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RESULTS
Germplasm accessions had variability on each characters. Table 2 shows the minimum, maximum, mean, and coefficient of variation of each characters. There were several characters that had high coefficient of variation, such as empty grain and adulterant, chalky green grain, damaged yellow grain, red grain, broken rice, small broken rice, chalky rice, damaged yellow rice, and softness deviation.
International Journal of Advance Tropical Food
PCA was carried out on the 24 physicochemical characters of unhusked and milled rice of
46 rice germplasms from ICRR and ICABGRRD and resulted in 25 new variables (principal components) that were independent from each other and could explain all the variation within the data. From those 25 principal components, 8 components were chosen that had eigenvalue more than 1. With those 8 components, as much as 84.676% variation could be explained
(Table 3). The first principal component (PC1) had eigenvalue of 4.512 with the percentage of variance was 18.049%. PC8 had eigenvalue of 1.074 and the percentage of variance of
Graphical representation of variance percentage can be seen on the Figure 1. It can be shown that the first three of principal components have higher percentageof variance than the remaining components. On the other hand, PC4 and PC5 both have high enough variance to be included as indicators to determine important physicochemical characteristics.
Table 2. The minimum, maximum, mean, and coefficient of variation of physicochemical characters of the 46 rice accessions
Characters
Minimum value
Maximum value
Mean
Coefficient of variation (%)
Unhusked rice water content (%)
Empty grain and adulterants (%)
Grain density (g/l)
1000 grains weight (g)
Calky green grain (%)
Damaged yellow grain (%)
Red grain (%)
Milled rice water content (%)
Brown rice yield (%)
Milled rice yield (%)
Head rice (%)
Broken rice (%)
Small broken rice (%)
Calky rice (%
Damaged yellow rice (%)
Length (mm)
Width (mm)
L/W ratio
Whiteness (%)
Translucency (%)
Milling degree (%)
Amylose content (%)
Gelatinization temperature*
Gel consistency (mm)
Softness deviation (%)
*) 1: gelatinization temperature 55-69°C, 2: gelatinization temperature 70-74°C, 3: gelatinization temperature > 74°C
International Journal of Advance Tropical Food
Principal component matrix
Rice germplasms were analyzed using PCA on their 24 physicochemical characters to obtain loading value on each characters. Those value could be used as indicators to choose important characters on each principal components. The value of each accession on each principal components, finally, could be used to show which accessions that have potential to be used in breeding program. Further analysis were using only 5 principle components since those 5 components were enough to conclude the correlation between several important quality characters. The PCA value of each characters is shown on the Table 4.
Tabel 3. Eigenvalue, % of variance, % of cumulative variance of physicochemical characters of the 46 rice accessions
Components
Eigenvalue
% of Variance
% of Cumulative Variance
Explanation: PC1 was the first principal component, PC2 was the second principal component, etc. Principal components were new reduced variables that were not correlated between each other in order to help to take a conclusion.
International Journal of Advance Tropical Food
Figure 1. Percentage of variance scree plot of physicochemical characters of the 46 rice accessions.
Tabel 4. Loading value of each characteristics
Karakter
Components
Unhusked rice water content
Empty grain and adulterants
Grain density
1000 grains weight
Calky green grain
Damaged yellow grain
Red grain
Milled rice water content
Brown rice yield
Milled rice yield
Head rice
Broken rice
Small broken rice
Calky rice
Damaged yellow rice
Length
Width
L/W ratio
Whiteness
Translucency
Milling degree
Amylose content
Gelatinization temperature
Gel consistency
Softness deviation
Information: |loading| ≥ 0.4 was bolden. Chosen parameter was boldened and underlined. Minus
(-) sign indicates negative correlation.
International Journal of Advance Tropical Food
PC1 shows important positive correlation
(loading>0.4) on grain density (DG), width (W), whiteness (WD), milling degree (MD), and amylose content (AC) and negative correlation (loading<-0.4) on milled rice
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] |
W3003650968
|
1
|
ness deviation
Information: |loading| ≥ 0.4 was bolden. Chosen parameter was boldened and underlined. Minus
(-) sign indicates negative correlation.
