Adherence Self-Efficacy Scale (ASES)

Abstract

The Adherence Self-Efficacy Scale (ASES), widely documented in psychometric and clinical literature as the HIV Treatment Adherence Self-Efficacy Scale (HIV-ASES), is an established 12-item psychometric instrument designed to evaluate an individual’s cognitive appraisal of their capability to adhere to complex medical regimens in the presence of formidable barriers. Developed by researchers at the Center for AIDS Prevention Studies (CAPS) at the University of California, San Francisco, the instrument is grounded in Albert Bandura’s Social Cognitive Theory. The scale captures two correlated yet distinct latent dimensions: Adherence Integration (the perceived capability to weave complex medical protocols, dosing schedules, dietary alterations, and social exposure into daily routines) and Adherence Perseverance (the conviction to sustain regimen adherence amidst treatment side effects, emotional distress, biological setbacks such as falling CD4 T-cell counts, clinical appointment hassles, and discouragement from interpersonal networks). Responses are recorded across a 10-point continuous-style Likert-type rating scale ranging from 1 (“cannot do it at all”) to 10 (“certain can do it”). Principal psychometric investigations demonstrate high internal consistency (ρ > .90; Cronbach’s α values exceeding .90 for both subscales and the total composite), strong 3-month test-retest reliability (r > .70), and sustained 15-month temporal stability (r > .40). Factor analytic procedures establish a stable two-factor structure (eigenvalues of 6.12 and 1.16, accounting for 61% of cumulative item variance). Validity analyses demonstrate robust convergent and predictive relationships with objective viral suppression, electronic pill monitoring records, CD4 lymphocyte recovery, and lower depressive symptom severity. The ASES remains a standard measurement tool in clinical trials, behavioral medicine, and epidemiological research.

Keywords

Adherence Self-Efficacy Scale, HIV-ASES, Medication Adherence, Antiretroviral Therapy, Social Cognitive Theory, Psychometrics, Chronic Disease Management, Treatment Perseverance, Behavioral Medicine, Self-Efficacy Assessment

Authors

The Adherence Self-Efficacy Scale was developed and validated by a collaborative team of clinical psychologists, biostatisticians, and public health behavioral researchers affiliated with the Center for AIDS Prevention Studies (CAPS) at the University of California, San Francisco (UCSF), in collaboration with the HIV Center for Clinical and Behavioral Studies at Columbia University and the New York State Psychiatric Institute:

• Mallory O. Johnson, Ph.D. — Department of Medicine, Center for AIDS Prevention Studies (CAPS), University of California, San Francisco, San Francisco, CA, USA.
• Torsten B. Neilands, Ph.D. — Department of Medicine, Center for AIDS Prevention Studies (CAPS), University of California, San Francisco, San Francisco, CA, USA.
• Susan E. Dilworth, M.S. — Department of Medicine, Center for AIDS Prevention Studies (CAPS), University of California, San Francisco, San Francisco, CA, USA.
• Stephen F. Morin, Ph.D. — Department of Medicine, Center for AIDS Prevention Studies (CAPS), University of California, San Francisco, San Francisco, CA, USA.
• Robert H. Remien, Ph.D. — HIV Center for Clinical and Behavioral Studies, New York State Psychiatric Institute and Columbia University, New York, NY, USA.
• Margaret A. Chesney, Ph.D. — Department of Medicine, Center for AIDS Prevention Studies (CAPS), and Osher Center for Integrative Medicine, University of California, San Francisco, San Francisco, CA, USA.

Purpose

The primary purpose of the Adherence Self-Efficacy Scale is to provide an empirically validated, brief, and theoretically robust metric to measure patient self-efficacy regarding medical treatment adherence. While originally conceptualized within the framework of antiretroviral therapy (ART) for people living with HIV, the tool was intentionally structured to evaluate a patient’s perceived agency across the full spectrum of disease self-management. Treatment adherence in chronic illnesses extends beyond the simple mechanical ingestion of pharmacologic agents; it involves following dietary adjustments, keeping scheduled clinical appointments, navigating complex physiological adverse events, maintaining behavioral routines despite stigma, and managing psychological discouragement.

In clinical trials and behavioral intervention studies, researchers require assessment instruments sensitive to therapeutic change that can pinpoint the exact cognitive hurdles undermining adherence. Traditional adherence measures (such as self-report recall calendars, pharmacy refill records, or plasma drug concentration assays) provide behavioral outcome indicators after lapses have taken place. In contrast, the ASES functions as a prospective cognitive-behavioral assessment tool. By identifying specific areas where an individual feels inadequate or uncertain—such as concealing treatment from peers due to stigma, or adhering when daily schedules are upended—clinicians and researchers can implement targeted psychoeducational or cognitive-behavioral coping interventions prior to treatment failure or the development of pharmacological drug resistance.

Furthermore, the scale fulfills an explanatory role in translational research. In behavioral medicine, self-efficacy is posited as a critical mediator that translates knowledge, intentions, and structural access into consistent health-protective execution. Measuring this construct with a reliable tool enables researchers to evaluate whether intervention effects (such as peer navigation, motivational interviewing, or mindfulness-based stress reduction) operate through the enhancement of task-specific self-efficacy beliefs.

Psychological Construct

The psychological construct evaluated by the ASES is treatment adherence self-efficacy. Rooted in Bandura’s social cognitive framework, self-efficacy refers to an individual’s subjective confidence in their capability to execute courses of action required to manage designated situations. Critically, adherence self-efficacy is not a static personality trait or a global measure of optimism; rather, it is a highly domain-specific, behavioral-cognitive appraisal that varies across situational demands, emotional states, and physiological contexts.

Psychometric investigation of the ASES revealed that adherence self-efficacy operates through two distinct, meaningful sub-dimensions:

1. Adherence Integration

Adherence Integration measures a person’s confidence in their ability to assimilate medical demands into their ongoing psychosocial environment and daily life. Chronic disease regimens demand continuous, uninterrupted temporal routines. The integration dimension captures an individual’s perceived capacity to:

• Routinize dosing regimens into typical weekday and weekend behavioral cycles without disruption.
• Execute treatment protocols in public or social settings where disclosure of an stigmatized health status (e.g., HIV) has not occurred, requiring psychological resilience against perceived stigma or social embarrassment.
• Adapt medical requirements to shifting lifestyle constraints, such as altered sleep cycles, travel, or nutritional modifications (e.g., taking medication with high-fat meals or under fasting conditions).
• Sustain behavioral consistency when predictable schedules are disrupted by unpredictable life events.

2. Adherence Perseverance

Adherence Perseverance assesses the psychological tenacity and conviction required to maintain adherence when confronted with substantive internal or external adversities. In long-term management of serious chronic conditions, individuals experience treatment fatigue, negative biological markers, drug toxicity, and clinical hurdles. The perseverance dimension evaluates perceived agency to:

• Continue treatment regimens even when adverse somatic side effects (e.g., nausea, fatigue, neuropathy, gastrointestinal distress) interfere with occupational and social activities.
• Remain adherent when biological monitoring appears non-responsive or discouraging (e.g., when immunological markers such as CD4 T-cell counts drop significantly despite rigorous adherence).
• Maintain regimen fidelity amidst negative affective states, demoralization, depression, or general hopelessness regarding personal health prognosis.
• Overcome institutional and logistical barriers, such as traveling to distant clinical sites, experiencing long wait times, or navigating bureaucratic healthcare systems.
• Resist social dissuasion, cynicism, or misinformation from family members, partners, or peers who express skepticism regarding the efficacy or legitimacy of the prescribed medical regimen.
• Maintain psychological benefit, positive purpose, and agency in the clinical partnership even when pharmacotherapy does not yield immediate clinical improvements.

Theoretical Framework

The ASES is anchored directly in Social Cognitive Theory (SCT), articulated by Albert Bandura (1977, 1986, 1997). Central to Bandura’s theory is the distinction between outcome expectancies (the belief that a given behavior will lead to specific outcomes) and efficacy expectations (the personal conviction that one can successfully execute the behavior required to produce those outcomes). In chronic illness, an individual may understand that adhering to medications suppresses viral replication, prevents disease progression, and prolongs life (high positive outcome expectancies), yet fail to adhere because they doubt their capacity to manage difficult side effects, remember complicated regimens, or endure social stigma (low self-efficacy).

