Job Performance of Academicians in Public University

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INTERNATIONAL ISLAMIC ECONOMIC SYSTEM CONFERENCE (I-iECONS 2021)

Job Performance of Academicians in Public University:

Does Health Status Matter?

Zurina Kefeli

Faculty of Economics and Muamalat, Universiti Sains Islam Malaysia (USIM), Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan Malaysia

Tel: +606 798 6401 E-mail: [email protected]

Nursilah Ahmad

Tel: +606 798 6312 E-mail: nursilah@usim.edu.my

Farhana Sabri

Faculty of Leadership and Management, Universiti Sains Islam Malaysia (USIM), Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan Malaysia

Tel: +606 798 8796 E-mail: farhanasabri@usim.edu.my

Fuadah Johari

Tel: +606 798 6412 E-mail: fuadah@usim.edu.my

Shamzaeffa Samsudin

Economic and Financial Policy Institute (ECOFI), School of Economics, Fiance and Banking, Universiti Utara Malaysia

Cheah Yong Kang

Economic and Financial Policy Institute (ECOFI), School of Economics, Fiance and Banking, Universiti Utara Malaysia

Abstract

Academic staff play a vital role in determining the success of the vision and mission of a university. They are expected to be competent and show effective performance in achieving their Key Performance Indicators (KPI). A high-quality academic staff is the source of a successful education system and having a good health status is vital for the academicians to produce high quality output. Therefore, it is important to study whether health status (physical and mental) is among the factors affecting the job performance of academicians in public universities. A total of 233 academic staff from Universiti Sains Islam Malaysia and Universiti Utara Malaysia were involved in the study. Data were collected using the non-probability convenient sampling technique through an online survey between March and April 2021. Data were analysed using logistic regression and the results show that the job performance of academicians was significantly associated with ethnicity, health status, presenteeism, and workplace health. An inverse relationship was observed for presenteeism and workplace health due to the COVID-19 pandemic.

Based on the findings, it is suggested that universities should provide appropriate facilities and a conducive atmosphere for their

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academic staff to increase their productivity and job performance in the future.

Keywords: Health status, mental health, job performance, public university, Key Performance Indicators (KPI)

1. Introduction

World Health Organization (WHO) defined health as a state of complete physical, mental and social well-being, and not merely the absence of disease. Good health is crucial in handling stress and living a longer, more active life.

Mental and physical health are probably the two most frequently discussed types of health. Researchers have linked spiritual, emotional, and financial health to lower stress levels and improved mental and physical well-being. Mental health is as important as physical health as part of a full active life. Furthermore, regular exercise, balanced nutrition, and adequate rest contribute to good physical well-being, and eventually improve a person’s overall quality of life.

A university’s most important asset is its academic manpower (Mohamed Ghouse Nasuruddin, 2018). They play a vital role in determining the success of the vision and mission of a university. In a university, the roles and responsibilities of academicians involve not only teaching and learning, but also research and publication, securing grants, attending seminars and conferences, consultation, training, innovation and commercialisation, community services as well as administration tasks. Many of these responsibilities such as research and publication output were set as Key Performance Indicators (KPI) by the universities. Academicians are expected to be competent and show effective performance in achieving their KPI. A study by Henry et al. (2020) found that personal, environmental, and behavioural factors were influencing research productivity among staff of University Teknologi MARA (UiTM). Furthermore, emotional intelligence intrapersonal skills, interpersonal skills, adaptability and general mood are positively related to job performance among academicians in private higher education institution in Malaysia (Shyue, Mohammad Falahat & Yin, 2020).

A high-quality academic staff is the source of successful education system (Bentley et al., 2013). Having a good health status is vital for the academicians to produce high quality output. Therefore, it is important to study whether health status (physical and mental) is among the factors affecting job performance of academicians in public universities.

2. Literature review

Many studies tend to focus on job motivation and job satisfaction of academic staff. Limited studies have looked at the effects of health status on job performance of academicians in Malaysia. Universities should have adequate knowledge for preparing and developing appropriate atmosphere among academic staff and realizing their tendencies and needs from the workplace. Bentley et al. (2013) suggested that a healthy climate at university increases not only the job satisfaction among academicians, but it also increases the academicians’ performance.

