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Record W2137883967 · doi:10.1177/0193945904270917

Clinical Trials With Complementary Therapies

2005· article· en· W2137883967 on OpenAlexaff
Kathleen Oberle, Marion Allen

Bibliographic record

VenueWestern Journal of Nursing Research · 2005
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsClinical trialAlternative medicineMedicineNursingPathology

Abstract

fetched live from OpenAlex

As interest in complementary and alternative therapies grows, nurses can expect to be asked for advice regarding their use, but there are few clinical studies on which nurses can base their responses. Conducting research with complementary therapies is therefore important for nursing, but there are some pitfalls in doing research with these products, particularly if one is using standard clinical-trials methods. In this article, the authors outline some of those pitfalls based on their experience conducting a clinical trial to examine the effects of elk velvet antler on symptoms of rheumatoid arthritis. They discuss design issues related to justification, method, and ethics and explore some important regulatory issues of which nurses should be aware. Some recommendations are presented to help nurses engaging in such research to avoid problems that could interfere with the smooth conduct of their studies.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.652
GPT teacher head0.652
Teacher spread0.000 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2005
Admission routes1
Has abstractyes

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