Examining the Potential of Safety Knowledge as Extension Construct for Theory of Planned Behaviour: Explaining Safety Practices of Young Adults at Engineering Laboratories and Workshops

Procedia - Social and Behavioral Sciences 116 ( 2014 ) 1513 – 1518

1877-0428 © 2013 The Authors. Published by Elsevier Ltd. Open access underCC BY-NC-ND license.

Selection and/or peer-review under responsibility of Academic World Education and Research Center. doi: 10.1016/j.sbspro.2014.01.426

ScienceDirect

5

World Conference on Educational Sciences - WCES 2013

Examining The Potential Of Safety Knowledge As Extension Construct

For Theory Of Planned Behaviour

: Explaining Safety

Practices Of Young Adults At Engineering Laboratories And

Workshops

Kean Eng Koo

*, M.D. Ahmad Nurulazam

, M.Z. Siti

Rohaida

,Tang Ghee Teo,

Zulhisyam Salleh

a_{University Sains Malaysia,School Of Educational Studies Penang,11800,Malaysia} b _{University Sains Malaysia, School of Management ,Penang,11800,Malaysia} c _{Politeknik Sultan Abdul Halim Mu’adzam Shah, Bandar Darulaman,06000,Malaysia}

Abstract

This study examined engineering students’ self reported intention and behaviour in practising safety at workshops and laboratories by using the Theory of Planned Behaviour (TPB) with extension of Safety Knowledge as research framework. Eighty eight (n=88) participants from three engineering departments of a completed a survey questionnaire measuring their responses to five constructs of the framework. The multiple regressions results show that subjective norms were the most significant predictors of behavioural intention towards practising safety followed by perceived behavioural control and safety attitude. The second block of multiple regressions found that safety behaviour can be significantly explained by using the constructs of safety knowledge and behavioural intention. Overall, this study has shown that three explanatory variables in the TPB can explain behavioural intention of practising safety with 52 % of variance and safety knowledge as an extension construct of the TPB model with behavioural intention can explain the young adults’ safety behaviour in the laboratories and workshops with the variance of 40%.

1. Introduction

Issues focusing on occupational accident among young adults caused by lack of safety knowledge and unavailability of proper safety training are the reminder that the accidents rates among them are increasing. Although international meta analyses findings from Salminen (2004) stated occupational accidents among young workers are non fatal but there is no confirmation that fatal occupational accident would not happen among young workers. As in Malaysia , the majority of occupational fatal accidents reported comes from the young worker age group (Social Security Organisation, 2008, 2010) and most of major contributor of young adults occupational

* Corresponding Kean Eng Koo. Tel.: +0-012-514-3402 E-mail address: [email protected]

Keywords: Theory of Planned Behaviour, safety knowledge, safety behaviour, engineering laboratories, young adults;

© 2013 The Authors. Published by Elsevier Ltd. Open access underCC BY-NC-ND license.

fatalities and accidents are from manufacturing and civil engineering sectors which is engineering based occupation (Social Security Organisation, 2008, 2010) . Indeed, international organisations have taken initiatives to implemented safety programmes have take off to increase safety awareness and practices among young adults (EU-OSHA, 2003; Schulte, Stephenson, Okun, Palassis, & Biddle, 2005; UNESCO-UNEVOC, 2004). Unfortunately, these initiatives implemented still not widely known and it engaged resistances from tertiary institutions in implementing such programme (Copsey, 2011; Debruyne et al., 2010). Thus, this issue continues to be significant for occupational, safety and health problem among young workers in current century.

