Using the Internet to Seek Information About Genetic and Rare Diseases: A Case Study Comparing Data From 2006 and 2011
Bibliographic record
Abstract
BACKGROUND: The Genetic and Rare Disease Information Center (GARD) is a major provider of Web-based information on genetic and rare diseases. Little is known about the type of Web-based information individuals seek about genetic and rare diseases or their reasons for seeking. OBJECTIVE: The objective of this paper is to describe the types of Web-based information sought about genetic and rare diseases and the reasons for seeking it from GARD by examining inquiries from 2006 and 2011. METHODS: There were 278 English-language email and Web-based inquiries posed to GARD by lay individuals (ie, patients, parents, and relatives), which were randomly selected from inquiries in 2006 (n=68) and 2011 (n=210) and examined using content analysis. RESULTS: Most often in both years, individuals sought basic disease information (51/68, 75.0% and 132/210, 62.8%; P=.067) and information about treatment (17/51, 33.3% and 62/132, 47.0%; P=.095). Specifically, inquirers requested information about their disease prognosis (6/51, 11.8% and 23/132, 17.4%; P=.347) and made requests for specialists (8/68, 11.8% and 31/210, 14.8%; P=.536). In both 2006 and 2011, a substantial subset of inquirers requested information related to undiagnosed symptoms, representing 16.2% (11/68) and 11.9% (25/210; P=.362) of inquiries, respectively. Inquirers were significantly more likely to have seen a health care provider before contacting GARD (99/210, 47.1% vs 20/68, 29.4%; P=.010) and to ask about clinical research studies in 2011 than in 2006 (24/210, 11.4% vs 2/68, 2.9%; P=.037). In the 2011 data set, the majority of the inquirers were women (201/210, 95.7%). In our 2006 sample, men were the majority source of inquiries (54/68, 79.4%). CONCLUSIONS: Findings from this study indicate that lay people contacting a genetic and rare disease information center most often seek information about disease prognosis, finding a specialist, and obtaining a diagnosis for symptoms. Unique characteristics of individuals searching the Internet for genetic and rare diseases information, includes a growing interest in participating in clinical research studies and a desire to supplement or better understand information discussed during a visit with a health care provider. These efforts represent advancements in patient self-advocacy.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".