A Pilot Randomized Clinical Trial Evaluating the Impact of Genetic Counseling for Serious Mental Illnesses
Bibliographic record
Abstract
OBJECTIVE: The serious mental illnesses schizophrenia, schizoaffective disorder, and bipolar disorder are complex conditions affecting 1% to 4% of the population. Individuals with serious mental illnesses express interest in genetic counseling, an intervention showing promise for increasing patient knowledge and adaptation. This trial aimed to evaluate the effects of genetic counseling for people with serious mental illnesses as compared to an educational intervention or wait list. METHOD: A pilot 3-arm (each n = 40; genetic counseling, a control intervention involving an educational booklet, or wait list), parallel-group, randomized clinical trial was conducted from September 2008 through November 2011 in Vancouver, Canada. Participants with schizophrenia, bipolar disorder, or schizoaffective disorder (DSM-IV) completed outcome measures assessing knowledge, risk perception, internalized stigma, and perceived control over illness at baseline and 1-month follow-up. The Brief Symptom Inventory was administered to control for current symptoms. Analyses included linear mixed-effects models and χ(2) tests. RESULTS: Knowledge increased for genetic counseling/educational booklet compared to wait list at follow-up (LRT1 = 19.33, Holm-adjusted P = .0003, R(2)LMM(m) = 0.17). Risk perception accuracy increased at follow-up for genetic counseling compared to wait list (Yates continuity corrected χ(2)1 = 9.1, Bonferroni P = .003) and educational booklet (Yates continuity corrected χ(2)1 = 8.2, Bonferroni P = .004). There were no significant differences between groups for stigma or perceived control scores. CONCLUSIONS: Genetic counseling and the educational booklet improved knowledge, and genetic counseling, but not the educational booklet, improved risk perception accuracy for this population. The impact of genetic counseling on internalized stigma and perceived control is worth further investigation. Genetic counseling should be considered for patients with serious mental illnesses. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT00713804.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".