Mathematics Deficits in Adolescents With Bipolar I Disorder
Bibliographic record
Abstract
OBJECTIVE: This study examined mathematical ability in adolescents with bipolar I disorder, compared to adolescents with major depressive disorder and psychiatrically healthy comparison subjects. METHOD: Participants (N=119) included adolescents in remission from bipolar disorder (N=44) or major depressive disorder (N=30), as well as comparison subjects (N=45) with no psychiatric history. Participants were assessed with the following measures: the Wide-Range Achievement Test, Revised 2 (WRAT-R2), Peabody Individual Achievement Test, Bay Area Functional Performance Evaluation Task-Oriented Assessment (functional mathematics subtest), Test of Nonverbal Intellegence-2, and a self-report of mathematics performance. RESULTS: WRAT-R2 and Peabody Individual Achievement Test scores for spelling, mathematics, and reading revealed that adolescents with bipolar disorder had significantly lower achievement in mathematics, compared to subjects with major depressive disorder and comparison subjects. Results for the Test of Nonverbal Intellegence-2 were not significantly different between groups. Adolescents with bipolar disorder took significantly longer to complete the Bay Area Functional Performance Evaluation mathematics task. Significantly fewer adolescents with bipolar disorder (9%) reported above-average mathematics performance, compared with the other groups. CONCLUSIONS: Adolescents with remitted bipolar disorder have a specific profile of mathematics difficulties that differentiates them from both adolescents with unipolar depression and psychiatrically healthy comparison subjects. These mathematics deficits may not derive simply from more global deficits in nonverbal intelligence or executive functioning, but may be associated with neuroanatomical abnormalities that result in cognitive deficits, including a slowed response time. These deficits suggest the need for specialized assessment of mathematics as part of a comprehensive clinical follow-up treatment plan.
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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 | 0.000 | 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".