Discrepancies between self-reported medication in adherence and indirect measurement adherence among patients undergoing antiretroviral therapy: a systematic review

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Abstract

Background

Given the critical importance of medication adherence in HIV/AIDS treatment, this study aims to compare medication adherence measured by self-report (SR) and indirect measurement among antiretroviral therapy (ART) patients, exploring the differences of adherence results measured by different tools.

Methods

We systematically searched PubMed, Embase, and the Cochrane Library to identify all relevant literature published up to November 22, 2023, without language restrictions, reporting adherence to ART measured by both SR and indirect measurement methods, while also analyzing individual and group adherence separately. Discrepancies between SR and indirect measurement results were assessed using the Mann–Whitney U test or Wilcoxon signed-rank test, with correlations evaluated using the Pearson correlation coefficient. Following one-to-one comparisons, meta-epidemiological one-step analysis was conducted, and network meta-analysis techniques were applied to compare results obtained through specific adherence assessment tools reported in the identified articles.

Results

The analysis encompassed 65 original studies involving 13,667 HIV/AIDS patients, leading to 112 one-to-one comparisons between SR and indirect measurement tools. Statistically significant differences were observed between SR and indirect measurement tools regarding both individual and group adherence ( P < 0.05), with Pearson correlation coefficients of 0.843 for individual adherence and 0.684 for group adherence. During meta-epidemiological one-step analysis, SR-measured adherence was determined to be 3.94% (95% CI: -4.48–13.44%) higher for individual adherence and 16.14% (95% CI: 0.81–18.84%) higher for group adherence compared to indirectly measured results. Subgroup analysis indicated that factors such as the year of reporting and geographic region appeared to influence the discrepancies between SR and indirect measurements. Furthermore, network meta-analysis revealed that for both individual and group adherence, the results obtained from most SR and indirect measurement tools were higher than those from electronic monitoring devices, with some demonstrating statistical significance ( P < 0.05).

Conclusions

The findings underscored the complexity of accurately measuring medication adherence among ART patients. Significant variability was observed across studies, with self-report methods showing a significant tendency towards overestimation. Year of reporting, geographic region, and adherence measurement tools appeared to influence the differences between SR and indirect measurements. Future research should focus on developing and validating integrated adherence measurements that can combine SR data with indirect measures to achieve a more comprehensive understanding of adherence behaviors.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-024-01221-4.

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Most cited references 67

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Self-report measures of medication adherence behavior: recommendations on optimal use.

Michael Stirratt, Jacqueline Dunbar-Jacob, Heidi Crane … (2015)

Medication adherence plays an important role in optimizing the outcomes of many treatment and preventive regimens in chronic illness. Self-report is the most common method for assessing adherence behavior in research and clinical care, but there are questions about its validity and precision. The NIH Adherence Network assembled a panel of adherence research experts working across various chronic illnesses to review self-report medication adherence measures and research on their validity. Self-report medication adherence measures vary substantially in their question phrasing, recall periods, and response items. Self-reports tend to overestimate adherence behavior compared with other assessment methods and generally have high specificity but low sensitivity. Most evidence indicates that self-report adherence measures show moderate correspondence to other adherence measures and can significantly predict clinical outcomes. The quality of self-report adherence measures may be enhanced through efforts to use validated scales, assess the proper construct, improve estimation, facilitate recall, reduce social desirability bias, and employ technologic delivery. Self-report medication adherence measures can provide actionable information despite their limitations. They are preferred when speed, efficiency, and low-cost measures are required, as is often the case in clinical care.

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Antiretroviral therapy adherence and viral suppression in HIV-infected drug users: comparison of self-report and electronic monitoring.

J Arnsten, P A Demas, H Farzadegan … (2001)

To compare electronically monitored (MEMS) with self-reported adherence in drug users, including the impact of adherence on HIV load, we conducted a 6-month observational study of 67 antiretroviral-experienced current and former drug users. Adherence (percentage of doses taken as prescribed) was calculated for both the day and the week preceding each of 6 research visits. Mean self-reported 1-day adherence was 79% (median, 86%), and mean self-reported 1-week adherence was 78% (median, 85%). Mean MEMS 1-day adherence was 57% (median, 52%), and mean MEMS 1-week adherence was 53% (median, 49%). One-day and 1-week estimates were highly correlated (r>.8 for both measures). Both self-reported and MEMS adherence were correlated with concurrent HIV load (r=.43-.60), but the likelihood of achieving virologic suppression was greater if MEMS adherence was high than if self-reported adherence was high. We conclude that self-reported adherence is higher than MEMS adherence, but a strong relationship exists between both measures and virus load. However, electronic monitoring is more sensitive than self-report for the detection of nonadherence and should be used in adherence intervention studies.

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Responses to a 1 month self-report on adherence to antiretroviral therapy are consistent with electronic data and virological treatment outcome.

Sundhiya Mandalia, J. Walsh, B. Gazzard (2002)

Many questionnaires on adherence to antiretroviral therapy are in use, but the validity of patients' responses has not been tested. The Medication Adherence Self-Report Inventory (MASRI) has been developed and tested for its validity against objective measures and treatment outcome. Prospective study comparing questionnaire responses with MEMS TrackCap (MC, a medication event monitoring system), pill count (PC) and plasma HIV viraemia in a publicly funded specialist HIV clinic. Patients self-medicating antiretroviral therapy who were not cognitively impaired and were able to read and understand English. Mean adherence by MC of the 78 subjects was 92.9% (SE, 1.8%) and by PC 96.8% (SE, 1.4%). Agreement between MC and responses to items about doses missed 1, 2 or 3 days ago was low (kappa = 0.23 (P < 0.03), 0.44 (P < 0.001) and 0.28 (P < 0.01) respectively). This improved when these responses were summated (kappa = 0.46;P < 0.001) and was similar to that for recall of non-adherence over the preceding 2 weeks (kappa = 0.54; P < 0.001). Mean self-reported adherence by visual analogue scale (VAS) over the preceding month was 93.3% (SE, 1.2%). This was strongly associated with both MC (r = 0.63; P < 0.001) and PC (r = 0.75; P < 0.001). On multivariate analysis, the strongest association between a MASRI item and MC was for the VAS. Both the 2 week recall and VAS items were inversely associated with viral load (P = 0.01). There was no association between dose timing (measured MC or questionnaire) or 3 day self-report and viral load. The MASRI provides a means of measuring patient adherence that is valid when compared with objective measures.

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Author and article information

Contributors

Liang Du: duliang0606@vip.sina.com

Tao Zhang:

ORCID: http://orcid.org/0000-0001-7535-1161

scdxzhangtao@163.com

Journal

Journal ID (nlm-ta): Infect Dis Poverty

Journal ID (iso-abbrev): Infect Dis Poverty

Title: Infectious Diseases of Poverty

Publisher: BioMed Central (London )

ISSN (Print): 2095-5162

ISSN (Electronic): 2049-9957

Publication date (Electronic): 5 July 2024

Publication date PMC-release: 5 July 2024

Publication date Collection: 2024

Volume: 13

Electronic Location Identifier: 51

Affiliations

[1 ]GRID grid.412901.f, ISNI 0000 0004 1770 1022, Center of Infectious Diseases, Research Center of Clinical Epidemiology and Evidence-Based Medicine, Innovation Insititute for Integration of Medicine and Engineering, , West China Hospital, Sichuan University, ; Chengdu, 610041 Sichuan People’s Republic of China

[2 ]Present Address: Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, ( https://ror.org/011ashp19) Chengdu, 610041 Sichuan People’s Republic of China

[3 ]Present Address: Sichuan Center for Disease Control and Prevention, ( https://ror.org/05nda1d55) Chengdu, 610041 Sichuan People’s Republic of China

[4 ]School of Public Health, Chengdu University of Traditional Chinese Medicine, ( https://ror.org/00pcrz470) Chengdu, 611130 Sichuan People’s Republic of China

Author information

Tao Zhang http://orcid.org/0000-0001-7535-1161

Article

Publisher ID: 1221

DOI: 10.1186/s40249-024-01221-4

PMC ID: 11225374

PubMed ID: 38970140

SO-VID: a3bfa1d4-34ad-466a-993c-c410b3ab59b1

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 9 March 2024

Date accepted : 24 June 2024

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100014718, Innovative Research Group Project of the National Natural Science Foundation of China;

Award ID: 72074161

Award ID: 81602935

Award Recipient : Liang Du

Funded by: FundRef http://dx.doi.org/10.13039/100012542, Sichuan Province Science and Technology Support Program;

Award ID: 2022YFS0229

Award ID: 2022YFS0641

Award Recipient : Rujun Liao

Funded by: Liangshan Prefecture Science and Technology Bureau Program

Award ID: 23ZDYF0025

Award Recipient : Rujun Liao

Funded by: FundRef http://dx.doi.org/10.13039/100015700, HIV and Drug Abuse Prevention Research Ethics Training Institute, Fordham University;

Award ID: 23ZDYF0112

Award Recipient : Rong Pei

Custom metadata

Keywords: hiv,aids,antiretroviral therapy,medication adherence,self-report,meta-epidemiological one-step analysis,network meta-analysis

Data availability:

Keywords: hiv, aids, antiretroviral therapy, medication adherence, self-report, meta-epidemiological one-step analysis, network meta-analysis

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Discrepancies between self-reported medication in adherence and indirect measurement adherence among patients undergoing antiretroviral therapy: a systematic review

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Abstract

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Conclusions

Graphical Abstract

Supplementary Information

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Annual Reviews HIV/AIDS: Public Health and Society

Most cited references 67

Self-report measures of medication adherence behavior: recommendations on optimal use.

Antiretroviral therapy adherence and viral suppression in HIV-infected drug users: comparison of self-report and electronic monitoring.

Responses to a 1 month self-report on adherence to antiretroviral therapy are consistent with electronic data and virological treatment outcome.

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