Skip to main content
International Journal of Environmental Research and Public Health logoLink to International Journal of Environmental Research and Public Health
. 2023 Feb 28;20(5):4331. doi: 10.3390/ijerph20054331

Psycho-Emotional Factors Associated with Depressive Symptoms during Lockdown Due to the COVID-19 Pandemic in the Mexican Population

Nora A Martínez-Vélez 1, Miriam Arroyo-Belmonte 1, Marcela Tiburcio 1,*, Guillermina Natera-Rey 1, Morise Fernández-Torres 1, Graciela Y Sánchez-Hernández 1
Editor: Jie Zhang1
PMCID: PMC10002454  PMID: 36901346

Abstract

The COVID-19 pandemic has had a significant impact on mental health, leading to the increase of depressive symptoms. Identifying these symptoms and the factors associated with them in women and men will allow us to understand possible mechanisms of action and develop more specific interventions. An online survey was conducted from 1 May to 30 June 2020 using snowball sampling; the final sample comprised 4122 adult inhabitants of Mexico; 35% of the total sample displayed moderate-to-severe depressive symptoms, with a greater proportion of depression being among female respondents. A logistic regression analysis revealed that individuals under 30 years of age, those with high levels of stress due to social distancing, those with negative emotions, and those who reported a significant impact of the pandemic on their lives have a higher risk of depression. Women with a history of mental health treatment and men with a history of chronic disease were also more likely to experience depressive symptoms. Social environment and sex are factors that intervene in the development of depressive symptoms, meaning that appropriate early identification and intervention models should be designed for the care of men and women in highly disruptive situations such as the recent pandemic.

Keywords: mental health, depressive symptomatology, COVID-19

1. Introduction

The public health emergency caused by COVID-19 began in December 2019, with the first cases in Mexico being identified in February 2020 and the declaration of a national emergency in the country at the end of March 2020 [1]. This emergency posed complex challenges for the general population as, in addition to the obvious consequences for physical health, it affected the mental health of men and women [2]. Much of the literature published to date has identified an increase in moderate or severe symptoms of acute stress, anxiety, and depression [3,4,5,6,7,8,9]. Since the start of the pandemic, there has been a worldwide increase of 27.6% in depressive disorders, with women and young people being the most affected [10]. Mexico has been no exception: an online survey of medical students conducted from April to December 2020 found that the prevalence of depressive symptoms increased during that period from 19.84% to 40.8% [11].

Few studies, however, have analyzed the factors behind this increase. Stress is well-known as a trigger of depressive reactions, fear, and anxiety [12,13,14,15,16]. Stressors related to previous natural disasters and accidents have been linked to declines in mental health not just during these events, but for many months or years after the events [17,18].

The stress generation model of depression (SGMD) [19,20] has substantially contributed to an advanced understanding of the relationship between stress and depression and of the factors and mechanisms involved in its persistence and recurrence; it allows us to understand that not all domains of stressful life events have an equal effect on people’s health. This model differentiates the impact of factors associated with the discord in people’s interpersonal relationships and the factors of their context (such as financial stress, academic or work difficulties, and poor health) in the shaping of depression [12,19,20]. The COVID-19 pandemic affected interpersonal relationships through restrictions on social interactions [21], and it has also generated contextual changes such as disruptions in employment, personal finances, and work–life balance [22,23].

However, we do not know if these factors have affected women and men equally or if they have had a differentiated impact on this increase in depression. Studies carried out at the start of the pandemic have found that being female, younger (particularly under 35 years of age), and having less education or financial resources were variables that were associated with the presence of depressive symptoms [9,16,24]. Other studies, however, suggest that various factors have been associated with a higher risk of depression during the COVID-19 pandemic. Early in the pandemic, pre-existing mental health conditions, living alone, and marital status were associated with elevated levels of anxiety and/or depression [25]. Physical health conditions, being in close contact with people with COVID-19, mental comorbidity, coping styles, stigmas, psychosocial support, personal protection measures, risk of contracting COVID-19, and concerns that a family member would be infected were also associated with depression [2,26].

In addition to these contextual stress factors, psycho-emotional factors also play a fundamental role in the configuration of depressive symptomatology. A pandemic triggers an emotional response [27] that can range from risk denial to high levels of fear and anxiety [28]. Some studies have suggested that women tend to be more worried, anxious, scared, sad, and angry than men [29,30]. The SGMD has also recognized the important role of emotion as an associated factor, which is usually conceptualized in broad categories such as negative versus positive emotions [31]. For example, it has been observed that positive affect may facilitate resilience in the presence of stressors and reduce vulnerability to mental health disorders [32].

Although there is evidence of differences between women and men in the stress and worry experienced during the pandemic, the contextual and psycho-emotional correlates that imply a greater risk of developing depressive symptoms have not been accurately identified. The purpose of this article, therefore, is to estimate the prevalence of depressive symptoms and to identify the influence of psycho-emotional and contextual stress factors associated with the COVID-19 pandemic on depressive symptoms in men and women in the early months of the pandemic lockdown. We expected to find similar results to those reported in previous research conducted, where the impact on women’s mental health is more severe than on men.

