Distinct Profiles on Subjective and Objective Adherence Measures in Patients Prescribed Antidepressants

doi:10.1007/s40265-019-01107-y

Review

. 2019 Apr;79(6):647-654.

doi: 10.1007/s40265-019-01107-y.

Distinct Profiles on Subjective and Objective Adherence Measures in Patients Prescribed Antidepressants

Hans Wouters^{1

2}, Didi Rhebergen³, Marcia Vervloet⁴, Antoine Egberts^{5

6}, Katja Taxis⁷, Liset van Dijk^{7

4}, Helga Gardarsdottir^{5

6

8}

Affiliations

¹ Department of Pharmacotherapy, Pharmacoepidemiology and Pharmacoeconomics (PTEE), Faculty of Science and Engineering, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands. j.wouters@umcg.nl.
² Department of General Practice and Elderly Care Medicine, University Medical Center Groningen, University of Groningen, Oostersingel, Building 50, P.O. Box 196, 9700 AD, Groningen, The Netherlands. j.wouters@umcg.nl.
³ Department of Old Age Psychiatry, InGeest Specialized Mental Health Care, Amsterdam UMC location VU Medical Center, Amsterdam, The Netherlands.
⁴ Nivel Netherlands Institute for Health Services Research, Utrecht, The Netherlands.
⁵ Division of Pharmacoepidemiology and Clinical Pharmacology, Faculty of Science, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands.
⁶ Department of Clinical Pharmacy, Division Laboratory and Pharmacy, University Medical Center Utrecht, Utrecht, The Netherlands.
⁷ Department of Pharmacotherapy, Pharmacoepidemiology and Pharmacoeconomics (PTEE), Faculty of Science and Engineering, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.
⁸ Faculty of Pharmaceutical Sciences, University of Iceland, Reykjavík, Iceland.

PMID: 30941607
PMCID: PMC6483946
DOI: 10.1007/s40265-019-01107-y

Review

Distinct Profiles on Subjective and Objective Adherence Measures in Patients Prescribed Antidepressants

Hans Wouters et al. Drugs. 2019 Apr.

. 2019 Apr;79(6):647-654.

doi: 10.1007/s40265-019-01107-y.

Authors

Hans Wouters^{1

2}, Didi Rhebergen³, Marcia Vervloet⁴, Antoine Egberts^{5

6}, Katja Taxis⁷, Liset van Dijk^{7

4}, Helga Gardarsdottir^{5

6

8}

Affiliations

¹ Department of Pharmacotherapy, Pharmacoepidemiology and Pharmacoeconomics (PTEE), Faculty of Science and Engineering, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands. j.wouters@umcg.nl.
² Department of General Practice and Elderly Care Medicine, University Medical Center Groningen, University of Groningen, Oostersingel, Building 50, P.O. Box 196, 9700 AD, Groningen, The Netherlands. j.wouters@umcg.nl.
³ Department of Old Age Psychiatry, InGeest Specialized Mental Health Care, Amsterdam UMC location VU Medical Center, Amsterdam, The Netherlands.
⁴ Nivel Netherlands Institute for Health Services Research, Utrecht, The Netherlands.
⁵ Division of Pharmacoepidemiology and Clinical Pharmacology, Faculty of Science, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands.
⁶ Department of Clinical Pharmacy, Division Laboratory and Pharmacy, University Medical Center Utrecht, Utrecht, The Netherlands.
⁷ Department of Pharmacotherapy, Pharmacoepidemiology and Pharmacoeconomics (PTEE), Faculty of Science and Engineering, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.
⁸ Faculty of Pharmaceutical Sciences, University of Iceland, Reykjavík, Iceland.

PMID: 30941607
PMCID: PMC6483946
DOI: 10.1007/s40265-019-01107-y

Abstract

Objective: A recurrent observation is that associations between self-reported and objective medication adherence measures are often weak to moderate. Our aim was therefore to identify patients with different profiles on self-reported and objective adherence measures.

Study design and setting: This was an observational study of 221 community pharmacy patients who were dispensed antidepressants. Adherence profiles were estimated with Latent Profile Analysis (LPA) using data on self-reported adherence (Medication Adherence Rating Scale) complemented with data on medication beliefs (perceived necessity and concerns measured with the Beliefs about Medicines Questionnaire) and data from objective adherence measures (electronic monitoring of medication taking and the Medication Possession Ratio calculated from pharmacy dispensing data).

Results: 'Goodness-of-fit' statistics indicated the presence of three classes: "concordantly high adherent" (83%, high adherence on all measures), "concordantly suboptimal adherent" (11%, low adherence on all measures), and "discordant" (6%, high self-reported adherence but lower adherence on objective measures).

Conclusion: Most patients had concordant outcomes on self-reported and objective measures of adherence. A small discordant class had high self-reported but low objective adherence. LPA will enable sensitivity analyses in future studies, for example excluding patients from the discordant class.

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Conflict of interest statement

Conflict of interest

The authors report no other conflicts of interest.

Ethical standards

All procedures performed in this study were in accordance with the ethical standards of the medical ethics committee of the University Medical Center of Utrecht, which approved the study, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Written informed consent was obtained from all individual participants who were included in the study.

