Next Article in Journal
The Mediation Effect of Attitudes for the Association between Thoughts and the Use of Condoms in a Mobile-App Environment: From Thought to Intention
Next Article in Special Issue
Perceived Stress in Relation to Demographics and Clinical Forms among Patients with Infective Endocarditis: A Cross-Sectional Study
Previous Article in Journal
Job Insecurity and Intention to Quit: The Role of Psychological Distress and Resistance to Change in the UAE Hotel Industry
Previous Article in Special Issue
Wellbeing Training Based on Contemplative Practices in a Sample of Intensive Care and Homecare Professionals: A Pilot and Feasibility Non-Randomized Clinical Trial
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 19
Issue 20
10.3390/ijerph192013614
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Association between Working Time and Burnout Syndrome in Peruvian Military during the Second Epidemic Wave of COVID-19

by
Mario J. Valladares-Garrido
1,2,*,
Luis Eduardo Zapata-Castro
3,4,
Cinthia Karina Picón-Reategui
5,
Ana Paula Mesta-Pintado
5,
Ronald Alberto Picón-Reategui
5,
Mariana Huaman-Garcia
6,
César Johan Pereira-Victorio
7,
Danai Valladares-Garrido
6,8 and
Virgilio E. Failoc-Rojas
9,*
1
South American Center for Education and Research in Public Health, Universidad Norbert Wiener, Lima 15046, Peru
2
Oficina de Epidemiología, Hospital Regional Lambayeque, Chiclayo 14012, Peru
3
Escuela de Medicina, Universidad Nacional de Piura, Piura 20002, Peru
4
Scientific Society of Medical Students, Universidad Nacional de Piura, Piura 20002, Peru
5
Escuela de Medicina, Universidad de San Martín de Porres, Chiclayo 15011, Peru
6
Escuela de Medicina, Universidad Cesar Vallejo, Piura 13001, Peru
7
School of Medicine, Universidad Continental, Lima 15046, Peru
8
Unidad de Epidemiología y Salud Ambiental, Hospital de Apoyo II Santa Rosa, Piura 20008, Peru
9
Research Unit for Generation and Synthesis Evidence in Health, Universidad San Ignacio de Loyola, Lima 15024, Peru
*
Authors to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(20), 13614; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph192013614
Submission received: 14 September 2022 / Revised: 9 October 2022 / Accepted: 13 October 2022 / Published: 20 October 2022
(This article belongs to the Special Issue Development of Stress, Burnout and Occupational Hygiene)
Versions Notes

Abstract

:
There is scant evidence on the impact of the COVID-19 pandemic on burnout in front-line military personnel and how working time may influence on this condition. We aimed to determine the association between working time and Burnout syndrome in military personnel. A cross-sectional study was conducted using secondary data among 576 military personnel from Lambayeque, Peru during the second wave of COVID-19 in 2021. We used the Maslach Burnout Inventory instrument to measure Burnout Syndrome. We evaluated its association with work time, measured as the number of months that the military member worked during the pandemic. The prevalence of burnout syndrome was 9%. Of the total sample, 39.1% and 10.3% presented depersonalization and emotional exhaustion, respectively. Military personnel working for more than 18 months had a 104% higher prevalence of Burnout syndrome (PR: 2.04, 95%CI: 1.02–4.10). Exposure to a prolonged work time during the pandemic increased the prevalence of Burnout syndrome in military personnel. This information helps to understand the potential effects of the pandemic on this population and provides insight into the time the military members would need rest to prevent Burnout syndrome.

1. Introduction

The COVID-19 pandemic has had a major impact on mental health worldwide [1,2,3,4,5,6,7]. Burnout Syndrome (BS) is a mental health problem caused by overwork or stress and affects different types of workers [8,9,10]. During the COVID-19 pandemic, health, police, and military personnel led the frontline teams, so they were exposed to a high risk of direct contagion with people with suspected COVID-19. Military personnel have carried out multiple activities to ensure the safety, mobility, social distancing, and immunization of the population against COVID; they have provided support to health entities (Grupo Comando COVID-19 Sipán-Lambayeque Perú), food distribution, transfer of sick and dead people as a result of COVID-19, among others. [11,12]. For this reason, there has been an increase in cases of BS in the military, but also of emotional alterations, depersonalization disorder, and negative impact on aspects of their fulfillment [13].
Of Mexican policemen, it was found that 39.1% presented emotional exhaustion [14]. In another study, 32.9% of BS was estimated in a group of military personnel during the COVID-19 pandemic [15]. Likewise, at the beginning of the pandemic, a higher frequency of BS was reported in the military compared to the civilian population [15]. Furthermore, in another study conducted on military physicians in the United States, it was found that BS and emotional exhaustion affected 10% and 73%, respectively [16]. While in Brazilian police officers, a higher frequency of Burnout symptoms was reported in those who consumed alcohol and drugs, considering as possible risk factors [9]. Other multiple risk factors have been documented for the development of BS in the military: stress, time spent at work, and not having time to spend with family and friends, among others [13,14,15]. Conversely, some important protective factors for BS are physical activity, religious affiliation, personal self-realization, and job gratification [14,17], although there might be many others.
Multiple studies have evaluated the impact of COVID-19 on mental health [6,18,19]. However, most have focused on healthcare professionals, the general population, and even university students [20,21,22,23]. Additionally, there is inconclusive evidence on the effect of the pandemic on the development of emotional and/or physical exhaustion in the military [24]. Furthermore, previous studies have not measured potential influencing factors for the development of BS: having chronic diseases (arterial hypertension, obesity) [25] and seeking psychological help during the pandemic [14], which have been addressed in this research. Neither has the perception of military personnel regarding the government’s actions during the COVID-19 health emergency been analyzed [26,27], which would be considered as a possible factor observed by this type of population regarding the commitment of the authorities to support their workers. Our research is relevant because it is necessary to document solid evidence of the impact of COVID-19 on military burnout. In addition, information bias was present in previous research [28,29]. Another point not considered in similar studies on military workers is the lack of evaluation of circumstances such as the experience of post-traumatic stress since they work in dangerous situations and face critical incidents that can be potentially traumatic [14,29]. Additionally, other studies lack rigorous biostatistical methods and only focus on descriptive results [17,25,28].
Workload has been shown to affect mental health in the military. However, it is unknown how much the pandemic has affected this phenomenon. We propose that time on duty during this stage would entail prolonged time without leisure or family activities, which may increase the risk of BS. Therefore, this study aimed to identify whether working time is associated with BS in the Peruvian military personnel. For this purpose, we have proposed the following hypothesis: (1) The prevalence of BS in the Peruvian military personnel is high during the pandemic, (2) There are specific characteristics in this population that increases the prevalence of BS, and (3) higher time in service is independently associated with the development of BS.

2. Materials and Methods

2.1. Study Design and Population

An analytical cross-sectional study of secondary data analysis was carried out, whose objective was to evaluate whether working time influences the presence of Burnout Syndrome in military personnel in the Lambayeque region, Peru from 2 to 9 November 2021.
The population consisted of 820 military personnel who were working in the first line of attention in front of COVID-19 in the Lambayeque region, Peru during the second wave (2021). In the primary study, a sample size of 582 individuals was estimated using an expected prevalence of 12.8% [30], 99% confidence level, precision of 2.5%, and adding 20% of the sample to compensate for possible participant losses and rejections. A higher number of participants (n = 710) than required was obtained, representing 86.6% of the study population.
For the present analysis, records from 576 military personnel were used after excluding 134 observations with missing information of the Maslach Burnout Inventory (MBI), which measured the dependent variable. A convenience sampling method was used.