According to Social Cognitive Theory, perceived self-efficacy regulates human functioning through cognitive, motivational, affective, and selection processes:

• Cognitive Processes: People with high self-efficacy visualize success scenarios that provide positive guides and supports for performance, whereas those with low self-efficacy dwell on personal deficiencies and visualize obstacles as insurmountable.
• Motivational Processes: Self-efficacy determines the level of effort individuals will expend and how long they will persist in the face of obstacles. When facing drug toxicity or health setbacks, high self-efficacy fosters perseverance.
• Affective Processes: Perceived coping efficacy governs emotional distress, anxiety, and depression. Believing that one cannot manage illness demands activates physiological stress pathways and avoidance behaviors, which in turn lead to missed doses.

The ASES also aligns with the Information-Motivation-Behavioral Skills (IMB) Model of adherence (Fisher, Fisher, Amico, & Harman, 2006). Within the IMB model, biomedical knowledge (Information) and positive attitudes toward treatment (Motivation) are necessary prerequisites, but they are translated into long-term behavioral adherence through Behavioral Skills. Perceived self-efficacy is the cognitive bedrock of these behavioral skills, determining whether a patient feels capable of executing pill-taking strategies, managing side effects, acquiring social support, and interacting effectively with medical providers.

Validity

Psychometric evaluations of the ASES have established strong evidence across construct, convergent, predictive, and discriminant validity paradigms.

Construct and Factorial Validity

Construct validity was initially confirmed through structural factor analytic studies conducted by Johnson and colleagues (2007) across longitudinal cohorts of diverse patients receiving active antiretroviral therapy. The data verified that the construct is multi-faceted, capturing distinct operational challenges (integration into daily routine versus perseverance in the face of somatic and psychological barriers). Confirmatory structural models demonstrated good overall fit to empirical data, supporting the scale’s theoretical architecture.

Convergent Validity

Convergent validity was demonstrated through statistically significant associations between ASES scores and theoretically related psychosocial and behavioral constructs:

• Medication Adherence: Total ASES scores and both subscales demonstrated strong, positive correlations with 30-day visual analog scale (VAS) adherence ratings and timeline follow-back adherence interviews (r values typically ranging between .35 and .55, p < .001).
• Electronic Drug Monitoring: In validation subsets utilizing the Medication Event Monitoring System (MEMS)—a microelectronic cap recording the precise time and date of medication bottle openings—higher baseline ASES scores significantly correlated with higher percentages of prescribed doses taken on schedule (p < .01).
• Depressive Symptomatology: Significant negative correlations emerged between ASES scores and the Center for Epidemiologic Studies Depression Scale (CES-D), confirming that depressive symptoms erode adherence self-efficacy, while high efficacy buffers against emotional demoralization.
• Social Support: Positive associations were identified between the ASES and validated measures of perceived emotional and tangible social support.

Predictive and Criterion-Related Validity

The ASES exhibits robust criterion-related validity with respect to hard objective clinical and biomedical markers:

• Viral Load Suppression: Prospective analyses demonstrated that patients scoring in the upper quartiles of the ASES were significantly more likely to achieve and maintain undetectable HIV RNA viral loads (< 50 copies/mL) at 3-month, 6-month, and 12-month follow-up assessments, even after controlling for baseline viral load, age, and previous regimen history.
• Immunological Function: Higher ASES perseverance scores prospectively predicted maintenance and elevation of absolute CD4+ T-lymphocyte counts over a 15-month clinical observation window.
• Healthcare Utilization: Longitudinal regressions indicated that individuals with lower baseline adherence self-efficacy exhibited higher frequencies of missed clinical outpatient visits and greater rates of acute emergency department utilization.

Discriminant Validity

Discriminant validity has been demonstrated by weak, non-significant correlations with demographic variables such as chronological age, gender identity, and socioeconomic status, as well as distinct cognitive constructs like generalized intelligence or basic illness knowledge. This underscores that adherence self-efficacy reflects a specific behavioral confidence rather than overall cognitive ability or demographic privilege.

