Table 5.

Confirmatory factor analysis

Construct	Indicator	Estimate	Std.Err	z-value	P(> |z|)
$\mathrm{\Delta }\text{Wellbeing}=\sim$	ΔWB1	1.000
	ΔWB2	0.896	0.016	54.518	0
	ΔWB3	0.955	0.016	58.917	0
	ΔWB4	0.804	0.018	44.686	0
	ΔWB5	0.848	0.017	51.041	0
$\mathrm{\Delta }\text{Productivity}=\sim$	ΔP1	1.000
	ΔP2	− 1.268	0.053	− 24.084	0
	ΔP3	− 1.120	0.053	− 20.979	0
	ΔP4	− 1.239	0.053	− 23.263	0
	ΔP5	− 1.229	0.055	− 22.266	0
	ΔP6	− 1.306	0.058	− 22.677	0
	ΔP8	1.460	0.057	25.512	0
$\text{Ergonomics}=\sim$	Erg1	1.000
	Erg2	0.964	0.035	27.395	0
	Erg3	0.820	0.037	22.128	0
	Erg4	0.937	0.035	26.663	0
	Erg5	1.064	0.034	31.535	0
	Erg6	1.258	0.035	35.821	0
Disaster	DP1	1.000
$\text{Preparedness}=\sim$	DP2	0.716	0.089	8.079	0
	DP3	1.181	0.112	10.521	0
	DP4	0.923	0.105	8.805	0
	DP5	1.186	0.120	9.888	0

Notes: converged after 50 iterations with 185 free parameters (n = 1377); estimates may exceed 1.0 because they are regression coefficients, not correlations as in Principal Component Analysis; negative estimates indicate reversed items