MétaCan
Menu
Back to cohort
Record W175470906 · doi:10.1023/a:1009459908884

A Method for Analyzing Videotaped Genetic Counseling Sessions

2000· article· en· W175470906 on OpenAlexaff
Alexander Liede, L Kerzin-Storrar, David Craufurd

Bibliographic record

VenueJournal of Genetic Counseling · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of Toronto
FundersUniversity of Manchester
KeywordsInter-rater reliabilityGenetic counselingCoding (social sciences)Reliability (semiconductor)PsychologyApplied psychologyConsistency (knowledge bases)Test (biology)Rating scaleComputer scienceDevelopmental psychologyStatisticsArtificial intelligenceGenetics

Abstract

fetched live from OpenAlex

This study describes the development and evaluation of a multi-item scale for analyzing the genetic counseling process, the Manchester Observation Code (MOC) for genetic counseling. The instrument is specific to the field of genetic counseling and is designed for analysis of the communication between counselor and client. Coding is done directly from videotaped sessions. Because communication is the means by which genetic counseling is accomplished, the method measures four relevant components of communication: (1) grammatical form, (2) purpose, (3) subject, and (4) cue source. The instrument enables an observer to code the counselor's statements into these four components. Three videotaped sessions were used to measure interrater reliability, or the consistency of rating for each of the four communication domains using this method. Three videotaped sessions were also used to measure test-retest reliability, or the consistency of the designed method from one time to another. A total of 21 videotaped sessions were tested using the method. A statistical measure of reliability established consistency of the designed method; Cohen's kappa yielded 0.7 for interrater reliability and 0.79 for test-retest reliability. These findings suggest this instrument may be used to identify important elements of the genetic counseling process.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.315
Teacher spread0.303 · 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 designNot applicable
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

Citations11
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Genetic CounselingSame topicBRCA gene mutations in cancerFrench-language works237,207