China 4 Department of Nosocomial Infection Control, Second Affiliated Hospital, Army Medical University, Chongqing 400037, China 5 Department of Medical Affairs, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China

† Yetao Luo and Shuangjiang Zheng contributed equally to this work and should be considered co-corresponding authors *Correspondence: Yetao Luo luoyetao1992@126.com Shuangjiang Zheng zhenghust913@163.com 1 Department of Nursing, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China

© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Introduction Patient safety incidents (PSIs) not only affect patients and their families but also impact healthcare workers, who may experience adverse psychological consequences [1]. The term ‘second victim’, introduced by Wu, encap sulates healthcare providers affected by unexpected PSIs [2]. Studies indicate that a significant proportion of healthcare providers, ranging from 10.4 to 43.3%, have endured the ordeal of becoming a second victim during their careers [3]. Amidst the COVID-19 pandemic, the well-being of healthcare workers has been thrust into the spotlight, underscoring the importance of safeguarding their well-being for the broader goal of patient safety [4, 5]. Currently, interest in the phenomenon of the second victim continues to grow, with a consensus that these individuals may suffer negative outcomes post-PSIs. They can exhibit a spectrum of psychological and psy chosomatic symptoms, including distressing memories, guilt, and sleep disturbances [6–8], presenting significant challenges for the human resources department within the health care system. However, constructivist perspec tives suggest that second victims are not merely passive recipients of trauma; instead, they actively interpret their experiences and derive lessons from them [9], potentially leading to posttraumatic growth (PTG) [10]. PTG refers to the process of discovering benefits, promoting stress-related growth, and thriving follow ing a traumatic event [11]. For example, some general surgeons reportedly improved their theoretical and practical knowledge following bile duct injuries dur ing laparoscopic cholecystectomy [12]. Similarly, several studies have reported that second victims often learn valuable lessons from their unexpected and unfortunate clinical experiences, viewing them as part of the natural recovery process [9, 13–15]. It is reported that explor ing the lessons learned by second victims addresses their immediate psychological needs and refines the vulnera bilities within patient safety systems [16]. While previous studies have provided valuable insights into the positive outcomes that can arise from critical incidents, there is a significant gap in research that applies a theoretical framework to systematically assess the levels of PTG and its determinants. The Stress Process Model (SPM), introduced by Pearlin in 1981 [17], is a foundational framework for under standing the dynamics of workplace stress. The model is structured around three core elements: stressors, which are the initiating events; mediators, which influence the stress response; and outcomes, which represent the con sequences of stress. SPM provides a systematic approach to analyzing the complex interplay among these ele ments, making it a valuable tool in various stress-related research domains. SPM has been successfully employed

to comprehend phenomena such as depression and burn out in biomedical students [18] and the positive aspects of caregiver burden in dementia [19]. While the SPM has not been extensively applied to patient safety, its concep tual framework resonates with the stress experienced by second victims. In this study, we defined “outcomes” as two related but distinct adverse consequences of stress, PTG and second victim syndrome. A stressor refers to stimulate that compels individuals to adapt. Previous research has shown that PSIs, such as the degree, type, and frequency of harm, are significant factors in the symptoms experi enced by second victims [20]. These factors also play a crucial role in PTG [21]. Mediators refers to the physiological and psychologi cal responses that constitute the perception of being stressed. According to the qualitative research [9, 13–15], mediators may be associated with coping styles, situ ational influences such as social support, and appraisals (such as perceptions of threat and levels of distress). These mediating factors establish a complex pathway linking stressors and PTG. To elaborate: (1) Coping strategies are pivotal in shaping an indi vidual’s stress response. Positive methodologies, such as problem solving and social support seeking, can attenu ate stress reactions, foster resilience and potentially culminate in PTG [22]. In stark contrast, strategies char acterized by avoidance and denial, often categorized as negative, can exacerbate stress responses, impede recov ery and potentially lead to the manifestation of second victim syndrome [23]. (2) Perceived threat, a subjective evaluation of the stressor’s potential harm, also plays a crucial role in shap ing stress outcomes. A heightened sense of threat can intensify stress reactions, impede recovery, and poten tially result in negative outcomes. On the other hand, a diminished perception of threat can moderate stress responses, facilitating adaptation and recovery, and may lead to PTG. (3) Social support, another key mediator, is character ized by a sense of belonging and attachment to friends, family, or colleagues and includes both emotional and physical support [24]. The ability to connect with others is a critical aspect of PTG [25, 26]. Evidence suggests that a supportive social network, particularly support from managers, can mitigate second-victim syndrome [15, 27, 28]. Recent research has further confirmed that both positive coping styles [29] and perceived threat [30] act as mediators between perceived social support and PTG. Learning from errors is fundamental to improving patient safety [31]. Thus, this study aimed to (1) assess the level of PTG among second victims, and (2) identify the factors that influence PTG through SPM. The hypo thetical model is shown in Fig. 1. Our findings could aid

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Fig. 1 Hypotheses of posttraumatic growth among second victims based on the stress process model

health care systems worldwide in better supporting and understanding these second victims, thereby improving health care provision and patient safety. Methods Design We used a descriptive, cross-sectional study design with cluster sampling. The current study utilized the Strength ening Reporting of Observational Studies in Epidemiol ogy (STROBE) cross-sectional checklist [32]. Setting This study was conducted in a large, comprehensive hospital, which is a major health care provider in the region. The hospital comprises 38 clinical departments and 8 medical technology departments, with a total of 4616 beds. In 2023, the hospital served an impressive 3.4564 million outpatient visits, discharged 197,100 inpa tients, and performed 89,000 surgeries. The patient pop ulation is diverse, with individuals coming from all over the country. This diversity in the patient population also translates to a wide range of cases and experiences for health care professionals, thereby adding to the richness and complexity of the data collected in our study.

engaged in patient care or patient management; (b) those who have experienced or witnessed a patient safety inci dent within the past year; (c) individuals who self-assess as having been negatively impacted during these events; and (d) those who have provided informed consent and demonstrated a willingness to participate. Our study aimed to capture the experiences of those with a greater degree of responsibility and autonomy in their roles. Given the limited experience of interns and trainees and the supervised nature of their roles, they may not engage with or respond to these incidents in the same depth as our target population. Therefore, interns and trainees were excluded from the study. Sample size The sample size was calculated with a confidence interval of 95% at a proportion of second victims of 76.88% [33], a marginal error of 5%, and a permissible error of 5%. Con sidering a loss to follow-up rate of approximately 30%, the required sample size was 357. To ensure the reliability of SEM, a priori power analysis based on the recommen dation of Kline et al. [34] of a 20:1 sample size-to-param eter ratio was used for estimating the sample size. Based on a maximum of 20 parameters, the priori-determined sample size was 400.

Participants Inclusion and exclusion criteria

Measures Patient safety incidents (PSIs)

Drawing upon prior studies [33] and definitions [2], the participants, namely, the second victims, are identified as follows: (a) health care professionals who are directly

PSIs are primarily evaluated based on their frequency and severity. First, participants were asked to report the

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frequency with which they had experienced or witnessed PSIs in the past month. The responses were scored as fol lows: 3 (always, ≥ 11), 2 (often, 5 ~ 10), 1 (seldom, 1 ~ 5), or 0 (none). Second, participants were required to indi cate the type of their most recent PSI based on the defini tion and classification provided by the Chinese National Health Commission for medical adverse events [35]. The categories were defined as follows: Level I (events with factual errors leading to consequences), Level II (events without factual errors but still leading to significant consequences), Level III (events without factual errors but leading to minor or no consequences), and Level IV (events without factual errors and without any resulting consequences). A cumulative score was calculated based on these two parameters. A higher total score suggests a greater level of stress induced by the PSIs. The reliability of this scoring system was confirmed with a Cronbach’s alpha of 0.712 in this study. Perceived threat The Perceived Threat Scale (PTS), molded after the Per ceived Life Threat Scale [36], was employed to assess the perceived threat. This 4-item tool assessed the perceived threat of PSIs to one’s life or work, the likelihood of simi lar future incidents, the potential disruption to work or life, and the severity of the incident’s consequences. A 5-point Likert scale was used to quantify the responses. The scale demonstrated acceptable reliability in this study, with a Cronbach’s alpha of 0.756. Coping style The coping style was assessed using the Trait Coping Style Questionnaire (TCSQ), which is divided into two dimensions: negative coping (NC) and positive coping (PC). Each dimension contains 10 items, and a 5-point Likert scale was used for scoring (5 points for “strongly agree” and 1 point for “strongly disagree”). A higher score in each dimension indicates more pronounced positive or negative strategies. The TCSQ is widely used in the Chinese population, and the two dimensions are typi cally analyzed separately [37]. In this study, the Cron bach’s alpha was 0.814 for the positive coping dimension and 0.805 for the NC dimension, demonstrating good reliability. Social support Social support was measured using the Second Vic tim Experience and Support Tool (SVEST). The SVEST was developed by Burlison et al. [38] and is the first tool designed to evaluate the experiences of second vic tims and the quality of support resources available to them. This tool has been widely used in China [13, 33]. The social support part includes five dimensions and 18 items, with a Cronbach’s alpha of 0.854, indicating good

reliability. The responses are scored using a 5-point Lik ert scale (5 points for “strongly agree” and 1 point for “strongly disagree”). A higher score on this scale indicates a greater level of perceived social support. Second-victim symptoms (SVS) The negative outcome, second victim symptoms (SVS), was also assessed using the SVEST of [38]. This aspect of the tool includes two dimensions and eight items, with a Cronbach’s alpha of 0.901, indicating excellent reliability. Posttraumatic growth (PTG) PTG was measured using the Chinese Posttraumatic Growth Inventory (C-PTGI). The C-PTGI was adapted and translated into Mandarin by Wang [39] from the Posttraumatic Growth Inventory [40]. The C-PTGI consists of 20 items distributed across 5 dimensions. Responses are scored on a six-point Likert scale, with 6 points given for “very much” and 1 point for “not at all”. Based on the participants’ scores, they were categorized into three levels of growth: low (less than 60 points), middle (60–65 points), and high (66–100 points). In this study, the C-PTGI demonstrated excellent reliability, with a Cronbach’s alpha of 0.953. Data collection The online survey was created through a free website (https://www.wjx.cn/). In November 2021, the sur vey link was disseminated to qualified participants via WeChat groups. This distribution was facilitated by department heads and head nurses to ensure that the link reached the intended audience. The groups were chosen based on the cluster sampling method; each group rep resented a ‘cluster.’ The clusters were formed based on the departments, specifically including medical depart ments, surgery departments, and technology-related departments. We carried out the survey across all regular employee within these departments, encompassing three professional categories: nurses, doctors, or medical tech nical staff. To ensure data quality, we excluded the follow ing questionnaires: (a) those with identical answers on both reverse and forward questions; (b) those completed in less than nine minutes, as per the pilot study; and (c) those in which all of the answers were the same. Data analysis Data analysis was performed using IBM SPSS and AMOS version 26.0 (IBM Corp, Armonk, NY, USA). We used descriptive statistics to describe the demographic infor mation. Continuous data, such as the scores from the C-PTGI, are reported as the means along with their standard deviations (SDs). To ensure the reliability of our model, we first checked for multicollinearity among the independent variables by calculating the variance

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inflation factor (VIF). The results showed that the VIF for all variables was less than 3, indicating no significant multicollinearity issues among the variables. Bivariate analyses were conducted to explore the relationships among all of the variables. To identify the underlying mechanisms of PTG among second victims, we employed structural equation modeling (SEM). We assessed the model fit using several indices [41]: a relative chi-square (χ2/df) less than 5, a goodness-of-fit index (GFI) over 0.9, a comparative fit index (CFI) above 0.90, and a root mean squared error of approximation (RMSEA) below 0.08. The bootstrap method (with 5000 samples) was used to calculate the 95% confidence intervals (CIs) for direct effects, indirect effects, and total effects. A P value less than 0.05 (two-sided) was considered to indicate statisti cal significance. Ethical consideration Ethical approval for the study was obtained from the Eth ics Committee of the First Affiliated Hospital of Chongq ing Medical University (reference number 2019-067). Participants were assured that their decision to partici pate or not would not affect their professional status or Table 1 Demographic characteristics of the participants ( n = 474) Characteristics N % Sex Male 118 24.89 Female 356 75.11 Age (years) 21–30 86 18.14 31–40 278 58.65 41–50 71 14.98 51–60 39 8.23 Occupation Nurse 243 51.27 Doctor 171 36.08 Medical technical staff 60 12.66 Departments Medical departments 203 42.83 Surgery departments 195 41.14 Technology-related departments 76 16.03 Education level College degree 17 3.59 Bachelor degree 244 51.48 Master degree or above 213 44.94 Marriage statues Married 383 80.80 Unmarried 91 19.20 Work experience (years) ≤5 85 17.93 6–10 158 33.33 11–20 151 31.86 > 20 80 16.88

opportunities within the institution. Only those who pro vided written consent on the first page of the survey were allowed to proceed with answering the questions. They were informed that they could withdraw from the study at any time. To ensure confidentiality, any data sharing or reporting was conducted in a manner that protected the privacy of individual participants. To prevent any unnec essary administrative coercion and to ensure the integrity of the data, each questionnaire was anonymized. Addi tionally, measures were taken to permit each IP address to submit the survey only once. Results Demographic characteristics of the participants Ultimately, a total of 1023 health care service provid ers actively participated and completed the survey, 238 of whom were excluded due to inadequate quality. Fur thermore, an additional 311 respondents were excluded because they did not meet the criteria for being consid ered second victims. Consequently, a final analysis was conducted utilizing data from 474 eligible participants. Most participants were female (75.11%) and married (80.80%). Approximately half of the participants were nurses (51.27%), with ages ranging from 31 to 40 years (58.64%). Of these, 42.83% worked in medical depart ments, while 85% worked in surgery departments; only a minority of participants worked in technology-related departments such as radiology departments (20%). Table 1 presents the demographic characteristics of all participants. Descriptive statistics and correlations of the variables The mean PSIs score was 1.80 (SD = 0.54). Partici pants reported a slight perceived threat (mean = 2.19, SD = 0.81). Coping style scores indicated a greater mean for PCs (3.17 ± 0.54) than for NCs (2.71 ± 0.56). Partici pants displayed a high level of social support (3.67 ± 0.53) and moderate distress (SVS = 2.84 ± 0.85). The mean C-PTGI score was 2.72 ± 0.85, indicating a moder ate level of growth, with the highest score for personal strength (3.08 ± 0.99) and the lowest for spiritual change (2.59 ± 0.97). According to the C-PTGI cutoff, 36.06% of second victims reported some level of psychological improvement after PSIs. PTG had negative and positive associations with NC ( r = -0.190, p < 0.001) and perceived threat, PC, and social support ( r = 0.098, r = 0.288, r = 0.354; all p < 0.05), respectively. Details were shown in Table 2. Path analysis results The initial model results showed an unsatisfactory fit, leading to model modification. Nonsignificant paths (PSIs → NC, PSIs → SVS, social support → SVS, PSIs → PTG, NC → PTG) and paths inconsistent with the correlation

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Table 2 Pearson correlation coefficients for the study variables Variable Mean ± SD 1 2

3

4

5

6

1. patient safety incidents

1.80 ± 0.54 2.19 ± 0.81 3.17 ± 0.54 2.71 ± 0.56 3.67 ± 0.53 2.84 ± 0.85 2.72 ± 0.85

1

2. perceived threat 3. positive coping 4. negative coping 5. social support

0.216*** -0.153***

1

-0.109* 0.225*** -0.221*** 0.353***

1

0.117* -0.112* 0.142**

-0.494*** 0.335*** -0.375*** 0.288***

1

-0.329*** 0.503*** -0.190***

1

6. second victim’s symptoms 7. post-traumatic growth SD: Standard deviation * P < 0.05, ** P < 0.01, *** P < 0.001

