Offera: A method for evaluating office risk factors of work-related musculoskeletal disorders (WMSDs)

Abstract

Background

Office risk factors linked to work-related musculoskeletal disorders (WMSDs) are frequently evaluated using ergonomic risk assessment tools.

Objective

This study aimed to explore the office risk factors linked to work-related musculoskeletal disorders (WMSDs) by developing an Office Ergonomic Risk Assessment (OFFERA) method.

Methods

The development and evaluation of OFFERA method, divided into two stages which include the development of OFFERA system components and psychometric properties of OFFERA method.

Results

In the reliability testings, observers showed strong agreement both between different observers (K = 0.62–0.78) and when the same observer repeated their measurements (K = 0.81–0.96). In the validity testings, the relationship between the final score of OFFERA and the musculoskeletal symptoms is statistically significant for the wrists/hands, lower back, knees, and ankle/leg.

Conclusion

Tests have demonstrated that the OFFERA approach can be easily used across many different types of office work.

Keywords

observational method workplace assessment risk assessment computer work reliability validity

Introduction

The prevalence of musculoskeletal disorders (MSDs) in office environments underscores the significance of ergonomics in the modern workplace.¹ This issue is of particular concern, as MSDs pose a significant risk not only to the physical well-being of affected individuals but also to their professional productivity and the broader societal implications.^1,2 Musculoskeletal disorders are a type of disorder in which the occurrence of injuries involves the muscles, bones, nerves, tendons, ligaments, joints, and spinal disc.³ Besides that, the past studies have found that the back, shoulders, neck, arms, and hands are the most affected body parts associated with computer work. This is because previous studies have discovered that the chairs used by office workers are often related to muscle disorders.^4,5 Inappropriate posture, such as an awkward posture and prolonged sitting, as well as movement retained over several hours of work, including repetitive motions like typing or clicking, are common causes of health issues associated with WMSDs in computer users.^1–4 The use of computers in occupations like customer service, sales, and offices has skyrocketed as a result of recent advancements in information technology.^5–8

In order to evaluate risk factors for WMSDs, a number of techniques have been developed to evaluate posture.⁹ The most widely used technique for evaluating WMSDs is an ergonomic risk assessment tool.^9,10 There are six ergonomic risk assessment tools that are commonly used to identify office workstation-related work musculoskeletal disorders (WMSDs) such as Rapid Upper Limb Assessment,¹¹ Rapid Entire Body Assessment,¹² Composite office ergonomic risk assessment,¹³ Quick Exposure Checklist,¹⁴ Assessment of Repetitive Tasks¹⁵ and Rapid Office Strain Assessment.¹⁶ However, despite examining six previously assessed tools, several gaps identified.^17,18 For example, most of the tools did not cover the wide range of risk factors found in the office workplace, which includes office components and office environments.¹⁹ There were also not testing the validity and reliability testing the development process.^17–20 Therefore, this study aimed to explore the office risk factors linked to work-related musculoskeletal disorders (WMSDs) by developing an Office Ergonomic Risk Assessment (OFFERA) method.

Aims

The development of OFFERA aim to

The OFFERA method was developed to evaluate the exposure of individual worker at office workstations to ergonomic risk factor associated with MSD.

This tool also assesses the level of risk for worker at office workstation.

This worksheet is used to evaluate required or selected office component (including body posture) and the office environment.

The OFFERA method is generally used to assess workers who are often in a sitting position and those who mainly use their upper body and arms during work.

The OFFERA method was designed to be user-friendly without the need for expensive equipment. To perform the assessment of office workers exposed to ergonomic risk factors linked to WMSD, non-experts require very little training.

Application of OFFERA at the workplace

OFFERA may be utilized when an ergonomic workplace assessment indicates the necessity for additional analysis and:-

The entire body posture is engaged.

Posture can be characterized as static, dynamic, subject to rapid changes, or unstable.osture is static, dynamic, rapidly changing or unstable

The primary use of OFFERA is to assess musculoskeletal risk, typically within the context of a more comprehensive ergonomic analysis and then :-

Compare the effects of current and modified workstation design

Analyze results like equipment suitability or productivity.

Inform employees about the risks to their musculoskeletal system posed by various work postures.

Development and evaluation of OFFERA method

The development and the evaluation of OFFERA method, divided into two stages which include the development of OFFERA system components and psychometric properties of OFFERA method. The first stage includes a review of the current techniques of observational method; identification of the domains and items, selection of the items; specification and rating scores for each item; generation of OFFERA final score and action level; establishment of the form format and instructions and the prototype of OFFERA method. Meanwhile second stage explains the details of the psychometric properties where presents the details of the training session to test the reliability of OFFERA method and a pilot test for the validity of OFFERA method including generation of the final version of OFFERA method. Figure 1 shows the overall development and evaluation process of the OFFERA method.

Figure 1.

The development yand evaluation process of office ergonomic risk assessment (OFFERA) method.

Stage 1: development of OFFERA system components

Six steps were performed to develop OFFERA system components, namely identification of the domain and items, selection of the items, specifications and the rating score assigned for each item, generation of the final score and action level, establishment of the form format and instructions, and the establishment of OFFERA prototype.

Identification of the domains and items

Publication materials from 2020 until 2024 were searched from AMED, CINAHL, Scopus, ProQuest and PubMed. From previous literature, various terms or keywords determined the domains and items for the risk factors of office workstation related to musculoskeletal disorders (WMSDs). For example, office components, working posture, office environments, computer work, musculoskeletal diseases, and physical. This study identified the risk factor available at the office workstation involving ergonomic problems. From the literature review, six domains and nineteen items for the assessment of risk factors of WMSDs among office workers were identified as shown in Figure 2.

