Depression seriously damage the health of nurses. It is not conducive to the provision of medical services and hospital management. Meanwhile, nurses are a highly vulnerable group to workplace violence (WPV), increasing the risk of depression. Nurses with different personalities may have various views and feelings towards WPV, and their impact on depression may also vary. This study aims to reveal the impact of the five-pattern personality traits of traditional Chinese medicine (TCM) on WPV and depression among nurses, providing a new perspective for managers to implement psychological interventions.
Methods
A cross-sectional study was conducted. 2,788 valid questionnaires nationwide were collected based on Wenjuanxing from June to July 2024. We used Patient Health Questionnaire Depression Scale-9 item, The five- pattern Personality Traits of TCM Scale, and Workplace Violence Scale. We used latent class analysis, structural equation modeling, and simple slope analysis to analyze depression classes, mediating effects, and moderation effects, respectively.
Results
Depression is classified into three types: “Good mental health group” (34.2%), “Moderate depression group” (23.0%), and “Severe depression group” (42.8%). “Taiyang”, “Shaoyang”, and “Balance of Yin-Yang” personalities alleviate nurses’ feelings of WPV, thereby reducing the impact of WPV on depression. The values of mediating effect are -0.402, -0.393, and -0.426, respectively (P < 0.05). “Taiyin” personality exacerbate nurses’ perception of WPV, thereby increasing the impact of WPV on depression. The value of mediating effect is 0.418 (P < 0.05). “Taiyang” and “Shaoyang” personalities reduce the impact of WPV on depression of nurses, and the effect become more significant as the scores increase. The values of moderating effect are 0.033 and -0.0563 respectively (P < 0.05). “Taiyin” and “Shaoyin” personalities increase the impact of WPV on depression, and the effect become more significant as the scores increase. The values of moderating effect are -0.0444 and -0.0220 respectively (P < 0.05).
Conclusions
The prevalence of depression and WPV among Chinese nurses is serious. Excellent personality effectively improve the relationship between WPV and depression. Nursing managers should arrange suitable positions for nurses based on their different personality traits. At the same time, it is necessary to actively cultivate excellent personality traits in nurses to reduce the frequency of WPV and improve their mental health.
Hinweise
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Introduction
By the end of 2023, the total number of registered nurses in China reached 5.63 million, with about 4 registered nurses per 1000 population [1]. Nurses, as the largest professional group in the healthcare industry, play a crucial role in maximizing the efficiency of the healthcare system. However, due to factors such as the doctor-patient relationship, adverse events, heavy workload, and medical risks, nurses often bear immense psychological pressure [2, 3]. Especially as population aging intensifies, the demand for medical services has skyrocketed, further exacerbating nurses’ mental health issues [4]. Depression is the most prevalent psychological issue faced by nurses. International data indicates that the prevalence of depression is generally higher in developing countries, exceeding 34% [5‐8]. In developed countries, there are significant variations in the prevalence of depression among nurses, ranging from 3.8% to 60.5% [9‐15]. According to Chinese data, the prevalence of depression among nurses was 43.8% in 2020 [16] and 86.7% in 2022 [17]. For nurses, depression can increase the risk of cardiovascular and metabolic diseases [18], and premature death [19]. For patients, depression can lead to a decline in the quality of nursing services, including falls and medication errors [20]. For nursing management, depression can lead to an increase in nurse turnover and exacerbate the shortage of human resources in medical institutions [21]. Given the severity of depression among Chinese nurses, identifying factors is crucial.
The Affective Events Theory (AET) emphasizes the focus on the causes of employees’ emotional reactions in the work environment and analyzes its formation mechanism [22]. AET points out that emotional reactions contain mood (happiness/depression) and emotion (thrill/anger), and holds that work events are the direct cause of emotional reactions [22]. As a negative event that nurses often undergo in their work environment, workplace violence (WPV) refers to threats, abuse, or aggressive behavior [23]. WPV is detrimental to their own safety, health, and well-being in the workplace. A study on WPV among 42,222 nurses shows that the pooled prevalence of WPV is 58% [24]. Nursing stuff is one of the high-risk groups of WPV [25]. WPV directly leads to depression among nurses. The frequent occurrence of WPV reduce nurses’ sense of professional identity and work enthusiasm, leading to a series of negative emotions and an increased risk of depression [26]. Research on Chinese healthcare workers indicates that those who have experienced WPV have twice the risk of developing depression compared to those who have not experienced WPV [27].
