Abstract
Mental disorders are a leading cause of morbidity worldwide, and healthcare professionals are particularly vulnerable due to occupational stressors, a vulnerability intensified during the coronavirus disease 2019 pandemic. This study assessed the prevalence of mental health disorders among hospital workers and examined changes in their perceived mental health during the pandemic. A descriptive cross-sectional study was conducted with 215 employees attending the Health Surveillance Service of Virgen Macarena University Hospital (Seville) between January 2019 and December 2022. Data were collected from occupational health records and a telephone survey, including the General Health Questionnaire (12 items) questionnaire. The prevalence of diagnosed mental health disorders was 7.0%, with mixed anxiety-depressive disorder being the most frequent. Most affected workers required short-term temporary incapacity due to common contingencies, and 36.7% required job adaptations, mainly involving task modifications. During the pandemic, 68.1% of workers reported a perceived worsening in mental health, which was more common among alcohol users. Among those receiving treatment, 70.8% required medication adjustments, and 31.2% reported increased analgesic use. Although prevalence rates were lower than expected, likely due to underdiagnosis and prioritization of coronavirus disease 2019-sensitive evaluations, the profile of affected workers was consistent with previous literature, predominantly women around 50 years old, often Assistant Nursing Care Technicians. These findings highlight the crucial role of occupational health services in early detection, monitoring, and support of healthcare professionals. Identification of alcohol use, psychiatric medication adjustments, and increased analgesic intake as risk factors emphasize the need for proactive interventions to sustain the healthcare workforce.
Keywords: anxiety, COVID-19, depression, health care workers, health profile, mental health
1. Introduction
1.1. Background
The International Labour Organisation defines occupational health as “the highest degree of physical, mental and social well-being of workers and not merely the absence of disease or infirmity resulting from protection against hazards.”[1] This definition emphasizes that safeguarding workers’ health extends beyond physical risks; neglecting mental or social well-being also constitutes a failure of occupational health protection, which lies at the core of occupational medicine. Mental health disorders have long represented a major public health concern. As early as 2006, the European Study of the Epidemiology of Mental Disorders-Spain study reported that 19.5% of participants had experienced a mental health condition at some point in their lives,[2] and by 2020, the Primary Care Clinical Database (Base de Datos Clínicos de Atención Primaria) estimated a prevalence of 27.4% in the general population.[3]
Work plays a dual role in this context: it can promote social integration and personal fulfillment, but it can also act as a significant risk factor, as occupational stress is a well-established trigger for the onset or worsening of mental health disorders.[4] Within the workplace, the most common mental health problems include anxiety disorders, depressive disorders, personality disorders, and psychotic disorders, with anxiety being the most prevalent, particularly among young women, and with prevalence declining with age.[5] Regardless of the specific diagnosis, these conditions typically lead to similar occupational consequences, including reduced productivity and increased absenteeism.[6] Such outcomes are further exacerbated by factors such as job insecurity and low perceived workplace support.[7] The coronavirus disease 2019 (COVID-19) pandemic amplified these challenges,[8–10] contributing to the emergence of new conditions such as post-traumatic stress disorder (PTSD).[11]
1.2. Significance of the study
Health care professionals constitute a particularly vulnerable group. Their work is widely recognized as one of the most stressful professions, exposing them to a higher risk of mental health problems compared with the general population. Most studies have focused on physicians and nurses, reporting concerning trends even before the pandemic, for example, steadily rising burnout levels among physicians[12] and higher suicide rates among nurses compared with the general population.[13] The pandemic added further strain, with stressors specific to health care such as role variability, shift work, and night duties. Of these, irregular schedules have been most consistently identified as destabilizing factors, as they can exacerbate preexisting conditions and trigger indirect symptoms like insomnia, itself a risk factor for mental health deterioration.[14]
The broader literature confirms that the COVID-19 pandemic had a profound impact on mental health. Increased symptoms of anxiety, depression, PTSD, insomnia, and somatization have been consistently reported across populations, with health care workers among the most affected. Within this group, frontline staff, less experienced professionals, and those who had personally suffered from the disease were particularly vulnerable, reflecting the intense job demands, uncertainty, and resource shortages that characterized the early stages of the crisis.[14,15] Importantly, contracting COVID-19 has been linked to a higher prevalence of depression and a greater burden of psychological and cognitive symptoms, especially among those requiring hospitalization.[16,17] In addition to the psychological stress of the pandemic, biological mechanisms, such as cytokine storm-related brain damage, have also been proposed as contributing factors.[18] Workers with preexisting psychiatric conditions faced an especially difficult situation, as the isolation and uncertainty of the pandemic heightened the risk of decompensation.[19] Some disorders, such as obsessive-compulsive disorder, are particularly sensitive to such contexts, with evidence pointing to a worsening of compulsive washing during this period.[20] Taken together, these findings emphasize the importance of monitoring mental health in occupational settings, particularly among health care workers.
