Quantification of risk perception: Development and validation of the construction worker risk perception (CoWoRP) scale

Journal of Safety Research 71 (2019) 25–39

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Quantification of risk perception: Development and validation of the construction worker risk perception (CoWoRP) scale Siu Shing Man a,⇑, Alan Hoi Shou Chan a, Saad Alabdulkarim b a b

Department of Systems Engineering and Engineering Management, City University of Hong Kong, Kowloon, Hong Kong Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia

a r t i c l e

i n f o

Article history: Received 2 January 2019 Received in revised form 18 May 2019 Accepted 4 September 2019 Available online 12 November 2019 Keywords: Construction industry Construction workers Risk perception Risk-taking behavior Scale development

a b s t r a c t Introduction: The construction sector is leading in the number of accidents and fatalities; risk perception is the key to driving these numbers. Previous construction safety studies on risk perception quantification have not considered affective risk perception of construction workers or conducted comprehensive reliability and validity testing. Thus, this study aims to fill this need by developing a psychometrically sound instrument – the Construction Worker Risk Perception (CoWoRP) Scale – to assess the risk perception of construction workers. Method: Four phases of scale development, namely, item development, factor analysis, reliability assessment, and validity assessment were conducted with the collection and testing of data from a group (n = 469) of voluntary construction workers in Hong Kong. Results: The CoWoRP Scale with 13 items was shown to have acceptable test–retest reliability, internal consistency reliability, as well as content, convergent, discriminant, and criterion-related validity. Also, the CoWoRP Scale was affirmed to have three dimensions of worker risk perception, namely risk perception – probability, risk perception – severity, risk perception – worry and unsafe. These three dimensions of worker risk perception were negatively correlated with their risk-taking behavior. Conclusions: The CoWoRP Scale is a reliable and valid instrument for measuring the risk perception of construction workers and is expected to facilitate the construction safety studies that take risk perception of construction workers into account. Practical applications: The CoWoRP Scale could serve as an aptitude test to identify the characteristics of construction workers most likely to perceive lower risk in risky work situations. In turn, this information could help safety management provide safety training programs to those workers to enhance their risk perception and thereby minimizing their risk-taking behavior, reducing unnecessary training costs, and improving the construction safety performance. Ó 2019 National Safety Council and Elsevier Ltd. All rights reserved.

1. Introduction Due to the launch of large-scale infrastructure projects, the Hong Kong construction industry has significantly thrived recently. Large-scale infrastructure projects are defined as those infrastructure projects with a construction cost of greater than HK$ 1 billion (US $128.21 million; Mok, Shen, & Yang, 2015). One example is the Tung Chung New Town Extension project, which records a construction cost of HK $12.76 billion (US $1.64 billion; Civil Engineering and Development Department, 2018). The noticeable growth in the scale and complexity of construction projects has invoked a huge demand for construction workers. The Council (2018) reported that the total number of valid registered construc⇑ Corresponding author. E-mail address: [email protected] (S.S. Man). https://doi.org/10.1016/j.jsr.2019.09.009 0022-4375/Ó 2019 National Safety Council and Elsevier Ltd. All rights reserved.

tion workers in Hong Kong has increased from 225,625 in late 2007 to 463,735 in early 2018, accounting for an increase of 105.5%. The Labour Department, , 2017 also verified that, from 2012 to 2016, the number of industrial fatalities and the industrial fatality rate in the Hong Kong construction industry have been steadily reduced through the concerted effort of the various stakeholders of occupational safety. Despite these improvements, the construction industry still has the largest number of fatalities relative to all other industrial sectors over the past decade. In 2016, 34.2% of industrial accidents and 55.6% of industrial fatalities occurred in the Hong Kong construction industry (Labour Department, 2016). Compared to other industrial sectors, fatality and accident rates in the construction industry recorded roughly three and two times higher than average corresponding rate, respectively (Labour Department, 2016). The number of industrial fatalities in the Hong Kong construction industry increased from 12 in 2016 to 22 in

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2017, indicating an increase of 83.3% (Labour Department, 2018). These observations corroborated that the construction industry is a dangerous industry compared with other industries in Hong Kong. Apart from Hong Kong, other countries, such as the United States and the UK recognized the construction industry as dangerous (Teran, Blecker, Scruggs, García Hernández, & Rahke, 2015). According to the Construction Chart Book (CPWR – The Center for Construction Research and Training., 2018), in 2015 about 20% of the total (4,836) U.S. industrial fatalities happened in the construction sector, indicating an increase of 26% compared to the number of construction fatalities in 2011. Moreover, the construction fatality rate in the United States in 2015 was 9.9 per 100,000 full-time equivalent workers, representing an increase of 10% compared to those in 2011. The possible reasons for the increase in the number of construction fatalities are believed to be related to the risk-taking behavior of construction workers. The underlying causes of their risk-taking behavior, such as social influence, situational influence, safety supervision, attitude toward risk-taking behavior, and risk perception have been identified in a previous qualitative study of Man, Chan, and Wong (2017). In Hong Kong, the occupational safety and health ordinance (Chapter 509) was enacted to ensure the safety and health of workers when they are at work, both non-industrial and industrial (Labour Department, 2019). The Commissioner for Labor is empowered to enforce this ordinance by issuing improvement notices and suspension notices against workplace activities, which may expose employees to an imminent hazard. Any employer who fails to comply with both notices commits an offence, punishable by a fine of up to HK$ 200,000 (US $25,641) and HK$ 500,000 (US $64,103) respectively, and imprisonment of up to 12 months. Given the unsatisfactory safety performance of the construction industry, considerable research focused on the contributing factors leading to industrial accidents. Traditionally, these factors could be classified into two domains, namely, unsafe behaviors that deviate from acceptable safety procedures and unsafe conditions, such as unsafe mechanical or physical environment and hazards (Shin, Gwak, & Lee, 2015). In Hong Kong, various stakeholders of construction safety have been making efforts over the last two decades to remove unsafe conditions by offering protective clothing and tools and by developing safety managerial policies and systems and legislations (Development Bureau, 2014). Despite the apparent effectiveness in reducing the rate of construction accidents, the number of construction-related accidents has increased over the past five years (Labour Department, 2016). Consequently, other than eliminating unsafe conditions, extra efforts are necessary in removing unsafe behaviors among construction workers to reduce the number of construction accidents and fatalities. Previous studies confirmed that unsafe human behaviors are considered the cause of approximately 80% of accidents (Fleming & Lardner, 2002; Han & Lee, 2013). In addition, the risk perception of construction workers is one of the important factors that influences their unsafe behaviors at work (Man et al., 2017). Thus, extra research efforts must be focused on understanding the risk perception of construction workers. Risk perception (RP) can be referred to as the intuitive risk judgment made by the majority of people to evaluate hazards (Slovic, 1987). This judgment consists of two components, namely, cognitive and affective (Sjöberg, 1998; Slovic, Finucane, Peters, & MacGregor, 2004). The cognitive component relates to the two aspects of judgment: the ‘‘probability” of experiencing an accident or an injury and its ‘‘severity” resulting from exposure to a risk source (Kouabenan, Ngueutsa, & Mbaye, 2015). For the affective component, emotions have been recognized as important in RP (Sjberg, 2007). In accordance with the study of Rundmo (2000), the two aspects of the affective component of RP have been mea-

