[The Management of Depression in Older Adults and Their Family Caregivers: Findings from a Research Program in Quebec].
Notice bibliographique
Résumé
Objectives A research group based at St. Mary's Research Centre, St. Mary's Hospital, Montreal, has conducted a research program over the past two decades that aims to inform improvements in the management of depression in primary care and general medical settings, among older adults. This paper reviews the findings from this research program, discusses the findings in the context of other research, and highlights the implications for practice and health policy.Methods Narrative review and synthesis of 25 published articles, that included: 4 systematic reviews, 10 observational studies, 9 intervention trials, and 2 consensus conference reports.Results The results pertain to 4 research areas: detection of depression in primary care and general medical settings; collaborative care of depression; depression self-care interventions; and the role of family and friends in supporting depression self-care interventions.Conclusions We propose six recommendations for improving the management of depression in the target population. 1) Depression detection and treatment can be improved through collaborative care models that involve primary care physicians, mental health specialists and non-physician mental health workers who are trained to assist with the detection of depression, with the delivery of brief, low-intensity psychological interventions and with self-care support. More research and evaluation are necessary to determine the factors that enhance the effectiveness, cost-efficiency, and consumer-centeredness of these interventions. 2) Supported depression self-care (and other low-intensity interventions such as short problem-solving therapy) offered by telephone or via internet, either as part of collaborative or usual care are feasible treatment options but more research is necessary to determine their effectiveness in different clinical populations. Some populations (e.g., those aged 75 and over, with visual and/or mild cognitive impairment) are likely to need greater or face-to-face support. 3) As most family physicians are unlikely to have the necessary time or interest to support depression self-care interventions, other sustainable programmatic contexts are needed for delivery of these interventions. Options include: nurses or other mental health workers in multidisciplinary family medicine groups; regional mental health programs; and voluntary organizations dedicated to assisting in the management of chronic illnesses. Research is needed on the feasibility and effectiveness of using peer support workers or volunteers to provide coaching of depression self-care interventions. 4) Involvement of family or friends in depression self-care may improve outcomes (e.g., dyadic interventions) but further research is necessary. 5) Further research should explore the potential of depression self-care interventions to prevent major depression and in depression relapse prevention in this population.
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 | 0,007 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,007 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
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 ».