Evidence map›Paper›PMID 34145856›Full record

ArticleBeijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences2021

[To explore medication adherence of patients with type 2 diabetes mellitus using the latent profile analysis based on the Big Five personality theory].

P Chen, Z M Li, Y Guo, X Y Sun, B Edwin

Open access · greenAbstract read
In one paragraph

Article in Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 91% of its field
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

P ChenDepartment of Social Medicine and Health Education, Peking University School of Public Health, Beijing 100191, China.
Z M LiDepartment of Social Medicine and Health Education, Peking University School of Public Health, Beijing 100191, China.
Y GuoDepartment of Social Medicine and Health Education, Peking University School of Public Health, Beijing 100191, China.
X Y SunDepartment of Social Medicine and Health Education, Peking University School of Public Health, Beijing 100191, China.
B EdwinDepartment of Health Behavior, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, North Carolina 27599-7440, USA.
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore the personality portraits of patients with type 2 diabetes mellitus (T2DM), its relationship with medication adherence and the influencing factors of medication adherence.

methodsT2DM patients from 22 community health service stations of 4 community health service centers in Tongzhou district and Shunyi district in Beijing were selected as the research objects. A self-designed questionnaire was used to collect demographic information. The short version of Big Five personality scale was used to collect personality information, and latent profile analysis was used to explore their personality portraits. The medication adherence was evaluated by medication adherence scale, and the difference of medication adherence among the different personality portraits was explored by analysis of variance. The influencing factors of medication adherence were explored by the ordinal Logistic regression model.

resultsIn the study, 751 T2DM patients were included. Latent profile analysis showed that the T2DM patients in this study could be divided into four types of personality portraits, including introverted and stable type (42.7%), negative type (12.7%), anxiety type (15.3%) and active and responsible type (29.3%). Among them, 75 patients said that they did not use medicine or insulin, 5 patients were lack of data, and finally 671 patients with T2DM were included in the analysis about medication adherence. The analysis of variance showed that there was no significant difference in medication adherence between anxiety type (5.55±1.65) and negative type (5.94±1.53,

conclusionT2DM can be classified into four types of personality portraits based on Big Five personality theory. The anxiety and negative type after the combination of anxiety type and negative type is the independent risk factor for poor medication adherence. In addition, education level is also the influencing factor of medication compliance.

Indexed as

Diabetes Mellitus, Type 2AnxietyBeijingHumansMedication AdherencePersonalityBig Five personality theoryLatent profile analysisMedication adherencePersonality portraitType 2 diabetes mellitus

Identifiers

PMID34145856
PMCPMC8220047
OpenAlexW3171532397

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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.