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AET also suggests that, despite employees’ emotional reactions to work events, their personality predetermines the intensity of their reactions to these events (either very strong or less so) [22]. Personality is a unique physical and mental makeup shaped by the interaction between an individual and their social environment, reflecting their behavior, thought patterns, and emotional traits [28]. Among the factors constituting personality, the psychological structure that can actively trigger or guide human behavior, enabling individuals to respond similarly to different stimuli, is termed as personality trait [28]. According to AET, traits are one of the factors influencing emotional responses [22]. First, traits directly affect employees’ cognitive evaluation of work events, which in turn affects emotional responses. For example, neurotic personality trait contributes to the development of depression [29]. Second, traits can regulate the relationship between work events and emotional responses. For example, employees with highly negative traits are more sensitive to work events, leading to negative emotional reactions [30]. Previous studies indicate that nurses with different personality traits experience varying levels of WPV. Nurses who are less sociable and less tolerant are more exposed to physical violence [31]. Nurses with prosocial personality traits are more likely to experience psychological violence, and nurses with strong autonomous personality traits will experience less physical violence [32]. These are due to the different components of personality traits.
Traditional Chinese Medicine (TCM) emphasizes the “Yin-Yang” five-pattern personality, believing that personality is a functional regulatory system and a psychological reference model [33]. TCM believes that diseases can be treated by adjusting the balance of “Yin” and “Yang”, as well as the circulation of vital energy and blood in the body [34]. According to the different contents of “Yin” and “Yang”, people’s personalities are divided into “Taiyang”, “Shaoyang”, “Taiyin” and “Shaoyin”, and “Balance of Yin-Yang”. “Taiyang” personality is competitive, motivated, and impulsive; “Shaoyang” personality is outgoing, easy-going, and fickle; “Taiyin” personality is pessimistic, suspicious, and anxious; “Shaoyin” personality is calm, restrained, and cautious; “Balance of yin-yang” personality is dignified, flexible, and adaptable [35]. These represent the intensity, flexibility, convergence, persistence, and balance of the reflection on things. The five-pattern personality traits of TCM has been recognized by the academic community and is used to measure personality traits of various groups, which is of great significance for disease diagnosis and treatment, as well as mental health [36]. Previous studies suggest that “Taiyin” personality increase the risk of depression [37, 38]. “Balance of Yin-Yang” personality decrease the risk of depression [37]. There is currently no research on the impact of the the five-pattern personality traits of TCM on WPV.
TCM, as a cultural heritage of the Chinese nation, is the crystallization of valuable medical experience and treatment methods. However, there is currently no research on the impact of the five-pattern personality traits of TCM on WPV and depression among nurses. This study reveals the differences and impacts of nurses’ personality traits by analyzing the relationships and pathways among three factors, providing a reference for disease research from the perspective of personality psychology in TCM.
Based on AET, this study hypothesizes:
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(1)
Nurses with “Taiyang”, “Shaoyang”, and “Balance of Yin-Yang” personalities will experience less WVP, thereby reducing depression. Nurses with “Shaoyin” and “Taiyin” personalities will experience more WVP violence, increasing depression.
Therefore, we assume that WVP mediates the relationship between the five-pattern personality traits of TCM and depression. The hypothetical model is shown in Fig. 1-(1).
Fig. 1
Theoretical framework based on AET in this study
×
(2)
When faced with the same level of WVP, “Taiyang”,
“Shaoyang”, and “Balance of Yin-Yang” personalities will reduce the impact of WVP on depression. “Shaoyin” and “Taiyin” personalities will increase the impact of WVP on depression.
Therefore, we assume that the five-pattern personality traits of TCM moderate the relationship between WVP and depression. The hypothetical model is shown in Fig. 1-(2).
Materials and methods
Study design
A cross-sectional study based on Wenjuanxing from June to July 2024 (https://www.wjx.cn) was conducted nationwide. Wenjuanxing is a professional online survey platform. Compared with traditional survey methods and other survey websites, Wenjuanxing has the advantages of being fast, easy to use, and low-cost, and has been widely used by scholars. We sent the online questionnaire link to the hospital nurses’ work platform and invited them to participate anonymously in this survey. In order to ensure the sample size as much as possible, the questionnaire link was resent to the work platform every 7 days to remind nurses to participate in this survey. Each questionnaire required the informed consent of the nurses before being answered. All collected data was managed through the Wenjuanxing platform.
