Theoretical foundations of adherence behaviors: synthesis and application in adherence to oral oncology agents

Patient Adherence to Oral Anticancer Agents: A Mapping Review of Supportive Interventions

The development and use of oral anticancer agents (OAAs) continue to grow, and supporting individuals on OAAs is now a priority as they find themselves taking these drugs at home with little professional guidance. This mapping review provides an overview of the current evidence concerning OAA-supportive adherence interventions, identifying potential gaps, and making recommendations to guide future work. Four large databases and the grey literature were searched for publications from 2010 to 2022. Quantitative, qualitative, mixed-method, theses/dissertations, reports, and abstracts were included, whereas protocols and reviews were excluded. Duplicates were removed, and the remaining publications were screened by title and abstract. Full-text publications were assessed and those meeting the inclusion criteria were retained. Data extracted included the year of publication, theoretical underpinnings, study design, targeted patients, sample size, intervention type, and primary outcome(s). 3175 publications were screened, with 435 fully read. Of these, 314 were excluded with 120 retained. Of the 120 publications, 39.2% (n = 47) were observational studies, 38.3% (n = 46) were quasi-experimental, and 16.7% (n = 20) were experimental. Only 17.5% (n = 21) were theory-based. Despite the known efficacy of multi-modal interventions, 63.7% (n = 76) contained one or two modalities, 33.3% (n = 40) included 3, and 3.3% (n = 4) contained four types of modalities. Medication adherence was measured primarily through self-report (n = 31) or chart review/pharmacy refills (n = 28). Given the importance of patient tailored interventions, future work should test whether having four intervention modalities (behavioral, educational, medical, and technological) guided by theory can optimize OAA-related outcomes.

Psychometric Properties of a Machine Learning-Based Patient-Reported Outcome Measure on Medication Adherence: Single-Center, Cross-Sectional, Observational Study

BACKGROUND

Medication adherence plays a critical role in controlling the evolution of chronic disease, as low medication adherence may lead to worse health outcomes, higher mortality, and morbidity. Assessment of their patients' medication adherence by clinicians is essential for avoiding inappropriate therapeutic intensification, associated health care expenditures, and the inappropriate inclusion of patients in time- and resource-consuming educational interventions. In both research and clinical practices the most extensively used measures of medication adherence are patient-reported outcome measures (PROMs), because of their ability to capture subjective dimensions of nonadherence. Machine learning (ML), a subfield of artificial intelligence, uses computer algorithms that automatically improve through experience. In this context, ML tools could efficiently model the complexity of and interactions between multiple patient behaviors that lead to medication adherence.

OBJECTIVE

This study aimed to create and validate a PROM on medication adherence interpreted using an ML approach.

METHODS

This cross-sectional, single-center, observational study was carried out a French teaching hospital between 2021 and 2022. Eligible patients must have had at least 1 long-term treatment, medication adherence evaluation other than a questionnaire, the ability to read or understand French, an age older than 18 years, and provided their nonopposition. Included adults responded to an initial version of the PROM composed of 11 items, each item being presented using a 4-point Likert scale. The initial set of items was obtained using a Delphi consensus process. Patients were classified as poorly, moderately, or highly adherent based on the results of a medication adherence assessment standard used in the daily practice of each outpatient unit. An ML-derived decision tree was built by combining the medication adherence status and PROM responses. Sensitivity, specificity, positive and negative predictive values (NPVs), and global accuracy of the final 5-item PROM were evaluated.

RESULTS

We created an initial 11-item PROM with a 4-point Likert scale using the Delphi process. After item reduction, a decision tree derived from 218 patients including data obtained from the final 5-item PROM allowed patient classification into poorly, moderately, or highly adherent based on item responses. The psychometric properties were 78% (95% CI 40%-96%) sensitivity, 71% (95% CI 53%-85%) specificity, 41% (95% CI 19%-67%) positive predictive values, 93% (95% CI 74%-99%) NPV, and 70% (95% CI 55%-83%) accuracy.

CONCLUSIONS

We developed a medication adherence tool based on ML with an excellent NPV. This could allow prioritization processes to avoid referring highly adherent patients to time- and resource-consuming interventions. The decision tree can be easily implemented in computerized prescriber order-entry systems and digital tools in smartphones. External validation of this tool in a study including a larger number of patients with diseases associated with low medication adherence is required to confirm its use in analyzing and assessing the complexity of medication adherence.