2.2. Procedure

First, permission was requested from Lambayeque military authorities. Then, the principal investigator trained the field team to conduct the interviews, under the supervision of the military officer and designed the questionnaires in REDCap, a data entry system with rigorous data collection, validation, and quality control characteristics. Interviews were conducted with military personnel in person using REDCap. A link to the questionnaire was created in REDCap and shared with the supervising military officer. The military population was organized into three groups in two daily shifts (morning and afternoon). Once the military was gathered, the officer in charge distributed the link via text message and/or WhatsApp. The military members then filled out the informed consent form and subsequently answered the questionnaires of interest from their phones. The field team was attentive to resolving doubts and technical problems that could arise at the time of filling out the interviews with the military. At all times, compliance with biosecurity measures was verified: correct use of masks, social distancing, use of alcohol gel for hand disinfection, and use of open spaces in military centers.

2.3. Measures

The dependent variable was BS, which was measured with the Maslach Burnout Inventory-Human Services Survey (MBI-HSS). The Spanish-validated version of the instrument was used [31,32]. It is composed of 22 questions divided into three dimensions, which uses a Likert scale from 0 (never) to 6 (every day): 9 emotional exhaustion (EE) questions, 5 depersonalization (DP) questions, and 8 personal realization (PR) questions. BS was operationally defined as military personnel who presented low levels of PR and high levels in the DP and EE dimensions [33]. We used tercile classification of each dimension, where values above the 66th percentile were considered high and those below the 33rd percentile as low. The MBI-HSS presents excellent psychometric properties of validity and reliability (comparative fit index-CFI: 0.91) [31,34]. In addition, high internal consistency has been estimated in each dimension: EE (Cronbach’s alpha: 0.84), DP (Cronbach’s alpha: 0.71) and PR (Cronbach’s alpha: 0.75) [35]. This instrument has been used in the military population of the Peruvian army [28,36,37]. In our research, we found optimal internal consistency. The overall Cronbach’s alpha was 0.91. In the dimensions of EE, DP, and PR we estimated a Cronbach’s alpha value of 0.90, 0.76, and 0.93, respectively.
The main independent variable was working time, operationally defined as the report of working time since the onset of the COVID-19 pandemic in months. This variable was categorized as 1 to 6 months, 7 to 12 months, 13 to 18 months, and 19 months or more.
Fear of COVID-19 was measured with the Fear of COVID-19 Scale (FCV-19S). This questionnaire consists of 7 questions and uses a Likert scale from 1 (strongly disagree) to 5 (strongly agree). It presents excellent levels of validity (test–retest reliability: 0.72) and reliability (Cronbach’s alpha: 0.72) in the general population [38].
The level of physical activity was assessed with the International Physical Activity Questionnaire, short version (IPAQ-S). This instrument collects self-reported information of the level of physical activity that the participant performed during the last 7 days through 4 domains (leisure time, transportation, work, and domestic activities) [39]. The short version is composed of 9 items. It presents adequate reliability and validity. It has been applied in the Latin American population [40,41] and during the COVID-19 pandemic [42].
General-psychosocial and other data section were the following: general variables were measured (age, sex, marital status, religion, having a child), report of pathological antecedents (harmful habits, body mass index, arterial hypertension), psychosocial (food insecurity, report of having sought help for mental health problems, trust in the government to manage the pandemic).

2.4. Statistical Analysis

Stata 17 was used for the data analysis.
Frequencies and percentages were estimated for descriptive analysis of categorical variables. For numerical variables, normal distribution was evaluated and then the best measure of central tendency and dispersion was estimated.
In the bivariate analysis, the chi-square test was used to evaluate the association of the independent variables for BS. For numerical variables, the nonparametric Mann–Whitney U test was used. A significance level of 5% was used.
To estimate whether working time and other covariates are associated with BS, prevalence ratios (PR) and confidence intervals (95%) were estimated using generalized linear models (GLM) with Poisson distribution, log link function, and robust variance. This technique allows analyzing dichotomous values of the outcome (No BS = 0, BS = 1), transforming the original scale into a logarithmic scale and increasing statistical precision by excluding outliers. The association of interest (working time and BS) was adjusted for the secondary independent variables. Potential collinearity between the independent variables included in the multiple regression model was evaluated with the variance inflation factor (VIF) test. All the variables entered the model since collinearity was not significant.

2.5. Ethical Aspects

The primary study was approved by the Ethics Committee of Universidad San Martin de Porres with document number 269-2022-CIEI-FMH-USMP. The confidentiality of the participants was maintained, and informed consent was requested from each military member. The database obtained for the analysis was anonymized.

3. Results

We analyzed a sample of 576 military personnel between 2 to 9 November 2021. The characteristics of participants are shown in Table 1.

3.1. Work Time and Other Factors Associated with Burnout Syndrome in Bivariate Analysis

We found statistically significant differences in the bivariate exploratory analysis between the prevalence of BS and the variables physical activity (p = 0.021) and work time (p = 0.006). Table 2 details the bivariate analysis.

3.2. Work Time and Other Factors Associated with Burnout Syndrome in Simple and Multiple Regression Analysis

In the simple regression model, we found that military personnel who had been working for 19 months or more during the COVID-19 pandemic had a 94% higher prevalence of presenting BS (PR: 1.94; 95%CI: 1.01–3.75). This association was maintained in the multiple regression, where the prevalence of BS increased by 104% in military personnel with that range of working time (19 months or more) (PR: 2.04, 95%CI: 1.02–4.10). Additionally, we found that divorced military personnel had a higher prevalence of BS than single military personnel (PR: 8.08; 95%CI: 2.05–31.82) (Table 3).
In the analysis of BS dimensions, we found that military personnel with working time longer than 18 months had a 30% lower prevalence of emotional exhaustion (PR: 0.46, 95%CI: 0.22–0.97). No statistically significant difference was observed between work time and the depersonalization and personal realization dimensions (Table 3).
Obese military personnel (PR: 3.21; 95%CI: 1.17–8.80) and with fear of COVID-19 (PR: 5.71; 95%CI: 3.43–9.0) had a higher prevalence of emotional exhaustion. In contrast, military personnel with non-Catholic religion were associated with a lower prevalence of this dimension (PR: 0.41; 95%CI: 0.17–0.98) (Table 3).
The prevalence of depersonalization increased in military members with food insecurity (PR: 1.29; 95%CI: 1.03–1.61) and fear of COVID-19 (PR: 2.03; 95%CI: 1.66–2.48). In the case of the personal fulfillment dimension, we found that military cohabiting (PR: 1.82; 95%CI: 1.13–2.94), Catholic (PR: 1.55; 95%CI: 1.08–2.22), high physical activity (PR: 2.24; 95%CI: 1.34–3.73) were positively associated with this dimension (Table 3).

