Modelling the Relationship Between Job Satisfaction, Need for Recovery and Occupational Fatigue Using PLS-SEM Among Malaysian Truck Drivers

Main Article Content

Nurul Atikah Che Hasan
Shamsul Bahri Mohd Tamrin
Karmegam Karuppiah
Nurul Ainun Hamzah

Abstract

Introduction: Fatigue is one of the occupational hazards among truck drivers which can impair drivers’ performance and increase fatal accidents. This study aims to investigate the relationship between organizational factors and work-related factors towards occupational fatigue levels among truck drivers in Malaysia. Materials and methods: A questionnaire was validated, and one hundred-sixty eight drivers (168) were recruited based on a stratified random sampling method. The job satisfaction survey (JSS) and Need for Recovery (NFR) questionnaire were administered in a Malay-validated form. Structural equation modelling (PLS-SEM) was used to test the hypotheses. Results: According to the results, job satisfaction (p<0.001) and need for recovery (NFR) (p<0.05) were found to be significant factors which influence the occupational fatigue of the truck drivers. Conclusion: To summarized, the study identified organizational and work-related factors as the significant contributors factors to occupational fatigue. Therefore, the emphasis on organization and work-related management is essential to reduce fatigue occurrence among truck drivers. 

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Che Hasan, N. A., Mohd Tamrin, S. B., Karuppiah, K., & Hamzah, N. A. (2025). Modelling the Relationship Between Job Satisfaction, Need for Recovery and Occupational Fatigue Using PLS-SEM Among Malaysian Truck Drivers. Malaysian Journal of Medicine and Health Sciences, 21(3), 85–93. https://doi.org/10.47836/mjmhs.21.3.11
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Original Articles

References

MIDA. Malaysian Investment Development Authority. Malaysia, well-positioned as a regional logistics hub and gateway to Asean [Cited 2024 March 7] Available from https://www.mida.gov.my/malaysia-well-positioned-as-a-regional-logistics-hub-and-gateway-to-asean/

Schneider E, Irastorza X. OSH in figures: Occupational safety and health in the transport sector - An overview. Luxembourg. 2011.

Huhta R, Hirvonen K, Partinen M. Prevalence of sleep apnea and daytime sleepiness in professional truck drivers. Sleep Med. 2021;81:136-43. https://doi.org/10.1016/j.sleep.2021.02.023

Mozafari A, Vahedian M, Mohebi S, Najafi, M. Work-related musculoskeletal disorders in truck drivers and official workers. Acta Medica Iranica. 2015;53(7):432–38

Rahimpour F, Jarahi L, Rafeemanesh E, Taghati, A, Ahmadi F. Investigating job stress among professional drivers. Journal of Molecular Biology Research. 2020;10(1):29–36.doi:10.5539/jmbr.v10n1p29

Ren X, Pritchard E, van Vreden C, Newnam S, Iles R, Xia T. Factors associated with fatigued driving among Australian truck drivers: a cross-sectional study. Int J Environ Res Public Health. 2023;20(3):2732. https://doi.org/10.3390/ijerph20032732

Phillips RO. A review of definitions of fatigue – and a step towards a whole definition. Transportation Research Part F: Traffic Psychology and Behaviour. 2015;29:48–56. https://doi.org/10.1016/j.trf.2015.01.003

Lim SM, Chia SE. The prevalence of fatigue and associated health and safety risk factors among taxi drivers in Singapore. Singapore Medical Journal. 2015;56(2):92. doi: 10.11622/smedj.2014169

Maynard S, Filtness A, Miller K, Pilkington-Cheney F. Bus driver fatigue: A qualitative study of drivers in London. Applied Ergonomics. 2021;92:103309. https://doi.org/10.1016/j.apergo.2020.103309

Chan T, Chen R, Yeh C, Yeh, S. Study on the risk factors of work-related fatigue indicators. International Journal of Management and Applied Science. 2019;5(2):62–7.