Estimation of sample size
This study adopted the sample size calculation formula for cross-sectional studies:n = z2p(1-p)/d2. Based on the principle of P < 0.05 in statistical testing, z was set as 1.96, and allowable error (d) was set as 0.1p. p represents the prevalence of depression. The prevalence of depression among nurses in China ranges from 18.6% to 86.7% [16, 17]. p was set as 0.186 in order to include more research subjects. The sample size was calculated as 1681. To prevent too many invalid questionnaires, we increased the number of questionnaires by 30%, and we should include at least 2185 participants. Finally, after excluding questionnaires with insufficient response time and completely repetitive answers, we selected 2788 participants.
Inclusion criteria for research subjects: (1)Voluntary participation in this study; (2)Obtained nursing qualification certificate; (3)Age > 18 years old; (4)Nurses who are currently employed. Exclusion criteria for research subjects: (1)Individuals who have previously been diagnosed with depression and are currently receiving treatment; (2)Individuals with mental disorders, neurological disorders, tendencies towards personality disorders or personality disorders: (3) Individuals who are experiencing drug abuse or alcohol dependence; (4)Individuals who have received psychological or psycho-therapeutic treatment within the past year.
Measurement
Measurement of depression
We adopted the Patient Health Questionnaire Depression Scale-9 item (PHQ-9) [39]. The PHQ-9 contains nine questions, which describes the frequency of symptoms in the past two weeks, and uses a 0-3 level scoring system (0 = None; 1 = Few days; 2 = More than half of the time; 3 = Almost every day). The total score is obtained by adding all the items, ranging from 0 to 27. The higher the score, the more severe the depression. In our study, we used latent class analysis as the basis for distinguishing depressive characteristics among nurses. In China, the PHQ-9 is widely employed in nurses, teenagers, elderly, and patients with demonstrated reliability and validity. In this study, the internal consistency reliability results between the items show that the Cronbach’s coefficient is 0.946, and the correlation coefficient between the scores of each item ranges from 0.537 to 0.740 (P < 0.05), indicating that the scale used in this study has good reliability. The discriminant validity shows that there is a significant difference in the total PHQ-9 score among the three groups of nurses with good mental health, moderate depression, and severe depression (F = 16,885.812, P < 0.001). Through exploratory factor analysis (EFA) in construct validity, each item in the PHQ-9 scale has a good burden on the main factor (0.744-0.878), and confirmatory factor analysis (CFA) show that the χ2/df is 2.166, the RMSEA is 0.053, and the GFI, IFI, TLI, and CFI indices are greater than 0.90, indicating that the scale used in this study has good validity.
Measurement of the five-pattern personality traits of TCM
This study used the Five-Pattern Personality Traits of TCM Scale (simplified version) developed by Yang and Xue [40] and simplified by Wang [41]. It includes five dimensions: Taiyang (9 items), Shaoyang (9 items), Balance of Yin-Yang (7 items), Shaoyin (9 items), and Taiyin (9 items), with a total of 43 items. All questions are answered with “Yes” or “No” (0 = No; 1 = Yes), and a high score in a certain factor indicates a stronger tendency towards personality traits. A high score of Taiyang indicates subjectivity, impulsiveness, and ambition. A high score of Shaoyang indicates agility, optimism, and wit. A high score of Balance of Yin-Yang indicates a calm attitude, strong adaptability, and a peaceful mentality. A high score of Shaoyin indicates coldness, high vigilance, and caution. A high score of Taiyin indicates overthinking, timidity, and indecisiveness. In China, the Five-Pattern Personality Traits of TCM Scale (simplified version) is widely employed in nurses, college student, patients with chronic diseases with demonstrated reliability and validity.
In this study, the internal consistency reliability results among the five dimensional items show that the Cronbach’s coefficient are 0.976, 0.937, 0.948, 0.923, and 0.911, respectively, and the correlation coefficient between the scores of each item in the five dimensional range from 0.498 to 0.739, 0.424 to 0.715, 0.399 to 0.689, 0.419 to 0.763, and 0.408 to 0.768 (P < 0.05), respectively, indicating that the scale used in this study has good reliability. Through EFA in construct validity, each item in the five dimensional has a good burden on its main factor (0.468-0.866), and CFA show that the χ2/df are less than 3; the RMSEA are less than 0.08, and the GFI, IFI, TLI, and CFI indices are greater than 0.90, indicating that the scale used in this study has good validity.