Interventions to Improve Adherence to Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia: A Systematic Review

BACKGROUND

Lack of adherence to tyrosine kinase inhibitors (TKIs) is a significant problem resulting in incomplete cytogenetic response and increased mortality in patients with chronic myeloid leukemia (CML). Few studies have been conducted on interventions to improve adherence. The authors conducted a systematic review to explore studies that examined the impact of strategies to improve TKI adherence among individuals with CML.

METHODS

The first 2 authors completed a systematic literature review according to the guidelines in Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA). Studies (n=2633) conducted between 1980 and 2019 were identified through 3 databases and examined for inclusion/exclusion criteria.

RESULTS

Fourteen studies were identified which met the eligibility criteria. The studies only examined adherence to imatinib, dasatinib, or nilotinib. Ten of the 14 used large data sets (commercial health insurance plans or Surveillance Epidemiology and End Results [SEER] data) for analysis. The majority of the studies used a cohort design. Adherence was defined and measured in a variety of ways with most studies using 80% or higher as adequate adherence. Strategies not focused on health care costs used a multidisciplinary team approach.

CONCLUSION

Development of evidence to improve treatment adherence to TKIs for CML have relied on large data sets rather than prospective trials. Current studies lack patient focused interventions.

Self-Report for Measuring and Predicting Medication Adherence: Experts' Experience in Predicting Adherence in Stable Psychiatric Outpatients and in Pharmacokinetics

THE PROBLEM

Poor adherence to appropriately prescribed medication is a global challenge for psychiatrists.

PRIOR STUDIES

Measuring adherence is complicated. In our recent three-country naturalistic study including more than 1000 patients and their adherence to multiple medication prescriptions at the same time, patients' self-report of adherence to each specific drug was the only practical option for measuring adherence. Systematic literature reviews provide inconsistent results for sociodemographic, clinical and medication variables as predictors of adherence to psychiatric drugs. Our studies over the last 10 years in relatively stable psychiatric outpatients have shown that some self-reported health beliefs had consistent, strong effects and a better predictive role. Three dimensions of these health beliefs are characteristics of the individual: 1) attitudes toward psychiatric medication such as pharmacophobia (fear of taking drugs or medicines), 2) health locus of control (the belief patients have about who or what agent determines the state of their health), 3) psychological reactance (an emotional reaction in direct contradiction to rules or regulations that threaten or suppress certain freedoms in behavior). They can be measured by the Patient Health Beliefs Questionnaire on Psychiatric Treatment. The attitude toward each specific medication can be measured by the necessity-concern framework and summarized as the presence or absence of skepticism about that drug. After 25 years conducting pharmacokinetic studies in psychiatric drugs, particularly antipsychotics, we have limited understanding of how to use blood levels to predict the effects of non-adherence or to establish it.

EXPERT OPINION ON FUTURE STUDIES

Future studies to predict adherence should include the inpatient setting and explore insight. Studying the pharmacokinetics associated with non-adherence in each psychiatric drug is a major challenge. Medication adherence is a complex and dynamic process changing over time in the same patient. Personalizing adherence using psychological or pharmacological variables are in their initial stages.

Designing and Testing a Treatment Adherence Model Based on the Roy Adaptation Model in Patients With Heart Failure: Protocol for a Mixed Methods Study

BACKGROUND

Adherence to treatment is an important factor to decrease repeated and costly hospitalization owing to heart failure (HF). The explanation and prediction of medication adherence and other lifestyle recommendations in chronic diseases, including HF, are complex. Theories lead to a better understanding of complex situations as well as the process of changing behavior and explain the reasons for the existence of a problem.

OBJECTIVE

The aim of this study is to report a protocol for a mixed methods study setting out to investigate the empirical validity of the Roy Adaptation Model as a conceptual framework for explaining and predicting adherence to treatment in patients with HF in Iran.

METHODS

This mixed methods study consists of an exploratory sequential design to be conducted in 2 phases. The first phase involves identifying the factors associated with treatment adherence in patients with HF through content analysis of the literature and elucidating the perception of participants in the context of Iranian health care where the model of adherence to treatment is designed based on the Roy Adaptation Model. The second phase addresses the interrelationships among variables in the model through a descriptive study using structural equation modeling. Finally, following the summarization and separate interpretation of the qualitative findings and quantitative results, a decision is made about the extent to and ways in which the results of the quantitative stage can be generalized or tested for the qualitative findings.