Figure 2.

Identification of the OFFERA items and parameters.

According to the guidelines, 30 papers were chosen as possible reference materials out of 89 documents that met the specified criteria. It was discovered from the literature that, seat pan domains has four items, namely seat pan height, seat pan depth, backrest, and armrest, while the desk domain has two items which are desk depth and desk height. The monitor has two items which are monitor angle and monitor distance. On the other hand, the device input domain consists of three items, which are keyboard, mouse position, and mouse size, and the accessories domain consist of telephone, document holder, keyboard wrist rest, mouse wrist rest, and footrest. Lastly, the environment domain has three items which are lighting, temperature, and noise.

Selection of the items

The selection of each item was determined based on the assessment of the level of evidence and the strength of association. There are three categories for strength of association: first, the statistically insignificant positive association (p > 0.05) or Odd Ratio (OR < 1.00) or 95% of Confidence Interval (95% CI ≤ 1.00). Second, the moderate association with OR between 1.01 and 2.00 or (0.01 < p < 0.05), and the last one, the strong association where OR > 2.00 or (p < 0.01). Therefore, the selection of each item was based on the moderate and strong association measured by the OR and 95% CI value. The eighteen items for the risk factors of work-related musculoskeletal disorders among office workers selected. The items are from chairs (4 items), desks (2 items), monitors (2 items), devices input (3 items), accessories (4 items) and environments (3 items). These items are seat pan height, seat pan depth, backrest, armrest, desk height, desk depth/width, monitor angle, monitor distance, keyboard position, mouse positioned, mouse size, telephone, document holder, wrist rest for keyboard and mouse, lighting, temperature, and noise.

Specification and assigning rating scores

After the items selected were finalised, the specifications were made and the rating scores were assigned. This step utilized two types of scale, namely nominal scale and category scale. Nominal scale allows the subjects to be assigned into two categories. Similarly, categories scale assigns the subject in group. Rating scores are assigned to each item's range of scale based on criteria derived from the interpretation of pertinent literature. When working posture or range of motion have minimal or neutral risk factors, they receive a score of zero. Parts of the movement with more extreme posture are assigned higher numbers, suggesting the presence of risk factors that put strain on the body segment's structure. Every body part posture has a scoring system that gives a logical and memorable number sequence.

Generation of OFFERA final score and action level

The generation of OFFERA scoring system has been divided into two sections, the final score of OFFERA scoring system and OFFERA action level. The development of the final scoring system used the sum scores of the weighted items. In addition, based on the previous studies,^17–20 the eligible observational method such as RULA, REBA, and QEC uses the metric of sum score of the weighted item in producing their final score. The risk factors for each item started from 0 indicating low risk. OFFERA scoring system was divided into two parts: sub score 1 and sub score 2. Sub score 1 covers: Score A (seat pan height + seat pan depth + backrest + armrest); Score B (desk height + desk depth); and Score C (keyboard + mouse position + mouse size). Sub score 2 covers: Score D (monitor angle + monitor distance); Score E (telephone + document holder + keyboard wrist rest + mouse wrist rest); and Score F (lighting + temperature + noise). The final score was produced when the task score was multiplied with the duration score. Task score were calculated through the summation of Sub score 1 and Sub score 2. Figure 3 shows the summary of the final score for OFFERA method.

Figure 3.

Summary of the OFFERA scoring system.

In addition, the generation of action level for this tool referred other tools such as RULA, QEC and ROSA Tool.^11,14,16 Table 1 shows the four Action Level of the prototype OFFERA method. The range score for action level 1 was from 1–29 (negligible) indicating that the posture can be accepted if it is not repeated for a long period. The range score for action level 2 was 30–58 (low risk). It represents that further investigation needs to be done and changes are required for that posture. For action level 3, further investigation and changes are needed soon as the score between 59 and 87 represents medium risk factors and the final action level where the score from 88–117 (high risk) indicates that changes are required immediately. Table 1 shows the prototype of OFFERA range of final score are higher than the range of final score for RULA and ROSA. This is because the calculation of final score for OFFERA score used the sum scores of the weighted items. However, RULA and ROSA final score were used risk matrices for their final scoring system.

Table 1.

Action level of the OFFERA method.

Action Level	Score & Indication
Action Level	RULA	ROSA	OFFERA method
Action level 1	A score of 1 or 2 indicates that the posture is acceptable if not maintained	A score of 1 or 2 indicates that the posture is acceptable and should be maintained	A score of (1-29) indicate that the posture can be accepted if is not maintained or repeated for a long period of time.
Action level 2	A score of 3 or 4 shows that further investigation is needed	A score of 3 or 4 shows that further investigation is needed	A score of (30-58) shows that further investigation needs to be done and changes are required.
Action level 3	A score of 5 or 6 shows that further investigation and changes are needed soon	A score of 5 or 6 show that further investigation and changes needed soon	A score of (59-87) indicates the further investigation and changes are needed soon
Action level 4	A score of 7 or more indicates investigation and changes are required immediately	A score of 7 or more indicate investigation is needed and changes are required immediately	A score of (88-117) indicates that inquiry and change are required immediately.

