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Why These Studies Use Both MMAS and SEAMS

10/19/2025

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The MMAS (Morisky Medication Adherence Scale) and SEAMS (Self-Efficacy for Appropriate Medication Use Scale) are frequently paired in academic research because they complement each other in evaluating medication adherence—a critical factor in managing chronic diseases where non-adherence can lead to poor health outcomes, increased hospitalizations, and higher healthcare costs. Here’s a breakdown of the rationale, drawn from patterns in the literature:
• Complementary Measurement Focus: MMAS is a self-reported tool that directly quantifies adherence behaviors, such as forgetting doses or stopping medication prematurely. It’s simple, validated across cultures (e.g., Chinese or Malaysian versions in several studies), and scores patients as low, medium, or high adherers. SEAMS, on the other hand, measures a patient’s confidence (self-efficacy) in managing medication regimens under various circumstances, like when side effects occur or routines change. Self-efficacy, rooted in Bandura’s social cognitive theory, is a psychological predictor of behavior; low self-efficacy often correlates with poor adherence. Studies use both to capture not just “what” patients do (adherence via MMAS) but “why” they might struggle (self-efficacy via SEAMS), enabling a more holistic analysis.
• Mediation and Correlation Analysis: Many papers explore SEAMS as a mediator or moderator in adherence models. For instance, higher SEAMS scores often predict better MMAS outcomes, as seen in epilepsy or diabetes studies where self-efficacy mediates the impact of depression, health literacy, or temperament on adherence. This allows researchers to test interventions (e.g., education or “talking pill bottles”) that boost self-efficacy to improve adherence. Validation studies also correlate the two for convergent validity, showing strong positive relationships (e.g., r = 0.926 in one Chinese lupus study).
• Application in Specific Populations and Interventions: In pediatric leukemia or rural chronic disease management, both scales help tailor home-based or community interventions. For example, baseline high scores in both might indicate minimal room for improvement in low-literacy groups, while longitudinal tracking shows gains post-intervention. They’re cost-effective, quick to administer, and adaptable to diverse settings like multiple sclerosis or osteoporosis treatment, where adherence to long-term therapies is challenging.
• Broader Research Trends: Adherence research often integrates these with other tools (e.g., beliefs questionnaires or HbA1c tests) to build predictive models. Their joint use stems from the need to address multifaceted barriers—behavioral, psychological, and educational—in real-world clinical practice. As non-adherence affects up to 50% of chronic disease patients globally, combining MMAS (outcome-focused) and SEAMS (process-focused) supports evidence-based strategies for better patient outcomes.

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1. Relationship between Patient Preferences, Attitudes to Treatment, and Adherence to Teriflunomide in Relapsing Multiple Sclerosis (Published in Patient Preference and Adherence, 2022). This study used MMAS-8 to assess adherence to teriflunomide therapy after nine months and SEAMS to evaluate self-efficacy in medication use. 2. Association between Medication Literacy and Medication Adherence among Patients with Hypertension (Published in Frontiers in Public Health, 2023). Researchers applied the Chinese version of MMAS-8 (C-MMAS-8) for adherence measurement and SEAMS for self-efficacy assessment in a cohort of hypertensive patients.
3. Medication Adherence in Leukemia Children Receiving Home-Based Treatment and Its Related Factors (Published in Pediatric Blood & Cancer, 2023). The study incorporated MMAS-8 to gauge adherence levels and SEAMS to measure self-efficacy among pediatric leukemia patients under home care.
4. Management of Chronic Diseases in Rural Areas: A Study of 232 Cases (Published in American Journal of Translational Research, 2022). MMAS-8 and SEAMS were used to score adherence and self-efficacy, respectively, with improvements noted over time in an experimental group receiving interventions.
5. Reliability and Validity of the Chinese Version of the Eight-Item Morisky Medication Adherence Scale in Chinese Patients with Systemic Lupus Erythematosus (Published in International Journal of Rheumatic Diseases, 2022). This validation study correlated MMAS-8 scores with SEAMS to confirm convergent validity.
6. Psychometric Properties of the Osteoporosis-Specific Morisky Medication Adherence Scale in Postmenopausal Women with Osteoporosis Newly Treated with Bisphosphonates (Published in Annals of Pharmacotherapy, 2012). The osteoporosis-specific version of MMAS (OS-MMAS) was evaluated alongside SEAMS and beliefs about medicines questionnaires.
7. Addressing Low Health Literacy with ‘Talking Pill Bottles’: A Pilot Study in a Community Pharmacy Setting (Published in Journal of the American Pharmacists Association, 2017). Both SEAMS and MMAS-8 were employed to track changes in self-efficacy and adherence over 90 days in a low-health-literacy population.
8. Development and Validation of Malaysia Medication Adherence Assessment Tool (MyMAAT) for Diabetic Patients (Published in PLoS One, 2020). MMAS-8 was compared with SEAMS in validating a new adherence tool for diabetes management.
9. The Role of Depressive Symptoms and Self-Efficacy in the Relationship between Temperament and Medication Adherence in Patients with Epilepsy (Published in Epilepsy & Behavior, 2025). MMAS-8 measured adherence, while SEAMS assessed self-efficacy as a mediator in the context of depressive symptoms.
10. Association of Health Literacy and Medication Self-Efficacy with Medication Adherence and Diabetes Control (Published in Patient Preference and Adherence, 2018). SEAMS evaluated self-efficacy, and MMAS assessed adherence in diabetic patients, with links to HbA1c outcomes.
11. The Mediating Effect of Self-Efficacy on the Relationship between Health Literacy and Medication Adherence among Patients with Type 2 Diabetes Mellitus (Published in Patient Preference and Adherence, 2023). SEAMS and MMAS-8 were used to explore mediation effects in diabetes adherence.
12. Depression and Medication Adherence among Older Korean Patients with Hypertension (Published in Asian Nursing Research, 2017). SEAMS and MMAS were part of the assessment battery, with regression analysis on their relationships.
13. The Analysis of Factors Affecting Medication Adherence in Patients with Hypertension (Published in Patient Preference and Adherence, 2024). MMAS-8, SEAMS, and beliefs questionnaires were combined to identify adherence factors.
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What Is Adherence? Understanding How to Measure and Improve Medication Adherence