Chen C, Zhang J. Exploring background risk factors for fatigue crashes involving truck drivers on regional roadway networks: a case-control study in Jiangxi and Shaanxi, China. 2016;5:582. https://doi.org/10.1186/s40064-016-2261-y

Bunn TL, Slavova S, Rock PJ. Association between commercial vehicle driver at-fault crashes involving sleepiness/fatigue and proximity to rest areas and truck stops. Accident Analysis and Prevention. 2019;126:3–9. https://doi.org/10.1016/j.aap.2017.11.022

Al-Mekhlafi AA, Shahrul A, Isha N, Sabir, AA. Fatigue Assessment of Oil and Gas Tanker Drivers : Psychomotor Vigilance Test (PVT-192). 2020 (November).

Iridiastadi H, Abdurrahman I, Puspasari M, Soetisna HR. Fatigue and sleepiness during long haul duration driving: A preliminary study among Indonesian commercial drivers. Transport Problems. 2020;15(2):17–24.

Meng F, Li S, Cao L, Li M, Peng Q, Wang C, Zhang W. Driving Fatigue in Professional Drivers: A Survey of Truck and Taxi Drivers. Traffic Injury Prevention. 2015;16(5):474–483. https://doi.org/10.1080/15389588.2014.973945

Arnold PK, Hartley LR. Policies and practices of transport companies that promote or hinder the management of driver fatigue. Transportation Research F, Special Issues. 2001;4(1):1–17. https://doi.org/10.1016/S1369-8478(01)00010-9.

Li Ya, Itoh K. Satisfaction factors of occupational truck drivers and their impacts on traffic safety. Journal of Japan Industrial Management Association. 2013;63(4):277–88. https://doi.org/10.11221/jima.63.277

Devi, S., Vasudevan, A., Sagadavan, R., & Shiney. (2023). Drivers of Employee Job Satisfaction During Pandemic in Manufacturing Industries. International Journal of Professional Business Review, 8(10), e01018. https://doi.org/10.26668/businessreview/2023.v8i10.1018

Hernández-Rodríguez, V., Maeso-González, E., Gutiérrez-Bedmar, M., & García-Rodríguez, A. (2022). Psychosocial risk and job satisfaction in professional drivers. Frontiers in Psychology, 13(September), 1–9. https://doi.org/10.3389/fpsyg.2022.994358

Sluiter JK, van der Beek AJ, Frings-Dresen MH. The influence of work characteristics on the need for recovery and experienced health: a study on coach drivers. Ergonomics. 1999;42(4):573-83. https://doi.org/10.1080/001401399185487

Zuraida R, Abbas BS. The factors influencing fatigue related to the accident of intercity bus drivers in Indonesia. International Journal of Technology. 2020;11(2):342-352.

Sluiter JK, De Croon EM, Meijman TF, Frings-Dresen MHW. Need for recovery from work related fatigue and its role in the development and prediction of subjective health complaints. Occupational and Environmental Medicine. 2003;60(1):i62–i70. https://doi.org/10.1136/oem.60.suppl_1.i62

Ani MF, Kamat SR, Mohamad M, Hambali RH, Husain K. A study of psychophysical factor (heart rate) for driver fatigue using regression model. Malaysian Journal of Public Health Medicine. 2018;2:1-9.

Al-Mekhlafi ABA, Isha ASN, Chileshe N, Abdulrab M, Saeed AAH, Kineber AF. Modelling the relationship between the nature of work factors and driving performance mediating by role of fatigue. International Journal of Environmental Research and Public Health. 2021;18(13):6752. https://doi.org/10.3390/ijerph18136752

Chin-Siang A, Talib MA, Juhari R, Madon Z. Psychometric properties of the Malay version of the job satisfaction survey among malaysian military personnel. Pertanika J. Soc. Sci. Hum. 2014;22(1):285-306.

Hasan, NAC. Development of occupational fatigue model based on the subjective and objective fatigue measurement among logistic truck drivers in malaysia. PhD Thesis. Universiti Putra Malaysia. 2023.

Abraham J, Barker K. Exploring gender difference in motivation, engagement and enrolment behaviour of senior secondary physics students in new South Wales. Research in Science Education. 2014;45(1):59–73. https://doi.org/10.1007/s11165-014-9413-2

Fincham JE. Response rates and responsiveness for surveys, standards, and the Journal. Am J Pharm Educ. 2008;72(2):43. https://doi.org/10.5688/aj720243

Hair JF, Hult GTM, Ringle CM et al., Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. Springer; 2021.

