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Record W2002415352 · doi:10.1017/s1041610203008834

Why Participate in an Alzheimer’s Disease Clinical Trial? Is It of Benefit to Carers and Patients?

2003· article· en· W2002415352 on OpenAlexaff
Maree Mastwyk, Stephen Macfarlane, Dina LoGiudice, Karen A. Sullivan

Bibliographic record

VenueInternational Psychogeriatrics · 2003
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsClinical trialMedicineRandomized controlled trialDiseaseFamily medicine

Abstract

fetched live from OpenAlex

BACKGROUND: We explored carer motivation for seeking participation for a relative in an Alzheimer's disease (AD) clinical drug trial, to assess impressions of the value of trial participation. We also surveyed the carers of patients who did not meet study entry screening criteria to see if our conduct of the screening visit was acceptable and ethical. METHOD: A retrospective questionnaire was sent to the carers of 36 randomized participants and 22 carers of patients who did not meet study entry screening criteria for an AD clinical treatment trial. RESULTS: Twenty-nine (81%) of the trial participant carers and 15 (68%) of carers of the group who did not meet study entry criteria returned their questionnaires with sufficient information for analysis. The prime motivators in seeking trial participation were to help their relative feel better and live longer, to contribute to medical science, to improve the health of others, and the hope of a cure. Carers of both groups found research staff supportive and would recommend trial participation to others. CONCLUSIONS: Even though trial participation is onerous and patients were generally perceived by carers as not having improved, both the screening visit and participation in the trial itself were seen as positive experiences and the expectations of carers were met.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.028
metaresearch head score (Gemma)0.122
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.122
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.107
GPT teacher head0.462
Teacher spread0.355 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations19
Published2003
Admission routes1
Has abstractyes

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