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Coping in healthcare personnel: certain coping strategies as predictors of anxiety and depression

Published online by Cambridge University Press:  15 June 2026

Paula García-Barja ,
Beatriz Talavera-Velasco Open the ORCID record for Beatriz Talavera-Velasco [Opens in a new window] ,
Daniel Vázquez-Estévez  and
Lourdes Luceño-Moreno
Paula García-Barja
Affiliation:
Department of Social and Work Psychology and Individual Differences, Complutense University of Madrid, Madrid, Spain
Beatriz Talavera-Velasco*
Affiliation:
Department of Social and Work Psychology and Individual Differences, Complutense University of Madrid, Madrid, Spain
Daniel Vázquez-Estévez
Affiliation:
Division of Psychology, C.E.S. Cardenal Cisneros, Madrid, Spain
Lourdes Luceño-Moreno
Affiliation:
Department of Social and Work Psychology and Individual Differences, Complutense University of Madrid, Madrid, Spain
*
Correspondence: Beatriz Talavera-Velasco. Email: beatriztalavera@ucm.es
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Abstract

Background

Healthcare personnel exhibit higher levels of anxiety and depression, with differences in the use of coping strategies to manage stressful situations.

Aims

To assess which coping strategies, sociodemographic factors and job-related variables predict anxiety and/or depression among healthcare professionals.

Method

A total of 744 participants, including physicians, nurses and nursing assistants were involved in a cross-sectional study.

Results

The ordinary least squares estimator was used to estimate the parameters. The results identified negative self-focus (β = 0.42, β = 0.45, p < 0.001), positive reappraisal (β = −0.20, β = −0.30, p < 0.001) and open emotional expression (β = 0.12, p < 0.001; β = 0.08, p < 0.01), as coping strategies significantly associated with anxiety and depression. Additionally, seeking social support was related to depressive symptoms (β = −0.02, p < 0.01), but not of anxiety. Interestingly, avoidant coping was associated with lower levels of both anxiety and depression (β = −0.14, p < 0.001). The absence of family responsibilities was associated with lower levels of anxiety and depression (β = −0.11, β = −0.10, p < 0.001). Being male was linked to lower anxiety levels (β = −0.11, p < 0.001), while being female was associated with greater depressive symptoms (β = 0.09, p < 0.01). Holding the position of nursing assistant was identified as a variable associated with anxiety and depression (β = 0.08, p < 0.05; β = 0.06, p < 0.05).

Conclusions

These results are essential for tailoring interventions aimed at occupational health.

Keywords

Anxietydepressioncoping strategieshealthcare professionals

Information

Type
Paper
Information
BJPsych Open , Volume 12 , Issue 4 , July 2026 , e163
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Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press on behalf of Royal College of Psychiatrists