sured by asking respondents whether they ‘‘worry” and whether they feel ‘‘unsafe” regarding the outcomes of risky scenarios. Various research efforts have focused on the understanding of the effect of RP on human behaviors. For instance, Plapp and Werner (2006) considered RP as fundamental for behaviors toward risks associated with natural hazards, such as flood, windstorm, and earthquake. Moreover, the scope has been extended to include technological hazards such as food technology hazards (Bearth & Siegrist, 2016). The concept of RP has also been applied to public health-related issues, such as binge drinking (Bajac, Feliu-Soler, Meerhoff, Latorre, & Elices, 2016; Chen, 2017), chicken contamination (Kuttschreuter, 2006), and influenza vaccination (Weinstein et al., 2007). Apart from the significant value of RP to public health-related issues, the importance of RP has notably solicited increasing attention from the researchers in safety research areas, such as transportation and occupational safety. In transportation safety, Lu, Xie, and Zhang (2013) conducted a study to explore how and why anger and fear can influence driving RP of drivers. Cristea and Delhomme (2016) found that RP played an important role in engaging or not in risky behaviors among bicyclists. Ji, Yang, Li, Xu, and He (2018) discovered that RP negatively influences incident involvement among airline pilots. Harbeck and Glendon (2018) affirmed that RP of young drivers negatively predicted their reported engagement in risky driving. As for occupational safety, a few studies focused on a diversity of industries in the past decade. The effect of RP on various safety behaviors, such as the usage of hearing protection devices (Arezes & Miguel, 2008) and involvement in safety management (Kouabenan et al., 2015), was studied. Generally, the effect of RP on workers concerning their safety behavior is affirmed to be positive. In the aviation industry, Ji, You, Lan, and Yang (2011) investigated the effects of hazardous attitude, RP, and risk tolerance on safety behaviors among 118 commercial airline pilots in China. They found a direct positive influence of RP on the safety behaviors of airline pilots. In the construction industry, Perlman, Sacks, and Barak (2014) studied RP among construction superintendents by asking them to assess their risk level and to estimate the probability and the severity of possible accidents regarding the hazards in a typical construction project with different methods (including virtual environment, photographs, and documents) of presenting the hazards. They verified that most participants assessed higher risk levels to hazards attributable to moving equipment in the virtual environment than those presented with photographs and documents. Moreover, Gürcanlı, Baradan, and Uzun (2015) studied the evaluation of the RP of construction equipment operators in Turkey and validated that the RP of the operators who took safety and health training and those who worked with flaggers was statistically significantly higher than that of the untrained operators and operators who worked without flaggers. This finding consequently affirmed the importance of safety and health training and working with an assistant, such as a flagger, in increasing the RP of workers (Gürcanlı et al., 2015). Using a sample of 120 construction workers, Xia, Wang, Griffin, Wu, and Liu (2017) recently tested the hypotheses that RPs (rational and emotional perspectives) have a positive but different influence on safety behavior. They found that emotional RP, which was referred to individual’s direct perception of risk, significantly affects the safety behavior of construction workers, whereas rational RP, which was defined as the multiplication of the risk’s probability and severity, has no significant effects on safety behavior of construction workers. Although the importance of RP in construction safety has been recognized recently, a lack of a well-designed (i.e., reliable and valid) measurement for assessing the RP of construction workers is observed. For instance, Xia et al. (2017) had only performed

S.S. Man et al. / Journal of Safety Research 71 (2019) 25–39

reliability testing for the measurement of RP; however, detailed validity assessments, such as content validity, convergent validity, discriminant validity, and criterion-related validity, were not reported. In addition, Xia et al. (2017) previously affirmed that the measurement of the RP of construction workers did not consider the two aspects (i.e., worry and unsafe) of affective RP. Evidently, Xia et al. (2017) made a pioneering attempt in measuring the RP of construction workers and reported valuable findings. However, their study lacked detailed validity assessments and consideration for the two aspects (i.e., worry and unsafe) of affective RP. For the indication of how this study is different from and further advances previous similar work in the RP quantification literature, a comprehensive survey of published health and safety related studies (n = 18) on RP quantification was conducted and the results are summarized in Appendix A. The results showed that although five construction safety studies made an attempt to measure the cognitive RP of construction workers, none of them considered affective RP of construction workers and did report validity tests such as content, convergent, discriminant, and criterion-related validity. Therefore, the current study aimed to fill this research gap by developing and establishing through a testing of a well-designed instrument called the Construction Worker Risk Perception (CoWoRP) Scale to assess the RP of construction workers with incorporating affective RP and conducting validity assessments. 2. Methodology For the development of the CoWoRP Scale for assessing the RP of construction workers, four phases of activities, namely, item development, factor analysis, reliability assessment, and validity assessment (DeVellis, 2016), were conducted with the collection and testing of data from a group (n = 469) of voluntary construction workers in Hong Kong. A convenience sampling technique was used for the selection of construction workers in the Hong Kong government construction projects. 2.1. Phase I: Item development The items for the CoWoRP Scale were identified through a literature review (e.g., safety information, safety guidance, casebooks of fatal accidents, and industrial accident statistics) and a focus group discussion with five experienced safety and health professionals in the construction industry. The five experienced safety and health professionals were safety consultants of over 10 years work experience in construction safety, such as safety audit/review, safety training, risk assessment, and safety management advisory services. After the literature review and the focus group discussion, a total of 36 risky scenarios with potential danger to construction workers at work were created (Table 1). These scenarios were as general as possible to ensure that construction workers of all the various trades are likely to experience them in real-life work environments and can easily understand the risks involved in the situations. The four aspects of the two components (cognitive and affective) of RP, namely, RP – probability, RP – severity, RP – worry, and RP – unsafe were measured with scale items in four respective sets of questions. In this study, RP – probability and RP – severity were defined as the extent to which people assess the probability and severity of experiencing an accident or an injury resulting from exposure to a risk source, respectively. RP – worry and RP – unsafe were referred to the extent to which people worry about and feel unsafe regarding the outcomes of risky scenarios, respectively. Each set of questions contained nine risky scenarios involving fall from height, being struck by falling object, contact with electricity or electric discharge, slip, trip or fall on the same level, being

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injured whilst lifting or carrying, and other safety risks (Labour Department, 2016). Specifically, items 1 to 9 were used to measure RP – probability with an 11-point phrase completion scale ranging from 0 indicating ‘‘not at all likely” to 10 indicating ‘‘extremely likely;” items 10 to 18 were used to measure RP – severity with an 11-point phrase completion scale ranging from 0 indicating ‘‘not at all severe” to 10 indicating ‘‘extremely severe;” items 19 to 27 were used to measure RP – worry with an 11-point phrase completion scale ranging from 0 indicating ‘‘not at all worried” to 10 indicating ‘‘extremely worried;” and items 28 to 36 were used to measure RP – unsafe with an 11-point phrase completion scale ranging from 0 indicating ‘‘extremely safe” to 10 indicating ‘‘extremely unsafe.” The use of 11-point phrase completion scale in the CoWoRP Scale is attributable not only to its better psychometric properties than 4-, 5-, and 6- point Likert scales but also to its easy comprehension (Leung, 2011). The underlying reason for using four different sets of nine scenarios to measure four aspects of RP separately other than using the same nine scenarios or the same all 36 scenarios to measure four aspects of RP repeatedly is to avoid measurement error of items to be correlated (DeVellis, 2016). For the exploration of the extent to which the content domain of interest can be reflected by a specific set of items (DeVellis, 2016), the content validity of the CoWoRP Scale items was evaluated using item- and scale-level content validity indices with another group of five experienced occupational safety and health professionals (Polit & Beck, 2006). They were asked to rate each of the 36 scale items in terms of its relevance to the underlying construct (i.e., RP) with the use of a four-point scale (1-not relevant, 2-somewhat relevant, 3-quite relevant, and 4-highly relevant; Polit & Beck, 2006). In other words, the professionals were asked to rate the extent to which these items can illustrate potential construction safety risks. According to Polit and Beck (2006), item-level content validity index was calculated as the number of experts giving a rating of either 3 or 4 (thus dichotomizing the ordinal scale into relevant and not relevant), divided by the total number of experts, while scale-level content validity index was defined as the average of the item-content validity indices for all items on the scale. Items were kept if they had an item-content validity index of 1.0 (Lynn, 1986). The result of content validity assessment showed that all 36 items had an item-content validity index of 1.0, leading to a scale-level content validity index of 1.0. Therefore, all the 36 items of the preliminary version of the CoWoRP Scale were, thus, retained with excellent content validity (Polit & Beck, 2006). 2.2. Questionnaire survey A questionnaire survey was conducted to collect data that were then analyzed in the following phases of activities (i.e., factor analysis, reliability assessment, and validity assessment). 2.2.1. Participants Participants were selected using a convenience sampling technique. A face-to-face questionnaire survey was conducted on the construction sites of the Hong Kong government construction projects. Potential participants were construction workers who worked on the construction sites during our visit and were invited to complete the questionnaire. Incentives (e.g., fast food store cash coupons or cooling towels) valued at $20 HK ($2.6 US) were given to those who completed the questionnaire to facilitate the participation of construction workers in this study. A total of 469 workers participated in this study. The Cochran’s formula was used to calculate a minimum sample size (385) for determine statistical significance (Cochran, 2007) where the margin of error was set at 5%, with a confidence level of 95%, ± 5% pre-

