Development of a novel ergonomic index assessment in the workplace based on physical,cognitive,and environmental components

Abstract

BACKGROUND:

Currently, proper assessment of the existing ergonomic hazards, focusing on improving the health of individuals, is of great importance.

OBJECTIVE:

This study aims to develop a new model for ergonomic index assessment in the workplace, focusing on physical, cognitive, and environmental components.

METHODS:

To determine the parameters to be measured for each group of occupations, the most critical indicators in each ergonomic dimension were identified using a review of scientific texts and obtaining expert opinions. The opinions of 30 experts were studied in three stages Delphi study. Cronbach’s alpha was used to calculate model reliability in SPSS version 25. An analytical hierarchy process was used to determine the weight values of each component and parameter. The weights were calculated in Expert Choice version 11.

RESULTS:

The mean CVI and CVR values were 0.92 and 0.80, respectively. Cronbach’s alpha values for each of the physical, environmental, and cognitive components and the entire model were 0.91, 0.87, 0.85, and 0.89, respectively. Physical components and parameters of physical condition during work, mental workload, lighting, and thermal stress in the workplace were among the most important parameters in the three groups of office, operational, and services jobs.

CONCLUSION:

The model can be a practical step toward properly evaluating the ergonomic components and planning to implement control measures to reduce physical, cognitive, and environmental risk factors. Considering the study of different variables in occupational ergonomic risk assessment, this model can be a helpful tool in ergonomic management systems used in different occupational environments.

Keywords

Ergonomic evaluation model physical component cognitive component environmental component analytical hierarchy process Delphi study

1 Introduction

In recent years, due to the increased human interaction with various machines, tools, and simple and complex systems, the need for ergonomics has been created and still plays an influential role in improving the health of workers in various occupations [1, 2]. The international associations have termed ergonomics “the design of work so that human competencies can be employed in the most suitable feasible way without devastating human limitations.” The practical purpose of ergonomics is the conditioning and justification of the adaptation of work to humans [1].

Among the most important components of ergonomics are physical, environmental, cognitive, and organizational dimensions. Physical ergonomics is mainly related to the concepts such as anatomy, anthropometry, work physiology, inappropriate posture, workstation analysis, and occupational biomechanics. Environmental ergonomics mainly consists of the effect of physically harmful factors of the work environment such as noise and vibration, lighting, and thermal stresses on human performance and applying this information in the design and redesign of the human activity environment. Cognitive or perceptual ergonomics is concerned with thought processes such as perception, memory, stress, mental workload, and the body’s response to thesestressors [3].

Finally, organizational ergonomics is related to optimizing technical-organizational systems such as structures, policies, and processes that can involve all people in the organizations at all levels with ergonomic issues and lead the organization to achieve ergonomic goals and promote productivity [4 –6].

One of the most important ergonomic disorders in the workplace is musculoskeletal disorders. Work-related musculoskeletal disorders (WRMSDS) are among the most common types of occupational injuries and the leading cause of disability of workers, loss of working time, increased costs, and economic losses [7 –9].

Such disorders may be caused by long-term exposure to the causative agents over a long time or may be caused by a sudden impact on the part of the musculoskeletal system. These injuries are often multifactorial phenomena [10, 11]. Risk factors for work-related musculoskeletal disorders can generally be divided into four categories: 1) work-related physical or biomechanical factors, 2) work-related organizational or psychosocial factors, 3) individual factors, and 4) social content-related factors [12, 13]. The main physical risk factors for work-related musculoskeletal injuries are: lifting and moving heavy loads, applying force, contact pressure, performing repetitive movements, vibration, undesirable static postures, and improper organization. Exposure to such factors creates adverse effects on the body and endangers health status [3, 14].

Studies in UK have shown that 55% of occupational diseases are related to musculoskeletal disorders [15]. In the workplace, if a person’s physical and mental abilities do not match with their occupational demands, it can create a variety of negative consequences such as increased job dissatisfaction and absence, stress, reduced physical capacity, fatigue, and reduced job productivity. Furthermore, one of the most critical negative consequences is the increase in the prevalence of work-related musculoskeletal disorders [16]. One of the influential cognitive factors in the occurrence of occupational injuries is the mismatch between the mental workload of workers and their abilities and limitations [17]. Workload has complex and multidimensional meanings; the mental workload is the amount of effort that the mind makes during the task and is related to the individual’s mental abilities and how information is received and processed and ultimately leads to decisions and actions [18, 19]. Factors such as workload, job stress, burnout, etc., make it easier for physical and psychological factors to influence ergonomic disorders [20]. Previous studies have shown that the risk of musculoskeletal disorders in workers increases with increasing workload, stress, and job stress index [21 –23].

Another influential factor in the prevalence of ergonomic disorders in the workplace is the individual risk factors such as a person’s lifestyle. Previous studies have shown that factors involved in the lifestyle, such as smoking, overweight, diet, sleep, stress, and sedentary lifestyles, contribute to chronic diseases such as musculoskeletal disorders [24, 25]. Ergonomic disorders are prevalent in most industrialized countries and are considered one of the most common, debilitating, and costly disorders and cause significant damage to the health and economy of communities every year [3]. The consequences of ergonomic disorders in workers are significant and lead to the onset of psychological problems such as depression and burnout, and one of the main reasons for absenteeism and economic problems. Therefore, ergonomic disorders are considered a major problem for different societies [26, 27].

Paying attention to the principles of ergonomics by focusing on working environments with a proactive approach to improve the health of individuals and the organization’s productivity is very important. Physical ergonomics is one of the most important components of ergonomics that has been studied and evaluated so far. Previous studies have shown that one-dimensional evaluations in ergonomics (physical ergonomics) are not sufficient and effective studies in this field require comprehensive attention to all aspects of ergonomics (physical, environmental, cognitive, and organizational). It should be noted that the ergonomic assessment method introduced during the present study is part of the TUGA ergonomic management and analysis (TEMA) cycle, which is presented in Fig. 1 (the third step). Therefore, due to the importance of this issue, the lack of similar assessment models, and the primary and essential role of ergonomics in improving the health of employees and increasing productivity, the present study aimed to develop a novel ergonomic assessment model in the workplace based on physical, cognitive and environmental components.

Fig. 1

TUGA ergonomics management and analysis cycle.

2 Methods

The present study aimed to create an ergonomic index assessment model focusing on three physical, cognitive, and environmental components using the Delphi study and analytical hierarchy process (AHP) in a large power plant industry in Iran in 2021. The study consisted of five main steps, presented in the following sections.

2.1 Identification of the studied parameters and measuring tools

At this stage, to determine the parameters to be measured for each group of occupations, the most important parameters and indicators in each of the ergonomic dimensions; includes physical ergonomics, environmental ergonomics, and cognitive ergonomics using library studies, brainstorming, review of scientific texts published in valid scientific indexes in similar industries (ISI-Web of Science, Scopus, PubMed) as well as obtaining expert opinions were identified. In this step, 84 studies in the field of ergonomic evaluation and management methods in the workplace were extracted. Then, in the second stage and finalization of the selected studies, 43 articles were selected according to the study criteria (based on physical, cognitive, and environmental components).

2.2 Creating an ergonomic index assessment model algorithm

To determine the indicators measured in each job subgroup, all jobs in the studied industry were divided into three general groups: 1) office, 2) operational, and 3) services jobs.

The following are the definitions of each of the studied components and indicators.

2.2.1 Physical ergonomics (Table 1)

Table 1
Scoring guide for the determining factors and measuring tools in physical ergonomics

Parameters Tools Range of score / risk level Final score

Real score Model score

Posture Rapid Entire Body Assessment (REBA) 1–15 1–3 0

4–7 1

8–10 1.5

11–15 2

Rapid Upper Limb Assessment (RULA) 1–7 1–2 0

3–4 1

5–6 1.5

7 2

Rapid Office Strain Assessment (ROSA) 1–10 1–4 0

5–7 1

8–9 1.5

10 2

Manual material handling WISHA lifting calculator Variable <PEL 0

=PEL 1

>PEL 2

Snook tables Variable <PEL 0

=PEL 1

>PEL 2

WRMSD_S^* Cornell Musculoskeletal 0–90 0–20 0

Discomfort Questionnaires 21–40 1

(CMDQ) 41–60 1.5

61–90 2

Muscle fatigue Muscle Fatigue Assessment (MFA) Low, moderate, high and very high risk level Low 0

Moderate 1

High 1.5

Very high 2

Energy consumption Systematic Workload Estimation (SWE) Lower / higher than Physical Work Capacity (PWC) <PWC 0

=PWC 1

>PWC 2

Anthropometry^ Qualitative Assessment Suitable / not Suitable Not suitable +1

Biomechanics^* Job Strain Index (SI-JSI) Low, moderate and high risk level >7.1 +1

Personal risk factor^**** Questionnaire – medical examination – Existence of risk factors +1

Final score of physical component Without normalized weight Job assessment: 0–12 Low 0–0.99

