Treatment of Depression and Anxiety by Naturopathic Physicians: An Observational Study of Naturopathic Medicine Within an Integrated Multidisciplinary Community Health Center
Bibliographic record
Abstract
OBJECTIVES: This project was designed to assess the quality of care received by patients with depression and anxiety who were seen by naturopathic physicians in a community health center. METHODS: The Natural Medicine Quality Improvement Project for the Treatment of Depression and Anxiety (NMQP-DA) was conducted over a 26-month period from December 2009 through February 2012 at HealthPoint, a non-profit, consumer-governed, community health center network located in suburban King County, Washington. A total of 112 patients enrolled in the NMQP-DA, and 60 were seen for two or more visits, thus meeting eligibility criteria for inclusion in the study. The mean number of visits was 3.3. The Patient Health Questionnaire (PHQ-9) depression screener and the Generalized Anxiety Disorder 7-item scale (GAD-7) anxiety screener were the outcome measures. RESULTS: The overall improvement in symptoms of depression and anxiety was highly significant (p < 0.0001) when comparing the group's average initial screener scores to their average final screener scores for both depression (16.4 vs. 8.6) and anxiety (12.4 vs. 7.2). The response rate, as measured by a 50% decrease in scores, for those with initial scores ≥10 was 58.6% for depression (PHQ-9) and 50% for anxiety (GAD-7). CONCLUSIONS: This study adds new data to the limited literature on the nature and effectiveness of naturopathic medicine to treat anxiety and depression in the context of an integrative community health center.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".