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Table 1 Details of thirty-six risky scenarios. Construct

Item

RP – probability 1 2 3 4 5 6 7 8 9 RP – severity 10 11 12 13 14 15 16 17 18 RP – worry 19 20 21 22 23 24 25 26 27 RP – unsafe 28 29 30 31 32 33 34 35 36

Content

Scale format

If you experience the following work events or situations, how likely will you be to experience negative consequences in your perspective? Working on the top of a container without using any safety measures Wearing a safety belt whose buckle is attached to the bamboo scaffolding as a secure anchorage when working on a bamboo scaffolding Working on a moving route of lifting Engaging in electrical works (e.g., electric arc welding) in a workplace that is affected by rainy weather Using electrical equipment with damaged wires Not wearing safety shoes on a construction site Lifting 17 kilograms of construction wastes on the ground with a stooped posture Smoking on a construction site Not wearing approved ear protectors when working in a noisy workplace If you experience the following work events or situations, how severe will the potential negative consequences be in your perspective? Working on an unstable trestle ladder Working at heights with high winds Working under suspended materials Using electrical equipment without insulation and proper earthing of electrical circuitry in a wet workplace Not checking the power source whether it is turned off before replacing a bulb Walking through a poorly lit corridor Pushing a wheelbarrow with heavy objects on an uneven ground Not wearing chemical protective gloves when handling chemicals Not using goggles when using abrasive wheels If you experience the following work events or situations, how worried will you be about the potential negative consequences? Wearing a safety belt that is not connected to the independent lifeline when working on a gondola Climbing up a beam to work without using any safety measures Staying under an outer wall bamboo scaffolding Not wearing insulating gloves when carrying out live works Cleaning or adjusting electrical equipment when the power source is not cut off Improperly placing wires on the ground Wearing too loose or too tight clothes to move heavy objects Using a phone when working on a construction site Not wearing masks when working in a dusty workplace If you experience the following work events or situations, how unsafe will you feel regarding the potential negative consequences? Climbing a bamboo scaffolding from ground up to the first floor Standing on the lifted fork of forklift to work Not wearing a helmet on a construction site Touching electric cables with the exposure of live parts, without knowing if the wire is live or not Immersing electric cables in water Walking through an improperly paved carpet or a mat Wearing protective gloves of inappropriate size to move heavy objects Drinking alcohol while working Not wearing a reflective vest when working in a dim workplace

An 11-point phrase completion scale ranging from 0 (indicating ‘‘not at all likely” to 10 (indicating ‘‘extremely likely”)

cision, and 0.5 population proportion. In our study, the margin of error for this study sample size (469) was 4.525% with a confidence level of 95%, ± 5% precision, and 0.5 population proportion. The demographic information of the participants, including age, gender, education, marital status, and work experience in the construction industry, was collected. Over 65% of the participants were between 26 and 55 years of age. Moreover, the majority of the respondents were male (94.03%), received at least primary school education (95.10%), and had at least one year of work experience in the construction industry (97.87%). For marital status, 64.61% of the respondents were married. Table 2 shows the detail of the demographic information of the participants. The majority of the sample were males, similar to the Hong Kong construction industry working population in which 90.35% of workers were male in 2017 (Census and Statistics Department, 2018). Therefore, this study sample better represents the targeted working population.

An 11-point phrase completion scale ranging from 0 (indicating ‘‘not at all severe” to 10 (indicating ‘‘extremely severe”)

An 11-point phrase completion scale ranging from 0 (indicating ‘‘not at all worried” to 10 (indicating ‘‘extremely worried”)

An 11-point phrase completion scale ranging from 0 (indicating ‘‘extremely safe” to 10 (indicating ‘‘extremely unsafe”)

2.2.2. Materials For testing the convergent, discriminant, and criterion-related validity of the CoWoRP Scale, in addition to the items of the CoWoRP Scale, items of other constructs, such as RP related to public daily-life health and safety, work stress, perceived behavioral control, and risk-taking behavior were added to the questionnaire. Although RP related to daily-life health and safety and RP related to construction safety have different contexts, they are similar constructs because of their concerning RP. Thus, the inclusion of RP related to daily-life health and safety was appropriate for convergent validity analysis of the CoWoRP Scale. Work stress is the response people may have when they are assigned with work demands and pressures that are not matched to their knowledge and abilities, and challenge their ability to cope (World Health Organization, 2018) while perceived behavioral control is defined as people’s perceived ability to perform a given behavior (Ajzen,

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S.S. Man et al. / Journal of Safety Research 71 (2019) 25–39 Table 2 Summary of the demographic information of participants (n = 469).

Age (years)

Gender Education level

Marital status

Work experience (years) in the construction industry

Description

Frequency

Percentage (%)

18–25 26–35 36–45 46–55 56–65 > 65 Male Female No formal education Primary school Lower secondary Higher secondary Post-secondary Unmarried Married Divorced/separated Widowed <1 1–5 6–10 11–20 21–30 >30

67 104 100 113 69 16 441 28 23 107 158 124 57 144 303 15 7 10 149 81 125 62 42

14.30 22.17 21.32 24.09 14.71 3.41 94.03 5.97 4.91 22.81 33.69 26.44 12.15 30.70 64.61 3.20 1.49 2.13 31.77 17.27 26.65 13.22 8.96

1985). By definitions, work stress and perceived behavioral control are different from RP. Also, Man et al. (2017) found that work stress, perceived behavioral control and RP of construction workers are the reasons for their risk-taking behavior. Therefore, work stress and perceived behavioral control of construction workers were selected to assess the discriminant validity of the CoWoRP Scale. Risk-taking behavior was selected for criterion-related validity analysis of the CoWoRP Scale because it was believed that the higher the level of RP of construction workers, the less risktaking behavior they engage in at work. Given that RP and risktaking behavior of construction workers were measured at the same time, the concurrent criterion-related validity of the CoWoRP Scale was appropriate in this study. The entire questionnaire comprised 57 items. Specifically, RP in the context of the construction industry was measured using the preliminary version of the CoWoRP Scale, including 36 items with

an 11-point phrase completion scale (refer to Section 2.1). For the measurement of RP related to public daily-life health and safety, a scale of six items proposed by Weber, Blais, and Betz (2002) was used. Work stress was measured with six items adapted from the job stress questionnaire of Kawada and Otsuka (2011). Perceived behavioral control was measured using three items adapted from a study on the adoption of online tax e-services (Wu & Chen, 2005). The items of work stress and perceived behavioral control were appropriately modified to fit the current research context. Moreover, a six-item measure of occupational risk-taking behaviors validated by Rundmo (1996) was used. Table 3 presents item details of RP related to public daily-life health and safety, work stress, perceived behavioral control, and risk-taking behavior. 2.2.3. Procedure A brief introduction of the research background and purposes was provided to the participants. Subsequently, informed and written consents were obtained from them before they answered the questionnaire. The participants were informed that they had the right to drop out from the survey any time and that the information collected would be processed with absolute anonymity and confidentiality to minimize potential response bias, such as social desirability bias. The respondents were instructed to read and to answer each of the 57 items of the questionnaire. Moreover, respondents were asked not to discuss with each other and to keep quiet during the questionnaire survey. 2.3. Phase II: Factor analysis Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were employed in the factor analysis of the preliminary version of the CoWoRP Scale (36 items) using Statistical Package for the Social Sciences (SPSS) 21 and Analysis of Moment Structures (AMOS) 21, respectively. EFA is a statistical technique extensively applied and broadly utilized in scale development to explore the underlying dimensions (factors) of scale items (Comrey & Lee, 2009). CFA is frequently used for the study of the latent structure of a test instrument and for the verification of the pattern of itemfactor relationships (that is, factor loadings) and the number of the underlying dimensions of the instrument (Brown & Moore, 2012).

Table 3 Item details of RP related to public daily-life health and safety, work stress, perceived behavioral control, and risk-taking behavior. Construct

Item

Content

Scale format

RP related to public dailylife health and safety (RPD-L)

RPD-L1 RPD-L2 RPD-L3 RPD-L4 RPD-L5 RPD-L6 WS1 WS2 WS3 WS4 WS5

Buying an illegal drug for your own use Engaging in unprotected sex Not wearing a seatbelt when being a passenger in the front seat Not wearing a helmet when riding a motorcycle Exposing yourself to the sun without using sunscreen Often eating high-cholesterol foods You have to do an enormous amount of work. You cannot complete all your work in the allotted time. You have to work very hard. You have to profoundly focus your attention. You do a difficult job that requires a high level of knowledge and skills. You have to constantly think about your work during working hours. I would be able to take risks at work. Taking risks at work was entirely within my control. I had the resources, knowledge, and ability to take risks at work. You always ignore safety regulations to get a job done. You always carry out work activities that are forbidden. You always perform your work duties incorrectly. You always take risks to complete your work duties. You always do not use personal protective equipment. You always break procedures to carry out jobs quickly.

5-point Likert scale, ranging from 1 = ‘‘not at all risky” to 5 = ‘‘extremely risky”.

Work stress (WS)

WS6 Perceived behavioral control (PBC) Risk-taking behavior (RTB)

PBC1 PBC2 PBC3 RTB1 RTB2 RTB3 RTB4 RTB5 RTB6

5-point Likert scale, ranging from 1 = ‘‘totally disagree” to 5 = ‘‘totally agree”.

5-point Likert scale, ranging from 1 = ‘‘totally disagree” to 5 = ‘‘totally agree”. 5-point Likert scale, ranging from 1 = ‘‘totally disagree” to 5 = ‘‘totally agree”.

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2.3.1. Result Although no consensus emerged among researchers regarding the rule-of-thumb sample size for factor analysis, in general, the more the data collected, the more accurate the analysis results. Comrey and Lee (2009) corroborated that sample sizes of 300 and 500 are regarded as good and very good, respectively. In addition, Bartlett’s Test of Sphericity (Bartlett, 1950) and Meyer-Olkin (KMO) Measure of Sampling Adequacy (Kaiser, 1970) can be used to assess the extent to which the data are suitable for factor analysis. Here, Bartlett’s Test of Sphericity (v2 = 12,279.829, p < 0.001) was significant, and the value of KMO statistics was 0.947, indicating the acceptable suitability of the data for factor analysis. After demonstrating the sufficiency of collected data for factor analysis, EFA was conducted using the maximum likelihood extraction method and direct oblimin rotation to explore the underlying dimensions of the preliminary version of the CoWoRP Scale items. As suggested by Osborne and Costello (2009) for EFA, items with a factor loading less than 0.5 were dropped out of the CoWoRP Scale. Moreover, items that load on the factors other than its designed one were removed. For example, if item 2 which was designed to measure RP – probability was found to load on RP – severity with a factor loading greater than 0.32, it was decided to remove item 2 from the scale due to a crossloading (Osborne & Costello, 2009). In addition, items with a communality value less than 0.2 were removed (Wu, Yin, Wu, & Li, 2017). Communality is the proportion of item variance that can be explained by the factor it loads on. With consideration of these three criteria, 19 items were removed, leaving a total of 17 items of the CoWoRP Scale for further analysis (Table 4). For clarity of presentation, factor loadings below 0.3 are not shown in Table 4 as done in the study of Baglin (2014). The scree test and eigenvalue (>1) recommended by Osborne and Costello (2009) were then used to decide the number of factors to be extracted. The graph of the eigenvalues in the scree test (Fig. 1) was studied, and the break point or natural bend in the data where the curve flattens out was identified. Three factors were clearly identified from the results, where two factors (i.e., probability and severity) were related to cognitive RP, whereas one factor (i.e., the combination of worry and unsafe) was related to affective RP. In addition, the eigenvalues of probability, severity, and the combination of worry and unsafe were 7.313, 1.564, and 2.282, respectively. These dimensions accounted for 58.928% of the total variance. The result of EFA is shown in Table 4.

For the verification of the pattern of item-factor relationships (factor loadings) and the number of the underlying dimensions of the instrument, the CFA was conducted using another sample of 536 construction workers with the maximum likelihood method. This sample demographic information was similar to those described in Table 2 for the original sample. As suggested by Fornell and Larcker (1981) for handling the CFA results, four items (item 1, 6, 7, and 25: Table 1) with a factor loading less than 0.7 were removed from the CoWoRP Scale, leaving 13 items, out of the 17 items obtained by the EFA. These 13 items with factor loading ranging from 0.826 to 0.988 constituted the final version of the CoWoRP Scale (Table 5). The Chi-square (v2 ) value, which is traditionally regarded as a measure to evaluate the overall model fit and to assess the magnitude of discrepancy between the sample and fitted covariances matrices, was 377.451 (df = 62) (p < 0.01). Given the sensitivity of the Chi-square value to the sample size (Bentler & Bonett, 1980), other goodness-of-fit statistics, namely, root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker-Lewis index (TLI) recommended by Kline (2015) and Hooper, Coughlan, and Mullen (2008), were employed for model evaluation. The CFA results indicated that the value of RMSEA (0.098) failed to satisfy the requirement (<0.08). The measurement model was then modified based on the result of modification indices. Particularly, a pair of error term (error 11 and error 12) were allowed to be correlated. Table 6 summarizes the values of these goodness-of-fit statistics, demonstrating acceptable model fit to data. Fig. 2. shows the three-factor measurement model of RP. 2.4. Phase III: Reliability assessment Given the sufficiency of evidence for a sound factor structure of the CoWoRP Scale, its reliability was then assessed. Reliability can be defined as the consistency of a test or measurement (Weir, 2005). Two types of reliability of the final version of the CoWoRP Scale (13 items), namely, internal consistency and test-retest were studied. 2.4.1. Internal consistency reliability Internal consistency reliability was used to describe the extent to which all the items in a scale or a test measure the same concept or construct (Tavakol & Dennick, 2011). Cronbach’s alpha was

Table 4 The result of the exploratory factor analysis. Item

Content

Factor loading RP-P

1 Working on the top of a container without using any safety measures 3 Working on a moving route of lifting 4 Engaging in electrical works (e.g., electric arc welding) in a workplace that is affected by rainy weather 5 Using electrical equipment with damaged wires 6 Not wearing safety shoes on a construction site 7 Lifting 17 kilograms of construction wastes on the ground with a stooped posture 10 Working on an unstable trestle ladder 11 Working at heights with high winds 12 Working under suspended materials 13 Using electrical equipment without insulation and proper earthing of electrical circuitry in a wet workplace 24 Improperly placing wires on the ground 25 Wearing too loose or too tight clothes to move heavy objects 26 Using a phone when working on a construction site 27 Not wearing masks when working in a dusty workplace 33 Walking through an improperly paved carpet or a mat 34 Wearing protective gloves of inappropriate size to move heavy objects 36 Not wearing a reflective vest when working in a dim workplace Eigenvalue cumulative % of explanatory variance

Note: RP-P, RP – probability; RP-WU, RP – worry and unsafe; RP-S, RP – severity.

RP-WU

Communality RP-S

0.566 0.681 0.948 0.910 0.611 0.606 0.786 0.795 0.927 0.721

07.313 40.417

0.633 0.518 0.770 0.608 0.821 0.919 0.609 02.282 51.563

01.564 58.928

0.428 0.531 0.772 0.742 0.488 0.467 0.614 0.669 0.849 0.606 0.597 0.269 0.548 0.506 0.603 0.803 0.527

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Fig. 1. Scree plot for the analysis of the number of factors to be retained.

Table 5 Item details of the final version of the CoWoRP Scale with 13 items. Factor

Scale format

Item

RP – probability

An 11-point phrase completion scale ranging from 0 (indicating ‘‘not at all likely” to 10 (indicating ‘‘extremely likely”)

If you experience the following work events or situations, how likely will you be to experience negative consequences in your perspective? RP-P1. Working on a moving route of lifting RP-P2. Engaging in electrical works (e.g., electric arc welding) in a workplace that is affected by rainy weather RP-P3. Using electrical equipment with damaged wires If you experience the following work events or situations, how severe will the potential negative consequences be in your perspective? RP-S1. Working on an unstable trestle ladder RP-S2. Working at heights with high winds RP-S3. Working under suspended materials RP-S4. Using electrical equipment without insulation and proper earthing of electrical circuitry in a wet workplace If you experience the following work events or situations, how worried will you be about the potential negative consequences? RP-WU1. Improperly placing wires on the ground RP-WU2. Using a phone when working on a construction site RP-WU3. Not wearing masks when working in a dusty workplace If you experience the following work events or situations, how unsafe will you feel regarding the potential negative consequences? RP-WU4. Walking through an improperly paved carpet or mat. RP-WU5. Wearing protective gloves of inappropriate size to move heavy objects RP-WU6. Not wearing a reflective vest when working in a dim workplace

RP – severity

RP – worry and unsafe

An 11-point phrase completion scale ranging from 0 (indicating ‘‘not at all severe” to 10 (indicating ‘‘extremely severe”)

An 11-point phrase completion scale ranging from 0 (indicating ‘‘not at all worried” to 10 (indicating ‘‘extremely worried”)

An 11-point phrase completion scale ranging from 0 (indicating ‘‘extremely safe” to 10 (indicating ‘‘extremely unsafe”)

employed, with a criterion level of 0.7, to measure the internal consistency reliability of the CoWoRP Scale (Cronbach, 1951). For the interest of completeness, internal consistency reliability related to the entire scale and each of the three factors were tested here. Cronbach’s alpha values of the CoWoRP Scale as a whole, RP – probability, RP – severity, and RP – worry and unsafe were 0.900, 0.857, 0.893, and 0.888, respectively, indicating acceptable internal consistency reliability.

Factor loading

0.951 0.988 0.976

0.938 0.964 0.975 0.973

0.926 0.826 0.923

0.878 0.883 0.872

2.4.2. Test-retest reliability Test–retest reliability was the method used to measure how constant scores of a scale remain from one occasion to another (i.e., temporal stability of a scale; DeVellis, 2016). The intra-class correlation coefficient (ICC) with two-way mixed effects and absolute agreement recommended by Koo and Li (2016) was employed to measure the test-retest reliability of the CoWoRP Scale. They suggested that ICC estimate values less than 0.5, between 0.5 and

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Table 6 Overall goodness-of-fit statistics of the confirmatory factor analysis performed. Goodness-of-fit statistics

Recommended values

Values

Results

Reference

RMSEA CFI TLI

< 0.08 > 0.90 > 0.90

0.073 0.983 0.979

Acceptable Acceptable Acceptable

Hair, Black, Babin, and Anderson (2010), Kline (2015), McDonald and Ho (2002)

Fig. 2. Three-factor measurement model of RP with standardized estimates on arrows; *: p < 0.05.

0.75, between 0.75 and 0.9, and greater than 0.9 are indicative of poor, moderate, good, and excellent test-retest reliability, respectively. All participants who had completed the questionnaire survey were invited to redo the questionnaire survey after four weeks but only twenty-one participants agreed to do so. This was possibly due to the high rate of labor mobility in the Hong Kong construction industry. Also, it’s always not easy to ask the workers to redo the seemingly boring task of completing a questionnaire. The values of ICC of the CoWoRP Scale as a whole, RP – probability, RP – severity, and RP – worry and unsafe were 0.877, 0.732, 0.896, and 0.705, respectively, showing acceptable testretest reliability. 2.5. Phase IV: Validity assessment The final phase of the CoWoRP Scale development involved testing for convergent, discriminant, and criterion-related validity of the final version of the CoWoRP Scale (13 items). Psychological constructs are unobservable; thus, an instrument’s degree of convergence with and discrimination from the measures of other constructs must be demonstrated to determine the utility of the measure for assessing the psychological construct of interest (Fiske & Campbell, 1992). Convergent validity refers to the correlation between two or more scores on scales, which are designed to assess similar constructs (Chen & Tung, 2014). Convergent validity can also be determined using the factor loadings and average variance extracted (AVE) value for every construct (Fornell & Larcker, 1981). Discriminant validity refers to the extent to which the measure is indeed novel and not simply a reflection of few other variables (Churchill, 1979). The Fornell and Larcker (1981) technique was employed to assess the discriminant validity of the CoWoRP Scale

by comparing the square roots of the AVE value of each construct, namely, work stress, perceived behavioral control, and RP (as measured by the CoWoRP Scale) with the correlations among these constructs. The three factors of the CoWoRP Scale (that is, RP – probability, RP – severity, and RP – worry and unsafe) had items with factor loadings greater than 0.70 and the values of AVE greater than 0.5, illustrating the acceptable convergent validity of the CoWoRP Scale (Fornell & Larcker, 1981; Table 7). The Fornell and Larcker (1981) technique suggested that discriminant validity is obtained if the square roots of the AVE of the three factors of the CoWoRP Scale are greater than the correlations among the constructs. All the square roots of the AVE of the three factors of the CoWoRP Scale were greater than the construct correlations, implying acceptable discriminant validity (Table 8). In addition, the correlations between the three factors of the CoWoRP Scale and RP related to public daily-life health and safety were relatively large, which ranged from 0.320 to 0.564 with statistical significance, further confirming that the CoWoRP Scale had acceptable convergent validity (DeVellis, 2016). As for the discriminant validity of the CoWoRP Scale, the correlations among the three factors of the CoWoRP Scale and work stress and among the three factors of the CoWoRP Scale and perceived behavioral control were relatively small, ranging from 0.032 to 0.288, also expressing the acceptable discriminant validity of the CoWoRP Scale (DeVellis, 2016). Criterion-related validity can provide evidence of a relationship between a measure and another measure (DeVon et al., 2007; Hinkin, 1995). The correlation between RP and the risk-taking behaviors of construction workers was assessed for the evidence of concurrent criterion-related validity (DeVon et al., 2007). The correlations among the three factors of the CoWoRP Scale and the risk-taking behavior of construction workers were statistically

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S.S. Man et al. / Journal of Safety Research 71 (2019) 25–39 Table 7 Reliability and descriptive statistics of scales. Factor

Item

Factor loading

Cronbach’s alpha

AVE

Mean

SD

Risk perception – probability (RP-P)

RP-P1 RP-P2 RP-P3 RP-S1 RP-S2 RP-S3 RP-S4 RP-WU1 RP-WU2 RP-WU3 RP-WU4 RP-WU5 RP-WU6 RPD-L1 RPD-L2 RPD-L3 RPD-L4 RPD-L5 RPD-L6 WS1* WS2* WS3 WS4 WS5 WS6 PBC1 PBC2 PBC3 RTB1 RTB2 RTB3 RTB4 RTB5 RTB6

0.706 0.918 0.845 0.780 0.825 0.907 0.786 0.757 0.724 0.719 0.751 0.883 0.727 0.688 0.690 0.804 0.652 0.525 0.663 0.481 0.465 0.692 0.786 0.670 0.658 0.767 0.698 0.824 0.816 0.866 0.827 0.851 0.790 0.833

0.857

0.685

0.893

0.682

0.888

0.581

0.828

0.456

0.792

0.495

0.805

0.585

0.930

0.690

7.539 7.840 7.817 7.552 7.785 7.974 8.049 6.851 5.667 7.115 6.461 6.456 7.230 4.141 3.819 3.763 4.115 3.166 3.454 3.463 3.017 3.618 3.716 3.580 3.264 3.200 3.345 3.200 2.499 2.301 2.243 2.271 2.173 2.290

2.408 2.501 2.379 2.280 2.190 2.099 2.081 2.427 3.013 2.521 2.596 2.560 2.489 1.003 1.196 1.063 1.033 1.139 1.088 1.089 1.143 1.108 1.075 1.123 1.160 1.224 1.177 1.189 1.282 1.181 1.131 1.152 1.187 1.239

Risk perception – severity (RP-S)

Risk perception – worry and unsafe (RP-WU)

Risk perception related to public daily-life health and safety (RPD-L)

Work stress (WS)

Perceived behavioral control (PBC)

Risk-taking behavior (RTB)

Note: Items with an asterisk star were deleted from the analysis as the factor loading was smaller than 0.5.

Table 8 Correlations among constructs. Constructs RP-P RP-S RP-WU RPD-L WS PBC RTB

RP-P 0.828 0.518*** 0.400*** 0.320*** 0.170*** 0.117*** 0.180***

RP-S 0.826 0.518*** 0.537*** 0.277*** 0.032 0.246***

RP-WU

0.762 0.564*** 0.288*** 0.130* 0.101*

RPD-L

0.675 0.366*** 0.067 0.179***

WS

PBC

RTB

0.696 0.136* 0.078

0.764 0.375***

0.831

Bolded values: square root of AVE; unbolded values: inter-construct correlations; RP-P = Risk perception – probability; RP-S = Risk perception – severity; RP-WU = Risk perception – worry and unsafe; RPD-L = Risk perception related to public daily-life health and safety; WS = Work stress; PBC; Perceived behavioral control; RTB = Risk-taking behavior; *: p < 0.05; **: p < 0.01; ***: p < 0.001

significant, ranging from 0.101 to 0.246 (Table 8). Although these correlations were not as high as we expected, the moderate concurrent criterion-related validity of the CoWoRP Scale was acquired (DeVon et al., 2007).

3. Discussions In recent years, RP has become one of the hot research topics in the context of construction safety and has evoked increasing research attention. To date, however, a shortage of a welldesigned (i.e., reliable, valid, and comprehensive) measurement for the assessment of the RP of construction workers is still observed. Appendix A shows that previous studies on risk perception quantification did not consider affective RP of construction workers and did not report validity tests such as content, convergent, discriminant, and criterion-related validity. To fill this research gap, the current study employed the four phases of scale

development, namely, item development, factor analysis, reliability assessment, and validity assessment to develop and evaluate the CoWoRP Scale, which was designed to assess not only cognitive RP but also affective RP of construction workers. The findings of this study are extremely promising. Specifically, the results in Phase I displayed the excellent content validity of the CoWoRP Scale, indicative of its items sufficiently reflecting the content domain of interest (i.e., RP). Moreover, the results in Phases II and III stressed that the CoWoRP Scale is a threedimensional and reliable instrument with acceptable internal consistency reliability and test-retest reliability. The threedimensional structure of the CoWoRP Scale was overarching and provided evidence of the probability, severity, and worry and unsafety factors of risk perception among construction workers. The internal consistency reliability and test-retest reliability of the CoWoRP Scale exhibited that its items measured what it was presumed to measure and that its score was temporally stable. In addition, the results in the final phase confirmed that the CoWoRP

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Scale has acceptable convergent, discriminant, and criterionrelated validity. Moreover, expected relationships among scores on the CoWoRP Scale and other scales, such as RP related to public daily-life health and safety, work stress, perceived behavioral control, and risk-taking behavior, were obtained. Remarkably, the correlation between RP and risk-taking behavior among construction workers was affirmed to be negatively significant (Table 8), suggesting that construction workers who hold a high level of RP tend to have less risk-taking behaviors at work. 3.1. Theoretical implications The CoWoRP Scale developed in this paper is expected to generate the following important theoretical implications. Theoretically, the CoWoRP Scale could invoke novel insights into the emerging ‘‘RP” literature in construction safety. For instance, with the CoWoRP Scale, exploring the RP of construction workers as a personrelated variable in their risk-taking behaviors could be made in the future. In accordance with occupational safety and health statistics provided by the Labour Department, 2016, 34.2% of industrial accidents and 55.6% of industrial fatalities were observed in the Hong Kong construction industry in 2016. Moreover, unsafe human behaviors were considered the cause of 80% of accidents (Fleming & Lardner, 2002). In many previous studies, RP has been confirmed to influence unsafe behaviors in a wide range of research areas, such as transportation safety (Machin & Sankey, 2008; Rhodes & Pivik, 2011), beach swimming safety (McCool, Moran, Ameratunga, & Robinson, 2008), and occupational safety (Leiter, Zanaletti, & Argentero, 2009). In the context of construction industry, the qualitative study of Man et al. (2017) asserted that risk-taking behavior is one type of unsafe behaviors and that the RP of construction workers is regarded as an important factor in their risk-taking behaviors. Consequently, these findings validated that further research attention should be given to the relationship between the RP of construction workers and their risk-taking behaviors. However, the extent to which the RP of construction workers influences their risk-taking behaviors remains unknown and should receive further research efforts in the future. The need to use a reliable and valid (i.e., good psychometric properties) measurement to assess the cognitive and affective RP of construction workers should be satisfied before conducting the abovementioned research. Previous construction safety studies related to RP (e.g., Xia et al., 2017) failed to consider affective RP in explaining behaviors of construction workers, probably because of the lack of a reliable and valid scale for measuring such construct. Thus, the CoWoRP Scale that incorporates affective RP is expected to facilitate important theoretical contributions to the related research areas. Second, the findings of this study provided evidence of the three dimensions of the RP of construction workers (i.e., probability, severity, and worry and unsafety). Rundmo (2000) confirmed that the RP of workers can be measured in terms of four aspects, where two aspects (i.e., probability and severity) relate to cognitive RP and others (i.e., worry and unsafe) relate to affective RP. However, the results of Phase II are surprisingly indicative of the three aspects of RP among construction workers. Hence, two aspects (i.e., probability and severity) relating to cognitive RP were confirmed, whereas two aspects (i.e., worry and unsafe) relating to affective RP were combined into one aspect (i.e., the combination of worry and unsafe). This finding verified that construction workers held a simple conceptualization of RP, although it was presented as a complex construct in the previous study of Rundmo (2000). In the study of Rundmo (2000), risk perception – worry was defined as the extent to which workers feel worried when thinking about experiencing an accident, while risk perception – unsafe referred to the extent to which workers feel unsafe when considering expe-

