Background
Nurses’ mental health has become a common concern worldwide. During the COVID-19 pandemic, depression was significantly more prevalent among nurses compared to the general population [1]. A 2024 review found that approximately 32% of nurses experienced varying degrees of depression during the COVID-19 pandemic [2]. Additionally, a multicenter cross-sectional study conducted in China reported a prevalence of depression among nurses at 25.9% [3]. Depressed mood can adversely affect nurses’ physical health [4], increase the risk of suicide [5], impair work quality, increase the incidence of medical errors [6], lead to burnout, and increase the likelihood of leaving the profession [7].
Diathesis-stress theory is a theoretical model commonly used to explain the onset and development of depression [8]. According to this model, depression arises from the interaction between stressors and individual traits, with stress influencing depression by activating predisposed traits. Stress encompasses both distal stress, such as childhood abuse and neglect, and proximal stress, such as perceived stress. Studies have shown that childhood adversity is a predictor of adulthood depression [9]. A cohort study has reported a dose-dependent relationship between childhood adversity and major depression in adulthood [10]. Given that various adversities often occur simultaneously, it is more ecologically valid to consider their cumulative effects rather than to analyze the independent effects of each adversity. Additionally, perceived stress, a typical form of proximal stress, is significantly associated with a depressed mood. A longitudinal study indicated that perceived stress before the COVID-19 pandemic predicted depressed mood 1–2 years later [11]. The relationship between perceived stress and depression has also been confirmed in a study among healthcare workers [12]. However, whether distal and proximal stress have the same mechanism of influence on depression requires further investigation.
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Coping is an important mediator of psychological stress. Selye’s stress theory posits that, under stress, individuals mobilize their coping resources to maintain a state of inner equilibrium. However, prolonged or excessive stress can deplete coping resources, potentially leading to psychological problems. Studies have confirmed that coping is a mediator between stressors and depression [13]. For example, coping styles mediated the relationship between fear of COVID-19 and depression among frontline nurses [14]. Most studies on coping have been variable-centered, using scale totals to determine coping styles among individuals. This approach often overlooks population heterogeneity and fails to differentiate between subgroups of nurses with different coping profiles. Consequently, a “person-centered” approach is more appropriate. According to Helsper, latent profile analysis (LPA) is a more rigorous method of analysis than cluster analysis [15]. The role of coping profiles in the relationship between stress and depression among nurses has not been adequately studied. Understanding different coping profiles is valuable for hospital administrators to provide targeted interventions and support for the prevention and alleviation of depression among nurses.
Additionally, further exploration is needed into whether coping profiles can serve as mediators in both distal and proximal stress-depression relationships. Childhood adversity and perceived stress differ in terms of stress controllability, magnitude, and duration, which may lead to distinct mechanisms influencing depression.
This study aims to explore whether both childhood adversity and perceived stress predict depression in nurses, examine coping profiles generated by the LPA, and explore how these coping profiles mediate the effects of childhood adversity and perceived stress on depression in nurses.
Methods
Participants and setting
This cross-sectional study utilized convenience sampling to conduct a questionnaire survey among nurses at a tertiary hospital in Fujian Province. The inclusion criteria were as follows: (1) possession of vocational qualification certificates and employment in a hospital setting; (2) absence of dyslexia and ability to communicate fluently in Mandarin; (3) willingness to participate in this study. The exclusion criteria were as follows: (1) diagnosis of a mental disorder; (2) receipt of psychotherapy or antipsychotic medication at the time of the study; (3) nursing students and visiting scholars. The questionnaire, which required complete answers to be submitted, was distributed via the Wenjuanxing platform. Excluding 7 non-clinical nurses, 737 valid samples were obtained.
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The sample size required for the study was analysed using the pwr package in R software, with a predetermined effect size of f2 = 0.02, statistical power 1 – β = 0.8 and a significance level of α = 0.05, indicating that a minimum of 602 subjects were required [16]. The sample size of this study is 737, which meets the requisite sample size.
Measurement tools
Depression
The Patient Health Questionnaire-9 (PHQ-9) was used to assess depression [17]. It consists of nine items, each with a score range of 0–3. The scores for all items were summed to obtain a total score, with higher scores indicating greater levels of depression. Validation and reliability have been confirmed in the Chinese nurse population [18]. The internal consistency coefficient for the PHQ-9 in this study was 0.922.