Most of the safety training is only introduced at the workers’ first day of work and employers expect the workers to absorb all safety information briefed. Behaviour changes theories and models states behaviour changes needed time to adapt and adopt the safety practice trained (Bandura, 2001; Geller, 2001b; Heinrich, Petersen, Roos, & Hazlett, 1980). Most researchers suggested safety practices and safety knowledge should be exposed as early as possible for developing safety culture as their norm (Copsey, 2011; O'Callaghan & Nausbaum, 2006; L. Quine, Rutter, & Arnold, 1998) or from unconsciously unsafe behaviour into unconsciously safe behaviour (Geller, 2001a, 2001b). The concept of exposing safety at education level compared the beginning of working environment would lead to a better safety practices among young workers (EU-OSHA, 2010; Schulte et al., 2005). Langerman (2009) indicated educational or academic laboratories are unsafe venue for study or work after reviewed most of 98 academic laboratories accident reports and related published articles. In the similar issue, James Kaufman, President of Laboratory Safety Institution (LSI), had stated academic laboratory has 10 to 50 more frequently chances of being involved in accident compared to industrial laboratories and 100 to 1000 greater times compared to Dow or DuPont (Benderly, 2009; Schulz, 2005). Unfortunately, in terms of engineering base education, not much engineering laboratories has conducted safety researches except for chemical engineering.

There are still not concrete evidents explaining why especially young adults tend to engage in risking their safety practices in the academic laboratories. Researchers hypotheses that young adults may choose to ignore hazardous condition and situation in the academic laboratory may be due to lack of safety knowledge and safety training (Breslin, Polzer, MacEachen, Morrongiello, & Shannon, 2007; Hill Jr & Nelson, 2005; Schulte et al., 2005), safety beliefs (Blair, Seo, Torabi, & Kaldahl, 2004; Crowe, 1995), effects of peers & supervisors, self efficacy and personal controllability (Benderly, 2009; Geller, 1994, 2001b; Hill Jr & Nelson, 2005; Langerman, 2009; Montano, Kasprzyk, Glanz, Rimer, & Viswanath, 2008; Moyano Díaz, 2002; O'Callaghan & Nausbaum, 2006). The drawback of gathering these information are lack of researches regarding to engineering academic laboratory and lack of reliable and valid instrument measuring these factors (Berghaus, 2010; Byrd-Bredbenner et al., 2007). Based on the elements of the hypothesised, Theory of Planned Behaviour (TpB) is identified as the most suitable theory because TpB consists of almost every elements mentioned in the hypotheses. A theoretical framework was developed and uses safety knowledge construct as an extension of TpB. Based on literature reviews, safety knowledge scale is suitable to be paralleled with behavioural intention and perceived behavioural control as predictors for the young adults’ safety practice behaviour in the academic laboratory.

2.0 Design and Procedures

Based on the number of occupational accident among young adults and the proneness of accidents in academic laboratories, the current study sought out to examine the safety practices behaviours of the engineering students before these students are send out for their real industrial attachment. Purposive sampling is used to identify classes to ensure a well represented of two main electrical courses in the electrical engineering department and not to create much disturbance in their laboratory activities. Second year electrical engineering diploma students were chosen to determine their safety practices behaviour before they will be attached to the industries for the duration of 5 months. 120 sets of questionnaires were given out and only 88 sets or 73.3% returned. The ratios of valid cases to independent variables is 29.3 : 1 satisfied the preferred requirement sample size ratios of 15:1 for applying the multiple regression analysis (Field, 2009).

2.1 Development of the questionnaire

The development of the items for theory of planned behaviour were based on the guideline manuals written by Francis et al. (2004). Elicitation survey was conducted on a group of engineering students (n=30) to ensure that the items developed will represent the population perceptions towards to the theoretical constructs. The results of the

elicitation survey were coded and sorted into themes. The most frequent or popular themes will be used as represented items. Direct measurement for attitude involves the use of bipolar adjectives for evaluative belief and the semantic differential scale were use for the measurement. The bipolar adjectives items are adapted from (Ajzen, 2001; Francis et al., 2004; Johnson & Hall, 2005; Lajunen & Räsänen, 2004; L Quine, Rutter, & Arnold, 2001). As for subjective norms, items were derived from the elicitation survey where five most percept important person or group were identified and chosen which are instructor/lecturer, classmate, close friends, laboratory supervisor and administrator. Perceived behavioural control measurement consists of 6 self-efficacy subscale items and personal controllability subscale of 5 items. Based on Ajzen (2001) recommendation, three basic items are used to determine intention of a person and the stems or the items statement starts as” I intend...”, “ I want...” and “ I plan...”(Francis et al., 2004; Johnson & Hall, 2005; Lajunen & Räsänen, 2004). As for the extension construct for the theoretical framework, the safety knowledge items are adapted from a research concerning safety climate related to chemical industry (Vinodkumar & Bhasi, 2009) which is found to have the similar factors needed.