International Journal of Advance Tropical Food
PC1 shows important positive correlation
(loading>0.4) on grain density (DG), width (W), whiteness (WD), milling degree (MD), and amylose content (AC) and negative correlation (loading<-0.4) on milled rice yield (MRY), damaged yellow rice (DYRP), length (L), L/W ratio (LWR), gel consistency (GC), and softness deviation (SD). Thus, PC1 can be used to select accessions that have round grain, high amylose content with hard texture, and white colored. On the other hand, PC1 is negatively correlated with milled rice yield which is undesireable. Graphical representation of
PC1 is shown on Figure 2.
Figure 2. Diagram of the principal component matrix of physicochemical characters on PC1.
PC2 shows positive correlation
(loading>0.4) on weight of 1000 grains
(W1000), calky green grain (CGG), damaged yellow grain (DYG), broken rice percentage (BRP), small broken rice
(SBRP), calky rice (CRP), whiteness
(WD), milling degree
(MD), gel consistency (GC), and softness deviation
(SD). On the other hand, it is negatively correlated (loading<-0.4) with head rice percentage (HRP) and amylose content
(AC).
This indicates bad quality characteristics with low head rice, but high broken grain. Nevertheless, PC2 still can be utilized to select which accessions having low amylose content
(sticky rice). Graphical representation of the PC is shown on Figure .
Figure 3. Diagram of the principal component matrix of physicochemical characters on PC2.
PC3 indicates important positive correlation (loading>0.4) on grain density (GD), weight of
1000 grains (W1000), brown rice yield (BRY), milled rice yield (MRY), translucency (T), and amylose content (AC). On the other hand, it negatively correlates (loading<0.4) with softness deviation (SD). This component has good correlation with high yield character with high density and weight. It also indicates low deviation on softness. That means this
WCG
EG
GD
CGG
DYG
RG
WCR
BRY
MRY
HRP
BRP
SBRP
CRP
DYRP
L
W
LWR
WD
T
MD
AC
GT
GC
SD
Loading value
Characters
WCG
EG
GD
CGG
DYG
RG
WCR
BRY
MRY
HRP
BRP
SBRP
CRP
DYRP
L
W
LWR
WD
T
MD
AC
GT
GC
SD
Loading value
Characters
International Journal of Advance Tropical Food
0190101-16 component can be used to select accession with high yield and likeable texture. PC3’s graph is shown on the Figure
Figure 4.
Figure 4. Diagram of the principal component matrix of physicochemical characters on PC3.
PC4 shows important positive correlation (loading>0.5) on calky green grain (CGG), red grain (RG), calky rice
(CRP), length (L), length/width ratio
(LWR), and gelatinization temperature
(GT). It was negatively correlated
(loading<-0.4) with width
(W), transluecency (T), and gel consistency
(GC). This component is suitable as indicator for long and slender grain. On the other hand, it has several undesirable characteristics, such as higher percentage of green, red, and calky grain. It also has more opaque appearance. Graph of the PC4 is shown on the Figure 5.
Figure 5. Diagram of the principal component matrix of physicochemical characters on PC4.
WCG
EG
GD
CGG
DYG
RG
WCR
BRY
MRY
HRP
BRP
SBRP
CRP
DYRP
L
W
LWR
WD
T
MD
AC
GT
GC
SD
Loading value
Characters
WCG
EG
GD
CGG
DYG
RG
WCR
BRY
MRY
HRP
BRP
SBRP
CRP
DYRP
L
W
LWR
WD
T
MD
AC
GT
GC
SD
Loading value
Characters
WCG
EG
GD
CGG
D
|
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] |
W3003650968
|
2
|
LWR
WD
T
MD
AC
GT
GC
SD
Loading value
Characters
WCG
EG
GD
CGG
DYG
RG
WCR
BRY
MRY
HRP
BRP
SBRP
CRP
DYRP
L
W
LWR
WD
T
MD
AC
GT
GC
SD
Loading value
Characters
WCG
EG
GD
CGG
DYG
RG
WCR
BRY
MRY
HRP
BRP
SBRP
CRP
DYRP
L
W
LWR
WD
T
MD
AC
GT
GC
SD
Loading value
Characters
International Journal of Advance Tropical Food
PC5 positively correlates (loading>0.4) with brown rice yield (BRY) and head rice percentage (HRP); and negatively correlates (loading<-0.4) with red grain
(RG) and broken rice percentage (BRP).
