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Perceptions and motivations of Canadian autologous blood donors

2001· article· en· W2114814792 on OpenAlexaffabout
Catherine Moltzan, Normand L. Proulx, Janis Bormanis, Nedra R. Lander, H DeGroot, G. Rock

Bibliographic record

VenueTransfusion Medicine · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsDonationMedicineBlood donorSAFERDemographicsPerceptionAutologous bloodFamily medicineHealth careSurgeryIntensive care medicinePsychologyImmunology

Abstract

fetched live from OpenAlex

Preoperative autologous blood donation in Canada has increased in the last decade due to concerns about allogeneic blood safety. As economic policies necessitate the validation of autologous blood donation, it is important to assess potential changes. This study examines the motivations and perceptions of patients participating in a Canadian autologous blood donation programme. The study was conducted at the Ottawa Hospital, Civic Campus. Questionnaires were developed and then administered to 100 consecutive adult autologous blood donors. The questionnaires assessed patient demographics, motivation for participation and perceptions about blood safety. Autologous donation was presented to 82% of patients as an option by their physicians. However, 59% of all patients felt that they were motivated to donate by their own fears. Patients (87%) also felt that directed blood donation should be offered due to their perception that directed donation is safer. Three-quarters of patients would be willing to pay for autologous donation. Patients are concerned about the safety of allogeneic blood and they are motivated to seek other alternatives despite the fact that allogeneic blood is very safe. These perceptions and motivations must be taken into account as health care policy changes are considered.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.137
Threshold uncertainty score0.275

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.023
GPT teacher head0.241
Teacher spread0.219 · 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

Citations18
Published2001
Admission routes2
Has abstractyes

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