The Saskatchewan Caregiver Experience Study: Support Priorities of Caregivers of Older Adults
Bibliographic record
Abstract
BACKGROUND: Population aging is a global phenomenon. Many older adults living with chronic conditions rely on family and friend caregivers. The growing demand for family and friend caregivers underscores the necessity for adequate and effective support services. PURPOSE: The Saskatchewan Caregiver Experience Study sought to gather the perspectives of caregivers of older adults and set priorities for caregiver support. METHODS: An online survey with open-ended questions was employed in this qualitative descriptive study. In this manuscript, we present our findings from the survey question: "What do you think is most important for support in your caregiving role? In other words, what are your top priorities for support?" FINDINGS: This survey question received n = 352 responses, evenly distributed across Saskatchewan in urban-large (33%), urban-small/medium (32%), and rural (35%) settings. Support priorities of Saskatchewan caregivers were found to be access to help when they need it; an ear to listen and a shoulder to lean on; assistance in optimizing the care recipient's health; having healthcare professionals that care; and improved policies, legislations, and regulations. CONCLUSION: Services and interventions that assist caregivers are more likely to be accessed and utilized when caregivers are given the opportunity to identify their own support priorities. This study has the potential to inform health and governmental systems to support caregivers of older adults provincially within Saskatchewan, nationally in Canada, and in a global context.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".