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Background:
Systematic Review

Prevalence of Anxiety, Depression, and Stress among Teachers during the COVID-19 Pandemic: A Rapid Systematic Review with Meta-Analysis

1
Department of Developmental and Educational Psychology, University of the Basque Country UPV/EHU, 48940 Leioa, Spain
2
Psychiatry Service, Hospital Universitario Miguel Servet, 50009 Zaragoza, Spain
3
Pharmacy Service, Hospital Universitario Miguel Servet, 50009 Zaragoza, Spain
4
Department of Microbiology, Pediatrics, Radiology and Public Health, University of Zaragoza, 50009 Zaragoza, Spain
5
Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, 28029 Madrid, Spain
6
Aragonese Institute of Health Sciences (IIS Aragón), 50009 Zaragoza, Spain
*
Author to whom correspondence should be addressed.
Brain Sci. 2021, 11(9), 1172; https://doi.org/10.3390/brainsci11091172
Submission received: 2 August 2021 / Revised: 29 August 2021 / Accepted: 30 August 2021 / Published: 3 September 2021
(This article belongs to the Section Neuropsychology)

Abstract

:
Background: Since the beginning of the COVID-19 pandemic, teachers have been accumulating adverse psychological symptoms due to the closure of educational centers and the need to adapt to different teaching modalities. Methods: Medline and PubMed were searched for studies on the prevalence of depression, anxiety, stress, and burn-out in teachers, published from 1 December 2019 to 15 June 2021. Results: In total, eight studies were included in this study. The results show that teachers report levels of anxiety (17%), depression (19%), and stress (30%). In Asia, there has been more anxiety compared to other continents. Overall, anxiety has been higher among teachers in schools compared to universities. However, stress levels have been higher among teachers in universities compared to schools. Statistically, there were no significant differences regarding gender and age in any of the symptoms. Conclusions: The results suggest that teachers at different educational levels are experiencing adverse psychological symptomatology during the COVID-19 pandemic, and that anxiety levels vary between different countries. However, more international studies are needed to fully understand the impact of the pandemic on teachers’ mental health.

1. Introduction

In recent years, teachers have been showing more adverse psychological symptoms and higher sick-leave rates associated with these [1]. The pressure linked to work [2], together with the loss of status [3,4], has meant that stress [5,6], anxiety [7], depression [8], and burnout [9] have become common among teachers in different countries.
It should also be noted that the COVID-19 pandemic has led to significant health, social, psychological, economic, and educational changes around the world [10,11]. Among these changes, the closure of schools and universities has been one of the most widely implemented measure since the beginning of the pandemic to help maintain social distancing and slow down the spread of the virus [12,13]. According to UNESCO (United Nations Educational, Scientific and Cultural Organization), the duration of school closures has varied across countries and regions [14].
Moreover, since the closure of schools, research has shown that teachers have accumulated psychological symptoms, such as stress, anxiety, and depression, worldwide [15,16,17]. In fact, UNESCO [18] has already identified confusion and stress among teachers as one of the adverse consequences of social distancing measures.
This symptomatology is related to different causes. To begin with, it is related to the rapid change from face-to-face to virtual teaching, also known as emergency e-learning. In fact, many experts have pointed out that pandemic e-learning differs greatly from the deliberate and well-designed online teaching and that it has been perceived as an abrupt and unplanned change in learning contexts that has not been chosen by either learners or teachers [19]. Furthermore, in this context, the organization and didactic planning to transfer teaching contents into an online environment while maintaining their relevance has been a great challenge for teachers of all academic levels [20,21].
Likewise, the emergency e-learning has also provoked changes in teachers’ workload [22], at least in six motivational characteristics of the academic teachers’ job (task identity, task significance, skill variety, feedback, autonomy, and social dimensions of the work). All of these changes have impacted teachers’ motivation towards their own work [23]. Consequently, some of the research conducted focusing on teachers during the period of school closures and lockdown suggests that this crisis has caused symptoms such as anxiety or depression in teachers, in addition to increased rates of divorce and domestic violence, all of which may limit their ability to teach adequately [24].
Furthermore, teachers, especially in early childhood and primary education, are a highly feminized group. Consequently, there is a high number of female teachers who, during the lockdown period, had to take on the burden of caring responsibilities (children, elderly people, etc.) at home and combine these with their profession [5]. This is why female teachers may have had more stress, anxiety, and depression than men in the context of the pandemic [25,26].
However, the opening of schools and the return to classes did not make the psychological symptomatology among teachers disappear [27,28]. Indeed, the reopening of schools itself, amidst great uncertainty and controversy in many countries over the pandemic’s development, was a stressful time for many teachers [17,29,30].
In addition, when classes were reactivated, teachers had to prevent the spread of the virus and deal with selective lockdown and restrictive measures while performing their teaching activities [31]. In fact, the measures imposed to prevent contagion in schools have also had a direct impact on the way that teaching has been carried out, with many classes taking the bimodal or hybrid format (half of the students at home and half in class) [32,33], mirror classrooms [34], small bubble groups [35], or even going online for the whole or part of the 2020/2021 school year [36]. It should also be remembered that the protocols of the educational centers varied significantly between countries or even regions within the same country [14].
In terms of age, since the beginning of the pandemic, it has been observed that, among the general population, it is the younger people who suffered more psychological symptoms, such as anxiety, depression, specific phobias, cognitive change, avoidance, and compulsive behavior [37]. However, some studies with a focus on teachers have shown more psychological symptomatology in older people [17], and this may be due to the digital gap [38].
In regard to the teaching professional sector, in the current pandemic, teachers feel a greater responsibility for younger children, as they need more care and protection. This may lead teachers to feel under pressure to provide adequate care for children, in addition to addressing the concerns of their families [39]. Secondary-school and university teachers, however, may have felt less pressure in this respect, as their students are more autonomous and do not require such care from teachers [40].
Regarding the COVID-19 impact in different countries, the pandemic has impacted education in all countries. However, as UNESCO [14] points out, there have been differences in the conditions and measures implemented in education in different countries. When the pandemic began and schools were closed, only half of the countries with closed schools had alternatives to continue delivering teaching and learning [41]. According to UNESCO [42], the majority of countries that made education alternatives available were from Eastern Europe and Central Asia, followed by Asia and the Pacific, and finally Western Europe and North America. Therefore, inequalities in education in different countries [43] may also bring different psychological symptomatology among teachers.
It is therefore obvious that the pandemic has affected the psychological state of teachers; however, to our knowledge, there has been no systematic review and meta-analysis that has analyzed it. Therefore, the current meta-analysis aims to update the existing evidence on the prevalence of stress, anxiety, and depression among teachers during the COVID-19 pandemic. More specifically, it is intended to analyze whether gender, age range, country, and the academic sector affect the symptomatology of these professionals.

2. Materials and Methods

This study was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for reporting systematic reviews and meta-analysis [44] (Supplementary Materials Table S1).

2.1. Search Strategy

Two researchers (JBN and MPM) searched for all cross-sectional studies reporting the prevalence of depression, anxiety, stress, and burnout published from 1 December 2019 through 15 June 2021, using MEDLINE via PubMed. The search proceeded as follows:
“(“School Teachers”[Mesh] OR “Faculty”[Mesh] OR teacher*[tiab] OR professor*[tiab] OR lecturer*[tiab] OR instructor*[tiab]) AND (Depression[Mesh] OR Depressive Disorder[Mesh] OR depress*[tiab] OR Anxiety[Mesh] OR Anxiety Disorders[Mesh] OR anxi*[tiab] OR Trauma and Stressor Related Disorders[Mesh] OR “Stress, Psychological”[Mesh] OR stress*[tiab] OR Burnout, Psychological[Mesh] OR burnout[tiab])”.
No language restriction was made. References from selected articles were inspected to detect additional potential studies. Then we performed a manual search of the “grey literature” (e.g., medRxiv or Google Scholar) to detect other potentially eligible investigations. Any disagreement was resolved by consensus among third and fourth reviewers (NO-E and NI).

2.2. Selection Criteria

Studies were included if (1) reported cross-sectional data on the prevalence of depression, anxiety, stress, or burnout, or sufficient information to compute this, conducted during the COVID-19 outbreak; (2) focused on teachers; (3) included a validated instrument to assess the above outcomes; and (4) the full text was available.
We excluded studies focusing only on community-based samples of general population or specific samples that were not teachers (e.g., students, medical professionals, and patients), as well as review articles.
A predesigned data-extraction form was used to extract the following information: country, sample size, proportion of women, average age, response rate, and sampling methods, and also the instruments used to assess outcomes and their prevalent rates.

2.3. Methodological Quality Assessment

Articles selected for retrieval were assessed by two independent reviewers (JBN and JS) for methodological validity before they were included in the review using the Joanna Briggs Institute (JBI) standardized critical appraisal instrument for prevalence studies [45]. Quality was evaluated according to nine criteria, with each yielding a score of zero or one. One score was obtained for each criterion if the study was affirmative in the next questions: (1) Was the sample frame appropriate to address the target population? (2) Were study participants recruited in an appropriate way? (3) Was the sample size adequate? (4) Were the study subjects and setting described in detail? (5) Was data analysis conducted with sufficient coverage of the identified sample? (6) Were valid methods used for the identification of the condition? (7) Was the condition measured in a standard, reliable way for all participants? (8) Was there appropriate an statistical analysis? (9) Was the response rate adequate, and if not, was the low response rate managed appropriately?
Any disagreements that arose between the reviewers were resolved through discussions, or by further discussion with a third and fourth reviewers (NO-E and NI).

2.4. Data Extraction and Statistical Analysis

Freeman and Tukey’s double arcsine transformation of prevalence to stabilize the variance was applied [46]. A generic inverse variance method with a random effect model was used [47], which is more appropriate than fixed-effect models when the number of studies included in the meta-analysis is low (<10) [48]. The Hedges Q statistic was reported to check heterogeneity across studies, with statistical significance set at p < 0.10. The I2 statistic and 95% confidence interval (95% CI) were also used to quantify heterogeneity [49]. Values between 25% and 50% are considered low, between 50% and 75% are moderate, and 75% or more are high [50]. Heterogeneity of effects between studies occurs when differences in results for the same exposure-disease association cannot be fully explained by sampling variation. Sources of heterogeneity can include differences in study design or in demographic characteristics. We performed subgroup analyses to explore the sources of heterogeneity expected in meta-analyses of observational studies [51]. Meta-regression was not performed, due to lack of statistical power with less than 10 studies included in a meta-analysis [52]. We conducted a sensitivity analysis to determine the influence of each individual study on the overall result by omitting studies one by one. Publication bias was determined through visual inspection of a funnel plot and also Egger’s test [53] (p-values < 0.05 indicate publication bias), since funnel plots were found to be an inaccurate method for assessing publication bias in meta-analyses of proportion studies [54].
Statistical analyses were conducted by using JS and run with STATA statistical software (version 10.0; College Station, TX, USA) and R [55].

3. Results

Figure 1 shows the flowchart of the search strategy and study selection process. A total of 410 records were initially identified from Medline via PubMed, and 346 were excluded after a first screening of the titles and abstracts. Three extra records were then added after a manual search in a preprints database (MedRxiv). After reading the remaining 67 articles in full, we finally included eight in our meta-analysis [15,16,17,31,56,57,58,59]. Exclusion reasons are detailed in Figure 1.
Table 1 and Table 2 show the characteristics of the nine studies included in our meta-analysis. Table 1 gives a descriptive overview of the global characteristics, while Table 2 breaks down the methods of measurement of the primary outcomes and the prevalence found in each study. Six studies measured anxiety, five measured stress, and three measured depression levels. For this, all studies used standardized and validated scales, with the most widely used scale being the Depression, Anxiety, and Stress Scale (DASS, n = 3 studies). No articles were found that provided data on professional burnout in teachers during the Covid-19 pandemic.
The sample size ranged from 100 to 88,611 participants, and the mean age ranged from 31.4 to 43.9 years in the five reporting studies. All studies included both men and women, and the percentage of women ranged from 32% to 80%. All studies were conducted by using online questionnaires, and, of those reporting sampling methodology, all used non-randomized methods. Five studies reported the response rate, which ranged from 11% to 99%.
The risk of bias scores ranged from five to eight out of a possible total of nine, with a mean score of 6.6 (SD = 1.2) (Table 3). The main limitation (a), present in all studies, was that the recruitment of participants was inadequate, as all used non-randomized techniques or did not report the method in this regard. The other most common limitations were (b) response rate not reported, or large number of non-responders (six studies), and (c) sample size too small to ensure good precision of the final estimate (three studies).

3.1. Prevalence of Anxiety

The estimated overall prevalence of anxiety was 17% in teachers (95% CI: 9–28%), with significant heterogeneity between studies (Q test: p < 0.001; I2 = 99%) (Figure 2). Lower prevalence of anxiety was found for studies located in Asia (14% [95% CI: 11–16%]) compared to those located in other continents (22% [95% CI: 5–46%]); however, this difference did not reach statistical significance. In particular, studies conducted in China (14% [95% CI: 13–14%]) showed a lower prevalence of anxiety compared with studies conducted in other countries (19% [95% CI: 5–38%]). We also observed higher prevalence of anxiety for studies using the DASS-21 (22% [95% CI: 5–46%]) compared to those using the HAM-A/GAD-7/SAS (14% [95% CI: 11–16%]), and those focused in school teachers (16% [95% CI: 10–22%]) compared with studies focused in University teachers (10% [95% CI: 8–12%]); however, this difference did not reach statistical significance. No subgroup analysis according to sampling method was performed due to insufficient data available. Excluding each study one by one from the analysis did not substantially change the pooled prevalence of anxiety, which varied between 13% (95% CI: 10–17%), with Ozamiz-Etxebarria et al. excluded, and 18% (95% CI: 6–34%), with Li et al. excluded. This indicates that no single study had a disproportional impact on the overall prevalence. Visual inspection of the funnel plot (Figure 3) suggested no publication bias presence for the estimate of prevalence of anxiety in teachers, confirmed by non-significant results from the Egger’s test (p = 0.856).

3.2. Prevalence of Depression

Only tree studies reported prevalence of depression data. The estimated overall prevalence of depression was 19% in teachers (95% CI: 15–24%), with significant heterogeneity between studies (Q test: p < 0.001; I2 = 83.7%) (Figure 2). No subgroups analyses were performed due to insufficient number of studies available. Visual inspection of the funnel plot (Figure 3) suggested no publication bias presence for the estimate of prevalence of anxiety in teachers, confirmed by non-significant results from the Egger’s test (p = 0.263).

3.3. Prevalence of Stress

The estimated overall prevalence of stress was 30% in teachers (95% CI: 17–46%), with significant heterogeneity between studies (Q test: p < 0.001; I2 = 99.1%) (Figure 2). A statistically significant higher prevalence of anxiety for studies using the DASS-21 (19% [95% CI: 6–38%]) was observed compared to those using the K10 or IES (48% [95% CI: 46–50%]). We also observed lower prevalence of stress in school teachers (13% [95% CI: 7–22%]) compared with studies focused in University teachers (35% [95% CI: 12–66%]); however, this difference did not reach statistical significance. Studies using the snowball sampling method report a lower prevalence of stress (37% [95% CI: 35–39%]) compared to those with convenience sampling method (47% [95% CI: 45–50%]), with this difference being statistically significant. No subgroup analysis according to geographical location was performed due to insufficient data available. Excluding each study one by one from the analysis did not substantially change the pooled prevalence of anxiety, which varied between 26% (95% CI: 11–44%), with Ammar et al. excluded, and 36% (95% CI: 27–47%), with Evanoff et al. excluded. This indicates that no single study had a disproportional impact on the overall prevalence.
Our visual inspection of the funnel plot (Figure 3) suggested no publication bias presence for the estimate of prevalence of anxiety in teachers, confirmed by non-significant results from the Egger’s test (p = 0.648).

4. Discussion

4.1. Summary of Main Findings

The COVID-19 pandemic is having an unprecedented impact on teachers, with stress, anxiety, and depression being the most reported mental symptomatology. The present study provides an updated meta-analysis of studies reporting on the prevalence of stress, anxiety, and depression among teachers during the COVID-19 pandemic. Our meta-analysis is based on eight studies, and, to the best of our knowledge, this is the first review to report on overall prevalence rates of stress, anxiety, and depression across different ages, gender, countries, and educational sectors in teachers. Our findings show that teachers report levels of anxiety (17%), depression (19%), and stress (30%) with significant heterogeneity among the reviewed studies. These results were somewhat higher (especially referring to stress) than those recently found (in 2021) in a meta-analysis conducted in the general population during the pandemic where the prevalence of anxiety was 15.5%, the prevalence of depression was 15.97%, and the prevalence of stress was 13.29% [60]. Some of the research carried out on this subject has highlighted that this symptomatology may be due to emergency e-learning, teachers’ overload [22] and the uncertainty about the reopening of schools in the midst of the pandemic [28].
In terms of gender, there were no significant differences between male and female in neither stress or anxiety, and studies measuring depression did not differ on this variable. This finding is opposed to the initial expectations, as studies among the general population suggest that females are suffering more psychological symptoms during this pandemic [61]. Moreover, it was also expected that female teachers would have more symptoms than men in the context of the pandemic [25,26] due to the burden of caring responsibilities at home combined with their profession [5]. This may be due to the fact that teaching staff in general is composed of females, and therefore there may not have been significant results in terms of gender because of the feminization of the profession [62].
There were also no age differences among the symptomatology, despite the fact that older teachers were expected to have more symptomatology due to difficulties in adapting to the new emergency e-learning system [38].
Regarding country differences, a lower prevalence of anxiety was found in the studies located in Asia, in particular, the studies conducted in China. In a cross-country research performed to find differences in anxiety and behavioral response to the COVID-19 pandemic, it was found that anxiety was less common among patient societies, such as Asian societies [63]. In addition, teachers in Asia were already more familiar with e-learning and may have had more technological resources compared to other countries [64] and therefore may not have reported as much anxiety compared to other countries where technological resources might have been limited [42].
Finally, the most surprising finding is that higher anxiety levels were found at elementary levels of education, as expected, but more teachers with stress were found among university teachers. It may be that there was more anxiety among school teachers as this symptom is an emotional reaction of alertness to a threat [65]. Therefore, the threat of the pandemic was a one-off event among school teachers, as many of them had to work with groups of children without masks or have direct contact with them. However, stress is a broader process of adaptation to the environment, and it is well-known that university teachers have been accumulating stress long before the pandemic [66]. University teachers are responsible for the important task of training students in a variety of advanced specialized skills and promoting the development of science and technology and social progress, which are fundamental to any country’s prosperity [67]. However, all of these tasks may create stress symptomatology, in particular, at a time of uncertainty and high workload, such as during this pandemic [68]. In addition, university teachers must constantly interact with students, maintain a high level of professional performance, and meet targets and deadlines, even in times of pandemic. Thus, these are all factors that may increase stress among this group [69]. In addition, some “old diseases” that continue to exist among people not affected by COVID-19 should not be forgotten [70,71]. Pathologies such as neurosurgical, neurological, and psychiatric, among others, of the population have been blocked due to the COVID-19 pandemic, and this may have increased the emotional burden among people suffering from these diseases [71].
Therefore, considering the findings of the present work, it is necessary to reduce the psychological impact and to improve and avoid these situations of stress, anxiety, and depression during the pandemic among teachers. Having psychologically healthy teachers will be useful to avoid job losses due to emotional distress and will improve the quality of education for students. Therefore, it would be important that they receive support in the form of additional teachers and resources. It would also be important for them to receive emotional support by introducing workshops to strengthen the emotional resources of teachers in schools. In this way, the emotional environment in schools could be improved and the mental health of teachers could be protected. This improvement would have an impact on the mental health of pupils and their academic performance.

4.2. Strengths and Limitations

The greatest strength of the present study is that, to our knowledge, no meta-analysis has been carried out that focuses on teachers’ symptomatology in the face of the pandemic. This is why this study may provide the basis for further studies along this research line. Moreover, a rigorous approach to identify publication bias has been implemented (i.e., Egger’s test) which has demonstrated that there is no bias in the estimation of the pooled prevalence of anxiety, stress, and depression for teachers.
However, some limitations should be considered when interpreting our results, due to the biases presented in the grouped estimation of the results. One of the major limitations of the study is the quality of the available literature. Since the systematic review requires previous existing scientific publications, when evaluating any condition during the pandemic using this methodology, there will be a scarce availability of information and a high risk of including literature of moderate-to-low methodological quality. In the same vein, there have not yet been many studies on teachers’ symptomatology conducted in the face of the pandemic. In particular, no study was found that measured burnout, although this symptomatology was widely found in teaching before the pandemic [9].
Furthermore, the majority of the research reviewed was based on cross-sectional data and non-probabilistic samples and used a variety of self-report scales. Indeed, the studies that use DASS are non-Asian studies, and this is why the results are repeated. Therefore, as the epidemiological status of COVID-19 is constantly changing worldwide, longitudinal studies would be necessary to determine whether the elevated levels of anxiety, stress, and depression are sustained, reduced, or increased over time [72].

5. Conclusions

This meta-analysis shows that the proportion of teachers suffering from anxiety, stress, or depression during the COVID-19 pandemic is considerable. Therefore, there is an urgent need to prevent and treat common mental health issues among this population cohort. Specifically, the data show that the difference in measures implemented to deal with the impacts of the pandemic in education between countries is worrying, and that it is necessary to support those countries that may be facing greater challenges. In fact, there is already a large gap between countries in terms of progress in dealing with the pandemic [73,74], and it is important to address these inequalities, as these may be impacting essential social pillars, such as education.
It is also important to pay attention to the different symptomatology that teachers may be experiencing at different educational levels and provide the necessary resources to deal with these symptoms. Improving the emotional state of teachers would have a direct impact on their students, as it directly influences the quality of education and the emotional state of students [75].

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/brainsci11091172/s1. Table S1: PRISMA Checklist.

Author Contributions

Conceptualization, J.S., N.I.M. and N.O.-E.; methodology, J.S.; formal analysis, investigation, and data curation, J.B.-N. and M.P.-M.; writing—original draft preparation and writing—review and editing, J.S., N.I.M. and N.O.-E. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by KideOn Research Group of the Basque Government, Reference IT1342-19 (A category); and R + d + i Projects Research Challenges of the Ministry of Economy, Science and Innovation, grant number PID2020-119011RB-100 EDU.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Moreno, L.; Martín, J.; Rubio, S.; Díaz, E. Factores psicosociales en el entorno laboral, estrés y enfermedad. Edupsykhé. Rev. Psicol. Educ. 2004, 3, 95–108. [Google Scholar]
  2. Ferguson, K.; Frost, L.; Hall, D. Predicting teacher anxiety, depression, and job satisfaction. J. Teach. Learn. 2012, 8, 8. [Google Scholar] [CrossRef] [Green Version]
  3. González-Torres, M.C. Claves para Favorecer la Motivación de los Profesores Ante los Retos Educativos Actuales; Servicio de Publicaciones de la Universidad de Navarra: Pamplona, Spain, 2003. [Google Scholar]
  4. Bellei, C.; Valenzuela, J. El estatus de la profesión docente en Chile. Percepción de los profesores acerca del estatus profesional de la docencia. In ¿Héroes o Villanos? La Profesión Docente en Chile; Editorial Universitaria: Santiago, Chile, 2013; pp. 1–32. [Google Scholar]
  5. Ramos, G. Women at the Core of the Fight against COVID-19 Crisis. OECD. 2020. Available online: https://www.oecd.org/coronavirus/policy-responses/women-at-the-core-of-the-fight-against-covid-19-crisis-553a8269/ (accessed on 10 June 2021).
  6. Von der Embse, N.; Ryan, S.V.; Gibbs, T.; Mankin, A. Teacher stress interventions: A systematic review. Psychol. Sch. 2019, 56, 1328–1343. [Google Scholar]
  7. Pérez, V.M. Estrés y ansiedad en los docentes. Pulso Rev. Educ. 2003, 26, 9–22. [Google Scholar]
  8. Granados, L.; Aparicio Flores, P.; Fernández-Sogorb, A.; García-Fernández, J.M. Depresión, Ansiedad y Estrés y su Relación con el Burnout en Profesorado no Universitario. 2020. Available online: https://www.revistaespacios.com/a20v41n30/a20v41n30p11.pdf (accessed on 15 June 2021).
  9. García-Carmona, M.; Marín, M.D.; Aguayo, R. Burnout syndrome in secondary school teachers: A systematic review and meta-analysis. Soc. Psychol. Educ. 2019, 22, 189–208. [Google Scholar] [CrossRef]
  10. Minkos, M.L.; Gelbar, N.W. Considerations for educators in supporting student learning in the midst of COVID-19. Psychol. Sch. 2021, 58, 416–426. [Google Scholar] [CrossRef] [PubMed]
  11. Di Carlo, D.T.; Montemurro, N.; Petrella, G.; Siciliano, G.; Ceravolo, R.; Perrini, P. Exploring the clinical association between neurological symptoms and COVID-19 pandemic outbreak: A systematic review of current literature. J. Neurol. 2021, 268, 1561–1569. [Google Scholar] [CrossRef]
  12. Van Lancker, W.; Parolin, Z. COVID-19, school closures, and child poverty: A social crisis in the making. Lancet Public Health 2020, 5, e243–e244. [Google Scholar] [CrossRef]
  13. Viner, R.M.; Russell, S.J.; Croker, H.; Packer, J.; Ward, J.; Stansfield, C.; Mytton, O.; Bonell, C.; Booy, R. School closure and management practices during coronavirus outbreaks including COVID-19: A rapid systematic review. Lancet Child Adolesc. Health 2020, 4, 397–404. [Google Scholar] [CrossRef]
  14. UNESCO. Figures Show Two Thirds of an Academic Year Lost on Average Worldwide Due to Covid-19 School Closures. 2021. Available online: https://en.unesco.org/news/unesco-figures-show-two-thirds-academic-year-lost-average-worldwide-due-covid-19-school (accessed on 15 June 2021).
  15. Cruz, R.M.; Da Rocha, R.E.R.; Andreoni, S.; Pesca, A.D. Retorno ao trabalho? Indicadores de saúde mental em professores durante a pandemia da COVID-19. Rev. Polyphonía 2020, 31, 325–344. [Google Scholar] [CrossRef]
  16. Evanoff, B.A.; Strickland, J.R.; Dale, A.M.; Hayibor, L.; Page, E.; Duncan, J.G.; Kannampallil, T.; Gray, D.L. Work-Related and Personal Factors Associated With Mental Well-Being During the COVID-19 Response: Survey of Health Care and Other Workers. J. Med. Internet Res. 2020, 22, e21366. [Google Scholar] [CrossRef]
  17. Ozamiz-Etxebarria, N.; Dosil Santamaría, M.; Idoiaga Mondragon, N.; Berasategi Santxo, N. Estado emocional del profesorado de colegios y universidades en el norte de España ante la COVID-19. Rev. Española Salud Pública 2021, 95, e1–e8. [Google Scholar]
  18. UNESCO. Adverse Effects of School Closures. 2020. Available online: https://en.unesco.org/covid19/educationresponse/consequences (accessed on 15 June 2021).
  19. Moser, K.M.; Wei, T.; Brenner, D. Remote teaching during COVID-19: Implications from a national survey of language educators. System 2021, 97, 102431. [Google Scholar] [CrossRef]
  20. Khalili, H. Online interprofessional education during and post the COVID-19 pandemic: A commentary. J. Interprofessiona Care 2020, 34, 687–690. [Google Scholar] [CrossRef] [PubMed]
  21. Popa, D.; Repanovici, A.; Lupu, D.; Norel, M.; Coman, C. Using mixed methods to understand teaching and learning in Covid 19 times. Sustainability 2020, 12, 8726. [Google Scholar] [CrossRef]
  22. Palau, R.; Fuentes, M.; Mogas, J.; Cebrián, G. Analysis of the implementation of teaching and learning processes at Catalan schools during the Covid-19 lockdown. Technol. Pedagog. Educ. 2021, 30, 183–199. [Google Scholar] [CrossRef]
  23. Kulikowski, K.; Przytuła, S.; Sułkowski, Ł. E-learning? Never again! On the unintended consequences of COVID-19 forced e-learning on academic teacher motivational job characteristics. High. Educ. Q. 2021. [Google Scholar] [CrossRef]
  24. Al Lily, A.E.; Ismail, A.F.; Abunasser, F.M.; Alhajhoj Alqahtani, R.H. Distance education as a response to pandemics: Coronavirus and Arab culture. Technol. Soc. 2020, 63, 101317. [Google Scholar] [CrossRef]
  25. Stachteas, P.; Stachteas, C. The psychological impact of the COVID-19 pandemic on secondary school teachers. Psychiatriki 2020, 31, 293–301. [Google Scholar] [CrossRef]
  26. Li, Q.; Miao, Y.; Zeng, X.; Tarimo, C.S.; Wu, C.; Wu, J. Prevalence and factors for anxiety during the coronavirus disease 2019 (COVID-19) epidemic among the teachers in China. J. Affect. Disord. 2020, 277, 153–158. [Google Scholar] [CrossRef]
  27. Wakui, N.; Abe, S.; Shirozu, S.; Yamamoto, Y.; Yamamura, M.; Abe, Y.; Murata, S.; Ozawa, M.; Igarashi, T.; Yanagiya, T.; et al. Causes of anxiety among teachers giving face-to-face lessons after the reopening of schools during the COVID-19 pandemic: A cross-sectional study. BMC Public Health 2021, 21, 1–10. [Google Scholar] [CrossRef]
  28. Besser, A.; Lotem, S.; Zeigler-Hill, V. Psychological Stress and Vocal Symptoms Among University Professors in Israel: Implications of the Shift to Online Synchronous Teaching During the COVID-19 Pandemic. J. Voice 2020. [Google Scholar] [CrossRef]
  29. Beteille, T.; Ding, E.; Molina, E.; Pushparatnam, A.; Wilichowski, T. Three Principles to Support Teacher Effectiveness during COVID-19; World Bank Group: Washington, DC, USA, 2020. [Google Scholar]
  30. Kim, L.E.; Leary, R.; Asbury, K. Teachers’ narratives during COVID-19 partial school reopenings: An exploratory study. Educ. Res. 2021, 63, 244–260. [Google Scholar] [CrossRef]
  31. Li, D.; Lin, E.Z.; Brault, M.A.; Paquette, J.; Vermund, S.H.; Pollitt, K.J.G. Reopening Schools After a Novel Coronavirus Surge. Adv. Exp. Med. Biol. 2021, 1318, 785–813. [Google Scholar] [PubMed]
  32. Chavarría-Bolaños, D.; Gómez-Fernández, A.; Dittel-Jiménez, C.; Montero-Aguilar, M. E-Learning in Dental Schools in the Times of COVID-19: A Review and Analysis of an Educational Resource in Times of the COVID-19 Pandemic. Odovtos Int. J. Dental Sci. 2020, 22, 69–86. [Google Scholar]
  33. Schwarz, M.; Scherrer, A.; Hohmann, C.; Heiberg, J.; Brugger, A.; Nuñez-Jimenez, A. COVID-19 and the academy: It is time for going digital. Energy Res. Soc. Sci. 2020, 68, 101684. [Google Scholar] [CrossRef] [PubMed]
  34. Malkus, N.; Christensen, C.; Schurz, J. School District Responses to the COVID-19 Pandemic: Round 6, Ending the Year of School Closures; American Enterprise Institute: Washington, DC, USA, 2020. [Google Scholar]
  35. Ziauddeen, N.; Woods-Townsend, K.; Saxena, S.; Gilbert, R.; Alwan, N.A. Schools and COVID-19: Reopening Pandora’s box? Public Health Pract. 2020, 1, 100039. [Google Scholar] [CrossRef] [PubMed]
  36. Vera, J.D.; Hojas, D.P.; Ramirez, A.K.R.; Mora, D.M. Percepción del aprendizaje en el contexto de las clases en línea de la Universidad de Guayaquil frente a la COVID-19. Rev. Científica Sinapsis 2020, 3, 3. [Google Scholar] [CrossRef]
  37. 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. Psychiatr. 2020, 33, e100213. [Google Scholar] [CrossRef] [Green Version]
  38. Song, Y.; Chen, Y. Information and communication technology among early and late middle-aged adults in urban China: Daily use and anticipated support in old age. Australas. J. Ageing 2019, 38, e85–e92. [Google Scholar] [CrossRef]
  39. Hong, X.; Liu, Q.; Zhang, M. Dual Stressors and Female Pre-school Teachers’ Job Satisfaction During the COVID-19: The Mediation of Work-Family Conflict. Front. Psychol. 2021, 12, 691498. [Google Scholar] [CrossRef]
  40. Tous, C.M.; Amorós, M.M. Motivaciones para el estudio en universitarios. An. Psicol. Ann. Psychol. 2007, 23, 17–24. [Google Scholar]
  41. Artopoulos, A. COVID-19:¿ Qué hicieron los países para continuar con la educación a distancia? Rev. Latinoam. Educ. Comp. 2020, 11, 1–11. [Google Scholar]
  42. COVID-19 Impact on Education. 2020. Available online: https://www.researchgate.net/profile/Chandasiri-Olaganwatte/publication/341960453_International_Journal_of_Advanced_Education_and_Research_The_COVID-19_impact_on_education/links/5edba6ff92851c9c5e880b5d/International-Journal-of-Advanced-Education-and-Research-The-COVID-19-impact-on-education.pdf (accessed on 16 June 2021).
  43. Cáceres-Muñoz, J.; Jiménez Hernández, A.S.; Martín-Sánchez, M. Cierre de escuelas y desigualdad socioeducativa en tiempos del Covid-19. una investigación exploratoria en clave internacional. Rev. Int. de Educ. para la Justicia Soc. 2020, 9, 199–221. [Google Scholar] [CrossRef]
  44. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G.; Prisma Group. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med. 2009, 6, e1000097. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Moola, S.; Munn, Z.; Tufanaru, C.; Aromataris, E.; Sears, K.; Sfetc, R.; Currie, M.J.; Lisy, K.; Qureshi, R.; Mattis, P.; et al. Chapter 7: Systematic reviews of etiology and risk. In Joanna Briggs Institute Reviewer’s Manual; Aromataris, E., Munn, Z., Eds.; The Joanna Briggs Institute: Adelaide, Australia, 2017; pp. 219–226. [Google Scholar]
  46. Freeman, M.F.; Tukey, J.W. Transformations related to the angular and the square root. Ann. Math. Stat. 1950, 21, 607–611. [Google Scholar] [CrossRef]
  47. DerSimonian, R.; Laird, N. Meta-analysis in clinical trials. Control Clin. Trials. 1986, 7, 177–188. [Google Scholar] [CrossRef]
  48. Singh, A.; Hussain, S.; Najmi, A.K. Number of studies, heterogeneity, generalisability, and the choice of method for meta-analysis. J. Neurol. Sci. 2017, 381, 347. [Google Scholar] [CrossRef] [PubMed]
  49. von Hippel, P.T. The heterogeneity statistic I 2 can be biased in small meta-analyses. BMC Med. Res. Methodol. 2015, 15, 1–8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  50. Higgins, J.P.; Thompson, S.G.; Deeks, J.J.; Altman, D.G. Measuring inconsistency in meta-analyses. BMJ 2003, 327, 557–560. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  51. Egger, M.; Schneider, M.; Davey Smith, G. Spurious precision? Meta-analysis of observational studies. BMJ 1998, 316, 140–144. [Google Scholar] [CrossRef]
  52. Thompson, S.G.; Higgins, J.P. How should meta-regression analyses be undertaken and interpreted? Stat. Med. 2002, 21, 1559–1573. [Google Scholar] [CrossRef] [PubMed]
  53. Egger, M.; Davey Smith, G.; Schneider, M.; Minder, C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997, 315, 629–634. [Google Scholar] [CrossRef] [Green Version]
  54. Hunter, J.P.; Saratzis, A.; Sutton, A.J.; Boucher, R.H.; Sayers, R.D.; Bown, M.J. In meta-analyses of proportion studies, funnel plots were found to be an inaccurate method of assessing publication bias. J. Clin. Epidemiol. 2014, 67, 897–903. [Google Scholar] [CrossRef] [PubMed]
  55. R Core Team. R: A Language and Environment for Statistical Computing. 2013. Available online: https://www.gbif.org/zh/tool/81287/r-a-language-and-environment-for-statistical-computing (accessed on 1 June 2021).
  56. Akour, A.; Al-Tammemi, A.B.; Barakat, M.; Kanj, R.; Fakhouri, H.N.; Malkawi, A.; Musleh, G. The Impact of the COVID-19 Pandemic and Emergency Distance Teaching on the Psychological Status of University Teachers: A Cross-Sectional Study in Jordan. Am. J. Trop. Med. Hyg. 2020, 103, 2391–2399. [Google Scholar] [CrossRef] [PubMed]
  57. Ammar, N.; Aly, N.M.; Folayan, M.O.; Khader, Y.; Virtanen, J.I.; Al-Batayneh, O.B.; Mohebbi, S.Z.; Attia, S.; Howaldt, H.-P.; Boettger, S.; et al. Behavior change due to COVID-19 among dental academics-The theory of planned behavior: Stresses, worries, training, and pandemic severity. PLoS ONE 2020, 15, e0239961. [Google Scholar] [CrossRef]
  58. Godbole, M.; Ban, D.D.; Subramanian, A.A. A Cross Sectional Study to Assess the Prevalence of Anxiety and Perception of E-Learning among School Teachers. Indian J. Public Health Res. Dev. 2021, 12, 204–208. [Google Scholar]
  59. Zhao, Y.; Guo, Y.; Xiao, Y.; Zhu, R.; Sun, W.; Huang, W.; Liang, D.; Tang, L.; Zhang, F.; Zhu, D.; et al. The Effects of Online Homeschooling on Children, Parents, and Teachers of Grades 1-9 During the COVID-19 Pandemic. Med. Sci. Monit. 2020, 26, e925591. [Google Scholar] [CrossRef]
  60. Cénat, J.M.; Blais-Rochette, C.; Kokou-Kpolou, C.K.; Noorishad, P.-G.; Mukunzi, J.N.; McIntee, S.-E.; Dalexis, R.D.; Goulet, M.-A.; Labelle, P.R. Prevalence of symptoms of depression, anxiety, insomnia, posttraumatic stress disorder, and psychological distress among populations affected by the COVID-19 pandemic: A systematic review and meta-analysis. Psychiatry Res. 2021, 295, 113599. [Google Scholar] [CrossRef] [PubMed]
  61. Hossain, M.; Tasnim, S.; Sultana, A.; Faizah, F.; Mazumder, H.; Zou, L.; McKyer, E.L.J.; Ahmed, H.U.; Ma, P. Epidemiology of mental health problems in COVID-19: A review. F1000Research 2020, 9, 636. [Google Scholar] [CrossRef] [PubMed]
  62. Alba, B.G.; Márquez, E.P.; Calvo, P.J.J. La feminización de la Educación Infantil. Un estudio de caso de estudiantes varones en la Universidad de Málaga. REDU Rev. Docencia Univ. 2021, 19, 2. [Google Scholar]
  63. Buyukkececi, Z. Cross-country differences in anxiety and behavioral response to the Covid-19 pandemic. Eur. Soc. 2021, 23, S417–S447. [Google Scholar] [CrossRef]
  64. Lall, S.; Albaladejo, M.; Mesquita, M. La Competitividad Industrial de América Latina y el Desafío de la Globalización; BID-INTAL: Buenos Aires, Argentina, 2005. [Google Scholar]
  65. Okon-Singer, H. The role of attention bias to threat in anxiety: Mechanisms, modulators and open questions. Curr. Opin. Behav. Sci. 2018, 19, 26–30. [Google Scholar] [CrossRef]
  66. Harmsen, R.; Helms-Lorenz, M.; Maulana, R.; van Veen, K. The relationship between beginning teachers’ stress causes, stress responses, teaching behaviour and attrition. Teach. Teach. 2018, 24, 626–643. [Google Scholar] [CrossRef] [Green Version]
  67. Li, W.; Kou, C. Prevalence and correlates of psychological stress among teachers at a national key comprehensive university in China. Int. J. Occup. Environ. Health 2018, 24, 7–16. [Google Scholar] [CrossRef]
  68. Urcos, W.H.C.; Urcos, C.N.C.; Ruales, E.A.B.; Urcos, J.F.C. Stress, anguish, anxiety and resilience of university teachers in the face of covid-19. Utopía Y Prax. Latinoam. 2020, 25, 453–464. [Google Scholar]
  69. Teles, R.; Valle, A.; Rodríguez, S.; Piñeiro, I.; Regueiro, B. Perceived Stress and Indicators of Burnout in Teachers at Portuguese Higher Education Institutions (HEI). Int. J. Environ. Res. Public Health 2020, 17, 3248. [Google Scholar] [CrossRef] [PubMed]
  70. Cucu, A.I.; Turliuc, M.D.; Ciurea, A.V. The COVID-19 emergency does not rule out the diagnostic arsenal in intracerebral hemorrhage: Do not forget the old enemies. Brain Behav. Immun. 2021, 91, 792–793. [Google Scholar] [CrossRef]
  71. Montemurro, N. Intracranial hemorrhage and COVID-19, but please do not forget “old diseases” and elective surgery. Brain Behav. Immun. 2021, 92, 207–208. [Google Scholar] [CrossRef]
  72. Pierce, M.; McManus, S.; Jessop, C.; John, A.; Hotopf, M.; Ford, T.; Hatch, S.; Wessely, S.C.; Abel, K.M. Says who? The significance of sampling in mental health surveys during COVID-19. Lancet Psychiatry 2020, 7, 567–568. [Google Scholar] [CrossRef]
  73. Guterres, A. Tackling the Inequality Pandemic: A New Social Contract for a New Era. Nelson Mandela Annual Lecture. 2020. Available online: https://www.un.org/africarenewal/web-features/%E2%80%9Ctackling-inequality-pandemic-new-social-contract-new-era%E2%80%9D (accessed on 1 June 2021).
  74. Stantcheva, S. Inequalities in the Times of a Pandemic. Economic Policy. 2021. Available online: https://www.economic-policy.org/73rd-economic-policy-panel/inequalities-in-the-times-of-a-pandemic/ (accessed on 5 June 2021).
  75. Frenzel, A.C.; Goetz, T.; Stephens, E.J.; Jacob, B. Antecedents and effects of teachers’ emotional experiences: An integrated perspective and empirical test. In Advances in Teacher Emotion Research; Springer: Berlin/Heidelberg, Germany, 2009; pp. 129–151. [Google Scholar]
Figure 1. Flowchart of the study search and selection process.
Figure 1. Flowchart of the study search and selection process.
Brainsci 11 01172 g001
Figure 2. Forest plot for the prevalence of mental disorders among teachers.
Figure 2. Forest plot for the prevalence of mental disorders among teachers.
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Figure 3. Funnel plot for the prevalence of mental disorders.
Figure 3. Funnel plot for the prevalence of mental disorders.
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Table 1. Characteristics of the studies included in the meta-analysis.
Table 1. Characteristics of the studies included in the meta-analysis.
First Author (Publication Year)Sample CountryPopulationSample Size (n)Mean Age (SD)% Females (n)Response Rate (%)Sampling MethodQuality Assessment
Akour et al. (2020)JordanUniversity teachers38243.9
(9.9)
44.50%
(170)
98.7%Snowball8
Ammar et al. (2020)GlobalUniversity teachers1862NR53.47%
(996)
11.3%Convenience7
Cruz et al. (2020)BrazilSchool teachers8431.4
(NR)
75.00%
(63)
80.7%NR5
Evanoff et al. (2020)USAUniversity teachers870NR60.11%
(523)
19.7%NR7
Godbole et al. (2021)IndiaSchool teachers10038.7
(NR)
32.00%
(32)
NRConvenience5
Li et al. (2020)ChinaAll teachers8861136.22
(9.02)
76.93%
(68169)
94.8%Cluster8
Ozamiz-Etxebarria et al. (2021)SpainAll teachers162342.6
(9.96)
79.67%
(1293)
NRSnowball7
Zhao et al. (2020)ChinaSchool teachers210NR79.19%
(160)
NRNR6
Abbreviations: SD, standard deviation; NR, not reported.
Table 2. Outcome assessments of the included studies.
Table 2. Outcome assessments of the included studies.
First Author (Publication Year)Anxiety AssessmentDepression AssessmentDistress Assessment
ScaleCriteriaPrevalenceScaleCriteriaPrevalenceScaleCriteriaPrevalence
Akour et al. (2020) K10≥25187 (49%)
Ammar et al. (2020) IES≥26884 (47.5%)
Cruz et al. (2020)DASS-21NR18 (21.4%)DASS-21NR24 (28.6%)DASS-21NR11 (13.1%)
Evanoff et al. (2020)DASS-21Moderate to high83 (9.5%)DASS-21Moderate to high133 (15.3%)DASS-21Moderate to high105 (12.1%)
Godbole et al. (2021)HAM-A≥1810 (10%)
Li et al. (2020)GAD-7≥1012110 (13.7%)
Ozamiz-Etxebarria et al. (2021)DASS-21Moderate to high604 (37.2%)DASS-21Moderate to high316 (19.5%)DASS-21Moderate to high560 (34.5%)
Zhao et al. (2020)SAS≥5036 (17.1%)
Abbreviations: DASS-21, Depression, Anxiety, and Stress Scale; GAD-7, Generalized Anxiety Disorder scale; HAM-A, Hamilton Rating Scale for Anxiety; IES, Impact of Event Scale; K10, Kessler Psychological Distress Scale; NR, not reported; SAS, Zung Self-Rating Anxiety Scale.
Table 3. Quality assessment.
Table 3. Quality assessment.
Study123456789TOTAL
Akour et al. (2020)YNYYYYYYY8
Ammar et al. (2020)YNYYYYYYN7
Cruz et al. (2020)NUNYYYYYU5
Evanoff et al. (2020)YUYYYYYYN7
Godbole et al. (2021)NNNYYYYYU5
Li et al. (2020)YNYYYYYYY8
Ozamiz-Etxebarria et al. (2021)YNYYYYYYN7
Zhao et al. (2020)YUNYYYYYU6
Abbreviations: N, no; Y, yes, U, unclear; (1) Was the sample frame appropriate to address the target population? (2) Were study participants recruited in an appropriate way? (3) Was the sample size adequate? (4) Were the study subjects and setting described in detail? (5) Was data analysis conducted with sufficient coverage of the identified sample? (6) Were valid methods used for the identification of the condition? (7) Was the condition measured in a standard, reliable way for all participants? (8) Was there an appropriate statistical analysis? (9) Was the response rate adequate, and if not, was the low response rate managed appropriately?
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Ozamiz-Etxebarria, N.; Idoiaga Mondragon, N.; Bueno-Notivol, J.; Pérez-Moreno, M.; Santabárbara, J. Prevalence of Anxiety, Depression, and Stress among Teachers during the COVID-19 Pandemic: A Rapid Systematic Review with Meta-Analysis. Brain Sci. 2021, 11, 1172. https://doi.org/10.3390/brainsci11091172

AMA Style

Ozamiz-Etxebarria N, Idoiaga Mondragon N, Bueno-Notivol J, Pérez-Moreno M, Santabárbara J. Prevalence of Anxiety, Depression, and Stress among Teachers during the COVID-19 Pandemic: A Rapid Systematic Review with Meta-Analysis. Brain Sciences. 2021; 11(9):1172. https://doi.org/10.3390/brainsci11091172

Chicago/Turabian Style

Ozamiz-Etxebarria, Naiara, Nahia Idoiaga Mondragon, Juan Bueno-Notivol, María Pérez-Moreno, and Javier Santabárbara. 2021. "Prevalence of Anxiety, Depression, and Stress among Teachers during the COVID-19 Pandemic: A Rapid Systematic Review with Meta-Analysis" Brain Sciences 11, no. 9: 1172. https://doi.org/10.3390/brainsci11091172

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