This component is suitable to be an indicator for accessions that are potential for developing premium rice.
Graphical representation of PC5 is shown on Figure 6.
Figure 6. Diagram of the principal component matrix of physicochemical characters on PC5.
Table 5. Loading score of each accessions
Aksesi
Komponen
WCG
EG
GD
CGG
DYG
RG
WCR
BRY
MRY
HRP
BRP
SBRP
CRP
DYRP
L
W
LWR
WD
T
MD
AC
GT
GC
SD
Loading value
Characters
International Journal of Advance Tropical Food
Aksesi
Komponen
Information: Loading > 1 was boldened. Accessions that have loading>1 on both PC3 and
PC5 were boldened and shaded.
Accession selection according to the components’ score
Table 5 shows each accession’s score on each principal components. On PC1, the loading is from -3.978 (accession 10480) to 7.177 (accession 10500). On PC2, the loading is from 4.644 (accession 10497) to 6.163 (accession 10489). On PC3, the loading is from -7.721
(accession 10489) to 3.445 (accession 10515). On PC4, the loading is from -3.781 (accession
10599) to 4.640 (accession 10510). On PC5, the loading is from -3.655 (accession 10510) to
1.929 (accession 10527). The loading ranging from negative to positive on all five principal components means the characteristics of the accession have high degree of variation.
According to Gour et al. (2017), the value of cutoff used should be 1. It means, accessions to be considered will have loading score >1. Accessions that have the score >1 on PC1 were correlated with roundness shape and high amylose content with low milling yield (13 accessions); on PC2, they were correlated with low amylose content, ie sticky rice (9 accessions); on PC3, they were correlated with high yield rice and likeable texture (16 accessions); on PC4, they were correlated with long and slender grain (10 accessions); and finally, on PC5, they were correlated with premium rice (11 accessions). The grouping is shown on Table 6.
Table 6. Chosen accession having loading >1 on each components
International Journal of Advance Tropical Food
Information: Accessions that have both loading >1 on PC3 and PC5 were boldened
Suitable accessions for round-shaped rice development are 10500, 10592, 10477, 10496,
10515, 10577, 10482, 10572, 10506, 10548, 10591, 10474, dan 10550. For developing low amylose content or sticky rice, accession 10489, 10474, 10535, 10592, 10496, 10515, 10476,
10572, dan 10560 are
|
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W3003650968
|
3
|
548, 10591, 10474, dan 10550. For developing low amylose content or sticky rice, accession 10489, 10474, 10535, 10592, 10496, 10515, 10476,
10572, dan 10560 are considered. For long and slender grain, accession 10510, 10470, 10474,
10513, 10592, 10515, 10496, 10491, 10471, dan 10499 can be used as parents in the breeding program.
PC3 and PC5 can be used in tandem as indicator for accession with good milling quality, yield, and well liked by consumers. There are 7 potential accessions (Table 7) as genetic materials for premium rice development, i.e. 10479 (Umbul-umbul), 10486 (Babad Cianjur),
10491 (Marus), 10499 (619), 10515 (Siregi), 10551 (Logawa), dan 10562 (Umbul-umbul).
Table 7. Potential accessions having loading > 1 on both PC3 and PC5
Nomor Aksesi
Nama
Umbul-umbul
Babad Cianjur
Marus
Siregi
Logawa
Umbul-umbul
The grouping of accessions
The grouping of accessions from PCA result using HCPC showed that the accessions could be grouped into 4 according to their physicochemical characters. Group
I included 11 accessions, group II was 3 accessions, group III was 8 accessions, and group IV had 24 accessions.
By reviewing their score on each components, it was shown that group I had mainly positive score on PC1 and PC3, group II had negative score on PC1 and PC3, group III had negative score on
PC2, PC3, and PC5, finally, group
IV has positive score on PC3 and
PC5. It was not surprising that 6 of
7 potential accessions for premium rice were members of group IV
(Figure 7).
International Journal of Advance Tropical Food
Figure 7. Dendogram of accessions’ group with score on each component: a) dendogram
Dendogram pengelompokan aksesi serta nilai pada masing-masing komponen: a) dendogram resulted from HCPC analysis. Number I to IV indicates group’s number.
