Identifying Research Priorities to Promote the Well-Being of Family Caregivers of Canadians with Intellectual and/or Developmental Disabilities: A Pilot Delphi Study
Bibliographic record
Abstract
Current programming and resources aimed at supporting the well-being of family caregivers often fail to address considerations unique to those caring for people with intellectual and/or developmental disabilities (IDDs). As a result, many caregivers of people with IDD feel isolated, stressed, and burnt out. A targeted research agenda informed by key stakeholders is needed and would allow research teams to coordinate resources, talents, and efforts to progress family caregiver well-being research in this area quickly and effectively. To address this aim, this pilot study used a Delphi design based on 2 rounds of questionnaires. In round 1, 19 stakeholders (18 females, 1 male), including 12 family caregivers, 3 rehabilitation providers, 2 researchers, and 2 organizational representatives, identified broad areas for caregiver well-being research. After collating the responses from round 1, stakeholders were asked to rank whether each area was considered a research priority in round 2. Data were analyzed using descriptive statistics and conventional content analysis. Eighteen stakeholders completed the round 2 survey (1 caregiver did not complete the round 2 survey), after which a consensus was reached. Stakeholders identified nine broad priorities, including system-level programs and services, models of care, health promotion, social inclusion, equity and diversity, capacity building, care planning along the lifespan, and balancing formal and natural community-based supports. Although preliminary in nature, the research priorities generated using an inclusive and systematic process may inform future efforts to promote the well-being of caregivers of Canadians with IDD.
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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 | 0.070 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.019 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 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".