1.3. Aim of the study
Building on these premises, the present study aims to investigate the prevalence of mental health disorders among workers with a prior history of such conditions who attended the Health Surveillance Service of Virgen Macarena University Hospital in Seville, Spain. Specifically, the study seeks to examine key occupational, personal, and lifestyle variables that may influence mental health status and to evaluate whether workers’ perception of their mental health has deteriorated over time.
2. Material and method
2.1. Design
A descriptive cross-sectional study was conducted using a retrospective database.
2.2. Population and sample
The study population consisted of employees of the Virgen Macarena University Hospital who attended the Occupational Health Surveillance Service for a health examination (whether initial, periodic, or related to the assessment of particularly sensitive workers) between January 1, 2019 and December 31, 2022. Over this period, a total of 2982 occupational health examinations were conducted, distributed as 942 in 2019, 1064 in 2020, 976 in 2021, and 984 in 2022. A slight increase in examinations was observed during the pandemic years, reflecting a higher number of requests for evaluation as particularly sensitive workers.
An incidental sampling strategy was employed due to its practicality and accessibility, as the study primarily collected qualitative information and was designed as an initial exploration of the factors affecting mental health among healthcare workers. Eligible participants were hospital employees who attended the Health Surveillance Service within the study timeframe and had a documented personal history of a mental health disorder, formally diagnosed by a Mental Health specialist during a clinical consultation rather than self-reported. Pregnant workers were excluded from the analysis. Following the application of these inclusion and exclusion criteria, the final sample consisted of 215 workers, distributed across the years as 63 in 2019, 69 in 2020, 44 in 2021, and 39 in 2022.
Although data collection was completed in 2023, following a bibliographic search conducted in 2022, the study was finalized in 2024. The apparent delay in publication is therefore attributable to the time required for data compilation, analysis, and manuscript preparation, with the publication process initiated thereafter. This timeline ensures that the study provides a carefully curated dataset, despite being slightly retrospective.
2.3. Variables
The study included a range of demographic, socio-labor, COVID-19-related, and mental health variables. Demographic variables comprised sex and age. Socio-labor variables encompassed occupational category, job title, contract type, and shift type, as well as health screening suitability, preventive recommendations, and any job adaptations. Additional socio-labor factors included multi-employment, educational level, work-life balance issues, the presence of disabilities or handicaps, and temporary incapacity (TI), detailing the number, contingency, and duration of each episode. Household cohabitation model, toxic habits such as alcohol and tobacco use, and engagement in leisure or sports activities were also recorded.
COVID-19-related variables captured information on infection, classified according to severity, symptoms, and sequelae, as well as the working area during the pandemic, distinguishing between COVID-19 and non-COVID-19 units.
Mental health variables included a personal history of psychiatric disorders, encompassing anxiety, mood, mixed, schizophrenia/psychotic, and personality or behavioral disorders. Post-pandemic mental health perception and symptom assessment were evaluated using the General Health Questionnaire (12 items) (GHQ-12).[21–23] Data on medication intake were also collected, including psychotropic medications, adjustments to existing treatments, and increases in usual analgesia.
2.4. Procedure
An initial screening of all health examinations conducted during the study period was performed to identify the definitive sample that met the established inclusion and exclusion criteria. Occupational and clinical data were subsequently extracted from the Windmedtra system, the Occupational Health Software of the Andalusian Health Service, and from Diraya, the unified digital health record system of the Andalusian Health Service. In addition, participating workers provided information on education level, cohabitation model, multi-employment, work–life balance, COVID-19-related factors, and mental health–related variables. All participants also completed the GHQ-12 questionnaire.
