Home care providers' perceptions of shared decision‐making with older clients (and their caregivers): A cross‐sectional study
Bibliographic record
Abstract
Interprofessional care teams can play a key role in supporting older adults (and caregivers) in making informed health decisions, yet shared decision making is not widely practiced in home care. Based on an earlier needs assessment with older adults (and caregivers) with home care experience, we aimed to explore the perceptions of home care teams on the decisions facing their clients and their perceived involvement in shared decision making. A cross-sectional study was conducted with 614 home care providers (nurses, personal support workers, rehabilitation professionals) in three Canadian provinces (Quebec, Ontario, and Alberta). Home care providers considered the decision "to stay at home or move" as the most difficult for older adults. Those most frequently involved in decision making with older adults were family members and least involved were physicians. Although all home care providers reported high levels of shared decision-making, we detected an effect of respondent's discipline on self-perceived shared decision-making; nurses and rehabilitation professionals reported significantly higher levels of shared decision making than personal support workers. A more tailored approach is required to support shared decision making in interprofessional care teams.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".