A Systematic Review on Navigation Programs for Persons Living With Dementia and Their Caregivers
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: System navigation programs are becoming more available to meet the needs of patients with complex care needs. The aim of this review was to systematically assess the outcomes of navigation programs for persons with dementia and their family caregivers. RESEARCH DESIGN AND METHODS: A systematic review methodology was employed. Ten databases were searched for all relevant articles published until October 30, 2021. English-language full-text articles were included if they focused on implemented navigation program(s) that primarily supported persons with dementia who were aged 50 or older. Methodological quality was assessed by 2 independent raters using the Physiotherapy Evidence Database Scale, the STrengthening the Reporting of OBservational studies in Epidemiology checklist, and the Mixed Methods Appraisal Tool. RESULTS: Fourteen articles were included in the review. There was Level 1 evidence for the benefits of system navigation programs on delaying institutionalization, wherein benefits appeared to be specific to interventions that had an in-person component. There was Level 1 (n = 4) and Level 3 (n = 1) evidence on service use from time of diagnosis to continued management of dementia. Finally, Level 1 to Level 5 evidence indicated a number of benefits on caregiver outcomes. DISCUSSION AND IMPLICATIONS: There is strong evidence on the benefits of system navigation for people with dementia on delaying institutionalization and caregiver outcomes, but outcomes across other domains (i.e., functional independence) are less clear, which may be due to the varied approaches within system navigation models of care.
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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 | 0.009 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".