Risk Factors Assessment of Musculoskeletal Disorders among Professional Vehicle Drivers in India Using an Ordinal Priority Approach

: Professional driving involves sitting in uncomfortable positions, navigating difﬁcult terrain and roads, and occasionally conducting small repairs and other auxiliary transportation duties while at work for long periods. Drivers who engage in these activities may develop a variety of musculoskeletal disorders (MSDs). MSDs in professional drivers are accompanied by several risk factors. In this study, the various risk factors for MSD have been identiﬁed through the literature reviews, discussions with professional drivers, and consultations with ergonomics specialists. This study employed the ordinal priority approach (OPA), a multi-criteria decision-making (MCDM) technique, to rank the identiﬁed risk variables for MSD in order of importance. The same OPA method has also been used to identify the group of professional drivers who use eight different types of vehicles and are more likely to develop MSDs. The analyses ﬁndings show that the ﬁve main risk factors for MSDs among drivers are prolonged sitting, restricted posture, working hours, alcohol consumption, and uncomfortable seating. Additionally, among all drivers regarded as professionals, truck drivers are found to be the most at risk. For the study’s conclusions to be validated, a sensitivity analysis was also carried out. The results of this study are anticipated to help formulate strategies for lowering these hazards through the ergonomic design of drivers’ cabins by automobile OEMs (Original Equipment Manufacturers) and vehicle scheduling by concerned transportation organizations to reduce driver tiredness.


Introduction
A crucial component of people's daily life is transportation. Professional drivers play a significant role in the transportation system, and their dependability and productivity are key factors in the system's effectiveness [1]. Professional drivers are individuals who must operate a vehicle as part of their line of work, such as bus, taxi, or truck drivers [2]. Professional driving is a stressful job that is made more unpleasant by things such as bad weather, the speed, intensity, and density of the traffic flows, traffic jams, unreliable transportation schedules, unclear holidays, convoluted routes, etc. [3]. Drivers are exposed to activities that increase their risk of lower back pain and other spinal injuries, such as prolonged sitting, whole-body vibrations, uncomfortable postures, etc. Due to the

Identification of MSDs' Risk Factors
Drivers of tractors, buses, trucks, heavy machinery (such as cranes, excavators, and earthmovers), and cars who are frequently subjected to whole-body vibrations were the subjects of certain epidemiological investigations by Gallais and Griffin [10]. When compared to other industrial and agricultural drivers, they found that automobile drivers had substantially lower levels of whole-body vibration. The postural tension caused by a taxi cab's restricted leg movement or flexibility has been demonstrated to increase the incidence of musculoskeletal problems in drivers [11]. Additionally, the urban area's extremely congested traffic conditions and frequent stops put drivers under a lot of physical strain [12]. Some research [13,14] discovered a connection between workplace characteristics such as repetitiveness and static posture, as well as musculoskeletal problems, and individual aspects such as gender. Smoking is frequently cited as a contributing factor to back and neck discomfort, in addition to work-organizational and psychosocial issues, but excessive alcohol intake has been shown to have a protective effect [15]. Additionally, other research claimed that the most important risk factors for lower back and neck pain were personal, occupational, and psychological factors [16,17].
Truck drivers perform additional tasks such as loading and unloading the vehicle and getting in and out of the vehicle, which results in muscular injury, according to Sekkay et al. [18]. Numerous factors, including lengthy driving hours [19], insufficient rest, worn-out driving seats [20,21], poor driving posture [22], and whole-body vibration [23], have been linked to these muscle ailments. Furthermore, numerous research [8,[24][25][26] revealed that truck, bus, and taxi drivers experienced lower back pain as a result of extended driving, as well as physical and psychological issues. Due to the adoption of poor body posture while driving, the lower back is the predominant region of the body for musculoskeletal diseases when compared to other sections of the body. According to the research, drivers are particularly vulnerable to developing WMSD due to extended sitting positions, lengthy workdays, continual smoking, vibration, and psychosocial factors [21,24].
Job support has only a weak correlation with musculoskeletal discomfort [27,28], whereas job discontent and stress at work [8,27,29] are important risk factors for musculoskeletal injury. Discovered a substantial correlation between taxi drivers' lower back pain (LBP) and body mass index (BMI).
Twenty MSD risk factors associated with driving were found after a thorough assessment of the literature and discussions with experts, as shown in Table 1. As stated in Table 2, they were divided into three major categories: individual factors (IF), occupational factors (OF), and psychosocial factors (PF).

Description of the OPA Methodology
The best weights and ranks for the risk factors for MSDs are determined in this study using the ordinary priority approach (OPA). The rating of professional drivers who are more susceptible to MSD risk factors uses the same methodology. The most recent method for resolving MCDM issues that may be used for both individual and group decision-making is the ordinal priority approach (OPA), which was put forth by Ataei et al. [9]. OPA determines the weight of experts, criteria, sub-criteria, and alternatives in a straightforward manner. Sadeghi et al. [47] reported the following advantages of OPA over other MCDM tools.

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The OPA method does not require a pairwise comparison matrix and instead uses the order of criteria and alternatives.

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The OPA method does not require a decision-making matrix.

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The OPA method does not require normalization practice • OPA method does not require the averaging practice for accumulation of the experts' instead uses a mathematical model for the same. • OPA concurrently evaluates the rank of alternatives, the weight of experts, and the weight of attributes.
Mahmoudi and Javed [48] provided the essential sets, indexes, variables, and parameters associated with the OPA, which are shown in Table 3.  lmn is the nth alternative centered on mth criteria by experts l at rth rank. Moreover, W r lmn is the importance value of nth alternative centered on mth criteria by experts l at rth rank. The ranking of alternatives centered on each criterion is shown by Equation (1) The only logical assumption of B r lmn ≥ B r+1 lmn lmn is that W r lmn should be considerably greater than W r+1 lmn . Hence, Equation (2) holds.
As such, the importance weight difference in successive rank, Equation (2), can be modified and written as Equation (3) Multiplying both sides of Equation (3) by l, m, and r, it will be modified to generate Equation Equations (1)-(4) can be used for prioritizing and evaluating the importance and weight of the alternatives. Moreover, the same method can be utilized for the criteria and experts. Ataei et al. [49] have suggested the following steps for the ordinal priority approach (OPA) in detail.
Step 1: Selecting the decision criteria.
The criteria, as well as their sub-criteria, are specified and included in the decisionmaking process as per analyst opinion.
Step 2: Designating and ranking the experts.
The ranking of the experts who participate in the decision-making process (single or group) may include several factors such as their education level and year of experience.
Step 3: Ranking of criteria. At this stage, experts are asked to prioritize the criteria based on their experience. Experts have the liberty to include or exclude any criteria in the ranking process and mathematical model.
Step 4: Ranking of alternatives in each criterion.
In this stage, experts prioritize each alternative in each criterion according to their expertise. In the case of group decision-making, experts prioritize each alternative by taking each criterion into consideration.
Step 5: Solving of mathematical model for optimal weights. The mathematical model, which was developed based on steps 1 and 2 shown in Equation (5), is solved to obtain the optimal weight of the criteria.
W lmn ≥ 0, Where Z doesn't have any restriction on its sign.
Step 6: Evaluation of the weight of criteria, alternatives, and experts. Based on the results of the mathematical model in Equation (5), the weights of criteria, alternatives, and experts are calculated based on Equations (6)- (8).

Implementation of the Methodology
Three primary categories-individual (IF), occupational (OF), and psycho-socialwere used to classify the twenty MSD risk variables that were found in the literature (PF). A panel of five experts provided the input data for the rankings of risk factors and potential solutions (Refer Appendices A and B). The professors who were selected were actively involved in the MCDM research projects. Additionally, some of them focus on ergonomics and know the difficulties that drivers confront, which are described in the literature. Since they were managers of logistics firms that previously used professional drivers, the Deputy General Managers, Assistant Managers, and Managers were chosen for the study on professional drivers. They were the ones who were most familiar with the driver's issues and who understood the seriousness of such circumstances.
The experts were ranked keeping in mind their experience and education level. The details of the experts and their ranking are presented in Table 4.
Further, the category of professional drivers considered in this study who are vulnerable to MSD risk is shown in Table 5. Table 5. Category of professional drivers.