Establish format forms and instruction

The prototype OFFERA method used only a piece of A4 paper with landscape orientation (double sided). In order to design the prototype tool, both front page and back pages were used as shown in Figure 4. As for the front page, two different parts were included which were Part A (top side) and Part B (bottom side). Part A was designed for the basic information such as age, gender, and job description where as Part B was designed for three domains (chair, desk, and keyboard) risk factors in which nine items (seat pan height, seat pan depth, backrest, armrest, desk height, desk depth, keyboard, mouse position, and mouse size) were included for office workstation. On the other hand, at the back page, three domains were included consists of Part C (left side and the top of right side), Part D (the middle right side), and Part E (bottom right side). Part C was designed for three domains (monitor, accessories, and environment) risk factors in which nine items (monitor angle, monitor distance, telephone, keyboard wrist rest, mouse wrist rest, lighting, temperature, and noise of office workstation). Furthermore, Part D was designed for the task duration score and Part E was designed for the final score and action level.

Figure 4.

Format form for the OFFERA method.

Each of the observational method requires the instructions to ease the assessor in conducting the assessment using this tool. For the OFFERA method, nine steps were required to complete the assessment. The instructions of the OFFERA method are listed in Table 2.

Table 2.

Instructions of the OFFERA method.

Step	Description
1	Determine the chair risk factor Chair score (A) = A1 + A2 + A3 + A4
2	Determine the desk or workstation risk factor Desk Score (B) = B1 + B2
3	Determine the input device risk factor Input Device score (C) = C1 + C2 + C3
4	Determine the monitor risk factor Monitor Score (D) = D1 + D2
5	Determine the accessories risk factor Accessories Score (E) = E1 + E2 + E3 + E4
6	Determine the office environment risk factor and Environment score (F) = F1 + F2 + F3
7	Determine the work duration
8	Determine the task score and Final Score of OFFERA Method Task score = sub score 1(chair, desk, input device) + sub score 2 (monitor, accessories, environment) Final Score = task score × duration score
9	Determine the level of risk (action level) from final score

The prototype of OFFERA method

In the development of the prototype, the existing assessment tools such as Rapid Upper Limb Assessment,¹¹ Rapid Entire Body Assessment,¹² Composite office ergonomic risk assessment,¹³ Quick Exposure Checklist,¹⁴ Assessment of Repetitive Tasks¹⁵ and Rapid Office Strain Assessment¹⁶ were used as reference. This prototype covers both front and back pages. In this prototype, several items were considered including the title, basic information, domains score, task score, final score, and action level. Each score has a different colours: Score A (maroon); Score B (blue); Score C (green); Score D (purple); Score E (orange); and duration score (grey). This ease the assessor incalculating the final score of the prototype. The Action level are has four different colours applied, based on the risk level. The colours were: greeen (very low risk or negligible); yellow (low risk); orange (medium risk); and red (high risk).

Stage 2: psychometric properties of OFFERA method

The psychometric properties of outcome measure include such thing as level of measurement; reliability, validity, and responsiveness.²¹ This stage consists of the reliability and usability trial and validity trial of the OFFERA method.

Reliability and usability testing of the OFFERA method

Reliability tests were conducted on 44 non-experts (students of Industrial Engineering) from the Faculty of Mechanical, UTHM, in order to develop the OFFERA method. The students who took part in the OFFERA Method training session served as observers. Twelve female students (27.3%) and 32 male students (72.7%) made up the total number of observers. The observers (N = 44) ranged in age from 22 to 29 years old, with a mean age of 23.14 years (SD = 1.622). The demographic item summary for 44 undergraduate students is displayed in Table 3.

Table 3.

Demographic item of the observers in training session (N = 44).

Group of observer (Educational Level)	Gender N (%)		Age (year)
Group of observer (Educational Level)	Male	Female	Mean (SD)	Range
Diploma / STPM (N = 14)	12 (85.7%)	2 (14.3%)	24.50 (1.829)	23-29
Matric / Foundation (N = 30)	20 (66.7%)	10 (33.3%)	22.50 (1.042)	22-26
Total (N = 44)	32 (72.7%)	12 (27.3%)	23.14 (1.622)	22-29

Job A (Admin Counter), Job B (Accountant), and Job C (Research Assistant) are the three jobs into which the results of inter- and intra-observer reliability testing have been separated. The Kappa analysis's findings indicate that there is more agreement regarding intra-observer reliability than there is regarding inter-observer reliability. Table 4 shows the findings of the tests for Job A's intra-observer and inter-observer reliability. The Cohen's Kappa coefficient for intra-observer reliability and inter-observer reliability ranged between 0 and 53–0 and 95, respectively. These show that the observers who evaluated Job A using the OFFERA method had “moderate” to “very good” reliability. Furthermore, the percentage agreement ranged from 68 to 18 percent to 94 to 45 percent for both intra-observer and inter-observer, respectively, and both were greater than 50 percent.

Table 4.

Inter-observer and intra-observer reliability Job A (N = 44 observer).

OFFERA Items	Inter-observer reliability		Intra-observer reliability
OFFERA Items	K^a	Percentage (%) Agreement	K^a	Percentage (%) Agreement
Seat Pan height	0.78	81.82	0.81	84.09
Seat Pan depth	0.78	81.82	0.81	84.09
Backrest	0.84	86.36	0.95	95.45
Armrest	0.84	86.36	0.95	88.64
Desk Height	0.81	84.09	0.81	84.09
Desk Depth	0.53	68.18	0.53	68.18
Keyboard	0.58	70.45	0.81	77.27
Mouse positioned	0.87	88.64	0.90	90.91
Mouse size	0.84	86.36	0.90	90.91
Monitor Angle	0.67	75.00	0.71	77.27
Monitor Distance	0.81	84.09	0.87	88.64
Telephone	0.53	68.18	0.71	75.00
Document Holder	0.95	95.45	0.95	95.45
Keyboard Wrist rest	0.95	95.45	0.95	95.45
Mouse wrist rest	0.90	90.91	0.90	90.91
Lighting	0.95	95.45	0.93	93.18
Temperature	0.87	88.64	0.90	90.91
Noise	0.84	86.36	0.84	86.36

^aK-Cohen's kappa coefficient was used to evaluate the inter-observer reliability and intra-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.

