Evidence map›Paper›PMID 39211465›Full record

ArticleBelitung nursing journal2024

Adherence to treatment in pulmonary tuberculosis: Rodgers' evolutionary concept analysis.

Yunus Adhy Prasetyo, Sureeporn Thanasilp, Sunida Preechawong

Abstract read
In one paragraph

Article in Belitung nursing journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Yunus Adhy PrasetyoFaculty of Nursing, Chulalongkorn University, Bangkok, Thailand.ORCID https://orcid.org/0000-0001-7790-3820
Sureeporn ThanasilpFaculty of Nursing, Chulalongkorn University, Bangkok, Thailand.ORCID https://orcid.org/0000-0001-6638-2863
Sunida PreechawongFaculty of Nursing, Chulalongkorn University, Bangkok, Thailand.ORCID https://orcid.org/0000-0002-7116-6038

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Adherence to treatment is essential for the management of pulmonary tuberculosis. Nurses and healthcare professionals play a significant role in promoting adherence behavior among this population. Nevertheless, defining adherence to treatment within this particular population remains complex. Objective: This study aimed to explore and clarify the concept of adherence to treatment among individuals with pulmonary tuberculosis. Methods: Rodgers' evolutionary concept analysis was employed in this study. A literature search was conducted in the PubMed and Scopus databases to identify relevant studies published between July 2013 and July 2023. Results: The attributes of adherence to treatment in pulmonary tuberculosis consist of multiple components: biological, individual, social, health service, and policy-making processes. Antecedents include various patient-related factors as well as factors associated with clinical conditions and patient-health professional engagement. Three consequences of the concept have emerged: enhanced treatment efficacy, increased commitment to tuberculosis treatment adherence, and improved health service quality. Conclusion: This study provides a comprehensive operational definition of adherence to tuberculosis treatment, including its attributes, antecedents, and consequences. This framework will assist nurses in evaluating adherence more effectively. However, further research into the experiences of individuals adhering to tuberculosis treatment is needed to confirm and enhance these strategies.

Indexed as

concept analysishealth servicespulmonary tuberculosistreatment adherence

Identifiers

PMID39211465
PMCPMC11350354

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.