Forty four (n=44) electrical engineering students whom were not related to the conducted experiment sample, were randomly chosen for the pilot testing. The pilot testing was conducted to determine the reliability of the items towards the constructs and feedback on the understanding of the statements. The reliability of the pilot tested items are referred to Cronbach Alpha α and used for the each constructs where they are found to be acceptable level between 0.6 to 0.9 (Nunnally, 1978). Two experience lecturers with OSH management background conducted the validation of the items representing the constructs of the framework. The survey assessed the demographic variable including age, class year, department attached to and location of their hometown. Before answering questions related to their safety practices, questions related to their experiences of learning safety training or education. All the items uses seven (7) semantic differential scale to capture the participants expression effectively (Gay, Mills, & Airasian, 2009). The representation of lower numbers shows the disagreement (1) and the higher numbers (7) show a greater agreement on their attitudes.

3 Results

3.1 Description of the participants

Final sample was comprised of eighty eight (n=88) second year electrical engineering Diploma students of one of Malaysia’s Polytechnic situated at the Northern Region of Peninsular Malaysia in which the average age was 20.4 (SD =0.97) years old. Participants are between 17 to 25 years old to fit the study’s criteria settings for young adults. The sample was represented by 60 male (68.2%) and 28 female (31.8%). 68 or 77.3% of the participants has work experience compared to 20 (23.7%) participants have no working experience. 51.1% (45 individuals) of the participants has not received any safety education of training compared to 43 individuals have received an in-house training conducted by their previous employers or attended a Green Card safety programme.

Table 3.1 Summary of Descriptive and Correlation all variables

Measure ( Scale) Mean SD Α 1 2 3 4 5 6

1) Attitude Towards Safety Practices 2) Subjective Norms 5.27 5.88 1.37 0.83 0.80 0.86 _ 0.34** _ 0.28** 0.34** 0.42*** 0.60*** 0.14 0.28** 0.19* 0.33**. 3) Perceived Behavioral Control

4) Intention of Safety Practices 5) Safety Knowledge 6) Safety Practices Behaviours

4.93 6.24 5.90 6.06 0.77 0.78 0.96 0.72 0.71 0.82 0.88 0.85 _ 0.53*** _ 0.27** 0.46*** _ 0.39** 0.54*** 0.52*** _ Note. *p < .05, ** p < .01, ***p < .001.

3.2 Description of the measurements

The measurement of attitudes, subjective norms, perceived behavioral controls, and behavioral intentions indicated young adults engineering students had extremely high intentions to practice safety in their laboratories (M= 6.27 ± 0.77). They also conceived fairly high positive attitudes (M = 5.36 ± 1.25), placed emphasis on their subjective norms (M = 5.92 ± 0.83), and perceived a averagely high amount of control (M = 5.22 ± 2.10) over their safety practices in the academic laboratories. For items related to behavioral intentions, respondents generally rated their intentions as extremely high and felt they do have a reasonably high safety knowledge (M=5.90 ± 0.96) to

create their extremely good safety practice behaviour (M = 6.06 ± 0.72) in the laboratory as shown in Table 3.1. All measured elements are significantly correlated p < 0.05 except for the correlation between attitude and safety knowledge (r (44) = 0.14, p= n.s) as shown in Table 3.1. Behavioural intention is positively significant correlated to attitude, subjective norms and perceived behavioural control. As for safety practice behaviour, safety knowledge, perceived behaviour control and behavioural intention are all significant and positively correlated.

3.3 Multiple regression results

Two stage multiple regression analysis was used to analyses the relationship of Theory of Planned Behaviours constructs (Francis et al., 2004). The first stage of multiple regression was used to explore the relationship between behavioral intention and the antecedents of behavioral intention: attitude, subjective norm and perceived behavioral control. The results of the first stage regression indicated the three predictors explained 52% of the variance of young adult students’ intention to practice safety in the laboratory (R2=.52, F(3,88)= 29.51, p<.0.001). Subjective norms was found to be the most significant predictor for the behavioural intentions tendencies (β = .43, p<.001), followed by attitude (β = .33, p<.001), and perceived behavioural control is identified as the least significant predictor (β = .20, p<0.01).