Personal assessment: 0–13 Moderate 1–1.99

With normalized weight Job assessment: 0–4 High 2–2.99

Personal assessment: 0–5 Very high 3–5

Parameters	Tools	Range of score / risk level	Final score
Posture	Rapid Entire Body Assessment (REBA)	1–15	1–3	0
			4–7	1
			8–10	1.5
			11–15	2
	Rapid Upper Limb Assessment (RULA)	1–7	1–2	0
			3–4	1
			5–6	1.5
			7	2
	Rapid Office Strain Assessment (ROSA)	1–10	1–4	0
			5–7	1
			8–9	1.5
			10	2
Manual material handling	WISHA lifting calculator	Variable	<PEL	0
			=PEL	1
			>PEL	2
	Snook tables	Variable	<PEL	0
			=PEL	1
			>PEL	2
WRMSD_S^*	Cornell Musculoskeletal	0–90	0–20	0
	Discomfort Questionnaires		21–40	1
	(CMDQ)		41–60	1.5
			61–90	2
Muscle fatigue	Muscle Fatigue Assessment (MFA)	Low, moderate, high and very high risk level	Low	0
			Moderate	1
			High	1.5
			Very high	2
Energy consumption	Systematic Workload Estimation (SWE)	Lower / higher than Physical Work Capacity (PWC)	<PWC	0
			=PWC	1
			>PWC	2
Anthropometry^**	Qualitative Assessment	Suitable / not Suitable	Not suitable	+1
Biomechanics^***	Job Strain Index (SI-JSI)	Low, moderate and high risk level	>7.1	+1
Personal risk factor^****	Questionnaire – medical examination	–	Existence of risk factors	+1
Final score of physical component	Without normalized weight	Job assessment: 0–12	Low	0–0.99
		Personal assessment: 0–13	Moderate	1–1.99
	With normalized weight	Job assessment: 0–4	High	2–2.99
		Personal assessment: 0–5	Very high	3–5

^*Work-Related Musculoskeletal Disorder (Prevalence, Severity and Disability). ^**If Applicable. ^***In case of individual index calculation.

It generally focuses on the biomechanical, anatomical, physiological, and anthropometric properties of humans. This branch of ergonomics also examines the effect of physical factors on the performance of individuals. Participation in the design of office and industrial work environments and products and equipment used by individuals are among the projects related to this component [28].

The following indicators were used to evaluate this component:

Assessment of physical postures

Evaluate manual material handling (MMH)

Evaluation of the prevalence, severity, and disabilities caused by musculoskeletal disorders (WRMSD)

Muscle fatigue

Work physiology (determining the amount of energy consumed in each job based on past empirical studies)

Biomechanics and anthropometry

2.2.2 Cognitive ergonomics (Table 2)

Table 2
Scoring guide for the determining factors and measuring tools in cognitive ergonomics

Component Tools Range of score / risk level Final score

Real score Model score

Mental workload NASA Task Load Index 0–100 <45 0

(NASA – TLX) 45–55 1

>55 2

Occupational stress Job Content Questionnaire Variable Low 0

(JCQ) High 2

Sleep quality Pittsburgh Sleep Quality 0–21 0–6 0

Index (PSQI) >7 2

Cognitive failure Cognitive Failure 0–125 0–25 0

Questionnaire (CFQ) 26–50 1

51–75 1.5

76–125 2

Chronic mental disorders^* Questionnaire – medical examination – Existence of risk factors +1

Final score of cognitive component Without normalized weight Job assessment: 0–8 Low 0–0.49

Personal assessment: 0–9 Moderate 0.50–0.99

With normalized weight Job assessment: 0–2 High 1–1.99

Personal assessment: 0–3 Very high 2–3

Component	Tools	Range of score / risk level	Final score
Mental workload	NASA Task Load Index	0–100	<45	0
	(NASA – TLX)		45–55	1
			>55	2
Occupational stress	Job Content Questionnaire	Variable	Low	0
	(JCQ)		High	2
Sleep quality	Pittsburgh Sleep Quality	0–21	0–6	0
	Index (PSQI)		>7	2
Cognitive failure	Cognitive Failure	0–125	0–25	0
	Questionnaire (CFQ)		26–50	1
			51–75	1.5
			76–125	2
Chronic mental disorders^*	Questionnaire – medical examination	–	Existence of risk factors	+1
Final score of cognitive component	Without normalized weight	Job assessment: 0–8	Low	0–0.49
		Personal assessment: 0–9	Moderate	0.50–0.99
	With normalized weight	Job assessment: 0–2	High	1–1.99
		Personal assessment: 0–3	Very high	2–3

^*In case of individual index calculation.

This ergonomic component examines human, work, and environment interaction from a cognitive perspective. Cognitive ergonomics focuses on designing the interaction between humans and work according to the mental limitations of the user. Cognitive ergonomics studies perceptual processes (such as recognizing patterns, central cognitive processing (such as decision-making, problem-solving, memory), and sensory-motor processes (such as typing). On the other hand, cognitive ergonomics, a well-established zone within the discipline of Human Factors/Ergonomics (HF/E), desires to design systems to sustain optimal human mental performance and well-being when conducting occupational tasks and sub-task [29].