4. Discussion

4.1. Prevalence of Burnout Syndrome

The prevalence of BS was 9% [43]. This is almost similar to that reported by Queirós C. et al. who documented a prevalence of 11% in police officers in a literature review covering 26 countries worldwide [29]. However, it differs from the findings in specific European countries such as Spain 28.5–43.6% and Germany 46.6% in police officers [11,14,43]. These heterogeneous findings could be explained by two reasons; first, by a difference between the instruments used to assess BS, among them the Spanish Burnout Inventory (SBI) and the Maslach Burnout Inventory (MBI) [44,45]. Secondly, there is a difference in the appearance of the SARS-CoV-2 waves, in Europe, the second wave was from 2020 to January 2021; while in Peru and Latin America it arrived later between January 2021–August 2021, which allowed more time for emergency preparedness and response [44,45]. Nonetheless, it is vital to emphasize that these data would be justified by the highly stressful workload of such personnel [11] since among their main activities would be to provide security in support-contingency facilities, preserve internal order with compliance with schedules during curfews and mandatory social immobilization, control social distancing in crowded places; as well as the transfer of patients to isolation zones and home visits in areas of very high epidemiological risk for COVID-19, which would explain the appearance of BS [46,47]. Additionally, added to the surveillance orders, order control, restrictions, economic consequences, limited resources in our health system, and a large number of deaths, created adverse exposures both at home and at work for military personnel, who have been deployed in the country to support pandemic response efforts [48].
In addition, we found that 1 in 10 military personnel experienced emotional exhaustion, and 39.1% experienced depersonalization. Emotional exhaustion is defined as a state in which an individual feels emotionally worn out and drained because of accumulated stress in one’s personal or work life. Depersonalization is defined as a distant or indifferent attitude towards work, which manifests itself as insensitive and cynical behavior. The result found in this study is higher than that reported by a study in Mexico where 30.7% were found in the military [15]. Additionally, it differs from that found in European studies with a prevalence of 58.0% [11]. This could be explained by the fact that military personnel is a different population group since they are constantly mediating agents in situations characterized by serious conflicts and tensions [9]. They stand out among other professionals due to their high level of stress, causing untimely physical-emotional exhaustion [9] which, added to the responsibility of making difficult decisions, together with concerns about their exposure and that of their family, generates a negative impact on mental health in the short and long term, especially because depersonalization can lead them to a loss of motivation with a feeling of isolation, in an environment of maximum responsibility [49].

4.2. Working Time and Burnout Syndrome

Working 19 months or more in the face of the COVID-19 pandemic almost double the prevalence of BS. To our knowledge, there is no documented evidence on military personnel. Some studies revealed that the COVID-19 pandemic increases the prevalence of burnout in health professionals by up to 80%, especially in countries with a high number of COVID-19 infections [50]. This finding could be explained given that our first line of COVID-19 containment, which includes military personnel, was exposed to high job strain for a longer time relative to other groups, including working in stressful situations due to constantly changing control measures, deployment to new environments and high-risk areas, resource shortfalls, and fear of transmitting infection [51]. However, the prevalence of emotional exhaustion is reduced to 54% in military personnel working 19 months or more. This differs from what is found in the literature, since there are few documented reports with the same amount of time that our study evaluated (e.g., a 40.9% prevalence of burnout at 15 months of work activity has been reported [52]). This finding could be explained by reduced emotional exhaustion during the study period since there was already a first vaccine coverage for frontline staff.

4.3. Factors Associated with Burnout Syndrome

In our research, we found that having a divorced marital status increases the prevalence of burnout syndrome. Currently, there is a knowledge gap regarding specific studies with burnout. Similar mental health outcomes have been reported with other outcomes such as being at the lowest level for mental functioning at 14.30% in divorced military personnel [53]. This is similar to that reported in the world literature, as divorce consistently ranks among the most stressful life events in adulthood [54]. Even 20% of divorcees experience pronounced psychological problems and lower well-being even years after their separation, in addition to being associated with core components of burnout such as stress, distress, decreased coping, and disengagement [54]. This finding may be justified given that the association with adverse mental health outcomes including the emotional burden of divorce and chronic stress, along with the increased likelihood of subsequent military deployment, has been robustly demonstrated [53].
Obesity increased the prevalence of emotional exhaustion by 221%. This is similar to that reported by Kress A. et al. who have reported that in military personnel obesity increased the prevalence by 33% and 240% among men and women, respectively, [25]. Despite this finding, there is no additional evidence in our group of interest. The medical literature indicates that there is reverse causality between obesity and other mental health problems [55]. Two meta-analyses reported positive associations between obesity and anxiety-depression disorders (OR: 1.40 and OR: 1.58 respectively) [56,57]. Another meta-analysis reported that obesity increases the prevalence of depression by 55% (pooled OR: 1.55) [55]. Additionally, it has been found that obese workers have a higher risk of emotional exhaustion than those with a healthy weight (OR: 1.28) [55].
Regarding depersonalization, we found that military personnel with food insecurity had a 29% higher prevalence of depersonalization. Food insecurity is defined as the condition of not having reliable access to enough affordable and nutritious foods. So far, there are no solid reports of this association in this study group. For example, Beymer M. et al. found that 32.8% of military personnel had food insecurity and that this was significantly related to other mental health outcomes such as anxiety, depression, and suicidal ideation (OR:1.82, OR:1.78, OR:1.78; respectively) associated in turn to leave the service [58]. This result suggests that food insecurity may influence diverse dimensions in mental health, including burnout.
In addition, military personnel with fear of COVID-19 significantly increased the prevalence of emotional exhaustion. This is similar to that reported by Martinez-Cuazitl et al. who reported 32.9% emotional exhaustion in military personnel [15]. Additionally, other studies found 35.7% with moderate and 31.9% with severe emotional exhaustion, being the main predictors of this condition the working hours, psychological comorbidities, and fear of infection [59]. This finding could be explained because fear is a key source of mental health problems related to anxiety and distress [60], especially in an environment where our military personnel seeks to comply with the provisions of the Peruvian government, where there are high rates of infection given that 50,616 confirmed cases and 787 deaths have been recorded in the police; while in military personnel a total of 2000 and 70, respectively, surpassing any other professional group in Peru [61,62].
Regarding personal fulfillment, we found that military personnel with a high level of physical activity increased the prevalence of personal fulfillment by 124%. This association is not documented in the literature with our population of interest. However, it has been described that physical activity influences well-being and personal realization, as well as pain avoidance [63]. This association could be explained by the fact that military personnel with a high level of physical activity probably generate significantly higher levels of life satisfaction, self-esteem, and happiness compared to inactive people, especially because the biological pathways of physical activity act as a buffer against stress and stress-related disorders, optimize neuroendocrine and physiological responses to stressors and promote an anti-inflammatory system, improving neuroplasticity along with growth factor expression [64], and even generate lower levels of anxiety; thus improving their self-efficacy and motivation during daily life [65,66].

4.4. Implications of Findings in Mental Health

Attention should be paid to this population group and their mental health treatment and prevention strategies, since in a context of a COVID-19 pandemic, added to other possible risk factors such as substance abuse and constant stress due to intense work schedules in the first line of containment, could worsen the panorama. Especially since it has been shown that mental health stigma still exists among military personnel [15], it is vital to reduce the gaps in care in this area of health. Additionally, these findings are important for the design of better mental health wellness interventions and policies that involve physical activity with great support for military personnel and their families during emergencies.