Perceived stress
Perceived stress levels over the previous month were measured using the Perceived Stress Scale-4 (PSS-4) [19], which has been demonstrated to be a reliable instrument [20].This scale includes four items, each scored from 0 to 4, with items 2 and 3 reversed. The scores of the four items were summed to obtain a total score, with higher scores indicating higher levels of perceived stress. The internal consistency coefficient for the PSS-4 in this study was 0.792.
Adverse Childhood Experiences
The Chinese version of the Revised Adverse Childhood Experience Questionnaire (ACEQ-R) was used to assess the presence of 14 adverse experiences occurring before the age of 18 [21]. These experiences include abuse, neglect, parental separation or divorce, poor family functioning, peer bullying or victimization, and low socioeconomic status. Each item is scored as “0” for no experience and “1” for the presence of the experience. The scores for all 14 items are summed to obtain an individual’s total ACEQ-R score, with higher scores indicating more adverse experiences. Cumulative adversity scores were categorized into three groups: 0 for no childhood adversity, 1 for one type of childhood adversity, and 2 for multiple types of childhood adversity. The Chinese version demonstrated satisfactory reliability and validity [21]. The internal consistency coefficient for the ACEQ-R in this study was 0.874.
Coping styles
The Trait Coping Style Questionnaire (TCSQ) was employed to assess coping styles, consisting of 20 items divided into two dimensions, positive coping and negative coping, with 10 items for each dimension [22]. Each item is scored from 1 to 5. The total score for each dimension is obtained by summing the scores of the 10 items within that dimension, with higher scores indicating more pronounced coping characteristics in the respective dimension. The validity and reliability of the TCSQ have been demonstrated for use with healthcare personnel [23]. The internal consistency coefficient for the TCSQ in this study was 0.904.
Control variables
Data were collected on the following control variables: sex, age, body mass index (BMI), marital status, education, place of residence, years of work, monthly income, physical activity, and presence of illness.
Ethical considerations
All study procedures were approved by the ethics committee of Hospital (No. Quan Yi lun2020253) and were performed in accordance with the ethical standards laid down in the Declaration of Helsinki (as revised in Brazil 2013). All participants were given informed consent and informed of the purpose and procedures of the study.
Data analysis
Descriptive analyses were conducted to characterize the sociodemographic and psychographic features of the sample. Correlations between continuous variables were examined using correlation analyses, while ANOVA was used to investigate differences in the PHQ-9 scores across demographic variables.
The 20 items of the Trait Coping Styles Scale were analyzed as exogenous variables in LPA to identify potential subgroups with different coping profiles. Model fit was assessed using several criteria: the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and adjusted Bayesian Information Criterion (aBIC), with smaller values indicating better model fit; the entropy index, which is often used to evaluate classification accuracy, and its value ranges from 0 to 1, with values closer to 1 indicating higher accurate classification; and the Lo-Mendell-Rubin (LMR) and Bootstrapped Likelihood Ratio Test (BLRT), which compare the fit between models with k-1 and k-categories. Significant LMR and BLRT p-values indicate that the k-category model outperforms the k-1 category model, whereas non-significant values indicate that the k-category model does not significantly improve fit over the k-1 category model.
Unsorted multivariate logistic regression was used to examine the effects of sociodemographic variables, categories of adverse childhood experiences (ACEs), and perceived stress on coping profiles.
Mediation analysis was used to explore the role of coping profiles in the relationship between stress (childhood adversity and perceived stress) and depression.
Latent profile analyses were conducted using Mplus 8.3, mediation analyses were conducted using the Lavaan package in R software, and all other analyses were carried out using SPSS 27.0. The significance level was set at α = 0.05.
Results
Common method bias test
Using Harman’s one-way test, exploratory factor analysis was conducted on all the items of the four questionnaires, and the results revealed 10 common factors with extracted eigenroots greater than 1. The first common factor explained 19.50% of the total variation, which is below the critical threshold of 40%. Thus, there was no substantial common method bias in the measurements.
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Descriptive statistics
The mean age of the 737 nurses was 31.11 ± 6.39 years, mean BMI was 21.40 ± 3.19, and the mean years of work experience was 9.19 ± 7.40 years (Table 1). Of the participants, 717 (97.3%) were female, 489 (66.4%) were “married/cohabiting,” 484 (65.7%) lived in urban areas, 345 (46.8%) had a bachelor’s degree or higher, and 504 (68.4%) had a monthly income more than 4,000 yuan. Additionally, 411 (55.8%) did not engage in physical activity, and 673 (91.3%) had no illness. A total of 574 (77.9%) participants had no childhood adversity, 79 (10.7%) had experienced one type of childhood adversity, and 84 (11.4%) had experienced two or more types.
