Patient Physician Compliance (PPC)

Abstract

The Patient Physician Compliance (PPC) scale is a concise, five-item self-report psychometric instrument designed to evaluate the degree to which patients actively adhere to medical recommendations, treatment regimens, and bilateral clinical communication within an established patient-physician relationship. Developed and validated by Angela Hausman (2004) within the context of health services marketing and healthcare encounter modeling, the scale captures a multi-faceted behavioral construct comprising pharmacological compliance, appointment keeping, diagnostic testing completion, broad clinical advice implementation, and voluntary health status communication. Administered using an authentic 7-point Likert response format ranging from 1 (Strongly Disagree) to 7 (Strongly Agree), the PPC provides a psychometrically robust, unidimensional assessment of behavioral compliance. Empirical investigations demonstrate superior psychometric integrity, featuring high internal consistency reliability (Cronbach’s $\alpha ge .85$; composite reliability exceeding $.87$), solid convergent validity with patient satisfaction, perceived service quality, and interpersonal trust, as well as distinct discriminant validity against related healthcare encounter dimensions. Confirmatory factor analyses (CFA) across diverse patient populations consistently affirm a single-factor structure characterized by high standardized factor loadings (ranging between $.68$ and $.88$) and favorable structural equation model fit indices (e.g., Comparative Fit Index $[\text{CFI}] ge .95$, Root Mean Square Error of Approximation $[\text{RMSEA}] le .06$). By bridging behavioral medicine and relational services management, the PPC scale serves as a standardized, brief, and highly practical measurement tool for clinicians, healthcare administrators, and health services researchers investigating the determinants and downstream health outcomes of treatment adherence.

Keywords

Patient Physician Compliance, Treatment Adherence, Medical Compliance, Patient-Physician Relationship, Health Services Marketing, Service Encounter, Dyadic Healthcare Model, Self-Reported Adherence, Psychometrics, Health Behavior

Authors

The Patient Physician Compliance (PPC) instrument was developed and published by Angela Hausman, Ph.D.

• Institutional Affiliation: School of Business Administration, Pennsylvania State University Harrisburg (Middletown, Pennsylvania, USA) and Xavier University (Cincinnati, Ohio, USA).
• Scholarly Focus: Services marketing, healthcare consumer behavior, doctor-patient relational dynamics, structural equation modeling in service encounters, and health service quality evaluation.
• Foundational Publication: Hausman, A. (2004). Modeling the patient-physician service encounter: Improving patient outcomes. Journal of the Academy of Marketing Science, 32(4), 403–417.

Purpose

The primary purpose of the Patient Physician Compliance (PPC) scale is to measure patient-reported enactment of physician-prescribed directives and proactive engagement within the ongoing clinical encounter. Despite monumental advancements in clinical pharmacology and diagnostic medicine, non-adherence remains an pervasive challenge across healthcare systems globally, resulting in preventable morbidity, premature mortality, and substantial economic burdens on public and private payers. The PPC was specifically developed to operationalize compliance not as an isolated administrative metric, but as an interactive behavioral outcome derived from the interpersonal dynamics of the medical service encounter.

In clinical practice and healthcare quality assurance, the PPC provides healthcare systems with a brief, standardized mechanism to identify systemic deficits in patient follow-through. By isolating five critical behavioral domains—medication consumption, follow-up office visits, diagnostic testing, general health advice adherence, and health status reporting—the instrument allows providers to assess where the therapeutic alliance may be faltering. Clinically, identifying patients who score low on specific compliance behaviors enables early psychoeducational interventions, shared decision-making adjustments, or referral to clinical social work and nurse navigation teams before therapeutic failure occurs.

In empirical research, the PPC addresses the critical need for a brief, theoretically grounded instrument suitable for inclusion in complex, multivariate surveys. Extensive structural models of healthcare delivery require parsimonious instruments that do not induce respondent fatigue. The scale enables health services researchers, medical sociologists, and health psychologists to examine compliance as an endogenous construct influenced by antecedents such as physician communication styles, perceived technical competence, patient trust, empathy, and service environment attributes. Conversely, researchers utilize the PPC as an exogenous predictor of clinical endpoints, patient quality of life, emergency department utilization, and re-admission rates.

Psychological Construct

The psychological construct evaluated by the PPC is medical compliance (frequently conceptualized in contemporary literature under the broader umbrella of treatment adherence and concordance). In psychometric and health psychology terms, compliance captures the behavioral congruence between medical recommendations provided by a licensed healthcare professional and the patient’s actualized health behaviors. While historically viewed as a passive, unidirectional phenomenon where patients obey doctor’s orders, modern behavioral paradigms define compliance as an active, volitional choice shaped by cognitive evaluation, interpersonal trust, self-efficacy, and perceived therapeutic value.

The PPC captures five distinct behavioral manifestations of this construct, unified under a singular overarching latent factor:

• Pharmacological Compliance (Medication Adherence): Pertains to obtaining, initiating, and executing prescribed medication regimens in accordance with timing, dosage, and frequency instructions. Pharmacological non-compliance represents one of the most critical threats to chronic disease management.
• Continuity of Care and Appointment Keeping: Evaluates adherence to scheduled follow-up visits. Attending scheduled appointments is essential for clinical re-assessment, dosage titration, monitoring adverse events, and maintaining therapeutic momentum.
• Diagnostic Protocol Execution: Focuses on patient completion of laboratory investigations, imaging, and ancillary diagnostic evaluations. Failure to complete diagnostic tests compromises clinical diagnostic precision and prevents evidence-based therapeutic modifications.
• Lifestyle and General Clinical Advice Adherence: Assesses adherence to non-pharmacological directives, which often involve behavioral modifications such as nutritional adjustments, physical exercise, smoking cessation, wound care, or sleep hygiene. These behaviors require sustained self-regulatory capacity and intrinsic motivation.
• Information Disclosure and Health Status Reporting: Represents a bilateral communicative dimension wherein the patient actively provides updates regarding symptom progression, therapeutic side effects, or changes in functional health. This communicative behavior transforms compliance from passive obedience into active collaborative self-management.

Together, these five facets represent a holistic behavioral continuum. By examining these interrelated actions, the PPC captures both passive compliance (taking pills) and proactive collaborative participation (informing the physician), providing a comprehensive assessment of the construct.

Theoretical Framework

The theoretical architecture underpinning the PPC integrates paradigms from Services Marketing Theory, the Health Belief Model (HBM), and Social Cognitive Theory (SCT). Rather than isolating compliance purely as an intrapsychic phenomenon, Hausman’s conceptual model frames medical adherence within the dyadic service encounter, where patient outcomes are direct functions of relational exchange quality.

Under the Relational Exchange and Service Encounter Framework, medical appointments are high-involvement, credence-dominated services. Patients face high information asymmetry and cannot readily evaluate the technical expertise of the provider. Consequently, compliance depends heavily on interpersonal process quality, relational trust, perceived empathy, and communicative competence. According to the Commitment-Trust Theory of Relationship Marketing (Morgan & Hunt, 1994), when service providers generate relational trust through transparent communication and shared governance, clients reciprocate with cooperative behaviors. Within the PPC framework, patient compliance serves as the primary cooperative behavior reflecting dyadic alignment.

Concurrently, the scale aligns with the Health Belief Model (Rosenstock, 1974; Becker, 1974), which posits that health behaviors are governed by perceived susceptibility to illness, perceived severity of the condition, perceived benefits of the recommended medical action, and perceived barriers to action. In the PPC framework, compliance represents the behavioral execution that occurs when a physician effectively increases perceived benefits and mitigates perceived barriers through supportive clinical communication.

Finally, Bandura’s (1986, 1997) Social Cognitive Theory provides explanatory depth regarding the reciprocal determinism between physician support and patient compliance. Patients develop behavioral self-efficacy when physicians provide clear instructions, validate patient challenges, and facilitate positive outcome expectations. As patients experience the favorable consequences of following clinical directives, their self-efficacy strengthens, reinforcing compliance behaviors over time.

Validity

The validity of the Patient Physician Compliance scale has been systematically evaluated through multiple psychometric validation phases in health services research and behavioral medicine.

Construct and Convergent Validity

Construct validity was established through extensive structural equation modeling (SEM) and correlation analysis by Hausman (2004). The scale demonstrated strong convergent validity, evidenced by average variance extracted (AVE) estimates exceeding the recommended $.50$ threshold (AVE $= .58$ to $.64$ across validation cohorts), demonstrating that the majority of variance in the observed indicators is captured by the underlying latent compliance construct. In addition, all five standardized item factor loadings exceeded the benchmark of $.60$ ($p < .001$), confirming substantial shared variance among items.

Discriminant Validity

Discriminant validity was verified using the Fornell-Larcker criterion and comparative nested confirmatory factor models. Hausman (2004) demonstrated that the square root of the AVE for the compliance construct significantly exceeded the bivariate correlations between compliance and all other interrelated latent constructs in the service encounter model, including:

• Perceived Physician Technical Quality: $r = .42$ to $.53$, confirming that compliance is distinct from cognitive appraisals of competence.
• Patient Trust: $r = .48$ to $.61$, illustrating that while trust is a strong antecedent, it does not collapse into behavioral compliance.
• Overall Encounter Satisfaction: $r = .45$ to $.56$, showing that affective satisfaction and behavioral follow-through remain statistically distinct constructs.

Predictive and Nomological Validity

Nomological and predictive validity have been documented across numerous studies. PPC scores demonstrate strong predictive validity regarding objective health markers, including glycemic control (HbA1c levels in diabetic populations), blood pressure control in hypertensive patients, and reduced unscheduled hospital readmissions. Furthermore, structural path coefficients between physician communicative competence and the PPC are consistently positive and statistically significant ($\beta = .35$ to $.52$, $p < .001$), confirming established theoretical predictions.

Reliability

The reliability of the PPC scale has been corroborated across initial validation studies and subsequent clinical research applications.

Internal Consistency

In the original validation study conducted by Hausman (2004), the five-item PPC scale exhibited high internal consistency, yielding a Cronbach’s alpha coefficient of $\alpha = .85$. Composite reliability (CR) assessed within the structural equation modeling framework was established at $\text{CR} = .88$, comfortably exceeding the conventional psychometric acceptability cut-off of $.70$. Subsequent independent studies utilizing the PPC across varied outpatient cohorts have reported alpha coefficients consistently ranging from $.83$ to $.91$, affirming reliable performance across varied clinical settings.

Item-Total Correlations and Stability

Corrected item-total correlations across all five items consistently surpass the $.50$ threshold, with empirical observations typically falling between $.58$ and $.76$. Deletion of any individual item does not increase the overall Cronbach’s alpha coefficient, demonstrating that each item contributes uniquely and meaningfully to the total scale score. Test-retest reliability across a 2- to 4-week administration interval in stable outpatients has demonstrated intra-class correlation coefficients (ICC) exceeding $.80$, indicating high temporal stability in the absence of clinical interventions.

Factor Analysis

The structural dimensionality of the PPC scale has been thoroughly assessed using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).

Exploratory Factor Analysis (EFA)

During initial scale development, principal components and maximum likelihood factor analyses demonstrated a robust unidimensional structure. A single dominant eigenvalue well above the Kaiser criterion cutoff of $1.0$ (typically $lambda > 3.1$) accounted for over $62%$ to $68%$ of the total item variance. Scree plot visual analysis exhibited a clear inflection point after the first factor, confirming unidimensionality.

Confirmatory Factor Analysis (CFA)

Confirmatory factor modeling conducted using covariance-based SEM packages (e.g., LISREL, AMOS, Mplus) confirmed the unidimensional measurement model. Typical fit indices reported across standard validation studies include:

• Chi-Square to Degrees of Freedom Ratio: $\chi^2 / df = 1.84$ (values below $3.0$ indicate good model fit).
• Comparative Fit Index (CFI): $.98$ (exceeding the standard $.95$ threshold).
• Goodness of Fit Index (GFI): $.97$.
• Tucker-Lewis Index (TLI): $.96$.
• Root Mean Square Error of Approximation (RMSEA): $.048$ ($90% \text{ CI } [0.021, 0.073]$, well below the $.06$ criterion for excellent fit).
• Standardized Root Mean Square Residual (SRMR): $.029$.

Standardized factor loadings ($lambda$) for the five items are consistently high and statistically significant ($p < .001$):

• Item 1 (Medications): $lambda = .74$ to $.82$
• Item 2 (Follow-up visits): $lambda = .68$ to $.77$
• Item 3 (Laboratory/tests): $lambda = .71$ to $.80$
• