Bipolar Disorder Center for Pennsylvanians: Implementing an Effectiveness Trial to Improve Treatment for At-Risk Patients
Bibliographic record
Abstract
Objective: Adolescents, elderly persons, African Americans, and rural residents with bipolar disorder are less likely than their middle-aged, white, urban counterparts to be diagnosed, receive adequate treatment, remain in treatment once identified, and have positive outcomes. The Bipolar Disorder Center for Pennsylvanians (BDCP) study was designed to address these disparities. This report highlights the methods used to recruit, screen, and enroll a cohort of difficult-to-recruit individuals with bipolar disorder. Methods: Study sites included three specialty clinics for bipolar disorder in a university setting and a rural behavioral health clinic. Study operations were standardized, and all study personnel were trained in study procedures. Several strategies were used for recruitment. Results: It was possible to introduce the identical assessment and screening protocol in settings regardless of whether they had a history of implementing research protocols. This protocol was also able to be used across the age spectrum, in urban and rural areas, and in a racially diverse cohort of participants. Across the four sites 515 individuals with bipolar disorder were enrolled as a result of these methods (69 African Americans and 446 non-African Americans). Although clinical characteristics at study entry did not differ appreciably between African Americans and non-African Americans, the pathways into treatment differed significantly. Conclusions: Rigorous recruitment and assessment procedures can be successfully introduced in different settings and with different patient cohorts, thus facilitating access to high-quality treatment for individuals who frequently do not receive appropriate care for bipolar disorder.
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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 | 0.005 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".