Evidence map›Paper›PMID 35624424›Full record

ArticleBMC infectious diseases2022

Development and validation of self-management scale for tuberculosis patients.

Jin Li, Liwen Zhang, Jiani Zhou, Geng Wang, Rui Zhang, Jiaqing Liu, Shili Liu, Yong Chen, Song Yang, Quan Yuan and 1 more

Abstract read
In one paragraph

Article in BMC infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Jin LiDepartment of Social Medicine and Health Service Management, Army Medical University (Third Military Medical University), Chongqing, China.
Liwen ZhangChongqing Public Health Medical Center, Chongqing, China.
Jiani ZhouDepartment of Social Medicine and Health Service Management, Army Medical University (Third Military Medical University), Chongqing, China.
Geng WangDepartment of Social Medicine and Health Service Management, Army Medical University (Third Military Medical University), Chongqing, China.
Rui ZhangDepartment of Social Medicine and Health Service Management, Army Medical University (Third Military Medical University), Chongqing, China.
Jiaqing LiuDepartment of Social Medicine and Health Service Management, Army Medical University (Third Military Medical University), Chongqing, China.
Shili LiuDepartment of Social Medicine and Health Service Management, Army Medical University (Third Military Medical University), Chongqing, China.
Yong ChenDepartment of Social Medicine and Health Service Management, Army Medical University (Third Military Medical University), Chongqing, China.
Song YangChongqing Public Health Medical Center, Chongqing, China.
Quan YuanDepartment of Social Medicine and Health Service Management, Army Medical University (Third Military Medical University), Chongqing, China.
Ying LiDepartment of Social Medicine and Health Service Management, Army Medical University (Third Military Medical University), Chongqing, China. lilyliying2012@163.com.

Funding

Chongqing outstanding youth project cstc2020jcyj-jqX0007National Natural Science Foundation of China 81773489
6 · The paper itself

Abstract

backgroundTuberculosis remains a major threat to global public health. Regarding its control, directly observed therapy is not suitable as a global strategy for all tuberculosis patients. Self-management may be an important patient-centered tuberculosis case management supplement to directly observed therapy. However, there is currently no well-established instrument for measuring the self-management of tuberculosis patients. This study aimed to develop and validate a self-management scale for tuberculosis patients.

methodsWe developed an initial scale based on the tuberculosis health promotion indicators framework developed by our research group. After item analysis and two rounds of exploratory factor analysis, a final version of the scale was developed. A survey of 462 tuberculosis patients was conducted to develop and validate this scale. Cronbach's α and intraclass correlation coefficients were used to assess reliability, and Pearson's correlation coefficients were used to evaluate content validity. Fit indices, convergent validity, and discriminant validity were evaluated using confirmatory factor analysis to determine the construct validity of the scale.

resultsThe scale was composed of 17 items in three dimensions ("adherence to treatment behavior," "transmission prevention behavior," and "supportive therapy behavior"). These three dimensions explained 76.60% of the variance. Cronbach's α of the scale was 0.905, and the intraclass correlation coefficient was 0.897. Additionally, Pearson's correlation analysis showed that each item was strongly correlated with the dimension to which it belonged (r = 0.849-0.915, p < 0.01). Most fit indices (Comparative Fit Index, Normed Fit Index, Incremental Fit Index, Goodness of fit index) reached the recommended threshold, and the average variance extracted values of the three dimensions were higher than 0.5. The values of the square root of the average variance extracted within each dimension were greater than the correlation between dimensions, and all heterotrait-monotrait values were below 0.85.

conclusionsThe self-management scale for tuberculosis patient demonstrated good reliability and validity and could be used as an instrument to evaluate the self-management of patients. Additionally, it could be used to develop evidence-based self-management interventions and evaluate those interventions.

Indexed as

Self-ManagementTuberculosisCase ManagementDirectly Observed TherapyHumansReproducibility of ResultsInstrument developmentSelf-managementTuberculosis

Identifiers

PMID35624424
PMCPMC9137130

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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.