↓ Skip to main content

Validation of the Adherence Barriers Questionnaire – an instrument for identifying potential risk factors associated with medication-related non-adherence

Overview of attention for article published in BMC Health Services Research, April 2015
Altmetric Badge

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
33 Dimensions

Readers on

mendeley
173 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Validation of the Adherence Barriers Questionnaire – an instrument for identifying potential risk factors associated with medication-related non-adherence
Published in
BMC Health Services Research, April 2015
DOI 10.1186/s12913-015-0809-0
Pubmed ID
Authors

Sabrina Müller, Thomas Kohlmann, Thomas Wilke

Abstract

Medication non-adherence is a major challenge in the real-life treatment of chronically ill patients. To meet this challenge, adherence interventions with a tailored approach towards patient-specific adherence barriers that are identified with a reliable and practicable questionnaire are needed. The aim of this investigation was to develop and validate such a questionnaire, the "Adherence Barriers Questionnaire (ABQ)". The German ABQ was developed and tested in 432 patients with atrial fibrillation in a multicentre observational cohort study. Evaluation of the questionnaire included an assessment of internal consistency as well as factor analysis. Criterion-related external validity was assessed by comparing the ABQ score with (1) the degree of self-reported adherence and (2) the time in therapeutic range which describes the anticoagulation quality achieved by patients treated with oral anticoagulation. The final 14-item ABQ scale demonstrated high internal consistency (Cronbach's alpha = 0.820). Factor analysis identified a three-factor solution, representing intentional adherence barriers with 5 items (31.9% of the variance), medication-/health care system-related adherence barriers with 5 items (13.3% of the variance) and unintentional adherence barriers with 4 items (7.7% of the variance). The ABQ correlated significantly with self-reported non-adherence (Spearman's rho = 0.438, p < 0.001) as well as time in therapeutic range (Spearman's rho = - 0.161, p < 0.010). Patients with above-average ABQ scores (increased number and/or strength of existing adherence barriers) were significantly (p < 0.005, Pearson Chi-Square) more likely to have a poor anticoagulation quality (TTR < 60%) than patients with a lower ABQ score (44.6% versus 27.3%). The ABQ is a practicable, reliable and valid instrument for identifying patient-specific barriers to medication-related adherence. Future research is required to examine the ability of the ABQ to identify patient perception/behaviour changes over time which may be important for the measurement of success of adherence interventions.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 173 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Bangladesh 1 <1%
Argentina 1 <1%
Slovenia 1 <1%
Unknown 169 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 27 16%
Student > Bachelor 23 13%
Student > Ph. D. Student 21 12%
Student > Doctoral Student 18 10%
Researcher 16 9%
Other 50 29%
Unknown 18 10%
Readers by discipline Count As %
Medicine and Dentistry 53 31%
Nursing and Health Professions 27 16%
Pharmacology, Toxicology and Pharmaceutical Science 20 12%
Unspecified 8 5%
Psychology 8 5%
Other 29 17%
Unknown 28 16%

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 14 April 2015.
All research outputs
#11,165,032
of 14,080,751 outputs
Outputs from BMC Health Services Research
#3,997
of 4,770 outputs
Outputs of similar age
#157,079
of 226,288 outputs
Outputs of similar age from BMC Health Services Research
#1
of 1 outputs
Altmetric has tracked 14,080,751 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,770 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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 226,288 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them