Healthcare professionals face high workloads, elevated emotional tension, extended working hours and limited availability of free time for family and social relationships. Reference Chen, Liang, Li, Guo, Fei and Wang1 Continuous exposure to adverse working conditions can lead, over time, to symptoms associated with psychological disorders such as anxiety and depression. Reference Sun, Zhang, Wang, Wang, Zhang and Song2 These symptoms are more prevalent among healthcare workers than in the general population. Some authors reported a prevalence of 44.6% for anxiety and 50.4% for depressive symptoms. Reference Lai, Ma, Wang, Cai, Hu and Wei3 Similarly, other research has found comparable prevalence rates after analysing 14 studies involving 7780 healthcare workers. Reference Sialakis, Sialaki, Frantzana, Iliadis, Ouzounakis and Kourkouta4 During the COVID-19 period anxiety affected 3–30% of the general non-healthcare population, compared with 32–72% among healthcare professionals. Reference Clavero and Ausín5 Regarding depressive symptoms, prevalence in the general population ranged from 6 to 57%, whereas among healthcare professionals, it ranged from 27 to 61%. Reference Clavero and Ausín5 Scientific literature has identified several factors associated with anxiety and depression among this professional group, which are explained below. Regarding job roles, nursing assistants have been reported to have the highest prevalence of anxiety and depression compared with physicians and nurses. Reference Azoulay, Cariou, Bruneel, Demoule, Kouatchet and Reuter6 However, other authors suggest that nurses experience higher levels of stress, anxiety and depression than other healthcare professionals. Reference Fageera, Babtain, Alzahrani and Khrad7 In terms of age, younger nurses and physicians tend to report higher rates of anxiety and depression, particularly those working on the front line. Reference Vizheh, Qorbani, Arzaghi, Muhidin, Javanmard and Esmaeili8 Conversely, healthcare workers over the age of 50 report fewer symptoms of anxiety and depression. Reference Gavana, Papageorgiou, Stachteas, Vlachopoulos, Pagkozidis and Angelopoulou9 Other associated variables include gender and educational level. Being female has consistently been linked to higher levels of anxiety and depression among healthcare professionals. Reference Cárdaba-García, Soto-Cámara, García-Santa-Basilia, Matellán-Hernández, Onrubia-Baticón and Martínez-Caballero10 Lower levels of education have also been associated with higher levels of anxiety and depression in this population. Reference Sarvandian, Hosseinpour, Hoseinynejad, Davasaz Irani, Pakseresht and Rahimi11 However, some studies suggest that healthcare professionals with a university degree or higher may be more likely to experience stress, anxiety and depression than those with lower educational attainment. Reference Itam, Minhat, Abd Rahman, Ibrahim, Shareh Ali and Shuhaimi12 The emergence and severity of anxiety and depression symptoms vary across individuals. Evidence suggests that the way people cope with adverse situations has a significant impact on their quality of life, and the use of maladaptive coping strategies may be associated with stress, anxiety and depression. Reference Wang, Xia, Xiong, Li, Xiang and Yuan13 Other theoretical models define coping strategies as cognitive and behavioural efforts aimed at managing internal or external demands that exceed an individual’s resources. Reference Lazarus and Folkman14 Both internal factors (such as coping strategies and personality traits) and external factors (such as available resources and social support) can positively or negatively modulate the impact of stressors. Coping is considered one of the primary defences for protecting workers mental health. Reference Huang, Lei, Xu, Liu and Yu15 Indeed, during the COVID-19 pandemic, coping strategies played a crucial role in managing workplace stress and emergency situations. Reference Finstad, Giorgi, Lulli, Pandolfi, Foti and León-Perez16 There are eight coping strategies categorised into two broad dimensions: problem-focused and emotion-focused strategies. Problem-focused strategies aim to modify or change the situation and include: (a) confrontation, in which the individual actively attempts to change the situation, and (b) planning. Emotion-focused strategies aim to reduce the emotional distress caused by a stressful situation and include: (c) acceptance, which involves acknowledging the situation and one’s responsibility in it; (d) self-control, referring to the regulation of one’s emotions and behaviours; (e) positive reappraisal, or reinterpreting a stressful situation in a more positive light; (f) distancing, used to psychologically detach from the conflict; (g) escape–avoidance, encompassing cognitive and behavioural attempts to avoid the problem; and (h) seeking social support, which spans both dimensions. Reference Lazarus and Folkman14 On their behalf, other authors identified seven coping strategies, distinguishing between rational strategies: problem-solving focus, positive reappraisal and seeking social support and emotion-centred strategies, which include negative self-focus, open emotional expression, religious coping and avoidance. Reference Sandín and Chorot17 Adaptive coping strategies are those that reduce the impact of stressors and enhance well-being, leading to improved stress management and better overall performance among healthcare professionals. Reference Abraham, Thom, Greenslade, Wallis, Johnston and Carlström18 Adaptive strategies include active coping, planning, suppression of competing activities, restraint, positive reinterpretation and seeking social support. Conversely, maladaptive or dysfunctional coping strategies may provide short-term relief but fail to address the underlying stressor and may even reinforce it in the long term. These include avoidance, rumination, negative self-focus and open emotional expression. Reference Carver, Scheier and Weintraub19

