Background
Nurses play a crucial role in public health and patient safety. Recent data from the Report on the Development of National Mental Health in China (2019–2020) [1], published by the Institute of Psychology of the Chinese Academy of Sciences, highlights significant concerns regarding nurses’ mental health. This concern may be partly due to the higher incidence of violence nurses face compared to other healthcare professionals [2]. Nurse-to-nurse horizontal violence (HV), characterized by aggressive, bullying, intimidating, or divisive behavior, can manifest physically, verbally, or emotionally. This form of workplace violence significantly harms nurses’ health and job satisfaction and is recognized as a critical issue in global career development [3]. The prevalence of HV varies widely, reported between 4.6% and 87.2% [3‐6], indicating that most nurses globally have encountered HV at some stage in their careers. This widespread issue negatively impacts the development of work environments in healthcare settings [3, 7‐10], nurses’ health [4, 11], and patient safety. However, experiencing HV can also lead to positive psychological changes, known as post-traumatic growth (PTG) [12]. PTG refers to the beneficial psychological transformations individuals undergo after facing significant life challenges. In nurses, PTG can reshape perceptions of interpersonal relationships, enhance clinical communication skills, improve patient safety, and foster both personal and professional growth [13]. PTG not only assists nurses in managing physical and psychological stress but also provides substantial potential for interventions to help individuals recover from trauma and mitigate its detrimental effects.
According to resource conservation theory [14, 15], a person’s capacity to overcome adversity and achieve post-traumatic growth (PTG) may hinge on their ability to perceive, access, and utilize internal and external resources effectively. Ten and Bakker’s resource categorization model [16], based on this theory, highlights that internal factors like executive function [17, 18] and resilience [19‐22] are crucial, alongside external factors such as organizational justice [23] and support from influential others [24].
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Resilience [19] is an individual’s ability to adapt to or bounce back from adverse circumstances. Some scholars [20, 21] have identified resilience as a significant positive predictor of PTG in stressful conditions. A high level of resilience can enhance the development of PTG in nurses, potentially mitigating the adverse effects of workplace violence (HV) on their psyche and facilitating their acquisition of PTG.
Executive function [17] is a high-level cognitive ability crucial for individuals when addressing and resolving complex tasks. Toh et al. [25] reported that high levels of executive function confer individuals with the ability to flexibly utilize self-emotion regulation strategies under high stress intensities, assisting individuals to cope with emotional stimuli of varying intensities. Therefore, HV-exposed nurses with high executive functioning tend to be more emotionally stable and have a higher probability of being able to obtain PTG in daily or acute stressful situations [26].
Notably, the environment may play a much more nurturing role in PTG than the intra-individual resources predicting it [27]. The development of HV-related PTG is no longer considered a purely binary issue between perpetrator and victim, and the potential influence of environmental resources from the team and leader on its existence is gradually being emphasized [28, 29]. Organizational justice are members’ perceptions of the fairness of rules and regulations, work procedures, and work information related to their rights and interests. A scholarly investigation [23] found that organizational justice reduced the risk of depression and increased personal power after exposure to work violence [30]. Accordingly, high organizational justice may provide positive resources for HV-exposed nurses and increase the likelihood of positive mental health outcomes.
Inclusive leadership is a leadership style that invites and appreciates the contributions of followers by demonstrating openness, flexibility, and availability [31]. Some scholars [32] reported that employees in stressful situations are more likely to be influenced by their leaders. Whereas, managers with a strong inclusive leadership style provide employees with a sense of recognition and belonging that ensures the availability of organizational resources and provides environmental conditions for employees to access new possibilities [33]. Accordingly, it may also be one of the important environmental resources for maintaining PTG in HV-exposed nurses.
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These elements are potential key predictors of PTG during adversity. Conducting a thorough study on the PTG status of nurses exposed to HV and its determinants is immensely valuable. Such research aids nursing managers in deeply understanding PTG within this group, enabling early identification and precise psychological interventions for those at high risk of psychological crises. To date, research on PTG has predominantly focused on survivors of severe traumas, such as disasters and cancer, neglecting the chronic, non-fatal workplace violence, especially among HV-exposed nurses. This study focuses on HV-exposed nurses to examine their PTG and its influencing factors, aiming to provide insights for nursing managers to develop specific mental health management strategies. In order to better understand the potential impact of internal and external resources on PTG, we developed a conceptual model based on resource conservation theory [14, 15] and resource categorization model [16]. As shown in Fig. 1, we hypothesize that resilience, dysexecutive, organizational justice, and inclusive leadership are important influencing factors for PTG in HV-exposed nurses.