Table 1
Demographic and clinical characteristics of nurses(N = 737)
Characteristics | ‾x ±ｓ or N (%) | Characteristics | N (%) | ||
|---|---|---|---|---|---|
Age, years | 31.11 ± 6.39 | Monthly income, yuan | ≤ 4000 | 233(31.6%) | |
BMI | 21.40 ± 3.19 | >4000 | 504(68.4%) | ||
Work years | 9.19 ± 7.40 | Physical activity | ≥ 3 h/week | 77(10.4%) | |
Sex | Male | 20(2.7%) | < 3 h/week | 249(33.8%) | |
Female | 717(97.3%) | No activity | 411(55.8%) | ||
Marital status | Single | 187(25.4%) | Illness | Yes | 64(8.7%) |
Divorced/widowed | 13(1.8%) | No | 673(91.3%) | ||
In love | 48(6.5%) | ACE categorizations | ACE = 0 | 574(77.9%) | |
Married/cohabiting | 489(66.4%) | ACE = 1 | 79(10.7%) | ||
Residence | Urban | 484(65.7%) | ACEs ≥ 2 | 84(11.4%) | |
Town | 122(16.6%) | ||||
Rural | 131(17.8%) | ||||
Education | College and below | 392(53.2%) | |||
Bachelor and above | 345(46.8%) | ||||
Relationship between depression score and other variables
Table 2 presents the results of correlation analyses. The nurses in this study had a depression score of 5.29 ± 5.44, a perceived stress score of 7.14 ± 2.10, a negative coping score of 21.77 ± 7.34, a positive coping score of 25.37 ± 7.90, and a total score of childhood adversity of 0.53 ± 1.35. Depression was significantly positively correlated with perceived stress, ACEs total score, and negative coping. Perceived stress was significantly positively correlated with both the ACEs total score and negative coping, while it was significantly negatively correlated with positive coping. ACEs total score was significantly positively correlated with negative coping. Additionally, negative coping was significantly positively correlated with positive coping.
Table 2
Correlations between PHQ, PSS, ACEs, negative coping, and positive coping (N = 737)
‾x ±ｓ | PHQ | PSS | ACEs | Negative coping | Positive coping | |
|---|---|---|---|---|---|---|
PHQ | 5.29 ± 5.442 | 1 | ||||
PSS | 7.14 ± 2.098 | 0.313** | 1 | |||
ACEs | 0.53 ± 1.349 | 0.201** | 0.093* | 1 | ||
Negative coping | 21.77 ± 7.338 | 0.574** | 0.202** | 0.153** | 1 | |
Positive coping | 25.37 ± 7.904 | 0.023 | − 0.296** | −0.034 | 0.318** | 1 |
The correlation analysis between PHQ-9 scores and continuous demographic variables, such as age, BMI, and years of work, showed no significant correlations with any of these variables. Analysis of differences in PHQ-9 scores across categorical variables indicated significant differences in PHQ-9 scores based on physical activity status, presence of illness, and ACE categorizations. Multiple comparison results showed that there was no significant difference in PHQ-9 scores between individuals who exercised ≥ 3 h per week (3.71 ± 4.97) and those who exercised < 3 h per week (4.42 ± 4.64, P = 0.315). However, both groups had significantly lower PHQ-9 scores compared to those who did not engage in physical activity (6.12 ± 5.83, P < 0.001). Nurses who were ill (7.20 ± 6.14) had significantly higher PHQ-9 scores compared to those who were not ill (5.11 ± 5.34, P = 0.003). Additionally, nurses with one type of childhood adversity (6.30 ± 5.75) and those with two or more types (8.52 ± 6.03) had significantly higher PHQ scores compared to those with no childhood adversity (4.68 ± 5.12, P < 0.05). Furthermore, nurses with one type of adversity had significantly lower PHQ scores than those with two or more adversities (P = 0.008).
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Latent profile analyses of coping styles
LPA was conducted using the 20 items from the TCSQ as exogenous variables. Fit indices for one-class to five-class were extracted for intermodel comparison (Table 3).
Table 3
Fit statistics for latent profile models of coping
Model | AIC | BIC | aBIC | LMR(P) | BLRT(P) | Entropy | Class Proportions |
|---|---|---|---|---|---|---|---|
C1
| 42919.624 | 43103.728 | 42976.714 | - | - | - | 1 |
C2
| 40144.577 | 40425.335 | 40231.639 | 0.0000 | 0.0000 | 0.888 | 0.438/0.562 |
C3
| 38469.681 | 38847.093 | 38586.715 | 0.0000 | 0.0000 | 0.917 | 0.408/0.218/0.373 |
C4
|
37397.429
|
37871.496
|
37544.435
|
0.0000
|
0.0000
|
0.934
|
0.099/0.395/0.320/0.186
|
C5
| 36900.375 | 37471.095 | 37077.353 | 0.1793 | 0.0000 | 0.947 | 0.098/0.380/0.183/0.324/0.015 |
As shown in Table 3, the AIC, BIC, and aBIC values from one-class to five-class show a decreasing trend; however, the decreasing magnitude becomes significantly smaller from four-class. Regarding the Entropy index LMR P-value and BLRT P-value, it was found that the entropy value of the five-class model was the highest (0.947); however, the LMR was not significant (P = 0.179), indicating that the five-class model was not better than the four-class model. Additionally, the five-class model had the smallest potential class probability of 1.5%, which is less than the preferred 5% threshold, indicating less representativeness. Considering these evaluation indicators, the four-class model was selected as the most appropriate for categorizing nurses’ coping profiles. According to this model, the distribution of coping profiles was as follows: 73 nurses (9.9%) were classified into Class 1, 291 (39.5%) into Class 2, 236 (32.0%) into Class 3, and 137 (18.6%) into Class 4 (Fig. 1).
Fig. 1
Profiles of coping of nurses. Note. P1～P10: positive coping item，N1～N10: negative coping item
×
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Nurses in the first class had the lowest scores in both positive and negative coping scores among all four groups; thus, they were named the “Low Coping” group. Nurses in the second class had higher scores in both positive and negative coping than those in the first class, but their positive coping scores were generally lower than those in the third and fourth classes; they were named the “Inadequate Coping” group. The third class of nurses had the highest mean value score for negative coping among the four groups. They scored very high on three items: “unpleasant events can easily cause mood swings,” “suppressing emotions in the bottom of the heart and not showing them, but can’t forget them,” and “preferring to be alone when encountering distress,” thus this group was named the “Emotional Suppression” group. The fourth class of nurses had the highest positive coping scores among the four groups and the lowest negative coping scores just above the first class; therefore, they were named the “Active Coping” group.
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To test the validity of the LPA in classifying the categories, a one-way ANOVA was conducted with the profiles of coping style as the independent variable and the scores of the two dimensions of positive coping and negative coping as the dependent variables (Table 4). The results showed that the main effect of coping profiles was significant for both dimensions. Post hoc tests revealed significant differences in coping scores between each pair of profiles in both dimensions. This finding suggests that there is heterogeneity within nurses’ coping profiles and that the four-class model effectively distinguishes between different coping profiles among nurses.
Table 4
Comparison of different coping profiles on the sub-dimension of coping styles(‾x ± s)
Variables | C1(Low Coping) | C2(Inadequate Coping) | C3(Emotional Suppression) | C4(Active Coping) | F
| post hoc tests |
|---|---|---|---|---|---|---|
N = 73 | n = 291 | n = 236 | n = 137 | |||
Positive coping | 11.48 ± 2.06 | 21.93 ± 3.35 | 28.13 ± 5.18 | 35.34 ± 4.84 | 617.872** | 4>3>2>1 |
Negative coping | 11.07 ± 2.00 | 19.56 ± 3.66 | 30.00 ± 4.87 | 18.00 ± 4.00 | 568.140** | 3>2>4>1 |
Comparison of different coping profiles on depressed mood
An ANOVA was conducted to explore whether there was a significant difference in depressed mood among the four profiles. Overall, the four groups differed significantly in their depressed mood (F = 72.001, P < 0.001). Post hoc tests revealed that Class 3 (Emotional Suppression) had the highest depression scores (8.82±6.49), followed by Class 2 (Inadequate Coping, 4.58±4.03), Class 1 (Low Coping, 1.95±3.37), and Class 4 (Active Coping, 2.52±3.22), with no significant difference between Class 1 and Class 4.