The following indicators were used to evaluate this component:

Mental workload

Occupational stress

Sleep quality

Burnout

Cognitive failure

2.2.3 Environmental ergonomics (Table 3)

Table 3
Scoring guide for the determining factors and measuring tools in environmental ergonomics

Component Tools Range of score / risk level Final score

Real score Model score

Noise Environmental / personal assessment 0–140 dB for environmental assessment, > 100 % Dose for personal assessment 0–65 dB 0

66–82 dB 1

82–85 dB 1.5

> 85 dB and Dose > 100 % 2

Vibration Whole Body Vibration (WBV) / Hand-Arm Vibration (HAV) 0.87 m.s^-2 for WBV and 2 m.s^-2 for HAV (OEL) Lower than allowed level 0

Higher than allowed level 2

Lighting Environmental / local assessment 270 lux for lighting and 100 nit for illuminance (OEL) Lighting > 270 Lux 0

Illuminance<100 nit

Lighting<270 Lux 2

Illuminance > 100 nit

Thermal stress Direct measure Existence of thermal stress In allowable range 0

Out of allowable range 2

Confined space Observation method Existence / non-existent Non-existent 0

Existence 2

Variable environmental condition^* Observation method Existence / non-existent Existence +1

Vulnerability to environmental risk ^** Questionnaire – medical examination Existence / non-existent Existence +1

Final score of environmental component Without normalized weight Job assessment: 0–11 Low 0–0.99

Personal assessment: 0–12 Moderate 1–1.99

With normalized weight Job assessment: 0–3 High 2–2.99

Personal assessment: 0–4 Very high 3–4

Component	Tools	Range of score / risk level	Final score
Noise	Environmental / personal assessment	0–140 dB for environmental assessment, > 100 % Dose for personal assessment	0–65 dB	0
			66–82 dB	1
			82–85 dB	1.5
			> 85 dB and Dose > 100 %	2
Vibration	Whole Body Vibration (WBV) / Hand-Arm Vibration (HAV)	0.87 m.s^-2 for WBV and 2 m.s^-2 for HAV (OEL)	Lower than allowed level	0
			Higher than allowed level	2
Lighting	Environmental / local assessment	270 lux for lighting and 100 nit for illuminance (OEL)	Lighting > 270 Lux	0
			Illuminance<100 nit
			Lighting<270 Lux	2
			Illuminance > 100 nit
Thermal stress	Direct measure	Existence of thermal stress	In allowable range	0
			Out of allowable range	2
Confined space	Observation method	Existence / non-existent	Non-existent	0
			Existence	2
Variable environmental condition^*	Observation method	Existence / non-existent	Existence	+1
Vulnerability to environmental risk ^**	Questionnaire – medical examination	Existence / non-existent	Existence	+1
Final score of environmental component	Without normalized weight	Job assessment: 0–11	Low	0–0.99
		Personal assessment: 0–12	Moderate	1–1.99
	With normalized weight	Job assessment: 0–3	High	2–2.99
		Personal assessment: 0–4	Very high	3–4

^* If applicable. ^** In case of individual index calculation.

Environmental ergonomics is a part of ergonomics that studies the harmful physical factors of the workplace and their impact on human performance [30].

The following indicators were used to evaluate this component:

Noise in the workplace

Vibration in the workplace

Lighting

Thermal stresses in the workplace

Confined space

It should be noted that exposure time is considered as an important risk factor in all tools used in the model. Therefore, this risk factor is present in the final score of the model as a latent variable.

2.3 Delphi study

In the next step, to complete the list of measured parameters according to the industry characteristics and the weighting of criteria and sub-criteria, the Delphi method and the Analytic Hierarchy Process (AHP) was used.

The Delphi method is a structured communication method or technique developed initially for prediction based on expert consensus. This method is a structured process for collecting and classifying the knowledge available to a group of experts, which is done by distributing questionnaires among these people and controlling feedback on the answers and comments received. Participants in the Delphi study included 5 to 20 experts [31, 32].

In this study, a Delphi questionnaire was designed after determining the parameters affecting the ergonomic index. To properly integrate the majority of the country’s specialists, the opinions of 30 experts, including Ph.D. and MS graduates in the fields of occupational health engineering, ergonomics, occupational medicine, industrial psychology, and physiotherapy, employed in 25 universities and 15 large power plants and manufacturing industries, in three stages of Delphi study were collected. In the first stage of the Delphi study, experts were asked to comment on the model’s overall structure, and in case other components or parameters were kept in mind, the model was approved at this stage. In the second stage, experts were asked to prioritize components and parameters according to their importance. At the end of this phase, all the studied parameters, the tools used to measure the values of the indicators, and their scoring range were determined according to the panel opinions. Then, to determine the importance of each of the components (criteria) and indicators to be measured (sub-criteria) in each of the job subgroups and to choose the weight of each parameter, the analytic hierarchy process (AHP) was used.

Content validity ratio (CVR) and content validity index (CVI) were used to determine the content validity of the model. The acceptable limit value of the CVR was considered 0.33 according to the Lawshe table and proportional to the number of participants in the Delphi study (30 experts) [33]. Also, the acceptable limit value of the CVI was considered to be 0.79 [34]. Cronbach’s alpha method was used to evaluate the reliability of the model. To evaluate the internal consistency of the model, 130 employees from three occupational groups, administrative or office (N = 44), operational (N = 43), and service (N = 43), were studied during the pilot phase. An alpha coefficient of 0.7 or higher was considered as the minimum score required to confirm the model’s reliability [35].