To evaluate differences in applications between years, the number of eligible health examinations and the final sample size were compared across each calendar year. Trends were assessed descriptively, highlighting increases or decreases in attendance, such as the observed rise in applications during the pandemic years, which was attributed to a higher demand for evaluation as particularly sensitive workers. This approach allowed for a year-by-year comparison, identifying temporal patterns in occupational health engagement and mental health risk among hospital staff.
2.5. Data analysis
For the purposes of this research, all data were collected from January 1, 2019, to December 31, 2022. Data were processed and analyzed using the Statistical Package for the Social Sciences, version 29.0 for Windows, licensed by the Virgen del Rocio University Hospital (IBM). A P value of < .05 was considered statistically significant.
Normality was assessed using the Kolmogorov–Smirnov or Shapiro–Wilk test, depending on subgroup size. As all variables followed a normal distribution, numerical variables were expressed as mean ± standard deviation. Qualitative independent variables were compared using the chi-square test.
Logistic regression analysis was applied to examine the relationship between dichotomous dependent variables and a set of explanatory variables. Variables that showed a significant association with the dependent variable at a univariate level (P < .15) were included in the model. The method then selected the best combination of predictor variables for the outcome, calculating odds ratios (OR) and their respective 95% confidence intervals for each variable included in the final model.
2.6. Ethical and legal considerations
The study adhered to the principles of the Declaration of Helsinki and complied with current Spanish legislation, including the Law 41/2002, of 14 November, Basic Law regulating patient autonomy and rights and obligations regarding clinical data and documentation, and the Organic Law 3/2018, of 5 December, on the Protection of Personal Data and guarantee of digital rights.
Ethical approval was obtained from the Research Ethics Committee of the Virgen Macarena and Virgen del Rocio University Hospitals of Seville (code SICEIA-2024-001088).
2.7. Study biases and limitations
As a retrospective study, the possibility of data loss cannot be fully excluded due to potential limitations in data collection procedures and the incidental sampling method employed. In addition, the cross-sectional design prevents the establishment of causal relationships, although it allows for the identification of meaningful associations that may guide future research. The heterogeneity of mental health–related pharmacological treatments represents another limitation, and future studies could benefit from analyzing specific medication subtypes, such as benzodiazepines or antipsychotics, to provide a more precise understanding of their effects. Similarly, the variable “increase in analgesic use,” intended to detect potential rises in somatic symptoms, could have been complemented by the evaluation of other relevant manifestations of mental health disorders, including insomnia, gastrointestinal disturbances, or fatigue. Finally, some variables were affected by incomplete reporting, as certain participants declined to provide personal information, such as living arrangements or leisure activities, which limited the comprehensiveness of the analyses in these domains. These factors should be considered when interpreting the results.
3. Results
A total of 72% of the workers in the sample were women, with a mean age of 50.6 years (standard deviation = 9.7). Table 1 presents the prevalence of mental health pathologies by type and year, showing that mixed anxious-depressive disorders were consistently the most frequent, while anxiety disorders were particularly notable in 2020 and 2021.
Table 1.
Prevalence by year and type of pathology.
| Global N (%) |
Anxiety Disorders N (%) |
Mood Disorders N (%) | Mixed disorder N (%) |
Psychotic disorder N (%) |
Personality disorder N (%) |
|
|---|---|---|---|---|---|---|
| 2019 | 63 (6.7) | 8 (12.7) | 21 (33.3) | 27 (42.9) | 3 (4.8) | 4 (6.3) |
| 2020 | 69 (6.5) | 17 (24.6) | 18 (26.1) | 29 (42) | 4 (5.6) | 1 (1.4) |
| 2021 | 44 (4.5) | 9 (20.4) | 10 (22.7) | 21 (47.7) | 4 (9.1) | 0 |
| 2022 | 39 (3.9) | 5 (12.8) | 11 (28.2) | 22 (56.4) | 1 (2.5) | 0 |
N = number of workers.
