Summary of Diabetes Self-Care Activities (SDSCA)

Abstract

The Summary of Diabetes Self-Care Activities (SDSCA) is one of the most widely utilized, empirically validated self-report instruments designed to assess multidimensional adherence to diabetes management regimens. Developed and refined by Russell E. Glasgow, Deborah J. Toobert, and Sarah E. Hampson, the SDSCA evaluates the frequency with which individuals with Type 1 or Type 2 diabetes engage in critical health-protective behaviors over the preceding seven days. The standard brief core battery measures five primary self-care domains: General Diet, Specific Diet, Exercise/Physical Activity, Blood Glucose Testing, and Foot Care, alongside items quantifying Smoking Status. An expanded version incorporates additional domains such as medication administration (both oral agents and insulin regimens), carbohydrate spacing, foot-soaking precautions, alcohol intake, and self-directed alternative remedies.

The SDSCA employs an intuitive, recall-based frequency metric: respondents indicate the number of days (from 0 to 7) during the previous week in which they performed each designated behavior. Across extensive clinical trials, epidemiological surveys, and psychometric meta-analyses, the instrument has consistently demonstrated acceptable-to-excellent test-retest reliability (mean r = .40 to .78 across domains), robust content and construct validity, and significant predictive associations with physiological biomarkers—including glycated hemoglobin (HbA1c)—and psychological constructs such as self-efficacy and quality of life. Unlike unidimensional compliance indices, the SDSCA operationalizes diabetes management as an orthogonal, multi-behavioral domain, reflecting clinical reality wherein adherence to one self-care behavior (e.g., foot inspection) does not necessarily correlate with adherence to another (e.g., aerobic exercise). Consequently, the SDSCA serves as an indispensable psychometric tool in clinical endocrinology, behavioral medicine, and translational health services research.

Keywords

Summary of Diabetes Self-Care Activities, SDSCA, diabetes self-management, behavioral medicine, psychometrics, treatment adherence, blood glucose monitoring, diabetes foot care, dietary adherence, physical activity.

Authors

The Summary of Diabetes Self-Care Activities was developed, psychometrically standardized, and revised across multiple iterative programmatic research programs by leading behavioral scientists at the Oregon Research Institute (ORI):

• Deborah J. Toobert, Ph.D.: Senior Research Scientist at the Oregon Research Institute, Eugene, Oregon, USA. Expert in chronic disease self-management, health behavior change interventions, and psychometric measurement of behavioral health practices.
• Sarah E. Hampson, Ph.D.: Senior Research Scientist at the Oregon Research Institute and Professor Emeritus of Psychology, University of Surrey, UK. Renowned specialist in personality psychology, illness perceptions, life-span developmental trajectories, and self-management behaviors.
• Russell E. Glasgow, Ph.D.: Director of the Dissemination and Implementation Science Program at the Adult and Child Consortium for Health Outcomes Research and Delivery Science (ACCORDS), University of Colorado School of Medicine; formerly Research Scientist at ORI and Deputy Director for Implementation Science at the National Cancer Institute (NCI). Pioneer of the RE-AIM evaluation framework and self-management interventions in chronic illness.

Purpose

Diabetes mellitus is a demanding chronic metabolic disorder that necessitates continuous, complex, and lifelong self-care by the patient. Achieving optimal metabolic control, mitigating microvascular complications (e.g., retinopathy, nephropathy, peripheral neuropathy), and preventing macrovascular events (e.g., myocardial infarction, stroke) relies predominantly on patient-enacted behavioral self-regulation. Historically, clinical assessments of diabetes adherence suffered from critical conceptual and psychometric flaws: they relied on global, subjective impressions of “compliance,” aggregated disparate behaviors into invalid composite scores, or utilized complex behavioral diaries with prohibitive respondent burden.

