Patients' consent preferences regarding the use of their health information for research purposes: a qualitative study
Bibliographic record
Abstract
OBJECTIVE: To explore the consent preferences of patients whose health data are currently being used for research purposes. METHODS: Semi-structured interviews were conducted with 17 patients whose primary physicians were taking part in a study that utilized de-identified individual-level health information from their electronic medical record. All physicians practised in southwestern Ontario. All interviews were taped, transcribed verbatim and analysed using a constant comparative method. All transcripts and debriefing notes were read and reread to elicit general themes. RESULTS: Three main themes emerged from the data: patients recognized the need to balance their consent preferences with time pressures in the clinical encounter when deciding the nature of consent for a study; patients generally regarded the seeking of consent as being an issue of respect for them as individuals; and patients were also weighing their perceived benefits and concerns related to the research. For these patients, seeking their consent was an important step in research participation. For some patients, the sponsor and the research topic were factors that would influence their decision to provide consent. CONCLUSION: Patients want their consent to be sought when their data are used for research purposes. This will involve explicitly informing patients that a study is taking place, providing written consent and offering regular updates about the study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.106 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".