Regarding living arrangements, nearly half of participants lived with a partner, while around 1-quarter lived alone. Alcohol consumption was predominantly sporadic, and most workers engaged in multiple leisure activities. Physical activity levels were distributed across low, moderate, and high categories. Table 2 summarizes occupational characteristics, highlighting that Auxiliary Nursing Technicians and general services staff were the largest professional groups, with most workers holding permanent contracts and working 12-hour rotating shifts.
Table 2.
Occupational variables.
| Category | Variable | N (%) |
|---|---|---|
| Professionals | Specialist Medical Practitioners | 8 (3.72) |
| Nurses, physiotherapists, midwives | 44 (20.4) | |
| Resident physician | 5 (2.3) | |
| Auxiliary Nursing Technician | 66 (30.6) | |
| Wardens | 23 (10.6) | |
| General services | 60 (27.9) | |
| Specialised technicians | 9 (4.1) | |
| Health department | Medical area | 46 (21.3) |
| Medical-surgical area | 10 (4.6) | |
| Surgical area | 19 (8.8) | |
| Medical services area | 23 (10.6) | |
| Anaesthesia/ICU | 8 (3.7) | |
| Emergencies | 25 (11.6) | |
| On-call staff | 30 (13.9) | |
| General services | 54 (25.1) | |
| Type of contract | Temporary | 29 (13.4) |
| Interim | 62 (28.8) | |
| Permanent | 124 (57.6) | |
| Type of working day | 12-hour rotating shift | 71 (33) |
| Fixed morning shift | 52 (24.1) | |
| Day work | 44 (20.4) | |
| 7-hour rotating shift | 22 (10.2) | |
| Other | 26 (12) | |
| Certified disability | No | 189 (87.9) |
| Yes | 26 (12) | |
| Type of disability | Physical | 8 (30.76) |
| Mental | 15 (57.69) | |
| Sensory | 3 (11.53) | |
| Occupational incapacity | No | 205 (95.3) |
| Yes | 10 (4.65) | |
| Training/Education | Upper Secondary Education | 29 (15.4) |
| Intermediate Vocational Training | 53 (28.1) | |
| Upper Vocational Training | 47 (22.5) | |
| postgraduate studies | 59 (31.3) | |
| Ability to work | Able | 123 (57.2) |
| Able with restrictions | 79 (36.7) | |
| Other | 13 (6) | |
| Adaptation | With change in functions and/or tasks | 49 (66.2) |
| Without change in functions and/or tasks | 10 (13.5) | |
| Change of position | 15 (20.2) | |
| Preventive recommendations | Physical | 32 (40.5) |
| COVID-19 | 28 (35.4) | |
| Organisational | 14 (17.7) | |
| Multi-employment and Work-life balance | Workers with another job | 12 (6.3) |
| Workers with work-life balance problems | 48 (25.5) |
COVID-19 = coronavirus disease-2019, ICU = intensive care unit, N = number of workers.
During the pandemic, the majority of workers remained active, with approximately 1-third assigned to COVID-19 units. About 63% reported having contracted COVID-19, mostly with mild symptoms. Sequelae were reported in nearly 1-third of infected workers, primarily physical. Table 3 presents mental health variables, showing that 68% of workers perceived a worsening of their mental health post-pandemic, and 45% screened positive on the GHQ-12.
Table 3.
Mental health variables.
| Variable | Answer | N (%) |
|---|---|---|
| Perception of health | Worse | 128 (68.1) |
| Not worse | 60 (31.9) | |
| GHQ-12 result | Positive screening | 86 (45.5) |
| Negative screening | 102 (54.2) | |
| Taking psychiatric medication | Yes | 120 (63.8) |
| No | 68 (36.2) | |
| Medication readjustment | Yes | 85 (70.8) |
| No | 35 (29.2) | |
| Increased analgesia | Yes | 60 (31.2) |
| No | 128 (68.1) |
GHQ-12 = General Health Questionnaire (12 items), N = number of workers.
TI processes were common, mostly short-term and attributed to common contingencies, with mental health–related causes representing a smaller proportion of total absences.