2. Materials and Methods

This was an exploratory descriptive study, and data was collected using an online survey; the main objective of the study was to explore substance use and the presence of mental health problems during the lockdown due to the COVID-19 pandemic.

The online survey was conducted using Google Forms in May and June of 2020, the period in which Mexico experienced the strictest lockdown. The link to the questionnaire was published on the official social media accounts (Facebook, (Zuckerberg, Saverin, McCollum, Moskovitz & Hughes, 2004, Cambridge, MA, USA), Twitter, (Dorsey, Williams, Glass & Stone, 2006, San Francisco, CA, USA) and WhatsApp (Acton, Koum, WhatsApp LLC, Menlo Park, CA, USA; Meta Platforms, Inc. version 2.21.15.20, 2009, Cambridge, MA, USA)) of the Ramón de la Fuente Muñiz National Institute of Psychiatry. A total of 4122 individuals were surveyed. All of them were aged 18 years or over, were residents of Mexico, and provided consent for their voluntary participation [33]. The questionnaire comprised 13 sections; however, we have only reported on the following:

Ten questions about sex, age, educational attainment, marital status, occupation, state of origin, income, and family characteristics.

Adversity and Stress Scale: Eleven questions formulated for this study were used to measure the stress level caused by the pandemic in different aspects of life during the previous month. The questions were divided into two groups: (a) relational stress, derived from the effects on social interactions at school or work or on the management of free time (six items); and (b) contextual stress, associated with changes in a person’s social and economic status (five items). There were five response options on a Likert scale ranging from 0 (“not at all or only slightly stressful”) to 4 (“very stressful”). The evaluation of the scale’s psychometric characteristics yielded a reliability coefficient of 0.86 for this sample [34].

Patient Health Questionnaire-2 (PHQ-2): This questionnaire included the first two questions from the PHQ-9, which identified depressive symptomatology in the previous two weeks. There were four response options ranging from 0 (“never”) to 3 (“almost every day”) with a maximum possible score of 6 [35]. In Mexico, the discriminating power of this questionnaire has been evaluated with indigenous women, and the best cutoff point found was 3, with a sensitivity of 80% and a specificity of 86.8% [36]. The reliability coefficient for this sample was 0.78. In the meta-analysis by Levis et al. [37], the cut-off point of ≥3 has a 72% sensitivity and 85% specificity independent of the respondent’s sex.

Perceived threat and experiences with coronavirus: This was a short version of three scales developed by Conway, Woodard, and Zubrod [38] that explore the perceived threat of the coronavirus (three items, α = 0.89: “Thinking about the coronavirus [COVID-19] makes me feel threatened”, “I am afraid of the coronavirus [COVID-19]”, and “I am stressed around other people because I worry I’ll catch the coronavirus [COVID-19]”), the impact of the coronavirus (six items, α = 0.84: “The coronavirus [COVID-19] has impacted me negatively from a financial point of view”, “I have lost job-related income due to the coronavirus [COVID-19]”, “I have had a hard time getting needed resources (food, toilet paper) due to the coronavirus [COVID-19]”, “It has been difficult for me to get the things I need due to the coronavirus [COVID-19]”, “I have become depressed because of the coronavirus [COVID-19]”, and “the coronavirus (COVID-19) outbreak has impacted my psychological health negatively”), and experiences with coronavirus (seven items, α = 0.71: “I have been diagnosed with the coronavirus [COVID-19]”, “I have had coronavirus-like symptoms at some point in the past two months”, “I have been sick from something other than the coronavirus in the past two months”, “I have been in close proximity with someone who has been diagnosed with coronavirus [COVID-19]”, “I have been in close proximity with someone who has had coronavirus-like symptoms in the last two months”, “I watch a lot of news about the coronavirus [COVID-19]”, and “I spend a huge percentage of my time trying to find updates online or on TV about coronavirus [COVID-19]”). The scales, translated into Spanish for this study, contain seven Likert responses ranging from 1 (“not true of me at all”) to 7 (“very true of me”) [33].

Emotional state: This questionnaire was created for the study; it is a list of 12 feelings, consisting of six positive (happiness, hope, pleasantness, joy, relaxation, tranquility) and six negative (boredom, stress, fear, vulnerability, worry, despair) emotions that could be experienced during the lockdown.

Descriptive statistics were used to determine the sociodemographic characteristics of the respondents. The mean score and dimensions of the scales and the prevalence of depressive symptomatology (PHQ-2 score ≥ 3) were obtained. X2 and Student’s t-tests were performed to evaluate the differences by sex. The effect size was measured with Cramer’s V coefficient for X2 tests and Cohen’s d for t-tests. Binomial logistic regression models were used to identify the factors associated with depressive symptomatology in men and women. Th adjusted odds ratios (OR) are reported with 95% confidence intervals (CI). The Hosmer–Lemeshow test was used to assess the fit of the models. All statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) for Windows (version 25.0, IBM Corp., Armonk, NY, USA).

3. Results

3.1. Respondent Characteristics

A total of 4122 responses were obtained. Only 28.2% of the respondents were men; the majority of respondents were aged 21–40 years (55.9%), were unpartnered (57.1%), had completed undergraduate and postgraduate studies (77.2%), and were employed (69.1%) (for more details about the survey, see Martínez-Vélez et al. [33]).

As can be seen in Table 1, significant differences were found between men and women in the psychosocial factors associated with the pandemic. More women than men reported having previously been in treatment for mental health (29.9% vs. 21.9%) together with a higher percentage of depressive symptoms (38.2% vs. 28.1%) and higher stress scores in interpersonal interactions. Likewise, women reported experiencing negative feelings more often than men and felt more threatened from the coronavirus. Conversely, men reported a greater number of previous chronic diseases than women (34.7% vs. 22.1%) and higher scores on the context-related stress (family economy, family health, socio-economic status); men also reported experiencing more positive feelings with statistically significant differences in relation to women.

Table 1.

Percentage distribution of the psychosocial factors associated with the pandemic by sex.

Men Women Total
(n = 1160) (n = 2962) (n = 4122)
f % f % f % X2/df p V *
Previous chronic illness
No 757 65.3 2051 69.2 2808 68.1 6.096/1 0.014 0.038
Yes 403 34.7 911 30.8 1314 31.9
Tx mental health in the past 12 months
No 906 78.1 2076 70.1 2982 72.3 26.768/1 0.000 0.081
Yes 254 21.9 886 29.9 1140 27.7
Depressive symptomatology
PHQ2 ≤ 2 834 71.9 1831 61.8 2665 64.7 37.062/1 0.000 0.095
PHQ2 ≥ 3 326 28.1 1131 38.2 1457 35.3
Mean SD Mean SD Mean SD t/df p d **
Relational stress 1.08 0.90 1.30 0.92 1.24 0.92 −6.95/4120 0.000 0.245
Contextual stress 1.44 1.02 1.73 1.04 1.63 1.05 −8.16/4120 0.000 0.285
Positive emotions during lockdown 17.52 5.58 16.92 5.27 17.08 5.36 3.15/4120 0.001 −0.107
Negative emotions during lockdown 16.77 6.46 19.58 6.30 18.79 6.47 −12.79/4120 0.000 0.435
Impact of coronavirus 15.97 8.68 16.22 8.65 16.15 8.66 −0.84/4120 0.401 0.029
Experiences of coronavirus 14.97 7.35 14.75 7.22 14.81 7.25 0.87/4120 0.386 −0.029
Threat of coronavirus 8.63 5.11 9.97 5.61 9.59 5.50 −7.32/4120 0.000 0.261

* Cramer’s V; ** Cohen’s d.

3.2. Depressive Symptoms

The respondents with depressive symptoms were mostly women, aged 21–30 years, single, and with bachelor’s degrees. People who reported having been in treatment for a mental health problem in the previous 12 months showed the highest percentages of depressive symptoms, and this difference was statically significant; however, the effect size of this difference was low. On the other hand, the lowest scores of depressive symptoms were reported among the group of respondents aged 31–40 years. The highest levels of stress, negative emotions or feelings, impact of coronavirus, experiences with the virus, and feeling threatened by COVID-19 were reported by people with three or more symptoms of depression (Table 2).

Table 2.

Percentage distribution of the demographic data and psychosocial factors associated with the pandemic due to depressive symptomatology.

Without Depressive Symptomatology
(PHQ2 ≤ 2)
With Depressive Symptomatology
(PHQ2 ≥ 3)
(n = 2665) (n = 1457)
f % f % X2/df p V *
Sex
Male 834 31.3 326 22.4 37.062/1 0.000 0.095
Female 1831 68.7 1131 77.6
Age
18–20 years 143 5.4 180 12.4 239.444/4 0.000 0.241
21–30 years 609 22.9 549 37.7
31–40 years 765 28.7 380 26.1
41–50 years 600 22.5 218 15.0
51 years or over 548 20.6 130 8.9
Marital Status
Single 1102 41.4 828 56.8 92.644/3 0.000 0.150
Married/partnered 1274 47.8 496 34.0
Divorced/separated 252 9.5 118 8.1
Widowed 37 1.4 15 1.0
Education
Elementary/Jr. High 75 2.8 49 3.4 26.799/3 0.000 0.117
High School 450 16.9 367 25.2
Bachelor’s Degree 1413 53.0 756 51.9
Graduate Degree 727 27.3 285 19.6
Occupation
Homemaker 129 4.8 75 5.1 175.391/5 0.000 0.206
Unemployed b/l 81 3.0 89 6.1
Unemployed s/l 105 3.9 97 6.7
Employed 1608 60.3 639 43.9
Student 332 12.5 366 25.1
Self-employed 410 15.4 191 13.1
Previous chronic illness
No 1819 68.3 989 67.9 0.061/1 0.807 0.004
Yes 846 31.7 468 32.1
Mental health Tx in the past 12 months
No 2103 78.9 879 60.3 162.575/1 0.000 0.199
Yes 562 21.1 578 39.7
Mean SD Mean SD t/df p d **
Pandemic-related stress
Relational stress 0.89 0.74 1.87 0.88 −37.826/4120 0.000 1.323
Contextual stress 1.32 0.92 2.24 1.00 −29.534/4120 0.000 0.990
Positive emotions during lockdown 18.38 5.23 14.72 4.76 22.143/4120 0.000 −0.699
Negative emotions during lockdown 16.38 5.78 23.21 5.24 −37.462/4120 0.000 1.181
Impact of coronavirus 13.73 7.45 20.57 8.97 −26.149/4120 0.000 0.980
Experiences of coronavirus 13.54 6.54 17.13 7.90 −15.590/4120 0.000 0.547
Threat of coronavirus 8.47 4.99 11.65 5.80 −18.434/4120 0.000 0.636

* Cramer´s V; ** Cohen’s d.

3.3. Identification of Factors Associated with Depressive Symptoms in Women and Men

The factors associated with depressive symptoms during the COVID-19 lockdown are shown in Table 3. The logistic regression model for men showed that those aged 18–20 years (OR = 2.74, 95% CI [1.33, 5.64]), and those aged 21–30 years (OR = 1.7, 95% CI [1.03, 9.96]) were more likely to present with depressive symptoms than those aged 51 years or over. Those who had a previous history of chronic disease were more likely to have symptoms (OR = 0.69, 95% CI [0.47, 1.48]) than those who did not. Furthermore, those who reported more stress associated with interpersonal relationships (OR = 1.8, 95% CI [1.44, 2.42]), more negative emotions (OR = 1.1, 95% CI [1.13, 1.22]), those experiencing a greater impact of COVID-19 (OR = 1.0, 95% CI [1.01, 1.05]), those with a greater degree of experience of the pandemic (OR = 1.0, 95% CI [1.01, 1.05]), and those with a greater perceived threat from COVID-19 (OR = 0.929, 95% CI [0.981–0.969]) were more likely to present depressive symptoms than those who reported lower levels of these factors.

Table 3.

Factors associated with the depressive symptomatology during lockdown by sex.

Risk of Depressive Symptomatology
Men * Women **
(n = 1160) (n = 2962)
OR p OR p
Social vulnerability
Age
51 years or over 1 - 1
18–20 years 2.74 0.01 4.62 0.00
21–30 years 1.72 0.05 1.90 0.00
31–40 years 0.96 0.89 1.37 0.07
41–50 years 0.82 0.52 1.12 0.52
Psychobiological vulnerability
Previous chronic illness
No 1 - 1 -
Yes 0.63 0.01 0.91 0.37
Tx mental health disorder in the past 12 months
No 1 - 1 -
Yes 0.69 0.06 0.77 0.01
Impact of COVID pandemic
Pandemic-related stress
Relational stress 1.87 0.00 1.64 0.00
Contextual stress 0.95 0.657 1.10 0.18
Positive emotions during lockdown 0.94 0.00 0.87 0.00
Negative emotions during lockdown 1.17 0.00 1.15 0.00
Impact of coronavirus 1.04 0.00 1.03 0.00
Experiences due to coronavirus 1.03 0.02 1.00 0.68
Threat of coronavirus 0.93 0.00 0.98 0.08

* Logistic regression model in men (χ2 = 460.26, gl = 13, p < 0.001); Hosmer–Lemeshow test (χ2 = 9.61, gl = 8, p = 0.294). The model explained between 33% Cox & Snell and 47% Negelkerke of the variance. The total correct prediction was 81%, and it included 57% of those who had depressive symptoms and 91% of those who did not. ** Logistic regression model in women (χ2 = 1296.24, gl = 13, p < 0.001); Hosmer–Lemeshow test (χ2 = 21.53, gl = 8, p = 0.06). The model explained between 35% Cox & Snell and 48% Negelkerke of the variance. The total correct prediction was 80%, and it included 70% of those who had depressive symptoms and 86% of those who did not.

Younger women were also more likely to present depressive symptoms than women over 51 years old. Having been in mental health treatment in the past 12 months increased the risk of presenting depressive symptoms (OR = 0.77, 95% CI [0.63, 0.95]). Those who reported more stress associated with interpersonal relationships (OR = 1.6, 95% CI [1.40, 1.89]), more negative emotions (OR = 1.1, 95% CI [1.12, 1.17]), and those with a greater impact of the coronavirus (OR = 1.0, 95% CI [1.02, 1.05]) were more likely to present depressive symptoms than those who reported lower levels of these factors.

4. Discussion

This study estimated the prevalence of depressive symptoms and their contextual and psycho-emotional correlates among Mexican women and men during the early months of the COVID-19 pandemic lockdown. It was found that 38% of women and 28% of men presented depressive symptoms. The prevalence of these symptoms was much higher than that reported in previous studies in Mexico, which has ranged between 12% and 25% depending on the study population [36,39]; furthermore, it was much higher than the prevalence of major depressive disorder in Mexico, which is estimated to be present in 7.2% of the general population [40]. A similar prevalence of depressive symptoms has been identified as a result of the pandemic in countries such as China and Spain with a greater proportion being found in women than in men [7,8].

Our results suggest that the COVID-19 pandemic has substantially affected the mental health of men and women in Mexico, and these findings are consistent with previous studies that reported that exposure to public health emergencies, such as in the case of the Ebola and SARS outbreaks, can cause mental health problems [41,42]. Global evidence supports the observation of this upward trend in depression symptoms due to emotional distress and stressors related to COVID-19, including the disruption of social relationships, isolation, fears of illness and economic loss, and concern for one’s own health and that of loved ones, all of which can trigger depression or exacerbate existing symptoms [21]. The survey showed high percentages of people who reported that they feared that their mental health would be affected by COVID-19 (between 87% and 92%). There was also a high level of negative emotions experienced during lockdown together with significant stress levels associated with the pandemic.

This high prevalence of stress and negative emotions, especially regarding relationships, was significantly linked to the presence of depressive symptoms for both sexes. These findings coincide with the stress generation model of depression (SGMD), which has documented that both interpersonal and non-interpersonal stress are well-established risk factors for major depressive disorder, with interpersonal stress having the greatest impact [12,19,20]. It has also been observed that positive emotions significantly reduce the effects of interpersonal stress on the severity of depressive symptoms, while negative emotions increase the effects of non-interpersonal stress on their severity [32].

For both men and women, the stressful effect of the COVID-19 pandemic lockdown on areas of life such as personal relationships and the changes in context or life situations led to a situation of continuous tension from different sources, including the economic status and health of the family, which resulted in an increased risk for depressive symptoms [43,44,45].

While the predictors of depressive symptomatology were similar between men and women, there were some differences between the two groups. In general, women tend to experience negative emotions more intensely than men, which can make them more susceptible to depression. The review study of Bracke et al. [46] points to the association between gender inequality and depression, showing that gender differences in depression converge in contexts of greater gender equality and increase in contexts of greater inequality. These effects compound the consequences for the mental health of taking on work and family functions at different stages of life. The SGMD also allows us to understand how gender can shape depression. For example, there is evidence that stress linked to interpersonal relationships can be greater for women, in part because of the greater emphasis such relationships have in women’s lives, especially those characterized by caring for others and emotional closeness [47].

On the other hand, in the case of men, having a pre-existing physical illness and experiencing direct encounters with COVID-19 (experiences of coronavirus) were more associated with depressive symptoms than in women. Rutland-Lawes et al. [48] also identified that a long-standing illness, together with other factors such as alcohol use, living alone/not alone, and employment status were all significant predictors of change in depression scores in men. In this sense, we can hypothesize that the loss of health or functionality and the risk of getting sick could be important predictors of depressive symptoms in men.

The findings of this study allow for a better, timely understanding of the psychological consequences of contingencies such as the COVID-19 pandemic, which is essential for several reasons. First, there is a high prevalence of psychological problems among those directly or indirectly exposed to potentially stressful situations. Such problems can affect the daily functioning of a substantial number of people and can cause immediate social and economic consequences, such as the loss of productivity at work and financial difficulties. Strategies for protecting the psychological health of men and women through mental health interventions are crucial for preventing or offsetting interruptions in the delivery of health services during emergencies.

There is an important need for a greater focus on and understanding of the effect of the environment on depressive disorders in men and women, which is better understood through solid frameworks and hypothetical constructs such as the SGMD. Empirical findings and new perspectives can greatly contribute to our understanding of these phenomena and also to the construction of interventions promoting mental health that are sensitive to differences in gender at times of great stress, such as in the recent pandemic.

Limitations. This study has certain limitations. First, its cross-sectional design means that causality cannot be inferred from the results. Second, since the population was under lockdown, the data were collected online through convenience sampling, and the results are therefore not generalizable to the entire population. Third, the answers were self-reported, which may have led to information biases. Finally, the lack of evidence about the validity of the PHQ-2 survey for assessing depressive symptoms among Mexican males is a limitation of our study, although some studies [37] do not make distinctions by gender regarding its sensibility and specificity. Therefore, the results should be taken with caution.

5. Conclusions

The findings of this study provide information on the structure and correlates of stress associated with the COVID-19 pandemic and their influence on the presence of depressive symptoms; they add to the knowledge on how socioenvironmental risk influences mental health [49]. The results also shed light on the nature and degree of psychological responses to the pandemic and have the potential to serve as a basis for the development of health promotion and prevention strategies which, together with existing efforts, have the potential to contain the burden of mental illness. The study shows that strategies that promote the mental health of the population should be encouraged to prepare for this type of contingency.

Acknowledgments

The authors are grateful to the Ramón de La Fuente Muñiz National Institute of Psychiatry for all of the facilities provided.

Author Contributions

Conceptualization, M.T., G.N.-R., N.A.M.-V., M.A.-B., G.Y.S.-H. and M.F.-T. formal analysis, M.A.-B. and N.A.M.-V.; investigation, M.T., G.N.-R., N.A.M.-V., M.A.-B., G.Y.S.-H. and M.F.-T.; data curation, N.A.M.-V. and M.A.-B.; writing—original draft preparation, N.A.M.-V. and M.A.-B.; writing—review and editing, M.T., N.A.M.-V. and M.A.-B. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The research protocol and data collection for this study were approved by the Ethics Committee of the Ramón de la Fuente Muñiz National Institute of Psychiatry (Approval No. CEI/C/011/2020).

Informed Consent Statement

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

Data Availability Statement

Not available.

Conflicts of Interest

The authors declare that they have no conflict of interest.

Funding Statement

This research received no external funding.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

References

  • 1.Secretaría de Salud Casos Confirmados a Enfermedad por COVID-19. Comunicado Técnico Diario. [(accessed on 30 May 2020)]. Available online: https://www.gob.mx/salud/documentos/coronavirus-covid-19-comunicado-tecnico-diario-238449.
  • 2.Hossain M.M., Tasnim S., Sultana A., Faizah F., Mazumder H., Zou L., Lizako E., McKyer J., Ahmed H.U., Ma P. Epidemiology of mental health problems in COVID-19: A review. F1000Research. 2020;9:2–16. doi: 10.12688/f1000research.24457.1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.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. 2020;20:1537–1545. doi: 10.1007/s11469-020-00270-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Li S., Wang Y., Xue J., Zhao N., Zhu T. The impact of COVID-19 epidemic declaration on psychological consequences: A study on active Weibo users. Int. J. Environ. Res. Public Health. 2020;17:2032. doi: 10.3390/ijerph17062032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Qiu J., Shen B., Zhao M., Wang Z., Xie B., Xu Y. A nationwide survey of psychological distress among Chinese people in the COVID-19 epidemic: Implications and policy recommendations. Gen. Psychiatry. 2020;33:e100213. doi: 10.1136/gpsych-2020-100213. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Roy D., Tripathy S., Kar S.K., Sharma N., Verma S.K., Kaushal V. Study of knowledge, attitude, anxiety & perceived mental healthcare need in Indian population during COVID-19 pandemic. Asian J. Psychiatry. 2020;51:102083. doi: 10.1016/j.ajp.2020.102083. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Rodríguez R., Garrido H., Collado S. Psychological impact and associated factors during the initial stage of the coronavirus (COVID-19) pandemic among the general population in Spain. Front. Psychol. 2020;11:1540. doi: 10.3389/fpsyg.2020.01540. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Wang C., Pan R., Wan X., Tan Y., Xu L., Ho C.S., Ho R.C. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int. J. Environ. Res. Public Health. 2020;17:1729. doi: 10.3390/ijerph17051729. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Xiong J., Lipsitz O., Nasri F., Lui L.M., Gill H., Phan L., Chen-Li D., Iacobucci M., Ho R., Majeed A., et al. Impact of COVID-19 pandemic on mental health in the general population: A systematic review. J. Affect. Disord. 2020;277:55–64. doi: 10.1016/j.jad.2020.08.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.COVID-19 Mental Disorders Collaborators Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. Lancet. 2021;398:1700–1712. doi: 10.1016/S0140-6736(21)02143-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Domínguez A.D., Guzmán G., Ángeles F.S., Manjarrez M.A., Secín R. Depression and suicidal ideation in Mexican medical students during COVID-19 outbreak. A longitudinal study. Heliyon. 2022;8:e08851. doi: 10.1016/j.heliyon.2022.e08851. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Connolly N.P., Eberhart N.K., Hammen C.L., Brennan P.A. Specifi city of stress generation: A comparison of adolescents with depressive, anxiety, and comorbid diagnoses. J. Cogn. Ther. 2010;3:368–379. doi: 10.1521/ijct.2010.3.4.368. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Gotlib I.H., Joormann J. Cognition and depression: Current status and future directions. Annu. Rev. Clin. Psychol. 2010;6:285–312. doi: 10.1146/annurev.clinpsy.121208.131305. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Hammen C. Depression and stressful environments: Identifying gaps in conceptualization and measurement. Anxiety Stress Coping. 2016;29:335–351. doi: 10.1080/10615806.2015.1134788. [DOI] [PubMed] [Google Scholar]
  • 15.Kendler K.S., Gardner C.O. Depressive vulnerability, stressful life events and episode onset of major depression: A longitudinal model. Psychol. Med. 2016;46:1865–1874. doi: 10.1017/S0033291716000349. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Shader R.I. COVID-19 and Depression. Clin. Ther. 2020;42:962–963. doi: 10.1016/j.clinthera.2020.04.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Goldmann E., Galea S. Mental health consequences of disasters. Annu. Rev. Public Health. 2014;35:169–183. doi: 10.1146/annurev-publhealth-032013-182435. [DOI] [PubMed] [Google Scholar]
  • 18.Norris F.H., Friedman M.J., Watson P.J., Byrne C.M., Diaz E., Kaniasty K. 60,000 disaster victims speak: Part I. An empirical review of the empirical literature, 1981—2001. Psychiatry. 2002;65:207–239. doi: 10.1521/psyc.65.3.207.20173. [DOI] [PubMed] [Google Scholar]
  • 19.Hammen C. Generation of stress in the course of unipolar depression. J. Abnorm. Soc. Psychol. 1991;100:555–561. doi: 10.1037/0021-843X.100.4.555. [DOI] [PubMed] [Google Scholar]
  • 20.Hammen C. Stress generation in depression: Reflections on origins, research, and future directions. J. Clin. Psychol. 2006;62:1065–1082. doi: 10.1002/jclp.20293. [DOI] [PubMed] [Google Scholar]
  • 21.Skałacka K., Pajestka G. Digital or In-Person: The Relationship Between Mode of Interpersonal Communication During the COVID-19 Pandemic and Mental Health in Older Adults From 27 Countries. J. Fam. Nurs. 2021;27:275–284. doi: 10.1177/10748407211031980. [DOI] [PubMed] [Google Scholar]
  • 22.Kwong A.S., Pearson R.M., Adams M.J., Northstone K., Tilling K., Smith D., Fawns-Ritchie C., Bould H., Ware N., Zammit S., et al. Mental health before and during the COVID-19 pandemic in two longitudinal UK population cohorts. Br. J. Psychiatry. 2021;218:334–343. doi: 10.1192/bjp.2020.242. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Ettman C.K., Abdalla S.M., Cohen G.H., Sampson L., Vivier P.M., Galea S. Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic. JAMA Netw. Open. 2020;3:e2019686. doi: 10.1001/jamanetworkopen.2020.19686. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Stanton R., To Q.G., Khalesi S., Williams S.L., Alley S.J., Thwaite T.L., Fenning A., Vandelanotte C. Depression, anxiety, and stress during COVID-19: Associations with changes in physical activity, sleep, tobacco, and alcohol use in Australian adults. Int. J. Environ. Res. Public Health. 2020;17:4065. doi: 10.3390/ijerph17114065. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Özdin S., Bayrak Özdin Ş. Levels and predictors of anxiety, depression and health anxiety during COVID-19 pandemic in Turkish society: The importance of gender. Int. J. Soc. Psychiatry. 2020;66:504–511. doi: 10.1177/0020764020927051. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Toledo A., Betancourt D., Romo H., Reyes E., González A. A cross-sectional survey of psychological distress in a Mexican sample during the second phase of the COVID-19 pandemic. OSF Prepr. 2020 doi: 10.31219/osf.io/wzqkh. [DOI] [Google Scholar]
  • 27.Taylor S. The Psychology of Pandemics: Preparing for the Next Global Outbreak of Infectious Disease. Cambridge Scholars Publishing; Newcastle upon Tyne, UK: 2019. [Google Scholar]
  • 28.Wheaton M.G., Abramowitz J.S., Berman N.C., Fabricant L.E., Olatunji B.O. Psychological predictors of anxiety in response to the H1N1 (swine flu) pandemic. Cognit. Ther. Res. 2012;36:210–218. doi: 10.1007/s10608-011-9353-3. [DOI] [Google Scholar]
  • 29.Van der Vegt I., Kleinberg B. In: Women Worry about Family, Men about the Economy: Gender Differences in Emotional Responses to COVID-19. Aref S., Bontcheva K., Braghieri M., Dignum F., Giannotti F., Grisolia F., Pedreschi D., editors. Volume 12467. Springer; Cham, Switzerland: 2020. Social Informatics. SocInfo 2020. Lecture Notes in Computer Science. [DOI] [Google Scholar]
  • 30.Ramos-Lira L., Rafull C., Flores-Celis K., Mora J., García-Andrade C., Rascón-Gasca M.L., Bautista A., Cervantes C. Emotional responses and coping strategies in adult Mexican population during the first lockdown of the COVID-19 pandemic: An exploratory study by sex. Salud Ment. 2020;43:243–251. doi: 10.17711/SM.0185-3325.2020.034. [DOI] [Google Scholar]
  • 31.Levenson R.W. Stress and illness: A role for specific emotions. Psychosom. Med. 2019;81:720–730. doi: 10.1097/PSY.0000000000000736. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Sewart A.R., Zbozinek T.D., Hammen C., Zinbarg R.E., Mineka S., Craske M.G. Positive affect as a buffer between chronic stress and symptom severity of emotional disorders. Clin. Psychol. Sci. 2019;7:914–927. doi: 10.1177/2167702619834576. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Martínez-Vélez N.A., Tiburcio M., Natera G., Villatoro Velázquez J.A., Arroyo-Belmonte M., Sánchez G.Y., Torres M. Psychoactive substance use and its relationship to stress, emotional state, depressive symptomatology, and perceived threat during the COVID-19 pandemic in Mexico. Front. Public Health. 2021;9:709410. doi: 10.3389/fpubh.2021.709410. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Arroyo-Belmonte M., Natera G., Tiburcio M., Martínez-Vélez N.A. Development and psychometric properties of the adversity and stress scale (ASS): Validation in the adult mexican population. Int. J. Ment. Health Addict. 2021:1–15. doi: 10.1007/s11469-021-00669-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Kroenke K., Spitzer R.L., Williams J.B. The patient health questionnaire-2: Validity of a two-item depression screener. Med. Care. 2003;41:1284–1292. doi: 10.1097/01.MLR.0000093487.78664.3C. [DOI] [PubMed] [Google Scholar]
  • 36.Arrieta J., Aguerrebere M., Raviola G., Flores H., Elliott P., Espinosa A., Reyes A., Ortiz-Panozo E., Rodriguez E.G., Mulkherjee J., et al. Validity and utility of the Patient Health Questionnaire (PHQ)-2 and PHQ-9 for screening and diagnosis of depression in rural Chiapas, Mexico: A cross-sectional study. J. Clin. Psychol. 2017;73:1076–1090. doi: 10.1002/jclp.22390. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Levis B., Sun Y., He C., Wu Y., Krishnan A., Mani P., Neupane D., Imran M., Brehaut E., Negeri Z., et al. Accuracy of the PHQ-2 Alone and in Combination With the PHQ-9 for Screening to Detect Major Depression: Systematic Review and Meta-analysis. JAMA. 2020;323:2290–2300. doi: 10.1001/jama.2020.6504. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Conway L., Woodard S., Zubrod A., Tiburcio M., Martínez-Vélez N.A., Sorgente A., Lanz M., Serido J., Vosylis R., Fonseca G., et al. How culturally unique are pandemic effects?: Evaluating cultural similarities and differences in effects of age, biological sex, and political beliefs on COVID Impacts. Front. Psychol. 2022;13:937211. doi: 10.3389/fpsyg.2022.937211. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Familiar I., Ortiz-Panozo E., Hall B., Vieitez I., Romieu I., Lopez-Ridaura R., Lajous M. Factor structure of the Spanish version of the Patient Health Questionnaire-9 in Mexican women. Int. J. Methods Psychiatr. Res. 2015;24:74–82. doi: 10.1002/mpr.1461. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Medina-Mora M.E., Borges G., Benjet C., Lara C., Berglund P. Psychiatric disorders in Mexico: Lifetime prevalence in a nationally representative sample. Br. J. Psychiatry. 2007;190:521–528. doi: 10.1192/bjp.bp.106.025841. [DOI] [PubMed] [Google Scholar]
  • 41.Cénat J.M., Felix N., Blais-Rochette C., Rousseau C., Bukaka J., Derivois D., Noorishad P.G., Birangui J.P. Prevalence of mental health problems in populations affected by Ebola virus disease: A systematic review and meta-analysis. Psychiatry Res. 2020;289:113033. doi: 10.1016/j.psychres.2020.113033. [DOI] [PubMed] [Google Scholar]
  • 42.Maunder R.G. Was SARS a mental health catastrophe? Gen. Hosp. Psychiatry. 2009;31:316–317. doi: 10.1016/j.genhosppsych.2009.04.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.González C., Ausín B., Castellanos M.Á., Saiz J., López A., Ugidos C., Muñoz M. Mental health consequences during the initial stage of the 2020 Coronavirus pandemic (COVID-19) in Spain. Brain Behav. Immun. 2020;87:172–176. doi: 10.1016/j.bbi.2020.05.040. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Kishore J., Anand T., Heena Nazli T. Depression during COVID-19 Pandemic in India: Findings from an Online Survey. Int. J. Prev. Curative Community Med. 2020;6:16–21. doi: 10.24321/2454.325X.202008. [DOI] [Google Scholar]
  • 45.Kola L., Kohrt B.A., Hanlon C., Naslund J.A., Sikander S., Balaji M., Benjet C., Lai E.Y., Eaton J., Gonsalves P., et al. COVID-19 mental health impact and responses in low-income and middle-income countries: Reimagining global mental health. Lancet Psychiatry. 2021;8:535–550. doi: 10.1016/S2215-0366(21)00025-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Bracke P., Delaruelle K., Dereuddre R., Van de Velde S. Depression in women and men, cumulative disadvantage, and gender inequality in 29 European countries. Soc. Sci. Med. 2020;267:113354. doi: 10.1016/j.socscimed.2020.113354. [DOI] [PubMed] [Google Scholar]
  • 47.Alloy L.B., Liu R.T., Bender R.E. Stress generation research in depression: A commentary. Int. J. Cogn. Ther. 2010;3:380–388. doi: 10.1521/ijct.2010.3.4.380. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Vigo D., Patten S., Pajer K., Krausz M., Taylor S., Rush B., Raviota G., Saxena S., Thornicroft G., Yatham L.N. Mental health of communities during the COVID-19 pandemic. Can. J. Psychiatry. 2020;65:681–987. doi: 10.1177/0706743720926676. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Rutland-Lawes J., Wallinheimo A.S., Evans S.L. Risk factors for depression during the COVID-19 pandemic: A longitudinal study in middle-aged and older adults. BJPsych Open. 2021;7:e161. doi: 10.1192/bjo.2021.997. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Not available.


Articles from International Journal of Environmental Research and Public Health are provided here courtesy of Multidisciplinary Digital Publishing Institute (MDPI)

RESOURCES