According to the findings, the observer's level of agreement with the keyboard, telephone, and desk depth was generally lower than others. This was demonstrated using Kappa analysis, which yielded inter-observer reliability results ranging from K = 0.53–0.58. Desk depth, on the other hand, has the lowest Kappa analysis value (K = 0.53) when it comes to intra-observer reliability. The degree of agreement for these items can be considered “moderate agreement,” per Rau²² (K = 0.4–0.59). This is due to the fact that when evaluating a worker's activity at the desk, the observers discovered that it was challenging to observe and define the range of desk depth. Apart from that, the observer reported that the desk depth, keyboard, and telephone instructions and illustrations were hard to follow, which led to misunderstandings during the evaluation. Additionally, when evaluating wrist posture using the OFFERA method, particularly for keyboard items, the observers found it challenging to distinguish between wrist postures, such as above or below, as well as the angle. Furthermore, other researchers experienced the same issue, believing that it was challenging for a spectator to determine whether the wrist angle during keying and clicking activity was 15° or 20° from its neutral position.²³ In addition, it has been noted that evaluating wrist posture during keying and clicking activity is more challenging than evaluating other joints.²⁴ For the telephone, keyboard, and monitor angle items, intra-observer reliability revealed a good level of agreement (K = 0.71–0.74). Both intra-observer reliability (K = 0.81–0.95) and inter-observer reliability (K = 0.78–0.84) result in good and very good level agreement for the seat pan height, seat pan depth, backrest, and armrest. Tahernejad's study²¹ found that using observational methods to evaluate a static posture, like sitting, was simpler than evaluating a dynamic posture. According to Table 4.2, the office environmental items produced very good agreement for both intra-observer and inter-observer reliability, with a range of K = 0.84–0.95. Aside from that, the findings indicate that the document holder and keyboard wrist rest items had the highest level of agreement (K) both between and within observers, with values of K = 0.95.

Table 5 shows the findings of the intra-observer and inter-observer reliability tests for Job B. The Cohen's Kappa coefficient agreement ranged from 0point 58 to 0point 98 for inter-observer reliability and from 0point 67 to 0point 98 for intra-observer reliability. These showed that observers who used the OFFERA method to evaluate Job B had “moderate” to “very good” reliability. Furthermore, both the intra-observer and inter-observer percentage agreement ranged above 70 percent, with the study achieving a range of 72–73 percent and 97–73 percent, respectively.

Table 5.

Inter-observer and intra-observer reliability Job B (N = 44 observer).

OFFERA Items	Inter-observer reliability		Intra-observer reliability
OFFERA Items	K^a	Percentage (%) Agreement	K^a	Percentage (%) Agreement
Seat Pan height	0.90	90.91	0.93	93.18
Seat Pan depth	0.84	86.36	0.95	95.45
Backrest	0.95	95.45	0.95	95.45
Armrest	0.95	95.45	0.95	95.45
Desk Height	0.87	81.82	0.84	86.36
Desk Depth	0.74	79.55	0.81	84.09
Keyboard	0.63	72.73	0.74	79.55
Mouse positioned	0.67	75.00	0.81	84.09
Mouse size	0.98	97.73	0.95	95.45
Monitor angle	0.58	70.45	0.67	75.00
Monitor distance	0.95	95.45	0.95	95.45
Telephone	0.74	79.55	0.84	86.36
Document Holder	0.95	95.45	0.98	97.73
Keyboard Wrist rest	0.93	93.18	0.98	97.73
Mouse wrist rest	0.87	88.64	0.93	93.18
Lighting	0.98	97.73	0.98	97.73
Temperature	0.95	95.45	0.95	95.45
Noise	0.71	77.27	0.95	81.81

According to the findings, the monitor angle agreement was generally lower than others (K = 0.58 for inter-observer reliability and K = 0.67 for intra-observer reliability), as determined by Kappa analysis. These findings can be classified as “moderate agreement” (K = 0.40–0.59) and “good” agreement (K = 0.60–0.79), per Altman (1991). When evaluating the neck posture for items like monitor angle in the OFFERA method, the observer had trouble defining and observing the angular ranges. According to the findings of other studies, it was extremely challenging to ascertain the worker's posture angle solely by observation.²⁵ Actually, Wang²⁶ mentioned the same problems and discovered that during the evaluation, observers favored using descriptive terms like bend up (extension) and bend down (flexion) rather than angle. For Cohen's Kappa, Rau²² recommended a “good” agreement between 0 and 79 and a “very good” agreement between 0 and 81 and 1 point. For both intra-observer reliability (K = 0.74) and inter-observer reliability (K = 0.63), the analysis revealed that the keyboard agreement was generally good. In addition, because wrist posture involves repetitive movement, it has been claimed that it is more challenging to evaluate than other joints.²⁶ In addition, the observer had trouble evaluating the keyboard items for the OFFERA method because the item illustrations were unclear, and it was challenging to ascertain the wrist posture position during the task, particularly when typing.