-0.270*** 0.354***

1

-0.035

0.098*

-0.013

analysis results (SVS → PTG, perceived threat → PTG) were removed. The final model demonstrated a good fit (χ2/df = 365.614/199 = 3.072, GFI = 0.922, CFI = 0.937, and RMSEA = 0.066). The total path estimates for the final model are shown in Table 3, and the validated model with standardized effects among variables is depicted in Fig. 2. Direct effect PC (direct β = -0.220, 95% CI = -0.328~ -0.115), NC (direct β = -0.359, 95% CI = 0.237 ~ 0.478), and perceived threat (direct β = 0.387, 95% CI = 0.281 ~ 0.493) had direct effects on SVS. Social support (direct β = 0.278, 95% CI = 0.148 ~ 0.404) and PC (direct β = 0.203, 95% CI = 0.108 ~ 0.295) directly influenced PTG. Direct effect PSIs positively influenced SVS indirectly via social sup port (indirect β = 0.041, 95% CI = 0.004 ~ 0.082) and per ceived threat (indirect β = 0.061, 95% CI = 0.022 ~ 0.11). PSIs had a negative indirect effect on PTG primarily through social support (indirect β = -0.041, 95% CI = - 0.084~-0.006). Social support indirectly influenced SVS negatively through PC (indirect β = -0.084, 95% CI = - 0.138~-0.041), NC (indirect β = -0.148, 95% CI = -0.213~- 0.097) and perceived threat (indirect β = -0.124, 95% CI = -0.186~-0.072). Its positive indirect effect on PTG was primarily via social support (indirect β = 0.078, 95% CI = 0.042 ~ 0.125). Total effect The total effects on SVS of perceived threat, NC, social support, PC, and PSIs were 0.387, 0.359, -0.355, -0.220, and 0.115, respectively, accounting for 47% of the varia tion in SVS. The total effects of social support, PC, and PSIs on PTG were 0.355, 0.203, and − 0.053, respectively, accounting for 19% of the variation in PTG. Discussion To the best of our knowledge, this is the first study inves tigating the underlying mechanisms of SVS and PTG among second victims. The final model indicated that perceived threats, coping styles, and social support as

stressors significantly influenced the outcomes. These findings have important implications for understanding and responding to the effects on second victims, reveal ing the important role of coping strategies and social sup port in the aftermath of patient safety incidents. Our research revealed that second victims exhibit moderate levels of SVS and PTG. This finding aligns with previous studies on survivors of different types of trauma [42, 43] and conforms to the fundamental concept of PTG, which posits that the positive and negative aspects of adjustment are independent [44]. This suggests that persistent distress and growth are not mutually exclusive and can coexist within an individual, a notion that is con sistent with constructivism and positive psychology [45, 46]. In our study, we found that the average PTG score for the personal strength dimension was high, whereas the average PTG score for the spiritual change dimen sion was low. The medical profession has a long-standing commitment to continuing education, ensuring that all health care providers and students maintain the highest quality of care [47]. This emphasis on continuous learn ing is particularly notable among those who have been victims or witnesses of adverse events or PSIs. Occa sionally, the ‘shame and blame’ culture or administrative policy within institutions has even served as a catalyst for the advancement of theory and practice improvement for second victims [48, 49]. On the other hand, psychologi cal growth was found to be relatively low. Only 36.06% of second victims reported experiencing positive growth following patient safety incidents, a finding that aligns with previous studies [50] and warrants further attention and consideration. Our study revealed that only PC and social support had direct effects on PTG, with total effects of 0.355 and 0.203, respectively. Furthermore, our results partially supported our hypotheses and previous findings [51–53], indicating that social support indirectly influences PTG through the style of PC. This implies that second victims with higher levels of social support are likely to receive more emotional or instrumental support, which may help them reshape their perception of errors and cope with the outcomes. This finding is consistent with other

