A Qualitative Study to Explore the Needs of Lung Transplant Caregivers
Bibliographic record
Abstract
INTRODUCTION: Providing support throughout the lung transplant process is an intensive task, which requires a dedicated caregiver. The needs of caregivers who must relocate with their loved one receiving the transplant are currently unknown. The objective of this study is to explore experiences and perceptions of lung transplant caregivers identified from a satellite clinic to inform the development of educational resources. METHODS: A qualitative study with a phenomenology approach was undertaken with individuals who have taken on the role of a caregiver for lung transplant candidates or recipients and must travel to the specialized transplant center. Semistructured interviews were conducted with 12 caregivers. Interviews conducted by phone were audio-recorded and then transcribed verbatim. NVivo software was used to code the data and identify emerging themes. RESULTS: Ideas were classified into the following 4 themes: (1) the stress of being a caregiver, (2) caregivers undertake a variety of roles, (3) caregivers require support, and (4) satisfaction with health care providers. Even though the caregivers lived an average of 7.1 (standard deviation 2) hours from the surgical transplant center, all expressed satisfaction with the level of care that they received. Caregivers identified several stressors during the transplant process and described various strategies for coping. CONCLUSION: Caregivers shared their experiences on the transplant process. It was evident that being a caregiver was a stressful and supports were necessary for those undertaking this role. These insights will help inform the development of a new educational resource for patients and caregivers.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".