Notice bibliographique
Résumé
To the Editor: We welcome the contribution by Drs. St. John and Montgomery. Their findings are consistent with ours.1 However, contrary to our findings, when they adjusted for physical function, the association lost significance. In our analyses, we adjusted for activity of daily living (ADL) limitations, which were found to be a significant predictor even while the effect of depressive symptoms remained highly significant. Drs. St. John and Montgomery also used ADLs and included an additional measurement for instrumental activities of daily living (IADLs). It appears that they added both variables into their model concurrently rather than determining the individual effect of each. It is possible that the IADL scale undermined the effect of physical impairment as measured using the ADLs. We adjusted for considerably more variables than Drs. St. John and Montgomery, which also may explain the different results. For example, we adjusted for arthritis and stroke, which may affect function. It may be that the physical function measured in their study was a confounder for these medical conditions Cognition did not significantly affect risk of nursing home admissions in Drs. St. John and Montgomery's model. This is inconsistent with some research.2-4 We believe that this requires more research. As a measure of social support, we included home ownership. Although this is not a comprehensive measure of social support, other research has also shown that those who do not own their own home are far more likely to be admitted to a nursing home4 and that home ownership can serve as a proxy for income. We also adjusted for economic level and marriage, which could possibly explain some differences. Drs. St. John and Montgomery acknowledge differences in the admitting practices for nursing homes in the United States and Canada. In Canada, entering a nursing home requires a panel review. Medicare requires a 3-day prior hospitalization and a physician's note that the individual can show some improvement before reimbursement is approved, which affects many admissions, although for direct admissions to long-term care in a nursing home, U.S. facilities accept anyone based on bed availability and insurance status (i.e., availability of private pay or Medicaid). Therefore, measures of physical function, cognitive status, depression, and physical health may play a different role in the risk of admissions in the United States than in Canada, where residents are only admitted for long-term care. Financial Disclosure: The authors do not have any financial investment in this research. Author Contributions: Dr. Harris performed the analysis with input from Dr. Cooper. Dr. Cooper and Dr. Harris both authored the letter. Sponsor's Role: There was no outside sponsorship of this research.
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 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,021 | 0,026 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,020 |
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 ».