Academics on Professional Helpers’ Education: How Do They Perceive the Work-Related Challenges?

Abstract

There is research on professional helper education and jobs working in a society with children and youth or supporting vulnerable people, but for academics, working in higher education, and preparing students for these work fields, it is not very common. This research focuses on academics from five European countries who prepare teachers, medical, healthcare, and clergy professionals. The aim is to design a map of pressures and challenges in their work. We hypothesized that academics in professional helper higher education (PHHE) perceive work-related challenges differently. Using explanatory research methodology, we considered higher education responsibilities: the working time and demands of academics. A total of 315 responses were used in our quantitative analyses from Romania, Slovakia, Hungary, Serbia, and Ukraine. The research questions were as follows: Are there differences between academics’ responsibilities and different PHHE scientific fields or work profiles? How do academics cope with work tasks and work time? How is a long hour-working academic’s profile? Statistical analyses using SPSS included cross-tabulation analysis, ANOVA and correlation tests, and factor analysis. We delimited two scientific fields and four academic working profiles: 1. academics in teacher education; 2. academics in medical/healthcare education; 3. leaders; 4. organizers; 5. classic lecturers; and 6. researchers. We designed five work demand patterns: controls and supports, global pressures, performance pressures, multi-role challenges, and lecturer roles. Drawing the map of pressures, we concluded that there are significant differences between those in teacher education in perceiving global (research, grant, and publish) responsibilities and performance pressures. At the same time, classic lecturers have significantly higher scores on perceiving performance challenges, and we deduced a positive and significant relation between multi-role challenges and overworking time. The design of the long hour-working profile of academics in PHHE is significantly associated with the medical and health scientific field. Men and academics from E.U. countries have significantly higher working time scores than females and workers outside E.U. Leaders have the highest working mean-time score comparing all the working fields and profiles. Our results for higher education teachers, researchers, policymakers, and institutional leaders can be useful in identifying work-related difficulties and maintaining a balanced distribution of work in the academic fields.

1. Introduction

Professional helpers (PHs) cultivate social, physical, psychological, intellectual, emotional, or spiritual well-being and health, and prevent or address the problems of individuals, groups, families, or communities (Bryan, 2009; Paar, 2022).

American Profession Guide (n.d.) (Figure 1) described related professions as teachers, special education professionals, social workers, social educators, medical assistants, doctors, nurses, midwives, counselors, clergy, foster parents, police, and emergency professionals with common traits and skills. They are described in the literature as workers in human services in society, working with clients, patients, vulnerable children, youth, disabled, ill, or old people, and engaging with their personality and their interpersonal relationships in their work (Čopková & Araňošová, 2020). Helping attitude scales were developed to measure the general care abilities and behaviors of professionals and non-professionals (Fischer & Turner, 1970; Shiarella et al., 2000; Nirmal & Malagi, 2019); many professions measure the different social, educational, psychological, health, and clergy helping service effectiveness and the characteristics, attitudes, satisfaction, and behaviors of the applicants (Greenley & Mechanic, 1976; Cook, 1984; Brouwer et al., 2010; Pisani et al., 2012). These professions have a low attractiveness, and supervising young workers is important in labor market integration (Pusztai & Csók, 2020); intellectual humility and integrity in the work of helping professionals is a basic trait that helps others (Paar, 2022). Emotional and interpersonal skills development of professional helpers (Burleson, 2003; Tharbe et al., 2020), respect for the values of clients (Corey & Corey, 2010), communication style, the traits of empathy and compassion (Reynolds & Scott, 1999; Milovanović & Marinković, 2014), the patience on behavior (Işık et al., 2022) and critical thinking (Gambrill & Gibbs, 2017) are frequently in the attention of researchers, but work-related problems and challenges of their professions are not very common.

The published works described the special helping work relations with beneficiaries, clients, and vulnerable people in different fields (Combs et al., 1971; Griffith & Bakanauskas, 1983; Bäckryd, 2016). The work-related stress issues of different professional’ fields were in focus, especially on organizational, psychology, and health research. The emotional exhaustion, depersonalization, and burnout of professionals are frequent social and health problems, and their work, families, and personal environment are affected by the supporting job (Shamai, 2005; Tabaj et al., 2015; Adams et al., 2017). Conceptualizing the work-related stress causes, work overload, time pressures, job control, work conditions, role-related challenges, work relations, career development, and organizational climate were identifiable (Cooper et al., 2001; Babatunde, 2013).

Data from qualitative and quantitative studies examined various jobs where employees are involved with their personalities, emotions, and interrelations in their work (Hilarski & Wodarski, 2001) and experimented with emotional exhaustion. Research usually highlights the selfless and prosocial traits of professional helpers but the “dark side” of the personality—Machiavellianism, narcissism, psychopathy—as a mediator in their job unsatisfaction is not a very common subject (Čopková & Araňošová, 2020). A comparison of the professional helper’s burnout among U.S. workers studied the differences depending on working fields. The quantitative research concluded that teachers, social workers, and clergy had similar burnout scores, worse than those of a counselor and better than those of police and emergency human resources (Adams et al., 2017). A quantitative analysis was conducted in the U.K. in 26 private and public organizations including 25. 352 workers, which compared 26 professional areas on the stress level, well-being, and job satisfaction scores of human resources. From the educational field, the authors included teachers, assistants, heads of teachers, and supervisors in school lunchtime, a total of 1820 responses. From medical and health professionals, the sample included some 1757 responses, and from the academic field, 1388 lecturers and researchers. Other professional helpers were included in the study sample: clergy, social services provided care, police, and prison officers. A total of 27.99% of the sample was from PH professions and 5.47% from academic fields. The study identified six ”at risk” occupations with a higher risk of emotional exhaustion: ambulance workers, teachers, social services, customer services—call centers, prison officers, and police employees, most of these included in the PH work field (Johnson et al., 2005).

In light of the identification of causes, the study makes the connection between job insecurity and the control level in some occupational fields: social services care, prison, and police employees, and another cause was the overload (the workload and time pressures) in social services, teachers and nurse occupations. Medical, health professionals, and teachers had the highest mean score on job dissatisfaction, higher than all the other professionals’ cumulated mean scores (Johnson et al., 2005).

The professional helper’s education develops students’ abilities, competencies, and traits at different levels of education, preparing them for a career of caring for and supporting others in society. This includes the theoretical knowledge and practical skills students should learn at different formal or nonformal trainings at middle or higher academic levels (BA, MA, and PhD studies), in private or public educational institutions, organizations, or directly from the workplaces of PH. A comparative quantitative study measured the helping attitude of students from India, including a total of 200 professional and non-professional females and men, and students’ altruism analysis measures were based on a helping attitude scale. The empirical analyses concluded that females had better helping attitudes than males, regardless of whether they were professionals (Hafsah, 2017). The overload of students and academics is a modern higher education topic. Kinman (2014) describes the changes that have occurred in the academic environment since the last century due to social and political changes and the phenomenon of expansion of higher education. The profession of academic lecturer or researcher was characterized by few stresses and challenges because of the autonomy and collegiality of the work. The job satisfaction of academics was higher than the average score of other professions (Johnson et al., 2005). The economic and educational neo-liberalism orientation and managerialism changed the higher education environment: the number of students increased, and the social and cultural diversification of students, and the digitalization of the institutions has also brought changes in the roles and tasks of actors (Kozma, 2008; Hrubos, 2011; Pusztai & Szabó, 2008). Academic works in managerialism conditions, the diversification of demands include grants and administration work, and their performance is measured on grants, international publications, and conference participation. The academic work was included in the “high risk” groups as the healthcare professionals. The overload of demands is connected with long hours working in academic fields. In the U.K., the authority, responsible for occupational health and safety work (Health and Safety Executive), defined work-related stress as “the adverse reaction people have to excessive pressures or other types of demand placed on them at work” and developed a self-reported questionnaire with 35 items for measure the workers well-being and performances. Academics reported working long hours and role unclarities (Kinman, 2014).

In this study, we focus on academics, preparing teachers, medical, healthcare, and clergy professionals. Our research question was as follows: Are there differences between academics’ responsibilities and different PHHE scientific fields or work profiles? How do academics cope with work tasks and work time? How is a long hour-working PHHE academic’s profile?

2. Study Methodology

We propose to design a map of the different pressures and challenges for different work profiles and scientific fields in PHHE. The research objectives were to examine academics’ workloads, identify work patterns, design a map of pressures and challenges for different work profiles and scientific fields, and identify time pressures with these. We use quantitative measurement to test the differences between academics in perceiving work-related challenges. We hypothesized that academics in PHHE differ in perceiving time and workload challenges.

2.1. Data Collection and Sample

The complex questionnaire named “Central and Eastern European Teachers in Higher Education” CEETHE 2023 overall contains 309 questions, and the objective of the survey was to explore the difficulties related to the work of academic human resources and their personal and professional well-being. In the questionnaire, we examined the professional and social background of the academics, their pedagogical methods, their achievement, workplace stress and resources, subjective health status, emotional well-being, leisure time activities, and the factors influencing these (burnout, workplace satisfaction and bullying, satisfaction with teaching, institutional environment, etc.), and their health behaviors (physical activity, nutrition, smoking, alcohol consumption, etc.) The questionnaire was developed based on qualitative research (7 focus group interviews with 41 academics) in Hungary, Slovakia, Ukraine, Romania, and Serbia (Kovács et al., 2024). It was translated into English, Serbian, Slovak, Ukrainian, and Romanian languages and was sent online in spring 2023 from the Centre for Higher Education Research and Development—Hungary. A total of 853 people filled out the questionnaire, and after data cleaning, the final number of respondents became 821 people. A total of 80% of the international academic sample came from three EU states (Romania, Slovakia, and Hungary), and 20% from non-EU countries (Serbia and Ukraine). Higher education institutions like the University of Novi Sad and the Technical College of Subotica in Serbia; János Selye University, the University of Prešov, and the University of Trnava in Slovakia; the Christian University of Partium in Romania; the State University of Oradea in Romania; Emanuel University from Oradea Romania; Sapientia Hungarian University of Transylvania and the Babes-Bolyai University (and their branches) in Romania; and the Ferenc Rákóczi II Transcarpathian Hungarian College and Uzhhorod National University in Ukraine participated in the quantitative examination of academics. Of the sample, 514 were Hungarian (61.8%), 115 Ukrainian (14.1%), 113 Romanian (13.8%), 40 Serbian (4.9%), and 36 Slovak (4.4%). A total of 27.9% specialized in medical/health sciences, 32.4% in humanities/pedagogy/languages/art sciences, 16.7% in social/economic sciences, and 23% in STEM/agriculture sciences. The Centre for Higher Education Research and Development from Hungary (CHERD–H) was responsible for the cooperation with these institutions, the data collection, and management.

For this study, we used 315 academic responses, and the selection criteria were as follows: they must teach at a higher education institution from one of these countries and their specialization must be in one of the professional helper higher education fields: medical/health science, pedagogy or theology science.

2.2. Socio-Demographic Characteristics, Academic Fields, and Working Profile of the Professional Helper Higher Education

Of the 315 respondents, 63% of the academics were women, 37% were men, the majority of the respondents (69%) were married, and 75% had children. About 48% reported having a relatively better material condition, 37% average, and 15% lower, compared to families in their environment. The average age was 46.7 (SD = 10.5). Of the respondents, 78% had a scientific degree, 64% were employed in the institutional academic role as a junior lecturer or in a lower position, and the average number of years working in higher education was 17.8 (SD = 11 years). On our professional helper sample (

Table 1. Professional helper in higher education fields and the working profiles of academics.

PHHE Academics	N
Teacher	112
Medical and health	194
Leaders	92
Organizers	66
Lecturers	88
Researchers	67

Sources: CEETHE 2023.

), 61% were specialized in medical and health sciences, 35.6% in pedagogy sciences, and 2.9% in theology sciences. In our quantitative examination teacher education field, we considered one independent subsample, academics from the medical and health fields, and we cumulated the medical and health subsample. The clergy subgroup was very small and for this reason, we could not include it in our statistical test as an independent professional helper higher education field.

In the initial processing of the data, the authors have delimited four working profiles of academics using cluster analysis: 1. leaders; 2. organizers; 3. lecturers; 4. researchers, in the function of their principal working actions (Berei et al., 2024). In this study, for our PHHE subsample, we use this delimitation (Table 1) to analyze the associations between academics, work demands, and time.