10/18/2025

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Medication adherence — the degree to which a patient correctly follows medical advice and takes their prescribed treatment — is one of the most important yet overlooked factors in healthcare outcomes. Poor adherence can lead to treatment failure, disease progression, avoidable hospitalizations, and increased healthcare costs. But what exactly is adherence, how can it be measured, and what tools can help clinicians and researchers evaluate it effectively?

What Is Adherence?
Medication adherence refers to the extent to which patients take their medications as prescribed — including the correct dose, timing, and frequency. The World Health Organization (WHO) describes adherence as a multidimensional behavior influenced by five key dimensions:


  1. Patient-related factors (beliefs, motivation, forgetfulness)
  2. Therapy-related factors (complexity, side effects)
  3. Condition-related factors (chronicity, symptom burden)
  4. Healthcare system factors (access, provider communication)
  5. Socioeconomic factors (cost, support, education)

Measuring adherence accurately is crucial not only for evaluating treatment effectiveness but also for identifying barriers that can be addressed through tailored interventions.

Tools to Measure Medication Adherence
There are numerous methods to assess adherence, ranging from subjective self-reports to objective monitoring:


  • Pharmacy refill records – Track how often prescriptions are refilled.
  • Pill counts – Compare the number of pills taken versus prescribed.
  • Electronic monitoring devices – Use smart caps or apps to log medication use.
  • Biological measures – Detect medication levels in blood or urine.
  • Self-report questionnaires – Quick, low-cost tools that measure adherence behavior or confidence.

Each tool has advantages and limitations. For instance, electronic monitoring provides detailed data but can be costly, while self-report scales are inexpensive and easy to administer but rely on honest and accurate reporting.

Lagging vs. Leading Metrics in Adherence Measurement
In quality improvement and behavior analysis, metrics are often categorized as lagging or leading:


  • Lagging metrics measure outcomes — what happened after the behavior occurred.
  • Leading metrics measure predictors — what behaviors or attitudes influence future outcomes.
In medication adherence research, both types of metrics are valuable. Understanding the difference can help clinicians design better adherence improvement strategies.

The Morisky Scales: A Lagging Adherence Metric
The Morisky Medication Adherence Scales (MMAS-4 and MMAS-8) are among the most widely used and validated self-report tools for assessing medication adherence. Developed by Dr. Donald E. Morisky, the MMAS identifies behaviors that reflect past adherence patterns — such as forgetting doses, stopping medication when feeling better, or being careless at times.

Why the MMAS is a lagging indicator:
  • It measures what has already occurred (past medication-taking behavior).
  • It provides a snapshot of adherence outcomes, not future intent.
  • It helps identify which behaviors led to poor adherence, guiding corrective action.
Researchers and clinicians use the MMAS to evaluate adherence outcomes in populations, assess the effectiveness of interventions, and predict health outcomes such as blood pressure control or glycemic stability.
The SEAMS: A Leading Adherence Metric
The Self-Efficacy for Appropriate Medication Use Scale (SEAMS) measures a patient’s confidence in their ability to take medications correctly under various circumstances — for example, when traveling, feeling ill, or having a busy day.
Why the SEAMS is a leading indicator:
  • It measures predictive behavior, not just past performance.
  • Higher self-efficacy often leads to improved future adherence.
  • It helps clinicians identify motivational and educational needs before problems arise.
By assessing confidence rather than behavior, the SEAMS offers a forward-looking measure that can help healthcare teams target early interventions and empower patients.

Using Both Metrics Together
The most effective adherence programs combine both lagging and leading measures:


  • MMAS (Lagging): Identifies what happened — missed doses, nonadherence patterns, reasons for lapses.
  • SEAMS (Leading): Predicts what is likely to happen — confidence, readiness, and barriers to consistent adherence.
When used together, these tools provide a comprehensive understanding of adherence, guiding tailored interventions that both address past issues and strengthen future adherence behaviors.








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    Author

    Dr Donald Morisky.

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