↓ Skip to main content

Does a multimethod approach improve identification of medication nonadherence in adolescents with chronic kidney disease?

Overview of attention for article published in Pediatric Nephrology, August 2018
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 3,596)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
8 news outlets
twitter
3 X users
facebook
2 Facebook pages

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
67 Mendeley
Title
Does a multimethod approach improve identification of medication nonadherence in adolescents with chronic kidney disease?
Published in
Pediatric Nephrology, August 2018
DOI 10.1007/s00467-018-4044-x
Pubmed ID
Authors

Cozumel S. Pruette, Shayna S. Coburn, Cyd K. Eaton, Tammy M. Brady, Shamir Tuchman, Susan Mendley, Barbara A. Fivush, Michelle N. Eakin, Kristin A. Riekert

Abstract

Medical provider assessment of nonadherence is known to be inaccurate. Researchers have suggested using a multimethod assessment approach; however, no study has demonstrated how to integrate different measures to improve accuracy. This study aimed to determine if using additional measures improves the accurate identification of nonadherence beyond provider assessment alone. Eighty-seven adolescents and young adults (AYAs), age 11-19 years, with chronic kidney disease (CKD) [stage 1-5/end-stage renal disease (ESRD)] and prescribed antihypertensive medication, their caregivers, and 17 medical providers participated in the multisite study. Five adherence measures were obtained: provider report, AYA report, caregiver report, electronic medication monitoring (MEMS), and pharmacy refill data [medication possession ratio (MPR)]. Concordance was calculated using kappa statistic. Sensitivity, specificity, positive predictive power, and negative predictive power were calculated using MEMS as the criterion for measuring adherence. There was poor to fair concordance (kappas = 0.12-0.54), with 35-61% of AYAs classified as nonadherent depending on the measure. While both providers and MEMS classified 35% of the AYAs as nonadherent, sensitivity (0.57) and specificity (0.77) demonstrated poor agreement between the two measures on identifying which AYAs were nonadherent. Combining provider report of nonadherence and MPR < 75% resulted in the highest sensitivity for identifying nonadherence (0.90) and negative predictive power (0.88). Nonadherence is prevalent in AYAs with CKD. Providers inaccurately identify nonadherence, leading to missed opportunities to intervene. Our study demonstrates the benefit to utilizing a multimethod approach to identify nonadherence in patients with chronic disease, an essential first step to reduce nonadherence.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 13%
Student > Master 9 13%
Student > Ph. D. Student 5 7%
Librarian 4 6%
Lecturer 4 6%
Other 10 15%
Unknown 26 39%
Readers by discipline Count As %
Nursing and Health Professions 8 12%
Medicine and Dentistry 8 12%
Social Sciences 8 12%
Psychology 6 9%
Pharmacology, Toxicology and Pharmaceutical Science 5 7%
Other 5 7%
Unknown 27 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 60. 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 08 January 2019.
All research outputs
#609,376
of 23,100,534 outputs
Outputs from Pediatric Nephrology
#16
of 3,596 outputs
Outputs of similar age
#13,369
of 301,794 outputs
Outputs of similar age from Pediatric Nephrology
#1
of 92 outputs
Altmetric has tracked 23,100,534 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,596 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 301,794 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 92 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.