Contradictions, methodological flaws, and potential for misinterpretations in ranking treatments of depression
Bibliographic record
Abstract
In this journal Malhi et al. recommended cognitive-behavior therapy (CBT), antidepressants, and counseling ahead of short-term psychodynamic therapy (STPP) referring to UK NICE guidelines for depression. However, these recommendations continue the ambiguous and therefore confusing NICE guidelines, which on the one hand list the above treatments as equal options as first-line treatment for depression and emphasizes the importance of patient preference and implementations factors, but on the other hand rank these first-line treatments, implying superiority of some treatments over others. Furthermore, we highlight several methodological flaws of the NICE treatment ranking and that the NICE treatment ranking is not justified by NICE’s own and independent evidence and criteria. Presently it is not clear which patients benefit from which empirically-supported treatment. Thus, we continue to discourage the devaluing of efficacious treatments so that as many patients as possible may benefit from them.
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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 | 0.681 | 0.889 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.023 | 0.016 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.013 | 0.010 |
| Research integrity | 0.010 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".