Expectations for therapy in pediatric rehabilitation: reframing meaning through metaphor
Bibliographic record
Abstract
PURPOSE: To propose a holistic approach and an accompanying tool to facilitate conversations about expectations of therapy in pediatric rehabilitation based on meanings generated through metaphor. METHODS: In this study, five parents and nine service providers took part in narrative interviews. Topics included the content and development of expectations over time. Participants reviewed written summaries of their interviews and provided feedback. Data analysis was grounded in a narrative methodological approach. Multiple levels of meaning from participant experiences were constructed through a parallel thematic analysis and metaphor analysis, revealing meaning participants attributed to expectations directly, and inferred indirectly. RESULTS: The thematic analysis produced three themes related to the difficult to define characteristics and mixed value of expectations. The metaphor analysis produced four metaphorical concepts related to how expectations affect the therapy process by adding a sense of Force (i.e., therapy momentum), Appreciation (i.e., understanding of the client), Illumination (i.e., envisioning new therapy activities), and Relationship (i.e., therapeutic rapport). CONCLUSIONS: We propose the "F.A.I.R." approach and tool comprising terminology that can help reframe the meaning of expectations away from focusing on binary realistic or unrealistic outcomes, and toward focusing on a plurality of optimal therapy processes.Implications for RehabilitationMeaningful conversations about expectations for therapy between parents and service providers in pediatric rehabilitation can be challenging, one-sided, or missed.Attention to metaphors used to describe expectations for therapy introduces additional terminology parents and service providers may use to help facilitate conversations.Service providers are encouraged to use a resource proposed here to learn about parents' expectations for therapy through a collaborative process involving shared questioning, observation, and reflection.
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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 | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.006 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".