2.4 Analytic Hierarchy Process (AHP)

The Analytic Hierarchy Process is a multi-criteria decision-making method for weighting the criteria and selecting the optimal option. Thomas L. Saaty introduced this method in 1983. The purpose of this method is to prioritize several criteria or options. Once the goal has been set, criteria for decision-making must be identified. These criteria are paired based on purpose, and their weight is determined. Finally, the options are paired comparisons according to each criterion, and the final priority of the options is determined [36]. The main purpose of the hierarchical analysis process method is to select the best option based on different criteria by forming a pairwise comparison matrix [37]. It should be noted that the weight of the main components and parameters will be different in each job subgroup.

2.4.1 Calculate weight

In the hierarchical process, the elements of each level are compared in pairs at a higher level than their respective element, and their weights are calculated, called relative weights. Next, the final weight of each option is specified, which is called the absolute weight. Then the weight of the criteria is determined concerning the goal, and combining them determines the final weight of the options. All comparisons in the analytical hierarchy process are made in pairs. In these comparisons, decision-makers will use verbal judgments [37]. Then, to increase the reliability of the results of the analysis of the questionnaires, the consistent rate of the system is controlled, and the acceptable amount of the decision was calculated. In the expert panel questionnaire, which is based on pairwise comparisons of all elements, the probability that a variable is not considered is zero.

Therefore, because all factors have been considered in this assessment and the designer cannot orient the design in a specific way, questionnaires based on pairwise comparisons have validity.

The reliability values of the expert panel questionnaire were considered the same as the adjustment rate. In this study, a value of 0.1 or less was considered as the acceptable compatibility limit of pairwise comparisons.

The final weights were calculated according to the purpose of the research in Expert Choice software version 11. This software is a system for analyzing, synchronizing, and modifying complex decisions and evaluations. Depending on the purpose, the influential factors constitute a tree of criteria, sub-criteria, factors, and options. Expert Choice utilizes the data provided to prioritize goals and informs the user of the correlations (comparisons compatibility rate). The values of the verbal preferences/judgments of element i over element j for pairwise comparisons are presented in Table 4.

Table 4
Values of verbal preferences / judgments of element i over j for pairwise comparisons

Number Definition

9 Extremely preferred

7 Very strongly preferred

5 Strongly preferred

3 Moderately preferred

1 Equally preferred

2,4,6,8 Intermediate preferred

Number	Definition
9	Extremely preferred
7	Very strongly preferred
5	Strongly preferred
3	Moderately preferred
1	Equally preferred
2,4,6,8	Intermediate preferred

Finally, using the studied model and based on the parameters in each criterion, the ergonomic conditions of each task will be evaluated based on the type of jobs, and finally, an ergonomic risk index will be obtained, which is the basis for decision-making about control measures. It should be noted that the ergonomic risk index is used in this article due to its ease of expression, and here it is equivalent to the “risk due to job/workplace design” (Table 5).

Table 5

Guide for the determining risk levels of the ergonomic risk index (risk index or risk due to job/workplace design)

Range of score	Risk level	Control measures
0 – 1.99	Acceptable (low)	No need any control measures
2 – 3.99	Tolerable and recoverable (Moderate)	Need for control measures in near future
>4	Not acceptable (high)^*	Urgent demand for control measures

* If one of the three components in the model scores the maximum score or is at a very high-risk level, the overall ergonomic index will be within the not-acceptable (high) risk level range.

In the following, due to the different scoring ranges in various tools, their score is matched after evaluating each parameter according to the score or levels of risk.

Also, in the proposed method, the following items will be added to the final score to personalize the ergonomic risk levels and observe the effect of individual parameters in calculating the personal ergonomic index (after the job assessment).

SPSS software version 25 was used to calculate descriptive statistics (mean, standard deviation, frequency, etc.) and Cronbach’s alpha.

2.5 Applying individual risk factors

If any of the following individual risk factors are present, a score will be added to the final score of the physical ergonomics component:

Age over 55 years, Body Mass Index (BMI) in the range of obesity, systemic complications such as bone diseases, romatological, inflammatory and visceral, osteoporosis, osteomalacia, history of cancer, history of structural problems spine, history of major trauma to the spine (fall from a height, accident, sports, etc.), history of skeletal surgery (especially spine), rheumatoid arthritis, history of long-term use of corticosteroid drugs such as corticosteroids, history of smoking and shift work.

If any of the following individual risk factors are present, a score will be added to the final score of the cognitive ergonomics component:

Chronic mental illnesses such as depression, anxiety, stress, post-traumatic stress disorder (PTSD), etc.

If any of the following risk factors are present, a score will be added to the final score of the environmental ergonomics component:

In case of variable environmental conditions and harmful physical agents of the working environment (such as activities in maintenance jobs), individual sensitivity to the physical agent of the working environment (such as sensitivity to noise, fear of light, etc.).

3 Results

A total of 30 experts were involved in the present study. The expert panel’s mean age and work experience were 39.66±7.13 and 7.88±4.13 years, respectively. 70.6% of the experts were Ph.D., and 29.4% had an MS degree. The three-stage Delphi study showed that the number of deleted parameters was one item (burnout from the cognitive ergonomics component), and the number of remaining parameters in the model was 16.

