Universal Access to Cognitive Behavioral Therapy and Antidepressants Is Necessary for All Patients With Major Depressive Disorder
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Abstract
Editorials3 December 2019Universal Access to Cognitive Behavioral Therapy and Antidepressants Is Necessary for All Patients With Major Depressive DisorderMark Sinyor, MSc, MDMark Sinyor, MSc, MDSunnybrook Health Sciences Centre and the University of Toronto, Toronto, Ontario, Canada (M.S.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/M19-2623 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail More than a century ago, Sigmund Freud pioneered a scientific approach to psychotherapy, which has since evolved to include several forms—none more ubiquitous than cognitive behavioral therapy (CBT) (1). Although these treatments may differ substantially in content, they share a simple overarching premise: Spending time talking with patients about their inner experiences can help change thinking and behavior. The mid-20th century discovery of psychotropic medications resulted in a parallel movement in psychiatry in which biological interventions were sought to treat mental disorders analogous to earlier efforts identifying antibiotics to treat infections (2). Although both forms of treatment have strong evidence ...References1. Churchill R, Moore TH, Caldwell D, et al. Cognitive behavioural therapies versus other psychological therapies for depression. Cochrane Database Syst Rev. 2010. [PMID: 25411559] MedlineGoogle Scholar2. Moncrieff J. Magic bullets for mental disorders: the emergence of the concept of an “antipsychotic” drug. J Hist Neurosci. 2013;22:30-46. [PMID: 23323530] doi:10.1080/0964704X.2012.664847 CrossrefMedlineGoogle Scholar3. Gartlehner G, Gaynes BN, Amick HR, et al. Comparative benefits and harms of antidepressant, psychological, complementary, and exercise treatments for major depression. An evidence report for a clinical practice guideline from the American College of Physicians. Ann Intern Med. 2016;164:331-41. [PMID: 26857743]. doi:10.7326/M15-1813 LinkGoogle Scholar4. Amick HR, Gartlehner G, Gaynes BN, et al. Comparative benefits and harms of second generation antidepressants and cognitive behavioral therapies in initial treatment of major depressive disorder: systematic review and meta-analysis. BMJ. 2015;351:h6019. [PMID: 26645251] doi:10.1136/bmj.h6019 CrossrefMedlineGoogle Scholar5. Ross EL, Vijan S, Miller EM, et al. The cost-effectiveness of cognitive behavioral therapy versus second-generation antidepressants for initial treatment of major depressive disorder in the United States. A decision analytic model. Ann Intern Med. 2019;171:785-95. doi:10.7326/M18-1480 LinkGoogle Scholar6. Hollon SD, DeRubeis RJ, Fawcett J, et al. Effect of cognitive therapy with antidepressant medications vs antidepressants alone on the rate of recovery in major depressive disorder: a randomized clinical trial. JAMA Psychiatry. 2014;71:1157-64. [PMID: 25142196] doi:10.1001/jamapsychiatry.2014.1054 CrossrefMedlineGoogle Scholar7. Cuijpers P, Hollon SD, van Straten A, et al. Does cognitive behaviour therapy have an enduring effect that is superior to keeping patients on continuation pharmacotherapy? A meta-analysis. BMJ Open. 2013;3. [PMID: 23624992] doi:10.1136/bmjopen-2012-002542 CrossrefMedlineGoogle Scholar8. Dunlop BW, Kelley ME, McGrath CL, et al. Preliminary findings supporting insula metabolic activity as a predictor of outcome to psychotherapy and medication treatments for depression. J Neuropsychiatry Clin Neurosci. 2015;27:237-9. [PMID: 26067435] doi:10.1176/appi.neuropsych.14030048 CrossrefMedlineGoogle Scholar9. GBD 2016 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390:1211-59. [PMID: 28919117] doi:10.1016/S0140-6736(17)32154-2 CrossrefMedlineGoogle Scholar10. Bachmann S. Epidemiology of suicide and the psychiatric perspective. Int J Environ Res Public Health. 2018;15. [PMID: 29986446] doi:10.3390/ijerph15071425 CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: Sunnybrook Health Sciences Centre and the University of Toronto, Toronto, Ontario, Canada (M.S.)Disclosures: The author has disclosed no conflicts of interest. The form can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M19-2623.Corresponding Author: Mark Sinyor, MSc, MD, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, FG52, Toronto, Ontario, M4N 3M5, Canada; e-mail, mark.[email protected]ca.This article was published at Annals.org on 29 October 2019. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoThe Cost-Effectiveness of Cognitive Behavioral Therapy Versus Second-Generation Antidepressants for Initial Treatment of Major Depressive Disorder in the United States Eric L. Ross , Sandeep Vijan , Erin M. Miller , Marcia Valenstein , and Kara Zivin Metrics Cited byCYP2C19 Genotyping May Provide a Better Treatment Strategy when Administering Escitalopram in Chinese PopulationCost effectiveness of CBT and antidepressant drugs in USA 3 December 2019Volume 171, Issue 11Page: 849-850KeywordsAntidepressantsCognitive behavior therapyMajor depressive disorderPenicillinPsychopharmacologySelective serotonin reuptake inhibitorsSmall for gestational ageSuicideSystematic reviews ePublished: 29 October 2019 Issue Published: 3 December 2019 Copyright & PermissionsCopyright © 2019 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.073 | 0.030 |
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".