[The Management of Depression in Older Adults and Their Family Caregivers: Findings from a Research Program in Quebec].
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".