The impact of iLiFE on informal carers of people with ILD
Bibliographic record
Abstract
Informal carers (IC) are the main source of support of people with ILD. Interventions to manage ILD involving IC are, however, scarce. We explored the impact of a home-based physical activity (PA) intervention for people with ILD (iLiFE– Lifestyle Integrated Functional Exercise for people with interstitial lung disease) on IC of people with ILD. A pre-post mixed-methods study nested in the iLiFE larger trial ( NCT04224233 ) was conducted. Measures of PA, support needs and health-related quality of life were collected at baseline and post-intervention (12-weeks) from IC. Semi-structured interviews were conducted in-person immediately after iLiFE. Interviews were audio-recorded, transcribed and analysed by deductive thematic analysis. Nine IC (5 male, 72±8y) participated. No significant differences were observed for PA, IC support needs and health-related quality of life. iLiFE promoted well-being and joy, IC own involvement, togetherness, patients’ health improvements and decrease in the burden of care (Fig. 1). This study showed that iLiFE is meaningful for IC of people with ILD, with high impact in their daily lives. Nevertheless, this intervention did not improve their PA levels, needs and health-related quality. Therefore, interventions specifically tailored to support IC of people with ILD are needed. erj;64/suppl_68/PA5022/F1 F1 F1
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".