Sex differences were observed in the type of pathology: anxiety and mixed disorders were more frequent among women, whereas personality/behavioral disorders were slightly more common in men.
Lifestyle and treatment factors were strongly associated with post-pandemic mental health perception. Workers who consumed alcohol, required treatment, or underwent therapeutic adjustments reported poorer perception of their mental health. Increased analgesic use was also linked to worse perception.
The logistic regression model confirmed alcohol consumption as a significant predictor of mental health deterioration, with drinkers being twice as likely to have an unfavorable GHQ-12 score compared to nondrinkers (OR = 2.04, 95% confidence interval: 1.023–4.07, P = .043). Moreover, the interaction between alcohol use and age was significant (OR = 1.076), indicating that the adverse effects of alcohol on mental health intensified with increasing age. In contrast, sex, TI status, and age alone were not significant predictors.
4. Discussion
The impact of the COVID-19 pandemic on mental health has been widely documented, with adverse effects reported among individuals with a prior psychiatric history, particularly those with obsessive-compulsive disorder or PTSD within the anxiety spectrum.[7,8,11,14] In the present study, the observed prevalence of diagnosed mental health conditions was lower than that reported in the general population, which may reflect underdiagnosis within the sample. Nevertheless, the distribution of psychiatric conditions aligned with previous literature, with mixed anxiety-depressive disorder being the most frequent overall.[3]
A potential explanation for this apparent under-reporting is the marked increase in requests for assessment as Especially Sensitive Workers (ESW) during the pandemic, primarily related to COVID-19 exposure. According to Article 25 of the Spanish Law on Occupational Risk Prevention, ESWs are individuals whose personal or medical characteristics increase vulnerability to workplace risks. During the pandemic, this included workers with chronic somatic conditions, older age, or pregnancy, many of which are unrelated to mental health. The persistence of high self-reported deterioration in mental health (68.1%) despite stable diagnosed prevalence supports the notion of underdiagnosis in the sample. Additionally, prevalence decreased in 2021 and 2022, coinciding with the normalization of healthcare services and a reduction in ESW requests, which allowed a reorientation toward routine occupational health screenings and preventive measures.
The demographic profile of the sample, predominantly women with a mean age of 50 years, is consistent with patterns described in the literature, which indicate a higher burden of mental health disorders among women, particularly with advancing age.[3] This distribution also reflects the gender composition of the healthcare workforce in the study hospital. The higher prevalence observed among general services staff, who are not clinical professionals, may reflect greater reluctance among healthcare professionals to seek formal mental health assessment. Regarding contract type, the higher prevalence among permanent employees likely relates to the fact that short-term temporary contracts may not consistently involve attendance at occupational health services for routine health evaluations. Most participants did not have a formally recognized disability, and among those who did, mental health conditions were most frequently influenced by the inclusion criteria.
Lifestyle behaviors provided additional insight into mental health patterns. Alcohol consumption was predominantly occasional, with daily intake reported by a small minority, and consistent with prior studies, it was associated with poorer self-perceived mental health.[24–27] Patterns of tobacco use differed from national surveys, with a higher proportion of former smokers compared to never-smokers.[28] While data on cohabitation, leisure, and physical activity were incomplete due to participant nondisclosure, available information suggested that protective factors such as living with a partner, higher educational attainment, and engagement in leisure activities may contribute positively, although they do not negate the broader impact of the pandemic on mental health.
Several occupational factors were notable. The most common work pattern was a 12-hour rotating shift, a schedule associated with circadian disruption.[29] Multi-employment and work-life balance difficulties were generally low, although younger workers reported challenges consistent with existing literature.[30] Among those requiring job adaptations, 17.7% needed organizational measures specifically targeting mental health conditions, while other adaptations addressed physical health needs. Anxiety and schizophrenia spectrum disorders were the most frequent conditions among these workers, although no statistically significant associations were observed in this sample.
