“The System is Broken”: Caregiver Perspectives of Barriers to Aging in Place with Dementia using the Social Ecological Model
Bibliographic record
Abstract
BACKGROUND: The majority of persons living with dementia in Canada reside at home, relying on support from family and/or friends that act as caregivers. This research examined the lived experiences of persons with dementia and their caregivers while aging in place, using the social ecological model to provide an understanding of various barriers for this group. METHOD: Fourteen caregivers were recruited to participate in in-depth one-on-one semi-structured interviews. Phenomenology was the theoretical orientation used to guide this qualitative research to present an accurate depiction of lived experience. Field notes, member checks, and triangulation were used to enhance the credibility of the study. RESULT: The social ecological model provided a framework to classify barriers to aging in place cited by caregivers. The subsequent theme They don't make it easy emphasized issues cited by participants regarding community and societal domains of aging in place care. CONCLUSION: Interviews provided knowledge concerning unmet needs and systematic issues faced by caregivers and persons living with dementia and their subsequent impact on care provision. Their stories provide a unique perspective of aging in place with dementia and shed light on the need for reform in health care policies to address systemic barriers and sincerely promote aging in place for all persons.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.018 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".