Exploring the Landscape of Intensive Outreach Services for Older Adults With Serious Mental Illness: A Scoping Review
Bibliographic record
Abstract
Older adults living with mental illness, particularly those with serious mental illness (SMI), represent a vulnerable and underserved patient population. Deinstitutionalization laid the groundwork for intensive outreach services for this population, yet little attention was paid to the unique needs of older individuals with SMI. We conducted a scoping literature review to map the landscape of intensive outreach services developed for older adults living with SMI. We specifically focused on peer-reviewed literature. EMBASE, MEDLINE, PsycINFO and CINAHL databases were searched for pertinent literature between 1990 and 2023. Fourteen studies were selected for inclusion from 2,952 articles screened. Most studies were descriptive (N = 7). There were three randomized controlled trials (N = 3), three quasi-experimental studies (N = 3) and one (N = 1) pre-experimental study. All programs had a multidisciplinary component with a wide range of allied health clinicians. Six programs were adapted from the assertive community treatment model. Three programs included medical specialists. Only seven studies focused on examining treatment outcomes or efficacy, though there was notable variability in outcome measures analyzed. While intensive outreach services for older adults with SMI show promise, this scoping review highlights the paucity of research in this area. Future research rigorously evaluating models of care, with emphasis on fidelity, cost-effectiveness and patient outcomes, will be essential to inform service delivery to this population.
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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 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".