Figures

**Fig. 1**
Time window of data from different adherence measures being collected

**Fig. 2**
Scoring profiles of patient classes on adherence measures. *Values on adherence measures are expressed as percentages to facilitate mutual comparisons between different adherence measures. *MARS* Medication Adherence Rating Scale, *MEMS* Medication Event Monitoring System, *MPR* Medication Possession Ratio

See this image and copyright information in PMC

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References

1. Oberguggenberger AS, Sztankay M, Beer B, Schubert B, Meraner V, Oberacher H, et al. Adherence evaluation of endocrine treatment in breast cancer: methodological aspects. BMC Cancer. 2012;12:474. doi: 10.1186/1471-2407-12-474. - DOI - PMC - PubMed
1. Wetzels GE, Nelemans PJ, Schouten JS, van Wijk BL, Prins MH. All that glisters is not gold: a comparison of electronic monitoring versus filled prescriptions–an observational study. BMC Health Serv Res. 2006;6:8. doi: 10.1186/1472-6963-6-8. - DOI - PMC - PubMed
1. Shi L, Liu J, Fonseca V, Walker P, Kalsekar A, Pawaskar M. Correlation between adherence rates measured by MEMS and self-reported questionnaires: a meta-analysis. Health Qual Life Outcomes. 2010;8:99. doi: 10.1186/1477-7525-8-99. - DOI - PMC - PubMed
1. Trivedi RB, Ayotte BJ, Thorpe CT, Edelman D, Bosworth HB. Is there a nonadherent subtype of hypertensive patient? A latent class analysis approach. Patient Prefer Adherence. 2010;4:255–262. doi: 10.2147/PPA.S11335. - DOI - PMC - PubMed
1. Ulbricht CM, Rothschild AJ, Lapane KL. The association between latent depression subtypes and remission after treatment with citalopram: a latent class analysis with distal outcome. J Affect Disord. 2015;188:270–277. doi: 10.1016/j.jad.2015.08.039. - DOI - PubMed

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[1] Oberguggenberger AS, Sztankay M, Beer B, Schubert B, Meraner V, Oberacher H, et al. Adherence evaluation of endocrine treatment in breast cancer: methodological aspects. BMC Cancer. 2012;12:474. doi: 10.1186/1471-2407-12-474. - DOI - PMC - PubMed

[2] Oberguggenberger AS, Sztankay M, Beer B, Schubert B, Meraner V, Oberacher H, et al. Adherence evaluation of endocrine treatment in breast cancer: methodological aspects. BMC Cancer. 2012;12:474. doi: 10.1186/1471-2407-12-474. - DOI - PMC - PubMed

[3] Wetzels GE, Nelemans PJ, Schouten JS, van Wijk BL, Prins MH. All that glisters is not gold: a comparison of electronic monitoring versus filled prescriptions–an observational study. BMC Health Serv Res. 2006;6:8. doi: 10.1186/1472-6963-6-8. - DOI - PMC - PubMed

[4] Wetzels GE, Nelemans PJ, Schouten JS, van Wijk BL, Prins MH. All that glisters is not gold: a comparison of electronic monitoring versus filled prescriptions–an observational study. BMC Health Serv Res. 2006;6:8. doi: 10.1186/1472-6963-6-8. - DOI - PMC - PubMed

[5] Shi L, Liu J, Fonseca V, Walker P, Kalsekar A, Pawaskar M. Correlation between adherence rates measured by MEMS and self-reported questionnaires: a meta-analysis. Health Qual Life Outcomes. 2010;8:99. doi: 10.1186/1477-7525-8-99. - DOI - PMC - PubMed

[6] Shi L, Liu J, Fonseca V, Walker P, Kalsekar A, Pawaskar M. Correlation between adherence rates measured by MEMS and self-reported questionnaires: a meta-analysis. Health Qual Life Outcomes. 2010;8:99. doi: 10.1186/1477-7525-8-99. - DOI - PMC - PubMed

[7] Trivedi RB, Ayotte BJ, Thorpe CT, Edelman D, Bosworth HB. Is there a nonadherent subtype of hypertensive patient? A latent class analysis approach. Patient Prefer Adherence. 2010;4:255–262. doi: 10.2147/PPA.S11335. - DOI - PMC - PubMed

[8] Trivedi RB, Ayotte BJ, Thorpe CT, Edelman D, Bosworth HB. Is there a nonadherent subtype of hypertensive patient? A latent class analysis approach. Patient Prefer Adherence. 2010;4:255–262. doi: 10.2147/PPA.S11335. - DOI - PMC - PubMed

[9] Ulbricht CM, Rothschild AJ, Lapane KL. The association between latent depression subtypes and remission after treatment with citalopram: a latent class analysis with distal outcome. J Affect Disord. 2015;188:270–277. doi: 10.1016/j.jad.2015.08.039. - DOI - PubMed

[10] Ulbricht CM, Rothschild AJ, Lapane KL. The association between latent depression subtypes and remission after treatment with citalopram: a latent class analysis with distal outcome. J Affect Disord. 2015;188:270–277. doi: 10.1016/j.jad.2015.08.039. - DOI - PubMed

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Distinct Profiles on Subjective and Objective Adherence Measures in Patients Prescribed Antidepressants

Affiliations

Distinct Profiles on Subjective and Objective Adherence Measures in Patients Prescribed Antidepressants

Authors

Affiliations

Abstract

Conflict of interest statement

Conflict of interest

Ethical standards

Informed consent

Figures

Similar articles

Cited by

References

Publication types

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Grants and funding

LinkOut - more resources

Full Text Sources

Medical

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