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Appropriate parental health literacy (HL) is essential to preventively maintain and promote child health. Understanding health information is assumed to be fundamental in HL models. We developed N = 67 items (multiple-choice format) based on information materials on early childhood allergy prevention (ECAP) and prevention of COVID-19 infections to assess the parental HL facet Understand. N = 343 pregnant women and mothers of infants completed the items in an online assessment. Using exploratory factor analysis for ordinal data (RML estimation) and item response models (1-pl and 2-pl model), we proved the psychometric homogeneity of the item pool. 57 items assess the latent dimension Understand according to the assumptions of the 1-pl model (weighted MNSQ < 1.2; separation reliability = .855). Person parameters of the latent trait Understand correlate specifically with subjective socioeconomic status (r = .27), school graduation (r = .46), allergy status (r = .11), and already infected with COVID-19 (r = .12). The calibrated item pool provides a psychometrically sound, constructvalid assessment of the HL facet Understand Health Information in the areas of ECAP and prevention of COVID-19 infections.
The COVID-19 pandemic has posed significant challenges to (expectant) mothers of infants in terms of family health protection. To meet these challenges in a health literate manner, COVID-19 protective measures must be considered important and must also be implemented appropriately in everyday life. To this end, N = 343 (expectant) mothers of infants indicated (a) how important they considered 21 COVID-19 infection prevention measures, and (b) how well they succeeded in implementing them in their daily life (20 measures). We performed data analysis using exploratory factor analysis for ordinal data and latent class analysis. One- and two-dimensional models (CFI = .960 / .978; SRMR = .053 / .039) proved to appropriately explain maternal importance ratings. The items on successfully applying COVID-19 measures in daily life can be modeled by the 5 factors hygiene measures, contact with other people, public transportation, staying at home, and checking infection status (CFI = 0.977; SRMR = .036). Six latent classes can be distinguished. Despite the largest class (39 %), classes are characterized by selective or general applicability problems. Classes reporting problems in the applicability of the measures rated them as generally less important (η = .582). Assessing and modelling importance and applicability of COVID-19 prevention measures allows for a psychometrically sound description of subjective perceptions and behaviors that are crucial for health literate practice in maternal daily life.