Measurement of workplace violence
We used the Workplace Violence Scale (WVS) [42], localized by Chinese scholar PX Wang [43], to investigate the WPV experienced by nurses in the past year. The scale includes five types (items) and frequency of physical attacks, emotional abuse, threats and intimidation, verbal harassment, and physical harassment. The scoring method for each item is 0 points for not experiencing this type of violence, 1 point for experiencing 1 time, 2 points for 2–3 times, and 3 points for 4 times or more, with a total score range of 0–15 points. In China, the WVS is widely employed in medical, nursing, and psychiatric care settings with demonstrated reliability and validity. In this study, the internal consistency reliability results between the items show that the Cronbach’s coefficient is 0.933, and the correlation coefficient between the scores of each item ranges from 0.680 to 0.783 (P < 0.05), indicating that the scale used in this study has good reliability. The discriminant validity shows that there is a significant difference in the total WVS score among the four groups of nurses with No, 1 time/year, 2–3 times/year, and ≥ 4times/year (F = 21,660.722, P < 0.001). Through EFA in construct validity, each item in the WVS scale has a good burden on the main factor (0.867–0.903), and CFA show that the χ2/df is 2.85; the RMSEA is 0.089, and the GFI, IFI, TLI, and CFI indices are greater than 0.90, indicating that the scale used in this study has good validity.
Measurement demographic and working factors
Demographic factors included age, marital status (“single” or “married”), education level (“undergraduate” or “postgraduate”), title (“primary” or “intermediate or above”), monthly income (“satisfied” or “dissatisfied”), physical exercise (“No”, “1 time/week”, “2 times/week”, and “ ≥ 3 times/week”). Working factors included night duty (“Yes” or “No”), working years (“ ≤ 1”, “1 ~ 5”, “6 ~ 10”, “11 ~ 20”, and “ ≥ 21”), hospital level (“first level hospital”, “secondary hospital”, and “tertiary hospital”), department (“clinical” or “non clinical”), employment method (“formal incorporation”, “contract nurses”, and “labor dispatching”).
Statistical analysis
First, SPSS 26.0 software was used to analyze the data. Count data was presented in the form of frequency and percentage. Quantitative data that follows a normal distribution were presented in the form of mean and standard deviation. The linear correlation between variables was analyzed using Pearson correlation analysis. Second, Mplus 8.3 software was used to establish a latent class model. The evaluation indicators for optimal model fitting include: (1) Akaike Information Criterion (AIC), a standard for measuring the goodness of fit of statistical models; (2) Bayesian Information Criterion (BIC) and adjusted Bayesian Information Criterion (aBIC), considering the magnitude of losses caused by misjudgments. (3) Entropy, determining the classification error rate of a model, with a value range of 0-1. (4) Lo Mendel Rubin (LMR) and Bootstrap Likelihood Ratio Test (BLRT), determining whether the fitting degree increases with the increase of class. Smaller values of AIC, BIC, and aBIC indicate better fitting of the model [44]. The closer the entropy value is to 1, the more accurate the model classification will be [44]. If the p-value of LMR and BLRT are less than 0.05, it indicated that the fit increased with the increase of the classes [45]. Third, Amos 24 software was used to establish the structural equation model (SEM) which examined the mediating role, and used the bias corrected percentile bootstrap method to verify the significance of the mediating effect. If the 95% confidence interval (CI) did not include 0, it indicated that the effect value was statistically significant [46]. In the SEM, WVP was added as a mediator variable, and night duty, physical exercise, and hospital level were added as a control variable. Last, the process plugin in SPSS 26.0 software was used to verify the moderating effect. If the interaction term is statistically significant, it indicates the existence of the moderating effect. Then the simple slope analysis was performed to visualize the interaction terms [47]. This study used a two-sided test, and P < 0.05 was considered statistically significant.
Results
Basic characteristics of participants
A total of 2788 nurses completed this study. The average scores of the five-pattern personality traits of TCM were ranked as follows: Taiyang (5.39 ± 2.68) > Shaoyin (4.63 ± 2.16) > Taiyin (4.23 ± 2.71) > Shaoyang (4.11 ± 2.40) > Balance of Yin-Yang (3.87 ± 2.03). The personality traits of nurses in this study were more inclined towards the Taiyang. The individual and job characteristics of the nurses are detailed in Table 1.
