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Record W2006745836 · doi:10.1007/s10897-008-9148-1

Cognitive and Behavioural Effects of Genetic Testing for Thrombophilia

2008· article· en· W2006745836 on OpenAlexaff
Jodi Heshka, Crystal Palleschi, Brenda J. Wilson, Jamie Brehaut, Julie Rutberg, Holly Etchegary, Nicole Langlois, Marc Rodger, Philip S. Wells

Bibliographic record

VenueJournal of Genetic Counseling · 2008
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineWorryThrombophiliaRisk perceptionGenetic counselingClinical psychologyVenous thromboembolismPhysical therapyPerceptionPsychiatryAnxietyPsychologyThrombosis

Abstract

fetched live from OpenAlex

Very few studies have examined the impact of genetic testing for thrombophilia on health behaviours, perceptions of control over risk factors for venous thromboembolism, or health services utilization. Through a postal questionnaire we compared first degree relatives with thrombophilia (carriers) most of whom had received counseling, to those without (non-carriers) with respect to: (a) perceived causes of venous thromboembolism; (b) perceived control; (c) health behaviour changes; and (d) use of health care services. 44/51 for carriers and 26/47 for non-carriers completed questionnaires. Carriers were more likely to believe their risk of venous thromboembolism 'is a little higher' or 'much higher' than average (p < 0.001) but some continued to believe their risk 'is the same as' or 'lower than' average. 16%-32% of carriers did not recognize major risk factors. Stress, worry, or depression, negative attitude, and over-exertion were over-interpreted as risks. 37.2% did not appreciate that thrombophilia increases risk. Behaviour changes were uncommon. There is a need for research on education and strategies to improve knowledge in thrombophilia carriers.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.609
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.048
GPT teacher head0.293
Teacher spread0.245 · 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

Citations13
Published2008
Admission routes1
Has abstractyes

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