Abstract P5-12-01: ARE WEB-BASED RESOURCES THE BREAST?: AN EVALUATION OF THE QUALITY OF ONLINE RESOURCES FOR BREAST CANCER PATIENTS
Bibliographic record
Abstract
Abstract Background: Cancer patients are increasingly using the internet to seek disease specific information. Our prior studies indicate that a majority of breast cancer patients use the internet to aid decision making and to inform themselves about their disease. Although there is a substantial amount of information available on the internet regarding breast cancer, there are no comprehensive studies evaluating the quality of this information and whether it is adequate to support patients' decision making. The purpose of this study was to apply a validated evaluation tool to evaluate the quality of online breast cancer patient information. Methods: Using the principles of design-based research, an evaluation tool was developed and validated for the purposes of evaluation of web-based patient information. To review the quality of breast cancer information, a list of the top 100 breast cancer websites was systematically compiled using the meta-search engines Yippy and Dogpile, and the search engine Google. The websites were assessed for administration, accountability, authorship, organization, readability, and content. Inter-rater reliability was evaluated. Results were analyzed using descriptive statistics. Results: Over 2000 hits were initially obtained using the search term “breast cancer” (the most common search term according to our previous studies) in the three search engines. After applying the pre-specified inclusion and exclusion criteria the “top 100” breast cancer sites were evaluated. The majority of breast cancer websites were administered by commercial businesses (47%) and non-profit organizations (33%). 86% of the websites disclosed ownership, sponsorship, and/or advertising. Only 34% of websites identified the author and 39% cited sources. The average readability of websites was a grade 9 level. The majority of the information was out of date and only 27% of websites had updated their content within the last two years. While 88% of the websites sufficiently covered breast cancer, only 18% addressed prognosis. Conclusions: While a majority of breast cancer patients use the internet to obtain information on their diagnosis and treatment options, this study demonstrates that web-based information is variable and there are distressing gaps in the information available. Although the assessed websites were mostly accurate, there were significant deficits in authorship, attribution, and currency. Of concern, our research has previously demonstrated that patients use authorship and attribution to determine the reliability of web-based information. Additionally, very few websites provided information regarding prognosis, an area research has identified as an important topic sought by breast cancer patients. The results of this study can be used to counsel patients on the strengths and weaknesses of web-based breast cancer information and to empower patients to choose sites likely to enhance their personal knowledge. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P5-12-01.
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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 | 0.026 | 0.104 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.006 |
| 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) | 0.006 | 0.001 |
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".