Developing the HLS19-YP12 for measuring health literacy in young people: a latent trait analysis using Rasch modelling and confirmatory factor analysis

Table 5 Fit statistics for different factor structures of 12-item short versions applying CFA

Model	Short version	\({{\varvec{\chi}}}_{{\varvec{M}}}^{2}\boldsymbol{ }({\varvec{d}}{\varvec{f}}),\boldsymbol{ }{\varvec{p}}\)	SRMR	\({\varvec{N}}{\varvec{o}}.{{\varvec{r}}}_{{\varvec{r}}{\varvec{e}}{\varvec{s}}}\) \((>.10)\)	RMSEA (CI)	CFI/TLI
one-factor	HLS₁₉-YP12	135.48 (54), .000	.030	none	.039 (.024-.053)	.985/.981
	HLS₁₉-Q12	174.13 (54), .000	.039	6 (-.18 – .14)	.057 (.044-.070)	.963/.955
	HLS₁₉-SF12	211.74 (54), .000	.052	9 (-.17 – .17)	.078 (.066-.090)	.926/.909
	HLS₁₉-Q12-NO	174.42 (54), .000	.042	5 (-.20 – .14)	.061 (.048-.074)	.958/.948
three-factor: HC,DP,HP	HLS₁₉-YP12	115.20 (51), .000	.028	1 (-.13)	.034 (.015-.049)	.989/.986
	HLS₁₉-Q12	163.64 (51), .000	.037	3 (-.15 – .12)	.054 (.040-.067)	.969/.959
	HLS₁₉-SF12	188.16 (51), .000	.047	10 (-.14 – .13)	.072 (.060-.085)	.940/.922
	HLS₁₉-Q12-NO	164.96 (51), .000	.039	5 (-.18 – .12)	.057 (.044-.070)	.965/.955

\({\chi }_{M}^{2}\): model chi-square, called either minimum fit function chi-square or likelihood ratio chi-square, was estimated using WLS estimator. If the fit of an over-identified model SRMR (Standardized Root Mean Square Residual or standardized difference between observed and model-implied data): values ≤ .050 is good and ≤ .080 is sufficient. SRMR is used as index for approximate fit if model Chi-square is significant; \(No.{r}_{res}\): number of residuals with a value > .10; (> .10) = highest value > .10; RMSEA (Root Mean Square Error of Approximation): values ≤ .06 indicate good model fit; CFI (Comparative Fit Index) and TLI (Tucker-Lewis index): values ≥ .95 are generally used as an indicator of acceptable model fit
HC Health Care, DP Disease Prevention, HP Health Promotion

ISSN: 1472-6963