Psychometric properties of a COVID-19 health literacy scale in a sample of German school principals applying Rasch analysis

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Abstract

Background

During the COVID-19 pandemic, health literacy was found to be an asset to manage health-related information. The HLS-COVID-Q22 has been developed to measure COVID-19 health literacy. External validation needs to be assessed in different populations to verify the questionnaire’s functioning. The present study aimed to evaluate the psychometric properties of the HLS-COVID-Q22 in a sample of German school principals.

Methods

The sample consisted of 2187 German school principals who completed the HLS-COVID-Q22 online from April to March 2021. The data was analyzed using Rasch analysis, applying the Partial Credit Model for polytomous data. Dimensionality, item fit statistics and rating scale functioning was tested. Values for item difficulty and person ability as well as reliability indices were computed.

Results

Unidimensionality could be confirmed. The rating scale categories worked as intended, participants used every rating step category. Generally, item fit was verified. One item showed potential misfit but could remain in the questionnaire as excluding the item did not reduce reliability. A person separation index of 3.41 and person reliability of 0.92 showed excellent differentiation between COVID-19 health literacy levels. Furthermore, the values for item separation of 20.08 and item reliability of 1.0 indicate good construct validity.

Conclusions

The German version of the HLS-COVID-Q22 appears to be a reliable measurement tool for the target population. Evidence for construct, statistical and fit validity was collected. Future studies need to test additional types of validity like convergent and divergent validity to further evaluate the questionnaire. Moreover, the psychometric properties of the translated versions of the HLS-COVID-Q22 should be compared using Rasch analysis.

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Health literacy and public health: A systematic review and integration of definitions and models

Karen Kristine Sørensen, Stephan Van den Broucke, James Fullam … (2012)

Background Health literacy concerns the knowledge and competences of persons to meet the complex demands of health in modern society. Although its importance is increasingly recognised, there is no consensus about the definition of health literacy or about its conceptual dimensions, which limits the possibilities for measurement and comparison. The aim of the study is to review definitions and models on health literacy to develop an integrated definition and conceptual model capturing the most comprehensive evidence-based dimensions of health literacy. Methods A systematic literature review was performed to identify definitions and conceptual frameworks of health literacy. A content analysis of the definitions and conceptual frameworks was carried out to identify the central dimensions of health literacy and develop an integrated model. Results The review resulted in 17 definitions of health literacy and 12 conceptual models. Based on the content analysis, an integrative conceptual model was developed containing 12 dimensions referring to the knowledge, motivation and competencies of accessing, understanding, appraising and applying health-related information within the healthcare, disease prevention and health promotion setting, respectively. Conclusions Based upon this review, a model is proposed integrating medical and public health views of health literacy. The model can serve as a basis for developing health literacy enhancing interventions and provide a conceptual basis for the development and validation of measurement tools, capturing the different dimensions of health literacy within the healthcare, disease prevention and health promotion settings.

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How to fight an infodemic

John Zarocostas (2020)

WHO's newly launched platform aims to combat misinformation around COVID-19. John Zarocostas reports from Geneva. WHO is leading the effort to slow the spread of the 2019 coronavirus disease (COVID-19) outbreak. But a global epidemic of misinformation—spreading rapidly through social media platforms and other outlets—poses a serious problem for public health. “We’re not just fighting an epidemic; we’re fighting an infodemic”, said WHO Director-General Tedros Adhanom Ghebreyesus at the Munich Security Conference on Feb 15. Immediately after COVID-19 was declared a Public Health Emergency of International Concern, WHO's risk communication team launched a new information platform called WHO Information Network for Epidemics (EPI-WIN), with the aim of using a series of amplifiers to share tailored information with specific target groups. Sylvie Briand, director of Infectious Hazards Management at WHO's Health Emergencies Programme and architect of WHO's strategy to counter the infodemic risk, told The Lancet, “We know that every outbreak will be accompanied by a kind of tsunami of information, but also within this information you always have misinformation, rumours, etc. We know that even in the Middle Ages there was this phenomenon”. “But the difference now with social media is that this phenomenon is amplified, it goes faster and further, like the viruses that travel with people and go faster and further. So it is a new challenge, and the challenge is the [timing] because you need to be faster if you want to fill the void…What is at stake during an outbreak is making sure people will do the right thing to control the disease or to mitigate its impact. So it is not only information to make sure people are informed; it is also making sure people are informed to act appropriately.” About 20 staff and some consultants are involved in WHO's communications teams globally, at any given time. This includes social media personnel at each of WHO's six regional offices, risk communications consultants, and WHO communications officers. Aleksandra Kuzmanovic, social media manager with WHO's department of communications, told The Lancet that “fighting infodemics and misinformation is a joint effort between our technical risk communications [team] and colleagues who are working on the EPI-WIN platform, where they communicate with different…professionals providing them with advice and guidelines and also receiving information”. Kuzmanovic said, “In my role, I am in touch with Facebook, Twitter, Tencent, Pinterest, TikTok, and also my colleagues in the China office who are working closely with Chinese social media platforms…So when we see some questions or rumours spreading, we write it down, we go back to our risk communications colleagues and then they help us find evidence-based answers”. “Another thing we are doing with social media platforms, and that is something we are putting our strongest efforts in, is to ensure no matter where people live….when they’re on Facebook, Twitter, or Google, when they search for ‘coronavirus’ or ‘COVID-19’ or [a] related term, they have a box that…directs them to a reliable source: either to [the] WHO website to their ministry of health or public health institute or centre for disease control”, she said. Google, Kuzmanovic noted, has created an SOS Alert on COVID-19 for the six official UN languages, and is also expanding in some other languages. The idea is to make the first information that the public receive be from the WHO website and the social media accounts of WHO and Dr Tedros. WHO also uses social media for real-time updates. WHO is also working closely with UNICEF and other international agencies that have extensive experience in risk communications, such as the International Federation of Red Cross and Red Crescent Societies. Carlos Navarro, head of Public Health Emergencies at UNICEF, the children's agency, told The Lancet that while a lot of incorrect information is spreading through social media, a lot is also coming from traditional mass media. “Often, they pick the most extreme pictures they can find…There is overkill on the use of [personal protective equipment] and that tends to be the photos that are published everywhere, in all major newspapers and TV…that is, in fact, sending the wrong message”, Navarro said. David Heymann, professor of infectious disease epidemiology at the London School of Hygiene & Tropical Medicine, told The Lancet that the traditional media has a key role in providing evidence-based information to the general public, which will then hopefully be picked up on social media. He also observed that for both social and conventional media, it is important that the public health community help the media to “better understand what they should be looking for, because the media sometimes gets ahead of the evidence”.

