Genetic influences on treatment-seeking for common mental health problems in the UK biobank
Bibliographic record
Abstract
The majority of those who experience clinical anxiety and/or depressive symptoms in the population do not receive treatment. Studies investigating inequalities in treatment outcomes rarely consider that individuals respond differently to their experience of the environment. Much of our environment is under genetic influence, via our behaviour, whereby individuals actively select their experiences. If genes influence who seeks and receives treatment, selection bias will confound genomic studies of treatment response. Furthermore, if some individuals are at high genetic risk of needing but not commencing treatment, then greater efforts could be made to engage them. The role of common genetic variation on four lifetime treatment-seeking behaviours (treatment-seeking, treatment-receipt, self-help, self-medication with alcohol/drugs) was examined in participants of the UK Biobank (sample size range: 48,106 - 75,322). Treatment-related behaviours were only modestly heritable in these data. Nonetheless, genetic correlations reveal substantial genetic overlap between lifetime treatment-related behaviours and psychiatric disorders, symptoms and behavioural traits. To our knowledge, this is the first study to examine genetic influences on treatment-related behaviours. Further work is required to determine whether genetic factors could be used alongside clinical, social and demographic factors to identify at risk groups and inform strategies which target early intervention.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".