Ethical considerations for engaging frail and seriously ill patients as partners in research: sub-analysis of a systematic review
Bibliographic record
Abstract
BACKGROUND: The commitment to engage patients as partners in research has been described as a political, moral and ethical imperative. Researchers feel ill-equipped to deal with potential ethical implications of engaging patients as partners. The aim of this study is to identify the ethical considerations related to engaging frail and seriously ill (FSI) patients as partners in research. METHODS: We conducted a sub-analysis of a prior systematic review of 30 studies that engaged FSI patients as partners in research. Studies were included if they reported ethical considerations associated with partnering. We performed deductive content analysis, data were categorized according to Beauchamp and Childress' Principles of Biomedical Ethics (2019): autonomy, non-maleficence, beneficence, and justice. RESULTS: Twenty-five studies were included. Common ethical considerations reported in relation to the principles were: autonomy - promoting desired level of involvement, addressing relational and intellectual power, facilitating knowledge and understanding of research; non-maleficence - protection from financial burden, physical and emotional suffering; beneficence - putting things right for others, showing value-added, and supporting patient-partners; and, justice - achieving appropriate representation, mutual respect for contributions, and distributing risks and benefits. CONCLUSIONS: When partnering with FSI patients, research teams need to establish shared values and ensure processes are in place to identify and address ethical issues. Researchers and patients should work together to clarify the intent and outcomes of the partnership, actively address power differentials, recognize and minimize the potential for unintended harm, and strive to maximize the benefits of partnership. SYSTEMATIC REVIEW REGISTRATION: The protocol for the original systematic review has been registered with the International Prospective Register of Systematic Reviews PROSPERO (CRD42019127994).
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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 | 0.062 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".