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When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions.

Mijke Rhemtulla, Patricia Brosseau-Liard, Victoria Savalei (2012)

A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category thresholds. Results revealed that factor loadings and robust standard errors were generally most accurately estimated using cat-LS, especially with fewer than 5 categories; however, factor correlations and model fit were assessed equally well with ML. Cat-LS was found to be more sensitive to sample size and to violations of the assumption of normality of the underlying continuous variables. Normal theory ML was found to be more sensitive to asymmetric category thresholds and was especially biased when estimating large factor loadings. Accordingly, we recommend cat-LS for data sets containing variables with fewer than 5 categories and ML when there are 5 or more categories, sample size is small, and category thresholds are approximately symmetric. With 6-7 categories, results were similar across methods for many conditions; in these cases, either method is acceptable.

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Author and article information

Contributors

Marlene Meyer: marlene.meyer@tum.de

Journal

Journal ID (nlm-ta): BMC Public Health

Journal ID (iso-abbrev): BMC Public Health

Title: BMC Public Health

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2458

Publication date (Electronic): 11 November 2024

Publication date PMC-release: 11 November 2024

Publication date Collection: 2024

Volume: 24

Electronic Location Identifier: 3118

Affiliations

[1 ]WHO Collaborating Centre for Health Literacy, TUM Health Literacy Unit, Department of Health and Sport Sciences, TUM School of Medicine and Health, Technical University of Munich, ( https://ror.org/02kkvpp62) Munich, Germany

[2 ]Public Health Centre Fulda, Fulda University of Applied Sciences, ( https://ror.org/041bz9r75) Fulda, Germany

[3 ]Centre for Applied Health Science, Leuphana University Lueneburg, ( https://ror.org/02w2y2t16) Lueneburg, Germany

[4 ]Institute of Nursing Science, University Hospital Würzburg, ( https://ror.org/03pvr2g57) Würzburg, Germany

[5 ]Department of Nursing Science, University of Würzburg, ( https://ror.org/00fbnyb24) Würzburg, Germany

Article

Publisher ID: 20648

DOI: 10.1186/s12889-024-20648-w

PMC ID: 11555876

SO-VID: 821cbf1f-60ac-4153-8491-7652c82fbf3a

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 13 June 2024

Date accepted : 6 November 2024

Funding

Funded by: Technische Universität München (1025)

Open Access :

Open Access funding enabled and organized by Projekt DEAL.

Custom metadata

ScienceOpen disciplines: Public health

Keywords: covid-19 health literacy,rasch analysis,psychometric properties,hls-covid-q22,german school principals

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ScienceOpen disciplines: Public health

Keywords: covid-19 health literacy, rasch analysis, psychometric properties, hls-covid-q22, german school principals

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Psychometric properties of a COVID-19 health literacy scale in a sample of German school principals applying Rasch analysis

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Abstract

Background

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Novel Coronavirus Disease COVID-19

Most cited references 61

Health literacy and public health: A systematic review and integration of definitions and models

How to fight an infodemic

When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions.

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