Analysis of factors influencing nurses’ coping profiles
To further analyze factors influencing nurses’ coping profiles, one-way multivariate logistic regression was conducted based on the LPA. This analysis combined coping profiles with the sociodemographic variables, perceived stress, and adversity during childhood. The results are presented in Table 5. The results showed statistically significant differences between the nurses’ coping profiles in terms of perceived stress, physical activity, and childhood adversity (P < 0.01).
A multifactorial multivariate logistic regression of coping profiles with the three factors that were statistically significant in the univariate analysis (i.e., perceived stress, physical activity, and childhood adversity) was performed, and the results are presented in Table 6. The results showed that higher PSS increased the likelihood of being classified into the “Low Coping,” “Inadequate Coping,” and “Emotional Suppression” profiles compared to the “Active Coping” profile. Nurses who engaged in ≥ 3 h of physical activity per week were less likely to be in the “Inadequate Coping” or “Emotional Suppression” profile, while those who engaged in < 3 h of physical activity per week were less likely to be in the “Emotional Suppression” profile. Nurses with ACEs ≥ 2 were more likely to have an “Emotional Suppression” profile.
Table 5
One-way multivariate logistic regression of coping profiles
Variables | Low Coping vs. Active Coping | Inadequate Coping vs. Active Coping | Emotional Suppression vs. Active Coping | ||||||
|---|---|---|---|---|---|---|---|---|---|
B | Wald | OR | B | Wald | OR | B | Wald | OR | |
Age | −0.023 | 1.037 | 0.977 | −0.01 | 0.401 | 0.99 | −0.025 | 2.211 | 0.975 |
BMI | 0.011 | 0.065 | 1.011 | −0.008 | 0.066 | 0.992 | −0.039 | 1.294 | 0.962 |
Work years | −0.022 | 1.222 | 0.978 | −0.012 | 0.804 | 0.988 | −0.023 | 2.610 | 0.977 |
PSS | 0.552** | 43.592 | 1.737 | 0.322** | 42.824 | 1.379 | 0.412** | 55.950 | 1.510 |
Sex | |||||||||
Male | −0.477 | 0.168 | 0.620 | 0.355 | 0.276 | 1.426 | 0.311 | 0.199 | 1.365 |
Female | 0 | 0 | 0 | ||||||
Marital status | |||||||||
Single | −0.595 | 2.524 | 0.552 | 0.101 | 0.182 | 1.107 | −0.075 | 0.090 | 0.928 |
Divorced/widowed | −0.595 | 0.260 | 0.552 | −0.199 | 0.072 | 0.820 | −0.264 | 0.116 | 0.768 |
In love | 0.167 | 0.075 | 1.182 | 0.340 | 0.554 | 1.405 | 0.275 | 0.339 | 1.316 |
Married/cohabiting | 0 | 0 | 0 | ||||||
Residence | |||||||||
Urban | −0.462 | 1.457 | 0.630 | −0.272 | 0.896 | 0.762 | −0.308 | 1.092 | 0.735 |
Town | 0.129 | 0.065 | 1.137 | 0.347 | 0.816 | 1.415 | 0.125 | 0.099 | 1.134 |
Rural | 0 | 0 | 0 | ||||||
physical activity | |||||||||
≥ 3 h/week | −1.078* | 5.251 | 0.340 | −1.271** | 16.386 | 0.281 | −1.585** | 20.595 | 0.205 |
<3 h/week | −0.331 | 1.097 | 0.718 | −0.518* | 5.039 | 0.596 | −0.684** | 8.097 | 0.505 |
No activity | 0 | 0 | 0 | ||||||
Education | |||||||||
College and below | 0.195 | 0.435 | 1.216 | −0.286 | 1.880 | 0.751 | −0.177 | 0.673 | 0.837 |
Bachelor and above | 0 | 0 | 0 | ||||||
Monthly income | |||||||||
≤ 4000 | 0.584 | 3.346 | 1.793 | 0.295 | 1.870 | 1.343 | 0.096 | 0.187 | 1.100 |
>4000 | 0 | 0 | 0 | ||||||
Illness | |||||||||
Yes | −0.067 | 0.011 | 0.935 | 0.459 | 1.203 | 1.582 | 0.691 | 2.716 | 1.996 |
No | 0 | 0 | 0 | ||||||
ACEs | |||||||||
ACE = 1 | −0.696 | 1.080 | 0.499 | 0.392 | 1.137 | 1.480 | 0.767* | 4.329 | 2.153 |
ACEs ≥ 2 | 0.198 | 0.130 | 1.219 | 0.494 | 1.541 | 1.639 | 1.160** | 8.925 | 3.190 |
ACE = 0 | 0 | 0 | 0 | ||||||
Table 6
Multifactorial multivariate logistic regression of coping profiles
Variables | Low Coping vs. Active Coping | Inadequate Coping vs. Active Coping | Emotional Suppression vs. Active Coping | ||||||
|---|---|---|---|---|---|---|---|---|---|