Fig. 1
A conceptual model of the hypothetical relationship between PTG and resources in HV-exposed nurses
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Methods and materials
Study design and sample
A multicenter cross-sectional design was adopted. By multi-stage cluster random sampling, 2838 nurses were recruited from eight tertiary hospital between February, 2023 ~ March, 2024. This study is part of a multicenter longitudinal follow-up research project.
Participants recruitment
The multi-stage cluster random sampling including 4 stages. The first stage was to divides the 16 prefecture-level cities (all cities contain both urban and rural areas) into 4 strata according to the current level of economic development [34], and 2 cities are randomly selected in each stratum, then a total of 8 cities are selected; the second stage was to randomly select one tertiary hospital in the selected city, for a total of 8 hospitals; and the third stage was to select no less than one-third of the departmental wards, such as Internal Medicine, Surgery, and Intensive Care Medicine, of the selected tertiary hospitals, and to include in the subjects all nurses who meet the criteria of the sampled departments.
Inclusion and exclusion criteria
The inclusion criteria were as follows: clinical nurse staff who are hospital employees possessing a certificate of nursing practice from the People’s Republic of China, do not charge any fees to third parties, have stationed in a fixed department for 6 months or longer and have had exposure to HV within the last 6 months. The exclusion criteria were as follows: nurses with previous non-HV psychological re-traumatization or psychological or pharmacological treatment, and who were not on duty at the time of the survey for various reasons or who did not agree to participate in this study.
Sample size
The lower limit of the sample size was calculated according to the sampling formula for rate n = Uα/22π(1-π)/δ2, Where Uα/2 is the statistic of U under the 95% confidence interval, π is the expected probability estimate, α = 0.05, Uα/2=1.96, the value of π in this study refers to the incidence of PTG among nurses exposed to HV, and based on the finding that the incidence of PTG among nurses exposed to HV in previous studies was 49.09% [35], π takes the value of 0.49 in this study, δ = 0.05, n = 384, considering 20% sample size loss, so the lower limit value of sample size in this study was 480.
Variables and Measures
We systematically collected socio-demographic information such as gender, age, marital status, children’s status, department type, educational background, and length of service as well as internal and external resources such as resilience, dysexecutive, organizational justice, and inclusive leadership as independent variables, and collected PTG as dependent variable.
The Chinese version of the nurse-to-nurse Negative Acts Questionnaire (NAQ-R)
Nurse-to-nurse horizontal violence was measured using the 19-item NAQ-R [36, 37], which comprises two subscales: overt type behaviors and covert type behaviors. Each item is rated with the various response alternatives from 1 (never) to 5 (almost every day), with total scores ranging from 19 to 95 and higher scores indicating more serious HV exposure. Those who choose 2 (very rarely) and 3 (almost once a month) are defined as experiencing HV, and those who choose 4 (almost once a week) and 5 (almost every day) are defined as experiencing severe HV. In other words, the NAQ-R threshold is 19 points, and any above 19 is regarded as exposure to HV within the previous six months. The NAQ-R has well documented psychometric properties, its Cronbach’s α was 0.98 [3] and has good discriminant validity [37, 38].
The Posttraumatic Growth Inventory-Short Form (PTGI-SF)
Posttraumatic Growth was measured using the 10-item PTGI-SF [39, 40], which comprises five subscales: relating to others, new possibilities, personal strength, spiritual change, and appreciation of life. Each item is rated on a 6-point Likert scale from 0 (I did not experience this change as a result of my crisis) to 5 (I experienced this change to a very great degree as a result of my crisis), with total scores ranging from 0 to 50 and higher scores indicating higher PTG [39]. The PTGI-SF has well documented psychometric properties, its Cronbach’s α was 0.93 [41], and has good discriminant validity [39, 42].
Colquitt’s Organizational Justice Measure (OJM)
Organizational Justice was measured using the 20-item OJM [43], which comprises four subscales: sense of procedural fairness, distributive fairness, interpersonal fairness, and informational fairness. Each item is rated on a 5-point Likert scale from 1 (Strongly disagree) to 5 (Strongly agree), with total scores ranging from 20 to 140 and higher scores indicating better perceived organizational justice [44]. The OJM has well documented psychometric properties, its Cronbach’s α was 0.95 [44], and has good construct validity [43].
Inclusive Leadership Scale (ILS)
Inclusive Leadership was measured using the 9-item ILS [33], which comprises three subscales: openness, accessibility, and availability. Each item is rated on a 5-point Likert scale from 1 (Strongly disagree) to 5 (Strongly agree), with total scores ranging from 9 to 45 and higher scores indicating better sense of inclusive leadership. The ILS has well documented psychometric properties, its Cronbach’s α was 0.92 [45], and shows good validity [46].
