Assessing the Prevalence of Depression among Individuals with Diabetes in a Medicaid Managed-Care Program
Bibliographic record
Abstract
OBJECTIVES: To determine the prevalence of self-reported depression symptoms among diabetic individuals enrolled in Gold Choice, a Medicaid managed care organization specifically for people with mental health and/or substance abuse diagnoses; and to assess the sensitivity and specificity of individuals' self-report with encounter data. METHODS: The 9-item depression scale of the Patient Health Questionnaire (PHQ-9) was mailed to 454 Gold Choice members in Western New York diagnosed with diabetes; and 249 completed PHQ-9 forms were returned (55% response rate). The PHQ-9 forms were compared to primary care encounter data to determine whether the respondents had been diagnosed with depression. Descriptive and inferential statistical analysis was undertaken. RESULTS: The majority (56%) of individuals in the sample screened positive for depression (PHQ-9 > or = 10), and half (49%) did not have evidence of a diagnosis in their encounter data. The percentage of those diagnosed with depression rose with increasing PHQ-9 severity levels, with 63% of individuals with the most severe depression (PHQ-9 > or = 20) having a diagnosis. This trend was statistically significant, confirmed by independent sample t-tests and chi-square tests. The sensitivity of the PHQ-9 was moderate (66%), as was the specificity (52%). CONCLUSIONS: The results of this study suggest that depressive disorders may be under-recognized and under-treated amongst individuals with diabetes in the primary care setting. Half (51%) of those with PHQ-9 scores > or = 10 had depression diagnoses, suggesting poor compliance rates and/or a need for therapy reassessment.
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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 | 0.001 | 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".