When the 44 observers evaluated the other OFFERA items—seat pan height, seat pan depth, backrest, armrest, mouse size, document holder, keyboard wrist rest, mouse wrist rest, lighting, and temperature, the Kappa values for inter-observer reliability (K = 0.84–0.98) and intra-observer reliability (K = 0.81–0.98) were higher. Because it did not involve repetitive motion, the Abasi²⁷ study found that static posture, such as sitting, was simpler to evaluate than dynamic posture. The observer also said that this approach was simpler to comprehend. According to the results, intra-observer reliability (K = 0.67–0.98) had a higher level of agreement (Kappa values) than inter-observer reliability (K = 0.58–0.98). Sonne¹⁶ also demonstrated that intra-observer reliability (ICC = 0.80–0.95) was greater than inter-observer reliability (ICC = 0.51–0.91). This shows that following their second use of the OFFERA method, the observers had a better understanding of how to conduct assessments using it.

Table 6 shows the findings of the intra-observer and inter-observer reliability tests for Job C. Cohen's Kappa coefficient showed a level of agreement between 0points 58 and 0points 98 for inter-observer reliability and between 0points 71 and 98 for intra-observer reliability. These showed that observers who evaluated Job B using the OFFERA method had “moderate” to “very good” reliability. In addition, the percentage agreement for OFFERA items ranged from 72 to 73 percent for inter-observer and 97 to 73 percent for intra-observer.

Table 6.

Inter-observer and intra-observer reliability Job C (N = 44 observer).

OFFERA Items	Inter-observer reliability		Intra-observer reliability
OFFERA Items	K^a	Percentage (%) Agreement	K^a	Percentage (%) Agreement
Seat Pan height	0.63	72.73	0.74	79.55
Seat Pan depth	0.95	95.45	0.95	95.45
Backrest	0.67	75.00	0.87	88.64
Armrest	0.95	95.45	0.98	97.73
Desk Height	0.74	79.55	0.78	81.82
Desk Depth	0.63	72.73	0.71	77.27
Keyboard	0.93	93.18	0.95	95.45
Mouse positioned	0.81	84.09	0.90	90.91
Mouse size	0.93	93.18	0.98	97.73
Monitor angle	0.74	79.55	0.78	81.82
Monitor Distance	0.87	88.64	0.95	95.45
Telephone	0.58	70.45	0.71	77.27
Document Holder	0.95	95.45	0.95	95.45
Keyboard Wrist rest	0.95	95.45	0.95	95.45
Mouse Wrist rest	0.90	90.91	0.95	95.45
Lighting	0.90	90.91	0.93	93.18
Temperature	0.87	88.64	0.95	95.45
Noise	0.98	97.73	0.93	93.18

Using Kappa analysis, the results showed that the level of agreement in evaluating telephone reliability is generally lower than others, with K = 0.58 for inter-observer reliability and K = 0.71 for intra-observer reliability. The findings can be categorized as “moderate agreement” (K = 0.40–0.59) and “good” agreement (K = 0.60–0.79), per Rau.²² It is challenging to observe the neck and shoulder posture when using a telephone, the observer discovered. Furthermore, according to the observer, the telephone items were challenging to observe, which led to misunderstandings during the evaluation. Good levels of agreement between observers were found for items like seat pan height, backrest, desk depth, desk height, and monitor angle (K = 0.63–0.74). Nonetheless, for items such as desk height, seat pan height, and desk depth, intra-observer reliability was found to be at the good level agreement (K = 0.71–0.78). According to the intra-observer reliability, the backrest's level of agreement was “very good” (K = 0.84). The armrest and seat pan depth, on the other hand, received “very good” agreement for both intra- and inter-observer reliability (0.95–0.98). According to Arippa,²⁸ evaluating leg posture was easier or more direct. In addition, static posture was simpler to evaluate using observational methods than dynamic posture. On the other OFFERA tool, the 44 observer's evaluation produced a higher Kappa value (K = 0.81–0.98).

According to Rahman's²⁹ usability test, the OFFERA method was shown to be quick to use (mean 4.48 ± 0.821) and easy to use (mean 4.48 ± 0.698). However, the observers had trouble reading the instructions because the font size was too small (mean 3.93 ± 1.096). Due to the relatively low score for 18 items (mean 3.73 ± 1.128), the OFFERA tool's pictures or illustrations were also marked as unclear. In addition, every participant concurred that the OFFERA method is adaptable to a variety of office-related tasks, affordable, and user-friendly.²⁹

One potential limitation of this study is the reliance on non-expert observers for reliability testing. While non-experts can be trained to follow standardized protocols, their limited experience and expertise may contribute to inconsistencies in scoring, particularly in identifying subtle or complex postures.³⁰ This may reduce inter-rater reliability and introduce greater variability in the data.^30,31 Furthermore, the use of a specific sample of office workers may limit the generalizability of the findings.³² Office workers often exhibit relatively uniform postural behaviors due to the sedentary nature of their work, which may not reflect the broader population, such as manual laborers or individuals in physically demanding roles.^32,33 Additionally, observer bias and challenges in scoring certain postures present further limitations.³⁴ Subjective interpretation of postural criteria, especially for transitional or ambiguous positions, can lead to misclassification.^34,35

Validity testing of the OFFERA method

In this study, validity of the prototype tool was assessed using concurrent validity. The concurrent validity was tested using the prototype of OFFERA method and Nordic Musculoskeletal Disorders Questionnaire.³⁶ This test has been carried out among 108 office workers with different office position including administrative assistants, administrative officers, research assistants, and secretaries. Table 7 shows the summary of the demographic data for 108 office workers in terms of gender, age, working experience in years, and working time in hours.