Regarding COVID-19 infection, most symptomatic workers experienced only mild disease, likely reflecting protective measures for COVID-19-sensitive ESWs and the early introduction of vaccination.[31] Medication also played a key role: workers receiving psychiatric treatment, particularly those requiring adjustments post-pandemic, and those increasing analgesic consumption, tended to report poorer mental health.[32] Additionally, age and alcohol consumption were associated with higher risk on the GHQ-12, suggesting an interaction between lifestyle factors and perceived mental health outcomes.[33]
Overall, this study provides a descriptive picture of mental health conditions among healthcare workers and the occupational and lifestyle factors associated with them. While the cross-sectional design limits causal inference, the findings emphasize the relevance of continuous monitoring and targeted support for workers exposed to high occupational stress and comorbidity.
4.1. Future Implications
The findings highlight the importance of early identification of workers at risk of mental health deterioration, including those with preexisting conditions, to provide timely support and reduce negative outcomes. Occupational health services can play a central role by implementing continuous monitoring, routine screenings, and tailored interventions that address both clinical and lifestyle-related risk factors such as alcohol consumption, medication adjustments, and increased analgesic use. Organizational adaptations, flexible scheduling, and preventive measures may further support workers’ well-being.
The pandemic emphasized the need for responsive occupational health strategies, including reassignment of ESW and interventions aimed at mitigating stressors. Future research should assess the effectiveness of these programs and explore longitudinal approaches to better understand the dynamics of mental health in healthcare professionals, ultimately informing policies that enhance resilience, reduce TI, and support workforce sustainability.[3]
5. Conclusion
Healthcare workers constitute a vulnerable population, particularly during periods of public health emergencies such as the COVID-19 pandemic. It is essential to identify occupational risk factors, including shift work, as well as personal factors such as alcohol consumption, not only to detect workers who already present mental health disorders but also to recognize those at risk of developing them. Early identification would enable the implementation of effective protective strategies across all levels of prevention, including primary, secondary, and tertiary measures, thereby strengthening occupational health frameworks and safeguarding workforce well-being. Ultimately, integrating continuous monitoring, targeted interventions, and support for at-risk staff is crucial to mitigate the influence of mental health challenges and maintain a resilient healthcare workforce.
Author contributions
Conceptualization: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Data curation: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Formal analysis: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Investigation: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Methodology: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Project administration: Lara Estefanía Jiménez-Ortega, María Ladisa, Juan Gómez-Salgado.
Resources: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Software: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Supervision: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Validation: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Visualization: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Writing – original draft: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Writing – review & editing: Lara Estefanía Jiménez-Ortega, María Ladisa, Manuel Delgado-Calderón, Juan Carlos Camacho-Vega, Ángel Vilches-Arenas, Luis El Khoury-Moreno, Julio Torrejón-Martínez, Juan Gómez-Salgado.
Abbreviations:
- COVID-19
- coronavirus disease 2019
- ESW
- especially sensitive worker
- GHQ-12
- General Health Questionnaire (12 items)
- OR
- odds ratio
- PTSD
- post-traumatic stress disorder
- TI
- temporary incapacity
The authors have no funding or conflicts of interest to disclose.
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
How to cite this article: Jiménez-Ortega LE, Ladisa M, Delgado-Calderón M, Camacho-Vega JC, Vilches-Arenas Á, El Khoury-Moreno L, Torrejón-Martínez J, Gómez-Salgado J. Occupational and lifestyle associations with mental health of healthcare workers. Medicine 2026;105:21(e48198).
Contributor Information
Lara Estefanía Jiménez-Ortega, Email: larae.jimenez.sspa@juntadeandalucia.es.
María Ladisa, Email: maria.ladisa.sspa@juntadeandalucia.es.
Manuel Delgado-Calderón, Email: manuel.delgado.calderon.sspa@juntadeandalucia.es.
Juan Carlos Camacho-Vega, Email: jccamacho@us.es.
Ángel Vilches-Arenas, Email: ava@us.es.
Luis El Khoury-Moreno, Email: lelkhoury@us.es.
Julio Torrejón-Martínez, Email: jtorrejon1@us.es.
