Does Receiving Information on Clinical Trials Affect Patients’ Condition?
Bibliographic record
Abstract
Background: When performing clinical trials on lifestyle-related diseases at our hospital, we have sometimes experienced patients who fulfilled the inclusion criteria at the time of receiving an explanation of the trial but who no longer met the criteria when they arrived to provide their consent to participate 1 month later. In some of these cases, we noticed that the patient's lifestyle subsequently improved. Therefore, we hypothesized that receiving information on clinical trials may affect lifestyle-related diseases. Methods: We enrolled patients aged 85 years or younger who received information on a double-blind randomized clinical trial on treatment-resistant hypertension (R-HT) or one on diabetic nephropathy. In these patients, we evaluated whether the trial information affected a range of variables. In addition, we compared the rate of change in variables between two groups, i.e., patients who became ineligible to participate and were not randomized (early dropouts) and patients who decided to participate and were randomized (patients randomized to treatment). We also conducted a questionnaire on changes in patients' motivation level, health awareness and behavior, and expectations and concerns and evaluated changes from before to after receiving an explanation of the trial. Results: Seven patients who received an explanation of the R-HT trial and 14 who received an explanation of the diabetic nephropathy trial participated in the present study. The only significant change in any variable was in the R-HT clinical trial, where systolic and diastolic blood pressure significantly decreased in the early dropout group. There were no significant differences between the two groups in the rate of change in variables. After receiving information about one of the studies, patients who became more proactive or involved in changing their health-related behavior, such as their exercise, eating, and drinking habits, increased in both groups. Conclusions: Receiving information on a clinical trial on hypertension can significantly affect blood pressure. Future research should examine whether providing information on clinical trials on other lifestyle-related diseases motivates patients to improve their lifestyles.
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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 | 0.015 | 0.128 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".