International Journal of Business Management (IJBM) Volume 1 Issue 2 2016

46

The Effect of Safety Training and Workers Involvement on

Healthcare Workers Safety Behavior: The Moderating Role

of Consideration of Future Safety Consequences

Munir Shehu Mashia, Chandrakantan Subramaniam

a*, Johanim Johari

a

a School of Business Management, Universiti Utara Malaysia, Malaysia

Keyword ABSTRACT

Safety training Workers

involvement

Consideration of future safety

consequences

Safety compliance

Safety

participation

Nurses

This paper proposes that consideration of future safety consequences (CFSC) would moderate the relationships

between safety training and workers involvement on

healthcare workers (HCWs) safety behaviors (safety compliance and safety participation). Survey data was

obtained among 229 nurses from Abuja secondary health

facilities, Nigeria. SmartPLS 3.0 was applied to test the hypotheses that comprised both the direct effect of safety

training and workers involvement on safety participation and

safety compliance and moderating role of CFSC on these

relationships and consequently bootstrapping was conducted to investigate the standard error of the estimate and t-values.

The findings showed that safety training positively relates to

safety compliance and safety participation and workers involvement positively relates to safety compliance and

participation. Furthermore, CFSC moderates the

relationships between workers involvement and safety compliance. The research provides empirical evidence on the

significance of CFSC as moderator. This contributes to the

utility of Social Exchange Theory (SET) and Construal

Level Theory (CLT). Furthermore, in order to achieve an optimally safe hospital environment, hospital management

should provide employees with safety training and involve

them in the safety activities and consider individual CFSC when making decisions on how to improve hospital safety.

*Corresponding Author. Email address: munirshehu@ymail.com

1. INTRODUCTION

Organizational accidents and injuries cause huge amount of employee’s lives

and property damages every year (Zhou & Jiang, 2015). The hidden costs may

range from four to five times the direct costs (Heinrich et al., 1980). Work-related

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injuries and accidents are the major concern for nurses in various hospitals, given

the risky nature of hospitals environment (Nixon et al., 2015). Nurses frequently

encountered with daily hazards which includes: physical, biological, and chemical

hazards (Nixon et al., 2015). Physical hazards range from environmental conditions

that may resulted to falls, cuts or electrical shocks. Biological hazards on the other

hand, range from exposure to blood-borne pathogens such as HIV/AIDS, bacteria,

hepatitis, and tuberculosis among others as a result of injecting patients, drawing, or

suturing of blood from the patients (Perry, Parker & Jagger, 2003). Chemical

hazards includes nurse’s contact with hazardous agents ranging from carcinogens,

corrosives and toxic (Ford & Wiggins, 2012). According to American Nurses

Association (2011), in the year 2011 alone, 40% of hospitals nurses reported

occupational injuries. In financial term, annual back injuries alone has been

projected to cost 16 billion dollars in medical treatment, worker’s compensation

benefits, employee turnover costs due to injuries (White, 2010). Nigeria is not

immune to these issues (Akinwale & Olusanya, 2015; Aluko et al., 2016; Mashi,

2014). For example, a report from the Federal Capital Territory Administration

(FCTA) reported over 100 HCWs recently suffered from needle stick injuries,

Hepatitis B and HIV/AIDS due to exposure to healthcare waste (Adejoro, 2014). As

Nigeria is aspiring to achieve its Vision 20:2020, the Vision reflects the country to

be among the world leading economy in the year 2020 (National Planning

Commission, 2010), occupational injuries and diseases that may impair productive

citizens deserves special attention.

Due to the high cost of injuries highlighted above, occupational safety

researchers and practitioners have identified the importance of safety training, —

which involves the acquisition of knowledge and skills that improve employee safe

behavior in the hospitals (Vredenburgh, 2002). This construct is regarded as an

important leading indicator of safety (e.g., Beus, McCord & Zohar, 2016; Christian,

Bradley, Wallace & Burke, 2009; McGonagle et al., 2016; Shea et al., 2016;

Sinelnikov, Inouye & Kerper, 2015; Zohar, 2010), and increase employee positive

safety behaviors (Cooper & Phillips, 2004; Neal & Griffin, 2004).

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Another important leading safety indicator is workers’ involvement in to safety

(Beus et al., 2016; Christian et al., 2009), —which involves the behavior-based

technique which includes employees in an upward information flow and safety

decision process (Vredenburgh, 2002). In safety management literature, there is a

call to incorporate other variables to moderate organizational factors with employee

safety behavior (Christian et al., 2009; Foster & Nichols 2015; Mickey et al., 2015;

Zohar, 2010) due to the inconsistency in the findings (Ismail, Asumeng & Nyarko,

2015; Vinodkumar & Bhasi, 2010). This inconclusiveness in safety literature

concerning these relationships calls for more research to examine possible

moderators to explain these relationships (Baron & Kenny, 1986).

Therefore, to identify possible constructs that can moderate these relationships

is significance to practitioners to use to reduce hospital injuries. This paper

addresses this research gap by investigating an important personality variable

potentially vital that may elicit the relationship between safety training, workers

involvement and healthcare workers safety behavior— consideration of future

safety consequences (CFSC)—which Probst, Graso, Estrada and Gree (2013) define

as the “degree to which employees consider the future versus immediate

consequences of their safety-related behaviors” (p. 125). Specifically, in this paper

we investigate the moderating effects of CFSC on relationships between safety

training, workers involvement and healthcare workers safety behavior (safety

compliance and safety participation) among nurses in Abuja secondary health

facilities in Nigeria.

