Providing research results to study participants: support versus practice of researchers presenting at the American Society of Hematology annual meeting
Bibliographic record
Abstract
Offering to provide research results to study participants is gaining increasing support based, in part, on the principle of respect for persons. The frequency and means of this practice is unknown in national and international research communities. All investigators who presented oral abstracts involving human research at the American Society of Hematology Annual Meeting (December 2003) were surveyed. Responses were received from 197 (42%) of 472 eligible investigators. Nonrespondents did not differ in study type or country of origin. Only 30% (n = 48) of those who completed the survey had a formal plan for the return of research results; 40% of these would return both a summary plus individual level results. Of the respondents, 69% (n = 109) supported or strongly supported the practice; only 3% opposed the practice. The most commonly cited reasons for not returning results were: did not consider it (38%), anticipated contact difficulties (32%), and participant difficulty understanding results (26%). Only 11 (7%) indicated that their institutional review board (IRB) mandates the offer to provide results to all participants; this did not vary significantly by country. Given the high level of support in the international research community, evaluation of well-planned interventions for offering to provide research results to participants should be a priority.
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 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 | 0.107 | 0.398 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".