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Table 3 The total path estimates in the final model Path β

studies in which second victims reported that unsupport ive practices could hinder the restoration of professional competence, thereby preventing them from “moving forward“ [54]. This suggests that in designing and imple menting interventions, we need to pay more attention to how to provide effective social support and how to foster positive coping mechanisms. Indeed, these two elements are also highlighted in second victim support programs, such as the forYOU [55] and RISE (Resilience in Stressful Events) peer support programs [56]. Our study elucidates intriguing findings that ques tion conventional paradigms regarding the relationship between trauma and ensuing growth. Specifically, con trary to our hypothesis, we observed that PSIs, perceived threats, negative coping strategies, and SVS did not facili tate PTG. The absence of this expected relationship might be attributable to the inherent characteristics of PSIs, which frequently precipitate substantial negative ramifi cations and engender feelings of culpability rather than fostering opportunities for growth [57]. This could be partly explained by the existence of an inverted-U shaped relationship between distress levels and PTG, whereby both excessively high and low distress levels obstruct the perception of growth [58]. Such a revelation neces sitates a comprehensive reevaluation of our understand ing of PTG, highlighting the potential merit of shifting our focus toward factors that encourage positive coping and adaptation, as opposed to concentrating exclusively on the trauma itself. Our research provides a fresh understanding of PTG among second victims. The findings suggest that PTG in second victims is not attributed to the suffering experi enced or the threats they perceived, but rather a proac tive response, tool support, and active refactoring [51]. This insight underscores that learning from errors is not just about experiencing distress but also about how to positively process and learn from these experiences, a viewpoint corroborated by previous research [59, 60]. For instance, studies have shown that proactive rumination can help individuals positively interpret and deal with traumatic events, overcome fear responses, and foster constructive responses, thereby supporting their growth post-trauma [42]. In contrast, intrusive rumination leads individuals to negatively interpret traumatic events and focus on their negative aspects, causing more anxiety and tension and potentially exacerbating psychological trauma [42]. Thus, our results highlight the importance of positive coping and social support in promoting PTG in second victims. Notably, our final model for second victims’ PTG explained only a small amount of variance (19%), which may be attributed to potentially unrecognized confound ing factors. As an adaptive system, health care delivery involves complexity and uncertainty [61, 62] as agents,

Bootstrap method 95% CI a Lower Upper P -0.136 0.014 0.117 0.055 0.264 0.003 -0.215 -0.009 0.029 0.279 0.473 < 0.001 -0.504 -0.316 < 0.001 -0.438 -0.195 < 0.001 -0.328 -0.115 < 0.001 0.237 0.478 < 0.001 0.281 0.493 < 0.001 0.148 0.404 < 0.001 0.108 0.295 < 0.001 0.004 0.082 0.025 -0.001 0.034 0.073 0.022 0.110 0.002 0.062 0.176 < 0.001 -0.138 -0.041 < 0.001 -0.213 -0.097 < 0.001 -0.186 -0.072 < 0.001 -0.435 -0.275 < 0.001 -0.072 -0.005 0.017 -0.021 -0.002 0.014 -0.084 -0.006 0.021 -0.033 0.002 0.089 -0.096 -0.014 0.010 0.042 0.125 < 0.001 0.062 0.176 < 0.001 -0.435 -0.275 < 0.001 -0.328 -0.115 < 0.001 0.237 0.478 < 0.001 0.281 0.493 < 0.001 -0.096 -0.014 0.010 0.234 0.471 < 0.001 0.108 0.295 < 0.001 0.002 0.023 0.015 0.002 0.038 0.021 0.002 0.032 0.019

Direct effect PSIs → PC

-0.061 0.158 -0.114 0.382 -0.411 -0.319 -0.220 0.359 0.387 0.278 0.203

PSIs → Perceived Threat PSIs → Social Support Social Support → PC Social Support → NC Social Support → Perceived Threat Perceived Threat → SVS Social Support → PTG Indirect effect PSIs → Social Support → PC → SVS PSIs → Social Support → NC → SVS PSIs → Social Support → Per ceived Threat → SVS PSIs → Social Support → SVS PC → PTG PC → SVS NC → SVS

