Commonly Experienced Health Care Barriers Index

Abstract

The Commonly Experienced Health Care Barriers Index (CEHCBI) is an empirically derived, brief psychometric instrument developed to quantify systemic, logistical, financial, and relational impediments encountered by individuals seeking medical services. Developed by Alannah Shelby Rivers, Keith Sanford, Morgan Brewington, and Ashley Buchanan (2024), the index was engineered across three rigorous developmental studies explicitly designed to address limitations in conventional health disparities measurement. Unlike traditional reflective scales, the CEHCBI operates as a causal indicator model (formative measurement model), recognizing that distinct barriers collectively precipitate healthcare avoidance, underutilization, and inequity without necessitating high inter-item correlations. The final instrument comprises six concise items rated on a 4-point Likert-type scale ranging from 1 (“NOT true”) to 4 (“completely true”), preceded by standardized situational instructional text assessing preventative checkups and acute illness episodes.

Psychometric evaluations conducted across diverse adult cohorts in the United States establish robust measurement properties. In content domain formulation, a preliminary pool derived from qualitative inquiry was refined via cluster analysis to isolate the core drivers of foregone healthcare. The CEHCBI demonstrates notable test responsiveness, detecting statistically significant disparities between Black and White respondents (d = 0.29, t(739) = 3.65, p < .001), indicating its utility in evaluating racial and structural health disparities. Convergent validity is evidenced by significant associations with health service underutilization (e.g., omitting needed medical care, missed prescription fills, missed outpatient appointments, and non-emergent emergency department utilization), adverse patient experiences (e.g., medical confusion, diminished patient-practitioner therapeutic alliance, reduced health-related quality of life), and acute contextual stressors (e.g., financial strain, perceived stress, neighborhood violence). Evaluation of temporal stability confirmed high 3-week test-retest reliability (r = .83, p < .001). The CEHCBI serves as a pragmatic, highly scalable index for clinical epidemiology, health psychology, and public health surveillance.

Keywords

Commonly Experienced Health Care Barriers Index, CEHCBI, Health Care Disparities, Structural Barriers, Health Care Utilization, Treatment Barriers, Formative Measurement, Causal Indicator Model, Patient-Provider Alliance, Health Equity

Authors

The Commonly Experienced Health Care Barriers Index was conceptualized, developed, and validated through an academic collaboration between Texas Woman’s University and Baylor University:

• Alannah Shelby Rivers, Ph.D. (Corresponding Author)
  Affiliation: Texas Woman’s University, School of Social Work, Psychology, and Philosophy, Denton, Texas, United States.
  ORCID: 0000-0001-8826-4606
  Email: [email protected]
  Mailing Address: P.O. Box 425470, Denton, TX 76204-5470, USA.
• Keith Sanford, Ph.D.
  Affiliation: Baylor University, Department of Psychology and Neuroscience, Waco, Texas, United States.
• Morgan Brewington, M.A.
  Affiliation: Baylor University, Department of Psychology and Neuroscience, Waco, Texas, United States.
  ORCID: 0009-0002-3357-8020
• Ashley Buchanan, M.A.
  Affiliation: Baylor University, Department of Psychology and Neuroscience, Waco, Texas, United States.

Purpose

The primary aim of the Commonly Experienced Health Care Barriers Index is to quantify, monitor, and identify actionable, modifiable impediments that obstruct adults from accessing timely medical evaluation and intervention. Substantial proportions of the population forgo necessary preventative screenings and acute outpatient medical attention, contributing to preventable morbidity, premature mortality, and exacerbated clinical costs when manageable chronic illnesses progress to acute medical crises. Historically, clinical health research has struggled to quantify these barriers using standardized tools that are simultaneously comprehensive, psychometrically sound, and brief enough for deployment within fast-paced clinical workflows and multi-panel epidemiological surveys.

Existing assessments of healthcare barriers have frequently suffered from distinct methodological and practical shortcomings. Many tools are length-prohibitive, consisting of dozens of idiosyncratic questions customized to specific chronic illness populations (e.g., oncology, diabetes, or severe psychiatric disorders), which impedes their generalizability across standard ambulatory populations. Conversely, brief assessments deployed in population-based surveys often rely on single-item indicators of insurance status or household income, which fail to capture the multidimensional matrix of logistical, relational, systemic, and financial factors that dissuade patients from obtaining care. Furthermore, numerous legacy instruments inappropriately apply classical reflective measurement theory to an environmental phenomenon that behaves causally rather than reflectively.

