Hanne Søberg Finbråten|Bodil Wilde?Larsson|Gun Nordström|Kjell Sverre Pettersen|Anne Trollvik|Øystein Guttersrud
Establishing the HLS-Q12 short version of the European Health Literacy Survey Questionnaire: latent trait analyses applying Rasch modelling and confirmatory factor analysis
Inland Norway University of Applied Sciences|Karlstad University|Inland Norway University of Applied Sciences|OsloMet – Oslo Metropolitan University|Inland Norway University of Applied Sciences|University of Oslo
european health literacy survey questionnaire hlseuq47 widely used assessing health literacy hl controversy whether comprehensive hlseuq47 data reflecting conceptual model four cognitive domains across three health domains ie 12 subscales fit unidimensional rasch models still hlseuq47 raw score commonly interpreted sufficient statistic combining rasch modelling confirmatory factor analysis reduced 47 item scale parsimonious 12 item scale meets assumptions requirements objective measurement offering clinically feasible hl screening tool paper aims 1 evaluating psychometric properties hlseuq47 associated short versions large norwegian sample 2 establishing short version hlsq12 sufficient psychometric properties using computerassisted telephone interviews november 2014 data collected 900 randomly sampled individuals aged 16 data analysed using partial credit parameterization unidimensional polytomous rasch model prm betweenitem multidimensional prm using onefactorial multifactorial confirmatory factor analysis cfa categorical variables using likelihoodratio tests compare datamodel fit nested models found observed hlseuq47 data likely 12dimensional rasch model three onedimensional rasch model several 12 theoretically defined subscales suffered low reliability owing items excluding poorly discriminating items items displaying differential item functioning redundant items violating assumption local independency parsimonious 12item hlsq12 scale suggested hlsq12 displayed acceptable fit unidimensional rasch model achieved acceptable goodnessoffit indexes using cfa unlike hlseuq47 data parsimonious 12item version hlsq12 meets assumptions requirements objective measurement offering clinically feasible screening without applying advanced psychometric methods site avoid invalid measures hl using hlseuq47 suggest using hlsq12 valid measures particularly important studies aiming explain variance latent trait hl explore relation hl health outcomes purpose informing policy makers