10-item Connor-Davidson Resilience Scale (CD-RISC-10)
Resilience was measured using the 10-item CD-RISC-10 [47‐49]. Each item is rated on a 5-point Likert scale from 0 (never) to 4 (very often), with total scores ranging from 0 to 40 and higher scores indicating higher resilience. The CD-RISC-10 has well documented psychometric properties, its Cronbach’s α was 0.94 [50], and has satisfactory validity [51].
Dysexecutive Questionnaire (DEX)
Dysexecutive was measured using the 20-item DEX [52, 53], which comprises five subscales: inhibition, intentionality, knowing-doing dissociation, in-resistance, social regulation. Each item is rated on a 5-point Likert scale from 0 (never) to 4 (very often), with total scores ranging from 0 to 80 and a higher score indicating higher frequency of dysexecutive behavior in daily life. The ILS has well documented psychometric properties, its Cronbach’s α was 0.88 [54], and has well validity [55, 56].
Traumatic experiences
Referring to the results of Okoli et al.‘s [57] open-ended questioning of nurses’ traumatic experiences and the original questionnaire constructed by Tedeschi and Calhoun [39], the present study provided participants with a single entry to find out if they had had any other traumatic experiences that may have affected their post-traumatic growth. Questions cover the following traumatic events: (i) Loss of a family member or friend (e.g., a friend or family member commits suicide or loses them to a serious illness); (ii) Accidents or natural disasters or community violence (e.g., a car accident or encounter with war violence or an earthquake/tornado; community violence includes, but is not limited to, domestic violence, street fights, shootings, etc.); (iii) Serious personal illness (e.g., traumatic surgery/long-term illness or mental health crisis); (iv) Relationship difficulties (e.g., separation/divorce or domestic violence); (v) Sexual abuse/rape; (vi) Family member illness (e.g. caring for a family member with a severe disability or terminal illness); (vii) Family/personal stress (e.g., unemployment/layoff or financial stress); (viii) Undisclosed. This tool was only used as a screening tool in this study, so the results are not detailed in the text.
Data collection
Data were collected between February, 2023 ~ March, 2024 in eight tertiary hospital in Shandong Province. The researchers distributed questionnaires (electronic version) via “Questionnaire Star” platform online. The questionnaire did not require nurses to provide the identified information (Such as name, ID). The participants were informed of the purpose and procedure of the study, and were notified of their right to leave the study at any time and to refrain from answering any questions. Before the study began, informed consent form in electronic form was obtained from all participants, which indicated that they completely understood the study procedures.
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Statistical analysis
Statistical analysis was completed using the Statistical Package for the Social Sciences (SPSS) version 24.0 (SPSS Inc.). Frequency and percentage are used to describe ordinal and categorized variables, such as sex; The means and standard deviations (M ± SD) are used to describe continuous variables whose data are in accordance with normal distribution, such as PTG; The t-test was used to evaluate if there is a statistically significant difference in PTGI-SF scores between two groups that were divided by sex or other characteristics; Analysis of variance (ANOVA) was used to analyze the differences in PTGI-SF scores between three or more groups; Once significant differences in the means have been found, Post hoc comparisons can provide further insight into the specific differences between the groups. Pearson’s correlation was applied to explore the correlation between PTG and other promising factors. If the Kolmogorov-Smirnov test demonstrates that PTG scores do not follow a normal distribution (p < 0.05), we will validate the between-group differences using the Mann-Whitney rank sum test and the Kruskal-Wallis rank sum test. All statistical tests were two-tailed and statistical significance for all analyses was set at 0.05.
Ethical considerations
This study was carried out in accordance with the Declaration of Helsinki. Institutional Review Board approval (approval number is hidden for anonymous review) was obtained from the medical institution where the study was executed.
Results
Common method bias
A Harman one-way test was used to test for possible common method bias in the administration of the test. After excluding sociodemographic characteristics, an exploratory factor analysis with rotation was performed on all questions. A total of seven factors were analyzed with the criterion of characteristic root greater than 1. The variance explained by the maximum factor variance was 26.615%, which did not exceed the critical value of 40%. It can be assumed that there is no serious common source bias in the administration of the test.
Descriptive statistics
A total of 3218 questionnaires were collected, for a return rate of 88.19% (2838). After excluding nurses who did not meet the inclusion criteria or questionnaires of low quality, 1190 HV-exposed nurses were enrolled in this study. The flowchart is shown in Fig. 2. These included 78 (6.6%) male and 1112 (93.4%) female, with a mean age of 35.11 ± 6.52 years and a median length of service of 10 (7, 16). The descriptive statistics for all study variables are shown in Table 1.