Table 7.

Demographic data for office worker (N = 108).

Characteristics (mean ± sd)		N	%
Gender	Male	36	33.3
Gender	Female	72	66.7
Age (33.90 ± 7.042)	20-30	38	35.2
	31–40	53	49.1
	> 40	17	15.7
Working Experience (Year) (8.40 ± 5.839)	0–5	40	37.0
	6–10	31	28.7
	11–15	23	21.3
	16–20	11	10.2
	> 20	3	2.8
Working Hours (7.89 ± 0.765)	< 8	9	8.3
	8–9	97	89.8
	> 9	2	1.9

From the demographic results shown, the number of the males working at the office was 36 (33.3%) whereas the number of females was 72 (66.7%). Most of the office workers were age between 31–40 years old (49.1%) followed by workers aged between 20–30 years old (35.2%) and those over 40 years old (15.7%). The median age of the office workers was 33.90 years (SD = 7.042) in the range between 21 to 54. Based on the results obtained, 40 of the office workers have working experience less than 5 years (37%) followed by 31 (28.7%) workers with working experience between 6 to 10 years, 23 (21.3%) workers with working experience between 11 to 15 years, 11 (10.2%) workers with working experience between 16 to 20 years, and 3 (2.8%) office workers with more than 20 years of working experience. In addition, the total mean (SD) for the working experience demographic variable was 8.4 years (SD = 5.839) in the range between 1 to 22 years. Other than that, the results showed that most of the office workers (89.8%) spend about 8 to 9 h per day for office tasks. However, about 9 (8.3%) office workers spent less than 8 h on work per day and 2 (1.9%) of them spend over than 9 h on work per day. In addition, studies by Suhaimi³⁷ stated that an individual office workers exhibit diverse behaviours some remain seated for extended periods, while others engage in frequent movement studies have consistently demonstrated that sedentary behaviour is prevalent across various office settings. For instance, a study involving 1338 Malaysian government office workers found that the mean daily sitting time was approximately 6 h, with a standard deviation of 1.37 h, indicating variability among individuals.³⁸ Despite this variability, the overall trend of prolonged sitting is evident.^37,38

Table 8 shows the relationship between OFFERA final scores and musculoskeletal symptoms. The relationship between the final score and the musculoskeletal symptoms was statistically significant for the wrists/hands (χ² = 7.942; p = 0.047), lower back (χ² = 13.478; p = 0.000), knees (χ² = 7.001; p = 0.008), and ankle/leg (χ² = 5.098; p = 0.024). Therefore, the five body regions which were found to be statistically insignificant (p > 0.05) were the neck (χ² = 0.855; p = 0.355), shoulder (χ² = 2.107; p = 0.550), elbows (χ² = 0.677; p = 0.713), upper back (χ² = 1.460; p = 0.227), and hips (χ² = 2.411; p = 0.120).

Table 8.

Relationship between OFFERA final scores and musculoskeletal symptoms (N = 108).

Body part	Musculoskeletal Symptoms	OFFERA Final Score		χ² ^a	P-value ^b
Body part	Musculoskeletal Symptoms	30–58	59–87	χ² ^a	P-value ^b
Neck	No	9	48	0.855	0.355
Neck	Yes	5	46	0.855	0.355
Shoulder	No	4	35	2.107	0.550
	Yes in the right	6	46
	Yes in the left	1	4
	Yes in the right	3	9
Elbow	No	13	85	0.677	0.713
	Yes in the right	0	4
	Yes in the left	-	-
	Yes in the both	1	5
Wrists	No	11	48	7.942	0.047
	Yes in the right	2	23
	Yes in the left	1	1
	Yes in the both	0	22
Upper back	No	12	66	1.460	0.227
Upper back	Yes	2	28	1.460	0.227
Low back	No	10	22	13.478	0.000
Low back	Yes	4	72	13.478	0.000
Hips	No	12	61	2.411	0.120
Hips	Yes	2	33	2.411	0.120
Knees	No	12	45	7.001	0.008
Knees	Yes	2	49	7.001	0.008
Ankle	No	10	37	5.098	0.024
Ankle	Yes	4	57	5.098	0.024

^aChi-Square analysis (χ²-test) was used to determine the relationship between the OFFERA scores and the development of pain or discomfort reported in NMDQ.

^bP-value:P < 0.05(acceptable) and P > 0.05 (unacceptable).

The OFFERA scores for the wrist was 59–87 among 43.6% of the workers, while wrist discomfort/pain was reported by 45.4% of workers in the NMDQ. Thus, there is a significant association between the final score and musculoskeletal symptoms (χ² = 7.942; p = 0.047). The OFFERA final score for the lower back region during office work yielded a score of 59–87 among 66.7% of the workers while lower back pain was reported by 70.4% of the workers in NMDQ, resulting a significant association for the lower back (χ² = 13.478; p = 0.000). The OFFERA scores for the knees scored 45.4% whereas knee pain was reported by 47.2% of the workers (NMDQ) resulting in the association being significant (χ² = 7.001; p = 0.008). The ankle region scored 52.8% in the range of 58–87 for the OFFERA method whereas 56.5% of workers reported discomfort in their ankles (NMDQ) resulting in a significant association (χ² = 5.098; p = 0.024).

