| Title |
Self-management behavior among patients with diabetic retinopathy in the community: a structural equation model
|
|---|---|
| Published in |
Quality of Life Research, September 2016
|
| DOI | 10.1007/s11136-016-1396-1 |
| Pubmed ID | |
| Authors |
Li Yang, Qunhong Wu, Yanhua Hao, Yu Cui, Libo Liang, Lijun Gao, Mingli Jiao, Ning, Hong Sun, Zheng Kang, Liyuan Han, Ye Li, Hui Yin |
| Abstract |
Diabetic retinopathy (DR) is an important, chronic complication of diabetes, requiring competent self-management that depends on adherence to behavioral regimens. This study attempted to identify factors influencing self-management behaviors and develop a model illustrating the interdependence of several factors associated with DR patients. In June-December 2012, 368 patients with DR completed questionnaires assessing self-management behavior, diabetes knowledge, health beliefs, social support, and treatment adherence. Structural equation modeling was used to test predicted pathways linking self-management behavior to diabetes knowledge, health beliefs, social support, and treatment adherence. The results indicated that health beliefs, treatment adherence, and duration of diabetes each had a direct impact on diabetes self-management (p < 0.05). Diabetes knowledge only indirectly influenced diabetes self-management, through health beliefs. Social support had a direct impact on diabetes self-management (β = 0.35, p < 0.01), and an indirect influence on diabetes self-management, through treatment adherence (β = 0.77, p < 0.01). Health beliefs, treatment adherence, and social support directly affect diabetes self-management, and diabetes knowledge indirectly affects diabetes self-management. This suggests that enhancing DR patients' health beliefs, treatment adherence, and social support would facilitate their diabetes self-management. Meanwhile, improved health education can strengthen diabetes knowledge, which in turn, can positively affect diabetes self-management. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 64 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 10 | 16% |
| Student > Ph. D. Student | 8 | 13% |
| Student > Master | 8 | 13% |
| Researcher | 5 | 8% |
| Student > Postgraduate | 5 | 8% |
| Other | 13 | 20% |
| Unknown | 15 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 19 | 30% |
| Medicine and Dentistry | 11 | 17% |
| Social Sciences | 5 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 3% |
| Business, Management and Accounting | 1 | 2% |
| Other | 7 | 11% |
| Unknown | 19 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 February 2017.
All research outputs
#18,531,724
of 22,953,506 outputs
Outputs from Quality of Life Research
#2,062
of 2,907 outputs
Outputs of similar age
#258,230
of 337,249 outputs
Outputs of similar age from Quality of Life Research
#43
of 63 outputs
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