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Fig. 2
Flow charts on inclusion of studies
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Table 1
Sociodemographic characteristics of HV-exposed nurses and the scores of PTG (n = 1190)
Variables | n(%) | M ± SD | t/F | p |
|---|---|---|---|---|
Sex | 2.430 | 0.995 | ||
Male | 78(7.0) | 18.93 ± 1.61 | ||
Female | 1112(93.0) | 18.26 ± 0.43 | ||
Marriage | 1.295a | 0.270 | ||
Unmarried | 190(15.97) | 17.54 ± 0.98 | ||
Married | 969(81.42) | 18.41 ± 0.46 | ||
Divorced | 16(1.34) | 18.06 ± 3.69 | ||
Widowed | 4(0.33) | 33.50 ± 6.14 | ||
Other | 11(0.08) | 17.09 ± 4.28 | ||
Children | 1.438a | 0.230 | ||
No children | 282(23.69) | 17.14 ± 0.79 | ||
1 child | 524(44.03) | 18.21 ± 0.66 | ||
2 children | 375(31.51) | 19.21 ± 0.72 | ||
> 2 children | 9(0.75) | 22.89 ± 5.60 | ||
Educational Background | 4.587a | < 0.01 | ||
Technical secondary school degree | 1(0.1) | - | ||
Junior college degree | 58(4.9) | 22.22 ± 1.73 | ||
Undergraduate degree | 1081(90.8) | 17.83 ± 0.44 | ||
Postgraduate degree | 50(4.2) | 24.06 ± 2.03 | ||
Department | 2.589a | < 0.01 | ||
Internal medicine ① | 371(31.2) | 16.70 ± 0.73 | ||
Surgery ② | 319(26.8) | 18.32 ± 0.79 | ||
Obstetrics & Gynecology ③ | 49(4.1) | 17.14 ± 2.26 | ||
Pediatrics ④ | 50(4.2) | 23.68 ± 1.82c | ||
Intensive Care Unit ⑤ | 226(19.0) | 18.72 ± 0.93 | ||
Emergency room ⑥ | 85(7.1) | 20.20 ± 1.72d | ||
Outpatient medical technology system ⑦ | 54(4.5) | 16.67 ± 1.74 | ||
Ophthalmology ⑧ | 3(0.3) | 10.00 ± 10.00 | ||
Other departments ⑨ | 33(2.8) | 25.48 ± 2.69b | ||
Occurrence and severity of HV
The prevalence of HV within eight tertiary hospitals in Shandong Province amounted to 45.03%. Among the 1190 HV-exposed nurses, 1105 (38.93%) encounter bullies who experienced HV occasionally/monthly and 85 (2.99%) encounter severe bullies who experienced HV weekly. In addition, we also attempted to analyze possible inter-group differences in sociodemographic characteristics and individual internal and external resource scores on severity of HV, the results of which can be found in Supplementary Materials.
As for the type of HV, 1,142 nurses (95.96%) experienced overt HVs, while 714 nurses (60.00%) experienced covert HVs, and 666 nurses (55.96%) experienced both. When focusing on the frequency of occurrence, the results showed that “Someone withholding information which affects your performance”, “Having your opinions ignored”, “Spreading of gossip and rumours about you” and “Given too much responsibility without appropriate supervision” were the four types of HVs with highly prevalence, all of which were covert HVs, as shown in Table 2 for the specific rankings.
