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Record W4283520129 · doi:10.1111/tme.12891

Blood donor notification of variant Creutzfeldt–Jakob disease risk: Lessons in communicating donor deferral and risk

2022· article· en· W4283520129 on OpenAlexaff
Claire Reynolds, Tali Yawitch, Patricia E. Hewitt, Heli Harvala

Bibliographic record

VenueTransfusion Medicine · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineDeferralRegretFamily medicineWorryFeelingDiseaseAnxietyPediatricsPsychiatryPsychologyInternal medicineSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: In 2005, the blood service in England notified 101 donors by letter that they may be at risk of variant Creutzfeldt-Jakob disease (vCJD) because a recipient of their blood later developed vCJD. Donor experience of the notification was studied in a 2009 survey. METHODS: Fifteen questions focused on satisfaction, emotional response and understanding of the notification letter. An average Likert score was calculated: 1 and 2 = dissatisfied, 3 = equivocal and 4 and 5 = satisfied; the per cent satisfied and dissatisfied were calculated and characteristics compared using the Fisher and Chi-squared tests. RESULTS: The questionnaire was completed by 56 of 90 notified donors, mostly repeat, U.K.-born donors over 45 years of age. Four years after notification, many individuals still felt surprise (44%), upset (44%) or worry (50%) about the letter, with 10 feeling depressed. Thirty per cent were uncertain if they had vCJD or not. For future notifications, 57% would still favour a detailed letter and 36% would prefer a discussion in person. DISCUSSION: It was notable how many individuals, 4 years later, still felt continuing anxiety about the vCJD notification letter, not noted in earlier interviews. This highlights a need for on-going support required in donor notifications where outcome for the individual is highly uncertain.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.270
Teacher spread0.237 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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