0.010

0.017

0.014

0.041 0.013

PSIs → PC → SVS

PSIs → Perceived Threat → SVS 0.061

PSIs → SVS

0.115 -0.084 -0.148 -0.124

Social Support → PC → SVS Social Support → NC → SVS Social Support → Perceived Threat → SVS

Social Support → SVS

-0.355

PSIs → Social Support → PTG -0.032

PSIs → Social Support → PC → PTG

-0.009

PSIs → Social Support → PTG -0.041

PSIs → PC → PTG

-0.012 -0.053

PSIs → PTG

Social Support → PC → PTG 0.078

Total effect PSIs → SVS

0.115 -0.355 -0.220 0.359 0.387 -0.053 0.355 0.203

Social Support → SVS

PC → SVS NC → SVS

Perceived Threat → SVS

PSIs → PTG

Social Support → PTG

PC → PTG

PSIs: Patient safety incidents; PTG: Post-traumatic growth β: Standardized regression coefficient; SE: Standard error a The bootstrap method yielded 5000 samples

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Fig. 2 The final model for factors influencing post-traumatic growth in second victims. (with standardized regression coefficients). * p < 0.05; ** p < 0.01; *** p < 0.001

and the relationships between these agents is constantly evolving. Thus, it is challenging to fully comprehend the entire system. Given this characteristic, perceived growth after adverse events or errors may emerge from a conflu ence of numerous contributory factors. Overall, our findings have broad implications for future research and provide directions for hospital human resource management and quality improvements. The safety of health care workers is a prerequisite for patient safety. Investing in support for second victims should be a priority for patient safety. Although errors are inevi table, health care managers should formulate practical strategies and provide available resources to assist sec ond victims. Implementing specific strategies, such as group interventions, can be beneficial, allowing second victims to share their experiences and gain strength from the experiences and support of others [63]. Mindfulness training could also be helpful [64], as it can assist second victims in better processing and accepting their experi ences rather than avoiding or resisting them. Limitations As with any study, it is important to consider the limita tions of this study when drawing conclusions. First, this cross-sectional design study made it difficult to infer cause-and-effect relationships. More long-term cohort studies are needed to fully confirm this hypothesis. This setting, with its large scale and diverse patient pool, pro vides a unique and comprehensive environment for our study of second victims, despite the limitation of being a

single-site study. Third, the use of a self-report question naire may lead to reporting bias and socially desirable responses. Finally, some other factors may explain the positive psychological changes, which could also cause bias. Conclusions Our cross-sectional research provides a new understand ing of the intricate relationships among perceived threats, coping mechanisms, and social support in the context of PTG. By strengthening social support and enhancing adaptive coping strategies, we can shift the consequences of an error from trauma to resilience and growth, offer ing a fresh approach to managing the repercussions of patient safety incidents. Acknowledgements The authors would like to thank the participants who contributed their time to the study. Author contributions HH, SZ, and MX designed the study and participated in writing and revising the manuscript. TL, QH, and XD contributed to interpreting the data, and YL, YP, and QZ participated in writing and revising the manuscript. YL collected the data, performed the statistical analysis, and contributed to interpreting the data. All authors have read and approved the manuscript. Funding This study was funded by the Chongqing Yuzhong Science and Technology Bureau and the Municipal Health and Health Committee (approval number: 20210104). However, the funders had no role in the study design, data collection, management, analysis or interpretation, manuscript writing or the decision to submit the report for publication.

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Data Availability The data and materials are available from the corresponding author.

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Declarations

Ethics approval and consent to participate This study was approved by the Medical Ethics Committee of The First Affiliated Hospital of Chongqing Medical University (No. 2019-067). After explaining the anonymity and confidentiality of participation, medical workers were informed that they could refuse to participate or withdraw from participation at any time without penalty. All participants provided written informed consent.

Consent to publish Not applicable.

Competing interests The authors declare no competing interests.

Received: 24 October 2023 / Accepted: 8 August 2024

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