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Table 2
The occurrence of 19 types of nurse-to-nurse horizontal violence
Dimensions | Items | M | SD | Score for items(n%) | Total | Rank | |||
|---|---|---|---|---|---|---|---|---|---|
2 | 3 | 4 | 5 | ||||||
Covert | Someone withholding information which affects your performance | 1.71 | 0.77 | 551(46.3) | 79(6.6) | 34(2.9) | 8(0.7) | 1515 | 1 |
Covert | Having your opinions ignored | 1.66 | 0.72 | 553(46.5) | 71(6.0) | 24(2.0) | 6(0.5) | 1445 | 2 |
Covert | Spreading of gossip and rumours about you | 1.66 | 0.76 | 516(43.4) | 73(6.1) | 34(2.9) | 6(0.5) | 1417 | 3 |
Covert | Given too much responsibility without appropriate supervision | 1.59 | 0.88 | 346(29.1) | 83(7.0) | 34(2.9) | 21(1.8) | 1182 | 4 |
Covert | Being ordered to do work below your level of competence | 1.53 | 0.80 | 344(28.9) | 81(6.8) | 30(2.5) | 10(0.8) | 1101 | 5 |
Covert | Having key areas of responsibility removed or replaced with more trivial or unpleasant tasks | 1.53 | 0.81 | 341(28.7) | 74(6.2) | 32(2.7) | 12(1.0) | 1092 | 6 |
Overt | Being humiliated or ridiculed in connection with your work | 1.51 | 0.76 | 353(29.7) | 67(5.6) | 30(2.5) | 7(0.6) | 1062 | 7 |
Overt | Being shouted at or being the target of spontaneous anger | 1.51 | 0.76 | 343(28.8) | 77(6.5) | 28(2.4) | 6(0.5) | 1059 | 8 |
Covert | Being ignored or excluded | 1.49 | 0.74 | 341(28.7) | 69(5.8) | 30(2.5) | 3(0.3) | 1024 | 9 |
Covert | Practical jokes carried out by other nurse you do not get along with | 1.47 | 0.73 | 344(28.9) | 62(5.2) | 23(1.9) | 6(0.5) | 996 | 10 |
Covert | Pressure not to claim something to which by right you are entitled (e.g. sick leave, holiday entitlement, travel expenses) | 1.48 | 0.78 | 301(25.3) | 79(6.6) | 23(1.9) | 11(0.9) | 986 | 11 |
Overt | Repeated reminders of your errors or mistakes | 1.43 | 0.72 | 296(24.9) | 65(5.5) | 24(2.0) | 4(0.3) | 903 | 12 |
Overt | Having insulting or offensive remarks made about your person, attitudes or your private life | 1.41 | 0.73 | 260(21.8) | 68(5.7) | 24(2.0) | 5(0.4) | 845 | 13 |
Overt | Persistent criticism of your errors or mistakes | 1.37 | 0.70 | 233(19.6) | 62(5.2) | 22(1.8) | 4(0.3) | 760 | 14 |
Overt | Being the subject of excessive teasing and sarcasm | 1.36 | 0.69 | 224(18.8) | 62(5.2) | 20(1.7) | 4(0.3) | 734 | 15 |
Covert | Excessive monitoring of your work | 1.36 | 0.73 | 210(17.6) | 59(5.0) | 22(1.8) | 9(0.8) | 730 | 16 |
Covert | Hints or signals from others that you should quit your job | 1.26 | 0.64 | 135(11.3) | 57(4.8) | 17(1.4) | 3(0.3) | 524 | 17 |
Overt | Threats of violence or physical abuse or actual abuse such as pushing or spitting on you | 1.26 | 0.66 | 121(10.2) | 58(4.9) | 20(1.7) | 4(0.3) | 516 | 18 |
Overt | Being intimidated by other nurses | 1.25 | 0.64 | 113(9.5) | 55(4.6) | 20(1.7) | 3(0.3) | 486 | 19 |
3.4 Demographic factors influencing PTG among HV-exposed nurses
On average, the PTGI-SF score was 18.30 ± 14.33. The PTGI-SF score of HV-exposed nurses was statistically significantly different among nurses with different departments (F = 2.589, p < 0.01) and educational background (F = 4.587, p < 0.01). In the correlation analysis, there was a non-significant negative correlation between PTG and age (r = -0.034, p = 0.740), length of service (r = -0.051, p = 0.651), as detailed in Table 3. Post hoc comparisons showed that HV-exposed nurses in other departments had significantly higher PTG than nurses in internal medicine, surgery, obstetrics and gynecology, intensive care units, and outpatient medical technology systems; HV-exposed nurses in pediatrics had significantly higher PTGs than nurses in internal medicine, surgery, obstetrics and gynecology, intensive care units, and outpatient medical technology systems; HV-exposed nurses in the emergency departments had significantly higher PTGs than internal medicine nurses at baseline, as detailed in Table 1.
3.5 Correlation between the PTG and resources of HV-exposed nurses
The mean scores for resilience, dysexecutive, organizational justice, and inclusive leadership were 25.89 ± 6.22, 32.17 ± 26.24, 96.25 ± 21.78, and 35.91 ± 6.80 for HV-exposed nurses, respectively. In the correlation analysis, we found that PTG was significantly correlated with resilience (r = 0.120, p < 0.01), and dysexecutive (r =-0.069, p < 0.05), while it was not significantly correlated with inclusive leadership (r = 0.021, p > 0.05), and perceived organizational justice (r = 0.030, p > 0.05), as detailed in Table 3.