2.3. Measurements and Variables

The complex questionnaire included measures of working time and the measures of work demands based on Kinman et al. (2006). The variables of the demands of academics working in higher education were measured with 16 items: Communication at work is effective; Satisfied with your influence on decisions; Your responsibilities are clarified in your work; Institutional management is increasingly sensitive to the needs of academics; Increasing pressure to publish; Increasing pressure to conduct research; Increasing pressure to submit tenders/proposals; Situation of teachers is getting worse; Performance appraisal is a threat to professional independence; No promotion opportunities; Too much emphasis on performance appraisal; Enough time to prepare for lectures; Workload can be managed; Too much administrative work; Too many different areas to cover; and Not enough time for student’s problems and questions; (Cronbach’s α = 0.869). The measuring scale of responses was 5: 1—not at all, 2—probably not, 3—undecided, 4—probably, and 5—to a great extent (Kinman et al., 2006).

Kinman et al. (2006) highlighted the time variable in academic work. Following this, in our study, we used the time variable. The respondents were asked how many hours they generally work in a typical week at their full-time job. This variable was measured in a quantitative format, using these intervals: 1—36–40 h; 2—41–45 h; 3—46–50 h; 4—51–55 h; 5—56–60 h; and 6—60 and up h. Among the factors influencing working time, we included region (EU or not EU country), gender (men or female), and scientific specialization (teacher education and medical/health education).

Following an explanatory research methodology, we used the SPSS software for statistical tests in our quantitative analyses: factorial analyses to design the latent structure of the work responsibilities, ANOVA and Chi-square to test differences and compare means, and a correlation test between working hours and academic fields or profiles.

3. Results

3.1. Workloads and Work Patterns in PHHE: The Map of Work Challenges

The first level of the examination focused on the academic’ workloads in PHHE. We delimited working patterns, and after that, we examined their association with the working fields and profiles. The general list of the responsibilities of academics working in higher education was introduced into the analysis after Kinman et al. (2006) with the question: Please rate to what extent the following statements describe your work as an academic. Factorial analyses were performed on varimax rotation, resulting in five factors (

Table 2. The factor coefficients and the cumulation of work demands in five factors.

	Control and Support	Global Pressures	Performance Pressures	Multi-Role Challenges	Lecturer Role
Satisfied with your influence on decisions	0.800
Communication at work is effective	0.796
Your responsibilities are clarified in your work	0.730
Institutional management is increasingly sensitive to the needs of academics	0.591
Increasing pressure to publish		0.950
Increasing pressure toconduct research		0.828
Increasing pressure to submit tenders/proposals		0.674
Performance affects my professional independence.			0.870
Too much emphasis on performance appraisal			0.656
Too many different areas to cover				0.655
Too much administrative work				0.618
Enough time to prepare for lectures					0.899

Source: CEETHE 2023.

) from the demand variables (KMO = 0.823 and p = 0.000 with 65.23% explanations: 1—18.69%; 2—17.90%; 3—10.78%; 4—9. 09%; and 5—8.76%). The work demand variable was cumulated on different work patterns factors and we named them as follows: 1. control and support; 2. global pressures; 3. performance pressures; 4. multi-role challenges; 5. lecturer role.

Next, we analyzed the work pattern difference scores of the academics on different working profiles using ANOVA test (

Table 3. The map of pressures and challenges. Scientific fields, higher education work profiles, and work patterns with differences.

Work Patterns	Control and Support	Global Pressures	Performance Pressures	Multi Roles	Lecturer Role
Working fields and profile
Teacher Education	N.s.	p = 0.047 F = 3.96	p = 0.02 F = 5.48	-	N.s.
Medical and Health Education	N.s.	p = 0.017 F = 5.76	p = 0.006 F = 7.72	N.s.	N.s.
Leaders	p = 0.006 F = 7.54	N.s.	N.s.	N.s.	N.s.
Organizers	N.s.	-	N.s.	N.s.	N.s.
Lecturers	N.s.	-	p = 0.05 F = 3.87	N.s.	N.s.
Researchers	N.s.	N.s.	N.s.	-	-

N.s.: not significant. Source: CEETHE 2023.

). The dependent variables were the work demand patterns, and the independent variables were the PHHE scientific fields (teacher education and medical/health fields) and working profiles (leaders, organizers, lecturers, and researchers). Teacher education academics have significantly higher scores on global (m = 0.15, SD = 0.86, N = 109) and performance pressures (m = 0.16, SD = 0.86, N = 109). Significant different results were found on work challenges in the medical and health education fields: academics have significantly lower scores on global pressures (m = −0.107, SD = 1.03, N = 184) and in performance pressures (m = −0.117, SD = 0.95, N = 184). In total, we found significant differences between working profiles: leaders differ in perceiving control and support tasks, and classic lecturers in perceiving performance tasks. Leaders have a significantly higher score on perceiving control and support demands (m = 0.22, SD = 0.84, N = 89) and classic lecturers have significantly higher scores than others on perceiving performance challenges (m = 0.18. SD = 0.77, N = 82).