The mean CVI was 0.92 (the obtained value was higher than 0.79, and the content validity of the model was confirmed). The mean CVR was also determined to be 0.80. The overall average was higher than 0.33 according to the number of panel members and the Lawshe method and was approved. To assess model reliability, 130 employees from three occupational groups, administrative (N = 44), operational (N = 43), and service (N = 43) were studied during the pilot phase. The mean and standard deviation of age and work experience of the subjects were 43.57±7.36 and 10.41±4.82 years, respectively. 10% of the studied employees were female, and 90% were male. 23% had a diploma, 26% had a master’s degree, 45% had a bachelor’s degree, and 6% had a master’sdegree.

Cronbach’s alpha values for each of the physical, environmental, and cognitive components and the entire model were 0.91, 0.87, 0.85, and 0.89, respectively, and model reliability was confirmed. Ultimately, the findings mentioned above showed that in the initial model, after conducting a three-stage Delphi study and implementing the pilot phase on 130 people, the validity and reliability values of the model were acceptable. The final obtained model for the three occupational groups of office, operational, and services, along with the weight values of the components and parameters, are presented in Figs. 2–4.

Fig. 2

Ergonomic evaluation model of office jobs.

Fig. 3

Ergonomic evaluation model of operational jobs.

Fig. 4

Ergonomic evaluation model of services jobs.

The obtained model for office jobs revealed that the weight values of physical, cognitive, and environmental components were 0.44, 0.42, and 0.14, respectively.

Parameters used to calculate the component of physical ergonomics include postural condition (0.55), manual material handling (0.035), prevalence, severity and discomfort caused by WRMSDS (0.20), muscle fatigue (0.115), consumption energy (0.10), biomechanics (sub-parameter: adding 1 point), anthropometry (sub-parameter: adding 1 point) and individual risk factors (sub-parameter: adding 1 point). Parameters used to calculate the cognitive ergonomic component include mental workload (0.48), occupational stress (0.27), sleep quality (0.11), cognitive failure (0.14), and chronic mental disorders (sub-parameter: adding 1 point). Parameters used to calculate the environmental ergonomic component include noise (0.16), vibration (0.06), thermal stress (0.33), lighting (0.41) and work in confined space (0.04), individual risk factors (sub-parameter: adding 1 point) and variable environmental conditions (sub-parameter: adding 1 point). It was found that the highest weight values for calculating physical, cognitive, and environmental components in office jobs were related to the postural condition, mental workload, and workplace lighting, respectively (Fig. 2).

The obtained model for operational jobs explained that the weight values of physical, cognitive, and environmental components were 0.57, 0.33, and 0.10, respectively.

Parameters used to calculate the component of physical ergonomics include postural condition (0.44), manual material handling (0.21), prevalence, severity and discomfort caused by WRMSDS (0.15), muscle fatigue (0.11), consumption energy (0.09), biomechanics (sub-parameter: adding 1 point), anthropometry (sub-parameter: adding 1 point) and individual risk factors (sub-parameter: adding 1 point). Parameters used to calculate the cognitive ergonomic component include mental workload (0.57), occupational stress (0.13), sleep quality (0.17), cognitive failure (0.13), and chronic mental disorders (sub-parameter: adding 1 point). Parameters used to calculate the environmental ergonomic component include noise (0.34), vibration (0.23), thermal stress (0.08), lighting (0.17) and work in confined space (0.18), individual risk factors (sub-parameter: adding 1 point) and variable environmental conditions (sub-parameter: adding 1 point). It was found that the highest weight values for calculating physical, cognitive, and environmental components in operational jobs were related to the postural condition, mental workload, and workplace noise, respectively (Fig. 3).

The obtained model for services jobs revealed that the weight values of physical, cognitive, and environmental components were 0.67, 0.17, and 0.16, respectively.

Parameters used to calculate the component of physical ergonomics include postural condition (0.41), manual material handling (0.20), prevalence, severity and discomfort caused by WRMSDS (0.15), muscle fatigue (0.10), consumption energy (0.14), biomechanics (sub-parameter: adding 1 point), anthropometry (sub-parameter: adding 1 point) and individual risk factors (sub-parameter: adding 1 point). Parameters used to calculate the cognitive ergonomic component include mental workload (0.38), occupational stress (0.17), sleep quality (0.37), cognitive failure (0.08), and chronic mental disorders (sub-parameter: adding 1 point). Parameters used to calculate the environmental ergonomic component include noise (0.22), vibration (0.12), thermal stress (0.30), lighting (0.26) and work in confined space (0.10), individual risk factors (sub-parameter: adding 1 point) and variable environmental conditions (sub-parameter: adding 1 point). It was found that the highest weight values for calculating physical, cognitive, and environmental components in operational jobs were related to the postural condition, mental workload, and thermal stress in the workplace noise, respectively (Fig. 4). The value of the adaptation rate was calculated to be less than 0.1 in all cases.