Category Notation
Cab Driver A Heavy machinery driver B Bus driver C Auto-rickshaw driver D E-rickshaw driver E Tractor driver F Truck driver G Two-wheeler taxi driver H The ideal weight of the risk factors for MSD was then computed using the OPA methods described in Section 3. The severity of each risk factor for each group of professional drivers was ranked by experts, and this ranking was utilized to determine the best weight of the alternatives. The risk variables for MSDs and the various professional driver groups were then rated according to their ideal weights. The ideal weight of the primary risk variables was eventually calculated using the optimal weight of the sub-risk factors. Table 6 displays the input information connected to each expert's ranking of the risk factors for MSDs. Subsequently, experts were also asked to prioritize the different professional driver groups according to each MSDs' risk factor. The opinion of expert1 related to this prioritization is shown in Table 7.
Similarly, the ranking of professional driver groups based on the severity of each MSDs' risk factors by other experts was also obtained. By using the input data from Tables 6 and 7, the linear mathematical model was solved, and computed the optimal solution of the model's variable, such as the importance weight of MSDs' risk factors and the weight of different categories of professional drivers and experts using Equations (6)-(8) described in Section 3. The degree of significance of the experts is represented by the sum of weight related to decision-making experts. Hence, the importance weight of experts is W 1 = 0.438, W 2 = 0.219, W 3 = 0.146, W 4 = 0.109, and W 5 = 0.087, respectively. In addition to this, the ratio of the optimal weight of each risk factor and the aggregate weight of each expert displayed in Table 8 indicates the degree of significance of each risk factor.
The ranking of factors given by the experts shows the significance of the criteria. Therefore, the weight of the criteria obtained after solving the linear mathematical model is listed in Table 9.
Similarly, the degree of significance of different categories of professional drivers is indicated by the ratio of the optimal weight of the category of professional drivers to the aggregate weight of each expert (Table 10). Furthermore, the rank of the category of professional drivers suggested by the experts determines the importance weight of the different categories of professional drivers. As a result, the importance weight of each category of professional drivers is determined after solving the mathematical model, and the ranking of the category of professional drivers based on their importance weight is listed in Table 11. Table 8. Importance value of each risk factor from the perspective of each expert.

Expert
Degree  Job support JS 0.0163 19 20 Job dissatisfaction JD 0.0154 20 Table 10. Importance value of each alternative from the perspective of each expert. The importance weight of the sub-factors determines the weight of the main factors. Finally, the weight of individual factors, occupational factors, and psycho-social factors are obtained, as shown in Table 12.  Table 12 shows that out of three main factors, 'occupational factors (OF)' appears to be the most important, followed by 'individual factors' and 'psycho-social factors.' Moreover, Table 9 reveals that the sub-factor 'prolonged sitting (PS)' and 'job dissatisfaction (JD)' are the most important and least important MSDs risk factors, respectively.

Degree of the Significance of Alternatives
OPA suggested that occupational factor is the top-ranked MSDs risk factor, and this finding is supported by the studies conducted by other researchers [50][51][52], in which they also found that occupational factors such as non-neutral posture, repetition, vibration, weightlifting, etc. strongly elevates the MSD risk. Results from Table 11 reveal that the significance of the MSDs risk factors is the maximum among truck drivers and the minimum among two-wheeler taxi drivers. The results also show that the significance of MSDs risk factors among cab drivers is next to that of truck drivers. These results are in line with the results of studies conducted by previous researchers [4,53,54].

Sensitivity Analysis
One cannot completely rule out the potential that a change in the rank of the experts will affect the ranking of the sub-factors. As a result, sensitivity analysis is carried out to assess the impact of a change in the experts' ranking on the weight of the risk factors for MSDs, as well as to check the reliability and robustness of the ranking of the factors. It is carried out by exchanging the expert ranks of every single person. The possible combination of a different set of experts' ranks is evaluated by using a relation n(n − 1), where 'n' represents the number of experts in the group decision-making process. Accordingly, the possible combination of experts' ranking is shown in Table 13.

Conclusions and Future Scope
MSDs among professional drivers of different types of vehicles hasalways been a major concern for ergonomists, engineers, and other professionals. In the present study, a relatively new MCDM method, i.e., OPA, was employed to compute the weight of the MSD risk factors associated with professional drivers. In addition, the different categories of professional drivers were also ranked based on the risk factors to identify the risky drivers among all categories of commercial vehicles. The results of the present study led to the following conclusions: Among the drivers of different types of vehicles, truck drivers are at the highest risk of MSDs, followed by cab drivers, bus drivers, heavy machinery drivers, auto-rickshaw drivers, tractor drivers, E-rickshaw drivers, and two-wheeler taxi drivers.
This research provides useful information to ergonomists/human factor engineers, automobile designers, transport planners, and other stakeholders in the transportation business on the significance of the various MSD risk factors that may lead to injuries to drivers. In terms of limitations, it is emphasized that this research does not determine the importance of the combined effect of the various MSDs risk factors. Further, it involved only a few experts in providing feedback during data collection. In addition, it determined the significance of the MSDs risk factors for drivers of only eight different types of vehicles.
The future scope of this research includes analysis of the interaction between the various MSD risk factors, incorporation of a bigger group of experts, and implementation of other statistical techniques such as factor analysis and structural equation modeling for validation of the results.

Research Implications
Musculoskeletal diseases are now a widespread health issue among employees in general and professional drivers in particular since they spend so much time at work and sitting in uncomfortable positions while driving. In order to reduce the hazards involved; it is important to study the characteristics that may contribute to MSDs in professional drivers. These factors include gender, ethnicity, BMI, age, and others. In order to effectively manage them and reduce the danger of acquiring MSDs, it has been attempted to identify and prioritize the major MSD risk factors that may cause MSDs in professional drivers.
Mitigating the risk cannot be achieved until the severity and criticality of involved factors are identified, which can easily be achieved by implementing multi-criteria decisionmaking (MCDM) techniques.Thus, in this study, initially, the MSD risk factors have been identified through the literature and discussions with the experts, and subsequently, the ordinal priority approach (OPA), which is an MCDM technique, has been employed to rank them. The same OPA method has also been used to identify the group of professional drivers who drive eight different types of vehicles and are more likely to develop MSDs. Based on the results of the present study, the decision makers of the transportation companies may understand the relative importance of the various MSD risk factors and may formulate effective strategies to prevent the risk of developing MSDs among professional drivers, which may ensure their better health conditions and may also help in the economic growth of the companies.

Section-1.1 Ranking of MSD's Risk factors
Experts are requested to prioritize the musculoskeletal disorder risk factors in between 1 to 20 based on their severity to give rise to musculoskeletal disorder in drivers in such a way that the most severe risk factor assigned with first rank and the least severe one assigned with last rank i.e., 20. (Note: please use the scroll-down menu to assign an appropriate rank to the given risk factors).  If selected categorization needs to be modified, please provide your valuable suggestion for modification: Expert's opinion (please use scroll-down menu): Risk factors were fairly categorized.
If selected categorization needs to be modified, please provide your valuable suggestion for modification:

Section-1.2 Ranking of alternatives
Experts are requested to prioritize the alternatives whose are listed below, as per their higher susceptibility to musculoskeletal disorder (MSD) due to given risk factors in such a way that the alternative which hasahigher susceptibility to MSD due to given risk factor is rank one and the alternative which have the least susceptibility to MSD due to given risk factor is on the last rank.

Alternatives:
Cab driver Heavy machinery driver Bus driver Auto rickshaw E-rickshaw Tractor drivers Truck driver Two-wheeler driver Procedure to prioritize the alternatives: Please use the scroll-down menu to select an appropriate alternative as per the given rank.
1. Assuming 'Gender' to be a MSDs risk factor, prioritize the following alternatives between 1 to 8 as per their higher susceptibility to MSD due to Gender.

Rank Category
Risk factors are fairly Categorized as per Biomechanics Science. Hence do not require any Modification.

Section-1.2 Ranking of alternatives
Experts are requested to prioritize the alternatives whose are listed below, as per their higher susceptibility to musculoskeletal disorder (MSD) due to given risk factors in such a way that the alternative which hasahigher susceptibility to MSD due to given risk factor is rank one and the alternative which have the least susceptibility to MSD due to given risk factor is on the last rank.

Alternatives:
Cab driver Heavy machinery driver Bus driver Auto rickshaw E-rickshaw Tractor drivers Truck driver Two-wheeler driver