Evidence map›Paper›PMID 31469852›Full record

ArticlePloS one2019

Implicit and explicit attitudes towards disease-modifying antirheumatic drugs as possible target for improving medication adherence.

M van Heuckelum, A J Linn, L Vandeberg, R C F Hebing, L van Dijk, M Vervloet, M Flendrie, M T Nurmohamed, S van Dulmen, B J F van den Bemt and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.7field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Trial
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 6 institutions in 2 countries.

M van HeuckelumDepartment of Rheumatology, Sint Maartenskliniek, Nijmegen, The Netherlands.ORCID 0000-0001-7179-4475
A J LinnAmsterdam School of Communication Research, University of Amsterdam, Amsterdam, The Netherlands.
L VandebergAmsterdam School of Communication Research, University of Amsterdam, Amsterdam, The Netherlands.
R C F HebingDepartment of Rheumatology, Amsterdam Rheumatology and Immunology Center, Reade, Amsterdam, The Netherlands.
L van DijkNivel (Netherlands Institute for Health Services Research), Utrecht, The Netherlands.
M VervloetNivel (Netherlands Institute for Health Services Research), Utrecht, The Netherlands.
M FlendrieDepartment of Rheumatology, Sint Maartenskliniek, Nijmegen, The Netherlands.
M T NurmohamedDepartment of Rheumatology, Amsterdam Rheumatology and Immunology Center, Reade, Amsterdam, The Netherlands.
S van DulmenNivel (Netherlands Institute for Health Services Research), Utrecht, The Netherlands.
B J F van den BemtDepartment of Pharmacy, Sint Maartenskliniek, Nijmegen, The Netherlands.
C H M van den EndeDepartment of Rheumatology, Sint Maartenskliniek, Nijmegen, The Netherlands.
Radboud University Nijmegen · NLReade · NLSint Maartenskliniek · NLNetherlands Institute for Health Services Research · NLUniversity of Amsterdam · NLUniversity of Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aims to explore the contribution of implicit attitudes and associations towards conventional disease-modifying antirheumatic drugs (cDMARDs), alongside explicit measures, on medication-taking behaviour and clinical outcomes in adult patients with rheumatoid arthritis (RA).

methodsIn this observational study, implicit attitudes (positive-negative) and health-related associations (health-sickness) were measured with Single Category Implicit Association Tests, whereas explicit outcomes were measured with a bipolar evaluative adjective scale and the Beliefs about Medicines Questionnaire Specific. The primary outcome of this study was medication-taking behaviour subjectively measured by self-report (i.e. validated Compliance Questionnaire on Rheumatology) and objectively measured with electronic drug monitors over a 3 month period. Spearman rank correlations were used to describe correlations between implicit and explicit outcomes. Nested linear regression models were used to assess the additional value of implicit measures over explicit measures and patient-, clinical-, and treatment-related characteristics.

resultsOf the 1659 initially-invited patients, 254 patients with RA agreed to participate in this study. Implicit attitudes correlated significantly with necessity-concerns differential (NCD) scores (ρ = 0.13, P = 0.05) and disease activity scores (ρ = -0.17, P = 0.04), whereas implicit health-related associations correlated significantly with mean scores for explicitly reported health-related associations (ρ = 0.18, P = 0.004). Significant differences in age, number of DMARDs, biologic DMARD use, NCD-scores, and self-reported correct dosing were found between the four attitudinal profiles. Nested linear regression models revealed no additional value of implicit measures in explaining self-reported medication-taking behaviour and clinical outcomes, over and above all other variables.

conclusionImplicit attitudes and associations had no additional value in explaining medication-taking behaviour and clinical outcomes over and above often used explicitly measured characteristics, attitudes and outcomes in the studied population. Only age and NCD scores contributed significantly when the dependent variable was correct dosing measured with self-report.

Indexed as

Medication AdherenceAdultAntirheumatic AgentsArthritis, RheumatoidAttitudeEducation, MedicalFemaleHumansMaleMiddle AgedPatientsSelf ReportSurveys and QuestionnairesAntirheumatic Agents

Identifiers

PMID31469852
PMCPMC6716669
OpenAlexW2971264194

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.