Dataset Information

Intentional and unintentional medication non-adherence in African Americans: Insights from the Jackson Heart Study.

ABSTRACT: BACKGROUND:Non-adherence to medications is common and leads to suboptimal outcomes. Non-adherence can be intentional (e.g., deciding to skip dosages) or unintentional (e.g., forgetting), yet few studies have distinguished these reasons. An improved understanding of the reasons for non-adherence could inform the development of effective interventions. METHODS AND RESULTS:We analyzed data from African Americans in the Jackson Heart Study who were prescribed medications for one or more chronic conditions. Participants were grouped by patient-reported adherence with non-adherence categorized as being intentional, unintentional or both. We used modified Poisson regression models to examine the factors associated with types of non-adherence. Of 2933 participants taking medication, 2138 (72.9%) reported non-adherence with 754 (35.3%) reporting only unintentional non-adherence, 263 (12.3%) only intentional non-adherence, and 1121 (52.4%) both. Factors independently associated with intentional non-adherence included female sex and depressive symptoms while factors associated with unintentional non-adherence included younger age and separated relationship status. Unintentional and intentional non-adherence was more common among participants taking anti-arrhythmic and anti-asthmatic medications, respectively. Higher levels of global perceived stress was associated with both types of non-adherence. The adjusted models for intentional and unintentional non-adherence had c-statistics of 0.65 and 0.66, respectively, indicating modest discrimination. CONCLUSION:Specific patient factors and individual medication classes were associated with distinct patterns of intentional and unintentional non-adherence, yet the overall modest discrimination of the models suggests contributions from other unmeasured factors. These findings provide a construct for understanding reasons for non-adherence and provide rationale to assess whether personalized interventions can improve adherence.

SUBMITTER: Mentz RJ

PROVIDER: S-EPMC6005189 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Intentional and unintentional medication non-adherence in African Americans: Insights from the Jackson Heart Study.

Mentz Robert J RJ Greiner Melissa A MA Muntner Paul P Shimbo Daichi D Sims Mario M Spruill Tanya M TM Banahan Benjamin F BF Wang Wei W Mwasongwe Stanford S Winters Karen K Correa Adolfo A Curtis Lesley H LH O'Brien Emily C EC

American heart journal 20180312

<h4>Background</h4>Non-adherence to medications is common and leads to suboptimal outcomes. Non-adherence can be intentional (e.g., deciding to skip dosages) or unintentional (e.g., forgetting), yet few studies have distinguished these reasons. An improved understanding of the reasons for non-adherence could inform the development of effective interventions.<h4>Methods and results</h4>We analyzed data from African Americans in the Jackson Heart Study who were prescribed medications for one or mo ...[more]

PMID: 29898849

Similar Datasets

Project description:ObjectiveTo categorise patient-reported outcome measures (PROMs) into their propensity to detect intentional and/or unintentional non-adherence to medication, and synthesise their psychometric properties.DesignSystematic review and regression analysis.EligibilityMedication adherence levels studied at primary, secondary and tertiary care settings. Self-reported measures with scoring methods were included. Studies without proxy measures were excluded.Data sourcesUsing detailed searches with key concepts including questionnaires, reliability and validity, and restricted to English, MEDLINE, EMBASE, CINAHL, International Pharmaceutical Abstracts, and Cochrane Library were searched until 01 March 2022. Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 (PRISMA-2020) checklist was used.Data analysisRisk of bias was assessed via COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN-2018) guidelines. Narrative synthesis aided by graphical figures and statistical analyses.Outcome measuresProcess domains [behaviour (e.g., self-efficacy), barrier (e.g., impaired dexterity) or belief (e.g., perception)], and overall outcome domains of either intentional (I), unintentional (UI), or mixed non-adherence.ResultsPaper summarises evidence from 59 studies of PROMs, validated among patients aged 18-88 years in America, the United Kingdom, Europe, Middle East, and Australasia. PROMs detected outcome domains: intentional non-adherence, n=44 (I=491 criterion items), mixed intentionality, n=13 (I=79/UI=50), and unintentional, n=2 (UI=5). Process domains detected include belief (383 criterion items), barrier (192) and behaviour (165). Criterion validity assessment used proxy measures (biomarkers, e-monitors), and scoring was ordinal, dichotomised, or used Visual Analogue Scale. Heterogeneity was revealed across psychometric properties (consistency, construct, reliability, discrimination ability). Intentionality correlated positively with negative beliefs (r(57)=0.88) and barriers (r(57)=0.59). For every belief or barrier criterion-item, PROMs' aptitude to detect intentional non-adherence increased by β=0.79 and β=0.34 units, respectively (R2=0.94). Primary care versus specialised care predicted intentional non-adherence (OR 1.9; CI 1.01 to 2.66).ConclusionsTen PROMs had adequate psychometric properties. Of the ten, eight PROMs were able to detect total, and two PROMs were able to detect partial intentionality to medication default. Fortification of patients' knowledge and illness perception, as opposed to daily reminders alone, is most imperative at primary care levels.

Dataset Information

Intentional and unintentional medication non-adherence in African Americans: Insights from the Jackson Heart Study.

Publications

Intentional and unintentional medication non-adherence in African Americans: Insights from the Jackson Heart Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets