MétaCan
Menu
Back to cohort
Record W2136927539 · doi:10.1186/1472-6939-4-2

The unique ethical challenges of conducting research in the rehabilitation medicine population

2003· article· en· W2136927539 on OpenAlexaff
Jeff Blackmer

Bibliographic record

VenueBMC Medical Ethics · 2003
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPhilosophy of medicineHarmSubject (documents)Engineering ethicsPopulationHealth careRehabilitationEthical issuesMedicineInformed consentAlternative medicinePsychologyPolitical scienceLawSocial psychologyPhysical therapyEngineeringPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The broad topic of research ethics is one which has been relatively well-investigated and discussed. Unique ethical issues have been identified for such populations as pediatrics, where the issues of consent and assent have received much attention, and obstetrics, with concerns such as the potential for research to cause harm to the fetus. However, little has been written about ethical concerns which are relatively unique to the population of patients seen by the practitioner of rehabilitation medicine. DISCUSSION: This paper reviews unique ethical concerns in conducting research in this population, including decision-making capacity, communication, the potential for subject overuse, the timing of recruitment, hope for a cure and therapeutic misconception and the nature of the health care provider-research subject relationship. SUMMARY: Researchers in the area of rehabilitation medicine should be aware of some of the unique ethical challenges posed by this patient population and should take steps to address any potential concerns in order to optimize subject safety and ensure that studies meet current ethical guidelines and standards.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.334
metaresearch head score (Gemma)0.927
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.3340.927
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.030
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.875
GPT teacher head0.698
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations26
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueBMC Medical EthicsSame topicEthics in Clinical ResearchFrench-language works237,207