Potential accessions are shaded in grey. b) accessions’ loading score on each components
## DISCUSSION
(619), 10515 (Siregi), 10551 (Logawa), dan 10562 (Umbul-umbul). The grouping of accessions resulted in 4 main group with the group IV is dominated by high yield and premium quality characters.
|
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W3003650968
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0
|
RESULTS
Conceptualizing Stress and Work Overload
Stress is a natural part of life and has an impact on people's social, psychological, and physical well- being. The way people handle stress has a significant influence on how it affects their general well-being. There has been a lot of research on stress management in the teaching profession. Many studies have been done to determine the sources of stress for educators. For example, a study by
Shaheen and Mahmood (2016) and Skaalvik and
Skaalvik (2016) reveals a number of stressors, such as work-related stress, depression, success-related feelings, a lack of emotional support, workload, interpersonal relationships, and the workplace.
According to Cooper and Dewe (2004) and Dlamini
& Adams (2014), stress factors can have physiological as well as psychological effects, which can result in health problems, anxiety, anger, depression, and feelings of inadequacy. Stress among teachers has serious effects on both teachers and students. Reduced job commitment, job satisfaction, and teaching quality have all been associated with high levels of stress (Caprara et al.,
2006; Klassen and Chiu, 2010). Teachers under stress may also exhibit less effective classroom management and teaching strategies, which can have a detrimental impact on students' learning outcomes. Teachers use a range of coping mechanisms to handle stress. These tactics fall into two general categories: direct action and palliative methods.
Exercise, smoking, and alcohol consumption are examples of palliative techniques that are intended to lessen emotional distress
(Howard & Johnson, 2004). Proactive approaches to managing stressors, such as talking to mental health specialists or colleagues, are referred to as direct action techniques. Teachers frequently rely on administrators and other staff members for social support, which is a critical component of stress management (Howard & Johnson, 2004). Teachers with positive social networks have been found to have better mental and physical health (Betoret,
2006). Furthermore, teachers' well-being is significantly impacted by the support of their spouses and romantic partners (Birditt & Antonucci,
2007). The unique stressors that preschool teachers encounter stem from their role as careers for young students. Teachers are required by the Kurikulum
Standard
Pra
Sekolah
(Standard
Preschool
Curriculum) to get their students ready for national exams. This creates a number of issues, including crammed classrooms and a lack of support from parents and administrators.
Preschool teachers' job satisfaction and commitment are negatively impacted by stress, which may result in attrition and lower the standard of instruction for young students. Stress among teachers is a common and alarming problem that is fueled by a number of factors. Effective coping mechanisms and social support networks are essential, given the detrimental effects of stress on educators and learners. By comprehending the difficulties educators encounter and recognizing effective coping strategies, the teaching profession can strive to establish a nurturing and enduring work atmosphere. To create more resilient coping mechanisms and safeguard the welfare of both educators and learners, more research is necessary.
This will ultimately help to create a supportive and productive learning environment.
On the other hand, work overload describes a situation in which a person is overburdened with tasks, responsibilities, or work that exceeds their ability to manage or finish. This may result in higher levels of stress, lower output, and detrimental effects on well-being and job satisfaction. According to Osaat and Ekechukwu
(2017), workloads are the duties or all the tasks carried out by workers in the course of their activities in their workplace. Relating to the lecturers, workloads are professional and non- professional duties carried out by the lecturers in the course of their activities in the instruction of students. Lecturers are the greatest assets as well as major stakeholders in the university industry. Osaat and Ekechukwu (2017) also note that the main work of lecturers is to teach and bring up the young generation of students to acquire skills and knowledge for growth and development. Teaching is a difficult task and demands serious commitment
241 to be effective. Teaching entails conducting thorough research, preparing the material adequately, and showing up to class on time to put it into practice. Teaching includes assessing students through quizzes, assignments, and examinations. In particular, teaching includes marking examination scripts and producing results.