4.5. Limitations and Strengths

The main limitations of our study are firstly a possible measurement bias given that variables such as stress, level of job satisfaction, coping styles, and social support could not be assessed which could have influenced our BS outcome [67]. Second, there is a possible selection bias given that we cannot infer that our study had a large coverage of all military personnel, as we only had one study site. Finally, given our cross-sectional study design, it does not allow us to have the necessary temporality to the data collected to attribute causality.
Nevertheless, our study relies on the use of properly validated instruments, adapted to our reality and with optimal psychometric properties to assess the main mental health outcomes. Additionally, our research includes coverage of military personnel in a department severely hit by the COVID-19 pandemic in Peru, thus helping to measure the urgent need to implement better community mental health services needed for different population groups that are destined to preserve order and security as the first line of containment of the COVID-19 pandemic [47]. Under this scenario, the mental health of military personnel is a public health problem that needs to be addressed, our study shows solid and documented evidence to give rise to future follow-up studies in military personnel in the northern region of Peru.

5. Conclusions

This study evidenced that roughly nine out of 100 Peruvian military personnel experienced BS during the pandemic. In particular, working time was a significative factor that influenced this condition. Other factors associated with increased prevalence of BS were having a divorced marital status, fear of COVID-19, obesity, food insecurity, and a high level of physical activity. These findings suggest that some individuals need special mental health attention to prevent BS and other mental health outcomes. With this information, solid and first-hand evidence are provided to contribute to the development of better policies and better-implemented interventions to strengthen mental health prevention and control, especially during a national emergency context. For example, there may be workshops fostering physical exercise, improving conditions for personnel with families, and identifying and approaching individuals with multiple risk factors. Based on our results, a service time of less than 19 months may be necessary to provide sufficient rest and prevent BS.

Author Contributions

Conceptualization, M.J.V.-G.; Data curation, M.J.V.-G. and L.E.Z.-C.; Formal analysis, M.J.V.-G., L.E.Z.-C. and V.E.F.-R.; Investigation, L.E.Z.-C., C.K.P.-R., A.P.M.-P., R.A.P.-R. and M.H.-G.; Methodology, M.J.V.-G., L.E.Z.-C., C.K.P.-R., A.P.M.-P., R.A.P.-R. and M.H.-G.; Project administration, M.J.V.-G.; Resources, M.J.V.-G.; Software, M.J.V.-G.; Supervision, M.J.V.-G.; Validation, M.J.V.-G., C.J.P.-V., D.V.-G. and V.E.F.-R.; Visualization, C.J.P.-V., D.V.-G. and V.E.F.-R.; Writing—original draft, L.E.Z.-C., C.K.P.-R., A.P.M.-P., R.A.P.-R. and M.H.-G.; Writing—review and editing, M.J.V.-G., L.E.Z.-C., C.K.P.-R., A.P.M.-P., R.A.P.-R., M.H.-G., C.J.P.-V., D.V.-G. and V.E.F.-R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Universidad San Martin de Porres with document number 269-2022-CIEI-FMH-USMP.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The dataset generated and analyzed during the current study is not publicly available because the ethics committee has not provided permission/authorization to publicly share the data but are available from the corresponding author on reasonable request.

