Bibliographic record
Abstract
Objectives: To increase public and professional understanding of caregiving experiences of people who care for adults with chronic physical illness; to promote the use of caregivers’ lived experiences in the education of healthcare professionals.Methods: Part 1: 40 qualitative audio/video recorded interviews were conducted with adult caregivers in a maximum variation sample from across Canada. Data collection and analysis is via rigorous qualitative research. 25 topics or themes are identified reflective of the participants’ concerns, meanings and priorities.Results including video, audio or text clips, and evidence-informed resources are published on www.healthexperiences.ca. The methods are adopted from the award-winning website (www.healthtalkonline.org) from Oxford University, UK.Part 2: collaboration with healthcare professionals, educational experts, researchers and caregivers to design educational modules to be piloted in University setting for healthcare professional education.Results: Caregivers described their experiences with the healthcare system as part of their role. They provide advice to health care professionals about issues such as access to information and services, attitude and behaviours, the impact of caregiving on their own well-being , and reflections on their role. Participants emphasize the importance of recognition for their role as part of the care team for patients with chronic physical illnesses. Some described the need for the healthcare system to consider caregivers as an important component in the ‘a circle of care’ around the patient. If caregivers suffer physical or mental illness, burn-out or lack of resources, the support system for the patient falls away. Educational modules featuring video and audio clips of caregivers’ stories are powerful educational tools in developing healthcare professional sensitivity to these issues in patient care.Conclusion: The www.healthexperiences.ca / www.experiencessante.ca sites are unique in Canada in the field of patient experiences and healthcare communication. It is a great resource to educate health care professionals about the caregivers’ perspective on caring for adults with chronic physical illness.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".