riencing an accident. As supported by the results of this study, risk perception – worry and risk perception – unsafe were found to combine into one factor called risk perception – worry and unsafe. Risk perception – worry and unsafe is defined as the extent to which construction workers worry and feel unsafe regarding the outcomes of risky scenarios. Therefore, in the course of developing the CoWoRP Scale, new insights into the structure of the RP among construction workers were acquired. According to the result of correlation analysis (Table 8), three aspects of RP among construction workers were positively correlated. In other words, affective RP was positively correlated with cognitive RP, indicating that construction workers who have a high level of affective RP are more likely to a high level of cognitive RP. This finding provided supportive evidence of the importance of affect in risk perception of people (Slovic & Peters, 2006). Third, the pioneering work of this study examined the correlation between RP and risk-taking behavior among construction workers. The results showed three types of RP were negatively correlated with risk-taking behavior among construction workers (Table 8), implying that construction workers who hold a high level of RP tend to engage in less risk-taking behaviors at work. As a result, new insights into construction worker behavior were gained, and the importance of construction worker RP in construction worker behavior and construction safety was accentuated. This work may stimulate more research efforts in investigating the underlying mechanism in the relationship between risk perception and risk-taking behavior among construction workers. Fourth, analysis of variance (ANOVA) was conducted to examine the effect of demographic variables on the CoWoRP score and the results showed that all demographic variables did not significantly influence the CoWoRP score. Due to the insignificance of the ANOVA results, it was decided not to report the details. For example, the p-value and effect size measure (i.e., g2) for the effect of the year of experience in the construction sector on the CoWoRP score were 0.112 and 0.139, respectively. The insignificant effect of demographic variables on the CoWoRP score implies that future research effort should be exerted to identify the factors that influence the RP of construction workers. 3.2. Practical implications Apart from theoretical implications, this research also generated at least three practical implications for the construction industry. Initially, managerial benefits may be obtained from the adoption of the proposed CoWoRP Scale in developing effective and comprehensive construction safety management strategies. Specifically, the CoWoRP Scale could serve as an aptitude test to identify the characteristics of construction workers most likely to perceive lower risk in risky work situations. In turn, this information could help safety management to provide additional safety training programs to those workers to enhance their RP (Leiter et al., 2009). By identifying workers who have the greatest need for safety (re)training, unnecessary training costs stemming from the provision of additional safety training for those who have a high level of risk perception can be reduced. Other than providing additional safety training programs to construction workers who hold a low level of RP, frequent regular safety inspection and supervision should be provided to them to prevent them from taking risks at work (Aksorn & Hadikusumo, 2008). During safety training, construction workers who have a low level of risk perception need to be provided with information about the potential negative consequences of the risk-taking behavior at work. The authors believe there are a mixed set of reasons for the low risk perception of workers. Nevertheless, such information provided in the training will hopefully increase their risk perception. Finally, safety management should provide information on risk and risk

S.S. Man et al. / Journal of Safety Research 71 (2019) 25–39

mitigation strategies for construction workers. Thus, construction safety management strategies with effectiveness and comprehensiveness can minimize the number of construction accidents and fatalities.

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of this study, additional future works must clearly be carried out to further validate this scale. Its limitations should also be addressed in the future. Acknowledgments

3.3. Limitations and future research Although the current study has achieved promising contributions, its limitations must be recognized. First, although the CoWoRP Scale is expected to have applicability across different countries, this study has been limited to the investigation in the Hong Kong construction industry. Thus, future research is necessary to attain further validation of the CoWoRP Scale across other countries. Second, the nature of this study was crosssectional, limited to a snapshot of the RP of construction workers at a specific point in time. Therefore, further research efforts should be made to investigate the adoption of longitudinal designs to elicit profound insights into the RP of construction workers (Menard, 2002). For illustration, longitudinal models may facilitate the investigation of the dynamics of the RP of construction workers. In the future, further research may also be conducted to study the nature and dynamics regarding the RP of construction workers’ triggers and inhibiting factors, which could be a useful basis on which effective safety interventions and managerial decision making can be made. Third, the items of the CoWoRP Scale were developed with a literature review and a group of five experienced safety and health professionals. Although another group of five experienced safety and health professionals were used to assess the content validity of the CoWoRP Scale, a larger group of experienced safety and health professionals should be used to further confirm the content validity of the scale in the future studies. Fourth, the sample size for test-retest reliability assessment in this study was only 21. There is no rule of thumb for the sample size of test-retest reliability assessment, but the number of participants used in this type test-retest reliability assessment can be 15 and 20 (Amer, Eliasson, Peny-Dahlstrand, & Hermansson, 2016; Foerde et al., 2018). In the future, a larger sample size should be used to further verify the test-retest reliability of the CoWoRP Scale. Fifth, this study did not focus on the extent to which RP – probability, RP – severity, and RP – worry and unsafe influence the risktaking behavior of construction workers. Given this reliable and valid CoWoRP Scale developed in this study, construction safety researchers are encouraged and confident to fill this research gap in the future. Finally, this study did not focus on the development of a guideline on using the CoWoRP Scale. Thus, in the future, scholars should pay attention to this research gap and provide the CoWoRP Scale score guideline for practitioners in the construction industry. 4. Conclusions This study developed and established a psychometrically sound and comprehensive instrument called the CoWoRP Scale with 13 items to assess the cognitive and affective of construction workers via the four phases of scale development, namely, item development, factor analysis, reliability assessment, and validity assessment. The outcomes of this study are expected to contribute to the emerging RP literature in the construction safety context. In addition, the three dimensions of RP among construction workers, namely, probability, severity, and worry and unsafe, were identified. Moreover, practical recommendations based on the findings of this study were derived and discussed. The theoretical and practical implications will draw the attention of practitioners and researchers to RP of workers to understand the risk-taking behavior of workers in the construction industry. Despite the useful results

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S.S. Man et al. / Journal of Safety Research 71 (2019) 25–39 Alan Hoi Shou Chan obtained his B.Sc. in Industrial Engineering from the University of Hong Kong in 1982. He was then awarded his MPhil and Ph.D. in human factors studies from the same university in 1986 and 1995, respectively. He has a wide range of research interests in work safety, work design, cognitive ergonomics, and compatibility.

Saad Alabdulkarim obtained his B.Sc. in Industrial Engineering from the King Saud University in 2011. He was then awarded his M.Sc. and Ph.D. in Industrial and Systems Engineering (human factors focus) from Virginia Tech in 2015 and 2017, respectively.