Acknowledgments

M.J.V.-G. was supported by the Fogarty International Center of the National Institutes of Mental Health (NIMH) under Award Number D43TW009343 and the University of California Global Health Institute.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Polizzi, C.; Giordano, G.; Burgio, S.; Lavanco, G.; Alesi, M. Maternal Competence, Maternal Burnout and Personality Traits in Italian Mothers after the First COVID-19 Lockdown. Int. J. Environ. Res. Public Health 2022, 19, 9791. [Google Scholar] [CrossRef]
  2. Valladares-Garrido, M.J.; Picón-Reátegui, C.K.; Zila-Velasque, J.P.; Grados-Espinoza, P. Prevalence and Factors Associated with Insomnia in Military Personnel: A Retrospective Study during the Second COVID-19 Epidemic Wave in Peru. Healthcare 2022, 10, 1199. [Google Scholar] [CrossRef]
  3. Rwafa-Ponela, T.; Price, J.; Nyatela, A.; Nqakala, S.; Mosam, A.; Erzse, A.; Lalla-Edward, S.T.; Hove, J.; Kahn, K.; Tollman, S.; et al. “We Were Afraid”: Mental Health Effects of the COVID-19 Pandemic in Two South African Districts. Int. J. Environ. Res. Public Health 2022, 19, 9217. [Google Scholar] [CrossRef]
  4. Ponce, V.V.; Garrido, M.V.; Peralta, C.I.; Astudillo, D.; Malca, J.T.; Manrique, E.O.; Quispe, E.T. Factores Asociados al Afrontamiento Psicológico Frente a La COVID-19 Durante El Periodo de Cuarentena. Rev. Cuba. Med. Mil. 2020, 49, 0200870. [Google Scholar]
  5. Fernandez-Canani, M.A.; Burga-Cachay, S.C.; Valladares-Garrido, M.J. Association between Family Dysfunction and Post-Traumatic Stress Disorder in School Students during the Second COVID-19 Epidemic Wave in Peru. Int. J. Environ. Res. Public Health 2022, 19, 9343. [Google Scholar] [CrossRef]
  6. Hernández-Díaz, Y.; Genis-Mendoza, A.D.; Ramos-Méndez, M.Á.; Juárez-Rojop, I.E.; Tovilla-Zárate, C.A.; González-Castro, T.B.; López-Narváez, M.L.; Nicolini, H. Mental Health Impact of the COVID-19 Pandemic on Mexican Population: A Systematic Review. Int. J. Environ. Res. Public Health 2022, 19, 6953. [Google Scholar] [CrossRef]
  7. Schmits, E.; Dekeyser, S.; Klein, O.; Luminet, O.; Yzerbyt, V.; Glowacz, F. Psychological Distress among Students in Higher Education: One Year after the Beginning of the COVID-19 Pandemic. Int. J. Environ. Res. Public Health 2021, 18, 7445. [Google Scholar] [CrossRef] [PubMed]
  8. Raudenská, J.; Steinerová, V.; Javůrková, A.; Urits, I.; Kaye, A.D.; Viswanath, O.; Varrassi, G. Occupational Burnout Syndrome and Post-Traumatic Stress among Healthcare Professionals during the Novel Coronavirus Disease 2019 (COVID-19) Pandemic. Best Pract. Res. Clin. Anaesthesiol. 2020, 34, 553–560. [Google Scholar] [CrossRef]
  9. Santos Chaves, M.S.R.; Shimizu, I.S. Burnout Syndrome and Sleep Quality among Military Police Officers in Piaui. Rev. Bras. Med. Trab. 2020, 16, 436–441. [Google Scholar] [CrossRef] [Green Version]
  10. Dimitriu, M.C.T.; Pantea-Stoian, A.; Smaranda, A.C.; Nica, A.A.; Carap, A.C.; Constantin, V.D.; Davitoiu, A.M.; Cirstoveanu, C.; Bacalbasa, N.; Bratu, O.G.; et al. Burnout Syndrome in Romanian Medical Residents in Time of the COVID-19 Pandemic. Med. Hypotheses 2020, 144, 109972. [Google Scholar] [CrossRef]
  11. Gómez-Galán, J.; Lázaro-Pérez, C.; Martínez-López, J.Á.; del Fernández-Martínez, M.M. Burnout in Spanish Security Forces during the COVID-19 Pandemic. Int J. Environ. Res. Public Health 2020, 17, 8790. [Google Scholar] [CrossRef]
  12. Lambayeque: Ministra de Defensa y Autoridades Articulan Esfuerzos Para Evitar Rebrote del Covid. Available online: https://elperuano.pe/noticia/112037-lambayeque-ministra-de-defensa-y-autoridades-articulan-esfuerzos-para-evitar-rebrote-del-covid (accessed on 26 May 2022).
  13. Ram, V.; Bhakta, J.P.; Roesch, S.; Millegan, J. Reducing Stress and Burnout in Military Healthcare Professionals through Mind–Body Medicine: A Pilot Program. Mil. Med. 2021, 186, usab389. [Google Scholar] [CrossRef]
  14. García-Rivera, B.R.; Olguín-Tiznado, J.E.; Aranibar, M.F.; Ramírez-Barón, M.C.; Camargo-Wilson, C.; López-Barreras, J.A.; García-Alcaraz, J.L. Burnout Syndrome in Police Officers and Its Relationship with Physical and Leisure Activities. Int. J. Environ. Res. Public Health 2020, 17, 5586. [Google Scholar] [CrossRef]
  15. Martínez-Cuazitl, A.; Martínez-Salazar, I.N.; Maza-De La Torre, G.; García-Dávila, J.A.; Montelongo-Mercado, E.A.; García-Ruíz, A.; Noyola-Villalobos, H.F.; García-Araiza, M.G.; Hernández-Díaz, S.; Villegas-Tapia, D.L.; et al. Burnout Syndrome in a Military Tertiary Hospital Staff during the COVID-19 Contingency. Int. J. Environ. Res. Public Health 2022, 19, 2229. [Google Scholar] [CrossRef]
  16. Williams, B.J.; Rudinsky, S.L.; Matteucci, M.J. Burnout in Military Emergency Medicine Resident Physicians: A Cross-Sectional Study With Comparisons to Other Physician Groups. Mil. Med. 2020, 185, e331–e334. [Google Scholar] [CrossRef] [Green Version]
  17. Solís, J.L.R.; González, T.M. Síndrome de burnout y satisfacción de vida en policías ministeriales mexicanos. Arch. Criminol. Segur. Priv. Y Crim. 2015, 3, 1–17. [Google Scholar]
  18. Paterlini, M.; Neri, E.; Nicoli, A.; Genova, F.; Villani, M.T.; Santi, S.; Agostini, F. Emotions, Stress and Coping among Healthcare Workers in a Reproductive Medicine Unit during the First and Second COVID-19 Lockdowns. Int. J. Environ. Res. Public Health 2022, 19, 5899. [Google Scholar] [CrossRef]
  19. Seda-Gombau, G.; Montero-Alía, J.J.; Moreno-Gabriel, E.; Torán-Monserrat, P. Impact of the COVID-19 Pandemic on Burnout in Primary Care Physicians in Catalonia. Int. J. Environ. Res. Public Health 2021, 18, 9031. [Google Scholar] [CrossRef]
  20. León-Rodríguez, D.A.; Bautista Castro, L.R.; Gómez Acosta, C.A.; Rincón, G.A.; Neme, W.O. Percepción de la afectación atribuida a la pandemia por COVID-19 en padres y madres de Colombia. Revlatinofamilia 2022, 14, 29–50. [Google Scholar] [CrossRef]
  21. Jiang, Y. Problematic Social Media Usage and Anxiety Among University Students During the COVID-19 Pandemic: The Mediating Role of Psychological Capital and the Moderating Role of Academic Burnout. Front. Psychol. 2021, 12, 612007. [Google Scholar] [CrossRef]
  22. Kumpikaitė-Valiūnienė, V.; Aslan, I.; Duobienė, J.; Glińska, E.; Anandkumar, V. Influence of Digital Competence on Perceived Stress, Burnout and Well-Being Among Students Studying Online During the COVID-19 Lockdown: A 4-Country Perspective. Psychol. Res. Behav. Manag. 2021, 14, 1483–1498. [Google Scholar] [CrossRef]
  23. García-Iglesias, J.J.; Gómez-Salgado, J.; Martín-Pereira, J.; Fagundo-Rivera, J.; Ayuso-Murillo, D.; Martínez-Riera, J.R. Impacto del SARS-COV-2 (COVID-19) en la Salud Mental de los Profesionales Sanitarios: Una Revisión Sistemática. Rev. Esp. Salud Pública 2020, 94, e1–e20. [Google Scholar]
