Voices of care for adults with disabilities and/or mental health issues in Western Canada: what do families and agencies need from each other?
Bibliographic record
Abstract
Our purpose in this paper is to report on the frustrations and unmet needs of paid, formal caregivers and unpaid, family caregivers who together provide care to adults with disabilities and/or mental health issues. We conducted eight focus group interviews between November 2010 and June 2011 in two large, urban centres and one smaller centre in Western Canada. Four of our focus groups were with family members including adults with disabilities and/or mental health issues, their parents and their siblings, and four were with representatives from agencies providing support and services to adults with disabilities and/or mental health issues and their families. Data were collected from 23 family members and 24 agency representatives who responded to questions about successes and struggles in meeting, and collaborating to meet, care needs of adults with disabilities and/or mental health issues. Each focus group session was digitally recorded and transcribed; field notes were also taken and we thematically analysed data according to family versus agency perspectives of their successes and barriers in care provision and care collaboration. We found that family members desire greater and more effective support in enriching the lives of adults with disabilities and/or mental health issues and in preparing for age-related changes. Agency representatives are keenly aware of the needs and challenges faced by families, yet grapple with being effective collaborators with families of widely varying priorities and styles of care and collaboration.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.033 | 0.011 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".