However, no association was found between the neck, shoulder, upper back, elbow, and hips score and the musculoskeletal symptoms. The shoulder score for the OFFERA final score was 58–87 among 54.6% of the workers but shoulder discomfort was reported by 63.9% of workers. Therefore, there was no association between the OFFERA score and shoulder discomfort (χ² = 2.107; p = 0.550). Similarly, no association was found between the neck, elbow, upper back, and hips score of the OFFERA tool and reported pain or discomfort in those regions (χ² = 0.855; p = 0.355), (χ² = 0.677; p = 0.713), (χ² = 1.460; p = 0.227), and (χ² = 2.411; p = 0.120). This is due to the fact that the observers commented that the items’ instruction and illustration were difficult to evaluate, particularly with regard to angular range, which made the observation challenging. In evaluating the neck posture for items like the telephone item and the monitor angle using the OFFERA method, for instance, observers found it challenging to observe and define the angular ranges.

The results show the relationship or correlation between the OFFERA final score and musculoskeletal symptoms was significant and increasing OFFERA score results reflect increasing body discomfort. Based on the study by Sonne,¹⁶ showed the total ROSA score and total discomfort were positively correlated in which if the ROSA score increase and the musculoskeletal discomfort also increase. Studies by Simon,³⁹ revealed that there was a high correlation between total body pains and increasing RULA scores in the office environment.

Final version of OFFERA method

The final version for office ergonomic risk assessment tool has been developed from the improvement of OFFERA prototype. The improvement of the OFFERA prototype was made based on the results of the reliability, usability and validity trials. The final version (OFFERA) had some changes on the contents, illustration and the scoring of risk factors for each item. The details of final version of the OFFERA method as shown in Figure 5 and 6.

Figure 5.

First page of the OFFERA method.

Figure 6.

Second page of the OFFERA method.

Conclusions

This study describes the creation of an exposure assessment tool (OFFERA), a participatory ergonomics process, and how user testing was used to evaluate it. A simple format was created, and tests were conducted on its validity, usability, and reliability. Both intra- and inter-observer reliability were examined. The results of the usability and reliability tests indicated that there was good to very good agreement between the observers in terms of both intra- and inter-observer reliability. Compared to the inter-observer reliability (K = 0.62–0.95), the intra-observer reliability (K = 0.68–0.96) was greater. In addition, the concurrent validity shows that the relationship between the final score of OFFERA and the musculoskeletal symptoms is statistically significant for the wrists/hands (χ² = 7.942; p = 0.047), lower back (χ² = 13.478; p = 0.000), knees (χ² = 7.001; p = 0.008), and ankle/ leg (χ² = 5.098; p = 0.024). Based on the results obtained, it can be concluded that this method is suitable for assessing the exposure risks for office workers. Furthermore, based on the input regarding the OFFERA tool's usability obtained through a questionnaire survey, every participant concurred that the OFFERA approach was both economical and easy to use.

Footnotes

Acknowledgements

The authors gratefully acknowledge the financial support provided by the Ministry of Higher Education Malaysia (MOHE) and Universiti Tun Hussein Onn Malaysia (UTHM).

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is funded by Ministry of Higher Education of Malaysia (MOHE) and Universiti Tun Hussein Onn Malaysia (UTHM) under Fundamental Research Grant Scheme (FRGS, Vot 1495).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

Putsa

Jalayondeja

Mekhora

, et al. Factors associated with reduced risk of musculoskeletal disorders among office workers: a cross-sectional study 2017 to 2020. BMC public Health 2022; 22: 1503.

Ali

Uddin

Ahsan

, et al. Association between daily commute and subjective health complaints among the office workers in an urban community. Heliyon 2021; 7: e07841.

Argus

Paasuke

. Musculoskeletal disorders and associated factors among office workers in an activity-based work environment. Int J Occup Saf Ergon 2022; 28: 2419–2425.

Kahya

. Assessment of musculoskeletal disorders among employees working office workplaces in the manufacturing sector. Work 2021 Jul 16; 69: 1103–1113.

Greggi

Visconti

Albanese

, et al. Work-related musculoskeletal disorders: a systematic review and meta-analysis. J Clin Med 2024; 13: 3964.

Vahdani

Gholami

Vahdani

, et al. Rheumatic and musculoskeletal diseases among office workers: a narrative review. J Pain Manag 2020; 13: 9–13.

Basakci Calik

Yagci

Oztop

, et al. Effects of risk factors related to computer use on musculoskeletal pain in office workers. Int J Occup Saf Ergon 2022; 28: 269–274.

İkiz

Ergin

. Musculoskeletal system problems in office workers: relationship of physical activity levels and quality of life. Int J Occup Saf Ergon 2023; 29: 321–328.

Valentim

Comper

Sandy Medeiros Rodrigues Cirino

, et al. Observational methods for the analysis of biomechanical exposure in the workplace: a systematic review. Ergonomics 2024: 1–22.

10.

Hulme

Stanton

Walker

, et al. Testing the reliability and validity of risk assessment methods in human factors and ergonomics. Ergonomics 2022; 65: 407–428.

11.

McAtamney

Corlett

. Rapid upper limb assessment (RULA). In: Handbook of human factors and ergonomics methods. Boca Raton, FL, USA: CRC Press, 2004 Aug 30, pp.86–96.

12.

Hignett

McAtamney

. Rapid entire body assessment (REBA). Appl Ergon 2000; 31: 201–205.

13.

Szabó

Németh

. Development an office ergonomic risk checklist: composite office ergonomic risk assessment (CERA office). In: Proceedings of the 20th congress of the international ergonomics association (IEA 2018) volume II: safety and health, slips, trips and falls 20. Cham, Switzerland: Springer International Publishing, 2019, pp.590–597.

