Long‐Term Effects of an Automated Personalized Self‐Care Program for Patients With Type 2 Diabetes

Elevated glycated hemoglobin (HbA1c) levels and longer disease duration increase the risk of complications in type 2 diabetes mellitus (T2DM), highlighting the need for continuous management. This study evaluated the 18-month effects of the Automated Personalized Self-Care (APSC) program on self-care self-efficacy, diabetes self-care, and complication risk indices in T2DM patients through a randomized controlled trial. Participants aged 40-69 years were assigned to either an intervention group using the APSC mobile app, which provided personalized goals, automated feedback, and monthly support, or a comparison group. The final analysis included 43 engaged participants from the intervention group and 78 from the comparison group. Data were collected at baseline, 6, 12, and 18 months using structured questionnaires and medical record reviews and analyzed using generalized estimating equations. Significant effects were observed for self-care self-efficacy, diabetes self-care activities, vegetable intake, HbA1c, and total cholesterol levels. The APSC program showed potential to improve long-term self-care and reduce complication risk in T2DM patients. Further research with a larger samples and strategies to promote long-term engagement is needed for its integration into routine diabetes care. Trial Registration: Clinical Research Information Service: KCT0007672.

Authors

Institutions

Publication Details

Journal
Nursing and Health Sciences
Published
2024-12-01
DOI
https://doi.org/10.1111/nhs.70008
Citations
2
Primary Topic
Diabetes Management and Education
Type
article
Field-Weighted Citation Impact
0.72

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Long‐Term Effects of an Automated Personalized Self‐Care Program for Patients With Type 2 Diabetes

Gaeun Park, Ah Reum Khang, Min Jin Lee, Haejung Lee et al.
2 citations
Nursing and Health Sciences
Diabetes Management and Education
0.72
article

Long‐Term Effects of an Automated Personalized Self‐Care Program for Patients With Type 2 Diabetes

Gaeun Park, Ah Reum Khang, Min Jin Lee, Haejung Lee, DaeEun Lee
article en
2 citations

Abstract

Elevated glycated hemoglobin (HbA1c) levels and longer disease duration increase the risk of complications in type 2 diabetes mellitus (T2DM), highlighting the need for continuous management. This study evaluated the 18-month effects of the Automated Personalized Self-Care (APSC) program on self-care self-efficacy, diabetes self-care, and complication risk indices in T2DM patients through a randomized controlled trial. Participants aged 40-69 years were assigned to either an intervention group using the APSC mobile app, which provided personalized goals, automated feedback, and monthly support, or a comparison group. The final analysis included 43 engaged participants from the intervention group and 78 from the comparison group. Data were collected at baseline, 6, 12, and 18 months using structured questionnaires and medical record reviews and analyzed using generalized estimating equations. Significant effects were observed for self-care self-efficacy, diabetes self-care activities, vegetable intake, HbA1c, and total cholesterol levels. The APSC program showed potential to improve long-term self-care and reduce complication risk in T2DM patients. Further research with a larger samples and strategies to promote long-term engagement is needed for its integration into routine diabetes care. Trial Registration: Clinical Research Information Service: KCT0007672.

Nursing and Health SciencesVol. 26(4)
Pusan National University Yangsan Hospital (KR), Pusan National University (KR)
National Research Foundation, National Research Foundation of Korea
Good health and well-being
Openalex Percentile: Top 24%
Diabetes Management and Education
0.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.