RESULTS

Content analysis of the literature in part 1 of the first phase was completed in 2017. Collection and analysis of qualitative data in part 2 of the first phase will be completed soon. The results are expected to be submitted for publication in 2019. Then, the second phase-the quantitative study-will be conducted.

CONCLUSIONS

The results of this study will provide valuable information about the empirical validity of the Roy Adaptation Model as a conceptual framework for explaining and predicting adherence to treatment in patients with HF, which, to date, have received little attention. The results can be used as a guide for nursing practice and care provision to patients with HF and also to design and implement effective interventions to improve treatment adherence in these patients.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/13317.

User acceptance of an app-based adherence intervention: Perspectives from patients taking oral anticancer medications

BACKGROUND

Widespread adoption by patients is imperative for the success of app-based interventions for enhancing adherence to oral anticancer medications. Patients' attitudes and beliefs should be evaluated to understand determinants of their acceptance and adoption of such interventions.

OBJECTIVE

To identify factors that influence cancer patients' intention to adopt an app-based system for enhancing oral anticancer medication adherence.

METHODS

This study was conducted as part of the usability evaluation of an app-based system for enhancing adherence. We followed the grounded theory approach employing audio-recorded face-to-face interviews for data collection from patients taking oral anticancer medications (n = 15) and caregivers of such patients (n = 3). Data analysis involved verbatim transcription of all interviews, coding of the transcripts and field notes, detailed memo writing, and constant comparative evaluation of emergent categories.

RESULTS

A conceptual framework of facilitating and hindering factors for users' adoption intention for an oral anticancer medication adherence app was developed. Findings suggest that facing difficulties in maintaining adherence and patients' perceived superiority of the app over their current methods facilitate adoption intention. In contrast, having to pay, lack of language options and users' perception of low competence in using an app were the hindrance factors.

CONCLUSION

This study showed that adoption of adherence apps could be explained by technology acceptance constructs, such as performance expectancy. Adoption intention was also facilitated by patients perceived vulnerabilities in maintaining adherence to their medications, which was a health behaviour construct. Implementation of app-based programs should address patients' perceived vulnerabilities and relative advantage of the app over their current methods. Clinicians and app developers should also consider the financial, technological and language barriers for end users.

Patients' Perception of App-based Educational and Behavioural Interventions for Enhancing Oral Anticancer Medication Adherence

Well-designed smartphone apps can potentially help in enhancing adherence to oral anticancer medications (OAMs). The objective of this study was to evaluate patients' perception on inclusion of various adherence-enhancing strategies as features of an app and their interest in using such app. A cross-sectional survey was conducted at the National Cancer Centre Singapore. A structured self-administered questionnaire was used to collect data from patients taking OAMs. Final analysis was based on 409 surveys and most of the respondents were female (291, 71.1%), Chinese (332, 81.2%), married (296, 72.4%) and breast cancer patients (211, 51.6%). Close to two-thirds of respondents rated medication information (65.0%), disease information (60.2%) and side effect self-management (60.2%) features as having the highest level of importance in an adherence app. Three hundred thirty-two (81.2%) of the respondents owned a smartphone, among which 92 (27.7%) reported using health-related apps. From respondents with smartphones, 219 (66.0%) were interested in using an app for OAM adherence. Age 65 and older compared to 21-54 years old (adjusted OR = 0.34; 95% CI = 0.15-0.76) and current use of a health app (adjusted OR = 1.91; 95% CI = 1.07-3.41) were significant predictors of interest to adopt an adherence app. In conclusion, patients value the inclusion of educational and behavioural interventions in adherence apps. Developers of adherence apps should consider including tools for side effect self-management and provision of information to educate patients on their medications and disease condition.

A systematic review of interventions to improve adherence to endocrine therapy

PURPOSE

Adherence to endocrine therapy for hormone positive breast cancer is a significant problem, especially in minority populations. Further, endocrine therapy reduces recurrence and thus mortality. However, little data are available on interventions to improve adherence. The authors conducted a systematic review to examine the impact of interventions, strategies, or approaches aimed to improve endocrine therapy adherence among women with breast cancer. A secondary aim was to determine if interventions had any cultural modifications.