Appendix A. Summary of past published health and safety related studies on risk perception quantification (n = 18)

Topic

Risk perception scale content

Methodology for scale development

Reference

Safety climate, attitudes and risk perception in Norsk Hydro

Questions are related to the probability for a respondent as well as for an employee in general suffering an accident in the plant where the respondent work, and the measures of affective reactions includes assessment of ‘‘worry” as well as ‘‘how safe” the respondent felt when thinking ‘‘about the risks in your work”. A seven-point bipolar scale is applied. It ranges from ‘‘very probable” to ‘‘not at all probable”, ‘‘very unsafe” to ‘‘very safe”, and ‘‘very worried” to ‘‘not at all worried”. Questions are about risks related to five commonly encountered content domains, i.e., ethical, financial (further decomposed into gambling and investment), health/safety, social, and recreational to measure perceived level of risk for each question with a seven-point Likert scale ranging from (1) not at all risky to (7) extremely risky. Questions include ‘‘what do you think your chances of getting breast cancer are on a scale of 0–100 (0 meaning no chance and 100 meaning definitely)”, ‘‘how certain they were about their answer to the previous question, on a scale from 1 (not at all) to 4 (very)” and ‘‘what do you think the chances are that you will have breast cancer someday? (with response categories from 0 to 100%)”. Questions are related to the chances are of getting a ticket if not wearing seat belt to measure perceived likelihood for each question with a five-point Likert scale (Never = 1, Seldom = 2, Sometimes = 3, Nearly always = 4, and Always = 5). Questions include ‘‘whether they believed work affected their health in a number of ways (for example, stress, hearing, stomach ache, muscular pains) with responses of ‘‘yes”=1, ‘‘no”=0, or ‘‘don’t know”. Questions are about the risk of transmitting HIV to an HIV–negative sex partner to measure the perceived level of risk for each question with a five-point Likert scale ranging from (1) no risk to (5) very great risk.

Cronbach’s alpha, validity assessment

Rundmo (2000)

Cronbach’s alpha, exploratory factor analysis, confirmatory factor analysis, factor loading, test–retest reliability, validity test with correlation analysis.

Weber et al. (2002)

No reliability assessment, no validity assessment

Bowen, Alfano, McGregor, and Andersen (2004)

No reliability assessment, no validity assessment

Chaudhary, Solomon, and Cosgrove (2004)

No reliability assessment, no validity assessment

Daniels (2004)

No reliability assessment, no validity assessment

Belcher et al. (2005)

A domain-specific risk-attitude scale: Measuring risk perceptions and risk behaviors

The relationship between perceived risk, affect, and health behaviors

The relationship between perceived risk of being ticketed and selfreported seat belt use

Perceived risk from occupational stress: a survey of 15 European countries

Condom use and perceived risk of HIV transmission among sexually active HIV-positive men who have sex with men

(continued on next page)

38

S.S. Man et al. / Journal of Safety Research 71 (2019) 25–39

Appendix (continued)

Topic

Risk perception scale content

Methodology for scale development

Reference

How accurately does the public perceive differences in transport risks?: An exploratory analysis of scales representing perceived risk

Questions include ‘‘How safe do you think it is to travel by means of (airplane, train, ship, bus, car, motorcycle, bicycle or walking)?” with the options of response (a) Very safe; (b)Safe; (c) A little unsafe; (d) Very unsafe, or are you; and (e) Unable to answer (do not know). Questions include different road environments and situations (e.g. rossing a local street), on a 4-point scale ranging from 1 (not at all dangerous) to 4 (very dangerous). Questions include ‘‘how likely they thought they were to develop one of four diseases (i.e. breast cancer, colon cancer, prostate cancer, heart disease, and diabetes) in their lifetimes on a scale of 0% (not at all likely) to 100% (extremely likely) scale”. No question contents are available but risk perception is measured with the worker’s perception about his or her own probability of suffering a work-related accident or illness, including occupational illness and several degrees of injury severity and through several classes of injuries and illness on a 6-point Likert-type scale, where 0 expresses the minimum level and 5 the maximum. Questions are about risks related to diabetes to measure three aspects of risk perception: perceived likelihood; anticipated feelings of risk; and anticipated worry for each question with seven-point Likert scale ranging from ‘‘not at all/ strongly disagree” (0) to ‘‘almost certain/ strongly agree” (6). Questions are related to road traffic risk to measure the perceived probability and severity of personal injury due to different types of accidents (e.g. meeting accidents, collision with animals, car driving off the road, etc.) and roles in traffic (e.g. as a pedestrian, as a driver of a motor vehicle, etc.) on a five-point Likert scale ranging from 1 (no probability/ minimal) to 5 (very high probability/ very severe/fatal). Questions are related to twelve risky driving behaviors to measure risk perception in terms of how risky it was to engage in each behavior on a 5-point scale from ‘‘Not risky at all” to ‘‘Extremely risky.” Questions are related to the probability that each accident would happen and the expected severity of

No reliability assessment, no validity assessment

Elvik and Bjørnskau (2005)

No reliability assessment, no validity assessment

Lam (2005)

No reliability assessment, no validity assessment

DiLorenzo et al. (2006)

Cronbach’s alpha, no validity assessment

Meliá, Mearns, Silva, and Lima (2008)

Cronbach’s alpha, no validity assessment

Cameron, Sherman, Marteau, and Brown (2009)

Cronbach’s alpha, no validity assessment

Nordfjærn, Jørgensen, and Rundmo (2011)

Cronbach’s alpha, no validity assessment

Rhodes and Pivik (2011)

No reliability test, no validity assessment

Perlman et al. (2014)

Parental risk perceptions of childhood pedestrian road safety: A cross cultural comparison

A Model of Disease-Specific Worry in Heritable Disease: The Influence of Family History, Perceived Risk and Worry About Other Illnesses

Safety climate responses and the perceived risk of accidents in the construction industrya

Impact of Genetic Risk Information and Type of Disease on Perceived Risk, Anticipated Affect, and Expected Consequences of Genetic Tests

A cross-cultural comparison of road traffic risk perceptions, attitudes toward traffic safety and driver behaviour

Age and gender differences in risky driving: The roles of positive affect and risk perception

Hazard recognition and risk perception in constructiona

39

S.S. Man et al. / Journal of Safety Research 71 (2019) 25–39 Appendix (continued)

Topic

Risk perception of construction equipment operators on construction sites of Turkeya Safety climate, perceived risk, and involvement in safety management

Do we see how they perceive risk? An integrated analysis of risk perception and its effect on workplace safety behaviora

Effect of distraction on hazard recognition and safety risk perceptiona

Risk perception scale content the consequences if the accident occurred in hazard and accident scenarios. Questions are related to the probability and severity assessment of accident scenarios. Questions are related to safety risks (fall or slip of even foot, radiological contamination, hearing impairment, irradiation, fall from height, fire, explosion, exposure to carcinogens, etc.) to measure the perceived probability and the perceived seriousness for each of these risks, on a 6-point Likert-type scale ranging from 0 (not applicable) and 1 (not very probable/serious) to 5 (very probable/serious). Questions are related to safety risk (falling from height, electrocution, hit by falling materials, collapse of earthwork or scaffolds, use of heavy machines, lifting of weights, toxicity and suffocation, use of motors, fire and explosions, overturning of scaffolds or tower cranes, and falling or slipping of even foot) to measure direct perceptions of the riskiness of these risks on a 5-point Likert-type scale ranging from 1 (extremely low) to 5 (extremely high). Also, the probability and severity of these similar risks also measured on a 5point scale (1 = extremely low and 5 = extremely high). Questions include risky scenarios to assess the likely frequency (e.g., number of injuries per worker-hour) and severity of adverse outcomes (e.g., treatment medical cost).

Note: aThe study is related to construction safety.

Methodology for scale development

Reference

No reliability test, no validity assessment

Gürcanlı et al. (2015)

Cronbach’s alpha, no validity assessment

Kouabenan et al. (2015)

Cronbach’s alpha, confirmatory factor analysis, no validity assessment

Xia et al. (2017)

No reliability test, no validity assessment

Namian, Albert, and Feng (2018)