Summarizing the differences in professional helper higher education, the global and performance demands make differences between scientific fields, and for classic lecturers, performance pressures are significantly bigger than for other working profiles.

Following Kinman et al. (2006), working time is an important factor in academic challenges. We analyzed the correlation between working time and academic responsibilities (

Table 4. The associations between working hours and different work patterns.

Work Patterns/Work Hours	Control and Support	Global	Performance	Multi-Roles	Lecturer Role
	N.s.	N.s	N.s.	p = 0.000 r = 0.232	p = 0.002 r = −0.178

N.s.: not significant. Source: CEETHE 2023.

), and we found significant associations between these two variables concerning the correlation coefficients, r: multi-roles and the increase in working hours has a positive association (p = 0.000, r = 0.0232), and lecturer role and working hours has a negative association (p = 0.002, r = −0.178).

Summarizing the statistically significant results on professional helper higher education, covering different working areas and administrative demands increase academics’ working hours. If the working hours increase, they do have not enough time for preparation for the classic lecturer’s role.

3.2. The Work Time and the Profile of a Long Hour Worker in the Academic Field

This level of the examination focused on the working time of PHHE academics and its association with the different scientific fields and work profiles. Our research question was: How is a long hour-working PHHE academic’s profile? The respondents were asked how many hours they generally work in a typical week at their full-time job. Chi-square tests focus on the association of the working time of academics with demographic characteristics, academic fields, and working groups (Figure 2). A quarter of the PHHE sample (26.5%) are minimalists in terms of working hours (Mhw-40 h/week or less), and the majority of the academics tend to work longer (Lhw) than the standard of 40 h. According to our results, males tend to work more hours than females, and academics from EU countries tend to work longer than those outside the EU. Analyzing the association with scientific specializations, academics in the health and medical fields had significantly the highest frequencies in the LhW category. The Chi-squared statistical test revealed some significant differences between the observed and expected frequencies depending on the academic fields and we calculated the coefficient of chance (OR). Those with medical and health specializations tend to work longer hours than in the teacher field (Chi-square coefficient = 13.4; p = 0.000; OR = 0.4). The chance in teachers’ fields to be minimalists in terms of working hours is significantly 2.7 or higher than in the medical and health fields (Chi-square coefficient = 14.6; p = 0.000; OR = 2.7).

ANOVA tests (

Table 5. Significant differences between the mean scores of working hours in the function of gender, region, and scientific fields.

	The Working Time Mean Score of Academics (N = 315)
Male	3.18
Female	2.58
All respondents	2.8
Sig.	p = 0.001; F = 10.87
EU countries	2.93
Not	2.24
All respondents	2.79
Sig.	p = 0.002; F = 9.9
Medical and health educational field	3.07
Not	2.34
All respondents	2.79
Sig.	p = 0.000; F = 17.4

Source: CEETHE 2023.

) certify the significant differences between the mean scores of working hours in the function of gender, region, and scientific fields. Analyzing the effect of demographic variables, significant differences were found depending on gender (F = 10.87 and p = 0.001) and region (F = 9.9 and p = 0.002) of the academics. The working time mean score of academic males was significantly higher than that of females, and the mean score, depending on the country or region in which they work, was different and significant.

Depending on the working time, professional helper leaders have the highest score of working hours score and academics in teacher education the lowest score (

Table 6. Working time mean scores of academics in different fields and working profile (N = 315).

Academics in PHHE	Mean	N	SD
Leaders	3.17	92	1.81
Medical and health education	3.07	192	1.56
Organizers	2.83	66	1.47
Lecturers	2.55	88	1.42
Researchers	2.53	67	1.33
Teacher Education	2.36	112	1.54
The mean score of the PHHE respondents	0.23	313	0.44

Source: CEETHE 2023.

). Medical and health education professionals had a higher score than those in teacher education, and leaders had the highest working time score.