In addition to the responsibilities listed above, lecturers handle a wide range of other tasks, some of which are difficult and occasionally conflict with their main responsibilities as academic staff members and teachers. Lecturers may experience work overload due to a variety of reasons, including grading and assessment, student supervision, resource constraints, long teaching days, research and publication obligations, and administrative duties. These lecturers' primary responsibility is teaching, which exposes them to a variety of tasks almost simultaneously. The National Universities
Commission
|
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W4394796190
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1
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In addition to the responsibilities listed above, lecturers handle a wide range of other tasks, some of which are difficult and occasionally conflict with their main responsibilities as academic staff members and teachers. Lecturers may experience work overload due to a variety of reasons, including grading and assessment, student supervision, resource constraints, long teaching days, research and publication obligations, and administrative duties. These lecturers' primary responsibility is teaching, which exposes them to a variety of tasks almost simultaneously. The National Universities
Commission
(NUC)
Benchmark
Minimum
Academic Standard (BMAS) recommendation of students to lecturers is not followed by many
Nigerian universities, which adds to the burden of teaching a large number of students in each class
(NUC, 2014). For various student categories
(regular undergraduate, part-time undergraduate, sandwich, postgraduate, pre-degree, open and distance education, etc.), they instruct up to four to five courses or more. As a result, they work continuously throughout the year with little to no vacation.
According to the American Psychological
Association (2002), one of the things that causes stress among workers is overwork (excess workload). However, the recommendations made by lecturers to students regarding the NUC
(National Universities Commission) are tailored according to the unique characteristics of each faculty. For instance, NUC (2014) shows that for the faculties of Administration, Arts, Education,
Law, and Social Sciences, the Lecturer-Student
Ratio (LSR) is 1:30; for Science, the LSR is 1:20; for Technology, Environmental Design, and
Management, and Agricultural Science, the LSR is
1:15. For Basic Medical Sciences, Clinical
Sciences, Dentistry, and Pharmacy, the LSR is 1:10.
Brief Historical Background of Obafemi
Awolowo University
Obafemi Awolowo University, located in IleIfe, Nigeria, is a renowned institution of higher education. It was established in 1962 as the
University of Ife by the regional government of
Western Nigeria, under the leadership of Chief
Samuel Ladoke Akintola, the then Premier of the
Western Region of Nigeria.
In 1987, the university was renamed Obafemi
Awolowo University in honor of Chief Obafemi
Awolowo, a prominent Nigerian nationalist, lawyer, and statesman who played a significant role in the country's fight for independence. Currently,
Obafemi Awolowo University houses 13 faculties:
1. Faculty of Administration
2. Faculty of Agriculture
3. Faculty of Arts
4. Faculty of Basic Medical Sciences
5. Faculty of Clinical Sciences
6. Faculty of Dentistry
7. Faculty of Education
8. Faculty of
Environmental
Design and
Management
9. Faculty of Law
10. Faculty of Pharmacy
11. Faculty of Science
12. Faculty of Social Sciences
13. Faculty of Technology
These faculties are then divided into various departments, offering a wide range of academic programs. Each department specializes in specific areas of study. In summary, Obafemi Awolowo
University provides a comprehensive educational experience.
The university has remained a well-known center of excellence over the years, according to information retrieved from the university website and signed by Omosule, registrar and secretary to the council (2023). Known as "the most beautiful" campus south of Sub-Saharan Africa, the university has produced National Merit Award winners and a
Nobel Laureate among its faculty. It has also led the way in the development of cutting-edge technologies that can help address some of the current problems facing society.
Academic Strengths of Obafemi Awolowo
University
Based on the report of the Federal Ministry of
Education (2020) to Obafemi Awolowo University,
Ile-Ife. The attached table shows the academic staff distribution among the 13 faculties in the University as of the 2018/2019 academic session.