Table 3.2 Multiple Regression Stage 1and Stage 2 ( N=88)

Predictors R R2 _{SE F B SE B Beta t} Stage 1 Behavioural Intention Attitude Towards Safety Practices 0.72 0.52 0.55 29.51*** 0.33 0.08 0.33*** 4.00*** Subjective Norms 0.36 0.07 0.43*** 5.16*** Perceived Behavioral Control 0.11 0.05 0.20** 2.44** Stage 2 Safety Practices 0.63 0.40 0.57 18.61*** Perceived Behavioral Control 0.13 0.09 0.13 1.33 Behavioural Intention of Safety Practices 0.29 0.10 0.31** 2.89** Safety Knowledge 0.26 0.07 0.34** 3.59**

Note. B = unstandardized regression coefficient; Beta = standardized regression coefficient *p < .05, ** p < .01, ***p < .001

The second stage of Multiple Regression was used to determine the relationship among the safety knowledge, behavioural intention, and perceived behavioural control toward the outcome of the safety practices behaviour in the academic laboratory. Table 3.2 contains the results of safety practices behaviour regressed on the three predictors in the theoretical framework, which show that at least two of the direct determinants influenced safety practices of the young adults, F(3,84) = 18.61, p < 0.001. In response to relationship, the analysis revealed that two direct determinants – safety knowledge, t(84) = 3.446, p < 0.01 and behavioural intention, t(84) = 2.89, p < 0.01 are statistically significant predictors for creating positive safety practices behaviour while perceived behavioral control, t(84) = 2.386, p < 0.05, was not statistically significant predictor of young adults safety practice in the laboratory. The second stage predictors accounted for 40 percent of the variance in young adult student’s safety practices behaviour.

.

4.0 Discussion and Conclusion

The aim of the this paper is to examine the main predictors underlying young adults students’ behaviour and behavioural intention on practicing safety in the engineering laboratory. Using TpB the research model, the results of this study has shown that subjective norm, attitude towards safety practices and perceived behavioural control have a significant effect on behavioural intention to practice safety. As for second stage multiple regression analysis results for TpB with knowledge as extension, level of safety knowledge and behavioural intention have significant effect towards safety practices in engineering laboratory while perceived behavioural control has no significant effect. Based on the result of two stage multiple regression, three independent variables used were able to explain 52

percent of the variance in young adult students’ intention of practicing safety while 40 percent of the variance of the students’ safety behaviour in the academic laboratory is explained by referring to second stage variables.

This result suggests that TPB is moderately efficient as a model to predict the behavioural intention to practice safety among electrical engineering students in Polytechnic. It is possible that instructors, supervisors and peers of the students play an important role to motivate and guide the young students to understand the important of practicing safety in laboratory. This findings support the current research for the use of ear protection for coal miners (Quick et al., 2008). Results from the delayed post test for the miners has found that miners’ attitude and perceived behavioural control had increase while subjective norms decrease after they adapted the use of ear protection. Other than subjective norms, positive attitude towards safety practise and better perceived behavioural control would increase the students’ behavioural intention as shown in other safety practice researches (Lajunen & Räsänen, 2004; Mullan & Wong, 2009; O'Callaghan & Nausbaum, 2006; Rosenbloom, Haviv, Peleg, & Nemrodov, 2008; Şimşekoğlu & Lajunen, 2008; Weiss, Okun, & Quay, 2004). In the second stage results, perceived behavioural control (PCB) is not significantly as hypothesised in TpB for safety practices in the laboratory compared to significant varabes of safety knowledge and behavioural intention. It was possible that PBC was not enough to motivate the young engineering students to behave safely in laboratory as their knowledge towards their own control belief is limited (Ajzen, 1991) as compared their intention and safety knowledge. Overall, the results of the TpB have shown, TpB with the used of safety knowledge has increased the capability of predicting and evaluate young adult students’ intention and behaviour.

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