Comparison of anonymous versus nonanonymous responses to a medication adherence questionnaire in patients with Parkinson's disease.

Parkinson’s disease adherence questionnaire anonymous nonadherence self-report

Journal

Patient preference and adherence
ISSN: 1177-889X
Titre abrégé: Patient Prefer Adherence
Pays: New Zealand
ID NLM: 101475748

Informations de publication

Date de publication:
2019
Historique:
entrez: 31 1 2019
pubmed: 31 1 2019
medline: 31 1 2019
Statut: epublish

Résumé

Adherence to medication can be assessed by various self-report questionnaires. One could hypothesize that survey respondents tend to answer questions in a manner that will be viewed favorably by others. We aimed to answer if anonymous and nonanonymous responses to a questionnaire on medication adherence differ. Adherence was assessed with the German Stendal Adherence with Medication Score (SAMS), which includes 18 questions with responses based on a 5-point Likert scale. Anonymous data from 40 subjects were collected during a symposium for patients with Parkinson's disease (PD), and nonanonymous data were obtained from 40 outpatient-clinic PD patients at the Department of Neurology. The two groups (anonymous self-reported questionnaire and nonanonymous) did not differ in terms of demographical characteristics and the SAMS sum score. However, anonymously collected data showed significant higher scoring for the item 6 ("Do you forget your medications?") than the data collected nonanonymously ( Overall assessment of adherence does not depend on whether the patient remains anonymous or not. There seems to be no relevant social desirability bias in nonanonymous responses.

Identifiants

pubmed: 30697036
doi: 10.2147/PPA.S186732
pii: ppa-13-151
pmc: PMC6342145
doi:

Types de publication

Journal Article

Langues

eng

Pagination

151-155

Déclaration de conflit d'intérêts

Disclosure The authors report no conflicts of interest in this work.

Références

Med Care. 2004 Mar;42(3):200-9
pubmed: 15076819
Ann Pharmacother. 2004 Sep;38(9):1363-8
pubmed: 15238622
J Clin Hypertens (Greenwich). 2008 May;10(5):348-54
pubmed: 18453793
Drugs Aging. 2009;26(2):145-55
pubmed: 19220071
Mayo Clin Proc. 2011 Apr;86(4):304-14
pubmed: 21389250
Community Ment Health J. 2013 Dec;49(6):625-9
pubmed: 23934237
JAMA. 2014 Sep 24;312(12):1237-47
pubmed: 25247520
Cochrane Database Syst Rev. 2014 Nov 20;(11):CD000011
pubmed: 25412402
Patient Prefer Adherence. 2015 Apr 13;9:569-78
pubmed: 25926723
Geriatr Gerontol Int. 2016 Oct;16(10):1093-1101
pubmed: 26482548
Acta Neurol Scand. 2017 May;135(5):507-515
pubmed: 27781263
Prev Med. 2017 Jun;99:269-276
pubmed: 28315760
JAMA. 2017 Jun 27;317(24):2476
pubmed: 28655013
J Hypertens. 2017 Dec;35(12):2346-2357
pubmed: 28777133
Medicine (Baltimore). 2018 Jun;97(23):e10962
pubmed: 29879046
Med Care. 1986 Jan;24(1):67-74
pubmed: 3945130

Auteurs

Tino Prell (T)

Department of Neurology, Jena University Hospital, Jena, Germany, tino.prell@med.uni-jena.de.
Center for Healthy Aging, Jena University Hospital, Jena, Germany, tino.prell@med.uni-jena.de.

Denise Schaller (D)

Department of Neurology, Jena University Hospital, Jena, Germany, tino.prell@med.uni-jena.de.

Caroline Perner (C)

Department of Neurology, Jena University Hospital, Jena, Germany, tino.prell@med.uni-jena.de.
Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.

Gabriele Helga Franke (GH)

University of Applied Sciences, Psychology of Rehabilitation, Stendal, Germany.

Otto W Witte (OW)

Department of Neurology, Jena University Hospital, Jena, Germany, tino.prell@med.uni-jena.de.
Center for Healthy Aging, Jena University Hospital, Jena, Germany, tino.prell@med.uni-jena.de.

Albrecht Kunze (A)

Department of Neurology, Jena University Hospital, Jena, Germany, tino.prell@med.uni-jena.de.

Julian Grosskreutz (J)

Department of Neurology, Jena University Hospital, Jena, Germany, tino.prell@med.uni-jena.de.
Center for Healthy Aging, Jena University Hospital, Jena, Germany, tino.prell@med.uni-jena.de.

Classifications MeSH