Quality of Patient Information Websites About Congenital Heart Defects: Mixed-Methods Study of Perspectives Among Individuals With Experience of a Prenatal Diagnosis
Bibliographic record
Abstract
BACKGROUND: When a heart defect is prenatally diagnosed in the fetus, expectant parents experience a great need for information about various topics. After the diagnosis, the Web is used for supplemental information, and the scarcity of research calls attention to the need to explore patient information websites from the perspectives of the intended consumers. OBJECTIVE: The overarching aim of this study was to explore the quality of Swedish patient information websites about congenital heart defects, from the perspectives of individuals with experience of a prenatal diagnosis of congenital heart defect in the fetus. METHODS: This was a mixed-methods study of websites identified through systematic searches in the two most used Web-based search engines. Of the total 80 screened hits, 10 hits led to patient information websites about congenital heart defects. A quality assessment tool inspired by a previous study was used to evaluate each website's appearance, details, relevance, suitability, information about treatment choices, and overall quality. Answers were given on a 5-point Likert scale, ranging from 1, representing the lowest score, to 5, representing the highest score. Each website was assessed individually by persons with experience of continued (n=4) and terminated (n=5) pregnancy following a prenatal diagnosis. Assessments were analyzed with Kendall's coefficient of concordance W, Mann-Whitney U test, Friedman's test, and a Wilcoxon-Nemenyi-McDonald-Thompson test. In addition, each assessor submitted written responses to open-ended questions in the quality assessment tool, and two joint focus group discussions were conducted with each group of assessors. The qualitative data were analyzed with inductive manifest content analysis. RESULTS: Assessments represented a low score (median=2.0) for treatment choices and moderate scores (median=3.0) for appearance, details, relevance, suitability, and overall quality. No website had a median of the highest achievable score for any of the questions in the quality assessment tool. Medians of the lowest achievable score were found in questions about treatment choices (n=4 websites), details (n=2 websites), suitability (n=1 website), and overall quality (n=1 website). Websites had significantly different scores for appearance (P=.01), details (P<.001), relevance (P<.001), suitability (P<.001), treatment choices (P=.04), and overall quality (P<.001). The content analysis of the qualitative data generated six categories: (1) advertisements, (2) comprehensiveness, (3) design, (4) illustrations and pictures, (5) language, and (6) trustworthiness. Various issues with the included websites were highlighted, including the use of inappropriate advertisements, biased information, poor illustrations, complex language, and poor trustworthiness. CONCLUSIONS: From the perspectives of the intended consumers, patient information websites about congenital heart defects are, to a large extent, inadequate tools for supplemental information following a prenatal diagnosis. Health professionals should initiate discussions with patients about their intentions to use the Web, inform them about the varied quality in the Web-based landscape, and offer recommendations for appropriate Web-based sources.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".