**4. Results**

### **4.1 Respondents' demography information**

Four hundred forty-three structured questionnaires were distributed, and 399 were returned representing 90.07%. The respondents' background information is as follows. The academic qualifications: National Diploma (3%), Bachelor of Science/Higher National Diploma (64%), Postgraduate Diploma (10%), Master of Science (17%), and Ph.D. (6%). Professional affiliation: Architects (20.8%), Builders (3.3%), Engineers (58.6%), Quantity Surveyors (16.8%), and Surveying and Geoformation (0.5%). Year of experience: 1–5 years (7.85%), 6–10 years (8.5%), 11–15 years (22.8%), 16–20 years (27.8%), and 21 years and above (33.1%). Firms, organizations, and institutions: Consulting firms (25.3%), Contracting firms (16.8%), Developer organizations (23.1%), Educational institutions (6.8%), Governmental agencies (22.8%), and Multinationals (5.3%).

*Approaches to Improving Occupational Health and Safety of the Nigerian Construction Industry DOI: http://dx.doi.org/10.5772/intechopen.113011*

## **4.2 Dimensionality of the scale**

Evaluation of the data was conducted through EFA. The cutoff value of the exploratory factor was fixed at 0.40 according to Yong and Pearce [39], through the principal component in varimax rotation. Values less than 0.4 were dropped, but values above 0.4 were considered for the analysis. **Table 2** shows the result of the EFA for this study. Kaiser-Meyer-Olkin (KMO) was used to evaluate the appropriateness of data for EFA. Pallant [40] highlighted that a KMO value of 0.6 is suggested as the minimum value for good factor analysis. The KMO result obtained was 0.828, therefore, the data were considered acceptable for the analysis. Confirmatory factor analysis was conducted with structural equation modeling-AMOS. CFA was used to develop and check the psychometric validity of the approaches to the improvement of occupational health and safety in the Nigerian construction industry. The unidimensional approach of OHS is the Establishment of the Nigerian Construction Industry Development Board, technical assistance and collaboration, skill development, awareness-raising and advocacy, use of International Labour Organization mechanism, international collaboration, proper monitoring and recording, and adequate allocation of resources. The initial goodness of fit showed that the model was not fitted as illustrated in **Figure 2**. The result of the indices was CFI = 0.874, incremental fit index (IFI) = 0.875, Tucker-Lewis index (TLI) = 0.864, P = 0.000, RMSEA = 0.05, P = 0.00, and ratio = 2.001. Although RMSEA = 0.05, P = 0.00, and ratio = 2.001 met the minimum threshold, CFI = 0.874, IFI = 0.875, and TLI = 0.864 did not meet the minimum threshold. Thereafter, variables that contributed to the poor fit of the model were dropped [41]. The total number



*a Rotation converged in seven iterations.*

#### **Table 2.**

*EFA of approaches to improving OHS.*

of six variables with low factor loadings was eliminated. **Figure 3** illustrates the final model with acceptable goodness of fit. **Table 3** illustrates the acceptable model fit of the approach to improving occupational health and safety of the Nigerian construction industry with the following indices such as minimum discrepancy divided by degree of freedom (CMIN/DF) = 1.846, CFI = 0.912, standardized root mean squared residual (SRMR) = 0.063, RMSEA = 0.055, and Pclose = 0.167. **Table 4** illustrates the standardized regression weight of the factors which are all above the minimum threshold of 0.5 of a good model.