Generally, the productivity loss due to health conditions has become a major concern for companies and organisations. Leroux, Rizzo & Sickles (2003) acknowledged the importance of both physical and mental health on labor productivity. They found self-reporting bias existed which may result to a bias in estimating labor productivity costs.

Mental illness is found to be pervasive and costly. Thus, mental health has long been regarded as an important measure of productivity at workplace. Mental health and productivity at work have been often associated with many factors including long working hours, underemployments, stress at workplace, relationships with supervisors and/or fellow employees, and among others. Previous studies found that productivity at workplace is measured by absenteeism and presenteeism. Presenteeism is defined as decreased on-the-job performance due to the presence of health problems (Schultz & Edington, 2007). The opposite of presenteeism is absenteeism. Iverson et al. (2010) studied the contributions of multiple physical and psychological health conditions on work productivity among consumer goods manufacturing firms in Germany. They found that 34.8% of the employees experienced absenteeism and 78.4% experienced presenteeism for at least one health condition which led to 12.35% loss in productivity.

According to Bubonya, Cobb-Clark, and Wooden (2017), absence rates are approximately five percent higher among workers who report being in poor mental health. This was supplemented by the job conditions, such as

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diminished productivity at work, job complexity, and stress on absenteeism. Furthermore, mental health at workplace has been determined by various factors across job dimensions, including the degree of control, security, stress, and complexity (Park, Rhee, & Barak, 2016). This suggest that job arrangements by the employers should be considered in organizing job scope and division. Finally, there is evidence that women generally experience more internalizing problems, mental health conditions and general health issues than men (Rosenfield & Mouzon, 2013).

3. Methodology 3.1 Data

The sample of this study comprised of 233 full-time academic staff including tutors, fellows, lecturers, senior lecturers, associate professors and full professors from Universiti Sains Islam Malaysia (USIM) and Universiti Utara Malaysia (UUM). Data were collected using the non-probability convenient sampling technique through face-to-face and online survey between March and April 2021. All respondents are aged between 28 to 66 years old.

As the dependent variable is discrete, a nonlinear probability model is employed in this study. The influence of predictive variables that determine the dependent variables were analysed using logistic regression. The independent variables include individuals’ sociodemographic characteristics, health status and lifestyle factors.

3.2 Instruments

The questionnaire was developed based on the Short Form Health Survey (SF-36). The SF-36 is a measure of health status and productivity and the five-item Mental Health Inventory (MHI-5), that is used in this study, is a sub- set of SF36. The questionnaire was divided into four sections. Section A consisted of questions pertaining to sociodemographic details, such as age, gender, marital status, ethnicity, income, and employment background.

Additionally, questions on types of diseases and physical activity were included in this section. Section B comprised questions related to physical and mental health. Section C and D contained questions about workplace health and job performance, respectively. Written consent was obtained from respondents prior to answering the questionnaires.

Respondents who did not give consent were not eligible for the survey.

The dependent variable was measured from a 5-item perception on academic performance i.e., “exceeded expectations” (score=1), “fully met expectations” (score=2), “met some but not all expectations” (score=3), “did not meet expectations” (score=4), and “not my KPI” on six KPIs set by the universities (teaching and learning, publication, research and innovation, consultation, seminars, and community services). To avoid bias in the estimation, we dropped the “not my KPI” responses. In calculating the average score, the total score will be divided by the number of KPIs for each respondent. An average score less than 2 denotes good job performance, while an average score more than 2 denotes poor job performance. From the analysis, those who responded “not my KPI”

were mainly lecturers from the medical faculty, tutors or research fellows.

Meanwhile, the independent variables include the sociodemographic, health and lifestyles factors. The health and lifestyles variables included in the analysis were physical activity (=1 if spend more than 150 minutes weekly, 0 otherwise), health status (divided into 5 categories: poor, fair, good, very good, excellent), mental health (good mental health if MHI-5 score>56, 0 otherwise), presenteeism (high presenteeism if MHI-5 score>56, 0 otherwise) and workplace health (=1 if average of the 5-item Likert scale>2.5, 0 otherwise) .

