Impact of the physical environment on patient outcomes of genetic counseling: An exploratory study
Bibliographic record
Abstract
The psychology literature shows that the physical space in which counseling sessions are conducted influences outcomes of the interaction. However, this phenomenon has not been quantitatively explored in genetic counseling (GC). Through retrospective review of naturalistic data from a psychiatric GC clinic (where data on patient outcomes are routinely tracked from pre- to 1 month post-appointment using the Genetic Counseling Outcome Scale (GCOS, empowerment) and the Illness Management Self Efficacy Scale (IMSES), we tested the hypotheses that patients seen in comfortably furnished counseling (C-type) rooms would have greater increases in (a) empowerment and (b) self-efficacy after GC than patients seen in medically oriented (M-type) rooms. We matched each patient with complete GCOS and/or IMSES who was seen in a C-type room between February 2012 and December 2017 to four M-type room controls where possible. We used t tests to compare change in outcome scale scores between groups. There were no significant differences in change in scores between patients seen in M-type (GCOS n = 84, IMSES n = 56) and C-type rooms (GCOS n = 22, IMSES n = 18) (p = 0.241, d = 0.26, and p = 0.602, d = 0.14, respectively). The effect sizes we demonstrate allow estimation of sample size calculations for the design of future prospective studies.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".