Exploring the Parental Perspectives and Experiences With the Use of a Home Mechanical Insufflation-Exsufflation Device
Bibliographic record
Abstract
Background: A mechanical insufflation-exsufflation (MI-E) device is a commonly used tool for airway clearance in children with an ineffective cough. Whereas the device has been shown to have multiple benefits, limited evidence exists regarding parents’ experiences with its home use in the Canadian context. This study’s objective was to explore the perspectives and experiences of parents who receive service through the IWK Health Centre and use an MI-E device at home with their child. Methods: The study used an interpretive description design. Semi-structured interviews, conducted with 9 participants, were audio recorded and transcribed verbatim. Transcripts were analyzed using a reflective thematic process. Results: Seven mothers and 2 fathers were interviewed. Following analysis, 3 themes were identified: (1) Learning about the MI-E device described participants’ journey from becoming aware of the device to acquiring knowledge and skills about its use; (2) using the device detailed the integral role the MI-E device played in their lives, including decisions around use, and parental role; and (3) changing lives outlined the physical, emotional, and social benefits the device provided to the child and their family. Conclusions: Participants provided detailed descriptions of their journey from learning to integrating the MI-E device into their child’s daily routine and family life. Its multiple associated benefits improved the child’s and their family’s quality of life. However, better education on its use was highlighted as a need for both parents and the health care professionals who work with them.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".