The unsung heroes: A scoping review of the experiences of lung transplant informal caregivers
Bibliographic record
Abstract
Informal caregivers support patients after lung transplantation (LTx). With growing recognition of the multiple demands placed on caregivers, this scoping review aimed to systematically map the literature surrounding informal caregiving experiences after LTx using JBI guidelines. Multiple databases were searched from January 2010 to May 2025 based on a combination of synonyms and controlled vocabulary related to "caregiver" and "lung transplant recipients". A total of 404 records were screened after the removal of duplicates. Among these, 16 sources met the inclusion criteria with 12 (75%) classified as full publications, 3 (19%) peer-reviewed conference abstracts, and 1 poster presentation. Most studies were based in North America (11/16 [69%]) with the remainder from Europe or Australia. Only 19% (3/16) of the sources were published within the past 5 years. There were 7 qualitative studies (44%), 6 quantitative (38%), 2 mixed methods (12%), and 1 literature review. Informal caregivers described a wide variety of challenges ranging from high levels of caregiver burden, psychological and emotional impacts, handling multiple daily practicalities, knowledge deficits, and the need for more support. Positive experiences of the informal caregiver role include positive adjustment, presence of support networks and relationships, improved quality of life, and benefiting from educational support and preparation. Informal caregivers remain an integral resource in supporting patients after LTx. However, most available evidence predates recent advances in transplantation practice-with 80% published before 2020-limiting its current relevance and highlighting the need for further research and targeted interventions to support this population.
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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 | 0.023 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.028 | 0.026 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".