Bibliographic record
Abstract
Abstract This chapter discusses the important role that informed consent plays in healthcare and medical research involving genetic testing. The requirement of informed consent for treatment and research poses additional difficulties for certain populations. The ethical challenges posed by the informed consent process for newborns, children, adolescents and incompetent adults are each addressed separately. This chapter also highlights two recent developments that have implications for informed consent: next‐generation genetic sequencing technologies and biobanking. These developments increase uncertainty over the predictive value of genetic test results. They also raise ethical concerns about the disclosure of the results of genetic tests to individuals and families, and the storage and future use of samples and data. In order to protect the interests of patients and research participants, these issues need to be addressed in the informed consent process. Key Concepts: Informed consent must be obtained before medical treatment or participation in medical research. Parental consent is generally required for research involving children and adolescents. Parental consent must be exercised in the best interests of the child or adolescent. In some circumstances, adolescents may be authorised to consent themselves for medical care or research. Whenever possible, assent from the child should be obtained according to his or her level of development and capacities. Research involving children and adolescents should present no more than minimal risk, unless there is a prospect of direct benefit. Explicit parental consent is not required for newborn screening since it is traditionally justified by the right of the child to receive the potential health benefits from screening. The storage of newborn bloodspots has increased the demand that newborn screening samples be made available for research. Biobanking involving children or newborn bloodspots has the potential to generate new medical knowledge but poses ethical challenges. The volume of data produced by next‐generation sequencing poses new challenges for informed consent, especially because of the possibility of discovery of incidental findings. The return of results in paediatric genetic studies raises complex issues for the use of next‐generation sequencing where incidental findings are revealed. Genetic research and diagnostic testing can also pose challenges for competent adults given the familial nature of genetic information. Research on incompetent adults is now allowed if it provides at least an indirect benefit to the related population, but few guidelines exist to allow legal representatives to make decisions about such participation. Biobanking involves the storage of biological samples, often for future research of an uncertain nature. Broad consent has been used to address this issue. Re‐consent of participants may be necessary if the research framework changes.
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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 | 0.131 | 0.225 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.041 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.025 | 0.026 |
| Insufficient payload (model declined to judge) | 0.025 | 0.010 |
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".