The use of adaptive coping strategies by healthcare professionals is associated with improved patient care, greater safety and reduced healthcare costs. Reference Marco, Broderick, Smith-Coggins, Goyal, Joldersma and Coombs20 Some authors emphasised that problem-focused strategies (e.g. active coping, planning, instrumental support, restraint, suppression of competing activities) and emotion-focused strategies (e.g. positive reappraisal, emotional support, acceptance, religious coping, humour) are beneficial and linked to a higher quality of life. Reference Crișan, Pop, Stretea, Milhem and Forray21 In contrast, dysfunctional coping strategies (e.g. denial, substance use, behavioural and emotional disengagement and venting) have a negative impact on healthcare professionals. Indeed, maladaptive strategies such as avoidance and escape have been shown to increase mental health problems, while strategies such as seeking social support, maintaining a positive attitude, fostering self-efficacy and engaging in problem-solving are associated with better health outcomes and lower stress levels. Reference Finstad, Giorgi, Lulli, Pandolfi, Foti and León-Perez16 The primary aim of this study is to evaluate which coping strategies predict anxiety and/or depression in healthcare professionals. Additionally, it seeks to examine the relationship between sociodemographic, work-related variables and coping strategies with anxiety and depression, with the goal of determining which variables and strategies are the most significant predictors. The main hypotheses are as follows: (a) the use of maladaptive coping strategies (such as negative self-focus, open emotional expression, or avoidance coping) will predict higher levels of anxiety and depression among healthcare professionals; (b) being female and/or younger will be associated with higher levels of anxiety and depression; (c) lower educational levels will be associated with more symptoms of anxiety and depression; and (d) professionals working as nursing assistants will report higher levels of anxiety and depression.

Method

Participants

A total of 744 healthcare professionals participated in the study. Of these, 626 (84.1%) were women and 118 (15.9%) were men. The mean age was 44.96 years (s.d. = 11.49), with participants ranging from 21 to 67 years of age. A total of 637 participants (85.6%) were employed in the Community of Madrid, while 107 (14.4%) worked in other regions of Spain. Regarding professional roles, 221 participants (29.7%) were physicians, 243 (32.7%) were nurses or midwives, and 280 (37.6%) were nursing assistants. In terms of marital status, 381 (51.2%) were married, 84 (11.3%) were separated, divorced, or widowed, and 279 (37.5%) were single. Additional demographic and occupational characteristics of the sample are presented in Table 1.

Table 1

Association between demographic variables and workers with anxiety and depression (n = 744)

A table showing the association between demographic variables and workers with anxiety and depression among 744 healthcare professionals.
Table 1 Long description

The table presents data on the association between demographic variables and workers with anxiety and depression among 744 healthcare professionals. It includes variables such as gender, age, educational level, family responsibilities, and marital status. The table is divided into three main sections: Descriptive, Anxiety, and Depression. The Descriptive section provides the number and percentage of participants for each variable. The Anxiety section includes R-squared values, B (beta) coefficients, and 95% confidence intervals. The Depression section similarly includes R-squared values, B (beta) coefficients, and 95% confidence intervals. Notable trends include a higher percentage of female participants (84.1%) compared to male participants (15.9%), and a significant association between gender and both anxiety and depression. Educational level also shows varying associations with anxiety and depression, with higher education levels generally showing lower B (beta) coefficients. Family responsibilities and marital status are additional variables analyzed for their association with anxiety and depression.

*p < 0.05; ***p < 0.001.

Instruments

Sociodemographic and occupational variables

An ad hoc questionnaire was administered to collect data on the following variables: gender, age, marital status, educational level, family responsibilities, current Autonomous Community of employment, job position, type of healthcare centre, whether or not the participant works in an intensive care unit (ICU), work schedule, if the professional does on-call work and type of employment contract.

