Experiences of four parents with physical therapy and early mobility of their children in a pediatric critical care unit: A case series
Bibliographic record
Abstract
PURPOSE: The aim of this study was to conduct a preliminary investigation into parents' experiences of physical therapy and early mobility (EM) for their children in a pediatric critical care unit (PCCU). METHODS: We conducted a series of four qualitative case studies using in-depth semi-structured face-to-face interviews. We recruited parents of children who had undergone surgery and received at least one EM physical therapy intervention while intubated. We conducted a thematic analysis of transcribed interviews to illuminate the factors that influenced EM experiences. RESULTS: Four parents participated in the study. We developed an overview of Parental Experiences with Physical Therapy and Early Mobility in a PCCU, which includes four themes that parents believed influenced their experiences: (1) environmental factors; (2) awareness of physical therapist and health care professional (HCP) roles; (3) communication among parents and HCPs; and (4) parental participation in their child's EM, within the overarching parental experiences in the PCCU. CONCLUSION: This study affords a preliminary understanding of parents' experiences with physical therapy and EM in a PCCU setting. Results provide an important foundation for future research on mobility in the context of pediatric critical care research and practice.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".