3.3 Empirical specification using logistic model

The logit model is used to determine the role of mental health, controlling the effect of demographic and socioeconomic variables on the likelihood of having presenteeism problem. In this model, job performance will be the dependent variable,

y

. For the logistic regression model, the specification is shown as follows:

where;

refers to the probability as whether a respondent has good job performance or not. is the dependent variable which is defined as

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4.1 Descriptive analysis

The characteristics of the respondents were presented in Table 1. Nearly half of the respondents (49.8%) were in the range between 40-49 years and majority of them were female (67.8%), married, Malays (88%), married (83.3%), household size between 1-5 (73.4%), without administration post (64.4%), monthly income≥RM14,001 (35.2%), not physically active (84.1%), good health status (48.9%), without mental health problem (78.5%), without presenteeism problem (70.4%) and have good workplace health (67%).

Table 1: Distribution of respondents by sociodemographic, health, and lifestyle factors (n=233)

Variables Frequency (%)

Job performance Good

Poor 176

57 75.5

24.5 Age

<40 40-49 ≥50

116 65 52

27.9 49.8 22.3 Gender

Male

Female 75

158 32.2

67.8 Ethnicity

Malay Chinese Indian Others

205 11 13 4

88.0 4.7 1.7 Marital status 5.6

Single Married

Widowed/Divorced

194 25 14

10.7 83.3 Household size 6.0

1-5

>6 171

62 73.4

26.6 Administration post

With admin post

Without admin post 83

150 35.6

64.4 Income

≤RM8,000 RM8,001-RM10,000 RM10,001-RM12,000 RM12,001-RM14,000 ≥RM14,001

24 62 41 24 82

10.3 26.6 17.6 10.3 35.2 Physical activity

Active (>150 mins)

Not active 37

196 15.9

84.1 Health status

Poor Fair Good Very good Excellent

49 6 114 42

22

21.0 2.6 48.9 18.0 Mental health 9.4

Problem

Without problem 50

183 21.5

78.5 Presenteeism

Problem

Without problem 69

164 29.6

70.4

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Based on job performance, the cross-tabulation analysis shows that among the respondents with good performance, 50.6% have a good health status, 23.3% have a fair health status, and 13.1% have a very good health status. Meanwhile, among those with poor performance, 43.9% reported to have a good health status, 33.3% have a very good health status, and 14% have a fair health status. Figure 1 shows the cross-tabulation between job performance and health status.

Figure 1: Cross-tabulation: job performance vs health status

Interestingly, if we cross-tabulate job performance against mental health, the distribution of respondents with mental health was almost the same either they have a good job performance or not. Figure 2 shows the cross- tabulation between job performance and mental health.

Figure 2: Cross-tabulation: job performance vs mental health Workplace health

Good

Poor 156

77 67.0

33.0

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The overall fit of the model is significant χ²=34.169, p-value<0.1. The Hosmer-Lemeshow test was used to assess the relationship between the observed and predicted probabilities and is found to be insignificant (p- value>0.05) indicating that the logistic regression model fits the data. The Negelkerke R square shows that 20.3% of the variation in the dependent variable was explained by the predictors. The predictable accuracy rate is 75.5%

which is good as many studies suggested that the classification percentage above 70% is acceptable.

Results from Table 2 indicate job performance of academicians was significantly associated with ethnicity, health status, presenteeism and workplace health. Effects of other variables considered in the logistic regression model were not significant. These variables include age, gender, marital status, household size, administration post, income, physical activity, and mental health.

The results show that academicians from Chinese ethnicity were associated with 94.6% reduction in odds for having a good job performance relative to respondents from the other ethnicity group (mainly consisted of Bumiputera from Sabah and Sarawak) (OR=0.054, CI0.95 = 0.003, 0.667). The results suggest that the Bumiputera from Sabah and Sarawak strive harder and have higher levels of performance than the Chinese academicians.

As expected, the odds ratio of having a good job performance among academicians with a very good self-rated health were 80.9% less likely as compared to those who reported to have an excellent health (OR=0.191, CI0.95 = 0.046, 1.171). These findings were supported by Iverson et al. (2010) that showed employees with multiple health conditions contributed to a lower work productivity.