Table 1
Individual and job characteristics of participants(n = 2788)
Variables
Frequency(n)
Percentage(%)
Age (years)
18 ~ 25
365
13.1
26 ~ 30
788
28.3
31 ~ 35
731
26.2
36 ~
904
32.4
Marital status
Single
637
22.8
Married
2151
77.2
Education level
Undergraduate
2036
73.0
Postgraduate
752
27.0
Title
Primary
1947
69.8
Intermediate or above
841
30.2
Monthly income
Satisfied
1505
54.0
Dissatisfied
1283
46.0
Physical exercise
No
612
22.0
1 time/week
605
21.7
2 times/week
577
20.7
≥ 3 times/week
993
35.6
Night duty
Yes
1465
52.5
No
1323
47.5
Working years
≤ 1
460
16.5
1 ~ 5
675
24.2
6 ~ 10
522
18.7
11 ~ 20
693
24.9
≥ 21
438
15.7
Hospital level
First level hospital
549
19.7
Secondary Hospital
1333
47.8
Tertiary hospital
906
32.5
Department
Clinical
1440
51.6
Non clinical
1348
48.4
Employment method
Formal incorporation
1042
37.4
Contract nurses
1071
38.4
Labor dispatching
675
24.2
Workplace violence
No
678
24.3
1 time/year
646
23.2
2–3 times/year
370
13.3
≥ 4times/year
1094
39.2
Physical attack
No
1102
39.5
1 time/year
373
13.4
2–3 times/year
626
22.5
≥ 4times/year
687
24.6
Emotional abuse
No
904
32.4
1 time/year
406
14.6
2–3 times/year
869
31.2
≥ 4times/year
609
21.8
Threats and intimidation
No
1093
39.2
1 time/year
277
9.9
2–3 times/year
684
24.5
≥ 4times/year
734
26.3
Verbal harassment
No
1295
46.4
1 time/year
264
9.5
2–3 times/year
634
22.7
≥ 4times/year
595
21.3
Physical harassment
No
1112
39.9
1 time/year
233
8.4
2–3 times/year
964
24.9
≥ 4times/year
749
26.9
The depression status of participants
The fitting indices for latent class models
Table 2 shows the fitting indices of the different latent class models. Firstly, we excluded the 4-class, 5-class, and 6-class models. Although the AIC, BIC, and aBIC of them were lower than other models, the sample size included in the group was too small. Secondly, we excluded the 2-class model. Although the Entropy values of it was higher than that of the 3-class model, it was only divided into two classes, which had little practical significance. Therefore, this study selected the 3-class model as a ideal model.
Table 2
Comparison of the fitting indices for latent class models
Models
AIC
BIC
aBIC
Entropy
LMR(P)
BLRT(P)
Class Probability(%)
1
77,104.161
77,210.956
77,153.764
2
59,624.167
59,790.293
59,701.328
0.960
< 0.001
< 0.001
49.3/50.7
3
55,249.334
55,474.791
55,354.052
0.952
< 0.001
< 0.001
34.2/23.0/42.8
4
53,927.962
54,212.750
54,060.238
0.961
< 0.001
< 0.001
33.9/14.2/9.3/42.6
5
53,063.805
53,407.924
53,223.638
0.933
< 0.001
< 0.001
17.2/20.3/13.3/7.2/42.0
6
52,440.318
52,843.767
52,627.709
0.938
< 0.001
< 0.001
17.8/19.8/6.0/7.4/6.8/42.2
P < 0.05 was considered statistically significant
Latent class plot
The latent classes of depression are shown in Fig. 2. Class-1, with scores less than 0.8 for each component of depression and a average score of 3.93 ± 2.86, was named “Good mental health group”, accounting for 34.2% of the participants (954/2788). Class-2, with scores around 1.4 for each component of depression and a average score of 12.17 ± 2.38, was named “Moderate depression group”, accounting for 23.0% of the participants (641/2788). Class-3, with scores around 2.5 for each component of depression and a average score of 22.42 ± 1.77, was named “Severe depression group”, accounting for 42.8% of the participants (1193/2788).
Fig. 2
Latent class plot based on the nine components of depression
×
Correlation analysis between variables
The correlation between variables should be tested before establishing a single mediation model. Table 3 shows that Taiyang, Shaoyang, and Balance of Yin-Yang were significantly negatively correlated with depression (P < 0.01) and WPV (P < 0.01) respectively. Shaoyin, Taiyin, and WPV were significantly positively correlated with depression (P < 0.01). Taiyin was significantly positively correlated with WPV(P < 0.01). Shaoyin was not correlated with WPV (P > 0.05), indicating that there was no mediating effect.
