INTRODUCTION

Work-related musculoskeletal disorders (WMSDs) and symptoms in the working population are common, occurring predominantly in the low back, neck and upper limbs (Hales and Bernard, 1996; Malchaire et al., 2001; Punnett and Wegman, 2004). In a study by Merlino et al. (2003) it is indicated that WMSDs are an important cause of worker disability and absenteeism in many occupational groups. These disorders include a large number of inflammatory and degenerative conditions affecting muscles, tendons, ligaments, joints, peripheral nerves and blood vessels. Bernard (1997) has stated that WMSDs are a common health problem and a major cause of disability. A range of physical, individual, and psychosocial risk factors are associated with the development of WMSDs (Kuorinka 1998; Punnett and Wegman 2004) .The physical risk factors include the physical demands imposed by performing the task, such as posture adopted, force applied, frequency and repetition of movement, task duration and vibration experienced (Bernard, 1997; Aptel et al., 2002). Therefore,

J. Hum. Ergol, 40: 19-36, 2011

Received 20 October 2010; accepted 25 November 2011

WERA: AN OBSERVATIONAL TOOL DEVELOP TO INVESTIGATE THE PHYSICAL RISK FACTOR ASSOCIATED WITH WMSDS

Mohd Nasrull abd rahMaN1*, Mat rebi abdul raNi2 aNd Jafri Mohd rohaNi3

1 Department of Manufacturing & Industrial Engineering , Faculty of Mechanical Engineering & Manufacturing, Universiti Tun Hussein Onn Malaysia (UTHM)

*E-mail: mnasrull@uthm.edu.my2,3 Department of Manufacturing & Industrial Engineering, Faculty of Mechanical Engineering,

Universiti Teknologi Malaysia (UTM)

This paper describes the development of the Workplace Ergonomic Risk Assessment (WERA) for investigating the physical risk factor associated with work-related musculoskeletal disorders (WMSDs). The initial development of WERA tool involved the following procedures: (1) first stage, development of WERA prototype from literature review, (2) second stage, evaluation of the psychometric properties including (a) validity trials and (b) reliability and usability trials. In the validity trials, the relationship of the individual WERA body part scores to the development of pain or discomfort is statistically significant for the wrist, shoulder and back regions. It shows that the WERA assessment provided a good indication of work-related musculoskeletal disorders which might be reported as pain, ache or discomfort in the relevant body regions. In the reliability trials, the results of inter-observer reliability shows that moderate agreement among the observers while from the feedback questionnaire survey about the usability of WERA tool, all participants including expert and management teams agreed that the prototype of WERA tool was easy and quick to use, applicable to workplace assessment for the wide range of job/task and valuable at work. It was confirmed that there was no need of training required to do WERA assessment. Therefore, the WERA assessment has been designed for easy and quick use, and for those who are trained to use it do not need previous skills in observation techniques although this would be an advantage. As WERA is a pen and paper technique that can be used without any special equipment, WERA assessment can be done in any space of workplaces without disruption to the task that have been observed.Key words: WERA; observational tool; ergonomic risk assessment; physical risk factor; work-related musculoskeletal disorder

20 MOHD NASRULL ABD RAHMAN et al.

this paper describes the development of the Workplace Ergonomic Risk Assessment (WERA) for assessing the physical risk factors associated with work-related musculoskeletal disorders. The development of this tool was based upon an extensive review of the scientific literature.

METHODS

The initial development of WERA tool involved the following procedures: (1) first stage, development of WERA prototype from literature review, (2) second stage, evaluation of the psychometric properties including (a) validity trials and (b) reliability and usability trials. The aims of the validity study is to determine the validity of WERA tool in the workplaces and the aims of the reliability and usability study is to determine the reliability and usability of WERA tool during the training session. Figure 1 shows the development process of the WERA tool.

Fig. 1. WERA development process.

Stage 1: Development of WERA prototype from literature reviewThe development of WERA occurred from an extensive review of the scientific literature. The

first step was the development of the method for recording the risk factors and the second step was the development of the scoring system and action levels which provided a guide to the level of risk and need for action to conduct more detailed assessments. The epidemiological evidence regarding to the physical risk factors in the development of WMSDs was collected to identify priorities risk factors for inclusion in the WERA tool. Current techniques of the observational tool especially for assessing the WMSDs were also reviewed to help form the strategy for the development of the WERA tool.

Stage 2a : Evaluation of the psychometric properties – validity trialsThe application of WERA tools were evaluated in construction industry, confirming its validity

in the workplaces. The total of 130 workers at three types of job in construction industries including wall plastering job (n=43), bricklaying job (n=45) and floor concreting job (n=42) were involved in this study. Each of the jobs was direct by observed using the WERA tool. During the task duration,

OBSERVATIONAL TOOL TO INVESTIGATE PHYSICAL RISK FACTOR 21

observation of the workplace was carried out by recording the job with a video camera (Sony DCR-SX63E). Three jobs were observed and videotaped during the task duration in order to gather data for the WERA assessment. From the videotape the angle of the body segments relative to the vertical was estimated (shoulders, wrists, back, neck and legs). An additional measurements were made on the weight of the load and distances of walking by using the weight scale and the measurement tape in the workplaces. During the resting time, a structured interview was conducted by using self-report charts given to all the subjects for each tasks. The aims of pilot testing was to establish whether WERA assessment provided a good indication of work-related musculoskeletal disorders which might be reported as pain or discomfort in the relevant body region.

Stage 2b : Evaluation of the psychometric properties – reliability and usability trialsFor the reliability and usability of this tool, WERA was presented as an assessment method

during the training session for the 33 participants including occupational safety and health (OSH) practitioners, managers and officers. All participants who undertook risk assessment were given training how to conduct a WERA assessment. This involved a trial assessment on three jobs by video films to familiarize the participants with the WERA process, together with subsequent discussion with the researcher. Three jobs of video films were recorded from home building industry including a wall plastering job, bricklaying jobs and a floor concreting job. The participants acting as observers were divided into two groups including an expert team and a management team. The three recorded jobs were assessed by each group in the same time during the day. Before watching the videos, the observers had 5-10 minutes going through a brief discussion about the purpose of the tool, instruction, scoring system and the terms defined in the WERA tool. After that, the video film was played and the observers made their assessment on each recorded task with the WERA tool. This use of the WERA tool required approximately 5-10 minute to complete for each task. The total time to complete for all 3 tasks amounted to 45 minutes including the examination of a feedback questionnaire from participants. If any subject could not complete the assessment within the time given, the video film task was re-wound and re-played to make sure all observers could finish their assessment for that task.

The usability of the WERA assessment was studied by a structured interview with a feedback questionnaire of WERA assessments from all participants after they completed the WERA assessment for three jobs during the training session. The questionnaire survey consisted of 9 questionnaires about the WERA assessment that was easy to use, quick to use, applicable to workplace assessment, applicable in wide range of job/task, valuable at work and requiring training on scoring system (rating is useful, colour coding, final score). The questionnaire survey used closed-ended questions with five-point likert scale rating (1=strongly disagree, 5=strongly disagree).

RESULTS AND DISCUSSION

Stage 1: Development of the Workplace Ergonomic Risk Assessment (WERA) The Workplace Ergonomic Risk Assessment (WERA) is developed to provide a method of

screening the working task quickly for exposure to the physical risk factors associated with work-related musculoskeletal disorders (WMSDs). The development of WERA occurred in two stages. The first stage was the development of the method for recording the risk factors and the second stage was the development of the scoring system and action levels which provided a guide to the level of risk and need for action to conduct more detailed assessments.

Step 1: Development of the method for recording the risk factorThe development of the method for recording the risk factors comprising six physical risk

factors including posture, repetition, force, vibration, contact stress and task duration. For the posture and repetition risk factor, five body parts were determined for the posture which were the shoulder,

22 MOHD NASRULL ABD RAHMAN et al.

wrist, back, neck and leg. And force was determined by lifting the load (weighted in kg), vibration was determined by the number of hours per day for using the vibration tool while contact stress was determined by the using of a handle tool or wearing hand gloves and task duration was determined by the number of hours per day when performing a task or job.

Shoulder postureAntony and Keir (2010) carried out an empirical study on the influence of external factors such

as arm posture, hand loading and dynamic exertion on shoulder muscle activity and this provided insight into the relationship between internal and external loading of the shoulder joint. It was found that adding a 0.5 kg load to the hand increased shoulder muscle activity by 4% maximum voluntary excitation (MVE), across all postures and velocities during the performed isometric and dynamic shoulder exertions in three shoulder planes (flexion, mid-abduction and abduction) covering four shoulder elevation angles (30°, 60°, 90° and 120°) (Antony and Keir, 2010). A study by Bernard (1997) found that work involving repeated or sustained flexion of the arm of greater than 60° was associated with shoulder disorders.

Forward head posture may contribute to work-related neck and shoulder pain during loaded shoulder flexion while sitting (Weon et al., 2010). When working with the computer display, about the 10% increase in forward head posture from their relaxed sitting postures was noted with no significant changes in posture as a result of the time-at-work study (Szeto et al., 2002). Individuals with forward head and rounded shoulder posture displayed significantly greater scapular internal rotation, during both tasks as well as greater scapular upward rotation, anterior tilting during the flexion task when compared with the ideal posture group (Thigpen et al., 2010). In a study by Veiersted et al. (2008) on the biomechanical workload in the neck and shoulder region of female hairdressers, it was found that the hairdressers worked with their arms elevated 60° or more for approximately 13% of the total working time and 16% during the specific hairdressing tasks. McAtamney and Nigel Corlett (1993) have examined the score for the upper arm based on categorize of the angular ranges. For example, the score 1 corresponded to the 20° extension to 20° of flexion, score 2 for the extension greater than 20° or 20°-45° of flexion, score 3 for the 45°-90° of flexion and score 4 for the 90° or more of flexion (McAtamney and Nigel Corlett 1993; Hignett and McAtamney 2000).

Therefore, the WERA tool for the shoulder posture score was categorized in 3 different risk levels including a low risk level for the 20° extension to 20° of flexion, a medium risk level for the extension greater than 20° or 20°-45° of flexion and a high risk level for the 45°-90° or more than 90°of flexion. Three descriptive terms were chosen to categorize the risk level for the shoulder posture such as low risk level for the neutral position, medium risk level for the moderate bent up or hands at about the chest level and high risk level for the extreme bent up or hands at above the chest level.

Shoulder repetitionFrom the study by Bernard (1997) it has been found that highly repetitive shoulder/arm

movement increases the risk of shoulder tendon disorders. It was reported that shoulder movement frequencies greater than 2.5 per min were associated with WMSDs, however no further data on the frequency at which the level of risk increased significantly were reported (Kilbom 1994a,b). Further, the shoulder injury affects both wrist and elbow motions during hammering (Côté et al., 2005). The side-difference in shoulder muscle activity, which was dependent on the type of motion carried out, suggesting a qualitative difference in the activation of muscles during the two types of movement. Dynamic abduction has the characteristics of a dominant arm task (i.e., task performed almost exclusively by the dominant arm) and reduced muscle activity for the dominant side during abduction indicates a dominance-related advantage in arm dynamics (Diederichsen et al., 2007).

As a result, risk level in the WERA tool was based upon the movement pattern of the arm, rather than on the number of movements within a given period. This approach has been supported by other investigators (Latko et al., 1999; David et al., 2008). Three descriptive terms were used to categorize the risk level (such as light, moderate, and heavy). The low risk level indicated the light movement

OBSERVATIONAL TOOL TO INVESTIGATE PHYSICAL RISK FACTOR 23

with more pauses, medium risk level indicated moderate movement with some pauses and high risk level indicated heavy movement with no rest.

Wrist postureBernard(1997) has reported that awkward wrist/hand posture is a risk factor for the development

of wrist disorders, especially in combination with other factors such as force, repetition and duration. Carey and Gallwey (2002) in their empirical research found that the extreme flexion caused higher discomfort than the other simple types of deviation, and the combination of flexion and ulnar deviation resulted in higher discomfort than the other types of combined deviation. Wrist posture changes from neutral to 35% increased discomfort, but combinations of deviated postures increased discomfort by up to 70% (Khan et al., 2010). Mogk and Keir (2008) have emphasized that tunnel alignment reduced the average carpal tunnel area and depth by nearly 15% in extension, but generally less than 5% in neutral and 2% in flexion. Subsequently, tunnel alignment also decreased carpal tunnel and non-circularity ratios to reveal a flatter, more elliptical shape throughout the tunnel in extension than in neutral and flexion (Mogk and Keir 2008).

In another study by Chen et al. (2006), it was reported that the interaction between wrist flexors contraction and joint position was significant only in the wrist flexion position while joint position exerted a powerful influence on length-tension regulation in multi articulate wrist flexors, three wrist positions (neutral, flexion and extension) and four levels of flexor contraction. McAtamney and Nigel Corlett (1993) have examined the score for the wrist posture based on categorization of the angular ranges. For example, the score 1 was for in neutral position, score 2 for the 0- 15° in either flexion or extension and score 3 for the 15° or more in either flexion or extension (McAtamney and Corlett, 1993; Hignett and McAtamney, 2000).

Therefore, the prototype of the WERA tool for the wrist posture score was categorized in 3 different risk levels in which low risk level was for the 0° neutral position, medium risk level for the 0°- 15° in either flexion or extension and high risk level for the 15° or more in either flexion or extension. Three descriptive terms were used to categorize the risk level for the wrist posture such as low risk level for the neutral position, medium risk level for the moderate bent up or bent down and high risk level for the extreme bent up or bent down.

Wrist repetitionArvidsson et al. (2003) have stated that the frequency of musculoskeletal disorders was high,

especially for the right wrist/hand. Although the work was non-forceful and there were minor extreme positions in the wrists, the results are consistent with reported exposure-response relations in other high-risk jobs. Thus, the repetitiveness and the high velocities are the likely causes for the high prevalence of disorders in the wrists/hands (Arvidsson et al., 2003). The maximum acceptable force for wrist extension with a pinch grip is smaller than any of the other motions investigated so far (Snook et al., 1999). For occupational repetitive work, 99.5% of the signal power was contained in the 0-5 Hz band. Two-dimensional angle distributions and power spectra gave comprehensive information about wrist postures and movements. Measures reflecting both static and dynamic properties were derived from time and frequency domains (Hansson et al., 1996).

Therefore in the WERA tool for wrist repetition is assessed by the number of times a similar motion pattern is repeated each time. Three descriptive terms were used to categorize the risk level such as less than 10 times per minute for the low risk level, 11 to 20 times per minutes for the medium risk level, and more than 20 times per minutes for the high risk level. This item was adopted from the Quick Exposure Check (QEC) assessment (David et al., 2008).

Back postureMork and Westgaard (2009) have emphasized that back posture moderately influenced

electromyographic activity, accounting for 19% (sitting) to 38% (standing) of intra-individual variation in muscle activity. It was found that interpretation low back muscle activity was very low

24 MOHD NASRULL ABD RAHMAN et al.

during seated posture, presumably due to the flexion-relaxation phenomenon (Mork and Westgaard 2009). A study by O'Sullivan et al., (2006) has found that relationship may exist between flexed spinal postures, reduced back muscle endurance, physical inactivity and low back pain in industrial workers with a reported history of flexion strain injury and flexion pain provocation. Trunk flexion variables including peak level, peak velocity, average velocity indicators, and percent time in flexion category indicators showed significant differences between cases and controls in the relationship to low back pain (Neumann et al., 2001a). The work and posture sampling approach is particularly useful for heterogeneous work situations where traditional task analysis is difficult and can provide information on work and tissue load parameters which have been directly associated with risk of reporting low-back pain (Neumann et al., 2001b)

Therefore in the WERA tool, back posture categories were defined as 0°-20°, 21°-60° and more than 60°, as used in other assessment tools (McAtamney and Corlett, 1993; Hignett and McAtamney, 2000; David et al., 2008). Three descriptive terms were chosen to categorize the risk level for the back posture such as low risk level for the neutral position, medium risk level for the moderate bent forward and high risk level for the extreme bent forward.

