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Record W4414919522 · doi:10.2147/copd.s534600

Development of a Multivariable Predictive Model for Adherence to Remotely Monitored Home-Based Pulmonary Rehabilitation in Patients with Chronic Obstructive Pulmonary Disease

2025· article· en· W4414919522 on OpenAlexaboutno aff
Sheng Ye, Zi Chen, Tingting Xia, Caihua Wang, Biyun Xu, Qin Li, Cheng Wang, Ye Zhang, Zhifei Yin, Jian Wang

Bibliographic record

VenueInternational Journal of COPD · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsnot available
FundersGovernment of Jiangsu Province
KeywordsSocial cognitive theoryPulmonary diseaseCognitionIntervention (counseling)RehabilitationMultivariable calculusDiseasePopulation

Abstract

fetched live from OpenAlex

Purpose: This study aimed to explore factors affecting adherence to remote home-based pulmonary rehabilitation (PR) in patients with stable chronic obstructive pulmonary disease (COPD) and to develop a predictive model. Patients and Methods: This multicenter, cross-sectional survey study included 86 patients who underwent 12 weeks of health education-integrated, home-based PR with remote monitoring. Patients were stratified into high-completion (HC, ≥ 70%) and low-completion (LC, < 70%) groups. Demographic data, clinical features, and psychological parameters were analyzed. Receiver operating characteristic curve and area under the curve (AUC) analyses evaluated the predictive performance of key indicators. Binary logistic regression identified four predictors: Pulmonary Rehabilitation Adapted Index of Self-Efficacy (PRAISE), Outcome Expectations for Exercise Scale (OEE), Montreal Cognitive Assessment (MoCA), and Visual Analog Scale (VAS). These components formed an optimized predictive model with corresponding formula and cutoff values. Results: A cross-sectional survey of 71 patients, 44 in the HC group and 27 in the LC group, revealed significantly higher scores in the HC group in the following domains of the 36-Item Short Form Health Survey (SF-36), including physical functioning, role limitations due to physical health, role limitations due to emotional problems, energy/fatigue, mental health, and social functioning, as well as in the MoCA scores (all p-values < 0.05). Significant intergroup differences were also observed in PRAISE, OEE and VAS scores (all p < 0.001). PRAISE (AUC = 0.810), OEE (AUC = 0.784), MoCA (AUC = 0.719), and VAS (AUC = 0.801) demonstrated discriminatory power in assessing PR adherence. The combined predictive model achieved an AUC of 0.895 (95% confidence interval: 0.812-0.977, p < 0.05), with 77.8% sensitivity and 93.2% specificity. Conclusion: Social cognitive theory (SCT) originated from social learning theory. It explains human behavior through a triadic, dynamic, and reciprocal model. This model posits continuous interaction among an individual's behavior, cognitive factors, and environmental context. The four-variable predictive model, based on SCT, effectively evaluates adherence to home-based PR under remote monitoring in patients with COPD. Among the indicators in the four-variable model, PRAISE shows potential as a target for intervention to enhance PR completion rates.

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)0.005
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.014
GPT teacher head0.304
Teacher spread0.290 · 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 designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

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