  24. Sargent, P.; Millegan, J.; Delaney, E.; Roesch, S.; Sanders, M.; Mak, H.; Mallahan, L.; Raducha, S.; Webb-Murphy, J. Health Care Provider Burnout in a United States Military Medical Center During a Period of War. Mil. Med. 2016, 181, 136–142. [Google Scholar] [CrossRef]
  25. Kress, A.M.; Peterson, M.R.; Hartzell, M.C. Association between Obesity and Depressive Symptoms among U.S. Military Active Duty Service Personnel, 2002. J. Psychosom. Res. 2006, 60, 263–271. [Google Scholar] [CrossRef] [PubMed]
  26. Enríquez, A.; Sáenz, C. Primeras Lecciones y Desafíos de la Pandemia de COVID-19 Para Los Países del SICA; CEPAL: Mexico City, Mexico, 2021; 106p. [Google Scholar]
  27. Ybaseta-Medina, J.; Becerra-Canales, B. El Personal de salud en la Pandemia por COVID-19. Rev. Médica Panacea 2020, 9, 72–73. [Google Scholar] [CrossRef]
  28. Castro Rojas, M.C.; Urquizo Maggia, J.A.; Leiva Loayza, E.I.; Castro Rojas, M.C.; Urquizo Maggia, J.A.; Leiva Loayza, E.I. Prevalencia Del Síndrome de Burnout En Personal Militar Del Instituto Geográfico Nacional Del Perú. Enfermería Glob. 2022, 21, 424–446. [Google Scholar] [CrossRef]
  29. Queirós, C.; Passos, F.; Bártolo, A.; Marques, A.J.; da Silva, C.F.; Pereira, A. Burnout and Stress Measurement in Police Officers: Literature Review and a Study With the Operational Police Stress Questionnaire. Front. Psychol. 2020, 11, 587. [Google Scholar] [CrossRef]
  30. Pietrzak, R.H.; Tsai, J.; Southwick, S.M. Association of Symptoms of Posttraumatic Stress Disorder With Posttraumatic Psychological Growth Among US Veterans During the COVID-19 Pandemic. JAMA Netw. Open 2021, 4, e214972. [Google Scholar] [CrossRef]
  31. Gilla, M.A.; Belén Giménez, S.; Moran, V.E.; Olaz, F.O. Adaptación y Validación Del Inventario de Burnout de Maslach En Profesionales Argentinos de La Salud Mental. Liberabit 2019, 25, 179–193. [Google Scholar] [CrossRef]
  32. Mejia, C.R.; Rojas, C.; Talledo-Ulfe, L.; Vilca, Z.P.; Valladares-Garrido, M.J.; Sánchez-Arteaga, K.; Cruz, B.; Ruiz-Arimuya, J.J. Síndrome de Burnout y factores asociados en estudiantes de medicina. Estudio multicéntrico en siete facultades de medicina peruanas. Rev. Chil. Neuropsiquiatría 2016, 54, 207–214. [Google Scholar] [CrossRef] [Green Version]
  33. Maticorena-Quevedo, J.; Beas, R.; Anduaga-Beramendi, A.; Mayta-Tristán, P. Prevalencia Del Síndrome de Burnout En Médicos y Enfermeras Del Perú, ENSUSALUD 2014. Rev. Peru. Med. Exp. Y Salud Publica 2016, 33, 241–247. [Google Scholar] [CrossRef] [Green Version]
  34. Cañadas-de la Fuente, G.A.; San Luis, C.; Manuel Lozano, L.; Vargas, C.; García, I.; de la Fuente, E.I. Evidencia de validez factorial del Maslach Burnout Inventory y estudio de los niveles de burnout en profesionales sanitarios. Rev. Latinoam. Psicol. 2014, 46, 44–52. [Google Scholar] [CrossRef] [Green Version]
  35. Gil-Monte, P.R. Factorial Validity of the Maslach Burnout Inventory (MBI-HSS) among Spanish Professionals. Rev. Saude Publica 2005, 39, 1–8. [Google Scholar] [CrossRef] [PubMed]
  36. Santiago Prado, A.F.; Paredes Jara, F.A. Dimensiones del Síndrome de Burnout y Estilos de Afrontamiento en Militares Profesionales del Ejército Peruano de la Séptima Brigada de Infanteria en Lambayeque, 2015. 2015. Available online: http://repositorio.upagu.edu.pe/handle/UPAGU/409 (accessed on 10 September 2022).
  37. Saborío Morales, L.; Hidalgo Murillo, L.F. Síndrome de Burnout. Med. Leg. Costa Rica 2015, 32, 119–124. [Google Scholar]
  38. Ahorsu, D.K.; Lin, C.-Y.; Imani, V.; Saffari, M.; Griffiths, M.D.; Pakpour, A.H. The Fear of COVID-19 Scale: Development and Initial Validation. Int. J. Ment. Health Addict. 2022, 20, 1537–1545. [Google Scholar] [CrossRef] [Green Version]
  39. Wolin, K.Y.; Heil, D.P.; Askew, S.; Matthews, C.E.; Bennett, G.G. Validation of the International Physical Activity Questionnaire-Short among Blacks. J. Phys. Act. Health 2008, 5, 746–760. [Google Scholar] [CrossRef] [Green Version]
  40. Salvo, D.; Reis, R.S.; Sarmiento, O.L.; Pratt, M. Overcoming the Challenges of Conducting Physical Activity and Built Environment Research in Latin America: IPEN Latin America. Prev Med. 2014, 69 (Suppl. 1), S86–S92. [Google Scholar] [CrossRef] [Green Version]
  41. Nicaise, V.; Crespo, N.C.; Marshall, S. Agreement between the IPAQ and Accelerometer for Detecting Intervention-Related Changes in Physical Activity in a Sample of Latina Women. J. Phys. Act. Health 2014, 11, 846–852. [Google Scholar] [CrossRef]
  42. Castañeda-Babarro, A.; Arbillaga-Etxarri, A.; Gutiérrez-Santamaría, B.; Coca, A. Physical Activity Change during COVID-19 Confinement. Int J. Environ. Res. Public Health 2020, 17, 6878. [Google Scholar] [CrossRef]
  43. Santa Maria, A.; Wolter, C.; Gusy, B.; Kleiber, D.; Renneberg, B. Reducing Work-Related Burnout among Police Officers: The Impact of Job Rewards and Health-Oriented Leadership. Police J. 2021, 94, 406–421. [Google Scholar] [CrossRef]
  44. Benítez, M.A.; Velasco, C.; Sequeira, A.R.; Henríquez, J.; Menezes, F.M.; Paolucci, F. Responses to COVID-19 in Five Latin American Countries. Health Policy Technol. 2020, 9, 525–559. [Google Scholar] [CrossRef] [PubMed]
  45. Cacciapaglia, G.; Cot, C.; Sannino, F. Second Wave COVID-19 Pandemics in Europe: A Temporal Playbook. Sci Rep. 2020, 10, 15514. [Google Scholar] [CrossRef] [PubMed]
  46. Sheard, I.; Burnett, M.E.; St Clair-Thompson, H. Psychological Distress Constructs in Police with Different Roles. Int. J. Emerg. Serv. 2019, 8, 264–279. [Google Scholar] [CrossRef]
  47. Ministra De Defensa Destaca El Trabajo Articulado Del Plan Sipán Para Superar La Pandemia. Available online: https://www.gob.pe/institucion/mindef/noticias/500975-ministra-de-defensa-destaca-el-trabajo-articulado-del-plan-sipan-para-superar-la-pandemia (accessed on 19 April 2022).
  48. Wynn, G.; Morganstein, J.C.; Jetly, R.; Ford, S.C.; Vance, M.C.; Meyer, E.G.; West, J.C.; Benedek, D.M.; Ursano, R.J. Military Mental Health and COVID-19. J. Mil. Veteran Fam. Health 2020, 6, 21–26. [Google Scholar] [CrossRef]
  49. Martínez-López, J.Á.; Lázaro-Pérez, C.; Gómez-Galán, J.; del Fernández-Martínez, M.M. Psychological Impact of COVID-19 Emergency on Health Professionals: Burnout Incidence at the Most Critical Period in Spain. JCM 2020, 9, 3029. [Google Scholar] [CrossRef]
  50. Morgantini, L.A.; Naha, U.; Wang, H.; Francavilla, S.; Acar, Ö.; Flores, J.M.; Crivellaro, S.; Moreira, D.; Abern, M.; Eklund, M.; et al. Factors Contributing to Healthcare Professional Burnout during the COVID-19 Pandemic: A Rapid Turnaround Global Survey. PLoS ONE 2020, 15, e0238217. [Google Scholar] [CrossRef]
