“Line care governs our entire world”: Understanding the experience of caregivers of children with intestinal failure receiving long‐term parenteral nutrition
Bibliographic record
Abstract
BACKGROUND: Children with intestinal failure (IF) receiving long-term parenteral nutrition (PN) require significant medical care, including high-risk procedures such as accessing a central venous catheter, with the majority provided by family caregivers in the home. This study sought to understand the experiences of family caregivers. METHODS: This was a qualitative study of family caregivers of children with IF. Participants were recruited from an intestinal rehabilitation program to participate in virtual focus groups, which were recorded and transcribed. Thematic analysis was used to capture and describe experiences. RESULTS: Thirteen caregivers providing care to 11 children participated in three virtual focus groups held between May and June 2020. Data analysis revealed five primary themes: (1) caregiving as a 24/7 commitment, (2) facing constant risk of death, (3) chronic illness creates difficult feelings and emotions, (4) effects on all aspects of family life, and (5) adapting and functioning as a family. The findings of this study pair well with the biopsychosocial model highlighting the need for multifaceted assessment and supports. CONCLUSION: The impact of caring for a child with IF receiving long-term PN is significant for caregivers and their families and has implications for all aspects of their lives. A better understanding of the impact on caregivers and their coping strategies lays the groundwork for the optimization of quality of life for caregivers and their family.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".