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Record W4415352654 · doi:10.2196/78007

Mapping the Quality of German-Language Health Information on the Treatment of Knee Osteoarthritis: Cross-Sectional Analysis

2025· article· en· W4415352654 on OpenAlexvenueno aff
Sandro Zacher, Jürgen Kasper, Julia Lauberger, Julia Lühnen, Lisa-Marie Redlich, Anke Steckelberg

Bibliographic record

VenueJMIR Infodemiology · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsQuality (philosophy)CertificationChecklistInformation qualityAffect (linguistics)Presentation (obstetrics)Public health

Abstract

fetched live from OpenAlex

BACKGROUND: Patients with knee osteoarthritis have a considerable need for information about their condition, its progression, and available treatments. Decision-making is often complex and requires evidence-based health information material (HIM). When medical consultations do not sufficiently address patients' needs, many seek additional information independently. OBJECTIVE: This study aimed to examine the quality of German-language HIM on knee osteoarthritis treatment and its suitability for supporting informed choice. In particular, the study analyzed the content of the HIM and assessed the balance in the presentation of treatment options. METHODS: A descriptive cross-sectional study was conducted. HIM was identified through a combination of search strategies, including a systematic internet search using commonly used German terms related to the treatment of knee osteoarthritis. Identified HIMs were independently assessed by 2 raters using the validated Mapping the Quality of Health Information (MAPPinfo) checklist, which operationalizes the criteria of the Guideline Evidence-Based Health Information. Information quality was calculated on a scale from 0% to 100%, representing compliance with the quality standard. A descriptive content analysis was also carried out to examine the range and balance of treatment options presented, as well as the reporting of benefits and complications associated with total knee arthroplasty (TKA). The presence of certification was recorded. RESULTS: A total of 94 HIMs were included. On average, the material met 14.6% (SD 9.4%) of the quality criteria. HIM from public and nonprofit providers performed better (mean 40.1%, SD 3.6% and mean 37.2%, SD 23.1%, respectively) than those from other providers. Overall, 14 HIMs presented treatment options in a balanced manner. Among the 78 HIMs that covered TKA, 38.5% (n=30) did not report any benefits, and 35.9% (n=28) omitted potential complications. Certified HIMs showed only moderately higher information quality than uncertified material (mean 26.8%, SD 16% vs mean 12.7%, SD 5.9%). CONCLUSIONS: Our results highlight the urgent need to improve the quality of German-language HIM on knee osteoarthritis. The deficits identified are fundamental and affect all dimensions of information quality. Although HIM from public or nonprofit organizations has better information quality, this does not facilitate informed choice. The frequent omission of complications and benefits of TKA and the unbalanced presentation of treatment options can influence decisions. Until structural improvements are made, patients seeking quality information should favor material from public or nonprofit providers. Additionally, the MAPPinfo checklist could form the basis of a differentiated certification system to make information quality more transparent for patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.106
GPT teacher head0.533
Teacher spread0.427 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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