Roles and experiences of informal caregivers of older adults in community and healthcare system navigation: a scoping review
Bibliographic record
Abstract
OBJECTIVE: Informal caregivers are playing a vital role in improving the degree to which older adults access community and healthcare systems in a more seamless and timely manner, thereby fulfilling their complex needs. It is critical to understand their experiences and perspectives while navigating these systems. This review aimed to identify and organise the research findings on the roles and experiences of informal caregivers of older adults while navigating community and healthcare systems. DESIGN: This scoping review was undertaken according to the Joanna Briggs Institute's Reviewer manual. Four databases were used: AgeLine, PsycINFO, CINAHL and Medline to capture literature with a focus on informal caregivers whose care recipients are aged 55 years or older. Articles were included if they focused on examining the experience, perspective and/or role of informal caregivers in providing care for their older care recipients, while articles were excluded if they only focused on healthcare professionals or older adults. RESULTS: A total of 24 studies were identified that met the study inclusion criteria. This review elucidated the roles of caregivers as a primary system navigator and as an advocate for older adults. Numerous challenges/barriers in system navigation were uncovered, such as lack of consistency in fragmented systems, as well as facilitators, including interface/coordination roles. Finally, recommendations for better system navigation such as caregiver engagement and integration of continuity of care services were identified. CONCLUSION: The need to raise the visibility of the roles and experiences of informal caregivers in system navigation was highlighted. Further research needs to focus on implementing interventions for informal caregivers incorporating a care coordinator to fill the care gap within community and healthcare systems. This review has the potential to foster greater integration of community and healthcare systems.
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 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".