Evidence map›Paper›PMID 37900056›Full record

ArticlePatient preference and adherence2023

Medication Bias During the Hospital-to-Family Transition Among Young and Middle-Aged Chinese Patients with Type 2 Diabetes: A Qualitative Study.

Man Yan, Peiling Zhang, Jiaxiang Yu

Open access · goldAbstract read
In one paragraph

Article in Patient preference and adherence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 39% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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 at 2 institutions in 2 countries.

Man YanDepartment of Nursing, Changzhou Hospital of Traditional Chinese Medicine, Changzhou, Jiangsu, People's Republic of China.
Peiling ZhangDepartment of Nursing, Changzhou Hospital of Traditional Chinese Medicine, Changzhou, Jiangsu, People's Republic of China.
Jiaxiang YuDepartment of Nursing, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.ORCID 0000-0001-8658-3662
Hangzhou Hospital of Traditional Chinese Medicine · CNUniversiti Putra Malaysia · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to examine the prevalence of medication non-adherence among young and middle-aged Chinese individuals diagnosed with type 2 diabetes, and to explore the underlying causes of such deviations. Methods: The Medication Discrepancy Tool (MDT) was used to assess medication deviations in a cohort of 100 patients who had been discharged from the hospital. Furthermore, 15 subjects were interviewed to gain a better understanding of their medication non-adherence experiences. Results: The rate of medication deviation in the studied cohort was 79.5%, with the most frequent deviation being a reduction in the types of drugs taken. The primary cause of this deviation was found to be patient-derived, with the most common reason being symptom improvement. Iatrogenic medication deviation was most often caused by incomplete or inaccurate medication education for medical staff at discharge, resulting in patients having to guess their own medication. Internal and extrinsic motivating factors were identified as the primary causes of medication deviation behavior. Conclusion: This study has demonstrated that medication non-adherence is a major issue among young and middle-aged Chinese individuals diagnosed with type 2 diabetes. Therefore, it is essential for nurses to be aware of the importance of medication adherence management and working.

Indexed as

medication deviationtransitional phasetype 2 diabetes mellitusyoung and middle-aged

Identifiers

PMID37900056
PMCPMC10606344
OpenAlexW4387891594

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.