The academic profile of a long hour worker in PHHE was drawn in significant association with the medical and health scientific field. Men and academics from EU countries have significantly higher working time scores, and comparing all the mean scores of academics, leaders in PHHE had the highest mean score.

4. Discussions

The research aimed to design a map of the challenges of academics in professional helpers’ higher education. We followed Kinman et al. (2006), who compared the academic scores in the U.K. regarding working time and stressors at their workplace.

Johnson et al. (2005), in a big data comparison of job dissatisfaction of employees, highlighted the teachers’ and medical/health respondents’ high scores. They compared 26 professional areas and concluded that teachers are at risk of emotional exhaustion, like ambulance or social services workers, and prison or police employees. The causes were connected with the workload and time pressures in teacher, nurse, and social service occupations. Other causes were identified in social services care, prisons, and police occupations: the control level in these fields. In our study, we focused on teacher and medical/health fields and we designed five work demand patterns: controls and supports, global pressures, performance pressures, multi-role challenges, and lecturer roles. We hypothesized that academics perceive work-related pressures differently. Our study compared teachers and medical/health academics in higher education, focusing on their work responsibilities following Kinman et al. (2006). Teacher education academics have higher scores on global and performance pressures than those in medical/health fields. The differences were statistically significant. Academic lecturers scored highest on performance pressures and academic leaders on control/support pressures. Medical and health workers had significantly higher scores on working hours than other specialists, and ANOVA tests certify the differences between academics in teacher education and the other PHHE fields. The increasing challenges to publish, conduct research, and submit tenders or proposals is a significantly higher challenge for teachers of teachers than for others. Young (2006), in a study of academics in social sciences, stated that teaching in higher education is an underestimated task compared to research and administrative work. Global competition in higher education is a significant challenge for institutions and academics (De Wit, 2011). Constructing the map of challenges of academics in PHHE, we concluded a significantly higher score in performance pressures for teacher education academics. They admit too much emphasis on performance, and these challenges affect their professional independence.

Kinman (2014) designed the changes in society and the job conditions in academic fields, including academic works in “high-risk” groups. He analyzed U.K. academic human resources reports and concluded that the long working hours, the overload of demands, and role unclarities were characteristics. Our analyses of statistical correlation concluded the same results. Multi-roles and different working areas increase the academic working hours. At the same time, our results support a negative association between working hours and lecturer roles. Quantifying academics’ activity in teaching and learning, researching and performing administrative work, and their effective career development (Zacher et al., 2019) is high pressure for them. The multi-role challenges of teachers (Croll et al., 1994) affect covering different working areas and increase academic working hours. In our examination, teacher education leaders have the highest score in working hours. This can affect their well-being and the functionality of institutions also (Konu et al., 2010). In our study designing the profile of a long hour-working academic, the following aspects of the demographic and academic field were relevant: gender, region, and scientific fields. Based on our results, men, academics from EU countries, and medical/health specialists have the highest mean score in working hours.

5. Conclusions

In our cross-border and cross-professional quantitative study, the focus was on academics involved in professional helpers’ higher education, who develop abilities, skills, and competencies for future workers.

Through factor analyses, we designed five work demand patterns: controls and supports, global pressures, performance pressures, multi-role challenges, and lecturer roles. Drawing the map of challenges (Figure 3), our attention was focused on global and performance challenges in teacher higher education. Multi-role pressures correlate positively with the increase in hours worked for all professional helpers. Time pressures were characteristics in the medical and health fields, for men, and academics from E.U. countries (Romania, Hungary, and Slovakia).

Our results for higher education teachers, medical/health academics, researchers, policymakers, and institutional leaders can be useful in identifying work-related difficulties and maintaining a balanced distribution of work in the academic fields. To prevent long working hours, policymakers can adopt macro-interventions. The overload of demands and role unclarities in the educational and medical/health profession can be identified at the personal and institutional levels, and restructuring work responsibilities and performing individual and institutional work reflection or self-reports can prevent these excessive pressures of academics and the long-term effects of stress (work unsatisfaction, emotional exhaustion, and burnt out). At the same time, academic mentoring of junior workers can be a useful method for the evaluation of work–life balance, skills and the performance of academics.

The study’s limitation is that the academic sample used in the study is not representative of this country. We conclude especially for teachers and the medical/health education field. These examinations should be expanded for other academic specializations.