Table 1. Academic Staff Distribution by Faculties 2018/2019 Academic Session
Faculty
Number of Academic Staff
Student
Enrolment
Teacher/ student ratio
Nuc
Ratio
No On
Ground
Nuc Benchm Ark
Shortfall
Excess
Administration
Agriculture
Arts
Basic Medical
Sciences
Clinical Sciences
Dentistry
Education
Environmental
Design and
Management
Law
Pharmacy
Science
Social Sciences
Technology
Total
Source: DAP Office, OAU
The above table illustrates the extremely deplorable state of affairs in the university, with only five (5) of the thirteen faculties having reached the required lecturer-to-student ratio and, consequently, meeting NUC benchmarks in their respective fields. There are
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W4394796190
|
2
|
ure
Arts
Basic Medical
Sciences
Clinical Sciences
Dentistry
Education
Environmental
Design and
Management
Law
Pharmacy
Science
Social Sciences
Technology
Total
Source: DAP Office, OAU
The above table illustrates the extremely deplorable state of affairs in the university, with only five (5) of the thirteen faculties having reached the required lecturer-to-student ratio and, consequently, meeting NUC benchmarks in their respective fields. There are significant gaps in the remaining eight faculties, with the Faculty of
Technology having the largest deficit at 154 academic staff members. Compared to the 370 shortages noted in the 2017/2018 session, there are now 435 total shortfalls for the 13 faculties.
However, the Registrar and Secretary to the
Council, Omosule (2023), states in the job advertisement for the university registrar position that the university's initial enrollment of 244 students has increased to 34,036 as of the
2021/2022 academic year. Additionally, the university, which began operations with 94 employees, has expanded to employ 4,000 people, of whom 2,635 are non-teaching staff and 1,365 are academic staff. The data above is consistent with the finding of Osaat and Ekechukwu (2017), which reveals that academic staff members in most universities in Nigeria are observed to be overworked because, regrettably, the number of academic staff does not keep up with the growing number of students enrolling in universities. In a nutshell, the abundance of data gathered overwhelmingly indicates that there is a significant shortage of staff members at Obafemi Awolowo
University, Ile-Ife, Nigeria. This inadequacy of lecturers has the potential to impose excessive workloads on the existing lecturers, subsequently having a detrimental impact on their performance and job satisfaction.
Work Overload: Impact on Lecturers' Stress
Levels, Job Satisfaction, and Overall Well-Being
Work overload can have a significant impact on lecturers' stress levels, job satisfaction, and overall well-being. When lecturers have an excessive workload, they often experience higher levels of stress. The pressure to complete numerous tasks within tight deadlines can lead to feelings of overwhelm and anxiety. Chronic stress can have detrimental effects on mental and physical health, leading to burnout, exhaustion, and decreased productivity (Dalbudak & Saricam, 2020).
Work overload can diminish job satisfaction among lecturers. When they constantly feel overwhelmed by their workload, they may find less enjoyment and fulfillment in their work. Lecturers may struggle to maintain enthusiasm for teaching,
243 conducting research, and engaging with students and colleagues, as the excessive demands on their time and energy can make their jobs feel burdensome (Olajide & Adewale, 2019; Oghuvbu,
Work overload can significantly impact the overall well-being of lecturers. The sustained pressure and demands can lead to a lack of work- life balance, causing strain on personal relationships, decreased leisure time, and neglect of self-care. Lecturers may experience physical symptoms such as headaches, fatigue, and sleep disorders. Moreover, work overload can negatively impact their psychological well-being, leading to feelings of overwhelm, frustration, and a compromised sense of purpose. Work overload brings about unnecessary stress, fatigue, and headaches, which has led to the demise of many lecturers (Bamigbola, 2023).
Paradoxically, excessive workload can impair lecturers' productivity and the quality of their work.
When lecturers are overloaded, they may have to rush through tasks, leading to subpar performance.
The lack of time for adequate preparation, grading, and feedback can compromise the quality of teaching and supervision, affecting the student's learning experience in the long run. If work overload persists over time, lecturers may find it challenging to engage in professional development activities, conduct research, or publish papers. A lack of time and energy may hinder their ability to pursue promotions, grants, and other career advancements, potentially affecting their career progression in academia (Nasir & Haron, 2018;
Alam & Mohd-Nor, 2017).
It should be noted that mitigating work overload is crucial to supporting lecturers' well- being, job satisfaction, and overall effectiveness.
Strategies such as workload distribution, realistic expectations, supportive work environments, adequate resources, and time management training can help alleviate the burden and create a healthier and more productive work environment for lecturers.
Empirical Studies
Previous research has shown that the excessive bureaucratic tasks that European university professors must add to their teaching and research responsibilities frequently have an impact on their psychosocial well-being, which includes their coping mechanisms, internal states (mood), and psychophysical well-being.
