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The health literacy (HL) facet Access to health information is measured in the European Health Literacy Survey (HLS-EU-Q47) 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 (η2 = .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 ωGH/COVID-19-IP/ECAP = .874/.883 /.897) and was associated with socioeconomic state (McArthur scale; rGH/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.
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.
Ziel der Studie: Die Strategie Aktiv Altern der Weltgesundheitsorganisation (WHO) umfasst die Bereiche Gesundheit, Teilhabe am sozialen Leben sowie Sicherheit im Alter. Als politischer Aktionsrahmen unterstützt die Strategie die zukünftige Alterspolitik der Kommunen. Wie kommunale Akteurinnen und Akteure selbst die WHO-Strategie beurteilen, ist Gegenstand dieser Befragung.
Methodik: Wir haben fünf Expertinnen und Experten aus dem Landkreis Konstanz mittels systematisierenden, leitfadengestützten Interviews befragt. Grundlage des Leitfadens bildete eine selbst konzipierte Indikatorenliste, die die 102 Handlungsempfehlungen strukturiert bündelt. Die Bekanntheit der WHO-Strategie und eine gegebenenfalls kurze Einführung in die drei Bereiche bildeten den Intervieweinstieg, anschließend erfolgte der Abgleich kommunaler Aktivitäten mit der Indikatorenliste, die Erhebung des kommunalen Handlungsbedarfes sowie die Identifikation bislang unberücksichtigter Aspekte. Im Sinne einer Triangulation führten wir eine quantitative Befragung in weiteren Landkreisen durch. Die Auswertung erfolgte mittels qualitativer Inhaltsanalyse nach Gläser und Laudel mit dem Extraktionsprogramm MIA.
Ergebnisse: Keine der interviewten Personen kannte die WHO-Strategie Aktiv Altern. Nach einer kurzen Erläuterung zur WHO-Strategie und Indikatorenliste, stuften die Interviewpersonen die Strategie jedoch als praktikabel ein. Als gut umsetzbar schätzten sie vor allem Handlungsempfehlungen aus den Teilbereichen Teilhabe in der Gesellschaft (z.B. Schaffung von Seniorenbeiräten), sowie aus dem Bereich Sicherheit im öffentlichen Raum und Verkehr (z.B. Schutzmaßnahmen für ältere Fußgänger/innen) ein. In einzelnen Bereichen, wie der medizinischen Versorgung und der formellen Pflege, vermissten die Interviewpersonen Indikatoren, so dass wir die Neuaufnahme zusätzlicher Handlungsempfehlungen empfehlen.
Schlussfolgerung: Die Bekanntheit der WHO-Strategie Aktiv Altern sollte in Richtung der Kommunen, der eigentlichen Zielgruppe, verbessert werden. Aktiv Altern ist, unter Berücksichtigung des hier festgestellten Weiterentwicklungsbedarfes, eine praktikable Orientierungshilfe und bietet mehrere Chancen für die Alterspolitik im kommunalen Feld.
Background
The SF-8 is a short form of the SF-36 Health Survey, which is used for generic assessment of physical and mental aspects of health-related quality of life (HRQoL). Each of the 8 dimensions of the SF-36 is covered by a single item in the SF-8. The aim of the study was to examine the latent model structure of the SF-8.
Method
One-, two- and three dimensional as well as bi-factor structural models were defined and estimated adopting the ML- as well as the WLSMV-algorithm for ordinal data. The data were collected in a German general population sample (N = 2545 persons).
Results
A two- (physical and mental health) and a three-dimensional CFA structure (in addition overall health) represent the empirical data information adequately [CFI = .987/.995; SRMR = .024/.014]. If a general factor is added, the resulting bi-factor models provide a further improvement in data fit [CFI = .999/.998; SRMR = .001]. The individual items are much more highly associated with the general HRQoL factor (loadings: .698 to .908) than with the factors physical, mental, and overall health (loadings: −.206 to .566).
Conclusions
In the SF-8, each item reflects mainly general HRQoL (general factor) as well as one of the three components physical, mental, and overall health. The findings suggest in particular that the evaluation of the information of the SF-8 items can be validly supplemented by a general value HRQoL.
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.