Evidence map›Paper›PMID 36763573›Full record

ArticlePloS one2023

Readability and topics of the German Health Web: Exploratory study and text analysis.

Richard Zowalla, Daniel Pfeifer, Thomas Wetter

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Richard ZowallaDepartment of Medical Informatics, Heilbronn University, Heilbronn, Germany.ORCID 0000-0003-1236-7398
Daniel PfeiferDepartment of Medical Informatics, Heilbronn University, Heilbronn, Germany.
Thomas WetterInstitute of Medical Informatics, Heidelberg University Hospital, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe internet has become an increasingly important resource for health information, especially for lay people. However, the information found does not necessarily comply with the user's health literacy level. Therefore, it is vital to (1) identify prominent information providers, (2) quantify the readability of written health information, and (3) to analyze how different types of information sources are suited for people with differing health literacy levels.

objectiveIn previous work, we showed the use of a focused crawler to "capture" and describe a large sample of the "German Health Web", which we call the "Sampled German Health Web" (sGHW). It includes health-related web content of the three mostly German speaking countries Germany, Austria, and Switzerland, i.e. country-code top-level domains (ccTLDs) ".de", ".at" and ".ch". Based on the crawled data, we now provide a fully automated readability and vocabulary analysis of a subsample of the sGHW, an analysis of the sGHW's graph structure covering its size, its content providers and a ratio of public to private stakeholders. In addition, we apply Latent Dirichlet Allocation (LDA) to identify topics and themes within the sGHW.

methodsImportant web sites were identified by applying PageRank on the sGHW's graph representation. LDA was used to discover topics within the top-ranked web sites. Next, a computer-based readability and vocabulary analysis was performed on each health-related web page. Flesch Reading Ease (FRE) and the 4th Vienna formula (WSTF) were used to assess the readability. Vocabulary was assessed by a specifically trained Support Vector Machine classifier.

resultsIn total, n = 14,193,743 health-related web pages were collected during the study period of 370 days. The resulting host-aggregated web graph comprises 231,733 nodes connected via 429,530 edges (network diameter = 25; average path length = 6.804; average degree = 1.854; modularity = 0.723). Among 3000 top-ranked pages (1000 per ccTLD according to PageRank), 18.50%(555/3000) belong to web sites from governmental or public institutions, 18.03% (541/3000) from nonprofit organizations, 54.03% (1621/3000) from private organizations, 4.07% (122/3000) from news agencies, 3.87% (116/3000) from pharmaceutical companies, 0.90% (27/3000) from private bloggers, and 0.60% (18/3000) are from others. LDA identified 50 topics, which we grouped into 11 themes: "Research & Science", "Illness & Injury", "The State", "Healthcare structures", "Diet & Food", "Medical Specialities", "Economy", "Food production", "Health communication", "Family" and "Other". The most prevalent themes were "Research & Science" and "Illness & Injury" accounting for 21.04% and 17.92% of all topics across all ccTLDs and provider types, respectively. Our readability analysis reveals that the majority of the collected web sites is structurally difficult or very difficult to read: 84.63% (2539/3000) scored a WSTF ≥ 12, 89.70% (2691/3000) scored a FRE ≤ 49. Moreover, our vocabulary analysis shows that 44.00% (1320/3000) web sites use vocabulary that is well suited for a lay audience.

conclusionsWe were able to identify major information hubs as well as topics and themes within the sGHW. Results indicate that the readability within the sGHW is low. As a consequence, patients may face barriers, even though the vocabulary used seems appropriate from a medical perspective. In future work, the authors intend to extend their analyses to identify trustworthy health information web sites.

Indexed as

Health LiteracyMedicineComprehensionHealth FacilitiesHumansInternetReading

Identifiers

PMID36763573
PMCPMC9916670

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.