Universal Access to Cognitive Behavioral Therapy and Antidepressants Is Necessary for All Patients With Major Depressive Disorder
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Résumé
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 ...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,004 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,073 | 0,030 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».