Back repetitionBernard (1997) has stated that the increased risk of low back pain was associated with increased

frequency of back movement when carrying out manual handling tasks. Back movement, but not pain or depression, was associated with greater repetition-induced summation of pain (Sullivan et al., 2009). In a study by Beach et al. (2006), it was reported that upper limb kinematic adaptations to precision placement constraints in repetitive lifting may alter the risk of reporting low back pain. Dolan and Adams (1998) have concluded that repetitive lifting induces measurable fatigue in the erector spine muscles, and substantially increases the bending moment acting on the lumbar spine. The QEC assessment by David et al. (2008) categorized back movement frequency into three exposure levels including ‘infrequently’ (around 3 times/min or less), ‘frequently’ (around 8 times/min), ‘very frequently’ (around 12 times/min or more). Therefore in the WERA tool for the back repetition is assessed by the number of times a similar motion pattern is repeated each time. Three descriptive terms were used to categorize the risk level such as 1-3 times per minute for the low risk level, 4-8 times per minutes for the medium risk level, and 9-12 times per minutes for the high risk level.

Neck posture and repetitionPast research on work-related musculoskeletal disorders (WMSD) has frequently examined

the activity of neck-shoulder muscles such as the upper trapezius (UT) and cervical erector spinal (CES) during typing tasks (Yuk et al., 2009). Neck pain is a common problem for adolescents and posture has been suggested as an important risk factor (Straker et al., 2009). Prolonged computer work with the extended neck is commonly believed to be associated with an increased risk of neck-shoulder disorders (Arvidsson et al., 2008). A study conducted by Burgess et al.(1999) has founded that lowering the monitor to a position 18° below eye level had no significant effect on the position of the neck relative to the trunk, while the mean flexion of the head relative to the neck increased by 5°. Awkward working posture at the trunk, neck and shoulders may be caused by a number of factors, including: workstation layout, visual demands of the job, design of equipment and tools, and work methods (Keyserling et al., 1993). Keyserling et al. (1992) in their empirical research found that the awkward postures of the trunk and neck were common, occurring in more than 70 percent of the jobs. If arm and wrist supports are effective in reducing the workload, they might be of use as preventive measures to reduce the risk of neck-shoulder complaints (Visser et al., 2000). Nimbarte et al. (2010) have indicated that the neck muscles play an active role during lifting and holding tasks at shoulder height. McAtamney and Corlett (1993) have examined the score for the neck posture based on categorization of the angular ranges. For example, the score 1 was stand for 0°-10° of flexion, score 2 for the 10°- 20° of flexion, score 3 for the 20° or more of flexion and score 4 for in extension.

Therefore, the prototype of the WERA tool for the neck posture score was categorized in 3

OBSERVATIONAL TOOL TO INVESTIGATE PHYSICAL RISK FACTOR 25

different risk levels including low risk level for the 0°-10° of flexion, medium risk level for the 10°-20° of flexion and high risk level for the 20° or more either flexion or extension. Three descriptive terms were chosen to categorize the risk level for the neck posture such as low risk level for neck in the neutral position with a little bent forward, medium risk level for the moderate bent forward and high risk level for the extreme bent forward or bent back. For the neck repetition, three descriptive terms were used to categorize the risk level such as light, moderate, and heavy. The low risk level indicated the light movement with more pauses, medium risk level indicated moderate movement with some pauses and high risk level indicated heavy movement with no rest.

Leg posture A study by Shinya et al. (2009) demonstrated that asymmetric loading is a simple biomechanical

factor that determines the time needed to initiate a subsequent lift-one-leg task. An increase in gravitational force has more impact on leg posture (Fong et al., 2009). Lower leg amputation generally induces asymmetrical weight-bearing (Duclos et al., 2009). In another study by Talis et al. (2008) it was stated that when performing maximal voluntary contractions, or during walking and quiet standing, the inter-limb difference in the maximal force production, stance/swing phase durations or weight bearing was typically less than 10%. Asymmetric leg loading in patients can be critical during sit-to-stand maneuver in comparison with quiet standing and walking, and visual information seems to play only a minor role in the control of the weight-bearing ability (Talis et al., 2008). Starting hip flexion was greater for controls and starting knee flexion was greater for patients, indicating that patients used more of a leg lift (Rudy et al., 2003). Hignett and McAtamney (2000) have examined the score for the leg posture based on categorization of the angular ranges. For example, the score 1 was for bilateral weight bearing or walking or sitting, score 2 for the unilateral weight bearing with unstable posture and plus 1 if the knees between 30° and 60° of flexion or plus 2 if the knees are more than 60° of flexion.

Therefore, the WERA tool for the leg posture score categorized 3 different risk levels including low risk level for the 0° in neutral position, medium risk level for the 30°- 60° of flexion and high risk level for the more than 60° of flexion. Three descriptive terms were chosen to categorize the risk level for the leg posture such as low risk level for leg in the neutral position, medium risk level for the moderate bent forward and high risk level for the extreme bent forward.

ForceA study conducted by Faber et al. (2009) has found that the manual lifting was considered an

important risk factor for the occurrence of low-back pain. Splitting a load, so it can be lifted beside the body (one load in each hand), instead of in front of the body, is expected to reduce low-back load (Faber et al., 2009; Rahman et al., 2010). Weight lifting and other forms of strength training are becoming more common because of an increased awareness of the need to maintain individual physical fitness (Busche, 2008). Karnezis (2005) has suggested that the wrists characterized by a low angle may be subjected during lifting activities to maximum joint reaction forces up to 50% higher than those in the wrists with a high tilt and emphasizing the importance of accurate restoration of the tilt during treatment of all distal radius fractures. A study by Dennis and Barrett (2003) has emphasized that when lifting an unevenly balanced load a two-person lifting team seems to adopt a lifting strategy that partially alleviates the larger spinal loads experienced by the team member at the heavier end of the load. Lifting a 20-kg split-load instead of a 20-kg single-load resulted in most cases in a reduction (8-32%) of peak L5/S1 compression forces (Faber et al., 2009). Prevention of work-related low back pain during phases of technological change should involve employees in planning and implementation (Elfering et al., 2010).

Therefore, the WERA tool for the forceful score was categorized in 3 different risk levels including low risk level for the load in 0-5kg, medium risk level for the load in 6-10kg and high risk level for the load more than 11kg. This approach has been used by other researchers, for example in RULA assessment, 3 levels, 0-2kg, 2-10kg, >10kg (McAtamney and Corlett, 1993; Hignett and

26 MOHD NASRULL ABD RAHMAN et al.

McAtamney, 2000) and QEC assessment, 4 levels, 0-5kg, 6-10kg, 11-20kg, >20kg (David et al., 2008).

VibrationThere are several occupational illnesses related with vibration transmission from power hand

tools to the hand-arm system (Besa et al., 2007). International standards have been developed to evaluate the risk of injury after exposure to this kind of vibrations; nevertheless, the current standards recognize that some aspects need to be investigated, such as the influence of vibration transmission direction, arm posture or hand grip force (Besa et al., 2007). Tool grip and push forces are important determinants of health risk associated with operation of powered hand tools (McDowell et al., 2006). In a study by Necking et al. (2004) it has been indicated that the vibrating tools may cause direct damage to muscle fibres as well as nerves. Prolonged exposure to hand-transmitted vibration has been related to an array of health disorders of the vascular, nervous and musculoskeletal systems in the upper extremity (Dong et al., 2003). Burström and Sörensson (1999) have found that the vibration response characteristics of the hand and arm differ, depending upon whether the exposure is of shock or non-impulsive type. In another study by Cherng et al. (2009) they conclude that by applying the design principles of ergonomics and by adding vibration damping/isolation mechanisms to the rivet tools, the vibration level can significantly be reduced and the tools become safer and user-friendly.

Therefore, the WERA tool for the vibration score was categorized in 3 different risk levels which are low risk level for never used of vibration tool , medium risk level for the occasional used of vibration tool and high risk level for the constant used of vibration tool. This practical approach has been applied for observational method that ask workers about their using of vibration tool in workplace (David et al., 2008).

Contact stress The use of hand tools is linked with many cumulative trauma disorders of the upper extremity

(Chaffin et al., 2006). The contact force for a given handle size can be expressed as a linear combination of grip and push forces, where the contribution of the grip force is considerably larger than that of the push force (Welcome et al., 2004). Brookham et al. (2010) have suggested that in order to reduce risky levels of inferior trapezius activation, light hand tool tasks such as drilling should be performed at neutral elevation and -45° internal rotation, or for slightly higher activations but still low risk at 60° shoulder flexion and -45° internal rotation. A study conducted by Woon et al. (2008) on the effects of tool edge radius on the frictional contact, has found that the flow stagnation during material separations could be attributed to the counterbalance of shear contact components. The distribution of pressure and the contact force in the hand-handle interface as a function of the handle size could lead to advancement of knowledge on the handle size issue (Aldien et al., 2005). For grasp tasks, the results indicate that hand size is critical when the external force requirement is constant, while there is an interaction between hand size and strength when it varies (Hall, 1997).

Therefore, the WERA tool for the contact stress score was categorized in 3 different risk levels which are low risk level for non-use of hand tool, medium risk level for the soft or round shape of the tool handle and high risk level for the hard or sharp from or without a tool handle.

Task durationBernard (1997) has stated that task duration is a risk factor for WMSDs of the back, shoulder/

arm, hand/wrist and neck. VaezMousavi et al. (2009) have explored the relationships between physiological response magnitudes, behavioural performance measures, current arousal level, and activation (defined as task-related change in arousal) during a continuous performance task. The tasks did not differ in terms of total task time, yet significant differences were found by using the occlusion paradigm and subjective workload ratings (Noy et al., 2004). The OSHA ergonomic standard (2000) has defined more than 2 consecutive hours per work day as critical in combination with other risk factors. When daily time exceeds 4 hours, the rates of WMSDs increase in the back and shoulder/neck especially in seating task (Winkel and Westgaard 1992). Gorelick et al. (2003) have suggested

OBSERVATIONAL TOOL TO INVESTIGATE PHYSICAL RISK FACTOR 27

that intense short-duration tasks, which may differentially target the back and its musculature, could leave the spine susceptible to increased risk of injury. Therefore, the WERA tool for the task duration score was categorized in 3 different risk levels including are low risk level for less than 2 hours, medium risk level for 2-4 hours and high risk level for more than 4 hours. This item was adopted from the QEC assessment (David et al., 2008).

Step 2: Development of the scoring system and action levelFrom the scientific literature review suggest that the risk factors should be considered in

combination with each other. Several epidemiology studies have indicated that the combination of two risk factors resulted in a higher magnitude of work-related musculoskeletal disorders (WMSDs) rate rather than a single risk factor assessed. For the example, combinations of high levels of force and high levels of repetition on hand/wrist symptoms (Ciriello et al., 2001), combinations of posture, frequency of lifting, and load on low back pain (Marras et al., 1995) and combinations of physical and psychosocial factors on the development of neck and upper limb disorders (Devereux et al., 2002).

On the basis of this principle, the scoring system for the WERA tool has been formulated (Table 1). All the physical risk factors were measured by combination of two items (Table 2). For example, the posture combination with repetition for the shoulder, wrist and the back body region and the posture combined with task duration for the neck and leg body region. Combination between force and wrist posture were also included in this assessment. To give a high level sensitivity for the

Table 1. Combination of risk level, score and indicator.

Combination of risk level Score Indicator

Low vs. Low 2 Low risk level for score of 2-3 Low vs. Medium 3

Low vs. High 4 Medium risk level for score of 4 Medium vs. Medium 4

Medium vs. High 5 High risk level for score of 5-6 High vs. High 6

Table 2. Score for combination of physical risk factor and total score for risk level.

WERA items Combination of risk factor Risk level Score

Low Medium High Shoulder 1a. Shoulder posture vs.

1b. Shoulder repetition 2-3 4 5-6

Wrist 2a. Wrist posture vs. 2b. Wrist repetition

2-3 4 5-6

Back 3a. Back posture vs. 3b. Back repetition

2-3 4 5-6

Neck 4a. Neck posture vs. 4b. Neck repetition

2-3 4 5-6

Leg 5a. Leg posture vs. 9. Task duration

2-3 4 5-6

Forceful 6. Forceful vs. 3a. Back posture

2-3 4 5-6

Vibration 7. Vibration vs. 2a. Wrist posture

2-3 4 5-6

Contact stress 8. Contact stress vs. 2a. Wrist posture

2-3 4 5-6

Task duration 9. Task duration vs. 6. Forceful

2-3 4 5-6

Total score for risk level 18-27 28-44 45-54

28 MOHD NASRULL ABD RAHMAN et al.

vibration, the combination with wrist posture was included. As in the case of the vibration sensitivity, the contact stress was also combined with the wrist posture. Finally, the total score was calculated based on the total number of nine risk factors that were combined for each other to get the final score and action level (Table 3).

Stage 2a: Psychometric properties – validity testing The total mean age of the samples (n=130) were 33.17 years (SD=5.42) in the range between 21

and 44 while the total mean working experiences were 6.44 years (SD=2.16) in the range between 2 and 12. The total working hours per day ranged from 8 to 9 hours (mean 8.67 ± 0.58). Table 4 shows the demographics of the workers in the home building industry.

In wall plastering job (n=43), the relationship of the individual WERA body part scores to the development of pain or discomfort is statistically significant for the wrist, shoulder and back regions. The wrist score for WERA body part was >4 in 86% of workers, while wrist pain or discomfort was reported by 86%, yielding a significant association between WERA body part score and self-reported pain (χ2=16.12; p =0.000). The WERA body part score for the shoulder regions during wall plastering job yielded a score >4 in 93% and caused shoulder pain or discomfort in 91%, the association being significant (χ2 =12.58; p =0.000). The back regions for WERA body part score was >4 in 91% of workers, with 98% reporting pain or discomfort in the back regions, with a significant association (χ2 =9.98; p =0.002). The neck score for WERA body part was 1-3 in 86% of workers, this score corresponds to the most neutral posture (standing position with hand below the waist). As neck pain or discomfort was reported by 70%, there was no association between WERA score and neck pain (χ2

=0.032; p =0.858). Similarly, no association was found in leg score for WERA tool and reported pain or discomfort in those regions. Table 5 shows the chi square statistical analysis (χ2 -test) of WERA body-part score and number of workers reporting pain, ache or discomfort in the wall plastering job.

In the bricklaying job (n=42), the relationship of the individual WERA body part scores to the development of pain or discomfort is statistically significant for the wrist, shoulder and back regions. The wrist score for WERA body part was >4 in 93% of workers, while wrist pain or discomfort was reported by 98%, yielding a significant association between WERA body part score and self-reported pain (χ2=13.32; p =0.000). The WERA body part score for the shoulder regions during bricklaying job yielded a score >4 in 90% and caused shoulder pain or discomfort in 98%, the association being significant (χ2 =9.37; p =0.002). The back regions for WERA body part score was >4 in 86% of workers, with 98% reporting pain or discomfort in the back regions, with a significant association (χ2 =6.15; p =0.013). The neck score for WERA body part was 1-3 in 86% of workers, this score

Table 3. Risk level, final score and action level or WERA tool.

noitcA erocs laniFlevel ksiRLow 18-27 Task is accepted Medium 28-44 Task is need to further investigate and require change High 45-54 Task is not accepted, immediately change

Task Age (year)

Working Experience(year)

Working per day (hours)

Mean SD Range Mean SD Range Mean SD RangeWall plastering (n=43) 32.67 5.85 2-12 6.28 2.33 20-44 8.67 0.58 8-9

Bricklaying (n=42) 33.36 5.42 2-12 6.52 2.16 20-44Floor concreting (n=45) 33.47 5.00 2-12 6.51 1.98 23-44

Total (n=130) 33.17 5.42 2-12 6.44 2.16 21-44

Table 4. Demographics of the workers in the home building industry (n=130).

OBSERVATIONAL TOOL TO INVESTIGATE PHYSICAL RISK FACTOR 29

corresponds to the most neutral posture (standing position with hand below the waist). As neck pain or discomfort was reported by 48%, there was no association between the WERA

score and neck pain (χ2 =1.02; p =0.313). Similarly, no association was found in leg score for the WERA tool and reported pain or discomfort in those regions. Table 6 shows the chi square statistical analysis (χ2 -test) of the WERA body-part score and the number of workers reporting pain, ache or discomfort in bricklaying job.

In floor concreting job, the relationship of the individual WERA body part scores to the development of pain or discomfort is statistically significant for the shoulder, back and wrist regions. The shoulder score for WERA body part was >4 in 87% of workers, while shoulder pain or discomfort was reported by 84%, yielding a significant association between WERA body part score and self-reported pain (χ2=13.77; p =0.000). The WERA body part score for the back regions during floor concreting job yielded a score >4 in 80% and caused back pain or discomfort in 91%, the association being significant (χ2 =11.81; p =0.001). The wrist regions for WERA body part score was >4 in 84% of workers, with 82% reporting pain or discomfort in the wrist regions, with a significant association (χ2=11.32; p =0.001). The neck score for WERA body part was 1-3 in 84% of workers, this score corresponds to the most neutral posture (standing position with hand below the waist). As neck pain or discomfort was reported by 73%, there was no association between WERA score and

Table 5. Chi-square statistical analysis (χ2-test) of the WERA body part scores (Low or >Medium) and the reported pain, ache or discomfort in the wall plastering job.

Body part Pain WERA score χ2 p < .05 1-3 >4

Shoulder No Yes

2 1

2 38

12.58 0.000

oN tsirWYes

4 2

2 35

16.12 0.000

oN kcaBYes

1 3

0 39

9.98 0.002

oN kceNYes

11 26

2 4

0.032 0.858

oN geLYes

12 28

1 2

0.015 0.903

χ2 -analysis of WERA body-part score and number of workers reporting pain, ache or discomfort in that region. The presence of pains, aches or discomfort was recorded as “pain”, their absence as “no pain”. For the WERA score, all the body part were scores either in 1-3 (Low), 4 (Medium) or 5-6 (High) for the risk level.

Table 6. Chi-square statistical analysis (χ2-test) of the WERA body part scores (Low or >Medium) and the reported pain, ache or discomfort in bricklaying job.

Body part Pain WERA score χ2 p < .05 1-3 >4

Shoulder No Yes

1 3

0 38

9.73 0.002

oN tsirWYes

1 2

0 39

13.32 0.000

oN kcaBYes

1 5

0 36

6.15 0.013

oN kceNYes

20 16

2 4

1.02 0.313

oN geLYes

15 21

2 4

0.15 0.700

χ2 -analysis of WERA body-part score and number of workers reporting pain, ache or discomfort in that region. The presence of pains, aches or discomfort was recorded as “pain”, their absence as “no pain”. For the WERA score, all the body part were scores either in 1-3 (Low), 4 (Medium) or 5-6 (High) for the risk level.

30 MOHD NASRULL ABD RAHMAN et al.

neck pain (χ2 =0.015; p =0.901). Similarly, no association was found in leg score for the WERA tool and reported pain or discomfort in those regions. Table 7 shows the chi square statistical analysis (χ2-test) of the WERA body-part score and number of workers reporting pain, ache or discomfort in floor concreting job.

Stage 2b: psychometric properties – reliability and usability testingThe total mean age of the observers (n=33) was 32.72 years (SD=4.13) in the range between 22

and 41 while the total mean working experiences were 4.57 years (SD=1.26) in the range between 2 and 9. Table 8 shows the demographics of the observes involved in training session.

Table 8. Demographics of the observers in training session (n=33).

Inter observer reliability testingThe test results for the inter-observer reliability of the prototype of WERA assessment are shown

in Table 9. When considering the assessment results of all 33 observers assessing all three tasks, their agreement on the assessment items were low as evaluated by kappa analysis, ranging between K=0.30-0.34 (for the shoulder, wrist, back, neck and leg items). According to Altman (1991), the strength of agreement for all these assessment items can be regarded as “fair agreement” (K=0.21-0.40). This is because the observers found that difficult to observe and defined angular ranges when assessing the posture of five body parts including the shoulder, wrist, back, neck and legs regions. The 33 observers assessment on forceful score, vibration and contact stress items were resulted in a higher kappa value (K=0.49-0.51) suggesting a “moderate agreement” among the observers. And the overall assessments of the task duration item was resulted in a higher kappa value (K=0.60) suggesting a “good agreement”. The value of kappa between 0.81 and 1.00 were considered ‘very good’, 0.61–0.80 ‘good’, 0.41–0.60 ‘moderate’, 0.21–0.40 ‘fair’, and less than 0.20 ‘poor’(Altman, 1991).

egA srevresbo fo puorG(year)

Working experience (year)

Mean SD Range Mean SD Range Management team (n=23) 33.04 5.00 22-41 5.35 1.61 3-9 Expert team (n=10) 32.40 3.27 27-37 3.80 0.92 2-5

9-2 62.1 75.4 14-22 31.4 27.23 )33=n( latoTNote: Management team – managers / officers, etc. and Expert team – safety and health officers (SHO)

Table 7. Chi-square statistical analysis (χ2-test) of the WERA body part scores (Low or >Medium) and the reported pain, ache or discomfort in floor concreting job.

Body part Pain WERA score χ2 p < .05 1-3 >4

Shoulder No Yes

4 2

2 36

13.77 0.000

oN tsirWYes

4 2

4 35

11.32 0.001

oN kcaBYes

3 4

1 37

11.81 0,001

oN kceNYes

10 28

2 5

0.015 0.901

oN geLYes

14 25

2 4

0.015 0.903

χ2 -analysis of WERA body-part score and number of workers reporting pain, ache or discomfort in that region. The presence of pains, aches or discomfort was recorded as “pain”, their absence as “no pain”. For the WERA score, all the body part were scores either in 1-3 (Low), 4 (Medium) or 5-6 (High) for the risk level.

OBSERVATIONAL TOOL TO INVESTIGATE PHYSICAL RISK FACTOR 31

Usability testingFrom the feedback questionnaire survey about the usability of the WERA tool for all participants

(n=33) including expert teams and management team using ratings (1=strongly disagree, 5=strongly agree) indicated that the prototype of the WERA tool was easy to use (mean 3.94 ± 0.93), quick to use (mean 3.88 ± 1.02), applicable to workplace assessment (mean 3.64 ± 1.11), applicable in a wide range of job/task (mean 3.58 ± 1.06) and valuable at work (mean 3.85 ± 1.06). The observers confirmed that there was no need of training to do WERA assessment when they rated low (mean 2.36 ± 1.58) for the item of training required to do assessment. This was because the WERA tool was rated as quick and easy to use among the observers. In the WERA tool for the scoring system item, they confirmed that the scoring system was useful for determining the risk level (mean 4.03 ± 0.68) colour coding was useful for risk level (mean 3.88 ± 0.65) and final score and action level were useful (mean 3.82 ± 0.85). Table 10 shows the observers ratings of feedback questionnaire of usability of the WERA tool.

Table 10. Observers ratings of feedback survey of WERA tool.

CONCLUSIONS

The Workplace Ergonomic Risk Assessment (WERA) was developed to provide a method of screening the working task quickly concerning exposure to the physical risk factors associated with work-related musculoskeletal disorders (WMSDs). The WERA assessment covers an extensive range of all physical risk factors including posture, repetition, forceful, vibration, contact stress and task

Table 9. Inter-observer reliability on assessment items as specified in the WERA.

)srevresbo 33( tnemeerga revresbo-retnI smeti AREW K* Overall K* Percentage agreement

(%) Task 1 Task 2 Task 3 Task 1-3 Shoulder 0.33 0.32 0.37 0.34 63.6

6.36 03.0 83.0 72.0 42.0 tsirW 6.06 13.0 13.0 43.0 72.0 kcaB 6.36 23.0 53.0 33.0 72.0 kceN

23.0 geL 0.32 0.30 0.31 63.6 8.48 94.0 84.0 54.0 45.0 lufecroF

Vibration 0.48 0.45 0.53 0.49 87.9 Contact stress 0.48 0.54 0.51 0.51 81.8 Task duration 0.68 0.58 0.53 0.60 84.8 Total Agreement (K*) 0.40 0.40 0.42 0.41 72.1 *K- Cohen’s Kappa coefficients was used to evaluate the inter-observer reliability. The value K: 0.0-0.19 are poor level agreement, 0.2-0.39 are fair level agreement, 0.4-0.59 are moderate level agreement, 0.6-0.79 are good level agreement and 0.8-1.0 are very good level agreement.

serocs gnitaR snoitseuQ Total score 1 2 3 4 5 Mean (SD)

1. )39.0( 49.3 722-31 drawrofthgiarts/esu ot ysaE2. )20.1( 88.3 891141 esu ot kciuQ3. Applicable to workplace assessment 2 5 1 20 5 3.64 (1.11) 4. Applicable in wide range of job/task 2 5 1 22 3 3.58 (1.06) 5. )97.0( 58.3 362121 )evitceffe tsoc( krow ta elbaulaV6. Need training required to do assessment 17 3 - 10 3 2.36 (1.58) 7. Scoring system (Ratings- low, medium, high) - 2 1 24 6 4.03 (0.68) 8. Scoring system (Colour- green, yellow, red) - 3 - 28 2 3.88 (0.65) 9. Scoring system (Final score- low, medium, high) 1 3 - 26 3 3.82 (0.85)

Note: Ratings scale range from 1=strongly disagree to 5= strongly agree.

32 MOHD NASRULL ABD RAHMAN et al.

duration. All the physical risk factors involved the five main body regions (shoulder, wrist, back, neck and leg) that have been identified associated with work-related musculoskeletal disorders (WMSDs) following an extensive review of the scientific literature. In the validity trials, the relationship of the individual WERA body part scores to the development of pain or discomfort is statistically significant for the wrist, shoulder and back regions. It shows that the WERA assessment provided a good indication of work-related musculoskeletal disorders which might be reported as pain, ache or discomfort in the relevant body region. In the reliability and usability trials, the results of inter-observer reliability shows that moderate agreement among the observers (K=0.41) while from the feedback questionnaire survey about the usability of WERA tool, all participants including expert and management teams agreed that the prototype of WERA tool was easy and quick to use, applicable to workplace assessment for the wide range of job/task and valuable at work. The observers confirmed that there was no need of training to do WERA assessment. Therefore, the WERA assessment has been designed for easy and quick use, and for those who are trained to use it do not need previous skills in observation techniques although this would be an advantage. As WERA is a pen and paper technique that can be used without any special equipment, WERA assessment can be done in any space of workplaces without disruption to the tasks that have been observed. Appendix 1 and 2 shows the Workplace Ergonomic Risk Assessment (WERA) tool.

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Appendix 1. Workplace Ergonomic Risk Assessment (WERA) Part A (No 1-5).

36 MOHD NASRULL ABD RAHMAN et al.

Appendix 2. Workplace Ergonomic Risk Assessment (WERA) Part B (No 6-9).

Based on WERA: An observational tool develop to investigate the physical risk factor associated with work-related musculoskeletal disorders,

Mohd Nasrull Abdol Rahman, Mat Rebi Abdul Rani and Jafri Mohd Rohani, Journal of Human Ergology, Year, Vol. (X), xxx-xxx