Evidence map›Paper›PMID 39391516›Full record

ArticleHeliyon2024

Trajectory and predictors of adherence to Nucleos(t)ide analogues medication among patients with chronic hepatitis B.

Lin Zhang, Jinping Tian, Di Xu, Yunyue Liu, Zhenjiang Zhang

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

5 authors.

Lin ZhangDepartment of Infectious Diseases, The Affiliated Suqian First People's Hospital of Nanjing Medical University, Suqian, Jiangsu Province, China.
Jinping TianDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China.
Di XuNanjing Drum Tower Hospital, Nanjing, Jiangsu Province, China.
Yunyue LiuZhongnan Hospital of Wuhan University, Wuhan, Hubei Province, China.
Zhenjiang ZhangDepartment of Infectious Diseases, The Affiliated Suqian First People's Hospital of Nanjing Medical University, Suqian, Jiangsu Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To investigate the developmental trajectory of medication adherence and its predictors in chronic hepatitis B (CHB) patients taking nucleos(t)ide analogues. Methods: A longitudinal study was conducted. Patients with CHB who met the inclusion criteria were selected using convenience sampling. Follow-ups were conducted at baseline, 3 months, 6 months, 9 months, and 12 months. Medication adherence was assessed using a medication adherence scale. Group-based trajectory modeling (GBTM) was used to explore medication adherence trajectories, and repeated measures ANOVA was used to describe changes in each trajectory. Unordered multinomial logistic regression analysis was used to explore predictive factors. Results: A total of 305 patients completed all follow-ups. Medication adherence was categorized into four trajectory groups: low adherence (4.9 %), decreasing adherence (24.3 %), increasing adherence (48.2 %), and high adherence (22.6 %). Multinomial logistic regression results showed that HBV-infected discrimination, depression, self-efficacy, and social support were significantly different among different medication adherence levels (p < 0.05). Conclusions: Medication adherence trajectories in patients with CHB exhibit heterogeneity. Healthcare professionals can develop personalized treatment plans based on patients' social and psychological characteristics to improve medication adherence.

Indexed as

Chronic hepatitis BMedication adherencePredictive factorsTrajectory

Identifiers

PMID39391516
PMCPMC11466648

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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.