Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedGetRelatedKeyword
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Function: require_once
Background: Medication adherence is frequently suboptimal in adults with chronic diseases, resulting in negative consequences. Traditional interventions to improve adherence are complex and not widely effective. Mobile applications may be a scalable means to support medication adherence.
Objective: To investigate the effect of mobile apps on medication adherence in adults with chronic diseases.
Methods: MEDLINE, EMBASE, CINAHL Plus, Cochrane Central Register of Controlled Trials, and Web of Science were searched for randomized controlled trials evaluating the effectiveness of any mobile application (app) intervention directed at patients with chronic disease to improve medication adherence in comparison with usual care. A random-effects model was used to pool the outcome data. Risk of bias and quality of study were assessed per Cochrane guidelines.
Results: Fourteen studies were included in this systematic review involving 1,785 participants, 940 of whom were randomized to a mobile app intervention group and 845 to the usual care group. The meta-analysis showed that the use of mobile apps was associated with a significant improvement in patient adherence to medication (Cohen's d = 0.40, 95% CI = 0.27-0.52; < 0.001), with a low quality of GRADE evidence. There was no evidence of publication bias (Egger's test; = 0.81) or substantial heterogeneity (I = 29%). In the sensitivity analysis, our findings remained robust to change in inclusion criteria based on study quality (Cohen's d = 0.43, 95% CI = 0.33-0.54; < 0.001). The included apps incorporated 9 features, sorted from high to low based on relative weights (RW): documentation (RW = 0.254), medication reminder (RW = 0.204), data sharing (RW = 0.148), feedback message (RW = 0.104), clinical decision support (RW = 0.097), education (RW = 0.081), customization (RW = 0.049), data statistics (RW = 0.041), and appointment reminder (RW = 0.041). In the subgroup analysis, the effect was not sensitive to study characteristics or app features (0.37 ≤ ≤ 0.95). App acceptability was reported by participants in the intervention group in 8 studies: 144 of 156 participants (91.7%) were satisfied with all aspects of the apps.
Conclusions: Compared with conventional care, mobile apps are effective interventions to help improve medication adherence in adults with chronic diseases. Although promising, these results should be interpreted with caution given the low level of evidence and short intervention duration. Future research will not only need to identify ideal app features and the costs to providers but also need to improve the apps to make them user friendly, secure, and effective based on patient-centered theory.
Disclosures: Funding for this study was provided by Chongqing Science and Technology Bureau (No. cstc2017shmsA130115). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors have no conflicts of interest to disclose.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391210 | PMC |
http://dx.doi.org/10.18553/jmcp.2020.26.4.550 | DOI Listing |
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