Assessment of the Importance of COVID-19 Prevention Measures and Their Applicability in the Daily Life of Pregnant Women and Mothers of Infants: Ordinal Factor Analysis and Latent Class Analysis

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 (? = .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. © 2023 Hogrefe Verlag GmbH & Co. KG. All rights reserved.

Use of Item Response Models in Assessing the Health Literacy Facet Understanding Health Information for Early Childhood Allergy Prevention and Prevention of COVID-19 Infections by Pregnant Women and Mothers of Infants

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, construct-valid assessment of the HL facet Understand Health Information in the areas of ECAP and prevention of COVID-19 infections.

Structural Analysis of the Health Literacy Facet Access to Information on General Health, COVID-19 Infection Prevention, and Early Childhood Allergy Prevention in Pregnant Women and Mothers of Infants

The health literacy (HL) facet Access to health information is measured in the European Health Literacy Survey (HLS-EU-047) by 12 items. To assess Access, we developed adapted item formulations for COVID-19 infection prevention (COVID-19-IP) and early childhood allergy prevention (ECAP) in addition to the original 12 items on General Health (GH). N = 343 (expectant) mothers of infants answered the items in an online assessment. Confirmatory structural analyses for ordinal data were adopted (WLSMV-algorithm). Women's item ratings varied significantly across domains (eta(2) = .017-.552). Bi-factor models exhibited the best data fit (GH /COVID-19-IP/ECAP: CFI = .964/.968/.977;SRMR: .062/.069 /.035): The general factor Access most strongly determined item information. Additionally, three subfactors contributed significantly (but rather weakly) to the item information in each domain. The overall score Access proved to be internally consistent (McDonald's omega(GH/COVID-19-IP/ECAP )= .874 /.883 / .897) and was associated with socioeconomic state (McArthur scale;r(GH/COVID-19-IP-ECAP) = .218/.210/.146). Access correlated not or only weakly with the other HL facets Understand. Appraise. and Apply. The health domains GH/COVID-19-IP, and ECAP moderated both the difficulty and the dimensional structure of the 12 Access items. This suggests that in the HLS-EU Access reflects not only the search competence but also the availability of health information.