  51. Armocida, B.; Formenti, B.; Ussai, S.; Palestra, F.; Missoni, E. The Italian Health System and the COVID-19 Challenge. Lancet Public Health 2020, 5, e253. [Google Scholar] [CrossRef] [Green Version]
  52. Kijima, S.; Tomihara, K.; Tagawa, M. Effect of Stress Coping Ability and Working Hours on Burnout among Residents. BMC Med. Educ 2020, 20, 219. [Google Scholar] [CrossRef]
  53. Wang, L.; Seelig, A.; Wadsworth, S.M.; McMaster, H.; Alcaraz, J.E.; Crum-Cianflone, N.F. Associations of Military Divorce with Mental, Behavioral, and Physical Health Outcomes. BMC Psychiatry 2015, 15, 128. [Google Scholar] [CrossRef] [Green Version]
  54. Hald, G.M.; Ciprić, A.; Strizzi, J.M.; Sander, S. “Divorce Burnout” among Recently Divorced Individuals. Stress Health 2020, 36, 457–468. [Google Scholar] [CrossRef]
  55. Proper, K.I.; Koppes, L.L.J.; Meijer, S.; Bemelmans, W.J.E. The Association Between Body Mass Index Status and Sick Leave and the Role of Emotional Exhaustion—A Mediation Analysis Among a Representative Sample of Dutch Employees. J. Occup. Environ. Med. 2013, 55, 1213–1218. [Google Scholar] [CrossRef] [PubMed]
  56. Gariepy, G.; Nitka, D.; Schmitz, N. The Association between Obesity and Anxiety Disorders in the Population: A Systematic Review and Meta-Analysis. Int. J. Obes. 2010, 34, 407–419. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Luppino, F.S.; de Wit, L.M.; Bouvy, P.F.; Stijnen, T.; Cuijpers, P.; Penninx, B.W.J.H.; Zitman, F.G. Overweight, Obesity, and Depression: A Systematic Review and Meta-Analysis of Longitudinal Studies. Arch. Gen. Psychiatry 2010, 67, 220. [Google Scholar] [CrossRef]
  58. Beymer, M.R.; Reagan, J.J.; Rabbitt, M.P.; Webster, A.E.; Watkins, E.Y. Association between Food Insecurity, Mental Health, and Intentions to Leave the US Army in a Cross-Sectional Sample of US Soldiers. J. Nutr. 2021, 151, 2051–2058. [Google Scholar] [CrossRef] [PubMed]
  59. Giusti, E.M.; Pedroli, E.; D’Aniello, G.E.; Stramba Badiale, C.; Pietrabissa, G.; Manna, C.; Stramba Badiale, M.; Riva, G.; Castelnuovo, G.; Molinari, E. The Psychological Impact of the COVID-19 Outbreak on Health Professionals: A Cross-Sectional Study. Front. Psychol. 2020, 11, 1684. [Google Scholar] [CrossRef]
  60. Gasparro, R.; Scandurra, C.; Maldonato, N.M.; Dolce, P.; Bochicchio, V.; Valletta, A.; Sammartino, G.; Sammartino, P.; Mariniello, M.; di Lauro, A.E.; et al. Perceived Job Insecurity and Depressive Symptoms among Italian Dentists: The Moderating Role of Fear of COVID-19. Int J. Environ. Res. Public Health 2020, 17, 5338. [Google Scholar] [CrossRef]
  61. Hernández-Vásquez, A.; Azañedo, D. COVID-19 in Peru: The Need to Pay Attention to the High Number of Police Deaths Due to the Pandemic. J. Public Health 2020, 42, 640–641. [Google Scholar] [CrossRef]
  62. Mininter: Policía Es La Institución Pública Con Más Fallecidos a Causa Del COVID-19|Noticias|Agencia Peruana de Noticias Andina. Available online: https://andina.pe/agencia/noticia-mininter-policia-es-institucion-publica-mas-fallecidos-a-causa-del-covid19-853721.aspx (accessed on 19 April 2022).
  63. Lawton, E.; Brymer, E.; Clough, P.; Denovan, A. The Relationship between the Physical Activity Environment, Nature Relatedness, Anxiety, and the Psychological Well-Being Benefits of Regular Exercisers. Front. Psychol. 2017, 8, 1058. [Google Scholar] [CrossRef] [Green Version]
  64. Silverman, M.N.; Deuster, P.A. Biological Mechanisms Underlying the Role of Physical Fitness in Health and Resilience. Interface Focus. 2014, 4, 20140040. [Google Scholar] [CrossRef] [Green Version]
  65. Martyn, P.; Brymer, E. The Relationship between Nature Relatedness and Anxiety. J. Health Psychol 2016, 21, 1436–1445. [Google Scholar] [CrossRef]
  66. Iwon, K.; Skibinska, J.; Jasielska, D.; Kalwarczyk, S. Elevating Subjective Well-Being Through Physical Exercises: An Intervention Study. Front. Psychol. 2021, 12, 702678. [Google Scholar] [CrossRef] [PubMed]
  67. Kok, B.C.; Herrell, R.K.; Grossman, S.H.; West, J.C.; Wilk, J.E. Prevalence of Professional Burnout Among Military Mental Health Service Providers. Psychiatr. Serv. 2016, 67, 137–140. [Google Scholar] [CrossRef] [PubMed]
Table
Table 1. Characteristics of participants.
Table 1. Characteristics of participants.
CharacteristicsN (%)
Age (years) *22 (19–32)
Gender
Female31 (5.4)
Male545 (94.6)
Marital status
Single420 (72.9)
Married136 (23.6)
Cohabitant13 (2.3)
Divorced7 (1.2)
Religion
None83 (14.4)
Catholic401 (69.6)
Non-Catholic92 (16.0)
Children
No417 (72.4)
Yes159 (27.6)
Alcoholism
No477 (82.8)
Yes99 (17.2)
Hypertension
No522 (90.6)
Yes54 (9.4)
BMI (categorized) †
Underweight/Normal339 (59.8)
Overweight189 (33.3)
Obesity39 (6.9)
Seeking mental health help
No530 (92.0)
Yes46 (8.0)
Trust in government to handle COVID-19
Yes310 (53.8)
No266 (46.2)
Food insecurity
No296 (51.4)
Yes280 (48.6)
Physical activity
Low64 (11.1)
Moderate 39 (6.8)
High473 (82.1)
Fear of COVID-19 †
No424 (80.8)
Yes101 (19.2)
Work time †
1 to 6 months146 (25.9)
7 to 12 months89 (15.8)
13 to 18 months 123 (21.9)
19 months or more205 (36.4)
Emotional exhaustion
No517 (89.8)
Yes59 (10.2)
Depersonalization
No351 (60.9)
Yes225 (39.1)
Personal realization
No333 (57.8)
Yes243 (42.2)
Burnout Syndrome
No524 (91.0)
Yes52 (9.0)
* Median (25th percentile–75th percentile). † The sum of the variables is not 576 due to missing values.
Table
Table 2. Characteristics associated with burnout syndrome in the military.
Table 2. Characteristics associated with burnout syndrome in the military.
VariablesBurnout Syndromep *
No (n = 524)Yes (n = 52)
n (%)n (%)
Age (years) ***22 (19–31.5)20 (19–35)0.422 **
Gender 0.607
Female29 (93.6)2 (6.5)
Male495 (90.8)50 (9.2)
Marital status 0.329
Single384 (91.4)36 (8.6)
Married123 (90.4)13 (9.6)
Cohabitant12 (92.3)1 (7.7)
Divorced5 (71.4)2 (28.6)
Religion 0.951
None76 (91.6)7 (8.4)
Catholic365 (91.0)36 (9.0)
Non-Catholic83 (90.2)9 (9.8)
Children 0.834
No380 (91.1)37 (8.9)
Yes144 (90.6)15 (9.4)
Alcoholism 0.057
No429 (89.9)48 (10.1)
Yes95 (96.0)4 (4.0)
Hypertension 0.350
No473 (90.6)49 (9.4)
Yes51 (94.4)3 (5.6)
BMI (categorized) 0.956
Underweight/Normal308 (90.9)31 (9.1)
Overweight172 (91.0)17 (9.0)
Obesity36 (92.3)3 (7.7)
Seeking mental health help 0.536
No481 (90.8)49 (9.3)
Yes43 (93.5)3 (6.5)
Trust in government to handle COVID-19 0.079
Yes276 (89.0)34 (11.0)
No248 (93.2)18 (6.8)
Food insecurity 0.213
No265 (89.5)31 (10.5)
Yes259 (92.5)21 (7.5)
Physical activity 0.021
Low63 (98.4)1 (1.6)
Moderate 38 (97.4)1 (2.6)
High423 (89.4)50 (10.6)
Fear of COVID-19 0.072
No378 (89.2)46 (10.9)
