Impact of Depression on the Intensity of Patient Navigation for Women with Abnormal Cancer Screenings
Bibliographic record
Abstract
Patient navigation is increasingly being used to support vulnerable patients to receive timely and quality medical care. We sought to understand whether patients with depression utilize additional patient navigation services after abnormal cancer screening. We compared depressed and non-depressed women using three different measures of intensity of patient navigation: number of patient-navigator encounters, encounter time, and number of unique barriers to care. The study population consisted of 1,455 women who received navigation after abnormal screening for breast or cervical cancer at one of six community health centers in Boston. Navigators spent a median of 60-75 minutes over one or two encounters per participant, with 49% of participants having one or more documented barrier to care. Depressed women did not differ in total numbers of encounters, encounter time, or unique barriers compared with non-depressed women. Our findings suggest that pre-existing depression does not predict which women will utilize additional navigation services.
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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".