Anxiety and depression

The Spanish adaptation of the Hospital Anxiety and Depression Scale (HADS) was used. Reference Terol, López-Roig, Rodríguez-Marín, Martín-Aragón, Pastor and Reig22 This instrument consists of 14 items assessing 2 dimensions: anxiety and depression, with 7 items for each. Responses are rated on a 4-point Likert scale ranging from 0 to 3, yielding total scores from 0 to 21 for each subscale. The scale has demonstrated adequate psychometric properties in terms of validity (two-factor structure) and reliability, with Cronbach’s α coefficients of 0.77 for the anxiety subscale and 0.71 for the depression subscale. Reference Terol, López-Roig, Rodríguez-Marín, Martín-Aragón, Pastor and Reig22 These Cronbach’s α indices are considered adequate. Reference Revelle and Zinbarg23 This questionnaire has been designed for use in hospital contexts, making it suitable for use with the healthcare professionals being evaluated. Reference Bjelland, Dahl, Haug and Neckelmann24

Coping strategies

The Coping with Stress Questionnaire Reference Sandín and Chorot17 was employed. This instrument includes 42 items that describe typical ways of thinking and acting when facing stressful or problematic life situations. It assesses seven core coping styles, each represented by six items: problem-focused coping (PFS), negative self-focus (NSF), positive reappraisal, open emotional expression (OEE), avoidance coping, seeking social support (SSS), and religious coping (RLG). Responses are given on a five-point Likert scale ranging from 0 (never) to 4 (almost always). Each subscale yields a score ranging from 0 to 24, with higher scores indicating greater use of that coping strategy. The questionnaire has shown a good fit to a seven-factor structure representing the seven coping styles, with reliability indices ranging from 0.64 to 0.92. Reference Sandín and Chorot17

Procedure

A cross-sectional correlational design was used. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2013. All procedures involving human subjects were approved by the Research Ethics Committee of the Complutense University of Madrid (Ref.: CE-20220519-05-SOC). The target population consisted of healthcare professionals working in hospitals and primary care centres within the Spanish public healthcare system. Data were collected through a Google Forms questionnaire that included sociodemographic and work-related variables, along with the rest of the study instruments. Written consent was obtained. The worker had to indicate that he/she had read the informed consent form and agreed to participate in the research. The consent appeared at the beginning of the questionnaire, before participants viewed the questions. The survey was distributed through the administrative staff of various hospitals and primary care centres across different Autonomous Communities of Spain. The study procedure was approved by the Ethics Committee prior to its implementation.

Data analysis

Data analyses were conducted using IBM SPSS Statistics for Windows, version 26.0 (IBM Corp., Armonk, NY, USA; https://www.ibm.com/support/pages/downloading-ibm-spss-statistics-26-transition-extended-support-30-sep-2025). Descriptive statistics (frequencies, mean and s.d.) were calculated for anxiety, depression and coping strategies. Linear regression equations were used to assess the relationship between each sociodemographic (variables in Table 1), occupational (variables in Table 2) and coping strategy variable with anxiety and depression scores. The coefficient of determination (R 2) and the standardised beta coefficient (β), along with their corresponding CI, were reported. To facilitate the analysis of categorical variables, these were transformed into dummy variables, which were used in the analyses as predictor variables. Finally, multivariate linear regression models were applied to identify which sociodemographic, occupational and coping strategy variables (considered together) were associated with anxiety and depression. The models were estimated using the least squares method, employing a forward stepwise selection procedure. Statistical significance was set at p < 0.05. The forward method was used to assess the predictive power of variables known in previous literature to be relevant in the prediction of anxiety and depression.

Table 2

Association between job variables with anxiety and depression (n = 744)

A table showing the association between job variables and anxiety and depression among 744 individuals.
Table 2 Long description

The table presents data on the association between various job variables and levels of anxiety and depression among 744 individuals. It includes descriptive statistics, R-squared values, beta coefficients, and 95 percent confidence intervals for each variable. The variables analyzed include job position, on-call work, work in ICU, type of workday, contract type, autonomous community, and work center. Notable findings include significant associations for certain job positions, contract types, and work centers with anxiety and depression. For instance, nursing assistants show a positive association with anxiety, while permanent staff status shows a negative association with depression.

ICU, intensive care unit. *p < 0.05.

Results

Regarding sociodemographic variables, being male was negatively associated with both anxiety and depression. Concerning educational level, having completed only primary education or high school was positively associated with anxiety, whereas having a medium-level qualification or vocational training degree was positively associated with both anxiety and depression. Additionally, not having family responsibilities was negatively associated with depression. Being a man is negatively associated with both anxiety and depression. The model was not statistically significant for age (see Table 1).

In terms of work-related variables, being a physician was negatively associated with anxiety, while being a nursing assistant was positively associated with both anxiety and depression. Furthermore, working in a region other than the Community of Madrid was negatively associated with depression (see Table 2).

With respect to coping strategies, problem-focused coping, positive reappraisal and seeking social support were negatively and significantly associated with both anxiety and depression, although seeking social support had a very small effect size.

In contrast, negative self-focus and open emotional expression were positively and significantly associated with both anxiety and depression. Additionally, avoidance coping and religious coping strategies were negatively and significantly associated only with depression (see Table 3).

Table 3

Association between coping strategies with anxiety and depression (n = 744)

Table showing association between coping strategies and anxiety and depression with variables, R squared values, beta coefficients, and confidence intervals.
Table 3 Long description

The table presents data on the association between various coping strategies and levels of anxiety and depression. It includes variables such as problem-solving focus, negative self-focus, positive reappraisal, emotional expression, acceptance, social support seeking, and religious coping. For each variable, the table provides R squared values, beta coefficients, and ninety-five percentage confidence intervals for both anxiety and depression. Notable trends include negative associations between problem-solving focus and both anxiety and depression, and positive associations between negative self-focus and both conditions. Avoidance coping and religious coping strategies show significant negative associations only with depression.

CSQ_PSF, problem-solving focus; CSQ_NSF, negative self-focus; CSQ_PR, positive reappraisal; CSQ_OEE, open emotional expression; CSQ_AC, avoidant coping; CSQ_SSS, seeking social support; CSQ_RLG, religious coping. *p < 0.05; **p < 0.01; ***p < 0.001.

Results related to internal consistency and correlations between factors are presented in Table 4. The anxiety scale showed a strong positive correlation with the negative self-focus coping strategy. The depression scale was strongly and positively correlated with negative self-focus and moderately and negatively correlated with positive reappraisal. Problem-solving focus was strongly and positively correlated with positive reappraisal and moderately and positively correlated with seeking social support (see Table 4).

Table 4

Correlation matrix (n = 744)

A table showing correlations between various psychological factors and coping strategies, including anxiety, depression, problem-solving focus, and more.
Table 4 Long description

The table presents a correlation matrix with 744 participants, showing the relationships between different psychological factors and coping strategies. It includes nine variables: HADS_A, HADS_D, CSQ_PSF, CSQ_NSF, CSQ_PR, CSQ_QEE, CSQ_AC, CSQ_SSS, and CSQ_RLG. The anxiety scale (HADS_A) shows a strong positive correlation with the negative self-focus coping strategy (CSQ_NSF). The depression scale (HADS_D) is strongly and positively correlated with negative self-focus and moderately and negatively correlated with positive reappraisal (CSQ_PR). Problem-solving focus (CSQ_PSF) is strongly and positively correlated with positive reappraisal and moderately and positively correlated with seeking social support (CSQ_SSS). The table also includes mean values (M), standard deviations (SD), and Cronbach’s alpha (α) for each variable. Row 1: HADS_A. Row 2: HADS_D, 0.744, 6.54, 4.35, 0.875. Row 3: CSQ_PSF, -0.322, -0.446, 14.9, 4.58, 0.871. Row 4: CSQ_NSF, 0.551, 0.612, -0.392, 14.58, 3.72, 0.691. Row 5: CSQ_PR, -0.391, -0.527, 0.633, -0.382, 14.35, 3.86, 0.754. Row 6: CSQ_QEE, 0.278, 0.242, -0.069, 0.307, -0.108, 7.30, 3.25, 0.671. Row 7: CSQ_AC, -0.056, -0.146, 0.250, -0.008, 0.367, 0.027, 11.53, 3.60, 0.610. Row 8: CSQ_SSS, -0.110, -0.212, 0.440, -0.085, 0.351, 0.250, 0.241, 12.11, 6.15, 0.938. Row 9: CSQ_RLG, -0.036, -0.078, 0.220, -0.041, 0.183, 0.006, 0.024, 0.180, 3.77, 5.42, 0.930.

HADS_A, anxiety; HADS_D, depression; CSQ_PSF, problem-solving focus; CSQ_NSF, negative self-focus; CSQ_PR, positive reappraisal; CSQ_OEE, open emotional expression; CSQ_AC, avoidant coping; CSQ_SSS, seeking social support; CSQ_RLG, religious coping. *p < 0.05; **p < 0.01; ***p < 0.001.

Normality was checked using standardised residual graphs, and both models showed normality fit. Independence was checked using the Durbin–Watson test. Both statistics were close to 2 (HADS A: 1.90; HADS D: 1.92), showing independence between prediction errors. Finally, multicollinearity was checked using Tolerance (TOL) and Variance Inflation Factor (VIF) indicators. For both models, Tolerance indicators were greater than 0.2 and VIF indicators were lower than 12, showing no presence of multicollinearity between predictors. Multicollinearity was assessed using the VIF and TOL statistics; there are no multicollinearity issues in the model.

The regression model for anxiety was statistically significant and explained 40.3% of the variance (F(7, 658) = 63.509, p < 0.001). The model for depression was also significant, explaining 50.1% of the variance (F(7, 658) = 94.315, p < 0.001). Variables common to both models included the coping strategies of negative self-focus, positive reappraisal, open emotional expression and the professional role of nursing assistant. Variables positively associated with anxiety included negative self-focus, open emotional expression and being a nursing assistant. Variables negatively associated with anxiety were positive reappraisal, not having family responsibilities and being male. For depression, the variables positively associated were negative self-focus, open emotional expression, being female and being a nursing assistant. In contrast, depression was negatively associated with positive reappraisal, seeking social support and not having family responsibilities (see Table 5).

Table 5

Regression model for anxiety and depression (n = 744)

Table showing regression model for anxiety and depression with variables, beta coefficients, and confidence intervals.
Table 5 Long description

The table presents a regression model for anxiety and depression, including variables such as coping strategies and professional roles. It consists of eight rows and six columns. The columns are labeled Variable, Anxiety B (beta), Anxiety 95% CI, Depression B (beta), and Depression 95% CI. The variables include coping strategies like negative self-focus, positive reappraisal, open emotional expression, and seeking social support, as well as demographic factors like gender and family responsibilities. The table shows beta coefficients and 95% confidence intervals for each variable’s association with anxiety and depression. Notable trends include positive associations of negative self-focus and open emotional expression with both anxiety and depression, while positive reappraisal is negatively associated with both. Being a nursing assistant is positively associated with both anxiety and depression. Gender differences are noted, with being male negatively associated with anxiety and being female positively associated with depression. Not having family responsibilities is negatively associated with both anxiety and depression.

CSQ_NSF, negative self-focus; CSQ_PR, positive reappraisal; CSQ_OEE, open emotional expression; CSQ_SSS, seeking social support. *p < 0.05; **p < 0.01; ***p < 0.001.

Discussion

The main objective of this study was to evaluate which coping strategies predict anxiety and/or depression among healthcare professionals. Additionally, the study examined which sociodemographic and occupational variables are associated with anxiety and depression, aiming to determine which variables and coping strategies have the most significant predicting power for these psychological outcomes. The results identified the following coping strategies as predictors of both anxiety and depression: negative self-focus, positive reappraisal and open emotional expression. Negative self-focus and open emotional expression were associated with higher levels of anxiety and depression, while positive reappraisal was associated with lower levels of these symptoms. Additionally, seeking social support emerged as a predictor of depressive symptoms only, according to our model. Other studies have also emphasised the usefulness of social support in alleviating work-related stress among healthcare workers. Reference Wang, Xu, Ren, Wang, Xu and Wang25 Research has shown that social support plays a crucial role in this professional group, as relationships with family and friends can buffer the effects of depressive symptoms and feelings of loneliness in the workplace. Reference Kulari and Pereira de Castro26 Regarding open emotional expression, previous research has emphasised the importance of reducing impulsive and uncontrolled emotional expression, as it is associated with depressive states and a greater likelihood of engaging in risk-related or dysregulated behaviours. Reference Alfonso-Benlliure and Meléndez Moral27 However, it should be noted that emotional expression per se is not inherently maladaptive, as its effects may vary depending on the degree of regulation and the cultural or contextual framework. Reference Gross and John28 In contrast, positive reappraisal has been shown to be an effective coping strategy, especially in the face of traumatic situations. It fosters optimism, minimises catastrophising and encourages acceptance, thereby helping individuals adapt to stress, grief and sadness. This strategy has also been linked to better functionality, reduced presenteeism and even greater effectiveness when combined with social support. Reference Mete, Demirhindi, Kahramanoğlu, Şahin and Tanır29 Therefore, the first hypothesis of this study is partially supported. Maladaptive strategies such as negative self-focus and open emotional expression were indeed associated with higher levels of anxiety and depression. However, only negative self-focus emerged as a predictor of both conditions, while open emotional expression was predictive of depression alone.

Interestingly, avoidant coping in our study was associated with lower levels of both anxiety and depression. This finding is particularly relevant, as individuals often resort to avoidance when they perceive they lack the resources to face environmental threats. This strategy typically includes efforts to withdraw from the stressful situation, avoid problems, seek emotional release, or disengage behaviourally or cognitively. Reference Roth and Cohen30 In this cross-sectional study, the inverse association between avoidance and depression could be explained by the regulatory function that certain avoidance strategies perform in emotionally demanding contexts such as healthcare, which is characterised by high chronic emotional exposure. In these environments, avoidance can reduce repetitive cognitive processing and rumination, processes closely linked to the development and maintenance of depressive symptoms. Reference Watkins31 In this sense, the impact of avoidance on depression would depend on the context and the time frame evaluated, which could explain the results observed. In any case, these contradictory findings suggest the need for further research to explore and clarify these relationships.

Regarding sociodemographic predictors, both the absence of family responsibilities and gender were associated with anxiety and depression. Specifically, participants without family responsibilities reported fewer symptoms. Conversely, other studies indicate that healthcare workers with caregiving duties, particularly nurses, and especially during the pandemic, showed higher levels of stress, anxiety and depression. Reference Alzailai, Barriball, Alkhatib and Xyrichis32 These results may be explained by heightened concern about infecting loved ones and the associated sense of responsibility. Being male was associated with lower levels of anxiety, while being female was linked to higher depressive symptoms. Although some studies have reported mixed findings on this matter, Reference Alnazly, Khraisat, Al-Bashaireh and Bryant33 others confirm gender differences in the prevalence of anxiety and depression among healthcare professionals, with women showing higher symptom levels. Reference Brulin, Lidwall, Seing, Nyberg, Landstad and Sjöström34 However, it is important to note that the observed gender differences may be partially explained by structural factors, such as gendered workload allocation, or workplace discrimination, rather than intrinsic differences. Reference Eagly, Wood, Van Lange, Kruglanski and Higgins35 Therefore, our second hypothesis is partially supported: being female did predict depression, although no significant relationship with anxiety was observed in our model. In contrast, age was not associated with either anxiety or depression and did not emerge as a predictor. Concerning the third hypothesis, a relationship was found between lower educational levels and increased symptoms of anxiety and depression. However, educational level did not appear as a predictor in the final model. Some authors argue that lower educational attainment is associated with positions involving high emotional strain, Reference Bonsaksen, Thørrisen, Skogen and Aas36 whereas higher education may lead to better employment opportunities characterised by greater autonomy and professional development, thereby reducing psychological distress. Reference Kristensen, Borg and Hannerz37 It is possible that these gender and occupational differences reflect not only individual characteristics but also organisational and structural factors – such as workload, autonomy and job insecurity – which have been shown to be linked to the psychological well-being of healthcare workers. Reference Shanafelt, Hasan, Dyrbye, Sinsky, Satele and Sloan38 Future studies should consider these contextual relationships to better understand mental health among healthcare professionals.

Regarding work-related variables, the role of nursing assistant emerged as a predictor of both anxiety and depression, supporting our fourth hypothesis. Previous research has shown that professionals in lower-level positions tend to report higher levels of anxiety and depression, Reference Vancappel, Jansen, Ouhmad, Desmidt, Etain and Bergey39 possibly due to reduced decision-making autonomy or more precarious working conditions compared with those in higher-ranking roles. Reference Kahya40 The findings of this study highlight the importance of incorporating coping strategies that predict anxiety and depression into prevention and intervention programmes for healthcare professionals. Specifically, this research supports promoting positive reappraisal and reducing the use of maladaptive strategies such as negative self-focus and open emotional expression. Furthermore, preventive strategies aimed at reducing depressive symptoms should include the promotion of social support. This study also emphasises the importance of considering key sociodemographic variables – such as family responsibilities and gender – when designing tailored interventions. This means that actions can be tailored to specific groups of workers (women, people with family responsibilities), which can improve the specificity and effectiveness of such interventions. Special attention should also be given to nursing assistants, as this group appears particularly vulnerable to anxious and depressive symptoms. It is recommended that these coping strategies be incorporated into emotional psychoeducation interventions for healthcare personnel, such as resilience workshops, group problem-solving, cognitive–behavioural training and mindfulness which have been shown to be effective in improving psychological well-being.

Finally, several limitations should be noted. The sample was incidental and non-randomised. It would be beneficial to increase the number of participants across job categories to assess potential differences (e.g. by region, healthcare setting, etc.). On the other hand, most of the sample is represented by women, people who work in Madrid, or nursing assistants, which may limit the generalisability of the results. Also, recruitment via Google Forms may have introduced self-selection bias, particularly if those experiencing higher distress were more likely to respond. Some of the scales in the coping questionnaire have Cronbach’s α coefficients below 0.70, so interpretations made for these scales should be treated with caution. The results for the seeking social support coping strategy should be confirmed in other studies with healthcare personnel, as the effect size for this factor is low in this study. Another limitation of the study is that there is a high correlation between the problem-solving orientation scales and the positive reappraisal scale. However, no multicollinearity issues were observed. Furthermore, this study was unable to employ other statistical techniques that require a larger sample size. For example, it was not possible to develop an integrated model based on structural equation modelling or an approach based on machine learning, as this would have required a larger sample. Given the cross-sectional nature of the study, no conclusions about causality or changes over time can be drawn. Future research should explore the role of coping strategies in longitudinal studies and evaluate their effectiveness through targeted interventions to reduce anxiety and depression symptoms. Moreover, linking these outcomes with organisational indicators such as absenteeism, turnover intentions, staff rotation and medical leave could provide valuable insights for optimising workforce costs in public healthcare systems.

Data availability

The data that support the findings of this study are openly available in Figshare at http://doi.org/10.6084/m9.figshare.29489147.

Author contributions

P.G.-B, B.T.-V. and L.L.-M.: conceptualisation, writing – original draft, writing – review and editing. P.G.-B., B.T.-V., D.V.-E. and L.L.-M.: conceptualisation, methodology, writing – original draft, writing – review and editing. P.G.-B., B.T.-V. and L.L.-M.: writing – original draft.

Funding

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

Declaration of interest

None.

References

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Figure 0

Table 1 Association between demographic variables and workers with anxiety and depression (n = 744)Table 1 long description.

Figure 1

Table 2 Association between job variables with anxiety and depression (n = 744)Table 2 long description.

Figure 2

Table 3 Association between coping strategies with anxiety and depression (n = 744)Table 3 long description.

Figure 3

Table 4 Correlation matrix (n = 744)Table 4 long description.

Figure 4

Table 5 Regression model for anxiety and depression (n = 744)Table 5 long description.

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