B | Wald | OR | B | Wald | OR | B | Wald | OR | |
PSS | 0.553** | 41.586 | 1.738 | 0.306** | 36.836 | 1.358 | 0.385** | 46.318 | 1.470 |
physical activity | |||||||||
≥ 3 h/week | −0.852 | 2.992 | 0.426 | −1.127** | 11.531 | 0.324 | −1.448** | 14.945 | 0.235 |
<3 h/week | −0.163 | 0.243 | 0.850 | −0.431 | 3.210 | 0.650 | −0.582* | 5.253 | 0.559 |
No activity | 0 | 0 | 0 | ||||||
ACEs | |||||||||
ACE = 1 | −0.798 | 1.357 | 0.450 | 0.351 | 0.838 | 1.420 | 0.728 | 3.487 | 2.071 |
ACEs ≥ 2 | −0.002 | 0.000 | 0.998 | 0.396 | 0.902 | 1.486 | 1.034* | 6.279 | 2.812 |
ACE = 0 | 0 | 0 | 0 | ||||||
Analysis of mediating effects
Mediation analysis was performed using the Lavaan package in R software, with physical activity and illness as control variables. ACE categorizations and perceived stress were used as independent variables, coping profiles were the mediator variable (with “Active Coping” as the reference group), and depression was the dependent variable. The results are presented in Table 7.
For ACE categorizations as the independent variable, the mediation analysis revealed a significant direct predictive effect of having two or more types of adversity on depression compared to those with no adversity (B = 2.712, P < 0.001). The confidence interval for the overall path coefficients did not include zero, indicating a significant total effect with a total effect size of 5.396. The path from ACEs to “Emotional Suppression” to depression was significant, with a confidence interval that did not include zero. The indirect effect for this path was significant, with an effect size of 1.801 and a mediated effect share of 33.38%.
The mediation analysis with perceived stress as the independent variable revealed a significant direct predictive effect on depression (B = 0.678, P < 0.001). The overall path coefficient confidence interval did not include zero, indicating a significant total effect size of 0.776. The path coefficients for “Low Coping” (effect size = −0.044, P < 0.001) and “Emotional Suppression” (effect size = 0.134, P < 0.001) were statistically significant. The mediating effects of “Low Coping” and “Emotional Suppression” accounted for 5.67% and 17.27% of the total effect size, respectively.
Table 7
Mediation analysis
Effect Size | Boot SE | Boot LLCI | Boot ULCI | |
|---|---|---|---|---|
ACEs→Low Coping→Depression | 0.085 | 0.063 | −0.022 | 0.227 |
ACEs→Inadequate Coping→Depression | −0.087 | 0.147 | −0.381 | 0.214 |
ACEs→Emotional Suppression→Depression | 1.801 | 0.506 | 0.822 | 2.777 |
ACEs→Depression | 5.396 | 1.019 | 3.373 | 7.334 |
PSS→Low Coping→Depression | −0.044 | 0.012 | −0.070 | −0.023 |
PSS→Inadequate Coping→Depression | 0.007 | 0.008 | −0.005 | 0.024 |
PSS→Emotional Suppression→Depression | 0.134 | 0.042 | 0.052 | 0.217 |
PSS→Depression | 0.776 | 0.086 | 0.597 | 0.939 |
Discussion
In the present study, we focused on the relationship between nurses’ distal stress (i.e., childhood adversity) and proximal stress (i.e., perceived stress) and depression, distinguished between nurses’ coping profiles through LPA, and explored the mediating role of coping profiles in the relationship between stress and depression. The results showed that individuals experiencing two or more adversities exhibited elevated depression levels compared to those with no adversities. Similarly, those who perceived higher levels of stress also exhibited elevated depressive symptoms. The nurses’ coping profiles consisted of four types: “Low Coping,” “Inadequate Coping,” “Emotional Suppression,” and “Active Coping.” “Emotional Suppression” mediates the relationship between childhood adversity and depression. In the relationship between perceived stress and depression, “Low Coping” and “Emotional Suppression” played a mediating role compared to the “Active Coping” profile.