METHODS

Two of the authors examined articles published between 2006 and 2017 from a wide variety of databases using Covidence systematic review platform.

RESULTS

In total, 16 eligible studies met criteria for review including 4 randomized controlled trials, 4 retrospective studies, and 8 with various observational designs. Eligible studies used a broad range of definitions for adherence and measured adherence by self-report, medical records, claims data, and combinations of these. All used 80% medication possession ratio as a standard for adherence. Patient information/education was the most frequent intervention strategy but did not demonstrate a significant effect except in one study. Significant results were noted when education was combined with communication strategies.

CONCLUSIONS

Researchers need a standard definition for adherence and a reliable measure that is feasible to use in a variety of studies. While education may be a necessary component of an intervention, when used alone, it is not a sufficient approach to change behavior.

A systematic review of interventions to improve adherence to endocrine therapy

PURPOSE

Adherence to endocrine therapy for hormone positive breast cancer is a significant problem, especially in minority populations. Further, endocrine therapy reduces recurrence and thus mortality. However, little data are available on interventions to improve adherence. The authors conducted a systematic review to examine the impact of interventions, strategies, or approaches aimed to improve endocrine therapy adherence among women with breast cancer. A secondary aim was to determine if interventions had any cultural modifications.

METHODS

Two of the authors examined articles published between 2006 and 2017 from a wide variety of databases using Covidence systematic review platform.

RESULTS

In total, 16 eligible studies met criteria for review including 4 randomized controlled trials, 4 retrospective studies, and 8 with various observational designs. Eligible studies used a broad range of definitions for adherence and measured adherence by self-report, medical records, claims data, and combinations of these. All used 80% medication possession ratio as a standard for adherence. Patient information/education was the most frequent intervention strategy but did not demonstrate a significant effect except in one study. Significant results were noted when education was combined with communication strategies.

CONCLUSIONS

Researchers need a standard definition for adherence and a reliable measure that is feasible to use in a variety of studies. While education may be a necessary component of an intervention, when used alone, it is not a sufficient approach to change behavior.

Integrative Review on Adherence in Haitians With Diabetes

In light of a marked increase in the incidence and prevalence of diabetes in the United States in recent years with associated health costs totaling $245 billion for 2012, diabetes has become a major health and fiscal concern. Haitian Americans as a cultural group have unique obstacles to effective treatment and management of diabetes. This paper analyzes recent studies relevant to these challenges in anticipation of new research pertaining to this population. Although medication compliance is generally referred to as adherence, it is a complex concept and key challenge in diabetes care. Accordingly, this paper will further define adherence by describing its relevance in effective treatment and management. It will also analyze key theoretical perspectives in diabetes care, summarize recent research, and make recommendations for effective future research on the impact of diabetes education in Haitian Americans.

Prevalence and Determinants of Adherence to Oral Adjuvant Endocrine Therapy among Breast Cancer Patients in Singapore

Objective:

The success of oral adjuvant endocrine therapy (OAET) is greatly influenced by patients’ level of adherence to treatment. The objective of this study is to measure the prevalence and determinants of adherence to OAET among breast cancer patients in Singapore.

Methods:

A cross-sectional survey of patients supplemented by analysis of their prescription records was used to collect data. Adherence to OAET was assessed using the Morisky Medication Adherence Scale-4 items and evaluation of refill gaps. Univariate and multivariate analyses were done to evaluate the association between patients’ characteristics and adherence to OAET.

Results:

A total of 157 women who have started OAET at least 6 months before the time of interview participated in the study, of which less than half (64 patients, 40.8%) of the patients had high adherence. Univariate analysis identified patients who were 57 years or older (P = 0.027), unemployed (P = 0.027), on aromatase inhibitors (P = 0.023), on three or more concurrent medications (P = 0.001), and had one or more comorbidities (P = 0.000) to be significantly more adherent. However, only the number of comorbidities was found to be an independent predictor of adherence in a multiple logistic regression analysis (adjusted odds ratio = 2.60; 95% confidence interval = 1.208–5.593; P = 0.015). Forgetfulness was the main reason for nonadherence mentioned by 63 (67.7%) of the 93 nonadherent patients.

Conclusions:

Low level of OAET adherence was found in this study, and forgetfulness was cited as the main reason for nonadherence. Patients were generally receptive to the implementation of various strategies to assist them with their medication-taking behavior