Validation of the Spanish version of the Neal, Griffin and Hart safety behavior scale

Figures & data

Table 1. Findings of selected studies about the psychometric properties of the SBS.

Authors	Participants	Sample size	Language	Factorial configuration	Type of analysis	Method and model specification	Factor loadings	Internal consistency	AVE	Factor correlation
Toderi et al. [58]	Construction and logistic workers	N = 277Age: NR	Italian	SC: 4 itemsSP: 4 items	CFA and SEM	Estimator: MLRModel: two first-order factors	>0.50	ω:SC 0.86SP 0.73	SC 0.61SP 0.41	0.48
Smith et al. [28]	Firefighters	N = 349Age: M 36.45 years, SD 9.08	English	SC: 3 itemsSP: 3 items	CFA and SEM	Estimator: NRModel: two first-order factors	NR	α:SC 0.80SP 0.83	NR	0.51
Kalteh et al. [59]	Petrochemical workers	N = 160Age: M 32.68 years, SD 7.39	Persian	SC: 4 itemsSP: 4 items	CFA	Estimator: ADFModel: two first-order factors	>0.70	α:SC 0.87SP 0.83	NR	0.77
Mashi et al. [30]	Healthcare workers	N = 229Age: M 39.85 years, SD NR	English	SC: 4 itemsSP: 4 items	CFA and SEM	Estimator: PLSModel: two first-order factors	>0.75	ω:SC 0.83SP 0.75	SC 0.66SP 0.44	0.53
Wong [48]	Nurses	N = 324Age: M 36.58 years, SD 11.45	Chinese	SC: 3 itemsSP: 3 items	CFA and SEM	Estimator: NRModel: two first-order factors	NR	α:SC 0.88SP 0.88	NR	0.27
Li et al. [46]	Miners	N = 593Age: M 32 years, SD 7.32	Chinese	SC: 3 itemsSP: 3 items	CFA and SEM	Estimator: MLModel: two first-order factors	>0.70	α:SC 0.83SP 0.85	NR	NR
Newaz et al. [40]	Construction workers	N = 352Age: 21–50 years ≈ 80%	English	SC: 3 itemsSP: 3 items	CFA and SEM	Estimator: MLModel: unidimensional	>0.70	NR	SB 0.55	NR
Brondino et al. [54]	Heavy industry (blue-collar workers)	N = 549Age: NR	Italian	SC: 4 itemsSP: 4 items	CFA, MCFA and SEM	Estimator: MLModel: two first-order factors	NR	ω:SC 0.86SP 0.75	NR	0.53
He et al. [5]	Construction workers	N = 655Age: 25–49 years ≈ 85%	Chinese	SC: 3 itemsSP: 3 items	CFA and SEM	Estimator: NRModel: two first-order factors	>0.85	α:SC 0.86SP 0.86ω:SC 0.78SP 0.79	SC 0.78SP 0.79	0.52
Li et al. [35]	Construction workers	N = 457Age: <51 years ≈ 94%	Chinese	SC: 3 itemsSP: 3 items	SEM	Estimator: NRModel: two first-order factors	>0.60	α:SC 0.89SP 0.90	NR	NR
Wong and Chan [51]	Hotel workers	N = 1023Age: M 35.20 years, SD 10.19	Chinese	SC: 3 itemsSP: 3 items	SEM	Estimator: NRModel: two first-order factors	NR	α:SC 0.77SP 0.82	NR	0.49
Xia et al. [41]	Construction workers	N = 120Age: 30–49 years ≈ 68%	Chinese	SC: 7 itemsSP: 3 items	CFA	Estimator: NRModel: two first-order factors	NR	α:SC 0.85SP 0.84	NR	0.66
Yu et al. [63]	Construction workers	N = 385Age: M 30.80 years, SD 1.11	Chinese	SC: 3 itemsSP: 3 items	CFA	Estimator: NRModel: unidimensional	>0.70	NR	SB 0.66	0.80
He et al. [36]	Construction workers	N = 536Age: 30–49 years ≈ 74%	Chinese	SC: 3 itemsSP: 3 items	SEM	Estimator: NRModel: two first-order factors	>0.80	α:SC 0.87SP 0.86ω:SC 0.92SP 0.92	SC 0.79SP 0.79	0.50
Heier et al. [57]	Healthcare workers	N = 160Age: <51 years ≈ 85%	German	SC: 4 itemsSP: 4 items	EFA and CFA	Estimator: MLModel: two first-order factorsRotation: promax oblique rotation	>0.50	α:SC 0.84SP 0.76	SC 0.54SP 0.44	0.43
Liu et al. [23]	Construction workers	N = 189Age: 19–50 years ≈ 85%	Chinese	SC: 7 itemsSP: 3 items	CFA	Estimator: MLModel: two first-order factors	>0.60	ω:SC 0.88SP 0.84	SC 0.65SP 0.64	0.79
Martínez-Córcoles et al. [60]	Nuclear power plants workers	N = 479Age: 45 years or younger = 21%, older than 45 years = 79%	Spanish	SC: 3 itemsSP: 3 items	CFA and SEM	Estimator: WLSModel: three CFA models including SC and SP as latent factors	NR	α:SC 0.88SP 0.86	NR	0.56
Saleem et al. [37]	Construction workers	N = 345Age: 18–45 years ≈ 82%	Malay	SC: 3 itemsSP: 3 items	SEM	Estimator: NRModel: two first-order factors	>0.90	α:SC 0.97SP 0.94ω:SC 0.97SP 0.94	SC 0.92SP 0.83	0.26
Xu et al. [21]	Pilots	N = 343Age: M 31.28 years, SD 6.60	Chinese	SC: 3 itemsSP: 3 items	CFA	Estimator: NRModel: unidimensional	NR	α:SB 0.83	NR	NR
Yu et al. [25]	Miners	N = 1207Age: M 32.15 years, SD 5.82	Chinese	SC: 3 itemsSP: 3 items	CFA	Estimator: NRModel: unidimensional	NR	ω:SB 0.87	SB 0.78	NR

