Illuminating their reality: the use of metaphor by parents of children with disabilities to express their experiences of health care
Bibliographic record
Abstract
Purpose To explore the nature and meaning of metaphors used by parents of children with disabilities when describing their healthcare experiences.Method A systematic procedure was used to identify and analyze metaphors spontaneously mentioned by parents in 13 focus groups held with 65 Canadian parents of children with disabilities. Attention was paid to identifying deep (i.e., meaningful) metaphors rather than common expressions.Results A total of 214 deep metaphors were identified and categorized into four target-source groupings. Parents used journey metaphors to describe experiences of uncertainty, conflict and harm metaphors to describe confrontational, harmful, and demeaning experiences of care, games and puzzles to describe the unknowns of care and attempts to resolve these unknowns, and metaphors concerning environmental barriers (i.e., walls and doors) to express feelings of exclusion and difficulties accessing care.Conclusions Parents’ metaphors expressed experiences of uncertainty, powerlessness, and attempts to exert agency in healthcare interactions. The metaphorical groupings provide new insights into how and why lack of family-centeredness in service delivery is bewildering, distressing, and disempowering to parents. Implications for service providers include paying attention to what metaphor use reveals about parents’ experiences, and discussing parents’ metaphors with them to create joint understanding, providing a fertile ground for 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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".