References
- [1].International Labour Organisation. Convention 161: Convention concerning Occupational Health Services. International Labour Organisation; 1985. [Google Scholar]
- [2].Haro JM, Palacín C, Vilagut G, et al. Prevalencia de los trastornos mentales y factores asociados: resultados del estudio ESEMeD-España. [Prevalence of mental disorders and associated factors: results from the ESEMeD-Spain study]. Med Clin (Barc). 2006;126:445–51. [DOI] [PubMed] [Google Scholar]
- [3].Subdirección General de Información Sanitaria. Salud mental en datos: prevalencia de los problemas de salud y consumo de psicofármacos y fármacos relacionados a partir de registros clínicos de atención primaria. BDCAP Series 2. Ministerio de Sanidad. 2021. [Google Scholar]
- [4].Modini M, Joyce S, Mykletun A, et al. The mental health benefits of employment: Results of a systematic meta-review. Australas Psychiatry. 2016;24:331–6. [DOI] [PubMed] [Google Scholar]
- [5].Szuhany KL, Simon NM. Anxiety disorders: a review. JAMA. 2022;328:2431–45. [DOI] [PubMed] [Google Scholar]
- [6].Yoshimoto T, Matsudaira K, Oka H, Kasahara S, Kokaze A, Inoue S. Presenteeism caused by health conditions and its economic impacts among Japanese workers in the post-COVID-19 era. J Occup Environ Med. 2025;67:e227–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Sussell AL, Yeoman K, Nixon CT, Scott KA, Robinson TS, Poplin GS. US workers’ self-reported mental health outcomes by industry and occupation. JAMA Netw Open. 2025;8:e2514212. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [8].Jacob L, Smith L, Koyanagi A, et al. Impact of the coronavirus 2019 (COVID-19) pandemic on anxiety diagnosis in general practices in Germany. J Psychiatr Res. 2021;143:528–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [9].Alharbi AA, Alqassim AY, Muaddi MA, et al. Generalized anxiety disorder symptoms during COVID-19 pandemic in Jazan, Saudi Arabia. Heliyon. 2022;8:e09424. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [10].Douglas M, Katikireddi SV, Taulbut M, McKee M, McCartney G. Mitigating the wider health effects of covid-19 pandemic response. BMJ. 2020;369:m1557. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [11].Carmassi C, Foghi C, Dell’Oste V, et al. PTSD symptoms in healthcare workers facing the three coronavirus outbreaks: what can we expect after the COVID-19 pandemic. Psychiatry Res. 2020;292:113312. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [12].Khanlari P, NoorbalaTafti A, Ghasemi F, Ghiyasvandian S, Azam K, Zakerian SA. Identification and classification of risk factors for mental health problems in healthcare workers using a systemic framework: an umbrella review. BMC Public Health. 2025;25:1581. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].Galbany-Estragués P, Millán-Martínez P. Escasez de enfermeras en España: del caso global a la situación particular. Informe SESPAS 2024. [Shortage of nurses in Spain: from the global case to particular situation. SESPAS report 2024]. Gac Sanit. 2024;38:102376. [DOI] [PubMed] [Google Scholar]
- [14].Fernández-Martínez S, Armas-Landaeta C, Pérez-Aranda A, et al. Post-COVID job stressors and their predictive role on mental health: a cross-sectional analysis between physicians and nurses. SAGE Open Nurs. 2024;10:23779608241278861. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [15].Tsamakis K, Tsiptsios D, Ouranidis A, et al. COVID‑19 and its consequences on mental health (Review). Exp Ther Med. 2021;21:244. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [16].Magnúsdóttir I, Lovik A, Unnarsdóttir AB, et al. Acute COVID-19 severity and mental health morbidity trajectories in patient populations of six nations: an observational study. Lancet Public Health. 2022;7:e406–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [17].Rogers JP, Chesney E, Oliver D, et al. Psychiatric and neuropsychiatric presentations associated with severe coronavirus infections: a systematic review and meta-analysis with comparison to the COVID-19 pandemic. Lancet Psychiatry. 2020;7:611–27. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [18].Nicolini H. Depresión y ansiedad en los tiempos de la pandemia de COVID-19. [Depression and anxiety during COVID-19 pandemic]. Cir Cir. 2020;88:542–7. [DOI] [PubMed] [Google Scholar]