Note: α = Cronbach's α reliability coefficient; ADF = asymptotically distribution-free estimator; AVE = average variance extracted; CFA = confirmatory factor analysis; EFA = exploratory factor analysis; MCFA = multilevel confirmatory factor analysis; ML = maximum likelihood estimator; MLR = maximum likelihood robust; N = sample size; NR = does not report; PLS = partial least squares estimator; SB = safety behavior; SBS = safety behavior scale; SC =  safety compliance dimension; SEM = structural equation modeling; SP = safety participation dimension; WLS = weighted least squares estimator; ω = McDonald's ω reliability coefficient.

Figure 1. Graphical representation of the CFA and ESEM factorial structures of the SBS tested in this study. Note: CFA = confirmatory factor analysis; ESEM = exploratory structural equation modeling; SBS = safety behavior scale.

Table 2. Descriptive statistics for the SBS items (N = 398).

Item	Mean	SD	Skewness	Kurtosis	K–S
Safety compliance
SB01	4.56	0.81	−2.43	6.57	0.40***
SB02	4.72	0.70	−2.96	9.10	0.47***
SB03	4.68	0.68	−2.82	9.73	0.44***
SB04	4.65	0.64	−2.10	5.02	0.43***
Safety participation
SB05	4.23	0.83	−0.81	0.26	0.28***
SB06	4.53	0.73	−1.85	4.63	0.37***
SB07	4.68	0.62	−2.39	7.49	0.44***
SB08	4.46	0.80	−1.70	3.16	0.36***

***p < 0.001.

Note: K–S = Kolmogorov–Smirnov test of normality; SBS = safety behavior scale.

Table 3. Means and standard deviations of the SBS dimensions for the overall sample and groups.

	Safety behavior
Group	Safety compliance	Safety participation
Overall sample	4.65 (0.61)	4.47 (0.58)
Subsamples by age
Young adults (age ≤ 35 years)	4.59 (0.67)	4.41 (0.63)
Middle-aged adults (age > 35 years)	4.79 (0.43)	4.63 (0.40)
Subsamples by type of contract
Permanent employees	4.73 (0.47)	4.53 (0.46)
Contractors	4.43 (0.88)	4.33 (0.82)
Subsamples by firm size
≤500 workers	4.58 (0.71)	4.43 (0.70)
>500 workers	4.71 (0.53)	4.51 (0.45)

Note: Standard deviations reported in parentheses. Means and standard deviations were calculated using all indicators of the corresponding factors. SBS = safety behavior scale.

Table 4. Model fit of the estimated CFA and ESEM measurement models as estimated for the overall sample.