We argued in this paper that CFSC will moderate these relationships because

of the following reasons: firstly, the extent literature confirmed that consideration of

future consequences (CFC) has an influence on the workers behavior of violating

the organizational rules and procedures (Takemura & Komatsu, 2013). Secondly,

recent empirical study has presented that individual high in CFC reported higher

intentions and sustain volunteerism (helping) others in the organization (Maki,

Dwyer & Snyder, 2016). Therefore, we argued that by integrating these constructs

will provide additional evidence to practitioners on how to improve safety

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compliance and participation in the organization. Such that, the relationships

between safety training, workers involvement and healthcare workers safety

behavior is expected to be stronger for the healthcare workers high in CFSC than

for those employees who are low in CFSC. In doing so, we advance the general

understanding in safety literature and contributes to safety management research,

and we offer additional information on the functioning of CFSC as an important

variable for hospital managements to use to improve healthcare worker safety.

Hence, the objectives of this study therefore are twofold: to examine the influence

of safety training and workers involvement on healthcare workers safety behavior

and to assess the moderating role of CFSC on the relationships.

2. LITERATURE REVIEW

2.1 SAFETY PERFORMANCE

In extent literature, due to the dearth of measures to assess the effectiveness of

organizational safety programs (Glendon & Litherland, 2001), no agreement is

reached on the actual safety performance components (Fernández-Muñiz et al.,

2007). Historically, to assess safety performance, studies focused on the direct

safety performance outcomes such as employees compensation cost, injuries

frequency among others (Moore & Viscusi, 1989). Nevertheless, these measures

were recognized as a poor measures of safety (Glendon & Mckenna, 1995) because

they were inadequately sensitive, retrospective and in some cases risk exposure is

ignored. These outcomes are occasional and thus, forms a skewed distribution

(Christian et al., 2009). Additionally, the high rates of under-reporting among the

industrial players in Nigeria (Tandberg et al., 1991) has resulted in suggesting that

safety performance outcomes recorded by the hospitals are too unreliable to

understand hospital safety (Cooper, 2000).

Due to the inadequacy of injuries and accident data highlighted above, many

researchers used safety behavior as the dependent variable in an effort to understand

safety performance (Barbaranelli, Petitta & Probst, 2015). Safety behavior “refers to

the employee rational reactions to dangerous external stimuli which conform to

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safety procedures to achieve the desired security objectives” (Zhang, Li & Zuo,

2015, p. 984). In other words, it is defined as “the safety-related actions or

behaviors that workers exhibit in almost all types of work to promote their safety

and that of others” (Burke & Signal, 2010, p. 3). Beus, McCord and Zohar (2016)

defined safety performance behavior “as any workplace behaviors that affect the

likelihood of physical harm to persons” (p. 3).

Employee safety compliance and participation are the main components of

safety performance behavior used in Griffin and Neal (2000) model that described

the actual behaviors that workers exhibit in the workplace (Griffin & Neal, 2000).

Safety compliance is defined as “generally mandated” behaviors (Neal, Griffin &

Hart, 2000, p. 101) which they drawn from the two main components of general job

performance from the work of Borman and Motowidlo (1993)—task performance

and contextual performance—safety compliance was used as task performance and

therefore refers to the core activities that workers carry out to preserve safety at

work. These behaviors includes following standard work procedures or wearing

personal protective equipment (Neal & Griffin, 2006).

Workers safety participation, on the other hand is defined as behaviors

“frequently voluntary” (Neal, Griffin & Hart, 2000, p. 101). In other words, are

behavior “that may not directly contribute to workplace safety, but that do help to

develop an environment that supports safety” (Griffin & Neal, 2000, p. 349) and

can be associated to safety improvement. These safety behaviors includes

voluntarily participating in safety activities, attending safety meetings, or helping

colleagues with safety-related matters (Neal & Griffin, 2006).

2.2 SAFETY TRAINING

Various antecedents were empirically tested in an effort to understand safety

performance across various work setting. For instance, Hayes, Perander, Smecko,

and Trask (1998) and Lee and Dalal (2016) explored how safety climate and culture

were important in predicting workers safety performance in the organizations.

Additionally, in their model, Griffin & Neal (2000) regarded safety knowledge and

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safety motivation as proximal factors that have a positive relationship with workers

safety behavior. Safety leadership was also found to have a positive relationship

with workers safety behavior (Smith, Eldridge, & DeJoy, 2016). Other study used

individual characteristics such as personality and age differences (e.g., Siu, Phillips

& Leung, 2003), level of education (Gyekye & Salminen, 2009) among others.

Training is “refers to instruction and practice for acquiring skills and

knowledge of rules, concepts, or attitudes necessary to function effectively in

specified task situations” (Cohen, Colligan, Sinclair, Newman & Schuler, 1998, p.

11). Safety training is an important risk prevention and control strategies to

guarantee every employee is safe in a good workplace conditions (Cohen, 1998).

Safety training is defined as “instruction in hazard recognition and control

measures, learning safe work practices and proper use of personal protective

equipment, and acquiring knowledge of emergency procedures and preventive

actions” (Cohen, 1998, p. 11). Safety training has been recognized as an important

organizational characteristic distinguishing organization with successful safety

program (Zohar, 1980), and is an effective means for employees to enhance their

skills and knowledge of safety in the organizations (Shea et al., 2016).