Table 3
Results of correlation analysis of baseline data for HV-exposed nurses
Variables | M ± SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
|---|---|---|---|---|---|---|---|---|
1.Age | 35.11 ± 6.52 | 1 | ||||||
2.Length of services | 12.18 ± 7.63 | 0.860** | 1 | |||||
3.PTG | 18.30 ± 14.33 | -0.034 | -0.051 | 1 | ||||
4.Resilience | 25.89 ± 6.22 | 0.169** | 0.146** | 0.120** | 1 | |||
5.Dysexecutive | 32.17 ± 26.24 | -0.156** | -0.132** | -0.069* | -0.366** | 1 | ||
6.Organizational justice | 96.25 ± 21.78 | 0.025 | -0.021 | 0.030 | 0.354** | -0.121** | 1 | |
7.Inclusive leadership | 35.91 ± 6.80 | 0.070* | 0.040 | 0.021 | 0.341** | -0.225** | 0.635** | 1 |
3.6 A multiple linear stepwise regression analysis of influencing factors on the PTG of HV-exposed nurses
To ensure a stable model, departments, educational background, resilience, and dysexecutive were included in a multiple linear stepwise regression based on the results of the t test, ANOVA and correlation analysis. A multiple linear stepwise regression provided the degree of variance in PTGI-SF scores of HV-exposed nurses that could be accounted for by influencing factors. The results showed that resilience, dysexecutive, educational background and type of departments may be the influencing factors of PTG (R2 = 0.045), as shown in Tables 4 and 5.
Table 4
Multiple linear stepwise regression analysis of influencing factors of PTG of HV-exposed nurses
Variables | b(95%CI) | SE | b’ | t value | p value |
|---|---|---|---|---|---|
(Constant) | 17.643(12.963,22.323) | 2.385 | - | 7.397 | < 0.001 |
Resilience | 0.267(0.135,0.398) | 0.067 | 0.116 | 3.972 | < 0.001 |
Dysexecutive | -0.043(-0.074,-0.011) | 0.016 | -0.078 | -2.661 | < 0.01 |
Educational background = Undergraduate degree a | -4.889(-7.672,-2.106) | 1.419 | -0.098 | -3.446 | < 0.01 |
Department = Pediatrics b | 4.174(0.147,8.200) | 2.052 | 0.058 | 2.034 | < 0.05 |
Department = Internal medicine b | -1.934(-3.687,-0.180) | 0.894 | -0.063 | -2.164 | < 0.05 |
Table 5
Explanation of the assignment of influencing factors of PTG in HV-exposed nurses
Variables | Assignments | |
|---|---|---|
Marriage | ||
Unmarried | Unmarried = 1, Married = 0, Divorced = 0, Widowed = 0, Other = 0 | |
Married | Unmarried = 0, Married = 0, Divorced = 0, Widowed = 0, Other = 0 | |
Divorced | Unmarried = 0, Married = 0, Divorced = 1, Widowed = 0, Other = 0 | |
Widowed | Unmarried = 0, Married = 0, Divorced = 0, Widowed = 1, Other = 0 | |
Other | Unmarried = 0, Married = 0, Divorced = 0, Widowed = 0, Other = 1 | |
Educational Background | ||
Technical secondary school degree (Tss.) | Tss. =1, Jc. =0, Und.=0, Pos. =0 | |
Junior college degree (Jc.) | Tss. =0, Jc. =1, Und. =0, Pos.=0 | |
Undergraduate degree (Und.) | Tss.=0, Jc. =0, Und. =1, Pos.=0 | |
Postgraduate degree (Pos.) | Tss. =0, Jc. =0, Und. =0, Pos.=0 | |
Department | ||
Internal medicine (Int.) | Int.=1, Sur.=0, OG = 0, Ped.=0, ICU = 0, Eme.=0, OMTS = 0, Oph.=0, Oth.=0 | |
Surgery (Sur.) | Int.=0, Sur.=1, OG = 0, Ped.=0, ICU = 0, Eme.=0, OMTS = 0, Oph.=0, Oth.=0 | |
Obstetrics & Gynecology (OG) | Int.=0, Sur.=0, OG = 1, Ped.=0, ICU = 0, Eme.=0, OMTS = 0, Oph.=0, Oth.=0 | |
Pediatrics (Ped.) | Int.=0, Sur.=0, OG = 0, Ped.=1, ICU = 0, Eme.=0, OMTS = 0, Oph.=0, Oth.=0 | |
Intensive Care Unit (ICU) | Int.=0, Sur.=0, OG = 0, Ped.=0, ICU = 1, Eme.=0, OMTS = 0, Oph.=0, Oth.=0 | |
Emergency room (Eme.) | Int.=0, Sur.=0, OG = 0, Ped.=0, ICU = 0, Eme.=1, OMTS = 0, Oph.=0, Oth.=0 | |
Outpatient medical technology system (OMTS) | Int.=0, Sur.=0, OG = 0, Ped.0, ICU = 0, Eme.=0, OMTS = 1, Oph.=0, Oth.=0 | |
Ophthalmology (Oph.) | Int.=0, Sur.=0, OG = 0, Ped.=0, ICU = 0, Eme.=0, OMTS = 0, Oph.=1, Oth.=0 | |
Other departments (Oth.) | Int.=0, Sur.=0, OG = 0, Ped.=0, ICU = 0, Eme.=0, OMTS = 0, Oph.=0, Oth.=0 | |
Discussion
The results of this study showed that the incidence of HV was at a moderately low level, with covert HV being more common. The PTG of HV-exposed nurses was at a low level, similar to the results of Niu [58], and lower than the results of Zeng et al. [35]. This implies that there is still a large upside for PTG in HV-exposed nurses. One possible explanation is that the negative events that previous studies have focused on, such as threats of intimidation from patients or other personnel, physical assaults, and other types of workplace violence are more serious in comparison with HV. Yet, when the intensity of trauma is within tolerance, individual PTG levels tend to increase along with the intensity of exposure [59]. Therefore, it is possible that workplace violence nurses have higher PTG levels than HV-exposed nurses. Another possible explanation is that previous studies have mostly focused on the neurological nurse population [58, 60], who care for a specific group of patients who are mainly psychiatric abnormalities and who experience verbal or physical aggression during hospitalization. As a result, psychiatric nurses tend to experience relatively high rates of incidence and intensity of workplace violence compared to nurses in other departments [61] and also achieve higher levels of PTG within tolerance.