3.1 Ergonomic index leveling

Finally, the risk matrix was created based on the values of each of the three studied ergonomic components. Then it was divided into three levels of acceptable (low), tolerable and recoverable (medium), and unacceptable (high) risk and in accordance with the principle of ALARP (as low as reasonably practicable) and the opinion of the expert’s panel. For this purpose, the maximum tolerable ergonomic index (average risk) in each physical, environmental and cognitive component was determined. The maximum final tolerable ergonomic score was defined according to the values of the three components, and the risk matrix was formed. The following equations are proposed to calculate the ergonomic risk index or risk due to job/workplace design: $ERI = [PE \times W] + [CE \times W] + [EE \times W]$ (1) $Physical Ergonomics = \sum P_{i} W_{Pi}$ (2) $Cognitive Ergonomics = \sum C_{i} W_{Ci}$ (3) $Environmental Ergonomics = \sum E_{i} W_{Ei}$ (4)

Where,

ERI: Ergonomic risk index; PE: Physical ergonomic; CE: Cognitive ergonomic; EE: Environmental ergonomic; Pi: Numerical index of sub-parameters of physical ergonomic; Wpi: Normalized weight of each of sub-parameters of physical ergonomic; Ci: Numerical index of sub-parameters of cognitive ergonomic;

W_ci : Normalized weight of each of sub-parameters of cognitive ergonomic; E_i: Numerical index of sub-parameters of environmental ergonomic; W_Ei: Normalized weight of each of sub-parameters of environmental ergonomic; W: Normalized weight of each of parameters of ergonomic risk index.

The input values for determining the scoring values of the three components of physical, cognitive, environmental, and the guide for determining the risk level of the ergonomic index are given in Tables 2–5. The standard guide of the applied methods was used to determine the cut-off point distribution. Also, to accurately identify ergonomic risk factors based on tasks and sub-tasks, the use of the tabular task analysis (TTA) designed during the present study was suggested (Table 6).

Table 6

Tabular task analysis (TTA) worksheet

		Unit:	Sector:		Date:
Job	Task	Sub-task	Ergonomic risk	Sub-task	Total time	Basic motion
		(work element)	factor^*	time	(in shift work.)	element^**

^* Posture, Force, Repetitive Movement, Vibration, Time, Manual Material Handling (MMH), Pulling, Pushing, Stress, Mental Workload, Noise, Thermal Stress, Lighting, etc. ^** Flexion, Extension, Hyper Extension, Abduction, Adduction, Supination, Pronation, Elevation, Depression.

4 Discussion

Currently, it is crucial to pay to the ergonomic management in different working environments with a comprehensive, forward-looking, proactive approach, focusing on continuous improvement and resilience engineering cycles. Following these concepts, the importance of assessments conducted in this area and the tools applied to assess and consequently evaluate and determine the risk levels and control measures as the heart of risk management systems in various sciences becomes more apparent. Many studies have been conducted in assessing the physical and sometimes cognitive components of ergonomics in the workplace so far [38].

However, various studies have shown that practical studies in this field require comprehensive attention to the workplace’s multiple components and dimensions of ergonomics. In the present study, three physical, cognitive and environmental components of ergonomics were studied to create a novel and comprehensive method of ergonomics assessment in different occupational groups in work environments. Among the selected parameters to evaluate the ergonomic index, 17 parameters remained in the model, and one parameter was removed according to the output of the Delphi study (burnout).

The evaluated parameters are the same in all three obtained models. The only difference between the assessment models of the ergonomic index is in the weight values of the existing components and parameters as well as the evaluation tool of some parameters in different occupational groups (e.g., in-office jobs, posture evaluation was done using the ROSA method and in operational or service jobs posture evaluation was done using REBA or RULAmethods).

The validity and reliability of the model were confirmed using CVR, CVI, and Cronbach’s alpha during the pilot phase.

The obtained model for office jobs showed that the weight values of physical, cognitive, and environmental components were 0.44, 0.42, and 0.14, respectively (Fig. 2).

The obtained model for operational jobs revealed that the weight values of physical, cognitive, and environmental components were 0.57, 0.33, and 0.10, respectively (Fig. 3).

Ultimately, the obtained model for services jobs demonstrated that the weight values of physical, cognitive, and environmental components were 0.67, 0.17, and 0.16, respectively (Fig. 4).

Physical components and parameters of physical condition during work, mental workload, lighting, and thermal stress in the workplace were among the most important parameters in the three groups of office, operational, and services jobs.

A previous study indicated that personal, psychological, and psychosocial parameters could be among the most critical predictors in the chronicity of acute and subacute nonspecific low back pain and ergonomic disorders. Hence, paying attention to all the mentioned factors in any workplace has particular importance [9].

Previous studies have shown that the use of different ergonomic evaluation methods as the most crucial step of ergonomic management plan in the workplace, is the most important part of ergonomic intervention programs in various industries and organizations and the implementation of appropriate and successful control programs requires the use of appropriate assessment tools [38 –41].

