Trend and geo-availability of somatic therapies for treatment resistant depression in the US
Bibliographic record
Abstract
Having failed at least two pharmacotherapies, treatment-resistant depression (TRD) constitutes a major burden to healthcare in the US and globally, affecting close to a third of people diagnosed with depression in the US. Several studies have demonstrated the higher economic burden associated with TRD. This study sought to investigate changes in the availability of TRD somatic treatment options (Electroconvulsive therapy [ECT], Ketamine infusion therapy (KIT), and Transcranial Magnetic Stimulation [TMS]) in the US between 2014 and 2020 and the geographic variations in availability of TRD treatment options in the US as of 2020. This study is a cross-sectional study of US mental health facilities providing TRD treatment options between 2014 and 2020. We used the 2014 to 2020 National Mental Health Services Survey (N-MHSS) data from the Substance Abuse and Mental Health Service Administration (SAMHSA). We estimated service availability per 100,000 US adults, both nationally and regionally, and computed a random-effect logistic regression to calculate the changes in the availability of the services over the study period. Overall, availability of any one of ECT, KIT, or TMS in US mental health facilities declined between 2014 and 2019 (0.23 vs. 0.18 per 100,000 US adults) but increased to 0.24 in 2020. While availability of ECT consistently declined between 2014 and 2020, ketamine and TMS reportedly became available only in 2020. North Dakota, Wyoming, and Utah had the highest availability per 100,000 US adults (0.86, 0.67, and 0.65) while Nevada, Oregon and Georgia had the lowest availability (0.04, 0.06, and 0.06) regionally. The US had less than one mental health facility offering somatic treatment options for TRD per 100,000 US adults as of 2020. Also, the observed increase in the availability of somatic treatment options for TRD across the US between 2014 and 2020 did not reflect the increasing need for more treatment options for the treatment of TRD.
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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".