Both childhood adversity and perceived stress significantly were significantly associated with higher depression levels in nurses, which is consistent with previous studies. For example, a Swedish longitudinal study found that greater exposure to adversity in childhood was associated with significantly higher odds of developing depression in adulthood [24]. Another study found a positive association between perceived stress and depression levels among healthcare workers [12]. The study concluded that the common mechanisms by which various stresses lead to depression may include neurobiological and cognitive-emotional processes. Neurobiologically, stress can lead to dysregulation of an individual’s HPA axis reactivity and sympathetic activation, which in turn leads to an enhanced inflammatory response, and these alterations can lead to profound changes in behavior, including the emergence of depressive symptoms [25]. Cognitive-emotional, adverse experiences or perceived stress may impair an individual’s attention, cognitive flexibility, and affective regulation, ultimately making the individual more susceptible to negative emotions [26]. Palamarchuk et al. suggested that distal stress primarily affects coping outcomes through habituation, whereas proximal stress primarily affects coping outcomes by sensitizing individuals [26].
Our findings confirm that the same individual may use more than one coping strategy when faced with stress [27]. In the nurse population, four distinct coping profiles were identified: “Low Coping,” “Inadequate Coping,” “Emotional Suppression,” and “Active Coping.” Individuals with an “Active Coping” profile used more positive coping strategies. Individuals with a “Low Coping” profile had low levels of both positive and negative coping. Individuals with “Inadequate Coping” profiles were characterized by significantly lower positive coping scores compared to “Active Coping” and “Emotional Suppression” profiles, although their positive and negative coping scores were higher than those of the “Low Coping” group. Individuals with “Emotional Suppression” had the highest negative coping scores among the four profiles and were significantly more likely to suppress emotions.
The results indicated that the “Emotional Suppression” group had the highest depression scores, followed by those in the “Inadequate Coping” group. The “Low Coping” and “Active Coping” groups had lower depression scores, with no significant difference between them. This result suggests that an overreliance on negative coping strategies, especially emotional suppression strategies, can significantly increase depression levels among nurses in the “Emotional Suppression” group despite their higher level of positive coping (which is only lower than that of the Active Coping group). These findings are consistent with previous research [28]. Although emotional suppression can reduce an individual’s outward expression of emotions, it does not alleviate the subjective experience of negative emotions. Instead, it leads to greater psychological pain [29]. Furthermore, emotional suppression depletes certain cognitive resources, impairs memory capacity, and triggers sympathetic activation of the cardiovascular system, which can lead to the onset of depressive mood [30]. Individuals in the “Inadequate Coping” group used less positive coping strategies when facing various life events. This coping characteristic is a risk factor for depressed mood, consistent with the findings of a previous study [31]. Individuals with low levels of positive coping are unable to actively utilize their cognitive resources when facing stressful situations, which hampers their ability to effectively reappraise information and regulate their emotions, thus predisposing them to more negative emotions. Individuals in the “Low Coping” and “Active Coping” groups exhibited lower depression levels, with no significant difference between the two groups. Helsper suggests that “Low Coping” is more appropriately viewed as a response set rather than a distinct coping type. Individuals in the “Low Coping” group may include those with low-stress levels, inability to recognize stressors, low metacognitive awareness of their coping strategies, or those who underreport their coping strategies [15]. Therefore, it is unsurprising that individuals in the “Low Coping” group self-report lower depression levels.
The results of multifactorial multivariate logistic regression with coping profiles as the dependent variable showed that individuals who were physically active for ≥ 3 h per week were less likely to fall into the “Inadequate Coping” or “Emotional Suppression” categories. Those who were physically active for < 3 h per week were also less likely to be categorized as having “Emotional Suppression” compared to those who did not engage in physical activity. Similar to the findings of Wu [32], physical activity was positively associated with positive coping. From a biological perspective, physical activity can reduce serum cortisol levels, improve immunity, increase the secretion of hormones such as dopamine, and increase positive emotions [33, 34]. Cognitively and emotionally, physical activity can regulate attention orientation, improve cognitive function, and enhance emotion regulation [35]. In terms of social adaptation, physical activity can significantly improve psychological resilience and self-efficacy, improve social adaptation and interpersonal relationships, and enhance one’s sense of control over external stressors. As a result, individuals who engage in regular physical activity can effectively utilize resources and cope with difficult situations rather than avoiding problems [32]. Through these pathways described above, individuals can increase their use of positive coping strategies.