The primary purpose of the SDSCA is to provide a brief, practical, psychometrically sound, and multidimensional measurement tool capable of evaluating discrete behavioral components of diabetes self-management. The instrument was intentionally engineered to serve both clinical practice and empirical research:

• Clinical Utility and Patient-Centered Care: In outpatient endocrinology clinics, primary care encounters, and diabetes self-management education (DSME) programs, the SDSCA enables clinicians to rapidly profile an individual patient’s behavioral strengths and vulnerabilities. Rather than labeling a patient generically as “non-compliant,” healthcare providers can identify specific areas where behavioral execution is deficient (e.g., regular blood glucose testing occurring 7 days per week, but foot examinations occurring 0 days per week), thereby guiding individualized, patient-centered behavioral counseling.
• Clinical Trials and Intervention Evaluation: In randomized controlled trials testing lifestyle modifications, digital health interventions, pharmacological regimens, or behavioral educational strategies, the SDSCA functions as a sensitive outcome metric to evaluate domain-specific intervention efficacy. Because each behavioral area is scored independently, researchers can detect whether an educational module successfully increased physical activity without erroneously assuming parallel gains in dietary compliance.
• Epidemiological and Health Disparities Research: The instrument’s low reading level, minimal completion time (typically 5 to 10 minutes), and cross-cultural adaptability make it suitable for large-scale population health surveillance and the investigation of health disparities across ethnically and socioeconomically diverse cohorts.

Psychological Construct

The psychological and behavioral construct quantified by the SDSCA is Diabetes Self-Care Behavior, defined as the set of self-directed, volitional actions performed by an individual with diabetes to maintain glycemic equilibrium, minimize acute metabolic crises, and prevent long-term microvascular and macrovascular sequelae. Crucially, the SDSCA treats diabetes self-care not as a singular trait or uniform behavioral disposition, but as a set of separate, non-fungible behavioral domains.

The multifaceted construct encompasses the following distinct behavioral dimensions:

• General Diet: Captures global adherence to a healthful nutritional regimen designed for metabolic management (e.g., following a prescribed or healthful eating plan over the past week and past month). This represents the respondent’s overarching cognitive-behavioral intention to align dietary choices with therapeutic guidelines.
• Specific Diet: Reflects concrete nutritional behaviors characterized by the consumption of health-promoting foods (e.g., consuming five or more servings of fruits and vegetables daily) and the deliberate avoidance or limitation of atherogenic, saturated-fat-dense foods (e.g., red meat, full-fat dairy). In the expanded inventory, it also captures the strategic spacing of dietary carbohydrates across daily meals to mitigate postprandial glycemic excursions.
• Physical Activity / Exercise: Measures engagement in both planned, structured exercise bouts (e.g., swimming, cycling, intentional walking sessions separate from workplace or domestic duties) and cumulative daily physical activity totaling at least 30 minutes. This construct reflects the physiologic mobilization of skeletal muscle to enhance insulin sensitivity and promote cardiorespiratory fitness.
• Blood Glucose Testing: Evaluates self-monitoring of blood glucose (SMBG), quantifying both the absolute frequency of capillary blood glucose assessments and the degree of adherence to provider-recommended monitoring frequencies. It captures the patient’s vigilance in tracking real-time glycemic data to inform daily therapy adjustments.
• Foot Care: Measures preventative dermatological and podiatric self-examinations aimed at preventing diabetic foot ulcers and subsequent lower-extremity amputations. Sub-behaviors include daily visual inspection of the feet, checking inside footwear for foreign objects or structural degradation, thorough washing, and avoiding tissue maceration (e.g., drying between toes while avoiding prolonged foot soaking).
• Medication Adherence: Assesses pharmacological compliance across prescribed regimens, specifically distinguishing between oral hypoglycemic tablets and subcutaneous insulin injections. It captures whether patients execute daily medication administration precisely as prescribed.
• Harm Reduction and Alternative Practices: Assesses concurrent lifestyle behaviors that interact with metabolic pathology, including active cigarette smoking (which amplifies macrovascular risk exponentially), alcohol intake, and the autonomous utilization of dietary supplements, botanicals, or unprescribed home remedies.

Theoretical Framework

The architectural foundation of the SDSCA is rooted in Social Cognitive Theory (SCT), pioneered by Albert Bandura, alongside contemporary paradigms of self-regulation and chronic disease self-management. SCT posits that human functioning is the product of continuous, reciprocal interactions among environmental influences, intrapersonal factors (cognitions, affect, biological events), and behavioral enactments—a triadic reciprocal causation model.