The results of t-test and ANOVA indicated that there were significant educational background and departmental differences in PTGI-SF scores among HV-exposed nurses. The results of multiple linear stepwise regression analysis further indicated that the PTGI-SF scores of nurses with bachelor’s degree were significantly lower than those of HV-exposed nurses with master’s degree, which is in agreement with Okoli et al. [57]. One possible explanation is that higher educational experiences endowed nurses with clearer perceptions of adversity as well as stronger stress coping skills, leading nurses to quickly adjust themselves to challenges after exposure to HV and helping nurses to achieve renewed growth in HV. As for the departmental differences in the presence of PTG, post hoc comparisons showed that HV-exposed nurses in pediatric, emergency and surgical departments had the top three levels of PTG, which is inconsistent with the results of the study by Zeng [35] et al. One possible explanation is that pediatric, emergency and surgical nurses have higher workloads and their physical and mental health is more severely impaired than in other departments [62]. Therefore, nurses need to learn more about coping with HV and negative emotions, and thus will also gain more experience and skills in coping with interpersonal stress in the workplace, and obtain higher levels of PTG. The results of multiple linear stepwise regression analysis showed that the PTG of HV-exposed nurses in the internal medicine department were significantly lower than those in other departments. However, in reality, studies exploring department type as an influencing factor on PTG in different setting have found a high likelihood of displaying volatile, unstable traits with changes in the environment, due to the imbalance in the proportion of subjects from different departments and the great challenge of homogenizing the administration.
For this reason, the present study did not compare or draw on the results of previous studies to explain this phenomenon, but rather advocated for a dialectical view of the results, focusing on the possibility that differences in other sociodemographic characteristics or resources between medical and non-medical nurses carve out the possibility of departmental differences in the occurrence of PTG. To verify this conjecture, this study further compared other demographic characteristics and resources between medical and non-medical HV-exposed nurses and found significant differences between the two in terms of gender, educational background, dysexecutive, and inclusive leadership scores (Supplementary Table 2). This implies that the departmental differences found in the present study may be attributable to the differences in educational background and dysexecutive that exist between medical and non-medical HV-exposed nurses. Future studies could further validate these findings.
The results pointed out that resilience may be an important intrinsic buffering resource for nurses to be protected from mental anguish after suffering from HV and to gain PTG from it, corroborating Lyu et al.‘s [63] view on resilience. This may be related to the fact that individuals with high levels of resilience are more inclined to assign positive meaning to negative events [64]. For instance, when forced to take over and complete a task that is beyond their competence, nurses with high levels of resilience are more inclined to view the task as a challenge to gain work experience and knowledge, to proactively assign developmental significance to the event and to gain knowledge and skills from it. As a result, nurses with high levels of resilience tend to experience more new growth as a result of the HV event. Therefore, nursing educators should increase the investment in the cultivation of nurses’ psychological resources, add professional courses on self-psychological construction and debugging for nursing students, and increase the resilience reserve of nurses to reduce the damage of HV exposure to the body and the psyche.