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W4394796190
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3
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satisfaction, and overall effectiveness.
Strategies such as workload distribution, realistic expectations, supportive work environments, adequate resources, and time management training can help alleviate the burden and create a healthier and more productive work environment for lecturers.
Empirical Studies
Previous research has shown that the excessive bureaucratic tasks that European university professors must add to their teaching and research responsibilities frequently have an impact on their psychosocial well-being, which includes their coping mechanisms, internal states (mood), and psychophysical well-being. According to Tight
(2010), the perception among academics today that their workloads are getting heavier may be directly related to the amount of time they spend on administration; nonetheless, the rising quantity and percentage of academic time that is spent on administrative tasks can have an impact on university lecturers' well-being. Put differently, the teacher's commitment to completing all of his responsibilities to the best of his ability, almost to the point of alienation, makes the workload a risk factor for stress (Pace, D'Urso, Zappulla, & Pace,
2019). Their research concludes that university professors' negative perception of their work-related well-being is predisposed by their workload, which is associated with bureaucratic university procedures. Furthermore, according to several studies (Cladellas & Castello, 2011; Gmelch et al.
1986; Navarro et al. 2010; Passanisian & Pace,
2017; Seiler & Pearson, 1985), this may pose a risk to the university as a whole. Hobson and Beach's
(2000) study highlighted the risk factors associated with psychological health, including excessive workloads and frustrating work-related excesses.
On the other hand, workload can decrease if one works in a non-compulsive manner and does not take on excessive tasks (Fritz & Sonnentag, 2006;
Meijman & Mulder, 1998).
Conversely, other research has indicated that university lecturers face occupational constriction due to inadequate funding and resources, work overload, or poor management practices relative to requirements, which may put them under stress
(Ford & Jin, 2015; McCormick & Barnett, 2011).
According to the Health and Safety Executive
(2018) in Great Britain, stress, anxiety, and depression are linked to 39% of work-related complaints. It also stated that the age group of 45–
54 has the highest rate of illness caused by occupational stress. According to the study, the third-most stressful, depressing, and anxious work environment is the "education" sector. Furthermore, it appears that mental health is a significant risk factor for occupational stress among lecturers in higher education, according to the study by Sun,
Wu, and Wang (2011) on occupational stress and its related factors among Chinese university lecturers.
Specifically, mental health, role overload, role insufficiency, social support, monthly income, role
244 limitations owing to physical problems, research funding, and self-rated disease were the factors significantly associated with a higher level of occupational stress (Lo Cascio, Guzzo, Pace, &
Pace, 2013).
Additionally, the study by Bauer et al. (2007) on working conditions: adverse events and mental health problems in a sample of 949 German teachers highlighted that many participants reported significant mental health problems regarding stress, concentration skills, sleep issues, decision-making ability, and feelings of depression and sadness. In a recent contribution, it was discovered (Hogan,
Hogan, & Hodgins, 2016) that workaholism is more common in academia in Ireland than in other professions and that it negatively affects both psychological well-being and work-related outcomes. According to research by Kinman and
Wray (2013), there is a tendency for stress to increase with time, and 75% of lecturers believe their job is stressful. Hobson and Beach (2000) looked at the relationship between psychological health, work-related stress, and excessive workloads.
The study conducted by Arbabisarjou, Ajdari,
Omeidi, and Jalalinejad (2013) examined the connection between hospital nurses' performance and job stress in Iran. The descriptive correlation research method was employed. Of all the nurses,
491 hospital nurses were randomly chosen to participate in the study. One hundred questionnaire copies were examined. Regression analysis and
Pearson coefficient correlation were used to analyze the data. The study's conclusion demonstrates that there is a negative relationship between performance and job stress.
A study by Warraich, Ahmed, Ahmend, and
Khoso (2004) examined the impact of stress on workers' job performance in Karachi, Pakistan's private universities. For the study
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W4394796190
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4
| " the nurses,\n491 hospital nurses were randomly chosen to participate in the study. One hundred que(...TRUNCATED)
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|
W4394796190
|
5
| "ugbe, and Onwuka (2012) as a requirement for enhancing the performance of female lecturers in Niger(...TRUNCATED)
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|
W4394796190
|
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