Under this theoretical framework, diabetes self-management is governed by several core cognitive mechanisms:

1. Domain-Specific Self-Efficacy: SCT asserts that self-efficacy—the subjective conviction that one can successfully execute the behaviors required to produce desired outcomes—is not a global personality trait but a task-specific cognitive appraisal. A patient may possess robust self-efficacy for self-administering insulin injections, yet exhibit profoundly low self-efficacy for maintaining a restricted-carbohydrate diet during social gatherings. The SDSCA’s multi-component design operationalizes this principle by measuring each self-care domain independently, acknowledging that mastery expectations and behavioral execution vary systematically across behavioral contexts.
2. Self-Monitoring and Feedback Loops: Central to cybernetic and cognitive models of self-regulation is the feedback loop: individuals must monitor their own performance, compare their actions against behavioral and physiological standards (such as target blood glucose parameters or dietary targets), and implement corrective adjustments. Instruments measuring diabetes self-care must capture the actual behavioral output of these self-regulatory loops rather than relying on abstract motivation or generalized health beliefs.
3. Behavioral Independence and Multi-Regimen Demands: Unlike conditions with straightforward pharmacological interventions (e.g., taking an antihypertensive once daily), diabetes management demands simultaneous execution of disparate behavioral competencies, including cognitive calculations (carbohydrate counting), motor-procedural skills (finger-stick blood testing, subcutaneous injections), and persistent impulse control (resisting calorie-dense foods). Psychometric research conducted by Glasgow, Toobert, and colleagues demonstrated that intercorrelations among these behavioral domains are remarkably low (typically r = .10 to .30). This empirical reality invalidated previous clinical assumptions that a patient is globally “adherent” or “non-adherent,” necessitating an assessment architecture that evaluates each behavioral domain on its own distinct continuum.

Validity

The validity of the SDSCA has been substantiated across dozens of independent psychometric investigations, diverse ethnic populations, and translated adaptations globally (including Spanish, Chinese, Turkish, Arabic, and Korean versions).

Construct and Structural Validity

Construct validity was established through extensive multidimensional evaluations. Confirmatory factor analyses consistently demonstrate that a multi-factor orthogonal or weakly correlated oblique model fits the data significantly better than a single-factor unidimensional model. Inter-scale correlations between primary domains (General Diet, Specific Diet, Exercise, Blood Glucose Testing, and Foot Care) are low to moderate (ranging from r = .02 to .35), confirming that diabetes self-care consists of relatively independent behavioral dimensions rather than a monolithic compliance construct.

Convergent Validity

Convergent validity has been established by correlating SDSCA subscale scores with validated objective benchmarks, structured clinical interviews, and standardized behavioral questionnaires:

• Diet: SDSCA General and Specific Diet subscale scores correlate significantly with multi-day food records, 24-hour dietary recalls, and the Block Food Frequency Questionnaire (correlations ranging from r = .30 to .52).
• Exercise: SDSCA Exercise subscale scores show moderate to high correlations with objective accelerometer data, pedometer step counts, and physical activity indices such as the Stanford 7-Day Physical Activity Recall (r = .35 to .60).
• Blood Glucose Testing: The SMBG items show strong concordance with memory-chip downloads extracted directly from patient blood glucose meters (r = .60 to .82), demonstrating that self-reported testing frequency closely mirrors electronically verified testing events.
• Foot Care: Foot care frequency correlates positively with clinical podiatric assessment ratings, visual skin integrity markers, and structured patient knowledge interviews.

Predictive and Criterion Validity

Criterion validity is demonstrated through the instrument’s capacity to predict metabolic control and clinical outcomes. Higher aggregate and subscale scores—particularly for Blood Glucose Testing, Medication Adherence, and Diet—are inversely correlated with HbA1c levels (statistically significant coefficients typically ranging from r = −.15 to −.38, depending on cohort composition and baseline glycemic control). Longitudinal intervention studies demonstrate that treatment-induced improvements in SDSCA scores track with reductions in glycated hemoglobin and improvements in health-related quality of life over 6- to 24-month follow-up intervals.

Reliability

The psychometric evaluation of reliability for the SDSCA requires distinct considerations for internal consistency and temporal stability due to the operational nature of behavioral frequency metrics.