Model	Type	CFI	TLI	rmsea [90% CI]	SRMR	AIC	BIC	SSA-BIC	Meets criteria
Confirmatory factor analysis models
SBQ1	Unidimensional CFA	0.966	0.933	0.078 [0.054, 0.102]	0.055	5591.37	5710.96	5615.77	No
SBQ2	Correlated two first-order factor CFA	0.994	0.990	0.030 [0.000, 0.059]	0.024	5552.28	5669.92	5584.24	Yes
SBQ3	Hierarchical CFA	0.994	0.990	0.030 [0.000, 0.057]	0.105	5562.33	5665.98	5583.48	No
SBQ4	Bifactor CFA	0.998	0.995	0.021 [0.000, 0.057]	0.015	5559.08	5686.64	5585.11	Yes
Exploratory structural equation modeling models
SBQ5	Correlated two first-order factor ESEM	0.996	0.991	0.017 [0.000, 0.057]	0.012	5558.80	5690.35	5585.64	Yes
SBQ6	Bifactor ESEM	The model converged but the error variance of item SB04 was found to be negative, even after being constrained to be positive and close to zero

Note: AIC = Akaike information criterion; BIC = Bayes information criterion; CFA = confirmatory factor analysis; CFI = comparative fit index; CI = confidence interval; ESEM = exploratory structural equation modeling; rmsea = root mean square error of approximation; SRMR = standardized root mean square residual; SSA-BIC = sample-size adjusted BIC; TLI = Tucker–Lewis index.

Table 5. Results of the retained CFA and ESEM measurement models comparison.

Model comparison	ΔCFI	ΔTLI	Δrmsea	ΔSRMR	ΔAIC	ΔBIC	ΔSSA-BIC	Differences
SBQ4 vs SBQ2	0.004	0.005	−0.009	−0.009	6.79	16.73	0.86	No
SBQ5 vs SBQ2	0.002	0.001	−0.013	−0.012	6.52	20.44	1.40	No
SBQ5 vs SBQ4	−0.002	−0.004	−0.004	−0.003	−0.28	3.71	0.54	No

Note: AIC = Akaike information criterion; BIC = Bayes information criterion; CFA = confirmatory factor analysis CFI = comparative fit index; ESEM = exploratory structural equation modeling; rmsea = root mean square error of approximation; SRMR = standardized root mean square residual; SSA-BIC = sample-size adjusted BIC; TLI = Tucker–Lewis index.

Figure 2. Correlated two first-order factor CFA representation of the SBS as estimated for the overall sample (N = 398). Note: CFA = confirmatory factor analysis; SBS = safety behavior scale.

Table 6. Model fit indices of model SBQ₂ as estimated by age, type of contract and firm size subsamples.

Group	CFI	TLI	rmsea [90% CI]	SRMR	AIC	BIC	SSA-BIC
Subsamples by age
Young adults (age ≤ 35 years)	0.996	0.994	0.025 [0.000, 0.063]	0.023	4152.91	4250.66	4165.05
Middle-aged adults (age > 35 years)	0.968	0.950	0.060 [0.000, 0.108]	0.055	1206.11	1279.01	1196.81
Subsamples by type of contract
Permanent employees	0.963	0.939	0.065 [0.038, 0.093]	0.039	3626.45	3726.18	3640.56
Contractors	0.974	0.955	0.085 [0.022, 0.137]	0.035	1707.04	1780.26	1691.83
Subsamples by firm size
≤500 workers	0.986	0.976	0.055 [0.000, 0.095]	0.028	2490.89	2576.34	2490.84
>500 workers	0.949	0.920	0.076 [0.046, 0.107]	0.042	2966.22	3054.81	2972.41

Note: AIC = Akaike information criterion; BIC = Bayes information criterion; CFI = comparative fit index; CI = confidence interval; rmsea = root mean square error of approximation; SRMR = standardized root mean square residual; SSA-BIC = sample-size adjusted BIC; TLI = Tucker–Lewis index.

Table 7. Reliability and AVE estimates of the safety behavior dimensions.

	Safety compliance		Safety participation
Group	Reliability	AVE	Reliability	AVE
Overall sample	0.873	0.633	0.781	0.472
Subsamples by age
Young adults (age ≤ 35 years)	0.873	0.632	0.831	0.555
Middle-aged adults (age > 35 years)	0.859	0.606	0.710	0.384
Subsamples by type of contract
Permanent employees	0.834	0.558	0.704	0.373
Contractors	0.896	0.685	0.868	0.628
Subsamples by firm size
≤500 workers	0.857	0.602	0.702	0.373
>500 workers	0.898	0.687	0.878	0.645

Note: Reliability estimates were based on McDonald's ω coefficient [74,78]. AVE = average variance extracted.

Table 8. Results of the MI analysis results by age, type of contract, and firm size.

