Strategies for Managing Depression Refractory to Selective Serotonin Reuptake Inhibitor Treatment: A Survey of Clinicians
Bibliographic record
Abstract
OBJECTIVE: To examine treatment practices in cases where selective serotonin reuptake inhibitors (SSRIs) are ineffective. METHODS: We surveyed 801 clinicians (including 630 psychiatrists) attending the Massachusetts General Hospital's annual psychopharmacology review course. Clinicians were presented with a vignette about a patient with depression who had responded partially to an SSRI and were asked to choose among various strategies available to manage this patient. RESULTS: Of those surveyed, 466 clinicians had been in practice a mean of 16.6 years (SD 10.7). Not all clinicians chose to answer every question. Among 455 respondents, 84% (n = 382) chose to increase the dose of the SSRI, 10% (n = 47) chose augmentation or combination, and 7% (n = 31) opted for switching agents. When asked to switch to another agent, 448 responded, of whom 52% (n = 235) chose a newer antidepressant, 34% (n = 152) chose another SSRI, 10% (n = 44) chose a tricyclic antidepressant (TCA), 2% (n = 8) chose a serotonin norepinephrine reuptake inhibitor (SNRI), 1% (n = 5) chose a monoamine oxidase inhibitor (MAOI), and 1% (n = 4) chose an undefined "other" agent. Among 445 respondents, bupropion was the most widely chosen augmenting agent (30%, n = 134), followed by lithium (22%, n = 98). West coast and Canadian clinicians preferred to switch to another SSRI rather than to a newer antidepressant. Canadian clinicians preferred lithium to bupropion as their first-choice augmenting agent, as did clinicians from academic settings. Clinicians from community, individual practice, or group settings favoured bupropion. More experienced clinicians preferred bupropion as a first-choice augmenter, whereas less experienced ones showed a slight preference for lithium. Canadian clinicians were more likely to use MAOIs as second-line agents. CONCLUSIONS: Clinicians in this sample often followed strategies different from those recommended in the literature. Bupropion may have an important role in augmentating treatment with SSRIs.
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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".