ArticleJournal of advanced nursing2022
REducing delay through edUcation on eXacerbations for people with chronic lung disease: Study protocol of a single-arm pre-post study.
Article in Journal of advanced nursing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 6 citations in OpenAlex.
- Clinical Meaningfulness of the Composite Endpoint, COPDCompEx, in Defining Exacerbations and Worsening of COPD: A Post Hoc Analysis of 4 Clinical Interventional Studies of COPD.International journal of chronic obstructive pulmonary disease · 2026Article
- REducing delay through edUcation on eXacerbations for people with chronic lung disease: Study protocol of a single-arm pre-post study.Journal of advanced nursing · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
Abstract
aimThis study protocol aims to examine the effectiveness and preconditions of a self-management program-named REducing Delay through edUcation on eXacerbations (REDUX)-in China.
backgroundThe high disease burden in people with chronic lung disease is mainly due to exacerbations. There is a need for effective exacerbation-management interventions. A nurse-led program, REDUX, helped patients self-manage exacerbations.
designA single-arm pre-post study.
methodsFifty-four patients and 24 healthcare professionals (HCPs) in Chinese primary care will be included. The core element of the program is a personalized action plan. HCPs will receive training in using the action plan to help patients manage exacerbations. The intervention will start when a patient is referred to the nurse for a post-exacerbation consultation and ends when the patient presents for the second post-exacerbation consultation. During the first post-exacerbation consultation, the patient and nurse will create the action plan. The primary outcomes in patients will include the delays between the onset of exacerbation and recognition, between exacerbation recognition and action, between exacerbation recognition and consultation with a doctor, and when the patients feel better after receiving medical help from HCPs. The secondary outcomes will include preconditions of the program. The ethics approval was obtained in September 2021. DISCUSSION: This study will discuss a culturally adapted nurse-led self-management intervention for people with chronic lung disease in China. The intervention could help Chinese HCPs provide efficient care and reduce their workload. Furthermore, it will inform future research on tailoring nurse-led self-management interventions in different contexts. IMPACT: The study will contribute to the evidence on the effectiveness and preconditions of REDUX in China. If effective, the result will assist the nursing of people with chronic lung disease.
trial registrationRegistered in the Chinese clinical trial registry (ID: 2100051782).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.