Layne, DM, Rogers B, Randolp. Health and gender comparisons in the long-haul trucking industry (a pilot study). American Association of Occupational Health Nurses. 2009;57(10):405-13. Doi: 10.3928/08910162-20090916-01

Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis: a global perspective. 7th ed. Upper Saddle River: Pearson Education; 2010.

Chin W. The partial least squares approach to structural equation modelling. In: Marcoulides GA, editor. New Jersey: Lawrence Erlbaum Associates; 1998.

Henseler J, Ringle CM, Sinkovics RR. The use of partial least squares path modeling in international marketing: New Challenges to International Marketing. In: Sinkovics RR, Ghauri PN, editor. Emerald Group Publishing Limited: Bingley; 2009.

Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research. 1981;18:39–50. https://doi.org/10.2307/3151312

Garver MS, Mentzer JT. Logistics research methods: employing structural equation modeling to test for construct validity. J.Bus. Logist. 1999;20:33-57.

Hair J, Black W, Babin B, Anderson R, Tatham RL. Multivariate data analysis. 6th Ed. Upper Saddle River: Pearson-Prentice Hall; 2006.

Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research. 1981;18:39–50.

Gaur SA, Gaur SS. Statistical methods for practice and research: a guide to data analysis using SPSS. 2nd ed. New Delhi: SAGE Publications; 2009.

Sarstedt M, Ringle CM, Hair JF. Partial least squares structural equation modelling: Handbook of market research. Springer; 2021.

Stone, M. Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society. 1974;36(2):111–47.

Geisser S. A predictive approach to the random effects model. Biometrika. 1974;61(1):101–107. https://doi.org/10.2307/2334290

Frone MR, Tidwell MCO. The meaning and measurement of work fatigue: Development and evaluation of the Three-Dimensional Work Fatigue Inventory (3D-WFI). Journal of Occupational Health Psychology. 2015;20(3):273. Doi: 10.1037/a0038700

Alam A, Asim M. Relationship between job satisfaction and turnover intention. International Journal of Human Resource Studies. 2019;9(2):163.

Diriwaechter P, Shvartsman E. The anticipation and adaptation effects of intra- and interpersonal wage changes on job satisfaction. Journal of Economic Behavior & Organization. 2017; 146:116-140. https://doi.org/10.1016/j.jebo.2017.12.010

Kivimäki M, Leino-Arjas P, Kaila-Kangas L, Luukkonen R, Vahtera J, Elovainio, et al. Is incomplete recovery from work a risk marker of cardiovascular death? prospective evidence from industrial employees. Psychosomatic Medicine. 2006;68(3):402-7. Doi: 10.1097/01.psy.0000221285.50314.d3

Park J, Kim Y. Association of exposure to a combination of ergonomic risk factors with musculoskeletal symptoms in Korean workers. Int J Environ Res Public Health. 2020;17(24):9456. Doi: 10.3390/ijerph17249456

Devereux JJ, Rydstedt LW, Cropley M. Psychosocial work characteristics need for recovery and musculoskeletal problems predict psychological distress in a sample of British workers, Ergonomics. 2011;54(9):840-8. https://doi.org/10.1080/00140139.2011.595830

Meijman T, Mulder G. Psychological aspects of workload: Handbook of Work and Organization: Work Physchology. In: Drenth PJD, Thierry H, de Wolff CJ. editors. 2nd ed. Hove: Psychology Press; 1998.

Moriguchi CS, Alem ME, Coury HJ. Evaluation of workload among industrial workers with the Need for Recovery Scale. Rev Bras Fisioter. 2011;15(2):154-9. Doi: 10.1590/s1413-35552011000200011

Nwaogu JM, Chan APC. Work-related stress, psychophysiological strain, and recovery among on-site construction personnel. Automation in Construction. 2021;125:103629,ISSN 0926-5805. https://doi.org/10.1016/j.autcon.2021.103629