Academicians who perceive that the workplace health is good were 51.5% less likely to have a higher job performance as compared to those who reported that they have poor workplace health (OR=0.476, CI0.95 = 0.236, 1.144). Meanwhile, academicians with presenteeism problem were 1.477 more likely to have a higher job performance as compared to those who have no presenteeism problem (OR=2.493, CI0.95 = 0.927, 6.070). This inverse relationship can be explained by the effects of the COVID-19 pandemic whereby most academicians in USIM and UUM were required to work from home. Moreover, even though they were physically present at their jobs, they may experience decreased productivity and below-normal work quality, also known as decreased presenteeism.

Table 2: Logistic regression results for factors affecting job performance

Variables β SE OR 95% CI

Age

<40 0.429 0.483 1.535 0.618, 4.154

40-49 0.568 0.430 1.765 0.760, 4.110

≥50 (ref) 1 1

Gender

Male 0.110 0.404 1.116 0.472, 2.339

Female (ref) 1 1

Ethnicity

Malay -1.604 1.116 0.201 0.020, 1.775

Chinese -2.916 1.333 0.054** 0.003, 0.667

Indian -2.062 1.749 0.127 0.003, 4.007

Others (ref) 1 1

Marital status

Single 1.035 0.988 2.814 0.418, 20.006

Married -0.337 0.749 0.714 0.163, 3.051

Widowed/divorced (ref) 1 1

Household size

1-5 0.140 0.387 1.150 0.511, 2.358

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Note: SE refers to standard error. OR refers to odds ratio. CI refers to confidence interval.

*=p<0.10, **=p<0.05, ***=p<0.001

The COVID-19 pandemic has influenced the job performance of academic staff. In the questionnaire, they were asked about their opinion to what extent the pandemic has affected their job performance. Figure 3 shows that 62.2% of the respondents agreed (38.6% agree and 23.6% strongly agree) that the COVID-19 pandemic has influenced their job performance. In contrast, 15.4% disagree (10.2%) and strongly disagree (5.2%) with the statement.

>6 (ref) 1 1

Administration post

With admin 0.231 0.375 1.259 0.606, 2.714

Without admin post (ref) 1 1

Income

≤RM8000 -0.097 0.690 0.908 0.238, 3.554

RM8,001-RM10,000 -0.107 0.513 0.898 0.294, 2.235

RM10,001-RM12,000 -0.132 0.593 0.876 0.269, 2.831

RM12,001-RM14,000 -0.613 0.597 0.542 0.161, 1.707

≥RM14,001 (ref) 1 1

Physical activity

Active (>150 mins) 0.966 0.612 2.627 0.832, 9.282

Not active 1 1

Health status

Poor -0.899 1.201 0.407 0.046, 5.245

Fair -0.182 0.807 0.834 0.187, 4.470

Good -0.315 0.759 0.730 0.197, 4.031

Very good -1.655 0.827 0.191** 0.046, 1.171

Excellent (ref) 1 1

Mental Health

Problem -0.064 0.516 0.938 0.343, 2.685

Without problem (ref) 1 1

Workplace health

Good -0.743 0.395 0.476* 0.236, 1.144

Poor (ref) 1 1

Presenteeism

Problem 0.913 0.472 2.493* 0.927, 6.070

Without problem (ref) 1 1

Nagelkerke pseudo R²= 20.4%

Chi-square = 34.308, df = 23, p<0.05

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Figure 3: Influence of COVID-19 pandemic on job performance 5. Conclusion

This study relates the effect of physical and mental health on job performance of academic staff in public universities in Malaysia, namely USIM and UUM. The results show that job performance of academicians was significantly associated with ethnicity, health status, presenteeism and workplace health. Academicians with excellent health status were more likely to have good job performance than the others. However, we found an inverse relationship between presenteeism and workplace health on job performance that can be related to the COVID-19 pandemic.

Further investigations need to be conducted in understanding job performance among academicians during the COVID-19 pandemic. Since this study is limited to USIM and UUM academic staff, in the future, a study with a wider coverage for instance covering academic staff from research universities (RU) and other non-RUs should be carried out. An in-depth study should also be conducted to understand the needs and types of support required by the academicians to handle various workload during the pandemic in fulfilling their KPIs. It is important for the universities to provide employee health programs that target highest-risk workers i.e., those with poor physical and mental health which can help to improve their job performance and eventually, their quality of life.

Acknowledgement

This research if funded by Universiti Sains Islam Malaysia - Matching Grant with Universiti Utara Malaysia (USIM/MG/UUM/FEM/055012/71019).

References

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