Characteristics of Diabetes Self-Care Agency in Japan Based on Statistical Cluster Analysis

Introduction Considering the situation where the number of people with diabetes is increasing, we need to find ways to support more efficient and effective outpatient clinics. Therefore, it is necessary to develop effective support methods and to elaborate a strategy as a system for support after gr...

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Main Authors: Eiko Umeda MSN, Yasuko Shimizu PhD, Kyoko Uchiumi PhD, Naoko Murakado MSN, Kumiko Kuroda PhD, Harue Masaki PhD, Natsuko Seto PhD, Hidetoki Ishii PhD
Format: Article
Language:English
Published: SAGE Publishing 2020-01-01
Series:SAGE Open Nursing
Online Access:https://doi.org/10.1177/2377960820902970
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spelling doaj-dc6a5a47d8a948158ee48ad17f1482a82020-11-25T03:34:41ZengSAGE PublishingSAGE Open Nursing2377-96082020-01-01610.1177/2377960820902970Characteristics of Diabetes Self-Care Agency in Japan Based on Statistical Cluster AnalysisEiko Umeda MSNYasuko Shimizu PhDKyoko Uchiumi PhDNaoko Murakado MSNKumiko Kuroda PhDHarue Masaki PhDNatsuko Seto PhDHidetoki Ishii PhDIntroduction Considering the situation where the number of people with diabetes is increasing, we need to find ways to support more efficient and effective outpatient clinics. Therefore, it is necessary to develop effective support methods and to elaborate a strategy as a system for support after grasping the characteristics of the entire population of people with diabetes. Objective The purpose of this study was to identify the characteristics of the diabetes population in outpatient settings by differences in self-care agency and to examine how to support them based on the recognized characteristics. Methods Participants were 261 people with diabetes under outpatient care in Japanese institutions from whom demographic data on age, gender, HbA1c, and treatment method were collected as well as self-care agency data based on the Instrument of Diabetes Self-Care Agency consisting of 40 items. The data were analyzed using cluster analysis to compare age, gender, HbA1c, duration of diabetes, type of diabetes, and insulin therapy between clusters. Results The analysis identified six clusters, including a group with favorable HbA1c but low total self-care agency scores that were likely to affect their blood glucose control in the future, although accounting for as small a portion as 3% of the total. In addition, a cluster with poor HbA1c and generally low self-care agency was also identified accounting for about a quarter of the total population. These clusters were considered to require further support. Clusters having markedly low self-care agency items, stress-coping ability, or the ability to make the most of the support available were also identified. Conclusion The six clusters need to be assisted in focusing on mental or social support. Accordingly, consideration of the support system for people with diabetes based on an understanding of the cluster characteristics seemed to enable more efficient and effective support.https://doi.org/10.1177/2377960820902970
collection DOAJ
language English
format Article
sources DOAJ
author Eiko Umeda MSN
Yasuko Shimizu PhD
Kyoko Uchiumi PhD
Naoko Murakado MSN
Kumiko Kuroda PhD
Harue Masaki PhD
Natsuko Seto PhD
Hidetoki Ishii PhD
spellingShingle Eiko Umeda MSN
Yasuko Shimizu PhD
Kyoko Uchiumi PhD
Naoko Murakado MSN
Kumiko Kuroda PhD
Harue Masaki PhD
Natsuko Seto PhD
Hidetoki Ishii PhD
Characteristics of Diabetes Self-Care Agency in Japan Based on Statistical Cluster Analysis
SAGE Open Nursing
author_facet Eiko Umeda MSN
Yasuko Shimizu PhD
Kyoko Uchiumi PhD
Naoko Murakado MSN
Kumiko Kuroda PhD
Harue Masaki PhD
Natsuko Seto PhD
Hidetoki Ishii PhD
author_sort Eiko Umeda MSN
title Characteristics of Diabetes Self-Care Agency in Japan Based on Statistical Cluster Analysis
title_short Characteristics of Diabetes Self-Care Agency in Japan Based on Statistical Cluster Analysis
title_full Characteristics of Diabetes Self-Care Agency in Japan Based on Statistical Cluster Analysis
title_fullStr Characteristics of Diabetes Self-Care Agency in Japan Based on Statistical Cluster Analysis
title_full_unstemmed Characteristics of Diabetes Self-Care Agency in Japan Based on Statistical Cluster Analysis
title_sort characteristics of diabetes self-care agency in japan based on statistical cluster analysis
publisher SAGE Publishing
series SAGE Open Nursing
issn 2377-9608
publishDate 2020-01-01
description Introduction Considering the situation where the number of people with diabetes is increasing, we need to find ways to support more efficient and effective outpatient clinics. Therefore, it is necessary to develop effective support methods and to elaborate a strategy as a system for support after grasping the characteristics of the entire population of people with diabetes. Objective The purpose of this study was to identify the characteristics of the diabetes population in outpatient settings by differences in self-care agency and to examine how to support them based on the recognized characteristics. Methods Participants were 261 people with diabetes under outpatient care in Japanese institutions from whom demographic data on age, gender, HbA1c, and treatment method were collected as well as self-care agency data based on the Instrument of Diabetes Self-Care Agency consisting of 40 items. The data were analyzed using cluster analysis to compare age, gender, HbA1c, duration of diabetes, type of diabetes, and insulin therapy between clusters. Results The analysis identified six clusters, including a group with favorable HbA1c but low total self-care agency scores that were likely to affect their blood glucose control in the future, although accounting for as small a portion as 3% of the total. In addition, a cluster with poor HbA1c and generally low self-care agency was also identified accounting for about a quarter of the total population. These clusters were considered to require further support. Clusters having markedly low self-care agency items, stress-coping ability, or the ability to make the most of the support available were also identified. Conclusion The six clusters need to be assisted in focusing on mental or social support. Accordingly, consideration of the support system for people with diabetes based on an understanding of the cluster characteristics seemed to enable more efficient and effective support.
url https://doi.org/10.1177/2377960820902970
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