- [19].Imbali Vázquez D, Romero López-Alberca C. Trastorno obsesivo-compulsivo en tiempos de COVID-19: una revisión sistemática. Escr Psicol. 2021;14:145–55. [Google Scholar]
- [20].Bacigalupe A, Cabezas A, Bueno MB, Martín U. El género como determinante de la salud mental y su medicalización. Informe SESPAS 2020. [Gender as a determinant of mental health and its medicalization. SESPAS Report 2020]. Gac Sanit. 2020;34:61–7. [DOI] [PubMed] [Google Scholar]
- [21].Goldberg DP, Gater R, Sartorius N, et al. The validity of two versions of the GHQ in the WHO study of mental illness in general health care. Psychol Med. 1997;27:191–7. [DOI] [PubMed] [Google Scholar]
- [22].Wojujutari AK, Idemudia ES, Ugwu LE. The evaluation of the General Health Questionnaire (GHQ-12) reliability generalization: a meta-analysis. Khalid S, editor. PLoS One. 2024;19:e0304182. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [23].Sánchez-López MP, Dresch V. The 12-Item General Health Questionnaire (GHQ-12): reliability, external validity and factor structure in the Spanish population. Psicothema. 2008;20:839–43. [PubMed] [Google Scholar]
- [24].González-Moreno A, Pérez-Ríos M, Guerra-Tort C, et al. Evolución de la prevalencia de consumo de alcohol y caracterización del consumo de riesgo en España: 2005-2022. Med Clín. 2025;164:106909. [DOI] [PubMed] [Google Scholar]
- [25].Observatorio Español de las Drogas y las Adicciones. Informe 2021: alcohol, tabaco y drogas ilegales en España. Ministerio de Sanidad, Delegación del Gobierno para el Plan Nacional sobre Drogas; 2021. Disponible en: https://pnsd.sanidad.gob.es/profesionales/sistemasInformacion/informesEstadisticas/pdf/2021_Informe_OEDA.pdf [Google Scholar]
- [26].Halsall L, Irizar P, Burton S, et al. Hazardous, harmful, and dependent alcohol use in healthcare professionals: a systematic review and meta-analysis. Front Public Health. 2023;11:1304468. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [27].Instituto Nacional de Estadística. Encuesta Europea de Salud en España (EESE) 2020. Ministerio de Sanidad; 2020. Disponible en: https://www.sanidad.gob.es/estadEstudios/estadisticas/EncuestaEuropea/Enc_Eur_Salud_en_Esp_2020.htm [Google Scholar]
- [28].Rey-Brandariz J, Ruano-Ravina A, Santiago-Pérez MI, et al. Evolución de la prevalencia de consumo de tabaco en España y sus 17 comunidades autónomas (1987-2020). [Evolution of smoking prevalence in Spain and its 17 autonomous regions (1987-2020)]. Med Clín (Barc). 2024;162:417–24. [DOI] [PubMed] [Google Scholar]
- [29].Fagundo-Rivera J, Gómez-Salgado J, García-Iglesias JJ, Gómez-Salgado C, Camacho-Martín S, Ruiz-Frutos C. Relationship between night shifts and risk of breast cancer among nurses: a systematic review. Medicina. 2020;56:680. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [30].Navarro-Mateu F, Tormo MJ, Salmerón D, et al. Prevalence of mental disorders in the South-East of Spain, one of the European Regions most affected by the economic crisis: the cross-sectional PEGASUS-Murcia Project. Li S, editor. PLoS One. 2015;10:e0137293. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [31].Molina JD, Amigo F, Vilagut G, et al. Impact of COVID-19 first wave on the mental health of healthcare workers in a Front-Line Spanish Tertiary Hospital: lessons learned. Sci Rep. 2024;14:8149. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [32].Fernandes S, Sosa-Napolskij M, Lobo G, Silva I. Impact of the COVID-19 pandemic in the Portuguese population: consumption of alcohol, stimulant drinks, illegal substances, and pharmaceuticals. Patel SKS, editor. PLoS One. 2021;16:e0260322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [33].Roberts A, Rogers J, Mason R, et al. Alcohol and other substance use during the COVID-19 pandemic: a systematic review. Drug Alcohol Depend. 2021;229:109150. [DOI] [PMC free article] [PubMed] [Google Scholar]