In this regard, the study conducted by Sadeghi Yarandi et al. showed that there was a significant relationship between the parameters of health responsibility, stress management, exercise, and nutrition on the topic of lifestyle, the component of physical demands of the job from the subject of occupational stress and physical load components, time pressure and mental workload and the prevalence of WRMSDs, which indicates the importance of pay attention to all aspects of ergonomics in the evaluation stage of ergonomic management and the existence of practical tools in this field [3]. The results of the study conducted by Mohammadfam also revealed that in addition to the physical parameters of the workplace, workload, job stress, and time pressure are among the essential parameters in ergonomic evaluation models [42]. Also, the study conducted by Schwartz et al. revealed that mental workload, different body postures during work, and occupational stress are related and can have mutualeffects [19].

A study conducted by Xinming Li et al. in 2019 showed that risk assessment methods with a proactive approach are very important due to the high physical demands required to work in the industry. The Physical Demands Analysis (PDA) method is a standard tool for assessing risks in three areas: physical, cognitive, and environmental. Among the parameters evaluated in the mentioned tools, we can mention occupational demands, environmental conditions, physical conditions, manual material handling, etc. [43]. All the above studies indicate that many key risk factors and indicators can evaluate and predict ergonomic disorders in the workplace. Therefore, the present study tried to create a comprehensive and integrated model to assess the most important ergonomic components and parameters in the work environment. The current model can also be employed to plan and implement management measures with prospective and proactive approaches. Considering the examination of many of the most important influential variables in the ergonomic index of personnel of different organizations and industries, the present model can be a suitable basis for planning control measures and making management decisions in different societies andorganizations.

4.1 Strengths and limitations of the study

Among the strengths of the present study is a novel model based on the most important ergonomic components in the workplace (physical, cognitive and environmental) and the most critical risk factors affecting the determination of these three components. Using this model can be a practical step toward identifying, assessing, and evaluating the most critical dimensions of ergonomics in the workplace, extracting the ergonomic index of jobs and employees, and optimal planning to implement corrective measures to reduce and eliminate physical, cognitive, and environmental risk factors.

Among the limitations of the present model is the lack of organizational or macro ergonomics components (such as dominant leadership styles in the organization, roles, communication, organizational structure, etc.) as one of the four main components of ergonomics due to executive time limitations. It is suggested that researchers in future studies consider the component of organizational ergonomics, apply the current model, and report its effectiveness in reducing the levels of ergonomic risk factors. One of the limitations of the AHP method is the lack of study of the dependence between different parameters. However, many parameters are interrelated and affect each other. It is suggested that in future studies, the analytic network process (ANP) method be used to examine the correlation values between different variables.

Since accurate identification of ergonomic hazards and risk factors is the most crucial prerequisite for assessing the ergonomic index of employees, in this research, it is recommended to use the TTA (tabular task analysis) designed in the present study (Table 6).

5 Conclusion

Examination of the studied model showed that the parameters used to calculate the component of physical ergonomics included the postural condition, manual material handling, prevalence-severity-discomfort caused by WRMSDS, muscle fatigue, energy consumption, biomechanics, anthropometry, and individual risk factors. The parameters used to calculate the cognitive ergonomic component included mental workload, occupational stress, sleep quality, cognitive failure, and chronic mental disorders, and finally, the parameters used to calculate the environmental ergonomic component included noise, vibration, heat stress, lighting, and work in a confined space, individual risk factors and unstable working environment. This model can be a practical step toward properly evaluating the ergonomic components and planning to implement control measures to reduce physical, cognitive, and environmental risk factors.

Conflict of interest

The authors declare that there is no conflict of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval

Not applicable.

Funding

None to report.

Footnotes

Acknowledgments

This research is part of a project to develop and implement a comprehensive TUGA ergonomic management and analysis model (TEMA), supported by the MAPNA Turbine Engineering and Manufacturing Company (TUGA). The authors express their gratitude to TUGA and the experts participating in the Delphi study.

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Development of a novel ergonomic index assessment in the workplace based on physical,cognitive,and environmental components

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1 Introduction

2.1 Identification of the studied parameters and measuring tools

2.2 Creating an ergonomic index assessment model algorithm

2.2.1 Physical ergonomics (Table 1)

2.4 Analytic Hierarchy Process (AHP)

2.4.1 Calculate weight

Table 4 Values of verbal preferences / judgments of element i over j for pairwise comparisons Number Definition 9 Extremely preferred 7 Very strongly preferred 5 Strongly preferred 3 Moderately preferred 1 Equally preferred 2,4,6,8 Intermediate preferred

3 Results

4.1 Strengths and limitations of the study

5 Conclusion

Conflict of interest

Ethical approval

Funding

Footnotes

Acknowledgments

References

Table 4
Values of verbal preferences / judgments of element i over j for pairwise comparisons

Number Definition

9 Extremely preferred

7 Very strongly preferred

5 Strongly preferred

3 Moderately preferred

1 Equally preferred

2,4,6,8 Intermediate preferred