Reliability

The Adherence Self-Efficacy Scale demonstrates high internal consistency, cross-sectional stability, and appropriate longitudinal test-retest reliability across multiple clinical trials and observational studies.

Internal Consistency

In the primary validation study by Johnson et al. (2007), internal consistency reliability analyses conducted across the 12 items revealed high homogeneity among items while preserving distinct subscale constructs:

• Overall HIV-ASES Composite: Scale reliability coefficients exceeded .90 (Raykov’s ρ > .90; Cronbach’s α = .92 to .94).
• Adherence Integration Subscale: Demonstrated strong internal consistency, with alpha coefficients consistently ranging from .86 to .90 across diverse ethnocultural patient samples.
• Adherence Perseverance Subscale: Exhibited equally robust reliability, yielding alpha coefficients between .87 and .91.

Test-Retest Reliability and Temporal Stability

Evaluating the stability of a self-efficacy scale requires a balance: the measure must demonstrate stability in stable conditions while remaining sensitive to clinical change, life disruptions, or behavioral interventions. The psychometric evaluation demonstrated:

• 3-Month Test-Retest Reliability: Over a 3-month observational window in clinically stable outpatients, test-retest reliability was high (r > .70, p < .0001), indicating strong measurement stability across short-to-medium intervals.
• 15-Month Temporal Stability: Over an extended 15-month period involving shifting life events and regimen adjustments, the test-retest coefficient remained moderate and statistically significant (r > .40, p < .001). This confirms that while the ASES measures a relatively stable psychological disposition, it remains responsive to environmental transitions, health changes, and clinical interventions over time.

Factor Analysis

The underlying dimensionality of the 12-item ASES was established using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) within structural equation modeling (SEM) frameworks.

Exploratory Factor Analysis

Initial factor extraction conducted on patient samples utilized principal components analysis and principal axis factoring with oblique (Promax) rotation, reflecting the theoretical expectation that sub-dimensions of adherence self-efficacy are correlated. The scree test and eigenvalue criteria (> 1.0) supported a two-factor model:

• Factor 1: Adherence Integration yielded an eigenvalue of 6.12. Items loading heavily on this factor reflect logistical, structural, and social integration of treatment into daily life (e.g., integrating treatment into daily routine, taking medication around individuals unaware of diagnosis, adjusting to schedule shifts and altered eating habits).
• Factor 2: Adherence Perseverance yielded an eigenvalue of 1.16. Items loading primarily on this factor capture psychological resilience in the face of adversity (e.g., sticking to plans despite side effects, continuing when CD4 counts drop, persisting through discouragement or clinic appointment hassles).
• Explained Variance: Together, these two factors accounted for approximately 61% of the total cumulative variance across the 12 items. Item factor loadings were strong, with standardized loadings ranging from .55 to .87, without problematic cross-loadings.

Confirmatory Factor Analysis and Structural Fit

Confirmatory factor analyses testing the two-factor oblique model confirmed adequate goodness-of-fit to the data across diverse samples, satisfying standard structural benchmarks:

• Comparative Fit Index (CFI) ≥ .95
• Tucker-Lewis Index (TLI) ≥ .94
• Root Mean Square Error of Approximation (RMSEA) ≤ .06 (90% CI: .04–.07)
• Standardized Root Mean Square Residual (SRMR) ≤ .05

The correlation between the two latent factors typically ranges between .60 and .75. This indicates that while Integration and Perseverance are interrelated aspects of treatment self-efficacy, they represent distinct behavioral targets that warrant individual assessment in clinical research.