Literature in occupational safety supports the view that safety training is a key

factor in maintaining and changing workers attitude toward safety (Ali et al., 2009;

Boughaba, Hassane & Roukia, 2014; Donald & Cantre, 1994; Keffane, 2014;

Mearns, Whitaker & Flin, 2003; Vinodkumar & Bhasi, 2010; Zohar, 1980).

Organizations can improve workers safety behavior via keeping them aware of

health and safety practices through seminars, workshops, training on the job among

others (Mearns, Hope, Ford & Tetrick, 2010). Study conducted in the US among the

representatives of 57 projects summited that higher safety performance is attained

with safety training (Hinze, Hallowell & Baud, 2013). Similar studies also found

that companies can transfer safety knowledge through workers orientation, toolbox

talks, and training sessions among others (Hallowell, 2012; Lu & Yang 2011;

Vredenburgh, 2002). In addition, meta-analytic findings show that perceptions of

safety training positively related to safety compliance and participation (Christian et

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al., 2009). Meta-analysis studies also reported strong empirical evidence of the

effectiveness of safety training on employees’ safety behaviors (Ricci, Chiesi, Bisio,

Panari, & Pelosi, 2016; Robson et al., 2012). Taken together, there are clear

evidence in the literature that workers perception of safety training is significantly

related to workers safety behaviors. Based on the above submission, empirical

evidence suggests that safety training is important in understanding worker’s safety

compliance and participation. Therefore, we hypothesized that:

Hypothesis 1a: Safety training is positively related to safety compliance.

Hypothesis 2a: Safety training is positively related to safety participation.

2.3 WORKERS INVOLVEMENT IN TO SAFETY

Various antecedents were empirically tested in an effort to understand safety

performance across various work setting. For instance, Hayes, Perander, Smecko,

and Trask (1998) and Lee and Dalal (2016) explored how safety climate and culture

were important in predicting workers safety performance in the organizations.

Additionally, in their model, Griffin & Neal (2000) regarded safety knowledge and

safety motivation as proximal factors that have a positive relationship with workers

safety behavior. Safety leadership was also found to have a positive relationship

with workers safety behavior (Smith, Eldridge, & DeJoy, 2016). Other study used

individual characteristics such as personality and age differences (e.g., Siu, Phillips

& Leung, 2003), level of education (Fernández-Muñiz et al., 2009; Gyekye &

Salminen, 2009) among others.

Employee involvement is a vital factor in the organization safety program used

to reduce injuries and accidents (Vinodkumar & Bhasi, 2010). Employee

involvement is the “extent employees could influence and control OHS

management issues at the workplace” (Masso, 2015, p. 64). In other words,

employee’s involvement into safety management process involves upward

communication flow among individuals or groups and decision-making process

within the organization (Vredenburgh, 2000) because employees use to make

suggestions about safety improvements, especially when new technologies and

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materials were introduced (Butler & Park, 2005). This factor is regarded among the

important indicator of positive organizational safety culture because is the best ways

to achieve safety ownership (Cooper, 1998; Ford & Tetrick, 2011; Liu, Bartram,

Casimir & Leggat, 2014). Employee’s involvement is a fundamental element of

safety management since it help organization to achieve main objectives and goal of

occupational safety and health implementation and improvement in organizational

safety conditions for the benefit of both employees and organizations (Podgórski,

2005).

High employee’s involvement in the organization’s strategic safety decisions

can reduce lost-time frequency rates (LTFR) (Shannon et al., 1996). Employee’s

involvement was examined to lower the frequency of unsafe behavior and injuries

in the organizations (Camuffo, De Stefano & Paolino, 2015; Rooney, 1992). Within

the hospital environment, Garrett and Perry (1996) found that employee’s

involvement in to safety decisions reduced injuries effectively within one year.

Vinodkumar and Bhasi (2010) reported employee involvement significantly related

with safety participation. Keffane and Delhomme (2013) also reported employee

involvement predicts safety compliance in a study aimed to understand the

performance of road safety practices in France. Based on the above submission,

empirical evidence suggests that employee’s involvement is important in

understanding employee’s safety compliance and participation. Therefore, we

hypothesized that:

Hypothesis 1b: Employee’s involvement is positively related to safety compliance.

Hypothesis 2b: Employee’s involvement is positively related to safety

participation.

2.4 CONSIDERATION OF FUTURE SAFETY CONSEQUENCES

Consideration of future consequences (CFC) is an individual differences

variable that explain how individuals differ in the extent to which they consider

distant versus immediate consequences of their potential behaviors. CFC is defined

as “The extent to which people consider the potential distant outcomes of their

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current behaviors and the extent to which they are influenced by these potential

outcomes” (Strathman, Gleicher, Boninger & Edwards, 1994, p. 743). Relative to

low CFC individuals, individuals high in CFC reported less use of alcohol and

tobacco (Strathman et al., 1994), exercise regularly (Ouellette et al., 2005), less

aggression (Joireman et al., 2003) participate in pro-environmental behavior

(Joireman et al., 2001), high academic performance (Peters, Joireman & Ridgway,

2005) among others. Probst et al. (2013) extended the concept to safety and define

consideration of future safety consequences (CFSC) as the “degree to which

employees consider the future versus immediate consequences of their safety-

related behaviors” (Probst et al., 2013, p. 125) and is related to various safety

outcomes (Probst et al., 2013).

We argue in this paper that consideration of future safety consequences

(CFSC) would provide additional explanation on what boundary condition safety

training and employee involvement can influence safety compliance and

participation. Therefore, the following hypothesis are advanced:

Hypothesis 3a: The positive relationship between safety training and safety

compliance will be stronger when consideration of future safety consequences is

high.

Hypothesis 3b: The positive relationship between workers involvement and safety

compliance will be stronger when consideration of future safety consequences is

high.

Hypothesis 3c: The positive relationship between safety training and safety

participation will be stronger when consideration of future safety consequences is

high.

Hypothesis 3d: The positive relationship between workers involvement and safety

participation will be stronger when consideration of future safety consequences is

high.

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2.5 CONCEPTUAL FRAMEWORK AND UNDERLINING THEORIES

This paper conceptualized that safety training and workers involvement which

are the independent variables influence the healthcare workers safety behavior

(safety participation and compliance). Also the CFSC is expected to moderate these

relationships. These relationships are shown in Figure 1 below.

The framework is underpinned by two theories i.e Social Exchange Theory

(SET) (Blau, 1964) and Construal Level Theory (CLT) (Liberman & Trope, 1998).

The SET “is one of the most influential conceptual paradigms for understanding

workplace behavior” (Cropanzano & Mitchell, 2005, P. 874). The primary tenets of

this theory is the reciprocity of commitments between employees and employer

over time (Blau, 1964). When an organizations exhibits a readiness to make

workplace safe and healthy, the employee oblige by engaging in desirable behavior

such as high compliance with work procedures and reducing undesirable behavior

such as unsafe behavior. In this paper, SET is theoretically applied to explain the

direct relationships between safety training, workers involvement and healthcare

workers safety behavior (Neal & Griffin, 2006). When hospital cares for their

workers safety (i.e., the hospitals give workers training and involve them in to

safety decision processes), the workers are likely to develop tacit obligations to

perform their duties, using behavior beneficial to the hospitals. When hospital

management offers adequate training to the workers, the HCWs would accordingly

carried out their responsibilities efficiently and safely, which then results in better

safety performance.

On the other hand, Construal Level Theory (CLT) (Liberman & Trope, 1998)

posits that employees have distinctive psychological links with events and objects

grounded on perceived social and temporal distances, taking along a remarkable

wrinkle to the discussion of individual safety behavior. According to this theory,

people construe distant future events using abstract representations. In contrast,

people who choose their behavior thinking only about immediate events using

concrete term (Trope & Liberman, 2010). This theory (Liberman & Trope, 1998) is

widely used in an effort to understand individual’s decision over time in the area of

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psychology (e.g., Fujita, & Sasota, 2011). Drawing from CLT (Trope & Liberman,

2010), this paper identify CFSC as plausible moderator that permit further

examination of safety training, workers involvement and safety behavior

relationships. Drawing from CLT theory, the study proposes that CFSC can play an

important role theoretically in explaining the moderating effects of CFSC on safety

training, workers involvement and safety behavior in that healthcare workers

framed their safety behavior in two different ways (i.e high-level vs. low-level

construal) (Liberman & Trope, 1998). Those with low-level construal frame their

safety behavior after immediate consideration (low-CFSC workers) while

healthcare workers with high-level construal is expected to frame their safety

behavior weighing at the future considerations.

Fig 1. Conceptual Framework

3. METHODOLOGY

3.1 SAMPLE AND DATA COLLECTION

The research methodology employed in this study was quantitative research

method using questionnaires to test the conceptual model. The study covered 12

secondary health facilities with total population of 1063 nurses and the required

samples sizes is 278 based on Krejcie and Morgan (1970) table of sample

determination. Four health facilities were randomly selected using cluster sampling

technique (the type of probability sampling) using the recommendation of Gay and

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Diehl (1992) five steps technique of selecting clusters with the total number of 317

nurses. Therefore, all the 317 nurses in these four facilities were responded to the

questionnaire. Of the 317 questionnaire distributed, 229 valid questionnaires were

returned and used which make the response rate of 72%. The 229 response is

enough for this study going by the G*power requirement, the minimum sample size

of 153 is required. Since the model had a 3 predictors and 4 interactions, we set the

effect size as medium (0.15) and required power of 0.95. The data was collected by

the researcher and the assistance of two research assistance. This study was

approved by the health and human services of the FCT. A cover letter was attached

to the questionnaire informing the nurses of the study goal. Respondents were

informed that participation was voluntary and that anonymity was guaranteed.

3.2 DATA ANALYSIS TECHNIQUE

The study employed Partial Least Square Structural Equation Modeling (PLS

SEM) SmartPLS 3.0 software (Ringle et al., 2015) to compute both the

measurement and structural models (Anderson & Gerbing, 1988). The rationales for

using PLS are: PLS path models are estimate with a small sample and with non-

normal data (Haenlein & Kaplan, 2004). PLS has the likelihood of providing

accurate computations of moderating effect because its accounts for error (Helm,

Eggert & Garnefeld, 2010). The two-step technique as recommended by Anderson

and Gerbing (1988) and suggestion of Hair et al. (2011), the bootstrapping

technique (5000 resample) was also used to ascertain the significance levels for the

path coefficient.

3.3 MEASURES

Six items adapted from Vinodkumar and Bhasi (2010) were used to measure

safety training. Internal consistency reliability of the items was 0.82. Sample items

include: “Newly recruits are trained adequately to learn safety rules and

procedures” and “safety training given to me is adequate to enable me to assess

hazards in the workplace”. Four items adapted from Vinodkumar and Bhasi (2010)

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were used to measure employee involvement. The internal consistency reliability of

the items was 0.69. Sample items include: “Management always welcomes opinions

from employees before making final decisions on safety-related matters”, and “my

company has safety committees consisting of representatives of management and

employees”.

Four items adopted from Neal and Griffin (2000) were used to measure safety

compliance. The items reported internal consistency reliability of 0.94. Sample

items include: “I carry out my work in a safe manner” and “I use all the necessary

safety equipment to do my job”. Four items adopted from Neal and Griffin (2000)

were used to measure safety participation. The items reported internal consistency

reliability of 0.89. Sample items include: “I promote the safety program within the

organization” and “I voluntarily carry out tasks or activities that help to improve

workplace safety”. Six items adapted from Probst et al. (2013) were used to

measure CFSC. The items reported internal consistency reliability of 0.71. Sample

items include: “Even though accidents reporting can take a lot of time and effort, it

helps other workers in the future” and “I sometimes need to compromise safety in

order to meet service delivery”. All the items in this section were measured using

five-point Likert scale ranging from 1= strongly disagree to 5= strongly agree.

4. RESULTS AND ANALYSIS

4.1 RESPONDENTS’ PROFILE

Based on the demographics characteristics of the respondents, majority of the

respondents are females 157(68.6%) while male consisted of 72 (31.4 %). Majority

of the respondents were of Hausa ethnic group 59 (29.8%), followed by Yoruba

ethnic group 51 (22.3%). Majority of the respondents are nursing 11 in term of

designation. Majority of the respondents are married 169 (73.8%). Also majority of

the respondents have nursing certificates 142(62%). The mean age and standard

deviation of the respondents were (M=14.67 SD=9.82). The respondents’ mean

years of experience and standard deviation as healthcare worker were (M=14.67

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SD=9.82). The respondents mean organizational tenure and standard deviation were

(M=4.67 SD=2.31).

4.2 DESCRIPTIVE STATISTICS

Table 1 presents the descriptive statistics, including the constructs means and

standard deviations and the reliability of the variables for descriptive purposes. As

presented in Table 1 the mean value of all the constructs ranged between 3.198 and

4.138. Composite reliabilities also ranged between 0.835 and 0.921 demonstrating

high reliability for all the variables in this study (Hair et al., 2014). Similarly,

Cronbach's Alpha value also ranged between 0.705 and 0.880 demonstrating high

reliability for all the variables (Hair et al., 2014).

Table 1: Mean, Standard deviation and Reliability of the Study Variables

Variable Mean Standard

deviation

Composite

Reliability

Cronbach's

Alpha

Safety Compliance 3.256 0.784 0.835 0.705

Safety Participation 3.975 0.566 0.854 0.743

Safety Training 3.258 0.927 0.921 0.896

Workers involvement 3.198 0.907 0.876 0.788

Consideration of Future

Safety Consequences

4.138 0.546 0.917 0.880

4.3 COMMON METHOD VARIANCE

Common method variance (CMV) in a study occur when two or more self-

reported measures are acquired from the same respondents at the same point of

time, the relationship between the constructs may be influenced by CMV(Podsakoff

et al., 2003). This type of variance is attributed to the measurement method rather

than the constructs. In this study, CMV was assessed (Podsakoff et al., 2003) using

Harman’s (1976) one-factor test principle component factor analysis. The rotation

shows that common method bias is not an issue in this study. No single factor

accounted for more than 50% of the variance (Podsakoff et al., 2003). The first

factor accounted for 31.7 percent of the variance.

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4.4 MEASUREMENT MODEL EVALUATION

To evaluate the measurement model in this paper, two types of validity were

assessed. Firstly, we assessed the convergent validity and secondly, discriminant

validity was assessed. Convergent validity is determined by examining the

composite reliability, loadings and average variance extracted (AVE) (Gholami et

al., 2013). As reported from Table 2 below, each construct has achieved the

loadings above 0.7, Composite reliability (CR) of all the constructs were all higher

than 0.7 and Average variance extracted (AVE) is above 0.5 as recommended by

Hair et al. (2014) (see Table 3).

Table 2: Convergent Validity

Constructs Items Loadings AVE CR

Consideration of Future Safety Consequences CFSC2 0.894 0.734 0.917

CFSC3 0.837

CFSC5 0.867

CFSC6 0.827

Safety Compliance COM1 0.82 0.629 0.835

COM2 0.775

COM4 0.783

Safety Participation PAR2 0.79 0.661 0.854

PAR3 0.833

PAR4 0.816

Safety Training STR1 0.891 0.663 0.921

STR2 0.815

STR3 0.763

STR4 0.887

STR5 0.795

STR6 0.718

Workers Involvement WKI1 0.797 0.703 0.876

WKI3 0.835

WKI4 0.881

Note: AVE = average variance extracted CR= Composite reliability

The discriminant validity (the extent to which items measure distinct concepts) was

assessed following the Fornell and Larcker (1981) criterion by comparing the

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square root of the AVE with the correlations among constructs (see Table 3). As

shown from Table 3, the square root of the AVEs (values in bolded) on the

diagonals were greater than the corresponding row and column values indicating the

measures were discriminant.

Table 3: Discriminant Validity Fornell-Larcker criterion

Constructs 1 2 3 4 5

1. CFSC 0.857

2. COM 0.058 0.793

3. PAR 0.234 0.305 0.813

4. STR 0.024 0.684 0.405 0.814

5. WKI -0.035 0.68 0.315 0.657 0.838

Note: Diagonals (in bold) signify the average variance extracted whereas the other entries

represent the squared correlations CFSC = Consideration of Future Safety Consequences

COM= Safety Compliance Par = Safety Participation STR= Safety Training WKI= Workers

Involvement

In addition to Fornell and Larcker (1981) criterion, the HTMT ratio was examined

as this criterion is regarded to be a more reliable criterion for evaluating

discriminant validity than the Fornell–Larcker criterion (Henseler et al. 2014;

Henseler, Ringle, & Sarstedt, 2015). The HTMT criterion in this study shows that

discriminant validity is achieved. The highest correlation found is between safety

training and workers Involvement 0.78, which is within the conventional yardstick

of 0.85 (Henseler et al., 2015) as shown in Tables 4. Therefore, both the two types

of validity in this study were achieved.

Table 4: Discriminant Validity Heterotrait-monotrait ratio (HTMT)

1 2 3 4 5

1. CFSC

2. COM 0.136

3. PAR 0.286 0.419

4. STR 0.077 0.69 0.494

5. WKI 0.069 0.71 0.409 0.78

Note: CFSC = Consideration of Future Safety Consequences COM= Safety Compliance Par

= Safety Participation STR= Safety Training WKI= Workers Involvement

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4.5 STRUCTURAL MODEL EVALUATION

Since the measurement model above is achieved in term of reliability and

validity, we evaluated the structural model to assess the hypothesized relationships

among the variable in this study (Hair et al., 2014). As presented in Table 4 and

Figure 2 below, we evaluated the standardize beta values and the t-values (Hair et

al., 2014). The t-values were obtain using bootstrapping procedure with 5000

resamples. In addition, we also calculated the predictive relevance (Q2) of the model

and effect sizes of each predictors on the dependent variables (f2) (Hair et al., 2014).

Figure 2 and Table 4 show the estimates for the full structural model, which

includes moderator variable (i.e., CFSC) in this study. All relationships in this study

are represented by standardized beta values. Additionally, in testing the

relationships of the structural model, the significance level was set at p<.001,

p<0.05 and p<.01 (1-tailed) (Hair et al., 2014). Significantly, the findings from

Table 4 demonstrated that among the two predictors of safety compliance, safety

training has the highest significant standardized beta coefficient (β=0.408), which

indicates that safety training is the most significant construct in predicting safety

compliance among nurses in Abuja secondary health facilities, Nigeria. Similarly,

among the two predictors of safety participation, safety training has the highest

significant standardized beta coefficient (β=0.301), which indicates that safety

training is the most significant construct in predicting both safety participation and

compliance in this study.

Fig. 2. Structural Model

63

Table 5: Results of the Structural Model Analysis (Hypotheses Testing)

Hypot

hesis

Relationships Std

Beta

Std

Error

t-

valu

e

P-

value

Decision

1a Safety Training -> Safety

Compliance

0.408 0.079 5.13

8

0.000

***

Supporte

d

1b Workers Involvement -> Safety

Compliance

0.402 0.085 4.72

1

0.000

***

Supporte

d

2a Safety Training -> Safety

Participation

0.301 0.077 3.91

3

0.000

***

Supporte

d

2b Workers Involvement -> Safety

Participation

0.125 0.077 1.62

4

0.052

*

Supporte

d

3a CFSC*Safety training -> Safety

Compliance

-

0.027

0.088 0.30

5

0.380 Not

Supporte

d 3b CFSC*Worker Involvement ->

Safety Compliance

0.159 0.092 1.72

5

0.043

**

Supporte

d

3c CFSC*Safety Training -> Safety

Participation

0.122 0.174 0.70

0

0.242 Not

Supporte

d

3d CFSC*Worker involvement ->

Safety Participation

-

0.080

0.117 0.68

4

0.247 Not

Supporte

d

Note: ***p < 0.01 **p<0.05 *p<0.1

4.6 INTERACTION EFFECT

As presented in Figure 3, Hypothesis 3b stated that CFSC moderates the

relationship between workers involvement and safety compliance. Specifically, this

relationship is stronger (i.e. more positive) for individuals with high CFSC than

individuals with low CFSC. As expected, the finding from Table 5 and Figure 2

showed that the interaction terms representing worker involvement*CFSC on safety

compliance (β = 0.159, t = 1.725, p < 0.05) was statistically significant. Therefore,

Hypothesis 3b was supported. As recommended by Dawson (2013) using two-way

interaction with continuous moderator, the result of the path coefficients (β) was

used to plot this relationship. Figure 3 indicated that the relationship between

worker involvement and safety compliance is stronger (i.e. more positive) for

individuals with high CFSC than individuals with low CFSC.

64

Fig. 3. Interaction effects

4.7 IMPORTANCE-PERFORMANCE MATRIX ANALYSIS (IPMA)

To extend the findings in this study, the post-hoc importance-performance

matrix analysis (IPMA) (Hair et al., 2014) was conducted using safety compliance

and safety participation as outcome variables. Figure 4 and 5 visualize the

performance level of each independent variable along with its importance on the

dependent variable so that decisions can be easily made by hospital management

from the graphical representation. The total effect, which draws on path coefficients

(on a scale from zero to 0.4 on the horizontal axis), shows the importance of the

independent variables, while the mean value of their scores (on a scale from zero to

100 on vertical axis) show their performance. From the Figure 4 it becomes obvious

that in relations to assigning priority by hospital management, the variable safety

training is highly relevant for increasing nurses’ safety compliance as its shows the

highest impact. Therefore, hospital management should focus and retain this area of

performance, or even expand the area. From the Figure 5 it becomes obvious that in

relations to assigning priority by hospital management, the variables safety training

and CFSC are highly relevant for increasing nurses’ safety participation due to their

main impact. Therefore, hospital management should focused and retain these areas

of performance, or even expand the areas to ensure nurses safety participation.

65

Fig. 4. IPMA of safety compliance

Fig. 5. IPMA of safety participation

5. DISCUSSION

The paper examined the moderating role of CFSC on the relationship between

safety training, workers involvement and healthcare workers safety behavior in

Nigeria. As presented in Table 5 above, The finding indicated that a positive

relationship exists between safety training and safety compliance of nurses in Abuja

secondary health facilities Nigerian (β=0.408; t =5.138; p = 0.000), thereby

supporting H1a. This finding is consistent with previous research (Lu & Yang 2011;

Vinodkumar & Bhasi, 2010; Vredenburgh, 2002). Additionally, the study found a

significant positive relationship between safety training and safety participation

66

(β=0.301; t=3.913; p=0.000) revealing H2a is also supported. The finding is in line

with prior studies (Donald & Cantre, 1994).This findings shows that the Abuja

secondary hospitals in Nigeria have a supportive climate for safety training and that

nurses are transferring the safety training they learned from the various safety

training program implemented by the hospital management to their jobs. This

findings is not surprising given that the study was conducted immediately after the

country suffered from Ebola epidemics, many nurses may have undergone rigorous

emergency response safety training.

The findings also revealed a significant positive relationship between workers

involvement and safety compliance among nurses in Abuja secondary health

facilities (β=-0.402; t =4.721; p = 0.000). Hence, H1b is also supported. The finding

of H1b is congruent with prior research (Camuffo, De Stefano & Paolino, 2015).

The finding also indicated that a positive relationship exists between workers

involvement and safety participation of nurses in Abuja secondary health facilities

Nigerian (β=0.125; t =1.624; p = 0.052), thereby supporting H2b. The finding is in

line with prior studies (Ford & Tetrick, 2011; Liu, Bartram, Casimir & Leggat,

2014). The possible reasons for obtaining these results in Abuja secondary health

facilities is that Abuja is the federal capital of Nigeria where majority of the NGOs

are located. These NGOs always encourages management to involve workers in

safety decisions and allow them to take part in all matters related to safety and

health through their representatives especially on protection measures.

The moderating findings revealed that CFSC moderates the relationship

between workers involvement and safety compliance (β = 0.159; t = 1.725; p =

0.043), hence H3b is accepted. This is in line with our postulation that the

relationship will be stronger for individuals high in CFSC than the individual with

low CFSC as reported in Fig. 3. The finding of H3b is pioneering in safety literature

and our major contribution in this area. The moderation result also shows that CFSC

did not moderates the relationship between workers involvement and safety

participation (β = -0.080; t = 0.680; p = 0.247), hence, H3d is not supported.

Additionally, CFSC fails to moderate the relationship between safety training and

67

safety compliance (β =-0.027; t =0.305, p = 0.380) thereby rejecting H3a. Likewise,

CFSC fails to moderates the relationship between safety training and safety

participation (β =0.112; t =0.700, p = 0.242). The plausible reasons for these results

is that the study population is new to this type of research, and the items are not

tested to non-western culture, also safety research in Africa is still at embryonic

stage (Salminen & Seo, 2015).

Another criteria for evaluating the structural model is coefficient of

determination (R²).The R² of the safety compliance is 0.565 which implied that

safety training, employee involvement and CFSC collectively explained 56.5% of

the variations in safety compliance among nurses in Abuja secondary health

facilities, Nigeria. Additionally, R² of safety participation is 0.221 which implied

that safety training, employee involvement and CFSC collectively explained 22.1%

of the variations in safety participation among nurses in Abuja secondary health

facilities, Nigeria. Chin (1998) classified R² of 0.19, 0.33 and 0.67 as weak,

moderate and substantial respectively. Therefore, the R² values in this study can be

classified as moderate. Other criterion for assessing a structural model is effect-size

(f²) which indicates the effect of particular exogenous latent variable on endogenous

variable. Cohen (1988) classified effect-size of 0.02, 0.15 and 0.35 as small,

medium, large respectively. The effect sizes (f²) of the safety training and workers

involvement on safety compliance were 0.220 and 0.221 which are all medium.

The effect sizes (f²) of safety training and workers involvement on safety

participation are 0.079 and 0.008 which are small effect and no effect respectively.

The effect-size (f²) of the moderator are 0.031 on compliance and 0.028 on

participation which are small respectively. The final evaluating criterion is

predictive relevance (Q²) which is assessed using construct-cross validated

redundancy. Therefore, Q² greater than zero indicates predictive relevance of a

model (Geisser, 1974). Q² of safety compliance is 0.34 and for safety participation

is 0.112 which are all greater than zero, which indicates the model of this study has

predictive relevance.

68

To extend the findings in the study, the post-hoc importance-performance

matrix analysis (IPMA) (Hair et al., 2014) was conducted using safety compliance

and safety participation as outcome variables. Based on Figure 4, it can be observed

that safety training and workers involvement are very significant factors in

determining nurses safety compliance in Abuja secondary health facilities. Based on

Figure 4, it can be observed that safety training and CFSC are very significant

factors in determining nurse’s safety participation in Abuja secondary health

facilities. Therefore, there is need for the hospital management to focus more on

safety training and workers involvement to ensure safety compliance. Similarly,

safety training and CFSC need to be given proper attention to ensure nurses safety

participation.

Early empirical studies (e.g., Hayes et al., 1998) have demonstrated that

employee positive perceptions of safety are linked with fewer incidents and accident

rates. Two management practices examined in this study contribute to the

healthcare workers perception of how strong safety management practices influence

their safety compliance and participation which have the likelihood of fewer

injuries. Healthcare workers safety training and workers involvement in this study

were significant predictors of safety compliance and participation. This should be

given emphasis in developing proper safety program in the hospitals. The findings

similarly show that CFSC is an important variable in HCWs safety behaviors. This

suggests that high CFSC individual would likely to demonstrate high safe behavior.

HCWs who have high CFSC are motivated to regulate their behaviors, to partake in

safety related matters. This findings suggests that CFSC is significant construct to

put into consideration when training HCWs in the hospitals.

Significantly, this paper showed that CFSC interacts with the effect of worker

involvement on HCWs safety compliance. An interesting results is that CFSC

significantly moderates relationship between worker involvement and HCWs safety

compliance. This indicates safety compliance increase for HCWs when worker

involvement is high and CFSC is high. Specifically, worker involvement leads to

higher safety compliance behavior when CFSC is higher rather than low (see Fig.

69

3). This suggests that hospitals where worker involvement is high and workers with

increased CFSC, safety compliance can be improved.

6. THEORETICAL AND PRACTICAL IMPLICATIONS

This findings in this study is significant to both theory and practice.

Theoretically, understanding safety training and employee participation practices

might provide evidence-based promotion of safety management practices in

hospitals and implementation of its philosophy. The study also reported the

predictive power of CFSC in understanding healthcare workers safety behavior. Our

study also tested the utility of social exchange theory (SET) (Blau, 1964) and

construal level theory (CLT) (Liberman & Trope, 1998) in safety context. To the

best of our knowledge this study is pioneering in using Construal Level Theory

(CLT) in safety context.

From practical perspectives, since findings suggest that the safety training play

an important role in employee safety compliance. Therefore, one can believe that a

committed implementation of safety training by all hospital stakeholders is likely to

provide useful changes in HCWs safety compliance. This possibly will present a

benefit for hospitals by maintaining a healthier status in the hospitals and improving

their morale. To the management, it will reduce compensation cost, lower employee

turn-over, reduce insurance premium, reduce lost time and provide efficient and

motivated workers and consequently, improved hospitals productivity. This

empirical findings also provides evidence to practitioners on possible weaknesses in

their safety training practices for safety improvement. We found that when safety

training is high, healthcare workers safety compliance can be increase. Hence, to

improve HCWs safety compliance and decrease hospitals injury incidents, safety

training should be given major attention. This findings is consistent with findings in

the chemical industry in the study of Vinodkumar and Bhasi (2010). The findings

have significant implications for management practice in hospitals, particularly

where HCWs safety is a major concern. The main implication of this paper is that

even though safety training and employee involvement are critical for keeping

70

employees safe, hospital management also need to consider individual CFSC issues

that may provide additional guide. We found initial evidence that CFSC is critical

for enhancing the positive effects of worker involvement and safety behavior.

Consequently, hospital managers and unit managers should consider the role of

CFSC when developing techniques to effectively promote safety compliance of

workers.

7. LIMITATION AND RECOMMENDATIONS FOR FUTURE RESEARCH

Generally, this research contributed to the safety literature on the utility of

CFSC by relating it directly to the hospital environment, which has not been

investigated in hospital setting before and significant of SMPs in understanding

nurses safety performance in African context. As in every empirical study, the

findings of this study is not without limitations. Therefore, while interpreting the

results, the following limitations can be taking into account. Firstly, only one

moderating hypothesis is supported in this study. Therefore, there is need to further

explore these model with the original consideration of future consequences (CFC)

scale developed by Strathman et al. (1994), as Strathman et al. conceptualized CFC

as a general individual differences variable that would be stable across many

settings. Therefore, future research is recommended to use Strathman et al. scale to

investigate the moderating effect of CFC on relationships between safety training

and workers involvement on healthcare workers safety behavior across various

hospitals.

Secondly, this study adopted a cross-sectional research design. Hence, no

causal inferences could be made to the population, such a statement of causal

inferences requires the collection of longitudinal data. Therefore, future studies are

recommended to use longitudinal design to detect variations over time. Finally, in

this study safety compliance and safety participation were assessed using self-report

measures which may be associated with social desirability bias (Grimm, 2010).

There is possibility that the respondents might have over-reported their safety

compliance and safety participation on the survey questionnaires. Thus, future

71

studies may use other method to assess safety compliance and safety participation.

More specifically, supervisor ratings of safety compliance and participation and/or

peers reporting of safety compliance and participation to control for the social

desirability bias.

8. CONCLUSION

The study examines the direct effect of safety training and workers

involvement on healthcare workers safety behavior (safety compliance and safety

participation). The study also examined the moderating effect of CFSC on the

relationship between safety training and workers involvement on healthcare workers

safety compliance and safety participation. The findings revealed that safety

training is positively related to safety compliance and safety participation. It also

revealed that workers involvement is positively related to safety compliance and

participation. CFSC moderates the relationship between workers involvement and

safety compliance. However, the moderating effect of CFSC on the relationship

between safety training and safety compliance had not been established, moderating

effect of CFSC on the relationship between safety training and safety participation

and the moderating effect of CFSC on the relationship between workers

involvement and safety participation had not been established in this study. Thus,

the study recommends future research to explore CFSC as a moderator in other

contexts.

72

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