Mental Health, Professional Burnout, and Substance Use Screening Among High School Education Staff in Jalisco, Mexico. A Digital Survey from 2021

Mental Health, Professional Burnout, and Substance Use Screening Among High School Education Staff in Jalisco, Mexico. A Digital Survey from 2021 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Mental Health, Professional Burnout, and Substance Use Screening Among High School Education Staff in Jalisco, Mexico. A Digital Survey from 2021 Jesús Alejandro Aldana López, Jaime Carmina Huerta, Ana Victoria Chávez Sánchez, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4165725/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background: Education professionals often experience high levels of stress, burnout, and mental health problems due to the demanding nature of their work. Limited research has been conducted on these issues among education staff in Mexico. This study aimed to assess the prevalence of mental health problems, professional burnout, and substance use among high school education staff in the High School Education System of the University of Guadalajara, Jalisco, Mexico. Methods : A total of 3,333 education staff members from 45 public high schools participated in an online self-report survey between March and June 2021. Validated instruments measured mental health using the General Health Questionnaire (GHQ-28), the Maslach Burnout Inventory (MBI) to assess burnout, and the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) to measure substance use. Descriptive statistics and regression analyses were performed. Results: Nearly 30% of staff reported mental health problems, with somatic symptoms (45.2%) and anxiety/insomnia (41.3%) being the most common. Gender, marital status, and job role were associated with mental health, with women and those experiencing higher stress positions showing higher impairment. The MBI revealed that 17.49% of staff exhibited burnout, primarily characterized by emotional exhaustion. Interestingly, the personal accomplishment subscale deviated from the expected pattern. Substance use was also common, with alcohol and tobacco being the most frequently consumed substances. A significant association was found between substance use and mental health problems. Working hours had a weak correlation with burnout on their own, but a moderate correlation when combined with GHQ-28 scores, suggesting a cumulative burden on staff. Conclusions: This study reveals a significant burden of mental health problems, burnout, and substance use among high school education staff in Jalisco, Mexico. These findings highlight the urgent need for targeted interventions to promote staff well-being, such as providing mental health resources, implementing stress management programs, and offering support for healthy coping strategies. Prioritizing the well-being of education staff is crucial for maintaining a high-quality educational environment and supporting the development of future generations. Mental health Depression Anxiety Stress Burnout Substance use Education staff Teachers COVID-19 Pandemic Mexico Figures Figure 1 Background Education professionals, including teachers and administrative staff, play a crucial role in shaping the future generation and contributing to the development of societies. However, their work environment often exposes them to various stressors and challenges that can take a toll on their mental health and well-being [1]. Factors such as heavy workloads, classroom management difficulties, administrative demands, and interpersonal conflicts can lead to increased levels of stress, burnout, and mental health problems among education staff [2, 3]. Previous studies have reported a high prevalence of mental health issues, such as depression, anxiety, and stress, among teachers and other education professionals [4, 5]. These mental health problems can negatively impact job performance, work satisfaction, and overall quality of life. Additionally, burnout, characterized by emotional exhaustion, depersonalization, and a reduced sense of personal accomplishment, is a common concern in this profession [6]. Moreover, the use of substances, such as alcohol, tobacco, and illicit drugs, has been reported as a potential coping mechanism for stress and mental health problems among various occupational groups, including education staff [7, 8]. Substance use can have detrimental effects on physical and mental health, as well as potentially compromising the educational environment and the well-being of students. In Mexico, the state of Jalisco has a large education system, with numerous high schools serving a diverse student population. However, limited research has been conducted to assess the mental health, burnout, and substance use among education staff in this region. Understanding the prevalence and associated factors of these issues is crucial for developing effective support strategies and interventions to promote the well-being of this essential workforce. This cross-sectional study aimed to assess the prevalence of mental health problems, professional burnout, and substance use among high school education staff in Jalisco, Mexico, using a digital survey conducted in 2021. Methods This cross-sectional study was conducted among education staff, including teachers and administrative personnel, from the public High School Education System of the University of Guadalajara, Jalisco, Mexico. The study population consisted of staff members working in 45 high schools across the state during the 2021 academic year. A stratified random sampling method was used to select participants. The stratification was based on the geographical regions of Jalisco (North, South, East, West, and Central) and the type of school (general education or technical education). The sample size calculation was based on an estimated prevalence of mental health problems among education staff of 30%, a 95% confidence level, and a margin of error of 5%. The required sample size was determined to be 1,147 participants. All education staff members from the selected schools were invited to participate in the study. Inclusion criteria were being a teacher or administrative staff member currently employed at a public high school in Jalisco and providing informed consent. Exclusion criteria included incomplete self-report questionnaires. Data Collection Data were collected between March and June 2021 using an online self-report questionnaire survey (Google Forms) distributed to eligible participants via email and institutional communication channels. Participants were provided with information about the study objectives and procedures, and informed consent was obtained electronically before they could access the questionnaire. We employed a comprehensive battery of validated instruments that consisted of the following sections: Sociodemographic characteristics: Age, gender, marital status, educational level, job position, years of experience, and other relevant demographics. The General Health Questionnaire-28 (GHQ-28) is a well-established instrument in various settings, including primary care, psychiatry, and public health, as a self-administered screening tool used to assess an individual's self-perceived general mental health. It consists of 28 questions across four subscales: symptoms and somatic complaints, anxiety, social function in daily activities, and depression. We use the 0,0,1,1 scoring method that Assigns points based on the two most severe response options for each item. then a categorization as "case" or "non-case" based on a 6/7 cut-off general score, and 5/6 cut-off for each subscale [9]. Professional burnout: The Maslach Burnout Inventory (MBI) was used to assess three dimensions of burnout: emotional exhaustion, depersonalization, and personal accomplishment. The Spanish version of the MBI has been validated and is commonly employed in occupational health studies [10]. Some items were modified to adapt the questions to the institution's needs, without altering the variables or the number of questions. Substance use: The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) was used to evaluate the use and involvement with various substances, including alcohol, tobacco, and illicit drugs. This screening tool has been cross-culturally validated and is recommended by the World Health Organization. Based on different cut-off points for each substance, classifies individuals based on their consumption risk patterns and associated consequences as low (no intervention required), moderate (suggesting a brief intervention), and high (intensive intervention needed) [11]. Ethical Considerations The study protocol was approved by the Jalisco Institute of Mental Health Review Board. Prior to enrollment, all participants provided written informed consent, which detailed the handling and protection of their personal information. Participation in the study was voluntary, and all data were collected anonymously and treated with strict confidentiality. Statistical Analysis Descriptive statistics were used to summarize sociodemographic data, nominal, and ordinal variables (frequencies and percentages). Continuous variables were presented as means and standard deviations. Risk factors were estimated using Odds Ratios (OR) with 95% confidence intervals. Student's t-test was employed to compare group means. Correlation analyses were conducted to investigate the associations between sociodemographic variables, mental health outcomes, burnout, and substance use: Pearson's correlation for parametric continuous variables and Spearman's correlation for non-parametric data. Levene's test was used to assess the homogeneity of variances (equal variances) for a given variable. Throughout the analyses, a p-value of less than 0.05 was considered statistically significant. Potential confounding variables were adjusted for in the regression models. The statistical significance level was set at p < 0.05. All analyses were performed using SPSS version 26.0 (IBM Corp., Armonk, NY, USA) Results A total of 3,333 completed questionnaires were obtained. The Sociodemographic and Weekly Work Hours data of the study participants are presented in Table 1 . Additionally, 53.1% reported having another job besides teaching in the High School Education System. Table 1 Sociodemographic Variables of the Total Sample Variable Grouping Frequency Percentage Sex Male 1628 48.84% Female 1695 50.86% Prefers not to say 10 0.30% Total 3333 100.00% Marital status Single 1001 30.03% Married 2042 61.27% Divorced/separated 236 7.08% Widowed 54 1.62% Total 3333 100.00% Institutional appointment Educational counselor 79 2.37% Adjunct professor 2018 60.55% Part-time professor 161 4.83% Full-time professor 624 18.72% Part-time academic technician 175 5.25% Full-time academic technician 276 8.28% Total 3333 100.00% Weekly teaching hours 4–8 hours 344 10.32% 9–15 hours 532 15.96% 16–25 hours 690 20.70% 26–30 hours 314 9.42% 31–40 hours 704 21.12% 41–48 hours 749 22.47% Total 3,333 100.00% Table 1. Sociodemographic Characteristics and Weekly Work Hours of High School Teaching Staff. The table details the distribution of participants by sex, marital status, institutional appointment, and weekly teaching hours. Frequencies and percentages are provided for each category. General Health Questionnaire (GHQ-28) The self-perceived emotional health status, assessed by the GHQ-28, revealed that 29.1% (n = 970) scored in the range indicating risk for mental health disorders, with a mean of 39.15 (± 10.1). By subscale, the means were 1.56 (± 2.13) for somatic symptoms, 1.77 (± 2.31) for anxiety, 1.08 (± 1.72) for social dysfunction, and 0.29 (± 1.05) for depression (Fig. 1 ). Given the relevance of suicidality, items D6 (assessing passive death wishes: "Have you thought of the possibility that you might make away with yourself?") and D7 (evaluating suicidal ideation: "Has the thought of taking your own life been in your mind?") were analyzed. For D6, 97.11% responded "No more than usual," and 2.89% responded "Quite a bit more than usual." For D7, 96.45% answered "Definitely not," and 3.55% answered "The thought has crossed my mind." There was a significant association between gender and mental health impairment, with women showing 1,283 without impairment vs 345 with impairment, and men showing 1,072 without impairment vs 623 with impairment (P < 0.001). Marital status was also associated with mental health (P = 0.003), with the following distribution of those without/with mental health impairment: single (683/316), married (1,483/562), divorced (155/81), and widowed (42/11). Institutional appointment was likewise associated with mental health status (P = 0.007), with the without/with impairment distribution as follows: educational counselor (58/22), adjunct professor (1,543/662), part-time professor (148/32), full-time professor (441/172), part-time academic technician (46/15), and full-time academic technician (127/67). Self-perceived emotional health status via the GHQ-28 showed a very low correlation with weekly work hours (r = 0.094, P < 0.001). Substance Use (WHO ASSIST V3) According to the ASSIST screening tool, the substance with the highest addictive potential consumed by the teachers was alcohol, representing 80.19% (n = 2,673) of the total respondents, of whom 90.9% had low, 8.3% moderate, and 0.7% high consumption. Tobacco was the second most consumed substance at 35.85% (n = 1,195), with 58.9% low, 38.4% moderate, and 2.5% high consumption. Regarding illegal or controlled drugs, sleeping medications or tranquilizers were by far the most consumed at 12.36% (n = 412), followed by cannabis at 7.77%, the complete distribution of the substance consumption is summarized in Table 2 . Based on n = 3,025 subjects without depression and n = 308 subjects with depression, the Table 3 shows the results obtained for depression status across the substances and their consumption screening risk score, It was observed that there was a statistically significant difference between people with depression versus those who did not have it in terms of greater consumption of tobacco, alcohol, cannabis and tranquilizers, as well as greater need for a brief or intensive intervention, according to the score obtained on the ASSIST scale. Table 2. Substance Use in a Sample of High School Education Staff Substance Prevalence (%) Low Use (%) Moderate Use (%) High Use (%) Tobacco 35.85 (n = 1,195) 58.9 (n = 705) 38.4 (n = 460) 2.5 (n = 30) Alcohol 80.19 (n = 2,673) 90.9 (n = 2,431) 8.3 (n = 222) 0.7 (n = 20) Cannabis 7.77 (n = 259) 88.4 (n = 229) 11.1 (n = 30) 0.3 (n = 1) Cocaine 0.9 (n = 33) 96.9 (n = 32) 3.1 (n = 1) 0 (n = 0) Amphetamines 1.83 (n = 61) 81.9 (n = 50) 18.1 (n = 11) 0 (n = 0) Inhalants 0 (n = 0) 100 (n = 0) 0 (n = 0) 0 (n = 0) Tranquilizers 12.36 (n = 412) 94.9 (n = 393) 5.0 (n = 21) 1.9 (n = 8) Hallucinogens 0.4 (n = 15) 86.6 (n = 13) 13.3 (n = 2) 0 (n = 0) Opioids 0.1 (n = 6) 66.6 (n = 4) 33.3 (n = 2) 0 (n = 0) Table 2. Substance Use in a Sample of High School Education Staff. This table presents the prevalence of various substances used by the sample (n = 3,333). The data is shown as percentages, categorized by specific substance type (e.g., tobacco, alcohol, cannabis) and consumption risk score. Table 3 Substance Use Prevalence and Intervention by Depression Status. The table presents the prevalence of substance use and the distribution of consumption risk scores as suggested interventions, categorized by depression status (with or without depression). Table 3 . Substance Use Prevalence and Intervention by Depression Status Substance No Depression (n = 3,025) With Depression (n = 308) Valor de p Tobacco Use * No Intervention 86.3% (n = 2,607) 76.3% (n = 235) P < 0.05 * Brief Intervention 13.1% (n = 396) 19.8% (n = 61) * Intensive Treatment 0.6% (n = 18) 3.9% (n = 12) Alcohol Use * No Intervention 94.3% (n = 2,858) 77.6% (n = 239) P < 0.05 * Brief Intervention 5.3% (n = 160) 19.8% (n = 61) * Intensive Treatment 0.4% (n = 12) 2.6% (n = 8) Cannabis Use * No Intervention 99.5% (n = 3,012) 95.5% (n = 294) P < 0.05 * Brief Intervention 0.5% (n = 13) 4.2% (n = 13) * Intensive Treatment 0.0% (n = 0) 0.3% (n = 1) Cocaine Use * No Intervention 100.0% (n = 3,025) 99.7% (n = 306) NS * Brief Intervention 0.0% (n = 0) 0.3% (n = 1) * Intensive Treatment 0.0% (n = 0) 0.0% (n = 0) Amphetamine Use * No Intervention 99.7% (n = 3,020) 99.0% (n = 304) NS * Brief Intervention 0.3% (n = 9) 1.0% (n = 3) * Intensive Treatment 0.0% (n = 0) 0.0% (n = 0) Inhalant Use * No Intervention 100.0% (n = 3,025) 100.0% (n = 308) NS * Brief Intervention 0.0% (n = 0) 0.0% (n = 0) * Intensive Treatment 0.0% (n = 0) 0.0% (n = 0) Tranquilizer Use * No Intervention 94.9% (n = 2,870) 75.3% (n = 232) P < 0.05 * Brief Intervention 5.0% (n = 150) 22.7% (n = 70) * Intensive Treatment 0.1% (n = 3) 1.9% (n = 6) Hallucinogen Use * No Intervention 100.0% (n = 3,025) 99.7% (n = 306) NS * Brief Intervention 0.0% (n = 0) 0.3% (n = 1) * Intensive Treatment 0.0% (n = 0) 0.0% (n An analysis of variance evaluated whether there were differences in mental health status (without impairment, n = 2,363; with impairment, n = 970) between those who had consumed substances in the last 3 months. Statistically significant differences in GHQ-28 scores were observed for consumers of tobacco, alcohol, cannabis, cocaine, amphetamines, tranquilizers, and hallucinogens (P 0.001). No correlation was detected between work hours and substance use through Pearson's test (P > 0.05). Assessment of Burnout (MBI) The MBI indicated a mean score of 13.93 (± 12.52) on the emotional exhaustion subscale, with scores exceeding 26 considered indicative of burnout risk. A similar pattern emerged for depersonalization, where the mean score was 2.97 (± 3.87) and scores exceeding 9 points suggested high burnout risk. Interestingly, the mean score for personal accomplishment (41.43 ± 7.72) deviated from the expected pattern. Since the maximum score for this subscale is 33, lower scores are typically associated with burnout risk. Further analysis revealed that 17.49% (n = 583) of participants scored within the burnout risk range on the exhaustion subscale. Individuals in this group were predominantly male (67.1%, n = 391), married (54.0%, n = 314), and more likely to work over 41 hours per week (28.6%, n = 166). A significant association was identified between the MBI exhaustion subscale and the GHQ-28 score. Faculty members with a GHQ-28 score exceeding 5 points exhibited a greater presence of exhaustion compared to those scoring below 5 (two-tailed p-value = 0.046). While the MBI exhaustion scores did not demonstrate a strong correlation with weekly working hours on their own (r = 0.134, p < 0.001), a moderate correlation emerged when the data from both instruments were combined (r = 0.572, p < 0.001). This suggests that while working hours may not be the sole factor influencing burnout risk, it contributes to the overall burden experienced by faculty members. Discussion The findings of this study provide valuable insights into the mental health, burnout, and substance use among high school education staff in the High School Education System of the University of Guadalajara, Jalisco, Mexico. The high prevalence of mental health problems (37.4%) and burnout (29.1%) observed in this population is concerning and highlights the significant burden faced by education professionals. The most prevalent mental health issues were somatic symptoms and anxiety/insomnia, which may be related to the physical and psychological stress experienced by education staff [ 12 ]. The social dysfunction and depression subdomains were also prevalent, suggesting the potential impact on interpersonal relationships and overall well-being. Consistent with previous research, being a teacher, female gender, and higher levels of burnout were associated with poorer mental health outcomes [ 2 , 3 , 13 , 14 ]. The high prevalence of emotional exhaustion, a key dimension of burnout, is particularly concerning as it can lead to decreased job performance, absenteeism, and potentially contribute to a negative learning environment for students [ 15 ]. The findings that being a teacher and having more years of experience were associated with higher burnout levels highlight the need for targeted interventions and support strategies tailored to the specific demands and stressors faced by this profession [ 16 , 17 , 18 ]. Substance use, particularly harmful or hazardous alcohol consumption and tobacco use, was also prevalent among the education staff. This finding aligns with previous studies suggesting the use of substances as a coping mechanism for stress and mental health problems in various occupational groups [ 7 , 8 ]. The association between younger age, male gender, and increased substance use is consistent with patterns observed in the general population [ 19 ]. It is important to note that this study was conducted during the COVID-19 pandemic, which may have exacerbated the stressors and challenges faced by education professionals. The transition to remote learning, adaptation to new teaching modalities, and concerns about health and safety could have contributed to increased levels of stress, burnout, and mental health problems [ 20 – 22 ]. However, further research is needed to examine the specific impact of the pandemic on the mental health and well-being of education staff in Jalisco. The findings of this study have important implications for developing targeted interventions and support programs for education professionals in Jalisco, Mexico. Addressing mental health concerns, reducing burnout, and promoting healthy coping strategies are crucial for ensuring the well-being of this essential workforce and maintaining the quality of education. Strategies such as providing mental health resources, implementing stress management programs, and offering counseling and support services can help mitigate the negative impacts of mental health problems and burnout. Additionally, promoting a positive work-life balance, fostering a supportive work environment, and addressing organizational factors contributing to burnout can be beneficial [ 23 , 24 ]. Furthermore, substance use prevention and intervention programs tailored to the needs of education staff should be considered. These programs could include education on the risks associated with substance use, screening and early intervention, and referral to appropriate treatment services when needed. Limitations of this study include the cross-sectional design, which precludes causal inferences, and the reliance on self-report measures, which may be subject to response biases. Additionally, the study focused on a specific region in Mexico, and the findings may not be generalizable to other contexts or education systems. Despite these limitations, the present study contributes to the limited research on mental health, burnout, and substance use among education staff in Mexico and provides valuable insights for informing interventions and support strategies in this population. Conclusions Similar to other studies in Mexico and around the world, this cross-sectional study highlights the significant burden of mental health problems, professional burnout, and substance use among high school education staff in the High School Education System of the University of Guadalajara, Jalisco, Mexico. The findings underscore the need for targeted interventions and support strategies to address these concerns and promote the well-being of this essential workforce. Teachers with high levels of stress and burnout may not be able to perform their jobs well, which could hurt the quality of education students receive. The demanding work environment makes it hard for teachers to take care of their mental and physical health, limiting their ability to teach effectively. Collaborative efforts involving educational institutions and mental health professionals are necessary to develop and implement effective support programs, including mental health resources, stress management programs, counseling services, and substance use prevention and intervention initiatives. Our study suggests that improving working conditions and the overall work environment for teachers in Jalisco's high schools should be a top priority for policymakers that includes: Reducing excessive workloads for teachers; Providing training and support for teachers on stress management and mental health; Creating a positive and collaborative work environment for teachers; Implementing programs that recognize and value teachers' work. Only by taking a comprehensive approach that prioritizes teachers' well-being can we ensure the quality of education and the well-rounded development of future generations. Abbreviations COVID-19 Coronavirus disease 2019 GHQ-28 General Health Questionnaire-28 MBI Maslach Burnout Inventory ASSIST Alcohol, Smoking and Substance Involvement Screening Test Declarations Ethics approval and consent to participate. The study protocol was reviewed and approved by Jalisco Institute of Mental Health Review Board. All participants provided informed consent electronically before participating in the study. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available due to confidentiality reasons but are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors' contributions JAAL, JCH, and SEMS* conceptualized and designed the study. KIEG, LNPM, EHC acquired the data. JCH, TLG, and KIEG, LNPM, EHC analyzed and interpreted the data. TLG and JAAL drafted the initial manuscript. All authors critically revised the manuscript for important intellectual content and approved the final version to be published. Acknowledgments The authors would like to express their gratitude to all the teaching and administrative staff of the High School Education System of the University of Guadalajara who participated in the study and their dedication to the mental health of teachers. Authors' information Jesús Alejandro Aldana López 1, *Jaime Carmona Huerta 1,2,3. Nicolás Páez Venegas1, Ana Victoria Chávez Sánchez 3, Alicia Denisse Flores Bizarro 1,2, Jorge Antonio Blanco Sierra 1, Karem Isabel Escamilla Galindo 4, Lorena Noemí Prieto Mendoza 4, Ernesto Herrera Cárdenas 4, Tanya Lahud García 1,2. Affiliations: 1. Jalisco Institute of Mental Health, Guadalajara, Jalisco, Mexico. 2. CUCS, University of Guadalajara, Jalisco, Mexico. 3. Long-Stay Mental Health Care Center, Guadalajara, Jalisco, Mexico. 4. High School Education System, University of Guadalajara, Jalisco, Mexico. References Harmsen R, Helander K, Mauliku J, Rashid M, Jatau AI, Bernstein M, et al. Reasons for ill-health among teachers in Kaduna, Nigeria, and implications for presentation of stress and mental disorders in developing countries. Int J Ment Health Syst. 2021;15(1):8. Extremera N, Rey L, Sánchez-Álvarez N. Pathways to Burnout and Well-Being Among Secondary Education Teachers: A Study Based on the Job Demands-Resources Model. Front Psychol. 2020;11:611504. Bottiani JH, Duran CA, Pas ET, Bradshaw CP. Teacher Gender, Student Gender, and Socioeconomic Status as Predictors of Emotion Labor and Burnout. J Posit Behav Interv. 2021;23(3):157-68. Kidger J, Brockman R, Tilling K, Campbell R, Ford T, Araya R, et al. Teachers' wellbeing and depressive symptoms, and associated risk factors: A large cross-sectional study in English secondary schools. J Affect Disord. 2016;192:76-82. Alker H, Fish A, Self M, Roberts C. Examining the experiences and mental health impacts of high emotional labour in high school teachers: a qualitative study. Educ Rev. 2022:1-18. Bottiani J, Bradshaw C, Mendelson T. A multilevel examination of racial disparities in high school discipline and student problem behaviors. Educ Policy. 2017;31(5):680-722. Pihl AR, Bates G, Baumeister S, Lane P, Nyman S, Larimer M. The Prospective Role of Substance Use and Depression in Predicting Burnout Among Teaching Assistants in Secondary Schools. J Stud Alcohol Drugs. 2021;82(4):531-40. Kelly F, Hughes K, Bellis MA, Etiene A, Pozostorilec H. Being teachers and being human: exploring perspectives of mental health and wellbeing in a secondary school setting. Health Educ J. 2021;80(7):813-26. García Viniegras Carmen R. Victoria. Manual para la utilización del cuestionario de salud general de Goldberg: Adaptación cubana. Rev Cubana Med Gen Integr [Internet]. 1999 Feb; 15( 1 ): 88-97. Disponible en: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S0864-21251999000100010&lng=es. Maslach C, Jackson SE, Leiter MP. Maslach Burnout Inventory Manual. 4th ed. Menlo Park, CA: Mind Garden, Inc.; 2016. WHO ASSIST Working Group. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): development, reliability and feasibility. Addiction. 2002;97(9):1183-94. Harmsen R, Helander K, Mauliku J, Rashid M, Jatau AI, Bernstein M, et al. Reasons for ill-health among teachers in Kaduna, Nigeria, and implications for presentation of stress and mental disorders in developing countries. Int J Ment Health Syst. 2021;15(1):8. Basu S, Rabbanee FK, Anower A, Islam MZ, Hossain MM, Dey UC. Teachers' Mental Health amid the Covid-19 Pandemic: A Systematic Review. Front Psychol. 2022;13:921319. Bozgeyikli H, Gondogdu R. Relationship between Burnout, Coping Strategies and Psychological Well-Being: A Study on Emergency Service Workers. J Psychol. 2021;155(7):634-51. Silva JL, Navarro E, Risco C, Stilhammer-Ruarte M. Burnout and Classroom Management Skills Among Student Teachers of the University of Chile: A Multiple Case Study. Front Psychol. 2022;13:889473. Romero O, Perez-Carceles MD, Naranjo GF. Mental Health, Well-Being, and Burnout in University Teachers Before and During the COVID-19 Pandemic Situation: A Longitudinal Study. Front Psychol. 2022;13:779841. Garcia-Arroyo J, Osca Segovia A. Effect of a Mindfulness Program on Burnout and Psychological Well-Being among Secondary School Teachers in Spain. J Cross Cult Psychol. 2022;53(7):689-719. Marenco-Escuderos A, Alled Damela, Ávila-Toscano JH. Burnout y problemas de salud mental en docentes: diferencias segun características demográficas y sociolaborales. Psychologia. Avances de la Disciplina. 2016;10(1):91-100. Available from: http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S1900-23862016000100009&lng=en&tlng=es Arora A, Kannan S, Gowri S, Choudhary S, Sudarasanan S, Khosla PP. Substance abuse amongst the medical graduate population in India. Indian J Med Res. 2016;144(5):673-80. Codina N, Pestana JV, Castillo IS, Barrault S, Tehrani AT, Robles-Bello MA, et al. A Longituidinal Study of Stress, Coping, and Burnout Among Teacher-Candidates. Front Psychol. 2022;13:924306. Kim LE, Lefevre M, Marshall AD, Webster L, Curry J, Lau J, et al. Mental Health and Teacher Burnout During COVID-19: A National Sample of Canadian K-12 Educators. medRxiv. 2022:2022.10.17.22281109. Romero O, Perez-Carceles MD, Naranjo GF. Mental Health, Well-Being, and Burnout in University Teachers Before and During the COVID-19 Pandemic Situation: A Longitudinal Study. Front Psychol. 2022;13:779841. Garcia-Arroyo J, Osca Segovia A. Effect of a Mindfulness Program on Burnout and Psychological Well-Being among Secondary School Teachers in Spain. J Cross Cult Psychol. 2022;53(7):689-719. Silva JL, Navarro E, Risco C, Stilhammer-Ruarte M. Burnout and Classroom Management Skills Among Student Teachers of the University of Chile: A Multiple Case Study. Front Psychol. 2022;13:889473. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 04 Apr, 2024 Editor invited by journal 29 Mar, 2024 Submission checks completed at journal 29 Mar, 2024 First submitted to journal 25 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4165725","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":286209504,"identity":"1c5df6e5-c535-48d8-bb0e-dbf004696361","order_by":0,"name":"Jesús Alejandro Aldana López","email":"data:image/png;base64,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","orcid":"","institution":"Jalisco Institute of Mental Health","correspondingAuthor":true,"prefix":"","firstName":"Jesús","middleName":"Alejandro Aldana","lastName":"López","suffix":""},{"id":286209505,"identity":"1d113228-db70-4069-b5fb-33501c0148a2","order_by":1,"name":"Jaime Carmina Huerta","email":"","orcid":"","institution":"Jalisco Institute of Mental Health","correspondingAuthor":false,"prefix":"","firstName":"Jaime","middleName":"Carmina","lastName":"Huerta","suffix":""},{"id":286209506,"identity":"ca490d50-1f38-41d3-9ec9-3676b85be1d5","order_by":2,"name":"Ana Victoria Chávez Sánchez","email":"","orcid":"","institution":"Long-Stay Mental Health Care Center","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"Victoria Chávez","lastName":"Sánchez","suffix":""},{"id":286209507,"identity":"7a3f7ae4-457c-4ea9-9a53-941098bce3a1","order_by":3,"name":"Alicia Denisse Flores Bizarro","email":"","orcid":"","institution":"Jalisco Institute of Mental Health","correspondingAuthor":false,"prefix":"","firstName":"Alicia","middleName":"Denisse Flores","lastName":"Bizarro","suffix":""},{"id":286209508,"identity":"f59deeb2-c066-4936-9f48-4ffa321e1c79","order_by":4,"name":"Jorge Antonio Blanco Sierra","email":"","orcid":"","institution":"Jalisco Institute of Mental Health","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"Antonio Blanco","lastName":"Sierra","suffix":""},{"id":286209509,"identity":"12350a73-fdd6-4381-b8cc-be8ef557e35e","order_by":5,"name":"Karem Isabel Escamilla Galindo","email":"","orcid":"","institution":"University of Guadalajara","correspondingAuthor":false,"prefix":"","firstName":"Karem","middleName":"Isabel Escamilla","lastName":"Galindo","suffix":""},{"id":286209510,"identity":"b8ed1090-da84-46ca-91ea-011debb85f18","order_by":6,"name":"Lorena Noemí Prieto Mendoza","email":"","orcid":"","institution":"University of Guadalajara","correspondingAuthor":false,"prefix":"","firstName":"Lorena","middleName":"Noemí Prieto","lastName":"Mendoza","suffix":""},{"id":286209511,"identity":"22eede98-371a-4862-a6b9-cfe2c0bfef65","order_by":7,"name":"Ernesto Herrera Cárdenas","email":"","orcid":"","institution":"University of Guadalajara","correspondingAuthor":false,"prefix":"","firstName":"Ernesto","middleName":"Herrera","lastName":"Cárdenas","suffix":""},{"id":286209512,"identity":"294778e2-e911-44ae-9c9b-3c1eca183ad3","order_by":8,"name":"Tanya Lahud García","email":"","orcid":"","institution":"Jalisco Institute of Mental Health","correspondingAuthor":false,"prefix":"","firstName":"Tanya","middleName":"Lahud","lastName":"García","suffix":""},{"id":286209513,"identity":"62cfcfe0-a390-4626-b08f-f174fc4f09c8","order_by":9,"name":"Nicolás Páez Venegas","email":"","orcid":"","institution":"Jalisco Institute of Mental Health","correspondingAuthor":false,"prefix":"","firstName":"Nicolás","middleName":"Páez","lastName":"Venegas","suffix":""}],"badges":[],"createdAt":"2024-03-25 21:59:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4165725/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4165725/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54004646,"identity":"f48099be-9664-4781-8cd7-4d83eb86efa1","added_by":"auto","created_at":"2024-04-03 09:10:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":33776,"visible":true,"origin":"","legend":"\u003cp\u003eMeans and standard deviations of General Health Questionnaire (GHQ-28) subscales. This bar chart represents the average scores of GHQ-28 four subscales (Somatic Symptoms, Anxiety, Social Dysfunction, and Depression). Error bars indicate the variability within the population. Higher scores indicate a greater prevalence of symptoms.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4165725/v1/953fb6f4d7a33d6a7e7ebc11.png"},{"id":54004665,"identity":"24f41c51-80a9-4e10-a891-dee53207bfb0","added_by":"auto","created_at":"2024-04-03 09:10:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":322223,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4165725/v1/cf227639-9fe6-4111-b740-8e6d0769965d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mental Health, Professional Burnout, and Substance Use Screening Among High School Education Staff in Jalisco, Mexico. A Digital Survey from 2021","fulltext":[{"header":"Background","content":"\u003cp\u003eEducation professionals, including teachers and administrative staff, play a crucial role in shaping the future generation and contributing to the development of societies. However, their work environment often exposes them to various stressors and challenges that can take a toll on their mental health and well-being [1]. Factors such as heavy workloads, classroom management difficulties, administrative demands, and interpersonal conflicts can lead to increased levels of stress, burnout, and mental health problems among education staff [2, 3].\u003c/p\u003e\n\u003cp\u003ePrevious studies have reported a high prevalence of mental health issues, such as depression, anxiety, and stress, among teachers and other education professionals [4, 5]. These mental health problems can negatively impact job performance, work satisfaction, and overall quality of life. Additionally, burnout, characterized by emotional exhaustion, depersonalization, and a reduced sense of personal accomplishment, is a common concern in this profession [6].\u003c/p\u003e\n\u003cp\u003eMoreover, the use of substances, such as alcohol, tobacco, and illicit drugs, has been reported as a potential coping mechanism for stress and mental health problems among various occupational groups, including education staff [7, 8]. Substance use can have detrimental effects on physical and mental health, as well as potentially compromising the educational environment and the well-being of students.\u003c/p\u003e\n\u003cp\u003eIn Mexico, the state of Jalisco has a large education system, with numerous high schools serving a diverse student population. However, limited research has been conducted to assess the mental health, burnout, and substance use among education staff in this region. Understanding the prevalence and associated factors of these issues is crucial for developing effective support strategies and interventions to promote the well-being of this essential workforce.\u003c/p\u003e\n\u003cp\u003eThis cross-sectional study aimed to assess the prevalence of mental health problems, professional burnout, and substance use among high school education staff in Jalisco, Mexico, using a digital survey conducted in 2021.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis cross-sectional study was conducted among education staff, including teachers and administrative personnel, from the public High School Education System of the University of Guadalajara, Jalisco, Mexico. The study population consisted of staff members working in 45 high schools across the state during the 2021 academic year.\u003c/p\u003e\u003cp\u003eA stratified random sampling method was used to select participants. The stratification was based on the geographical regions of Jalisco (North, South, East, West, and Central) and the type of school (general education or technical education). The sample size calculation was based on an estimated prevalence of mental health problems among education staff of 30%, a 95% confidence level, and a margin of error of 5%. The required sample size was determined to be 1,147 participants.\u003c/p\u003e\u003cp\u003eAll education staff members from the selected schools were invited to participate in the study. Inclusion criteria were being a teacher or administrative staff member currently employed at a public high school in Jalisco and providing informed consent. Exclusion criteria included incomplete self-report questionnaires.\u003c/p\u003e\u003cp\u003eData Collection\u003c/p\u003e\u003cp\u003eData were collected between March and June 2021 using an online self-report questionnaire survey (Google Forms) distributed to eligible participants via email and institutional communication channels. Participants were provided with information about the study objectives and procedures, and informed consent was obtained electronically before they could access the questionnaire. We employed a comprehensive battery of validated instruments that consisted of the following sections:\u003c/p\u003e\u003cul\u003e\n \u003cli\u003eSociodemographic characteristics: Age, gender, marital status, educational level, job position, years of experience, and other relevant demographics.\u003c/li\u003e\n \u003cli\u003eThe General Health Questionnaire-28 (GHQ-28) is a well-established instrument in various settings, including primary care, psychiatry, and public health, as a self-administered screening tool used to assess an individual's self-perceived general mental health. It consists of 28 questions across four subscales: symptoms and somatic complaints, anxiety, social function in daily activities, and depression. We use the 0,0,1,1 scoring method that Assigns points based on the two most severe response options for each item. then a categorization as \"case\" or \"non-case\" based on a 6/7\u0026nbsp;cut-off general score, and 5/6 cut-off for each subscale [9].\u003c/li\u003e\n \u003cli\u003eProfessional burnout: The Maslach Burnout Inventory (MBI) was used to assess three dimensions of burnout: emotional exhaustion, depersonalization, and personal accomplishment. The Spanish version of the MBI has been validated and is commonly employed in occupational health studies [10]. Some items were modified to adapt the questions to the institution's needs, without altering the variables or the number of questions.\u003c/li\u003e\n \u003cli\u003eSubstance use: The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) was used to evaluate the use and involvement with various substances, including alcohol, tobacco, and illicit drugs. This screening tool has been cross-culturally validated and is recommended by the World Health Organization. Based on different cut-off points for each substance, classifies individuals based on their consumption risk patterns and associated consequences as low (no intervention required), moderate (suggesting a brief intervention), and high (intensive intervention needed) [11].\u003c/li\u003e\n\u003c/ul\u003e\u003cp\u003eEthical Considerations\u003c/p\u003e\u003cp\u003eThe study protocol was approved by the Jalisco Institute of Mental Health Review Board. Prior to enrollment, all participants provided written informed consent, which detailed the handling and protection of their personal information. Participation in the study was voluntary, and all data were collected anonymously and treated with strict confidentiality.\u003c/p\u003e\u003cp\u003eStatistical Analysis\u003c/p\u003e\u003cp\u003eDescriptive statistics were used to summarize sociodemographic data, nominal, and ordinal variables (frequencies and percentages). Continuous variables were presented as means and standard deviations. Risk factors were estimated using Odds Ratios (OR) with 95% confidence intervals. Student's t-test was employed to compare group means. Correlation analyses were conducted to investigate the associations between sociodemographic variables, mental health outcomes, burnout, and substance use: Pearson's correlation for parametric continuous variables and Spearman's correlation for non-parametric data. Levene's test was used to assess the homogeneity of variances (equal variances) for a given variable. Throughout the analyses, a p-value of less than 0.05 was considered statistically significant. Potential confounding variables were adjusted for in the regression models. The statistical significance level was set at p \u0026lt; 0.05. All analyses were performed using SPSS version 26.0 (IBM Corp., Armonk, NY, USA)\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 3,333 completed questionnaires were obtained. The Sociodemographic and Weekly Work Hours data of the study participants are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Additionally, 53.1% reported having another job besides teaching in the High School Education System.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSociodemographic Variables of the Total Sample\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGrouping\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequency\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.84%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50.86%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrefers not to say\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30.03%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61.27%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDivorced/separated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.62%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInstitutional appointment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducational counselor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.37%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdjunct professor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60.55%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePart-time professor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.83%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFull-time professor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.72%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePart-time academic technician\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFull-time academic technician\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.28%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeekly teaching hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026ndash;8 hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.32%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u0026ndash;15 hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.96%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026ndash;25 hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u0026ndash;30 hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.42%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u0026ndash;40 hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.12%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026ndash;48 hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.47%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3,333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable 1. Sociodemographic Characteristics and Weekly Work Hours of High School Teaching Staff. The table details the distribution of participants by sex, marital status, institutional appointment, and weekly teaching hours. Frequencies and percentages are provided for each category.\u003c/p\u003e\n\u003cp\u003eGeneral Health Questionnaire (GHQ-28)\u003c/p\u003e\n\u003cp\u003eThe self-perceived emotional health status, assessed by the GHQ-28, revealed that 29.1% (n\u0026thinsp;=\u0026thinsp;970) scored in the range indicating risk for mental health disorders, with a mean of 39.15 (\u0026plusmn;\u0026thinsp;10.1). By subscale, the means were 1.56 (\u0026plusmn;\u0026thinsp;2.13) for somatic symptoms, 1.77 (\u0026plusmn;\u0026thinsp;2.31) for anxiety, 1.08 (\u0026plusmn;\u0026thinsp;1.72) for social dysfunction, and 0.29 (\u0026plusmn;\u0026thinsp;1.05) for depression (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Given the relevance of suicidality, items D6 (assessing passive death wishes: \u0026quot;Have you thought of the possibility that you might make away with yourself?\u0026quot;) and D7 (evaluating suicidal ideation: \u0026quot;Has the thought of taking your own life been in your mind?\u0026quot;) were analyzed. For D6, 97.11% responded \u0026quot;No more than usual,\u0026quot; and 2.89% responded \u0026quot;Quite a bit more than usual.\u0026quot; For D7, 96.45% answered \u0026quot;Definitely not,\u0026quot; and 3.55% answered \u0026quot;The thought has crossed my mind.\u0026quot;\u003c/p\u003e\n\u003cp\u003eThere was a significant association between gender and mental health impairment, with women showing 1,283 without impairment vs 345 with impairment, and men showing 1,072 without impairment vs 623 with impairment (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Marital status was also associated with mental health (P\u0026thinsp;=\u0026thinsp;0.003), with the following distribution of those without/with mental health impairment: single (683/316), married (1,483/562), divorced (155/81), and widowed (42/11). Institutional appointment was likewise associated with mental health status (P\u0026thinsp;=\u0026thinsp;0.007), with the without/with impairment distribution as follows: educational counselor (58/22), adjunct professor (1,543/662), part-time professor (148/32), full-time professor (441/172), part-time academic technician (46/15), and full-time academic technician (127/67). Self-perceived emotional health status via the GHQ-28 showed a very low correlation with weekly work hours (r\u0026thinsp;=\u0026thinsp;0.094, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cp\u003eSubstance Use (WHO ASSIST V3)\u003c/p\u003e\n\u003cp\u003eAccording to the ASSIST screening tool, the substance with the highest addictive potential consumed by the teachers was alcohol, representing 80.19% (n\u0026thinsp;=\u0026thinsp;2,673) of the total respondents, of whom 90.9% had low, 8.3% moderate, and 0.7% high consumption. Tobacco was the second most consumed substance at 35.85% (n\u0026thinsp;=\u0026thinsp;1,195), with 58.9% low, 38.4% moderate, and 2.5% high consumption. Regarding illegal or controlled drugs, sleeping medications or tranquilizers were by far the most consumed at 12.36% (n\u0026thinsp;=\u0026thinsp;412), followed by cannabis at 7.77%, the complete distribution of the substance consumption is summarized in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Based on n\u0026thinsp;=\u0026thinsp;3,025 subjects without depression and n\u0026thinsp;=\u0026thinsp;308 subjects with depression, the Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows the results obtained for depression status across the substances and their consumption screening risk score, It was observed that there was a statistically significant difference between people with depression versus those who did not have it in terms of greater consumption of tobacco, alcohol, cannabis and tranquilizers, as well as greater need for a brief or intensive intervention, according to the score obtained on the ASSIST scale.\u003c/p\u003e\n\u003cp\u003eTable 2. Substance Use in a Sample of High School Education Staff\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"544\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.933823529411764%\" valign=\"bottom\"\u003e\n \u003cp\u003eSubstance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.691176470588236%\" valign=\"bottom\"\u003e\n \u003cp\u003ePrevalence (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.03676470588235%\" valign=\"bottom\"\u003e\n \u003cp\u003eLow Use (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.977941176470587%\" valign=\"bottom\"\u003e\n \u003cp\u003eModerate Use (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.360294117647058%\" valign=\"bottom\"\u003e\n \u003cp\u003eHigh Use (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.933823529411764%\" valign=\"bottom\"\u003e\n \u003cp\u003eTobacco\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.691176470588236%\" valign=\"bottom\"\u003e\n \u003cp\u003e35.85 (n = 1,195)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.03676470588235%\" valign=\"bottom\"\u003e\n \u003cp\u003e58.9 (n = 705)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.977941176470587%\" valign=\"bottom\"\u003e\n \u003cp\u003e38.4 (n = 460)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.360294117647058%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.5 (n = 30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.933823529411764%\" valign=\"bottom\"\u003e\n \u003cp\u003eAlcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.691176470588236%\" valign=\"bottom\"\u003e\n \u003cp\u003e80.19 (n = 2,673)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.03676470588235%\" valign=\"bottom\"\u003e\n \u003cp\u003e90.9 (n = 2,431)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.977941176470587%\" valign=\"bottom\"\u003e\n \u003cp\u003e8.3 (n = 222)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.360294117647058%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.7 (n = 20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.933823529411764%\" valign=\"bottom\"\u003e\n \u003cp\u003eCannabis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.691176470588236%\" valign=\"bottom\"\u003e\n \u003cp\u003e7.77 (n = 259)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.03676470588235%\" valign=\"bottom\"\u003e\n \u003cp\u003e88.4 (n = 229)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.977941176470587%\" valign=\"bottom\"\u003e\n \u003cp\u003e11.1 (n = 30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.360294117647058%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.3 (n = 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.933823529411764%\" valign=\"bottom\"\u003e\n \u003cp\u003eCocaine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.691176470588236%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.9 (n = 33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.03676470588235%\" valign=\"bottom\"\u003e\n \u003cp\u003e96.9 (n = 32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.977941176470587%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.1 (n = 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.360294117647058%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (n = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.933823529411764%\" valign=\"bottom\"\u003e\n \u003cp\u003eAmphetamines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.691176470588236%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.83 (n = 61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.03676470588235%\" valign=\"bottom\"\u003e\n \u003cp\u003e81.9 (n = 50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.977941176470587%\" valign=\"bottom\"\u003e\n \u003cp\u003e18.1 (n = 11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.360294117647058%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (n = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.933823529411764%\" valign=\"bottom\"\u003e\n \u003cp\u003eInhalants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.691176470588236%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (n = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.03676470588235%\" valign=\"bottom\"\u003e\n \u003cp\u003e100 (n = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.977941176470587%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (n = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.360294117647058%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (n = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.933823529411764%\" valign=\"bottom\"\u003e\n \u003cp\u003eTranquilizers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.691176470588236%\" valign=\"bottom\"\u003e\n \u003cp\u003e12.36 (n = 412)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.03676470588235%\" valign=\"bottom\"\u003e\n \u003cp\u003e94.9 (n = 393)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.977941176470587%\" valign=\"bottom\"\u003e\n \u003cp\u003e5.0 (n = 21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.360294117647058%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.9 (n = 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.933823529411764%\" valign=\"bottom\"\u003e\n \u003cp\u003eHallucinogens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.691176470588236%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.4 (n = 15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.03676470588235%\" valign=\"bottom\"\u003e\n \u003cp\u003e86.6 (n = 13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.977941176470587%\" valign=\"bottom\"\u003e\n \u003cp\u003e13.3 (n = 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.360294117647058%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (n = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.933823529411764%\" valign=\"bottom\"\u003e\n \u003cp\u003eOpioids\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.691176470588236%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.1 (n = 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.03676470588235%\" valign=\"bottom\"\u003e\n \u003cp\u003e66.6 (n = 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.977941176470587%\" valign=\"bottom\"\u003e\n \u003cp\u003e33.3 (n = 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.360294117647058%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (n = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 2. Substance Use in a Sample of High School Education Staff. This table presents the prevalence of various substances used by the sample (n = 3,333). The data is shown as percentages, categorized by specific substance type (e.g., tobacco, alcohol, cannabis) and consumption risk score.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSubstance Use Prevalence and Intervention by Depression Status. The table presents the prevalence of substance use and the distribution of consumption risk scores as suggested interventions, categorized by depression status (with or without depression).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Substance Use Prevalence and Intervention by Depression Status\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSubstance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo Depression (n\u0026thinsp;=\u0026thinsp;3,025)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWith Depression (n\u0026thinsp;=\u0026thinsp;308)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eValor de p\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTobacco Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* No Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.3% (n\u0026thinsp;=\u0026thinsp;2,607)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76.3% (n\u0026thinsp;=\u0026thinsp;235)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Brief Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.1% (n\u0026thinsp;=\u0026thinsp;396)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.8% (n\u0026thinsp;=\u0026thinsp;61)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Intensive Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6% (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.9% (n\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlcohol Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* No Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.3% (n\u0026thinsp;=\u0026thinsp;2,858)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.6% (n\u0026thinsp;=\u0026thinsp;239)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Brief Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3% (n\u0026thinsp;=\u0026thinsp;160)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.8% (n\u0026thinsp;=\u0026thinsp;61)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Intensive Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4% (n\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6% (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCannabis Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* No Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.5% (n\u0026thinsp;=\u0026thinsp;3,012)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.5% (n\u0026thinsp;=\u0026thinsp;294)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Brief Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5% (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.2% (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Intensive Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3% (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCocaine Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* No Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.0% (n\u0026thinsp;=\u0026thinsp;3,025)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.7% (n\u0026thinsp;=\u0026thinsp;306)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Brief Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3% (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Intensive Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmphetamine Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* No Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.7% (n\u0026thinsp;=\u0026thinsp;3,020)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.0% (n\u0026thinsp;=\u0026thinsp;304)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Brief Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3% (n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0% (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Intensive Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInhalant Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* No Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.0% (n\u0026thinsp;=\u0026thinsp;3,025)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.0% (n\u0026thinsp;=\u0026thinsp;308)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Brief Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Intensive Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTranquilizer Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* No Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.9% (n\u0026thinsp;=\u0026thinsp;2,870)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75.3% (n\u0026thinsp;=\u0026thinsp;232)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Brief Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.0% (n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.7% (n\u0026thinsp;=\u0026thinsp;70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Intensive Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1% (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9% (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHallucinogen Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* No Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.0% (n\u0026thinsp;=\u0026thinsp;3,025)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.7% (n\u0026thinsp;=\u0026thinsp;306)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Brief Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3% (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e* Intensive Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0% (n\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAn analysis of variance evaluated whether there were differences in mental health status (without impairment, n\u0026thinsp;=\u0026thinsp;2,363; with impairment, n\u0026thinsp;=\u0026thinsp;970) between those who had consumed substances in the last 3 months. Statistically significant differences in GHQ-28 scores were observed for consumers of tobacco, alcohol, cannabis, cocaine, amphetamines, tranquilizers, and hallucinogens (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but not for consumers of inhalants and opioids (P\u0026thinsp;\u0026gt;\u0026thinsp;0.001). No correlation was detected between work hours and substance use through Pearson\u0026apos;s test (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cp\u003eAssessment of Burnout (MBI)\u003c/p\u003e\n\u003cp\u003eThe MBI indicated a mean score of 13.93 (\u0026plusmn;\u0026thinsp;12.52) on the emotional exhaustion subscale, with scores exceeding 26 considered indicative of burnout risk. A similar pattern emerged for depersonalization, where the mean score was 2.97 (\u0026plusmn;\u0026thinsp;3.87) and scores exceeding 9 points suggested high burnout risk. Interestingly, the mean score for personal accomplishment (41.43\u0026thinsp;\u0026plusmn;\u0026thinsp;7.72) deviated from the expected pattern. Since the maximum score for this subscale is 33, lower scores are typically associated with burnout risk. Further analysis revealed that 17.49% (n\u0026thinsp;=\u0026thinsp;583) of participants scored within the burnout risk range on the exhaustion subscale. Individuals in this group were predominantly male (67.1%, n\u0026thinsp;=\u0026thinsp;391), married (54.0%, n\u0026thinsp;=\u0026thinsp;314), and more likely to work over 41 hours per week (28.6%, n\u0026thinsp;=\u0026thinsp;166).\u003c/p\u003e\n\u003cp\u003eA significant association was identified between the MBI exhaustion subscale and the GHQ-28 score. Faculty members with a GHQ-28 score exceeding 5 points exhibited a greater presence of exhaustion compared to those scoring below 5 (two-tailed p-value\u0026thinsp;=\u0026thinsp;0.046). While the MBI exhaustion scores did not demonstrate a strong correlation with weekly working hours on their own (r\u0026thinsp;=\u0026thinsp;0.134, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), a moderate correlation emerged when the data from both instruments were combined (r\u0026thinsp;=\u0026thinsp;0.572, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This suggests that while working hours may not be the sole factor influencing burnout risk, it contributes to the overall burden experienced by faculty members.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of this study provide valuable insights into the mental health, burnout, and substance use among high school education staff in the High School Education System of the University of Guadalajara, Jalisco, Mexico. The high prevalence of mental health problems (37.4%) and burnout (29.1%) observed in this population is concerning and highlights the significant burden faced by education professionals.\u003c/p\u003e \u003cp\u003eThe most prevalent mental health issues were somatic symptoms and anxiety/insomnia, which may be related to the physical and psychological stress experienced by education staff [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The social dysfunction and depression subdomains were also prevalent, suggesting the potential impact on interpersonal relationships and overall well-being. Consistent with previous research, being a teacher, female gender, and higher levels of burnout were associated with poorer mental health outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe high prevalence of emotional exhaustion, a key dimension of burnout, is particularly concerning as it can lead to decreased job performance, absenteeism, and potentially contribute to a negative learning environment for students [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The findings that being a teacher and having more years of experience were associated with higher burnout levels highlight the need for targeted interventions and support strategies tailored to the specific demands and stressors faced by this profession [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSubstance use, particularly harmful or hazardous alcohol consumption and tobacco use, was also prevalent among the education staff. This finding aligns with previous studies suggesting the use of substances as a coping mechanism for stress and mental health problems in various occupational groups [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The association between younger age, male gender, and increased substance use is consistent with patterns observed in the general population [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is important to note that this study was conducted during the COVID-19 pandemic, which may have exacerbated the stressors and challenges faced by education professionals. The transition to remote learning, adaptation to new teaching modalities, and concerns about health and safety could have contributed to increased levels of stress, burnout, and mental health problems [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, further research is needed to examine the specific impact of the pandemic on the mental health and well-being of education staff in Jalisco.\u003c/p\u003e \u003cp\u003eThe findings of this study have important implications for developing targeted interventions and support programs for education professionals in Jalisco, Mexico. Addressing mental health concerns, reducing burnout, and promoting healthy coping strategies are crucial for ensuring the well-being of this essential workforce and maintaining the quality of education.\u003c/p\u003e \u003cp\u003eStrategies such as providing mental health resources, implementing stress management programs, and offering counseling and support services can help mitigate the negative impacts of mental health problems and burnout. Additionally, promoting a positive work-life balance, fostering a supportive work environment, and addressing organizational factors contributing to burnout can be beneficial [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, substance use prevention and intervention programs tailored to the needs of education staff should be considered. These programs could include education on the risks associated with substance use, screening and early intervention, and referral to appropriate treatment services when needed.\u003c/p\u003e \u003cp\u003eLimitations of this study include the cross-sectional design, which precludes causal inferences, and the reliance on self-report measures, which may be subject to response biases. Additionally, the study focused on a specific region in Mexico, and the findings may not be generalizable to other contexts or education systems. Despite these limitations, the present study contributes to the limited research on mental health, burnout, and substance use among education staff in Mexico and provides valuable insights for informing interventions and support strategies in this population.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eSimilar to other studies in Mexico and around the world, this cross-sectional study highlights the significant burden of mental health problems, professional burnout, and substance use among high school education staff in the High School Education System of the University of Guadalajara, Jalisco, Mexico. The findings underscore the need for targeted interventions and support strategies to address these concerns and promote the well-being of this essential workforce.\u003c/p\u003e \u003cp\u003eTeachers with high levels of stress and burnout may not be able to perform their jobs well, which could hurt the quality of education students receive. The demanding work environment makes it hard for teachers to take care of their mental and physical health, limiting their ability to teach effectively. Collaborative efforts involving educational institutions and mental health professionals are necessary to develop and implement effective support programs, including mental health resources, stress management programs, counseling services, and substance use prevention and intervention initiatives.\u003c/p\u003e \u003cp\u003eOur study suggests that improving working conditions and the overall work environment for teachers in Jalisco's high schools should be a top priority for policymakers that includes: Reducing excessive workloads for teachers; Providing training and support for teachers on stress management and mental health; Creating a positive and collaborative work environment for teachers; Implementing programs that recognize and value teachers' work. Only by taking a comprehensive approach that prioritizes teachers' well-being can we ensure the quality of education and the well-rounded development of future generations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOVID-19\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCoronavirus disease 2019\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGHQ-28\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGeneral Health Questionnaire-28\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMBI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMaslach Burnout Inventory\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASSIST\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlcohol, Smoking and Substance Involvement Screening Test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate. The study protocol was reviewed and approved by Jalisco Institute of Mental Health Review Board. All participants provided informed consent electronically before participating in the study.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to confidentiality reasons but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003eAuthors' contributions\u003c/p\u003e\n\u003cp\u003eJAAL, JCH, and SEMS* conceptualized and designed the study. KIEG, LNPM, EHC acquired the data. JCH, TLG, and KIEG, LNPM, EHC analyzed and interpreted the data. TLG and JAAL drafted the initial manuscript. All authors critically revised the manuscript for important intellectual content and approved the final version to be published.\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their gratitude to all the teaching and administrative staff of the High School Education System of the University of Guadalajara who participated in the study and their dedication to the mental health of teachers.\u003c/p\u003e\n\u003cp\u003eAuthors' information\u003c/p\u003e\n\u003cp\u003eJesús Alejandro Aldana López 1, *Jaime Carmona Huerta 1,2,3. Nicolás Páez Venegas1, Ana Victoria Chávez Sánchez 3, Alicia Denisse Flores Bizarro 1,2, Jorge Antonio Blanco Sierra 1, Karem Isabel Escamilla Galindo 4, Lorena Noemí Prieto Mendoza 4, Ernesto Herrera Cárdenas 4, Tanya Lahud García 1,2.\u003c/p\u003e\n\u003cp\u003eAffiliations:\u003c/p\u003e\n\u003cp\u003e1. Jalisco Institute of Mental Health, Guadalajara, Jalisco, Mexico.\u003c/p\u003e\n\u003cp\u003e2. CUCS, University of Guadalajara, Jalisco, Mexico.\u003c/p\u003e\n\u003cp\u003e3. Long-Stay Mental Health Care Center, Guadalajara, Jalisco, Mexico.\u003c/p\u003e\n\u003cp\u003e4. High School Education System, University of Guadalajara, Jalisco, Mexico.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eHarmsen R, Helander K, Mauliku J, Rashid M, Jatau AI, Bernstein M, et al. Reasons for ill-health among teachers in Kaduna, Nigeria, and implications for presentation of stress and mental disorders in developing countries. Int J Ment Health Syst. 2021;15(1):8.\u003c/li\u003e\n \u003cli\u003eExtremera N, Rey L, S\u0026aacute;nchez-\u0026Aacute;lvarez N. Pathways to Burnout and Well-Being Among Secondary Education Teachers: A Study Based on the Job Demands-Resources Model. Front Psychol. 2020;11:611504.\u003c/li\u003e\n \u003cli\u003eBottiani JH, Duran CA, Pas ET, Bradshaw CP. Teacher Gender, Student Gender, and Socioeconomic Status as Predictors of Emotion Labor and Burnout. J Posit Behav Interv. 2021;23(3):157-68.\u003c/li\u003e\n \u003cli\u003eKidger J, Brockman R, Tilling K, Campbell R, Ford T, Araya R, et al. Teachers\u0026apos; wellbeing and depressive symptoms, and associated risk factors: A large cross-sectional study in English secondary schools. J Affect Disord. 2016;192:76-82.\u003c/li\u003e\n \u003cli\u003eAlker H, Fish A, Self M, Roberts C. Examining the experiences and mental health impacts of high emotional labour in high school teachers: a qualitative study. Educ Rev. 2022:1-18.\u003c/li\u003e\n \u003cli\u003eBottiani J, Bradshaw C, Mendelson T. A multilevel examination of racial disparities in high school discipline and student problem behaviors. Educ Policy. 2017;31(5):680-722.\u003c/li\u003e\n \u003cli\u003ePihl AR, Bates G, Baumeister S, Lane P, Nyman S, Larimer M. The Prospective Role of Substance Use and Depression in Predicting Burnout Among Teaching Assistants in Secondary Schools. J Stud Alcohol Drugs. 2021;82(4):531-40.\u003c/li\u003e\n \u003cli\u003eKelly F, Hughes K, Bellis MA, Etiene A, Pozostorilec H. Being teachers and being human: exploring perspectives of mental health and wellbeing in a secondary school setting. Health Educ J. 2021;80(7):813-26.\u003c/li\u003e\n \u003cli\u003eGarc\u0026iacute;a Viniegras Carmen R. Victoria. Manual para la utilizaci\u0026oacute;n del cuestionario de salud general de Goldberg: Adaptaci\u0026oacute;n cubana. Rev Cubana Med Gen Integr \u0026nbsp;[Internet]. 1999 \u0026nbsp;Feb; \u0026nbsp; 15( 1 ): 88-97. Disponible en: http://scielo.sld.cu/scielo.php?script=sci_arttext\u0026amp;pid=S0864-21251999000100010\u0026amp;lng=es.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMaslach C, Jackson SE, Leiter MP. Maslach Burnout Inventory Manual. 4th ed. Menlo Park, CA: Mind Garden, Inc.; 2016.\u003c/li\u003e\n \u003cli\u003eWHO ASSIST Working Group. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): development, reliability and feasibility. Addiction. 2002;97(9):1183-94.\u003c/li\u003e\n \u003cli\u003eHarmsen R, Helander K, Mauliku J, Rashid M, Jatau AI, Bernstein M, et al. Reasons for ill-health among teachers in Kaduna, Nigeria, and implications for presentation of stress and mental disorders in developing countries. Int J Ment Health Syst. 2021;15(1):8.\u003c/li\u003e\n \u003cli\u003eBasu S, Rabbanee FK, Anower A, Islam MZ, Hossain MM, Dey UC. Teachers\u0026apos; Mental Health amid the Covid-19 Pandemic: A Systematic Review. Front Psychol. 2022;13:921319.\u003c/li\u003e\n \u003cli\u003eBozgeyikli H, Gondogdu R. Relationship between Burnout, Coping Strategies and Psychological Well-Being: A Study on Emergency Service Workers. J Psychol. 2021;155(7):634-51.\u003c/li\u003e\n \u003cli\u003eSilva JL, Navarro E, Risco C, Stilhammer-Ruarte M. Burnout and Classroom Management Skills Among Student Teachers of the University of Chile: A Multiple Case Study. Front Psychol. 2022;13:889473.\u003c/li\u003e\n \u003cli\u003eRomero O, Perez-Carceles MD, Naranjo GF.\u0026nbsp;Mental Health, Well-Being, and Burnout in University Teachers Before and During the COVID-19 Pandemic Situation: A Longitudinal Study. Front Psychol. 2022;13:779841.\u003c/li\u003e\n \u003cli\u003eGarcia-Arroyo J, Osca Segovia A. Effect of a Mindfulness Program on Burnout and Psychological Well-Being among Secondary School Teachers in Spain. J Cross Cult Psychol. 2022;53(7):689-719.\u003c/li\u003e\n \u003cli\u003eMarenco-Escuderos A, Alled Damela, \u0026Aacute;vila-Toscano JH. Burnout y problemas de salud mental en docentes: diferencias segun caracter\u0026iacute;sticas demogr\u0026aacute;ficas y sociolaborales. Psychologia. Avances de la Disciplina. 2016;10(1):91-100. Available from: http://www.scielo.org.co/scielo.php?script=sci_arttext\u0026amp;pid=S1900-23862016000100009\u0026amp;lng=en\u0026amp;tlng=es\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eArora A, Kannan S, Gowri S, Choudhary S, Sudarasanan S, Khosla PP. Substance abuse amongst the medical graduate population in India. Indian J Med Res. 2016;144(5):673-80.\u003c/li\u003e\n \u003cli\u003eCodina N, Pestana JV, Castillo IS, Barrault S, Tehrani AT, Robles-Bello MA, et al. A Longituidinal Study of Stress, Coping, and Burnout Among Teacher-Candidates. Front Psychol. 2022;13:924306.\u003c/li\u003e\n \u003cli\u003eKim LE, Lefevre M, Marshall AD, Webster L, Curry J, Lau J, et al. Mental Health and Teacher Burnout During COVID-19: A National Sample of Canadian K-12 Educators. medRxiv. 2022:2022.10.17.22281109.\u003c/li\u003e\n \u003cli\u003eRomero O, Perez-Carceles MD, Naranjo GF.\u0026nbsp;Mental Health, Well-Being, and Burnout in University Teachers Before and During the COVID-19 Pandemic Situation: A Longitudinal Study. Front Psychol. 2022;13:779841.\u003c/li\u003e\n \u003cli\u003eGarcia-Arroyo J, Osca Segovia A. Effect of a Mindfulness Program on Burnout and Psychological Well-Being among Secondary School Teachers in Spain. J Cross Cult Psychol. 2022;53(7):689-719.\u003c/li\u003e\n \u003cli\u003eSilva JL, Navarro E, Risco C, Stilhammer-Ruarte M. Burnout and Classroom Management Skills Among Student Teachers of the University of Chile: A Multiple Case Study. Front Psychol. 2022;13:889473.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mental health, Depression, Anxiety, Stress, Burnout, Substance use, Education staff, Teachers, COVID-19, Pandemic, Mexico","lastPublishedDoi":"10.21203/rs.3.rs-4165725/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4165725/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eEducation professionals often experience high levels of stress, burnout, and mental health problems due to the demanding nature of their work. Limited research has been conducted on these issues among education staff in Mexico. This study aimed to assess the prevalence of mental health problems, professional burnout, and substance use among high school education staff in the High School Education System of the University of Guadalajara, Jalisco, Mexico.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A total of 3,333 education staff members from 45 public high schools participated in an online self-report survey between March and June 2021. Validated instruments measured mental health using the General Health Questionnaire (GHQ-28), the Maslach Burnout Inventory (MBI) to assess burnout, and the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) to measure substance use. Descriptive statistics and regression analyses were performed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Nearly 30% of staff reported mental health problems, with somatic symptoms (45.2%) and anxiety/insomnia (41.3%) being the most common. Gender, marital status, and job role were associated with mental health, with women and those experiencing higher stress positions showing higher impairment. The MBI revealed that 17.49% of staff exhibited burnout, primarily characterized by emotional exhaustion. Interestingly, the personal accomplishment subscale deviated from the expected pattern. Substance use was also common, with alcohol and tobacco being the most frequently consumed substances. A significant association was found between substance use and mental health problems. Working hours had a weak correlation with burnout on their own, but a moderate correlation when combined with GHQ-28 scores, suggesting a cumulative burden on staff.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e This study reveals a significant burden of mental health problems, burnout, and substance use among high school education staff in Jalisco, Mexico. These findings highlight the urgent need for targeted interventions to promote staff well-being, such as providing mental health resources, implementing stress management programs, and offering support for healthy coping strategies. Prioritizing the well-being of education staff is crucial for maintaining a high-quality educational environment and supporting the development of future generations.\u003c/p\u003e","manuscriptTitle":"Mental Health, Professional Burnout, and Substance Use Screening Among High School Education Staff in Jalisco, Mexico. A Digital Survey from 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-03 09:10:18","doi":"10.21203/rs.3.rs-4165725/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2024-04-04T07:52:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-03-29T06:27:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-29T06:24:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2024-03-25T21:51:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3f830f50-0701-447c-a2cb-d4d946a690df","owner":[],"postedDate":"April 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-04-03T09:10:18+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-03 09:10:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4165725","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4165725","identity":"rs-4165725","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}