Instrument / Measurement Tool

• Full Instrument Name: Adherence Self-Efficacy Scale (ASES) / HIV Treatment Adherence Self-Efficacy Scale (HIV-ASES)
• Instrument Developer: Centre for AIDS Prevention Studies (CAPS), University of California, San Francisco (UCSF)
• Administration Format: Self-administered paper-and-pencil questionnaire, clinician- or researcher-administered structured interview, or computer-assisted self-interview (CASI / Web-based platform).
• Target Population: Adolescents and adults (ages 16+) undergoing medical treatment plans, antiretroviral regimens, or complex chronic disease therapies.
• Completion Time: Approximately 3 to 5 minutes.
• Number of Items: 12 items.
• Response Scale: 10-point continuous Likert-type scale, anchored from 1 (“cannot do it at all”) to 10 (“certain can do it”).
• Recall Period: “In the past month…”
• Subscales:
  • Adherence Integration: Evaluates perceived capability to integrate treatment into daily routines, social interactions, and dietary changes.
  • Adherence Perseverance: Evaluates perceived capability to sustain treatment during side effects, health discouragement, falling laboratory markers, and logistical obstacles.
• Scoring Procedures:
  • Subscale Scores: Calculated by computing the mean of the items comprising each subscale (sum of subscale item scores divided by the number of completed subscale items), yielding a subscale score ranging from 1.0 to 10.0.
  • Total Score: Calculated as the arithmetic mean across all 12 items (sum of all items divided by 12), yielding an overall self-efficacy index from 1.0 to 10.0.
  • Alternative Sum Scoring: If preferred, items may be summed directly (composite sum score range: 12 to 120); however, mean scoring is generally preferred to maintain direct correspondence with the 1–10 response scale and facilitate handling of occasional missing items.
  • Missing Data Rule: If a respondent omits more than 2 items across the 12-item instrument (or > 1 item on a subscale), composite scores should be treated with caution or imputed using validated psychometric procedures.

Permissions & Fee and Test Year

The Adherence Self-Efficacy Scale was validated and published in 2007 by Mallory O. Johnson and colleagues. The instrument is situated within the public academic domain for non-commercial research, clinical practice, and educational purposes. No licensing fees or royalties are required to administer, adapt, or evaluate the scale in academic research or public health interventions.

Terms of Use and Attribution Requirements:

• Individuals may utilize this scale for empirical research or educational purposes only and may not commercialize the instrument or incorporate it into fee-based proprietary software without explicit written permission from the copyright holders.
• When using the instrument, researchers must cite the original validation publication:
  

  Johnson, M. O., Neilands, T. B., Dilworth, S. E., Morin, S. F., Remien, R. H., & Chesney, M. A. (2007). The role of self-efficacy in HIV treatment adherence: Validation of the HIV treatment adherence self-efficacy scale (HIV-ASES). Journal of Behavioral Medicine, 30(5), 359–370.

• When presenting or publishing results obtained using survey materials from the Social and Behavioral Instruments (SABI) repository or CAPS, investigators are requested to acknowledge the University of North Carolina at Chapel Hill Center for AIDS Research (CFAR), an NIH-funded program (P30 AI50410).

References

• Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191
• Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall, Inc.
• Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman and Company.
• Chesney, M. A., Ickovics, J. R., Chambers, D. B., Gifford, A. L., Neidig, J., Zwickl, B., & Wu, A. W. (2000). Self-reported adherence to antiretroviral medications among participants in HIV clinical trials: The AACTG adherence instruments. AIDS Care, 12(3), 255–266. https://doi.org/10.1080/09540120050042917
• Fisher, J. D., Fisher, W. A., Amico, K. R., & Harman, J. J. (2006). An information-motivation-behavioral skills model of adherence to antiretroviral therapy. Health Psychology, 25(4), 462–473. https://doi.org/10.1037/0278-6133.25.4.462
• Johnson, M. O., Neilands, T. B., Dilworth, S. E., Morin, S. F., Remien, R. H., & Chesney, M. A. (2007). The role of self-efficacy in HIV treatment adherence: Validation of the HIV treatment adherence self-efficacy scale (HIV-ASES). Journal of Behavioral Medicine, 30(5), 359–370. https://doi.org/10.1007/s10865-007-9118-3
• Remien, R. H., Bastos, F. I., Berkman, A., Terto, V. J., Raxach, J. C., Parker, R. G., & Chesney, M. A. (2007). Universal access to antiretroviral therapy in Brazil: Does it ensure adherence and long-term viral suppression? AIDS and Behavior, 11(4), 621–632. https://doi.org/10.1007/s10461-006-9175-1

Items of the Scale