The results pointed out that executive function are one of the cognitive resources that affect nurses’ ability to obtain PTG from work interpersonal adversity, in line with the findings of Eren-Koçak et al. [18]. One possible explanation is that when the severity of dysexecutive is beyond the individual’s ability to tolerate, HV-exposed nurses tend to overdraw their internal positive psychological resources by depleting them due to excessive intensity of reflection, triggering their maladaptation to the negative event, exacerbating the nurse’s level of posttraumatic stress, and making it difficult for them to gain new experiences and grow from the negative experience [65]. Hence, managers should emphasize timely assessment and intervention of HV-exposed nurses’ ability to perform to reduce the damage of HV exposure to nurses’ physical and mental health and the quality of nursing care.
Implications
When rebuilding HV-exposed nurses’ internal reserves of psychological resources and facilitating their PTG, it may be more effective to target internal resources such as resilience and executive function to construct and implement targeted interventions rather than programs that focus on external resources. By recognizing the key influences of resilience and dysexecutive on the PTG, healthcare organizations should invest more funds in encouraging the training of psychological resources and self-tuning courses and seminars to improve nurses’ awareness and coping with HV. Our survey also emphasized the importance of dysexecutive on PTG, which suggests that head nurses should be attentive to strengthening clinical work-related factors that can impact dysexecutive, such as scheduling, identify nurses at risk for dysexecutive in a timely manner, and encourage and support nurses to participate in cognitive intervention programs to promote the acquisition of PTG by HV-exposed nurses, and to maintain the physical and mental health of nurses.
Strength of the study
This study was the first to examine the present status and contributing factors of PTG in HV-exposed nurses. It offered guidelines for identifying these nurses as being at high risk of experiencing a psychological crisis and for enhancing their mental well-being by fortifying their internal and external resource construction.
Limitations of the study
We have to recognize the limitations of the current study. First of all, due to real-world conditions and measurement tool limitations, we were unable to ensure that the duration of exposure to the HV was consistent among nurses. Therefore, we are unable to judge whether there is heterogeneity in the effects of resources on PTG under different lengths of HV exposure. Second, the participants in this study were mainly recruited from hospitals in Shandong Province. Future studies should consider expanding the geographical range of the sample and balancing the selection of participants from different regions. Third, the data collected in the form of self-report questionnaires in this study may cause recall bias due to distorted or incomplete memory. Fourth, the study was a descriptive cross-sectional one, and the causal relationship is not very persuasive. The conclusion that resilience and dysexecutive are related to PTG based on the cross-sectional data is not sufficient to explain the diversity of positive [66], curvilinear [67], or irrelevant [68] relationships between the variables in previous studies, and it does not account for the potential impact of time-dependency on the relationships between the variables. In the future, longitudinal study designs and appropriate data analysis methods are needed to clarify the relationships in depth.
Conclusion and recommendation
This study aims to describe the current state of PTG of HV-exposed nurses and its influencing factors. Overall, exposure to HV posed a moderate risk for nurses, while PTG levels among HV-exposed nurses were low to moderate. The current study suggests that educational background, department type, resilience, and dysexecutive were the main factors influencing PTG in HV-exposed nurses. The study found that resilience had a positive effect on PTG, while dysexecutive had a slight negative effect. Consolidation of resilience and alleviation of dysexecutive, while dialectically looking at educational background and department type, is necessary to improve PTG in HV-exposed nurses.
Acknowledgements
We would like to express our sincere gratitude to Shandong University and our supervisors for their valuable advice and supportive guidance throughout the research process. We would also like to thank the leaderships, head nurses and registered nurses of Qilu Hospital of Shandong Province, Jining People’s Hospital, Linyi People’s Hospital, Heze Municipal Hospital, the Second Affiliated Hospital of First Medical University, Weihai Central Hospital, Qingdao Municipal Hospital, and Laiyang Central Hospital for their critical role in collecting the necessary data. In addition, we are very grateful to the participants in the study and to all the other groups and individuals who contributed their time and energy to make this research possible. Their valuable contributions have played an important role in the success of this research.
Declarations
Ethics approval and consent to participate
This study was carried out in accordance with the Declaration of Helsinki. Institutional Review Board approval (approval number: 2023-R-016) was obtained from School of Nursing and Rehabilitation, Shandong University, the medical institution where the study was executed in China. All study subjects signed an informed consent form prior to participating in the Baseline survey.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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