scholarly journals The Relationship Between Patient Medication Adherence and Following Preventive Medicine Recommendation

2021 ◽  
Vol 34 (6) ◽  
pp. 1157-1162
Author(s):  
Michal Shani ◽  
Yochai Schonmann ◽  
Doron Comaneshter ◽  
Alex Lustman
2015 ◽  
Vol 98 (1) ◽  
pp. 120-124 ◽  
Author(s):  
Delesha M. Carpenter ◽  
Emily A. Elstad ◽  
Adam J. Sage ◽  
Lorie L. Geryk ◽  
Robert F. DeVellis ◽  
...  

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Dana Drzayich Antol ◽  
Adrianne Waldman Casebeer ◽  
Raya Khoury ◽  
Todd Michael ◽  
Andrew Renda ◽  
...  

An amendment to this paper has been published and can be accessed via the original article.


Author(s):  
Jyh-Jeng Wu ◽  
Yueh-Mei Chen ◽  
Paul C. Talley ◽  
Kuang-Ming Kuo

Effectively improving the medication adherence of patients is crucial. Past studies focused on treatment-related factors, but little attention has been paid to factors concerning human beliefs such as trust or self-efficacy. The purpose of this study is to explore the following aspects of patients with chronic diseases: (1) The relationship between emotional support, informational support, self-efficacy, and trust; (2) the relationship between self-efficacy, trust, and medication adherence; and, (3) whether chronic patients’ participation in different types of online communities brings about significant statistical differences in the relationships between the abovementioned variables. A questionnaire survey was conducted in this study, with 452 valid questionnaires collected from chronic patients previously participating in online community activities. Partial Least Squares-Structural Equation Modeling analysis showed that emotional support and informational support positively predict self-efficacy and trust, respectively, and consequently, self-efficacy and trust positively predict medication adherence. In addition, three relationships including the influence of emotional support on trust, the influence of trust on medication adherence, and the influence of self-efficacy on medication adherence, the types of online communities result in significant statistical differences. Based on the findings, this research suggests healthcare professionals can enhance patients’ self-efficacy in self-care by providing necessary health information via face-to-face or online communities, and assuring patients of demonstrable support. As such, patients’ levels of trust in healthcare professionals can be established, which in turn improves their medication adherence.


2015 ◽  
Vol 23 (1) ◽  
pp. 12-18 ◽  
Author(s):  
Lyndsay A Nelson ◽  
Shelagh A Mulvaney ◽  
Tebeb Gebretsadik ◽  
Yun-Xian Ho ◽  
Kevin B Johnson ◽  
...  

Abstract Objective Mobile health (mHealth) interventions may improve diabetes outcomes, but require engagement. Little is known about what factors impede engagement, so the authors examined the relationship between patient factors and engagement in an mHealth medication adherence promotion intervention for low-income adults with type 2 diabetes (T2DM). Materials and Methods Eighty patients with T2DM participated in a 3-month mHealth intervention called MEssaging for Diabetes that leveraged a mobile communications platform. Participants received daily text messages addressing and assessing medication adherence, and weekly interactive automated calls with adherence feedback and questions for problem solving. Longitudinal repeated measures analyses assessed the relationship between participants’ baseline characteristics and the probability of engaging with texts and calls. Results On average, participants responded to 84.0% of texts and participated in 57.1% of calls. Compared to Whites, non-Whites had a 63% decreased relative odds (adjusted odds ratio [AOR] = 0.37, 95% confidence interval [CI], 0.19-0.73) of participating in calls. In addition, lower health literacy was associated with a decreased odds of participating in calls (AOR = 0.67, 95% CI, 0.46-0.99, P = .04), whereas older age ( Pnonlinear = .01) and more depressive symptoms (AOR = 0.62, 95% CI, 0.38-1.02, P = .059) trended toward a decreased odds of responding to texts. Conclusions Racial/ethnic minorities, older adults, and persons with lower health literacy or more depressive symptoms appeared to be the least engaged in a mHealth intervention. To facilitate equitable intervention impact, future research should identify and address factors interfering with mHealth engagement.


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