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Record W151800064 · doi:10.1023/a:1022663324006

Assessment of the Effectiveness of Genetic Counseling by Telephone Compared to a Clinic Visit

2003· article· en· W151800064 on OpenAlexaff
Karan Sangha, Anita Dircks, Sylvie Langlois

Bibliographic record

VenueJournal of Genetic Counseling · 2003
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsUniversity of British ColumbiaChildren's & Women's Health Centre of British ColumbiaUniversity of Alberta HospitalAlberta Hospital Edmonton
Fundersnot available
KeywordsGenetic counselingAnxietyMedicineAmniocentesisTelephone counselingFamily medicineTelephone interviewPregnancyClinical psychologyPsychiatryPrenatal diagnosisIntervention (counseling)FetusGenetics

Abstract

fetched live from OpenAlex

Maternal serum screening, also known as the triple screen, is used during pregnancy to assess the risk of carrying a fetus with specific chromosome abnormalities or open spina bifida. All women in British Columbia who screen positive are eligible for genetic counseling and are offered amniocentesis. The purpose of this study is to determine what differences (if any) exist in patients' understanding and/or anxiety when genetic counseling for a positive triple screen is conducted in person versus over the telephone. Each patient who participated was given the choice of having genetic counseling in person or over the telephone, this after a randomized design failed to elicit any participants. Using a written postcounseling questionnaire, each patient was assessed for her understanding of the information presented in the session, and her anxiety regarding her risk. In this small pilot study, no large differences were detected in patients' understanding or anxiety when genetic counseling was conducted by telephone versus in person.

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)0.005
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.022
GPT teacher head0.368
Teacher spread0.347 · 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 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

Citations42
Published2003
Admission routes1
Has abstractyes

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