Table 3
Correlation analysis between variables
Variables
1
2
3
4
5
6
7
Taiyang
1
Shaoyang
0.602**
1
Balance of Yin-Yang
0.641**
0.685**
1
Shaoyin
−0.021
0.115**
0.071**
1
Taiyin
−0.448**
−0.417**
−0.446**
−0.009
1
WPV
−0.634**
−0.513**
−0.616**
0.033
0.558**
1
Depression
−0.770**
−0.592**
−0.713**
0.103**
0.632**
0.868**
1
**P < 0.01. P < 0.05 was considered statistically significant
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Mediating effect test
Route analysis
Table 4 shows the effects of Taiyang, Shaoyang, Balance of Yin-Yang, and Taiyin on WPV were significant (P < 0.01), and the effect of WPV on depression was significant (P < 0.01). The direct effects of Taiyang, Shaoyang, Balance of Yin-Yang, and Taiyin on depression were all significant(P < 0.01), indicating that WPV partially mediated the relationship between Taiyang, Shaoyang, Balance of Yin-Yang, Taiyin, and depression.
Table 4
Route analysis between variables
Path
Path coefficient
SE
Standardization
Path coefficient
C.R
P
Taiyang
Taiyang
→
WPV
−1.276
0.030
−0.634
−43.225
< 0.001
WPV
→
Depression
0.993
0.016
0.635
63.906
< 0.001
Taiyang
→
Depression
−1.160
0.031
−0.368
−37.033
< 0.001
Shaoyang
Shaoyang
→
WPV
−1.153
0.037
−0.513
−31.561
< 0.001
WPV
→
Depression
1.199
0.016
0.766
74.575
< 0.001
Shaoyang
→
Depression
−0.699
0.036
−0.199
−19.338
< 0.001
Balance of Yin-Yang
Balance of Yin-Yang
→
WPV
−1.642
0.040
−0.616
−41.229
< 0.001
WPV
→
Depression
1.082
0.017
0.692
65.212
< 0.001
Balance of Yin-Yang
→
Depression
−1.196
0.044
−0.287
−27.026
< 0.001
Taiyin
Taiyin
→
WPV
1.110
0.031
0.558
35.478
< 0.001
WPV
→
Depression
1.171
0.017
0.749
70.879
< 0.001
Taiyin
→
Depression
0.667
0.033
0.214
20.273
< 0.001
Night duty, physical exercise, and hospital level were added as a control variable in the SEM
P < 0.05 was considered statistically significant
Mediating effect model
The goodness of fit test of the four models shows that the relative chi square (chi square/degree of freedom) of each model is less than 3, and the root mean square approximation error (RMSEA) of each model is less than 0.08. The Goodness of Fit Index (GFI), the Comparative Fit Index (CFI), the Incremental Fit Index (IFI), the Normed Fit Index (NFI), and the Tucker-Lewis Index (TLI) of each model is higher than 0.90. Therefore, each model in this study has a good and appropriate fit.
Figure 3 shows the mediation effect value. In Fig 3-1, the direct effect of the Taiyang on depression was -0.368, the total effect was -0.770, the indirect effect of WPV was -0.402, and the mediating effect accounted for 52.2%. In Fig 3-2, the direct effect of the Shaoyang on depression was -0.199, the total effect was -0.592, the indirect effect of WPV was -0.393, and the mediating effect accounted for 66.4%. In Fig 3-3, the direct effect of the Balance of Yin-Yang on depression was
-0.287, the total effect was -0.713, the indirect effect of WPV was -0.426, and the mediating effect accounted for 59.7%. In Fig 3-4, the direct effect of the Taiyin on depression was 0.214, the total effect was 0.632, the indirect effect of WPV was 0.418, and the mediating effect accounted for 66.1%.
Fig. 3
Mediating effect model
×
Moderating effect test
The analysis results of moderating effect test were shown in Table 5. The moderating effect value (β) of Taiyang, Shaoyang, Taiyin, and Shaoyin personalities on the relationship between WPV and depression are 0.0333, −0.0563, −0.0444, and −0.0186 respectively, and the moderating effects of them are significant (P < 0.05). The moderating effect of Balance of Yin-Yang is not significant (β = −0.0186, P > 0.05).
