Group plus “mini” individual pre-test genetic counselling sessions for hereditary cancer shorten provider time and improve patient satisfaction
Bibliographic record
Abstract
BACKGROUND: Genetic counselling (GC) is an integral component in the care of individuals at risk for hereditary cancer predisposition syndromes (CPS). In many jurisdictions, access to timely counselling and testing is limited by financial constraints, by the shortage of genetics professionals and by labor-intensive traditional models of individual pre and post-test counselling. There is a need for further research regarding alternate methods of GC service delivery and implementation. This quality improvement project was initiated to determine if pretest group GC followed immediately by a 'mini' individual session, would be acceptable to patients at risk for hereditary breast and colon cancer. METHODS: = 112), were contacted by telephone and offered the option of a group counselling session (GGC), followed by a "mini" individual session, versus (TGC) traditional private appointments. GGC sessions consisted of a cancer genetics information session given to groups of 6-20 followed by brief 20 min "mini" individual sessions with the patient and genetic specialist. TGC individual appointments provided the same cancer genetics information and counselling to one patient at a time in the classic model. All but 2 participants selected group+mini session. A de-identified confidential 12-item, Likert scale survey was distributed at the conclusion of mini-sessions to measure perceptions of GGC and satisfaction with this counselling model. RESULTS: Sixty participants completed questionnaires. The majority of participants strongly agreed that they were comfortable with the group session (58/60); the explanation of cancer genetics was clear (54/59); they understood their cancer risks (50/60); and they would recommend such a session to others (56/59). 38/53 respondents disagreed or strongly disagreed that they would prefer to wait for a traditional private appointment. All 5 participating genetic counselors reported a preference for this model. At the end of the pilot project, the waitlist for counselling/testing was reduced by 12 months. CONCLUSIONS: Group pre-test genetic counselling combined with immediate "mini" individual session is strongly supported by patients and reduces wait times. Additional formal investigation of this approach in larger numbers of patients is warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".