14.

David

Woods

, et al. The development of the quick exposure check (QEC) for assessing exposure to risk factors for work-related musculoskeletal disorders. Appl Ergon 2008; 39: 57–69.

15.

Ferreira

Hunter

Birtles

, et al. Development of an assessment tool for repetitive tasks of the upper limbs (ART). Derbyshire: Health and Safety Executive, 2009.

16.

Sonne

Villalta

Andrews

. Development and evaluation of an office ergonomic risk checklist: ROSA – rapid office strain assessment. Appl Ergon 2012; 43: 98–108.

17.

Diego-Mas

Poveda-Bautista

Garzon-Leal

. Influences on the use of observational methods by practitioners when identifying risk factors in physical work. Ergonomics 2015; 58: 1660–1670.

18.

Graben

Schall Jr

Gallagher

, et al. Reliability analysis of observation-based exposure assessment tools for the upper extremities: a systematic review. Int J Environ Res Public Health 2022; 19: 10595.

19.

Nyman

Rhén

Johansson

, et al. Reliability and validity of six selected observational methods for risk assessment of hand intensive and repetitive work. Int J Environ Res Public Health 2023; 20: 5505.

20.

Gonçalves

Cardoso

Mattos

, et al. Assessment of work-related musculoskeletal disorders by observational methods in repetitive tasks—a systematic review. Occup Env Safet Health III 2022: 455–463.

21.

Tahernejad

Razeghi

Abdoli-Eramaki

, et al. Recommended maximum holding time of common static sitting postures of office workers. Int J Occup Saf Ergon 2023; 29: 847–854.

22.

Rau

Shih

. Evaluation of Cohen's kappa and other measures of inter-rater agreement for genre analysis and other nominal data. J English Acad Purp 2021; 53: 101026.

23.

Wang

Gao

, et al. Wrist in motion: a seamless context-aware continuous authentication framework using your clickings and typings. IEEE Trans Biomet Behav Ident Sci 2020 May 26; 2: 294–307.

24.

McFarland

Binder-Markey

Nichols

, et al. A musculoskeletal model of the hand and wrist capable of simulating functional tasks. IEEE Trans Biomed Eng 2023; 70: 1424–1435.

25.

Rodrigues

Xiao

Fukumura

, et al. Ergonomic assessment of office worker postures using 3D automated joint angle assessment. Adv Eng Inf 2022; 52: 101596.

26.

Wang

Zeng

, et al. Quantifying the impacts of posture changes on office worker productivity: an exploratory study using effective computer interactions as a real-time indicator. BMC Public Health 2023; 23: 2198.

27.

Abbasi

Alizadeh

Rajabi

, et al. Comparison of static and dynamic postural stability between individuals with and without forward head posture. Phys Treat - Specific Physical Therapy 2020; 10: 127–134.

28.

Arippa

Nguyen

Pau

, et al. Postural strategies among office workers during a prolonged sitting bout. Appl Ergon 2022; 102: 103723.

29.

Rahman

Mohamad

Salleh

, et al. Feedback survey on the usability of the OFFERA method for assessing an exposure risks of computer work related to WMSDs. In: MATEC Web of conferences. 135. Parc d'Activités de Courtabœuf, Les Ulis Cedex A, France: EDP Sciences, 2017, pp.00025.

30.

Eliasson

Palm

Nyman

, et al. Inter- and intra- observer reliability of risk assessment of repetitive work without an explicit method. Appl Ergon 2017; 62: –8.

31.

Woldendorp

Kleinbergen

JFE

Boonstra

, et al. Quality and usability of clinical assessments of static standing and sitting posture: a systematic review. J Back Musculoskelet Rehabil 2022; 35: 223–238.

32.

Chau

Daley

Srinivasan

, et al. Desk-based workers’ perspectives on using sit-stand workstations: a qualitative analysis of the Stand@Work study. BMC public health 2014; 14: 1–0.

33.

Wahlström

Olsson

Öhberg

, et al. Underlying factors explaining physical behaviors among office workers—an exploratory analysis. Int J Environ Res Public Health 2020; 17: 9158.

34.

Osqueizadeh

Bandpei

Rahmani

, et al. Reliability and Validity of Observational Methods for Postural Load Assessment: An Updated Systematic Review. Health Scope 2023 Nov 1; 12: 1–9.

35.

Graben

Schall Jr

Gallagher

, et al. Reliability analysis of observation-based exposure assessment tools for the upper extremities: a systematic review. Int J Environ Res Public Health 2022; 19: 10595.

36.

Crawford

. The nordic musculoskeletal questionnaire. Occup Med (Chic Ill) 2007; 57: 300–301.

37.

Suhaimi

Müller

Hafiz

, et al. Occupational sitting time, its determinants and intervention strategies in Malaysian office workers: a mixed-methods study. Health Promot Int 2022; 37: daab149.

38.

Faisal Mohamed

A. Iahad

. Preliminary investigation on Malaysian office Workers’ sedentary behaviour, health consequences, and intervention preferences: towards designing anti sedentary behaviour change support systems. In: International conference of reliable information and communication technology. Cham: Springer International Publishing, 2021 Dec 22, pp.677–687.

39.

Simon

Dully

Dindorf

, et al. Inertial motion capturing in ergonomic workplace analysis: assessing the correlation between RULA, upper-body posture deviations and musculoskeletal discomfort. . Safety 2024 Feb 2; 10: 16.