Table 5
Moderating effect test
Models
Variables
β
SE
P
95%CI
Model 1
Taiyang
−1.1277
0.0319
< 0.001
−1.1903 ~ −1.0652
WPV
0.9950
0.0176
< 0.001
0.9605 ~ 1.0295
Taiyang*WPV
0.0333
0.0056
< 0.001
0.0222 ~ 0.0443
Model 2
Shaoyang
−0.8682
0.0440
< 0.001
−0.9544 ~ −0.7820
WPV
1.1271
0.0202
< 0.001
1.0874 ~ 1.1667
Shaoyang*WPV
−0.0563
0.0087
< 0.001
−0.0733 ~ −0.0392
Model 3
Taiyin
0.6902
0.0328
< 0.001
0.6258 ~ 0.7545
WPV
1.1774
0.0185
< 0.001
1.1413 ~ 1.2136
Taiyin*WPV
−0.0444
0.0058
< 0.001
−0.0557 ~ −0.0330
Model 4
Shaoyin
0.2500
0.0393
< 0.001
0.1730 ~ 0.3271
WPV
1.3628
0.0166
< 0.001
1.3302 ~ 1.3955
Shaoyin*WPV
−0.0220
0.0073
0.0027
−0.0364 ~ −0.0076
Model 5
Balance of Yin Yang
−1.2453
0.0511
< 0.001
−1.3455 ~ −1.1450
WPV
1.0678
0.0195
< 0.001
1.0295 ~ 1.1060
Balance of Yin-Yang*WPV
−0.0186
0.0093
0.0562
−0.0369 ~ 0.0003
P < 0.05 was considered statistically significant
*Represents the interaction item
Simple slope analysis
Figure 4 shows the results of simple slope analysis. The effect of WPV on depression is gradually decreased in the low (− 1SD below the mean), mean, and high (+ 1SD above the mean) groups of Taiyang and Shaoyang respectively, and is gradually increased in the low (− 1SD below the mean), mean, and high (+ 1SD above the mean) groups of Taiyin and Shaoyin respectively.
Fig. 4
Simple slope plot of interaction between WPV on depression. Notes: low,−1 SD below the mean; high,+1SD above the mean
×
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Discussion
Classes of depression among nurses
We found three classes with different characteristics in nurses. They are “Good mental health group”, “Moderate depression group”, and “Severe depression group”. It means that the individual psychology of nurses not only varies in level, but also in structure. The proportion of nurses with moderate to severe depression was 65.8%, similar to previous study [17]. We also found 75.7% of nurses have experienced different types of WPV in the past year, higher than previous study [24]. It might be the reason for severe depression among nurses.
WVP mediates the relationship between the five-pattern personality traits of TCM and depression
We found that personality directly affect depression, or indirectly affect depression through WPV. WPV is a negative work-related event. It can seriously threaten the personal safety of nurses and subsequently damage the mental health. It can lead to cognitive resource depletion, decreased emotional regulation ability, and negative emotions and behaviors, such as depression [48, 49].
The mediating effect between “Yang” personalities and depression
“Taiyang”, “Shaoyang”, and “Balance of Yin-Yang” personality traits alleviate the impact of WPV, thereby reducing depression. The characteristics of “Yang” personality trait are optimism, good communication skills, and good adaptability [33]. Previous study shows that “Taiyang”, “Shaoyang”, and “Balance of Yin-Yang” personality traits were negatively correlated with negative automatic thinking [50]. Therefore, nurses with these three personality traits maintain a positive attitude when facing patients. They may find a good solution when facing medical disputes. Due to the personality traits of nurses, they may not consider certain language and behaviors of patients as signs of WPV [51]. Therefore, they perceive less WPV, which reduces the impact on depression.
The mediating effect between “Yin” personalities and depression
“Taiyin” personality trait exacerbated the impact of WPV, thereby increasing depression. “Taiyin” personality trait is characterized by overthinking, indecisiveness, alienation, and conservatism [33]. Previous study indicates that “Taiyin” personality trait were positively correlated with negative automatic thinking [50]. Therefore, nurses with “Taiyin” personality trait maintain a vigilant attitude when facing patients. They pay more attention to their emotions rather than finding effective communication solutions when facing medical disputes. Due to their unique personality traits, they exhibit more skepticism and sensitivity when communicating with patients [51]. They may perceive certain language and behavior of the patient as a manifestation of WVP. Therefore, they perceive more WPV, which increases the impact on depression.