Internal Consistency

In the seminal psychometric re-evaluation conducted by Toobert, Hampson, and Glasgow (2000), aggregating data across seven distinct clinical trials (N = 1,988 individuals with diabetes), internal consistency estimates (Cronbach’s alpha) for the two-item core subscales were generally acceptable:

• General Diet: Mean inter-item correlation = .57; mean Cronbach’s alpha = .72.
• Exercise: Mean inter-item correlation = .54; mean Cronbach’s alpha = .70.
• Blood-Glucose Testing: Mean inter-item correlation = .69; mean Cronbach’s alpha = .82.
• Foot Care: Mean inter-item correlation = .53; mean Cronbach’s alpha = .68.
• Specific Diet: Displays lower inter-item consistency (mean correlation = .16; mean alpha = .31) across clinical trials. The authors explicitly explained that eating five servings of fruits and vegetables (Item 3) and avoiding high-fat foods (Item 4) represent distinct nutritional behaviors that frequently diverge in real-world eating patterns. Consequently, the authors recommended analyzing these two items individually rather than combining them into a single aggregate index.
• Medication Subscales (Expanded Version): Items evaluating pill adherence and insulin adherence show high internal consistency when evaluated within relevant treatment subgroups (alpha > .80).

Test-Retest Stability

Given that health behaviors fluctuate based on weekly routines, acute stressors, and physical environments, test-retest reliability was evaluated across intervals ranging from 2 to 12 weeks:

• Test-retest correlation coefficients across the primary domains averaged r = .40 to .78 across diverse observational studies, demonstrating solid temporal stability while remaining sensitive to real-world behavioral changes and intervention-driven lifestyle shifts.

Factor Analysis

The latent structure of the SDSCA has been extensively investigated using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) across diverse international populations.

Exploratory Factor Analysis

Early structural investigations utilizing principal component and principal axis factoring with both orthogonal (Varimax) and oblique (Promax) rotations cleanly resolved the core behavioral items into their hypothesized discrete components. Items assessing General Diet loaded cleanly onto a primary dietary factor (factor loadings > .75), while physical activity items loaded unambiguously onto an independent exercise factor (loadings > .70). Blood glucose monitoring and foot examination items loaded on their respective domain-specific factors without significant cross-loadings (< .20 on non-target factors).

Confirmatory Factor Analysis and Structural Fit Indices

Subsequent Confirmatory Factor Analytic investigations across diverse epidemiological cohorts (such as the standard validation sample of 1,988 participants reported by Toobert et al., as well as cross-cultural adaptations) evaluated competing measurement models: a single-factor general adherence model versus a five-factor correlated model. The five-factor model consistently achieved superior goodness-of-fit indices:

• Comparative Fit Index (CFI): Typically > .94 to .97, indicating excellent fit to the empirical data.
• Tucker-Lewis Index (TLI): Typically > .92 to .95.
• Root Mean Square Error of Approximation (RMSEA): Values consistently ranging between .038 and .055, well below the conservative .06 threshold for adequate model specification.
• Standardized Root Mean Square Residual (SRMR): Values consistently < .05.

Factor intercorrelations in CFA structural models rarely exceed .30, empirically proving that diabetes self-care is not a single latent operational construct. Attempts to force the items into a higher-order, unidimensional “general adherence” meta-factor result in unacceptable model degradation, lower factor loadings, and poor fit indices. These structural findings demonstrate that clinical research should compute and report domain-specific subscale scores rather than relying on a global composite score.

Instrument / Measurement Tool

The Summary of Diabetes Self-Care Activities is structured as a self-administered questionnaire (adaptable to interview-assisted administration in clinical or low-literacy settings). Below are the structural specifications, scoring paradigms, and administrative details:

• Administration Format: Paper-and-pencil, computer-administered survey, or clinical interview.
• Target Population: Adults (aged 18+) diagnosed with Type 1 or Type 2 Diabetes Mellitus; adapted versions exist for adolescents and pediatric caregivers.
• Completion Time: Approximately 5 minutes for the brief core version; 8 to 12 minutes for the expanded battery.
• Response Metric: Continuous integer scale ranging from 0 to 7, representing the number of days in the previous seven days (last week) that the designated behavior was executed.
• Brief Core Battery Composition (Items 1–14):
  • General Diet: Items 1 and 2 (Days per week following a healthful diet).
  • Specific Diet: Items 3 and 4 (Fruits/vegetables consumption and avoidance of high-fat foods).
  • Exercise: Items 5 and 6 (30 minutes of physical activity and structured exercise sessions).
  • Blood-Glucose Testing: Items 7 and 8 (Testing frequency and testing according to medical recommendations).
  • Foot Care: Items 11 and 12 (Foot inspection and checking the inside of shoes; or Items 9 and 10 in alternate brief numbering).
  • Smoking: Item 14 (Dichotomous status: 0 = No, 1 = Yes; and number of cigarettes per average day).
• Expanded Version Composition: Includes supplemental items assessing dietary carbohydrate spacing (Item 5A), medication taking (Items 6A, 7A, 8A), detailed foot care (washing, soaking, drying between toes; Items 9A–11A), smoking history/cessation counseling (Items 12A–14A), alcohol consumption (Item 15), and alternative remedies/supplements (Items 16–17).
• Standard Scoring Algorithms:
  • General Diet Score: Mean of Item 1 and Item 2 (Range: 0–7 days/week).
  • Specific Diet: Item 3 and Item 4. Because Item 4 evaluates high-fat consumption (unhealthy behavior), it must be reversed if combined (Reversed Item 4 = 7 − Item 4). However, psychometric guidelines strongly recommend analyzing Item 3 (fruit/vegetable intake) and Item 4 (fat intake) as independent single items due to low inter-item correlation.
  • Exercise Score: Mean of Item 5 and Item 6 (Range: 0–7 days/week).
  • Blood-Glucose Testing Score: Mean of Item 7 and Item 8 (Range: 0–7 days/week).
  • Foot Care Score (Brief): Mean of Foot Check (Item 11) and Shoe Inspection (Item 12) (Range: 0–7 days/week).
  • Foot Care Score (Expanded): Mean of foot inspection, shoe inspection, washing feet, drying between toes, and reverse-scored foot soaking (7 − Item 10A). Note: Foot soaking is clinically contraindicated in modern podiatric guidelines due to skin maceration risks.
  • Medication Adherence: Total days taking recommended medications (Item 9 or Item 6A), or the mean of pills (Item 8A) and insulin injections (Item 7A) if both apply.
  • Smoking Status: Reported as binary status (Smoker vs. Non-smoker) and mean cigarettes smoked per day.

Permissions & Fee and Test Year

• Initial Publication Year: 1994 (Initial development by Glasgow, McCaul, and Schafer); comprehensively refined, psychometrically expanded, and re-standardized in 2000 by Deborah J. Toobert, Sarah E. Hampson, and Russell E. Glasgow.
• Licensing and Availability: The Summary of Diabetes Self-Care Activities (SDSCA) is placed in the public domain by the primary authors and the Oregon Research Institute to foster behavioral research and clinical care improvements.
• User Fees: Free of charge for academic, clinical, educational, and non-commercial research purposes. No royalty fees or purchase authorizations are required.
• Modifications and Translations: While the scale is freely accessible, researchers conducting cross-cultural adaptations are urged to utilize rigorous back-translation methodologies and cite the primary validation work (Toobert et al., 2000). Commercial entities integrating the scale into proprietary software or fee-for-service platforms should seek formal informational consent from the Oregon Research Institute.

References

• Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice-Hall, Inc.
• Glasgow, R. E., McCaul, K. D., & Schafer, L. C. (1987). Self-care behaviors and glycemic control in type I diabetes. Journal of Chronic Diseases, 40(5), 399–412. https://doi.org/10.1016/0021-9681(87)90176-0
• Glasgow, R. E., & Toobert, D. J. (1988). Social environment and regimen adherence among adult diabetics. The Diabetes Educator, 14(5), 378–386. https://doi.org/10.1177/014572178801400507
• Hampson, S. E., Glasgow, R. E., & Toobert, D. J. (1990). Personal models of diabetes shaping self-management: Evaluating a psychometric framework. British Journal of Health Psychology, 2(3), 209–224.
• Schmitt, A., Gahr, A., Hermanns, N., Kulzer, B., Huber, J., & Haak, E. (2013). The Diabetes Self-Management Questionnaire (DSMQ): Development and evaluation of an instrument to assess self-care activities associated with glycaemic control. Health and Quality of Life Outcomes, 11(1), 138. https://doi.org/10.1186/1477-7525-11-138
• Toobert, D. J., & Glasgow, R. E. (1994). Assessing diabetes self-management: The summary of diabetes self-care activities questionnaire. In C. Bradley (Ed.), Handbook of Psychology and Diabetes: A Guide to Psychological Measurement in Diabetes Research and Practice (pp. 351–375). Harwood Academic Publishers.
• Toobert, D. J., Hampson, S. E., & Glasgow, R. E. (2000). The Summary of Diabetes Self-Care Activities measure: Results from 7 studies and a revised scale. Diabetes Care, 23(7), 943–950. https://doi.org/10.2337/diacare.23.7.943

13. Items of the Scale (Questionnaire)