Model		TLI	CFI	rmsea [90% CI]	ΔTLI	ΔCFI	Δrmsea	Comparison	Decision
MI analysis by age (young adults and middle-aged adults)
M1	Configural invariance	0.966	0.978	0.056 [0.027, 0.081]	–	–	–	–	Accepted
M2	Weak invariance	0.969	0.977	0.054 [0.027, 0.078]	0.003	−0.001	−0.002	M2 vs M1	Accepted
M3	Strong invariance	0.962	0.968	0.059 [0.036, 0.081]	−0.007	−0.009	0.005	M3 vs M2	Accepted
M4	Strict invariance (a)	0.887	0.885	0.102 [0.085, 0.120]	−0.075	−0.083	0.043	M4 vs M3	Rejected
M4a	Partial strict invariance	0.956	0.959	0.064 [0.043, 0.084]	−0.006	−0.009	0.005	M4a vs M3	Accepted
MI analysis by type of contract (full-time employees and contractors)
M1	Configural invariance	0.928	0.954	0.081 [0.059, 0.104]	–	–	–	–	Accepted
M2	Weak invariance	0.938	0.954	0.075 [0.054, 0.097]	0.010	0,000	−0.006	M2 vs M1	Accepted
M3	Strong invariance	0.944	0.952	0.072 [0.051, 0.092]	0.006	−0.002	−0.003	M3 vs M2	Accepted
M4	Strict invariance (b)	0.873	0.870	0.108 [0.092, 0.126]	−0.071	−0.082	0.036	M4 vs M3	Rejected
M4a	Partial strict invariance	0.940	0.942	0.074 [0.055, 0.094]	−0.004	−0.010	0.002	M4a vs M3	Accepted
MI analysis by firm size (≤500 workers and >500 workers)
M1	Configural invariance	0.916	0.946	0.091 [0.070, 0.114]	–	–	–	–	Accepted
M2	Weak invariance	0.939	0.954	0.078 [0.057, 0.100]	0.023	0.008	−0.013	M2 vs M1	Accepted
M3	Strong invariance (c)	0.932	0.942	0.082 [0.063, 0.102]	−0.007	−0.012	0.004	M3 vs M2	Rejected
M3a	Partial strong invariance	0.937	0.947	0.079 [0.059, 0.099]	−0.002	−0.007	0.001	M3a vs M2	Accepted
M4	Strict invariance (d)	0.926	0.927	0.086 [0.068, 0.104]	−0.011	−0.020	0.007	M4 vs M3a	Rejected
M4a	Partial strict invariance	0.928	0.937	0.085 [0.066, 0.103]	−0.009	−0.010	0.006	M4a vs M3a	Accepted

Note: The following parameters were set to be estimated freely: (a) the uniqueness of SB02, SB03, SB05 and SB08; (b) the uniqueness of SB02, SB03 and SB08; (c) the intercept of SB08; and (d) the uniqueness of SB03. CFI = comparative fit index; CI = confidence interval; MI = measurement invariance; rmsea = root mean square error of approximation; TLI = Tucker–Lewis index.

Table

Item	Statement
SB01	Desempeño mi trabajo de una forma segura (I carry out my work in a safe manner)
SB02	Utilizo los equipos de seguridad necesarios para desempeñar mi trabajo (I use all the necessary safety equipment to do my job)
SB03	Manejo los procedimientos de seguridad correctos para desempeñar mi trabajo (I use the correct safety procedures for carrying out my job)
SB04	Me aseguro de tener los niveles más altos de seguridad cuando estoy trabajando (I ensure the highest levels of safety when I carry out my job)
SB05	Promuevo el programa de seguridad dentro de mi organización (I promote the safety program within the organization)
SB06	Yo pongo un esfuerzo extra para mejorar la seguridad en el lugar de trabajo (I put in extra effort to improve the safety of the workplace)
SB07	Ayudo a mis compañeros de trabajo cuando están trabajando en condiciones peligrosas o de riesgo (I help my co-workers when they are working under risky or hazardous conditions)
SB08	Participo voluntariamente en actividades o tareas que ayudan a mejorar la seguridad en el lugar de trabajo (I voluntarily carry out tasks or activities that help to improve workplace safety)

Note: Items SB01–SB04 are part of the safety compliance dimension, while items SB05–SB08 constitute the safety participation dimension. The original English version of the items is shown in parentheses.

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Data availability statement

The data presented in this study are available on request to the corresponding authors. The data are not publicly available due to privacy concerns.