Challenges Reported by Family and Friend Caregivers to Older Adults in the Saskatchewan Caregiver Experience Study
Bibliographic record
Abstract
The Saskatchewan Caregiver Experience Study sought to map the experiences of family and friend caregivers of older adults in the Canadian province of Saskatchewan. This study aimed to capture the lived experiences of these caregivers through a qualitative survey in June and July of 2022. This manuscript analyzes responses from 354 participants to the question: “What is the most challenging aspect of being a caregiver?” An inductive content analysis approach was taken to analyze the data. We identified key challenges related to caregiving in Saskatchewan, Canada, including exhaustion, balancing personal life, navigating complex systems, self-doubt, and caregiving from a distance. Participants emphasized the need for targeted support and interventions to assist them in their caregiving role. Participants’ experiences reflect a need for more supportive measures in healthcare and policy, especially considering the unique demographic and geographic context of Saskatchewan. A paradigm shift is needed toward supporting caregivers to allow older adults to age in place, rather than relying on institutions and care facilities. In the global context, these findings align with the need for culturally sensitive and region-specific support systems, addressing the universal aspects of caregiving.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".