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Record W2224093505 · doi:10.1136/medethics-2013-101899

Challenges with participant reimbursement: experiences from a post-trial access study

2015· article· en· W2224093505 on OpenAlexaff
Kathryn Mngadi, Janet Frohlich, Carl Montague, Jerome Amir Singh, Nelisiwe Nkomonde, Nomzamo Mvandaba, Fanelesibonge Ntombeka, Londiwe Luthuli, Quarraisha Abdool Karim, Leila E. Mansoor

Bibliographic record

VenueJournal of Medical Ethics · 2015
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsReimbursementAttendanceClinical trialMedicineHealth careRandomized controlled trialIntervention (counseling)Family medicineNursingPolitical science

Abstract

fetched live from OpenAlex

Reimbursement of trial participants remains a frequently debated issue, with specific guidance lacking. Trials combining post-trial access and implementation science may necessitate new strategies and models. CAPRISA 008, a post-trial access study testing the feasibility of using family planning services to rollout a prelicensure HIV prevention intervention, tried to balance the real-life scenario of no reimbursement for attendance at public sector clinics with that of a trial including some visits that focused on research procedures and others that focused on standard of care procedures. A reduced reimbursement was offered for 'standard of care' visits, meant primarily to cover transport costs to and from the clinic only. This impacted negatively on accrual, retention and participant morale, primarily due to the protracted delay in regulatory approval, during which time, the costs of living, including travel costs had increased. Relevant guidelines were reviewed and institutional policy was updated to incorporate the South African National Health Research Ethics Committee guidelines on reimbursement (taking into account participant time, travel and inconvenience). The reimbursement amount for 'standard of care' visits was increased accordingly. The question remains whether a trial that combines post-trial access with implementation science, with clear benefits for the participants and the provision of above standard medical care, should have reimbursement rates that approach those of a proof-of-concept trial, for 'standard of care' visits.

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)0.008
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.464
GPT teacher head0.537
Teacher spread0.073 · 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.

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

Citations7
Published2015
Admission routes1
Has abstractyes

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