The study results showed that the higher the level of perceived stress, the greater the likelihood of being categorized as “Low Coping,” “Inadequate Coping,” or “Emotional Suppression,” while individuals with ACEs ≥ 2 are more likely to fall into the “Emotional Suppression” profile. According to Lazarus’ theory, the assessment of stress and resultant distress influences the coping strategies employed by individuals [36]. In Resource Conservation Theory, Hobfoll argues that resources are a key component of an individual’s stress assessment and coping and that resourceful individuals may cope more effectively with stressful situations [37]. When individuals are faced with prolonged or excessive stress, they will invest additional coping resources, placing them in a crisis of resource scarcity. According to this view, nurses are more likely to cope actively when stress levels are low, whereas high stress levels or adverse experiences may deplete their coping resources and reduce their coping ability, potentially resulting in passive and suppressed coping styles [38].
Regarding the relationship between childhood adversity and depression, “Emotional Suppression” plays a stronger mediating role compared to “Active Coping.” This suggests that nurses who experience childhood adversity are more likely to adopt emotion-suppressing coping strategies, which subsequently lead to depression. A review by Gruhn aligns with this view [39]. According to the social learning theory, coping strategies are acquired through interpersonal interactions between children and caregivers; therefore, individuals who experience early adversity may not develop appropriate coping strategies, making them more vulnerable to psychosocial problems. Simultaneously, adverse experiences, such as uncontrollable experiences, can leave individuals with a sense of uncontrollability of all other stressors in adulthood, which can cause them to avoid the stressor or their own response to the stressor through emotional suppression. While these strategies are adaptive in the short term, they can increase the risk of psychological problems if used rigidly over time, regardless of the context [39].
“Low Coping” and “Emotional Suppression” played a mediating role in the relationship between perceived stress and depression compared to “Active Coping.” Specifically, nurses with higher levels of perceived stress are more likely to adopt emotional suppression and low coping strategies, which in turn lead to depression. Perceived stress affects individual coping patterns, with those with lower levels of self-reported stress being more likely to use adaptive coping. In contrast, the higher the perceived stress, the more likely an individual is to conserve resources by repressing emotions or narrowing attention and reducing exposure to the stressor. However, internalizing emotions or postponing addressing the problem ultimately leads to a low mood or lack of pleasure, which are core symptoms of depression [40].
The results of this study suggest that coping profiles play different roles in the relationships between childhood adversity, perceived stress, and depression. In addition to “Emotional Suppression,” which co-mediates the relationship between stress and depression, “Low Coping” also mediates the relationship between perceived stress and depression. This may be because perceived stress, as a proximal stressor, creates a stronger sense of urgency compared to distal stressors such as childhood adversity, which in turn interferes with cognitive functioning and places individuals in a state of “helplessness” or “numbness.” Ineffective coping with stress inevitably leads to more intense negative emotions over time.
This study has some limitations. First, the assessments were self-reported, which may introduce recall bias and social approval effects. Second, being a cross-sectional study, it cannot establish causality. Furthermore, the sample size was relatively small; a larger sample is needed to validate these findings in the future.
Conclusions
Both childhood adversity and perceived stress can significantly affect nurses’ depression, with coping profiles playing mediating roles. Therefore, when designing prevention strategies or intervention programs for the prevention of depression in nurses, hospital policymakers or clinical administrators should not only focus on nurses’ near-term perceived stress but also assess distant adversity, which may make the intervention approach more effective. Additionally, improving nurses’ coping profiles, such as recognizing stressful events, expressing emotions appropriately, learning a variety of coping strategies, and applying them flexibly to various stressful situations, will also help prevent and alleviate their maladaptive moods. Nevertheless, our study was a self-reported cross-sectional study, which precludes any possibility of establishing causality. Future studies with objective measures in other populations or settings, or in longitudinal designs, are necessary to confirm our findings.
Acknowledgements
The authors thank the nurses who participated in the study.
Clinical trial number
Not applicable.
Declarations
Ethics approval and consent to participate
All study procedures were approved by the ethics committee of Quanzhou First Hospital (No. Quan Yi lun2020253) and were performed in accordance with the ethical standards laid down in the Declaration of Helsinki (as revised in Brazil 2013). All participants were given informed consent and informed of the purpose and procedures of the study. Their privacy and anonymity were adequately protected, as no identifying information, such as names and addresses of any participant, was collected.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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