Person‐ and family‐centred goal‐setting for older adults in Canadian home care: A solution‐focused approach
Bibliographic record
Abstract
Goal-setting with older adults in home care is often inhibited by a lack of structure to support person- and family-centred care planning, paternalistic decision-making and task-oriented delivery models. The objective of this research study was to determine how goal-setting practices for older adults could be re-oriented around individuals' self-perceived goals, needs and preferences. Solution-focused semi-structured key informant interviews were conducted with older adult home care clients aged 65 years and older (n = 13) and their family/friend caregivers (n = 12) to explore changes, solutions and strategies for person- and family-centred goal-setting. Participants were recruited through community advertisement in a single region of Ontario, Canada between July and October of 2017. Interviews were conducted in-person and were audio-recorded and transcribed verbatim. Thematic analysis was guided by a multi-step framework method. Four themes emerged from the data: (1) seeing beyond age enables respect and dignity; (2) relational communication involves two-way information sharing; (3) doing 'with' instead of doing 'for' promotes participation and (4) collaboration is easier when older adults and caregivers lead the way. Older adults and caregivers want to be actively engaged in dialogue during care planning to ensure their preferences are included. The findings from this study add the direct perspectives of older adults and their caregivers to literature on solutions to address ageism, improve communication, enhance information sharing and promote collaboration in geriatric care. Next steps for this work could involve testing the changes, solutions and strategies that emerged to determine the effect on person- and family-centred home care delivery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".