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Enregistrement W4395108767 · doi:10.1016/j.lanwpc.2024.101076

Attempted emulation of a randomised depression screening trial

2024· article· en· W4395108767 sur OpenAlexaffabout
Brett D. Thombs, Christel Renoux

Notice bibliographique

RevueThe Lancet Regional Health - Western Pacific · 2024
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueHealth Systems, Economic Evaluations, Quality of Life
Établissements canadiensMcGill UniversityJewish General Hospital
Organismes subventionnairesnon disponible
Mots-clésEmulationDepression (economics)PsychologyMedicinePsychiatryComputer scienceSocial psychologyEconomicsKeynesian economics

Résumé

récupéré en direct d'OpenAlex

Chen et al.1Chen Y.-L. Wu M.-S. Wang S.-H. et al.Effectiveness of health checkup with depression screening on depression treatment and outcomes in middle-aged and older adults: a target trial emulation study.Lancet Reg Health West Pac. 2024; 43100978Google Scholar used observational data from Taiwan’s Adult Preventive Health Checkup Program to attempt to emulate a depression screening trial by comparing adults who attended a free health checkup to matched counterparts who did not. They reported that people in the health checkup arm were more likely to receive new depression treatment, had lower risk of psychiatric hospitalisation, and that those 65 years and older had higher suicide risk. A depression screening trial should enrol and randomly allocate patients not known to have depression; screen participants in the screening arm but not those in the comparator arm; ensure that participants in both arms have comparable health care access and, if determined to have depression, similar depression care options; and assess achievable screening outcomes, such as depression symptoms or diagnoses.2Thombs B.D. Ziegelstein R.C. Does depression screening improve depression outcomes in primary care?.BMJ. 2014; 348g1253Crossref PubMed Scopus (40) Google Scholar Emulated trials must approximate design elements as closely as possible, including treatment strategies, assignment procedures, and outcomes.3Hernán M.A. Robins J.M. Using big data to emulate a target trial when a randomized trial Is not available.Am J Epidemiol. 2016; 183: 758-764Crossref PubMed Google Scholar Emulating random assignment requires being able to make a strong case that patients in different trial arms are similar except for their treatment assignment.3Hernán M.A. Robins J.M. Using big data to emulate a target trial when a randomized trial Is not available.Am J Epidemiol. 2016; 183: 758-764Crossref PubMed Google Scholar It is unlikely that Chen et al.’s emulated trial arms achieved this. Using a small number of variables to create propensity scores would not likely address confounding from comparing people who sought preventive health care, outside of normal care, to people who did not. Health care available in the two trial arms, beyond depression screening, was not comparable. First, people in the screening arm had (1) health checkups, including a full personal and family history, physical examination, blood tests, and urine tests (2) plus depression screening. People in the comparator arm had neither. Second, people in the screening arm could access additional health checkups and depression screening in the years following the index health checkup, but patients in the comparator arm could not; they were censored if they did. Outcomes did not reflect benefits or harms that would be expected from depression screening or that would normally be included in a depression screening trial. Receiving new treatment occurs with more health care exposure but is not a health benefit. Since depression screening is done to find otherwise undetected cases, trials target symptoms or incident diagnoses. No depression screening trials have targeted hospitalisation and suicide outcomes as in Chen et al.’s study.4Thombs B.D. Markham S. Rice D.B. Ziegelstein R.C. Does depression screening in primary care improve mental health outcomes?.BMJ. 2021; 374: n1661Crossref PubMed Scopus (5) Google Scholar Several well-conducted depression screening trials have reported that screening did not improve mental health outcomes.4Thombs B.D. Markham S. Rice D.B. Ziegelstein R.C. Does depression screening in primary care improve mental health outcomes?.BMJ. 2021; 374: n1661Crossref PubMed Scopus (5) Google Scholar Results reported by Chen et al. do not inform the evidence base further. The authors declare no competing interests. Funding: Dr. Thombs is supported by a Tier 1 Canada Research Chair outside of the present work. There was no funding for the correspondence. Effectiveness of health checkup with depression screening on depression treatment and outcomes in middle-aged and older adults: a target trial emulation studyHealth checkups with depression screening could potentially promote depression treatment and reduce the risk of psychiatric hospitalisation; however, there was no effect on suicide. The treatment rate for depression remained low after screening for depression. Further attention to enhance referral and treatment is required. Full-Text PDF Open Access

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,017
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,440
Score d'incertitude au seuil0,705

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0170,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,530
Tête enseignante GPT0,482
Écart entre enseignants0,049 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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