MétaCan
Menu
← Back to cohort

Home-based physical activity in ILD: an RCT

2024· article· en· W4404104686 on OpenAlexaff
Cátia Paixão, Ana Sofia Grave, Vânia Fernandes, Francisca Teixeira Lopes, Maria Aurora Mendes, P. Ramalho, Pedro Gonçalo Ferreira, Dina Brooks, Alda Marques

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsHamilton Health SciencesSt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsRandomized controlled trialComputer scienceMedicineInternal medicine

Abstract

fetched live from OpenAlex

Home-based physical activity (PA) in interstitial lung disease (ILD) may be fundamental to tackle physical inactivity. We explored the efficacy and effectiveness of the Lifestyle Integrated Functional Exercise for people with ILD (iLiFE) trial ( NCT04224233 ). An RCT, assessor blinded, was conducted. After the baseline assessment, participants were randomly assigned to the experimental (EG: iLiFE-12-weeks of a home-based PA programme embedded in individuals’ daily routines) or the control (CG: usual care) group. Data were collected before and immediately after iLiFE. Primary outcome was PA (steps/day, time spent in moderate to vigorous PA [MVPA]/day/week). Secondary outcomes were symptoms, muscle strength, functional status, emotional function, healthcare utilisation, exacerbations and falls. Efficacy and effectiveness were assessed using intention-to-treat and per-protocol analysis with linear mixed methods. We included 48 participants (54% female, 67±11yrs, DLCO%p 50±17; nEG/nCG=24/24). Interaction group*time showed that iLiFE was efficacious and effective in maintaining PA levels and in improving muscle strength, functional status and health-related quality of life (p<0.05) in people with ILD (Fig. 1). No other significant interactions were observed. No adverse events were reported. iLiFE is an efficacious and effective intervention to maintain PA levels and improve other health-related domains in people with ILD and may now be considered to improve ILD management. erj;64/suppl_68/OA942/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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.072
GPT teacher head0.499
Teacher spread0.427 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicMobile Health and mHealth Applications→French-language works237,207→