The CEHCBI was created to resolve these critical issues by offering an evidence-based, 6-item instrument specifically optimized to detect everyday barriers across both preventative visits and episodic illness consultations. In clinical and translational settings, the instrument provides primary care providers, hospital social workers, and case managers with a rapid screening tool to identify why patients miss appointments, non-adhere to prescribed treatment plans, or utilize emergency departments for non-emergent conditions. In public health research and health policy evaluation, the CEHCBI serves as an outcome measure to track whether systemic healthcare reforms, community transit programs, or clinic operating hour expansions effectively reduce perceived and actual barriers. Finally, the tool addresses health equity research by providing a validated, standardized index capable of delineating racial, socioeconomic, and geographic disparities in access.

Psychological Construct

The psychological and behavioral construct quantified by the CEHCBI is the perceived and actual presence of friction points across the healthcare engagement continuum that lead directly to care avoidance or deferral. In psychometric theory, health barriers represent external, systemic, and interpersonal constraints that operate as proximal inhibitors of health-seeking actions. Unlike internal traits (such as neuroticism or trait optimism), health barriers are contextual conditions whose presence directly diminishes behavioral execution.

The construct encompasses six distinct, high-impact barrier domains identified through comprehensive qualitative investigation and statistical cluster analysis:

• Financial and Coverage Deprivation: This domain reflects the direct economic strain of healthcare acquisition, encompassing uninsurance, underinsurance, unaffordable out-of-pocket deductibles, copayments, and prescription medication costs. The psychological reality of this barrier involves cost-related dread, where individuals anticipate catastrophic financial distress or debt from seeking medical assistance.
• Transit and Spatial Access Limitations: This domain captures the physical inability to travel to healthcare facilities due to a lack of personal vehicular transportation, inadequate or inaccessible public transit infrastructure, geographic distance, or functional physical immobility. It represents a practical, physical barrier that renders healthcare inaccessible regardless of clinical need.
• Occupational and Role Inflexibility: Quantifying structural demands within the workplace, this domain captures the absence of paid sick leave, rigid working hours, fear of wage loss, or threat of occupational termination. The psychological conflict involves weighing immediate livelihood and employment security against personal physical well-being.
• Absence of Primary Care Continuity: This factor measures the systemic lack of an established primary care physician or medical home. Operating without a regular healthcare provider introduces friction, requiring individuals to navigate unfamiliar administrative bureaucracies, locate new providers, and undergo intake procedures, which heightens cognitive load and decision paralysis during illness.
• Administrative and Scheduling Delays: Reflecting systemic bottlenecks in healthcare operations, this barrier denotes prolonged appointment wait times, provider shortages, and delayed scheduling availability. When patients must wait weeks or months for an appointment, acute conditions may worsen, leading patients to perceive scheduling as futile and abandon care seeking entirely.
• Interpersonal Maltreatment and Perceived Medical Mistrust: This domain evaluates negative interpersonal interactions within clinical environments, including experiences of clinical bias, perceived discrimination, dismissive provider communication, invalidation, or perceived hostility from administrative staff. The affective sequelae include alienation, loss of psychological safety, and reluctance to place oneself in vulnerable medical situations.

Theoretical Framework

The conceptual architecture of the CEHCBI is rooted in health behavior theory, ecological systems frameworks, and advanced psychometric measurement models. Predominantly, the scale aligns with the Health Belief Model (Rosenstock, 1974) and the Behavioral Model of Health Services Use formulated by Ronald M. Andersen (1995).

Andersen’s Behavioral Model of Health Services Use

Andersen’s foundational framework posits that medical service utilization is a direct function of three interacting categories of determinants: predisposing characteristics (e.g., demographic variables, social structure, cultural health beliefs), enabling resources (e.g., personal finances, health insurance, transportation, community health infrastructure), and need factors (e.g., perceived clinical symptoms and professionally evaluated illness). The CEHCBI directly captures deficits within the enabling conditions category. Within Andersen’s model, even when need factors are severe and predisposing attitudes favor medical intervention, an absence of enabling resources introduces immediate structural disruption, suppressing utilization.

The Health Belief Model and Perceived Barriers

Under the Health Belief Model, the probability that an individual will execute a health-protective action (such as obtaining a mammogram, scheduling a diagnostic workup, or consulting a physician for chest pain) depends upon the balance between perceived disease threat (susceptibility and severity) and the perceived net benefit of the protective action minus the perceived barriers. Perceived barriers consistently emerge in empirical meta-analyses as the single most powerful predictor of health behavior non-execution. The CEHCBI standardizes the operationalization of these barriers, moving the field beyond idiosyncratic survey questions into a psychometrically validated index.

Causal Indicator (Formative) Measurement Theory

A central theoretical distinction of the CEHCBI lies in its deliberate operationalization as a causal indicator model (formative model) rather than an effect indicator model (reflective model) (Bollen & Bauldry, 2011). In classical reflective psychometrics (such as measuring depression or general intelligence), the latent construct is hypothesized to cause the item responses; therefore, all items are expected to share substantial positive intercorrelations, exhibit high internal consistency (Cronbach’s alpha), and yield a unidimensional factor structure upon exploratory factor analysis. If one symptom changes, the others are expected to move in tandem.

Conversely, healthcare barriers do not behave as reflective symptoms of an internal mental state; rather, they are external events and environmental conditions that cause the state of health care disenfranchisement. For instance, an individual who experiences reliable public transportation (low transportation barrier) may concurrently experience severe occupational inflexibility (high work barrier) or lack of financial resources (high financial barrier). Forcing these distinct external realities into a reflective framework is conceptually and psychometrically flawed. Because causal indicators need not correlate positively with each other, traditional reflective statistics (such as high inter-item alpha) are neither required nor theoretically expected. Instead, the items collectively construct the composite latent phenomenon.

Validity

The CEHCBI was validated through extensive psychometric methodologies reported by Rivers et al. (2024), establishing strong evidence across content, criterion, convergent, and construct domains.

Content Validity and Item Selection

To establish rigorous content validity without introducing survey fatigue, Rivers and colleagues initially generated a comprehensive pool of candidate items from qualitative investigations and existing healthcare literature. To avoid arbitrary item deletion, the researchers applied statistical cluster analysis to empirical response data. This mathematical grouping isolated discrete clusters representing the primary domains of healthcare friction. From each distinct cluster, the single indicator that demonstrated the highest conceptual clarity, variance, and explanatory power was selected. This process yielded a parsimonious 6-item composite that fully covers the ecological domain of healthcare access friction without psychometric redundancy.

Test Responsiveness and Disparities Sensitivity

Test responsiveness—the capacity of an instrument to differentiate between known groups and accurately detect meaningful disparities—was evaluated across demographic cohorts. The CEHCBI revealed statistically significant disparities between Black and White adult respondents, yielding a meaningful effect size:

d = 0.29, t(739) = 3.65, p < .001

This empirical divergence confirms the instrument’s sensitivity to structural racism, resource distribution inequities, and systemic barriers historically documented across minority healthcare navigation in the United States.

Convergent and Criterion Validity

The scale exhibited robust, statistically significant correlations with an extensive battery of behavioral, psychological, and contextual criteria, confirming that elevated CEHCBI scores predict real-world health detriments:

• Health Care Utilization Failures: Higher CEHCBI scores correlated significantly with omitting medically indicated care, failure to fill or renew essential prescriptions, missing scheduled outpatient consultations, and increased reliance on emergency departments for non-emergent care.
• Patient-Provider Relationship and Medical Navigation: Elevated barrier scores were inversely associated with the strength of the patient-practitioner therapeutic alliance and positively associated with self-reported medical confusion and difficulty comprehending clinical directives.
• Quality of Life and Well-being: CEHCBI scores correlated negatively with overall health-related quality of life (HRQoL), illustrating the psychological burden of unmet medical needs.
• Systemic and Contextual Stressors: Significant convergent associations were demonstrated with broader contextual distress markers, including personal financial crises, general perceived stress, and exposure to community and neighborhood violence.

Reliability

Evaluating the reliability of a causal indicator index requires specialized methodological considerations. In classical reflective psychometrics, internal consistency metrics such as Cronbach’s alpha ($lpha$) or McDonald’s omega ($\omega$) serve as primary indicators of reliability. However, in psychometric literature on formative measurement models (e.g., Bollen, 1989; Diamantopoulos & Winklhofer, 2001), high internal consistency is neither necessary nor mathematically appropriate, as causal indicators represent conceptually distinct environmental events that do not necessarily covary.

Accordingly, the primary indicator of reliability for the CEHCBI is temporal stability assessed via test-retest reliability:

• Full-Scale Temporal Stability: Over a 3-week administration interval, the overall CEHCBI composite demonstrated high test-retest reliability:

  r = .83, p < .001

  This confirms that an individual’s perceived barrier burden remains stable over short intervals in the absence of exogenous socioeconomic or systemic changes.

• Item-Level Temporal Stability: Test-retest reliability coefficients for the individual causal indicators over the 3-week interval ranged from r = .54 to r = .79. These findings demonstrate moderate-to-high individual item consistency over time, with variations reflecting the dynamic nature of specific barriers (e.g., fluctuating work schedules or acute transportation repairs).

Factor Analysis

In accordance with formal causal indicator modeling principles, standard exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are generally not applicable to formative composites in the conventional reflective manner. In classical factor analysis, observed variables are modeled as linear combinations of an underlying common latent factor, assuming that the latent factor accounts for the shared variance among the items (local independence). When indicators are causal, applying reflective common factor analysis produces distorted factor solutions, artificially depressed factor loadings, and misleading fit indices (Bollen & Bauldry, 2011).

Consequently, the empirical derivation of the CEHCBI bypassed traditional factor analysis in favor of cluster analysis during item reduction. Cluster analysis operates without the restrictive assumption that items must share common causal origins, instead grouping candidate items based on semantic and structural proximities across multidimensional space. Through this procedure, the authors identified six core clusters corresponding to the financial, transit, occupational, provider continuity, scheduling, and interpersonal domains. By retaining the highest-performing single item from each cluster, the researchers ensured maximal variance capture with minimal collinearity, precluding the need for traditional reflective factor extraction models.

Instrument / Measurement Tool

• Test Name: Commonly Experienced Health Care Barriers Index (CEHCBI)
• Authors: Alannah Shelby Rivers, Ph.D., Keith Sanford, Ph.D., Morgan Brewington, M.A., and Ashley Buchanan, M.A.
• Test Type: Formative / Causal Indicator Self-Report Index
• Year of Publication: 2023 (Print publication: 2024)
• Target Population: Adult individuals (18 years and older); validated in United States general population and community samples.
• Administration Format: Electronic self-report questionnaire (computer, tablet, or smartphone); adaptable to paper-and-pencil formats.
• Number of Items: 6 items
• Estimated Completion Time: 1 to 2 minutes
• Response Scale: 4-point Likert-type scale scored as:
  • 1 = “NOT true”
  • 2 = “a little true”
  • 3 = “moderately true”
  • 4 = “completely true”
• Scoring Procedures:
  • Total Composite Score: Calculated by summing the numerical values of all 6 items (sum score range: 6 to 24) or by computing the mean across all answered items (mean score range: 1.0 to 4.0). Higher composite scores reflect a greater overall burden of healthcare access barriers.
  • Domain Profile Analysis: Because the CEHCBI is a formative index, individual item scores should be inspected independently in clinical settings to identify specific targets for intervention (e.g., an individual scoring 4 on Item 2 requires transportation coordination rather than financial assistance).
  • Missing Data Handling: If mean scoring is utilized, a minimum of 5 completed items (83%) is recommended to retain score validity.

Permissions & Fee and Test Year

• Test Year: 2023 (Online First); 2024 (Official journal issue publication).
• Copyright & Permissions: The instrument was published under the copyright of the American Psychological Association (APA). The authors and APA permit the use of the scale for academic research, teaching, and non-commercial clinical evaluation purposes without payment of licensing fees.
• Commercial Usage: Any commercial reproduction, inclusion in commercial software platforms, or distribution for profit requires formal permission and licensing from the copyright holder (American Psychological Association) and the corresponding author.
• Primary Contact: Alannah Shelby Rivers, Ph.D., Texas Woman’s University, School of Social Work, Psychology, and Philosophy, P.O. Box 425470, Denton, TX 76204-5470, USA. Email: [email protected].

References

• Andersen, R. M. (1995). Revisiting the behavioral model and access to medical care: Does it matter? Journal of Health and Social Behavior, 36(1), 1–10. https://doi.org/10.2307/2137284
• Bollen, K. A. (1989). Structural equations with latent variables. John Wiley & Sons. https://doi.org/10.1002/9781118619179
• Bollen, K. A., & Bauldry, S. (2011). Three Cs in measurement models: Causal indicators, composite indicators, and covariates. Psychological Methods, 16(3), 265–284. https://doi.org/10.1037/a0024448
• Diamantopoulos, A., & Winklhofer, H. M. (2001). Index construction with formative indicators: An alternative to scale development. Journal of Marketing Research, 38(2), 269–277. https://doi.org/10.1509/jmkr.38.2.269.18845
• Rivers, A. S., Sanford, K., Brewington, M., & Buchanan, A. (2024). Development of a new measure of encounters with health care barriers: The Commonly Experienced Health Care Barriers Index. Psychological Assessment, 36(1), 30–40. https://doi.org/10.1037/pas0001284
• Rosenstock, I. M. (1974). Historical origins of the Health Belief Model. Health Education Monographs, 2(4), 328–335. https://doi.org/10.1177/109019817400200403

Items of the Scale