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The five-pattern personality traits of TCM moderate the relationship between WVP and depression
The moderating effect of “Yang” personalities
“Taiyang” and “Shaoyang” personality traits played negative moderating roles in the impact of WPV on depression. Study suggests that individuals with “Taiyang” and “Shaoyang” personality traits tended to adopt positive coping strategies [52]. Therefore, nurses with “Taiyang” and “Shaoyang” personality traits would persist in positive feedback and self motivation when facing WPV. Positive coping style can alleviate the impact of WPV on depression [53]. The excitatory factor in “Yang” personality trait can help enhance nurses’ emotional resilience and adaptability. They are better able to cope with challenges and pressures. However, excessive excitement can still affect depression [54].
The moderating effect of “Yin” personalities
“Taiyin” and “Shaoyin” personality traits played positive moderating roles in the impact of WPV on depression. Previous study shows that “Yin” personality trait tended to adopt negative coping strategies, such as avoidance and withdrawal [52]. Nurses with “Yin” personality traits tended to have a negative understanding and response to the situation [50]. When faced with WPV, nurses with “Yin” personalities tend to pay more attention to internal negative emotions. They are not good at expressing themselves externally. Therefore, they are prone to giving up opportunities to seek external resources and help, thereby exacerbating depression [30].
This study identified various factors and pathways contributing to nurses’ emotional reactions. However, it solely focused on the impact of personality and WPV on depression, overlooking the influence of organizational factors, work environment, or external support systems on depression. Research suggests that social support, organizational justice, and safety perceptions also influence emotional responses, potentially mitigating the impact of WPV on depression [55]. Secondly, this study only focuses on the emotional mechanism at the individual level, ignoring the complex psychological and situational dynamics of nurses. The inter-group emotional theory suggests that when individuals identify with a specific social group, their emotional experiences towards both internal and external groups undergo changes [56]. For instance, in a harmonious working environment, individuals tend to maintain good relationships with others, fostering a good social atmosphere. Negative workplace behaviors occur not only at individual nurses’ level but also derive from the broader contexts of organizational management and systemic factors [57]. Therefore, in subsequent research, scholars should consider the support systems for nursing staff and the impact of group environmental factors on depression and WPV.
Strengths and limitations
This study reveals for the first time the pathway through which the five-pattern personality traits of TCM affect WPV and depression in nurses. It links the “Yin” and “Yang” of the human body in TCM with WPV, providing new ideas for intervention measures for nurse managers. Several limitations of this study should be considered. First, due to limitations in cross-sectional studies, we are unable to determine the order in which variables occur. We cannot establish causal relationships. Second, due to potential cultural biases in interpreting personality traits and WVP, this may lead to response bias. And there may be cultural limitations in the application of TCM personality abroad. Third, using self-administered questionnaires for online data collection may result in selection bias. Forth, this study selected nurses nationwide, but the sample size was only 2788, which was relatively small. Fifth, the use of multiple statistical software programs may add unnecessary complexity and may make the methodology difficult to replicate.
Implication
The doctor-patient relationship is an indispensable part of nursing work, and personality plays an important role in this relationship. The unique personality of nurses not only affects their way of interacting with others, but also has an impact on communication and conflicts in their interactions. Hospital managers are advised to cultivate excellent personality traits among nurses in order to demonstrate effective solutions when faced medical disputes. This can alleviate the impact of injuries on physical and mental health, especially when the work pressure of nurses in China cannot be rapidly reduced in the short term.
Conclusions
The prevalence of depression and WPV among Chinese nurses is serious. Excellent personality can effectively improve the relationship between WPV and depression. Nursing managers should arrange suitable positions for nurses based on their different personality traits. Nurses with “Yang” personality should involve in medical activities with patients. They are also suitable for the position of medical dispute resolution. Nurses with “Yin” personality are more suitable for positions of administrative positions, research positions, and clinical support positions. At the same time, it is necessary to actively cultivate excellent personality traits in nurses, such as group activities and psychological intervention. Nurses should also establish correct values, broaden their horizons, and face problems with a better mindset.
Acknowledgements
The author would acknowledge all 3000 nurses who participated in this survey, and acknowledge the staffs who help send the questionnaire link to the work platform.
Declarations
Ethics approval and consent to participate
This study was approved by the Research Ethics Committee of China Medical University. All methods were carried out in accordance with Declaration of Helsinki. We protected personal privacy when handling personal data and kept personal records confidential.
Written or verbal informed consent was obtained from all individual participants included in the study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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