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Record W2274992954 · doi:10.4088/jcp.14m09710

A Pilot Randomized Clinical Trial Evaluating the Impact of Genetic Counseling for Serious Mental Illnesses

2016· article· en· W2274992954 on OpenAlexafffundabout
Catriona Hippman, Andrea Ringrose, Angela Inglis, Joanna Cheek, Arianne Albert, Ronald A. Remick, William G. Honer, Jehannine Austin

Bibliographic record

VenueThe Journal of Clinical Psychiatry · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsWomen's Health Research InstituteUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsSchizoaffective disorderPopulationGenetic counselingMedicineBonferroni correctionIntervention (counseling)Randomized controlled trialBipolar disorderPsychiatryClinical psychologySchizophrenia (object-oriented programming)Mental illnessPsychologyMental healthMoodPsychosis

Abstract

fetched live from OpenAlex

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 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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0150.001

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 head0.091
GPT teacher head0.491
Teacher spread0.401 · 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 designRandomized trial
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

Citations57
Published2016
Admission routes3
Has abstractyes

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