Abstracts from the 2024 Annual Scientific Meeting of the Canadian Academy of Geriatric Psychiatry and Canadian Coalition for Seniors’ Mental Health
Bibliographic record
Abstract
Background: Older adults living with severe mental illness (SMI) represent a vulnerable and complex patient population.Deinstitutionalization laid the groundwork for intensive outreach services designed for those with SMI, yet these programs have largely focused on adults.While reviews to date have examined community-based outreach for older adults with mental illness, none have focused on the SMI population.This presentation will describe the findings of our scoping review, which aimed to map the existing peer-reviewed literature on intensive outreach services for older adults with SMI.These findings will be presented alongside a discussion of barriers and facilitators to developing a novel psychogeriatric assertive community treatment (ACT) team after four years in practice.Methods: EMBASE, MEDLINE, PsycINFO and CINAHL databases were searched for pertinent literature between 1990 and 2023.Two reviewers independently screened titles, abstracts, and full texts.Data was extracted by one reviewer with independent review from a second author.Sixteen studies were selected for inclusion based on full text review.Results: Most studies were descriptive (N = 8).There were three randomized controlled trials (N= 3) and three quasi-experimental designs (N = 3).The majority of interventions involved multidisciplinary team-based services.Four programs included medical specialists.There was a wide range of allied health supports.Six programs were specifically adapted from the ACT model.Conclusions: Discussion will focus on describing the various models of care as revealed from our scoping review.We will further discuss lessons learned from four years of practice with a novel psychogeriatric ACT team in Toronto.
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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 | 0.015 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.022 | 0.020 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.126 | 0.025 |
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".