Yes96 (95.1)5 (5.0)
Time of work 0.006
1 to 6 months135 (92.5)11 (7.5)
7 to 12 months86 (96.6)3 (3.4)
13 to 18 months 115 (93.5)8 (6.5)
19 months or more175 (85.4)30 (14.6)
* p-value of categorical variables calculated with Chi-Square test.; ** p-value of categorical-numerical variables calculated with the U-test (Mann–Whitney).; *** Median—interquartile range.
Table
Table 3. Factors associated with burnout syndrome and its dimensions.
Table 3. Factors associated with burnout syndrome and its dimensions.
CharacteristicsBurnout SyndromeEmotional ExhaustionDepersonalizationPersonal Realization
Simple RegressionMultiple RegressionSimple RegressionMultiple RegressionSimple RegressionMultiple RegressionSimple RegressionMultiple Regression
PRCI 95%p *PRCI 95%p *PRCI 95%p *PRCI 95%p *PRCI 95%p *PRCI 95%p *PRCI 95%p *PRCI 95%p *
Age (years) 1.000.97–1.030.8711.000.95–1.040.8450.980.95–1-010.1220.990.95–1.040.8080.990.98–1.000.051.000.98–1.020.8131.011.00–1.020.0621.000.98–1.020.927
Gender
FemaleRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
Male1.420.36–5.580.6141.260.35–4.570.7271.070.35–3.220.910.690.17–2.790.6041.010.64–1.600.9541.160.3–2.150.6310.720.52–1.010.0550.780.54–1.130.192
Marital status
SingleRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
Married1.120.61–2.040.7241.650.54–5.090.3820.51.0.25–1.040.0650.400.10–1.700.2160.670.50–0.890.0060.530.31–0.900.0201.271.03–1.560.0261.290.84–1.980.238
Cohabitant0.900.13–6.010.9121.330.27–6.520.7240.660.10–4.410.6660.550.09–3.380.5180.720.32–1.640.4310.440.13–1.510.1891.581.01–2.480.0441.821.13–2.940.014
Divorced3.330.99–11.220.0528.082.05–31.820.0031.220.19–7.650.8310.580.10–3.260.5391.000.42–2.340.9990.480.16–1.490.2041.100.46–2.620.8241.330.58–3.070.503
Religion
NoneRef. Ref Ref. Ref. Ref. Ref. Ref. Ref.
Catholic1.060.49–2.310.8741.070.51–2.210.8640.650.35–1.190.1610.580.31–1.110.0991.210.87–1.690.2531.220.87–1.710.2531.721.18–2.490.0051.551.08–2.220.017
Non-Catholic1.160.45–2.980.7581.330.55–3.240.5250.670.30–1.510.3310.410.17–0.980.0441.350.92–1.990.1281.210.81–1.790.3521.520.98–2.350.0611.440.94–2.200.092
Children
NoRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
Yes1.060.60–1.880.8340.680.27–1.720.4130.740.41–1.340.3251.510.49–4.640.4720.770.59–0.990.0381.150.72–1.840.5591.281.05–1.560.0150.890.60–1.320.563
Alcoholism
NoRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
Yes0.400.15–1.090.0730.400.14–1.160.0921.510.86–2.640.1481.270.72–2.220.4051.230.97–1.570.0891.170.90–1.530.2420.990.76–1.280.9170.950.73–1.250.721
Hypertension
NoRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
Yes0.590.19–1.840.3640.720.25–2.120.5521.090.49–2.420.8320.960.41–2.250.9270.940.65–1.350.7370.850.58–1.240.4050.610.38–0.960.0340.750.49–1.150.189
BMI (categorized)
Underweight/NormalRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
Overweight0.980.56–1.730.9540.760.38–1.520.4381.120.66–1.910.6661.620.84–3.140.1510.790.62–1.000.0530.860.66–1.120.2591.070.87–1.310.5320.920.72–1.180.524
Obesity0.840.27–2.630.7660.510.11–2.440.4011.350.56–3.270.5013.211.17–8.800.0230.970.65–1.450.8951.220.78–1.900.3891.070.73–1.560.7360.980.65–1.460.909
Seeking mental health help
NoRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
Yes0.710.23–2.180.5440.780.26–2.300.6542.071.09–3.930.0271.810.95–3.430.071.180.85–1.650.3271.130.81–1.590.4711.100.79–1.530.5780.980.69–1.390.913
Trust in government to handle COVID-19
YesRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
No0.620.36–1.070.0840.880.51–1.530.6500.800.49–1.310.3740.770.44–1.340.3531.140.93–1.390.2221.080.87–1.340.4970.820.67–1.000.0520.820.67–1.010.063
Food insecurity
NoRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
Yes0.720.42–1.220.2170.660.39–1.100.1101.440.88–2.350.1461.430.88–2.320.1531.301.06–1.590.0131.291.03–1.610.0241.020.84–1.240.8470.990.81–1.210.918
Physical activity
LowRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
Moderate 1.640.11–25.550.7241.680.10–27.460.7170.730.24–2.210.5770.980.37–2.620.9681.200.77–1.860.4161.230.80–1.870.3471.520.81–2.900.1981.650.85–3.210.140
High6.770.95–48.220.0567.150.86–59.520.0690.690.36–1.350.2830.710.34–1.460.3480.940.68–1.290.7061.020.75–1.390.9042.071.29–3.330.0032.241.34–3.730.002
Fear of COVID-19
NoRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
Yes0.460.19–1.120.0870.590.25–1.370.2215.253.21–8.58<0.0015.713.43–9.50<0.0012.161.78–2.62<0.0012.031.66–2.48<0.0011.160.92–1.460.2211.190.94–1.520.147
Time of work
1 to 6 monthsRef. Ref. Ref. Ref. Ref. Ref. Ref. Ref.
7 to 12 months0.450.13–1.560.2070.480.14–1.650.2461.040.53–2.030.9180.970.48–2.000.9361.110.83–1.490.4971.130.84–1.530.4281.080.77–1.520.6691.010.71–1.430.956
13 to 18 months 0.860.36–2.080.7430.950.36–2.450.9080.880.46–1.690.7030.740.38–1.420.3661.160.89–1.510.2711.150.86–1.530.3511.090.80–1.480.5941.070.76–1.490.707
19 months or more1.941.01–3.750.0482.041.02–4.100.0440.450.23–0.900.0240.460.22–0.970.0410.700.52–0.930.0130.800.58–1.100.1651.391.08–1.800.0111.270.95–1.690.104
* p-values obtained with Generalized Linear Models (GLM), Poisson family, log-link function, robust variance.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Valladares-Garrido, M.J.; Zapata-Castro, L.E.; Picón-Reategui, C.K.; Mesta-Pintado, A.P.; Picón-Reategui, R.A.; Huaman-Garcia, M.; Pereira-Victorio, C.J.; Valladares-Garrido, D.; Failoc-Rojas, V.E. Association between Working Time and Burnout Syndrome in Peruvian Military during the Second Epidemic Wave of COVID-19. Int. J. Environ. Res. Public Health 2022, 19, 13614. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph192013614

AMA Style

Valladares-Garrido MJ, Zapata-Castro LE, Picón-Reategui CK, Mesta-Pintado AP, Picón-Reategui RA, Huaman-Garcia M, Pereira-Victorio CJ, Valladares-Garrido D, Failoc-Rojas VE. Association between Working Time and Burnout Syndrome in Peruvian Military during the Second Epidemic Wave of COVID-19. International Journal of Environmental Research and Public Health. 2022; 19(20):13614. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph192013614

Chicago/Turabian Style

Valladares-Garrido, Mario J., Luis Eduardo Zapata-Castro, Cinthia Karina Picón-Reategui, Ana Paula Mesta-Pintado, Ronald Alberto Picón-Reategui, Mariana Huaman-Garcia, César Johan Pereira-Victorio, Danai Valladares-Garrido, and Virgilio E. Failoc-Rojas. 2022. "Association between Working Time and Burnout Syndrome in Peruvian Military during the Second Epidemic Wave of COVID-19" International Journal of Environmental Research and Public Health 19, no. 20: 13614. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph192013614

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop