Josué Omar Nava-Manzo1
Jesus Alfonso Beltran-Sanchez1
Irma Marcela González-Treviño1
Angeles Dominguez1,2*- 1Tecnologico de Monterrey, Monterrey, Mexico
- 2Universidad Andres Bello, Santiago, Chile
Engineering education is complex and demanding. The COVID-19 pandemic necessitated a sudden shift from face-to-face to virtual teaching modalities, highlighting the need for robust university continuing education programs. This caused professors to invest more hours in attending training, which added to the stressors of the profession and those caused by the global situation and could add to the appearance of mental disorders such as anxiety, depression, stress, or burnout. This research aims to explore the relationship between continuing education programs and the prevalence of mental disorders such as anxiety, depression, stress, and burnout among faculty members. Utilizing a quantitative, non-experimental, cross-sectional, correlational design, the study involved 307 professors from the School of Engineering and Sciences at a private university in northeastern Mexico. Tools included a burnout scale, a stress scale, an anxiety scale, and a self-report depression scale. Findings suggest that faculty members dedicate an average of 20 h per semester to training programs. Although no significant gender differences in training hours were observed, perceived intensity differed with educational level and contract type, suggesting that continuing education programs impact faculty mental health variably. The study concludes a statistically significant relationship exists between stress, anxiety, burnout, and continuing education programs; but the magnitudes are too low to make generalizations. However, it was found that excessive time commitment is a factor that is detrimental to mental health; therefore, it is essential that training programs, in addition to meeting institutional and operational needs, also consider controls that promote the well-being and mental health of teachers. In this sense, continuing education programs contribute to professional growth and can also be a crucial component in the prevention and mitigation of mood disorders among teachers.
1 Introduction
Engineering programs are inherently complex, necessitating continual adaptation to meet the evolving challenges of industry and the environment (National Research Council, 1985). This complexity not only demands universities to maintain faculty who are current in their disciplines but also deeply knowledgeable about their operational contexts. Faculty of this discipline are expected to possess advanced teaching competencies to effectively impart knowledge and ensure the professional formation of future engineers (Sigahi and Sznelwar, 2022; Zilbovicius et al., 2020). Consequently, universities have become environments characterized by perpetual change and escalating demands (Villamar Sánchez et al., 2019).
Transitioning from being an expert engineer to an educator poses significant challenges, primarily involving the development of pedagogical skills and the ability to simplify complex content for students (Kokhan et al., 2021). A pertinent example is the increasing necessity to utilize digital tools and adapt teaching materials for online platforms. This adaptation requires professors to master technical procedures during virtual classes, a task that can induce anxiety and frustration, particularly among those unfamiliar with educational technology (Alfaro de Prado Sagrera, 2008). This intricate responsibility, coupled with the need to meet academic and social expectations and maintain high educational standards, contributes to an increased workload (Mitchell, 2004). Consequently, faculty members are at a heightened risk of experiencing mental health issues such as anxiety, depression, and burnout (Mora et al., 2021), which are interconnected and compound the challenges faced in academia.
This situation has been exacerbated by the COVID-19 pandemic, during which an educational paradigm shift occurred, adding to the challenges already faced (Maslach and Leiter, 2021). The consequences of the rapid transition to remote learning continue to be felt, highlighting significant impacts on educational processes (Said-Hung et al., 2021). Moreover, Evers et al. (2002) noted that with each passing year, teachers increasingly perceive a greater inability to continue their work due to activity overload and burnout. These psychosocial risks have become a prominent phenomenon within the workplace and have swiftly gained notoriety (Castañeda-Aguilera and García De-Alba-García, 2020).
1.1 Mental health concerns in academia
Recent studies among university faculty have identified multiple risk factors for anxiety disorders, including age, gender, marital status, educational level, discipline, and workload (Ma et al., 2022). This development is concerning for engineering schools and the broader community, with reported increases in cases of this syndrome worldwide (García and Ortiz, 2021; Gaitán-Rossi et al., 2021; Neri Vázquez et al., 2023).
Furthermore, the link between stress and anxiety in university professors has been extensively explored (Alvites-Huamaní, 2019; Cansoy et al., 2020; Ticona et al., 2021). Such disorders arise when individuals are unable to manage their activities or tasks effectively, necessitating the investment of additional personal resources (Lazarus and Folkman, 1984; Smetackova et al., 2019). Often, this situation is compounded by institutional pressures, such as demands for scientific production and dissemination, academic overload, conflict management, and administrative duties (Escudero and Barreto, 2022; Monroy-Castillo and Juárez-García, 2019). These pressures not only undermine well-being but also significantly impact work performance and classroom effectiveness (Corbett et al., 2021; Romeiro, 2015).
In response to growing awareness of burnout syndrome, faculties and schools of professional education have implemented measures to manage workload effectively (Oliveira et al., 2021). Burnout syndrome, characterized by emotional exhaustion, depersonalization, and diminished personal accomplishment, predominantly affects professions involving intensive social interaction, such as teaching (Karavasilis, 2019; Maslach and Leiter, 2016; Unda Rojas et al., 2020). Initially, burnout may be underestimated or remain unnoticed, often concealed by high levels of motivation (Bitran et al., 2019). However, continuous exposure to unmitigated stress can deteriorate an individual’s capacity for self-care, leading to more severe consequences (Burić et al., 2019; Pandey and Tripathi, 2001).
Depression, defined by the American Psychiatric Association (2014) as a pervasive feeling of sadness impacting interest, motivation, and satisfaction, frequently coexists with anxiety and burnout (Koutsimani et al., 2019). Research indicates a complex relationship between job stress, depression, and the overall mental health of university teachers, highlighting the multifaceted impacts of these conditions (Mendes et al., 2020). The significant overlap between burnout and depression underscores the necessity of addressing both the environmental stressors and their emotional and psychological repercussions (Sieglin and Ramos, 2007). Recognizing its importance, the World Health Organization (WHO) has included burnout in the 11th edition of the International Classification of Diseases (Živanović et al., 2021), further emphasizing the need for targeted interventions in professional settings.
The confluence of anxiety, depression, stress, and burnout severely impairs the psychological well-being and job performance of university teachers, highlighting the critical need for proactive mental health interventions (Mendes et al., 2020). The World Health Organization (2022) noted that mental disorders affect 15% of working-age adults, with depression and anxiety resulting in an estimated 12 billion lost workdays annually, costing the global economy about $1 trillion USD.
In response, universities have increasingly turned to continuing education programs to address academic, operational, and welfare needs comprehensively (de Lima Ferreira and Bertotti, 2016). According to Saline (1983) and Hammond (2004), these programs are typically structured into three main categories:
a. Teacher Training: Focused on enriching didactic and psycho-pedagogical competencies.
b. Discipline-Oriented: Aimed at keeping teachers current with the latest advancements in their respective fields.
c. Development and Integration: Designed to foster a fulfilling work environment and support positive psychological health.
1.2 Continuing education programs
Continuing education programs are instrumental in promoting lifelong learning and enhancing the capacity for and interest in professional development, crucial in the fast-paced technological landscape (OECD, 2017). Particularly in engineering, where the dynamic demands constant learning, continuing education programs serve as an essential strategy for fostering self-directed learning and personal growth management (Diaz, 2020; Hadgraft and Kolmos, 2020). Research has shown that continuing education programs enhance faculty engagement with engineers and other professionals, facilitate the creation of learning communities, and bolster the ability of engineering educators to design and implement effective instructional plans (Mesutoglu and Baran, 2021).
However, training may be affected by external conditions, such as the pandemic. The education sector, particularly hard-hit by COVID-19 pandemic, faced unprecedented challenges as it transitioned from traditional face-to-face instruction to online formats. This shift, crucial for maintaining both educational continuity and community health, placed considerable strain on all educational systems, including engineering education, which is inherently content-intensive and practice-oriented (Asgari et al., 2021; Beltran-Sanchez et al., 2020). The sudden need for online education highlighted the importance of robust continuing education programs (Donitsa-Schmidt and Ramot, 2020; Miranda et al., 2021). These programs expanded rapidly, offering an array of courses focused on teacher training and well-being, including educational technology and mental health care. While these resources were intended to support faculty, the surge in available courses may paradoxically impose additional demands on teachers’ time, potentially making these initiatives counterproductive.
The aim of this research is to examine the relationship between stress, anxiety, burnout, and participation in continuing education programs among faculty members at an engineering school in Mexico. Also, test the following hypothesis:
• H1: There is a statistically significant relationship among training hours, perceived training intensity, and mental health variables (p ≤ 0.050)
• H2: There are statistically significant differences in training hours, perceived training intensity, and mental health variables between men and women (p ≤ 0.050)
• H3: There are statistically significant differences in training hours, perceived training intensity, and mental health variables, across academic degrees (p ≤ 0.050)
• H4: There are statistically significant differences in training hours, perceived training intensity, and mental health variables across types of contracts (p ≤ 0.050)
• H5: Burnout and its dimensions, perceived stress, anxiety, and depression scores differ significantly across groups categorized by the number of hours invested in training (p ≤ 0.050)
2 Method
2.1 Study design
A quantitative, non-experimental, cross-sectional, correlational study was conducted to explore the relationship between continuing education programs and faculty mental health.
2.2 Context
This study was conducted at a private university in northeastern Mexico during the COVID-19 pandemic. At that time, the university’s continuing education programs aim to enhance knowledge, skills, and competencies across various domains, including institutional work culture, educational models, technological proficiency, and teaching practices, as well as the emergent teaching topics due to the switch to online education.
Typically, the institution’s teacher training comprised four basic courses totaling approximately 16 h, designed to integrate teachers into the instructional practices of the university. In response to the pandemic, the continuing education program was expanded to include four additional courses focused on remote technology and distance learning methodologies, extending the total training duration to 24 h. Subsequently, four more courses aimed at promoting mental well-being were added, bringing the minimum total program duration to 30 h. This expansion not only increased the workload for faculty but also introduced significant emotional and logistical challenges. The rapid shift to virtual teaching required teachers to navigate a steep learning curve and adapt to new tools and pedagogical approaches.
Under this framework, the institution categorizes courses as priority or optional. Priority courses address immediate institutional needs and are time-sensitive, focusing on strategic curriculum requirements and critical institutional issues. These courses are pragmatically designed with an applied orientation to cover essential knowledge areas and competencies crucial for the institution’s effective functioning. In contrast, optional complementary courses are characterized by their elective nature and flexible scheduling, accommodating the diverse interests and needs of university faculty. This flexibility allows faculty to select courses that align with their professional interests within a structured framework of institutional priorities, fostering a sense of autonomy and empowerment. Such an approach not only motivates faculty but also contributes to the continuous improvement of educational quality and job satisfaction. Complementary elective courses provide faculty with the freedom to explore personal interests, develop specialized skills, and broaden their knowledge beyond the core disciplinary areas. Their voluntary and adaptable format promotes a personalized and enriching educational experience, enhancing both professional and personal growth.
2.3 Sample
For the determination of the sample, a non-probabilistic convenience sampling method was used. This method is characterized by obtaining responses from individuals who are willing to participate in the study and who were selected without conscious bias (Coolican, 2017; Kerlinger and Lee, 2002). In this study participated 307 teachers of the engineering school at a private university in northeastern Mexico. The sample included 115 women and 192 men with an average age of 44.72 years (SD = 10.81) and an average teaching experience of 13.68 years (SD = 12.20). Professors were categorized by contract type: full-time teaching, full-time teaching and administrative duties, full-time teaching and research, administrative role with possibility to have teaching load, and part-time teaching (see Table 1).
Table 1. Distribution of the sample by university contract type.
Academic qualifications among the participants were as follows: 47.6% held doctorates, 49.8% master’s degrees, and 2.6% bachelor’s degrees. Participants also reported an average institutional tenure of 11.14 years (SD = 11.65).
Participants were informed about their confidential participation and about the use of their data for academic purposes.
2.4 Measures
Participants provided demographic information (gender, age, academic qualifications, contract type) and details about their engagement in continuing education programs, including the number of hours and perceived intensity of training. The number of training hours was self-reported by the participants. It was not possible to validate the number of hours given that some training is offered by the institution (internal continuing education programs) and some training is external. The maximum number of hours that the survey allowed in the survey was 150 h per semester. Regarding the perceived intensity of training was also self-reported in a 5-point Likert-type scale from very low intensity (1) to very high intensity (5).
Mental health outcomes were assessed using four adapted and validated scales measuring symptoms of depression, anxiety, stress, and burnout. The description of each scale follows.
2.4.1 Burnout
The burnout measurement model used is an adaptation of the proposal made by Gil-Monte et al. (2009), consisting of three dimensions: illusion, composed of five items (e.g., I feel that my participation as a teacher is a stimulating challenge; emotional exhaustion), measured with three items (e.g., I think I am saturated by my work as a teacher); and indolence, with four items (e.g., During my activities as a teacher I do not feel like attending to some students). The response options were in a Likert-type frequency scale (0 = never and 4 = always). The scale demonstrated evidence of construct validity (χ2 = 2054.0, p = 0.001, KMO = 0.85, λ = 0.32 to 0.94, variance explained = 60.8%) and reliability, as indicated by internal consistency measures, including Cronbach’s alpha (α = 0.86) and McDonald’s omega (ω = 0.83). The complete Spanish version of the scale is provided in Annex 1 for reference.
2.4.2 Perceived stress
Perceived stress was measured with an adaptation of the Cohen et al. (1983) scale, which is unidimensional and consists of five items measured by frequencies, where 0 equals never and 4 equals always. An example of an item is: “I feel unable to control the important things in my life.” The scale had evidence of construct validity construct validity (χ2 = 751.01, p = 0.001, KMO = 0.86, λ = 0.75 to 0.80, variance explained = 59.3%) and reliability, the latter identified by internal consistency, calculating Cronbach’s alpha (α = 0.88) and McDonald’s omega (ω = 0.88) coefficients. The full Spanish version of the scale is available in Annex 2 for reference.
2.4.3 Anxiety
An institutional version of the Generalized Anxiety Scale proposed by Spitzer et al. (2006) was applied. This is a Likert-type instrument composed of five items that are scored from 0 (never) to 3 (almost every day), where the maximum value obtained is 15, which indicates a severe degree of anxiety. An example of an item is: “I am so restless that it is difficult to sit still.” The scale demonstrated evidence of construct validity (χ2 = 768.44, p = 0.001, KMO = 0.87, λ = 0.67 to 0.86, variance explained = 60.0%) and reliability, the latter identified by internal consistency, calculating Cronbach’s alpha (α = 0.88) and McDonald’s omega (ω = 0.88) coefficients. Annex 3 includes the complete Spanish version of the scale.
2.4.4 Depression
The Self-Report Depression Scale proposed by Zung (1965) and validated by Diaz et al. (2005) was used. This adapted scale consists of seven items measured with a frequency scale where 0 equals never and 4 equals always. An example of an item is: “I feel more irritable than usual.” The scale had evidence of construct validity (χ2 = 1072.95, p = 0.001, KMO = 0.83, λ = 0.51 to 0.86, variance explained = 61.1%) and reliability, the latter identified by internal consistency, calculating Cronbach’s alpha (α = 0.84) and McDonald’s omega (ω = 0.84) coefficients. The complete Spanish version of the scale can be found in Annex 4.
2.5 Procedure
The present study lasted 5 months. During this time, the necessary approvals of the institutional authorities were obtained, and the data collection strategy was designed. Then, the implementation of the instrument occurred, in accordance with the ethics committee guidelines, through the Qualtrics platform, which facilitated the collection of data via an online portal accessible via a generic link sent by email. Participation was voluntary; all participants signed an informed consent form, and data was kept confidential. For the analysis, all identification information was removed to ensure anonymity. The data collected was analyzed and discussed by the research team. Finally, reports were prepared on the results found and recommendations.
2.6 Data analysis
Data analysis was performed with the IBM SPSS Statistics version 26 statistical software. The mean (measure of central tendency) and standard deviation (measure of dispersion) were used to describe the data. Likewise, quartiles were used to define groups (measure of position) and symmetry and kurtosis were checked to determine the distribution of the data.
Additionally, a series of hypothesis testing tests were applied, where the statistical significance value is equal to or less than 0.050. The tests are:
• Student’s t test for independent groups to compare means, complemented by Levane’s statistic to test the homogeneity of the variances of the groups and Cohen (1988) d statistic to determine the effect size.
• Pearson’s test-moment correlation coefficient (r) to identify linear relationships between two variables.
• Analysis of Variance (ANOVA) used to compare the means of three or more independent groups. Homogeneity of variances was tested by means of Levane’s statistic and effect size by means of the ω statistic2 (Field, 2009).
The levels of the measured variables were determined by intervals, considering the values of each of the scales, that is, equal-sized intervals centered around the mean. Thus, for perceived stress, depression and burnout with their dimensions, we considered: Very low (0.00–0.80), Low (0.80–1.60), Medium (1.60–2.40), High (2.40–3.20), Very high (3.20–4.00). On the other hand, for anxiety the intervals are: Very low (0.00–0.60), Low (0.60–1.20), Medium (1.20–1.80), High (1,0.80–2.40), Very high (2.40–3.00).
3 Results
The main findings indicate that teachers dedicate, on average, about 20 h to training programs during the semester and that this time investment represents a medium level of perceived intensity of the training. Table 2 shows the results related to teachers’ mental health, where the highest score corresponds to emotional exhaustion, one of the dimensions of the burnout model. The rest of the indexes tend to be low or very low.
Table 2. Descriptives related to training and mental health indices.
3.1 Continuing education, gender and mental health variables
Training hours in the continuing education programs were analyzed with respect to gender, academic qualifications, contract type, and the mental health variables. With respect to gender, a t-test was conducted to compare the mean hours of training between women and men. The results showed no statistically significant differences by gender in either duration of training, measured in hours (t = 1.04, p = 0.299, Cohen’s d = 0.12), or perceived training intensity (t = −0.43, p = 0.667, d = 0.05). Likewise, the differences between men and women were examined in relation to the mental health variables. Only the exhaustion, dimension of burnout, exhibited statistically significant differences, with women displaying a higher prevalence than men (t = 2.27, p = 0.024, Cohen’s d = 0.27).
3.2 Continuing education and teachers’ contract type
Further ANOVA testing with “contract type” as a factor showed differences in training hours and perceived training intensity among contract types. Faculty members with full-time teaching contracts (focus on teaching or on research) reported the highest training hours (F = 8.79, p = 0.001, ω2 = 0.32). Differences in the perceived training intensity were noted between part-time instructors and full-time researchers, with the latter group reporting higher levels (F = 2.82, p = 0.025, ω2 = 0.19). Moreover, analysis by contract type found significant differences among part-time instructors in perceived stress (F = 3.39, p = 0.020, post hoc = part-time teachers, administrative role < teaching and administrative role, ω2 = 0.25) and emotional exhaustion (F = 3.09, p = 0.033, post hoc = administrative role < teaching and administrative role, ω2 = 0.25).
In addition to the above, it was found that teachers with a “Teaching and research” contract report systematically higher levels in each of the mental health variables: Burnout (F = 19.51, p < 0.001, ω2 = 0.19), Illusion (F = 9.15, p < 0.001, ω2 = 0.10), Exhaustion (F = 21.06, p < 0.001, ω2 = 0.21), Indolence (F = 5.03, p = 0.032, ω2 = 0.05), Stress (F = 9.56, p < 0.001, ω2 = 0.10), Anxiety (F = 5.61, p < 0.001, ω2 = 0.06), and Depression (F = 5.18, p = 0.006, ω2 = 0.05). In most cases, the difference lies between part-time teaching and full-time teaching and research contracts.
3.3 Continuing education and academic qualifications
An Analysis of Variance (ANOVA) was performed to examine differences in training hours and perceived training intensity across academic qualifications. The analysis revealed no significant differences in training duration (F = 1.38, p = 0.253). However, significant differences were found in the perceived training intensity (F = 4.27, p = 0.010, ω2 = 0.17), with professors holding bachelor’s degrees reporting the highest perceived training intensity, although data homogeneity between groups was not observed. On the other hand, the same test was performed to identify differences in mental health variables among academic qualifications, the test results were that teachers with doctoral degree report higher in burnout (F = 10.16, p < 0.001, ω2 = 0.06), exhaustion (F = 12.46, p < 0.001, ω2 = 0.07), indolence (F = 3.47, p = 0.032, ω2 = 0.02), stress (F = 7.75, p < 0.001, ω2 = 0.04), anxiety (F = 5.24, p = 0.006, ω2 = 0.03), and depression (F = 5.51, p = 0.004, ω2 = 0.03).
3.4 Continuing education, training hours and mental health variables
Pearson’s correlation analysis explored the relationships among training hours, perceived training intensity, and mental health variables, revealing statistically significant correlations (p < 0.050). However, all correlations were trivial as none were greater than 0.30.
3.4.1 Analysis of training hours quartiles
To delve deeper into this last result, four groups were formed based on quartiles of reported training hours: low, mid-low, mid-high, and high. The criteria of training hours for each quartile is as follows: Professors were categorized into quartiles based on reported training hours:
• Low: 0–6 h (n = 99)
• Mid-Low: 6.01–15 h (n = 69)
• Mid-High: 15.01–25 h (n = 70)
• High: 25.01–121 h (n = 69)
An ANOVA was conducted to compare these groups, indicating significant differences in some dimensions of mental health. In Table 3, it is possible to observe that the test results indicate that training time has a statistically significant effect on burnout syndrome and its exhaustion dimension, as well as on perceived stress, anxiety and depression. That is, teachers who reported having received more hours of training (Group 4) also report higher levels of the above variables. However, the results for anxiety and depression should be interpreted with caution given the low effect size (Faul et al., 2007).
Table 3. Means, standard deviation, and Analysis of Variance between groups by hours of training in mental health variables.
4 Discussion
For coherence, this section is structured as the previous one.
4.1 Continuing education, gender and mental health variables
Even though the academic community is a population at risk, especially during the pandemic (Gaitán-Rossi et al., 2021; García and Ortiz, 2021; Gómez et al., 2019; Neri Vázquez et al., 2023), the results of this study reveal that the participants present a low level of anxiety, depression, perceived stress and burnout and no significant differences were found between age and gender groups. These findings, coincide with a systematic review by Ma et al. (2022) who conducted a meta-analysis on anxiety in teachers, where most of the analyzes studies suggest that anxiety levels tend to be low in the field of higher education. Although, this discrepancy cannot be attributed exclusively to the continuing education program, it is known that job satisfaction, academic grade, and sense of accomplishment are protective factors that significantly decrease the risk of mood disorder (Ma et al., 2022; Menghi, 2018).
4.2 Continuing education and teachers’ contract type
Although all professors have as a common denominator their participation in engineering education, it has been observed that tenured professors tend to dedicate more time to the continuing education program compared to their peers, especially in comparison with part-time instructors. This disparity in participation may be attributed to greater institutional commitment and job stability, as working on temporary contracts may lower attachment to the institution (Gómez et al., 2019). Regarding the differences found in the perceived intensity of the continuous education, this can be attributed to the level of commitment and responsibility by contract type; part-time instructors may require more training.
4.3 Continuing education and academic qualifications
Regarding the differences found in academic qualifications, these results coincide with the findings of Ma et al. (2022), who identified that groups of teachers with lower academic degrees tended to have a greater tendency to suffer burnout and stress. This phenomenon is mainly seen when learning and incorporating new technologies into the learning process (Fernández-Batanero et al., 2021). However, this stress factor gradually disappears when the individual masters and integrates technology into his or her life. This is because it facilitates social contact, creating a positive feeling that allows coping with stress instead of causing it (Mheidly et al., 2020).
However, in the context of engineering, according to the National Research Council (1985), the success and results of continuing education are not reported as a function of time spent. It is known that programs tend to show a positive effect as long as they have a clear objective that is aligned with the goals established by the companies and they combine interactive and non-interactive instructional support (Robertson et al., 2003). In this sense, the institutional program offered by the university combines a modality of courses called synchronous (instructor-led) and asynchronous (self-directed), which allows to adapt to the time of teachers and also allow self-management of learning.
4.4 Continuing education and training hours and mental health variables
The study reveals that professors at the institution average 18.89 h of training, perceived as moderately intense, aligning with the university’s statutory requirements. Despite the absence of clear guidelines in the literature regarding optimal duration for continuing education programs, factors such as duration, material quality, trainer experience, training context, participant knowledge level, and follow-up procedures significantly influence their effectiveness (Robertson et al., 2003).
It was observed that increased training duration correlates with heightened perceived stress and burnout, although these relationships are of low magnitude and do not necessarily indicate clinical anxiety disorders. Instead, they may reflect typical adjustments to new educational technologies and methodologies, a common occurrence among engineering faculty seeking to enhance their skills (Sastre-Merino et al., 2021).
5 Conclusion
The main objective of this study was to identify the relationship between stress, anxiety, burnout and continuing education programs in teachers of an engineering and science school. In this sense, it is possible to conclude that there is a statistically significant relationship between these variables, but with magnitudes too low to make the desired generalizations. Thus, hypothesis 1 was supported, however it is important to continue with its study for the reasons mentioned above.
In general, no significant differences were identified between men and women in terms of the number of hours invested in continuing education programs and the intensity with which they were perceived nor between mental health variables. Thus, hypothesis 2 cannot be confirmed. Conversely, statistically significant differences were identified among academic degrees about both the perceived intensity of continuing education programs and the mental health variables. Thus, hypothesis 3 is confirmed. Likewise, hypothesis 4 is confirmed by finding differences between the types of contracts, both in the hours spent and the perceived intensity of the training and the mental health variables Furthermore, a high number of training hours was identified as a factor detrimental to mental health (hypothesis 5).
The institution’s continuing education program is strategically based on four pillars: institutional culture, integration into teaching practice, human dignity, and health and welfare (Valenzuela and Galvis, 2019). By focusing on these key areas, the program underscores a commitment to holistic development, addressing both pedagogical skills and emotional well-being. This comprehensive approach reflects a deep understanding of the unique challenges faced by faculty, aiming to improve educational outcomes and foster a supportive work environment (Rodríguez-Martínez et al., 2018). Being human development part of institutional philosophy, their training programs, from the design to the implementation, promote well-being as well as equal opportunities for all, besides the disciplinary content. We consider that the continuing education programs by embedding such characteristics play a fundamental role that could act as a buffer to mitigate the stressors inherent to the academic environment through the promotion of educational effectiveness and the creation of a positive work climate (Menghi, 2018).
5.1 Limitations and recommendations
It is important to acknowledge the limitations of the present study. Despite the large sample size, the study is not representative of the entire engineering teaching population at the participating university. It is recommended to conduct further replications using a probabilistic sampling technique with a greater scope, which would allow to generalize the findings and increase the impact. Also, the inclusion of other disciplines would facilitate a more comprehensive understanding of the phenomenon under study. Moreover, as a cross-sectional study, it is challenging to ascertain the causal relationships between variables, and the results may be influenced by atypical situations. Therefore, it is recommended to pursue the study through longitudinal research designs that can monitor trends and provide more reliable results.
5.2 Future directions
Educational institutions develop continuing education programs as a strategic response to adapt to the new realities introduced by the pandemic. However, it is crucial to acknowledge that increased participation in continuing education programs could lead to work overload, adversely affecting teachers’ mental health and well-being. Balancing the demands of continuing education with academic and personal responsibilities is challenging and can exacerbate stress, contributing to feelings of overwhelm among faculty members (Kyndt et al., 2019).
It is important to adopt a holistic approach to the design and implementation of continuing education programs offered to university faculty. This approach should ensure the relevance and utility of courses while providing adequate support to enable effective participation without compromising faculty well-being. Considerations may include institutional policies that encourage a balance between professional development and self-care and the integration of additional resources for mentoring, counseling, and wellness services (Skaalvik and Skaalvik, 2017). Through such measures, continuing education programs can effectively enhance faculty skills and well-being, thereby improving the overall quality of higher education.
Thus, continuing education programs implemented by the university not only promotes faculty well-being and professional development but also acknowledges the critical importance of addressing both pedagogical and emotional needs. These programs contribute significantly to enhancing educational quality and creating healthier, more engaging work environments. However, it is imperative that these initiatives are carefully designed and implemented, considering the real-world challenges and daily realities faced by faculty. Properly executed, continuing education programs can effectively strengthen teaching capabilities and foster well-being in higher education settings.
To deepen understanding of continuing education programs and their impact on engineering faculty mental health, further research should adopt a qualitative approach to capture the nuanced realities of teaching experiences. Differentiated analyses of course types could elucidate which are most taxing, and longitudinal or quasi-experimental studies could help identify various influencing factors and test intervention strategies.
Despite the low prevalence of anxiety and depression found in this study, it is imperative not to underestimate the importance of mental health within this sector. Continuing education, especially programs that emphasize wellness, can play a pivotal role in mitigating risks associated with mental health issues, thereby not only contributing to professional growth but also helping prevent and mitigate mood disorders among faculty.
Data availability statement
The datasets presented in this article are not readily available because of confidentiality issues. Requests to access the datasets should be directed to AD, YW5nZWxlcy5kb21pbmd1ZXpAdGVjLm14.
Ethics statement
The studies involving humans were approved by Instituto Tecnologico y de Estudios Superiores de Monterrey. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
JN-M: Conceptualization, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review & editing. JB-S: Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. IG-T: Conceptualization, Visualization, Writing – review & editing. AD: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Visualization, Writing – review & editing.
Funding
The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This publication is a product of a project funded by the Impact Measurement Office of the Institute for the Future of Education at Tecnnologico de Monterrey. Also, the authors are thankful for the support from the project ID # I035 - IFE005 - C1-T3 – E of the Challenge-Based Research Funding Program 2022 at Tecnologico de Monterrey.
Acknowledgments
We are grateful to the School of Engineering and Sciences of the Tecnologico de Monterrey, its directors, and professors for allowing the collection of data for this study. The authors acknowledge the financial and technical support of Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Mexico, in the production of this work.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
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Supplementary material
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References
Alfaro de Prado Sagrera, A. (2008). New technologies and new occupational hazards. Stress and technostress. Revista Digital Salud Seguridad En El Trabajo. 1, 1–23.
Alvites-Huamaní, C. G. (2019). Teacher stress and psychosocial factors in teachers in Latin America, North America and Europe. Purposes Representations 7:141. doi: 10.20511/pyr2019.v7n3.393
American Psychological Association (2017). Ethical principles of psychologists and code of conduct. https://www.apa.org/ethics/code (Accessed April 30, 2024).
Asgari, S., Trajkovic, J., Rahmani, M., Zhang, W., Lo, R. C., and Sciortino, A. (2021). An observational study of engineering online education during the COVID-19 pandemic. PLoS One 16:e0250041. doi: 10.1371/journal.pone.0250041
Beltran-Sanchez, J. A., González-Treviño, I. M., and Dominguez, A. (2020). Digital education in times of COVID-19: the experience of medical educators. 2020 the 4th international conference on digital Technology in Education, 26–31.
Bitran, M., Zúñiga, D., Pedrals, N., Echeverría, G., Vergara, C., Rigotti, A., et al. (2019). Burnout in students of health-care professions. Risk and protection factors. Revista Medica Chile 147, 510–517. doi: 10.4067/S0034-98872019000400510
Burić, I., Slišković, A., and Penezić, Z. (2019). Understanding teacher well-being: a cross-lagged analysis of burnout, negative student-related emotions, psychopathological symptoms, and resilience. Educ. Psychol. 39, 1136–1155. doi: 10.1080/01443410.2019.1577952
Cansoy, R., Parlar, H., and Turkoglu, M. E. (2020). A predictor of teachers ' psychological well-being: teacher self-efficacy. Int. Online J. Educ. Sci. 12, 41–55. doi: 10.15345/iojes.2020.04.003
Castañeda-Aguilera, E., and García De-Alba-García, J. E. (2020). Professional burnout syndrome (burnout) in specialist surgeons: prevalence and risk factors. Cirugía Cirujanos 88, 354–360. doi: 10.24875/CIRU.19001502
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. 2nd Edn. USA: Lawrence Erlbaum Associates.
Cohen, S., Kamarck, T., and Mermelstein, R. (1983). A global measure of perceived stress. J. Health Soc. Behav. 24, 385–396. doi: 10.2307/2136404
Coolican, H. (2017). Research methods and statistics in psychology (6th ed.). London, UK: Psychology Press.
Corbett, L., Phongsavan, P., Peralta, L. R., and Bauman, A. (2021). Understanding the characteristics of professional development programs for teachers' health and wellbeing: implications for research and practice. Aust. J. Educ. 65, 139–152. doi: 10.1177/00049441211003429
de Lima Ferreira, J., and Bertotti, G. R. (2016). Continuing education for professional development in higher education teaching. Creat. Educ. 7, 1425–1435. doi: 10.4236/ce.2016.710148
Diaz, A. (2020). Engineering education 5.0: continuously evolving engineering education. Int. J. Eng. Educ. 36, 1814–1832.
Diaz, L. A., Campo, A., Rueda, G. E., and Barros, J. A. (2005). Proposal for an abbreviated version of the Zung scale for depression. Colomb. Med. 36, 168–172.
Donitsa-Schmidt, S., and Ramot, R. (2020). Opportunities and challenges: teacher education in Israel in the Covid-19 pandemic. J. Educ. Teach. 46, 586–595. doi: 10.1080/02607476.2020.1799708
Escudero, I., and Barreto, D. (2022). Psychosocial risk factors related to occupational stress in the university professor. Libre Empresa 19, 167–144. doi: 10.18041/1657-2815/libreempresa.2022v19n1.9425
Evers, W., Brouwers, A., and Tomic, W. (2002). Burnout and self-efficacy: a study on teachers' beliefs when implementing an innovative educational system in the Netherlands. Br. J. Educ. Psychol. 72, 227–243. doi: 10.1348/000709902158865
Faul, F., Erdfelder, E., Lang, A.-G., and Buchner, A. (2007). G*power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods 39, 175–191. doi: 10.3758/BF03193146
Fernández-Batanero, J.-M., Román-Graván, P., Reyes-Rebollo, M.-M., and Montenegro-Rueda, M. (2021). Impact of educational technology on teacher stress and anxiety: a literature review. Int. J. Environ. Res. Public Health 18:548. doi: 10.3390/ijerph18020548
Gaitán-Rossi, P., Pérez-Hernández, V., Vilar-Compte, M., and Teruel-Belismelis, G. (2021). Monthly prevalence of generalized anxiety disorder during the Covid-19 pandemic in Mexico. Salud Publica Mex. 63, 478–485. doi: 10.21149/12257
García, V., and Ortiz, J. J. (2021). El Riesgo Psicosocial Burnout en los Docentes de las Facultades de Ingeniería, durente la Pandemia de COVID-19. Effect Analysis in Women and Men. Int. Meeting Engin. Educ. ACOFI 2021, 1–12. doi: 10.26507/ponencia.1604
Gil-Monte, P., Unda, S., and Sandoval, J. (2009). Factorial validity of the "questionnaire for the evaluation of burnout at work syndrome" (CESQT) in a sample of Mexican teachers. Salud Mental 31, 205–214.
Gómez, V., Perilla, L., and Hermosa, A. (2019). Health risks of university teachers derived from occupational psychosocial factors. Universitas Psychol. 18, 1–15. doi: 10.11144/Javeriana.upsy18-3.rspu
Hadgraft, R. G., and Kolmos, A. (2020). Emerging learning environments in engineering education. Australas. J. Eng. Educ. 25, 3–16. doi: 10.1080/22054952.2020.1713522
Hammond, C. (2004). Impacts of lifelong learning upon emotional resilience, psychological and mental health: fieldwork evidence. Oxf. Rev. Educ. 30, 551–568. doi: 10.1080/0305498042000303008
Karavasilis, G. (2019). Work satisfaction or burnout and their impact on innovative work behavior of Greek teachers. J. Contemp. Educ. Theory Res. 3, 3–10. doi: 10.25656/01
Kerlinger, F., and Lee, H. (2002). “Investigacion del comportamiento” in Métodos de Investigación en Ciencias Sociales. 4th ed (Mexico: McGraw Hill).
Kokhan, S., Romanova, E., Skaily, A., Kowalski, V., Taneva, S., and Nodeina, L. (2021). Adaptation problems of teachers and students with disabilities in the university pedagogical process in Russia. Palaestra 35, 15–23.
Koutsimani, P., Montgomery, A., and Georganta, K. (2019). The relationship between burnout, depression, and anxiety: a systematic review and Meta-analysis. Front. Psychol. 10:284. doi: 10.3389/fpsyg.2019.00284
Kyndt, E., Donche, V., Coertjens, L., van Daal, T., Gijbels, D., and Van Petegem, P. (2019). Does self-efficacy contribute to the development of students' motivation across the transition from secondary to higher education? Eur. J. Psychol. Educ. 34, 457–478. doi: 10.1007/s10212-018-0389-6
Lazarus, R., and Folkman, S. (1984). Stress, appraisal and coping. New York: Springer Publishing Company.
Ma, K., Liang, L., Chutiyami, M., Nicoll, S., Khaerudin, T., and Van Ha, X. (2022). COVID-19 pandemic-related anxiety, stress, and depression among teachers: a systematic review and meta-analysis. Work 73, 3–27. doi: 10.3233/WOR-220062
Maslach, C., and Leiter, M. P. (2016). Understanding the burnout experience: recent research and its implications for psychiatry. World Psychiatry 15, 103–111. doi: 10.1002/wps.20311
Maslach, C., and Leiter, M. P. (2021). How to measure burnout accurately and ethically. Harv. Bus. Rev., 1–9.
Mendes, L., Campelo, E., Pinheiro, C., Pires, I., and Vasconcelos, G. (2020). Stress and depression in teachers in a public teaching institution. Global Nursing 19, 232–242. doi: 10.6018/eglobal.19.1.383201
Menghi, M. S. (2018). Teachers' mental health: protective factors. ConCiencia EPG J. 3, 13–30. doi: 10.32654/CONCIENCIAEPG.3-1-1
Mesutoglu, C., and Baran, E. (2021). Integration of engineering into K-12 education: a systematic review of teacher professional development programs. Res. Sci. Technol. Educ. 39, 328–346. doi: 10.1080/02635143.2020.1740669
Mheidly, N., Fares, M. Y., and Fares, J. (2020). Coping with stress and burnout associated with telecommunication and online learning. Front. Public Health 8, 1–7. doi: 10.3389/fpubh.2020.574969
Miranda, J., Navarrete, C., Noguez, J., Molina-Espinosa, J. M., Ramírez-Montoya, M. S., Navarro-Tuch, S. A., et al. (2021). The core components of education 4.0 in higher education: three case studies in engineering education. Comput. Electr. Eng. 93:107278. doi: 10.1016/j.compeleceng.2021.107278
Mitchell, J. E. (2004). Time professors spend improving their teaching. Front. Educ. 2004, 949–951. doi: 10.1109/FIE.2004.1408681
Monroy-Castillo, A., and Juárez-García, A. (2019). Psychosocial occupational risk factors in academics at higher education institutions in Latin America: a systematic review. Propósitos Representaciones 7:248. doi: 10.20511/pyr2019.v7n3.361
Mora, C., Bonilla, G., and Bonilla, J. (2021). Impact of the COVID-19 pandemic on teachers: burnout, anxiety and depression. Revista UNAE. 6, 41–60.
National Research Council (1985). Continuing education of engineers. Washington, DC: National Academy Press.
Neri Vázquez, J. R., Rodríguez López, M. G., Vargas Ruiz, A. G., and Ortiz Sauza, D. L. (2023). Incidence of depression and anxiety in the general population of Mexico. LATAM Revista Latinoamericana Ciencias Sociales Humanidades 4, 111–122. doi: 10.56712/latam.v4i6.1427
OECD (2017). “Enabling the next production revolution: a summary of Main messages and policy” in Organisation for economic co-operation and development. OECD.
Oliveira, S., Roberto, M. S., Veiga-Simão, A. M., and Marques-Pinto, S. (2021). A meta-analysis of the impact of social and emotional learning interventions on teachers’ burnout symptoms. Educ Psychol Rev. 33, 1779–1808. doi: 10.1007/s10648-021-09612-x
Pandey, R., and Tripathi, S. (2001). Occupational stress and burnout in engineering college teachers. J. Indian Acad. Appl. Psychol. 27, 67–73.
Robertson, M. K., Umble, K. E., and Cervero, R. M. (2003). Impact studies in continuing education for health professions: update. J. Contin. Educ. Health Prof. 23, 146–156. doi: 10.1002/chp.1340230305
Rodríguez-Martínez, M., Tovalin-Ahumada, J. H., Gil-Monte, P. R., Salvador-Cruz, J., and Acle-Tomasini, G. (2018). Emotional labor and job stressors as predictors of anxiety and depression in Mexican university professors. Informació Psicológica, 115, 93–107. doi: 10.14635/IPSIC.2018.115.11
Romeiro, S. (2015). Psychological and occupational well-being in teachers: an empirical correlational study. Int. Scientific J. 2, 123–148.
Said-Hung, E., Marcano, B., and Garzón-Clemente, R. (2021). Academic anxiety in teachers and COVID-19. Prisma Social 33, 290–305.
Saline, L. E. (1983). Continuing engineering education: one element of lifelong learning for engineers. IEEE Trans. Educ. 26, 122–126. doi: 10.1109/TE.1983.4321628
Sastre-Merino, S., Núñez-del-Río, M. C., Caravantes, A., and Bravo-Ramos, J. L. (2021). Perceptions of engineering faculty members of online teaching due to COVID-19. Int. J. Eng. Educ. 37, 1567–1581.
Sieglin, V., and Ramos, M. (2007). Job stress and depression among teachers in the Monterrey metropolitan area. Rev. Mex. Sociol. 69, 517–551.
Sigahi, T. F. A. C., and Sznelwar, L. I. (2022). Exploring applications of complexity theory in engineering education research: a systematic literature review. J. Eng. Educ. 111, 232–260. doi: 10.1002/jee.20438
Skaalvik, E. M., and Skaalvik, S. (2017). Dimensions of teacher burnout: relations with potential stressors at school. Soc. Psychol. Educ. 20, 775–790. doi: 10.1007/s11218-017-9391-0
Smetackova, I., Viktorova, I., Pavlas Martanova, V., Pachova, A., Francova, V., and Stech, S. (2019). Teachers between job satisfaction and burnout syndrome: what makes difference in Czech elementary schools. Front. Psychol. 10, 1–8. doi: 10.3389/fpsyg.2019.02287
Spitzer, R. L., Kroenke, K., Williams, J. B. W., and Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch. Intern. Med. 166, 1092–1097. doi: 10.1001/archinte.166.10.1092
Ticona, M., Zela Payi, N. O., and Vásquez Machicao, L. (2021). Anxiety and stress in virtual education in the period of health emergency due to COVID-19. Revista Científica de Sistemas e Informática 1, 27–37. doi: 10.51252/rcsi.v1i2.161
Unda Rojas, S., Hernández-Toledano, R. A., García-Arreola, O., and Esquivel Lozada, C. (2020). Psychosocial risk factors predictors of burnout syndrome (burnout) in high school teachers. Inform. Psicol. 91, 91–107. doi: 10.14635/iPSIC.2020.119.1
Valenzuela, J., and Galvis, Á. (2019). “Case of e-learning and b-learning at Tecnológico de Monterrey” in Direccionamiento estratégico de la modalidad híbrida en educación superior: Conceptos, métodos y casos para apoyar la toma de decisiones. ed. Á. Galvis (Bogota, Colombia: Ediciones Uniandes).
Villamar Sánchez, D., Juárez García, A., González Corzo, I. G., and Osnaya Moreno, M. (2019). Psychosocial factors and burnout syndrome in academics at a public university in Mexico. Propósitos Representaciones 7:111. doi: 10.20511/pyr2019.v7n3.360
World Health Organization. (2022). Mental health at work: policy brief. World Health Organization and International Labour Organization. https://iris.who.int/bitstream/handle/10665/362983/9789240057944-eng.pdf?sequence=1 (Accessed April 30, 2024).
Zilbovicius, M., Piqueira, J. R., and Sznelvar, L. (2020). Complexity engineering: new ideas for engineering design and engineering education. An. Acad. Bras. Cienc. 92, 1–15. doi: 10.1590/0001-3765202020181489
Živanović, M., Borjanić Bolić, E., and Vukčević Marković, M. (2021). Psychometric properties and structural validity of the Serbian version of the Copenhagen burnout inventory (CBIser). SAGE Open 11:215824402110488. doi: 10.1177/21582440211048889
Keywords: continuing education, anxiety, depression, stress, burnout, faculty development, higher education, educational innovation
Citation: Nava-Manzo JO, Beltran-Sanchez JA, González-Treviño IM and Dominguez A (2025) Continuing education program and its relationship with the mental health of engineering faculty members. Front. Educ. 9:1457642. doi: 10.3389/feduc.2024.1457642
Edited by:
Sarfraz Aslam, UNITAR International University, MalaysiaReviewed by:
Theingi Maung Maung, AIMST University, MalaysiaThanikachalam Vedhathiri, National Institute of Technical Teachers Training and Research Institute, Bhopal, India
Copyright © 2025 Nava-Manzo, Beltran-Sanchez, González-Treviño and Dominguez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Angeles Dominguez, YW5nZWxlcy5kb21pbmd1ZXpAdGVjLm14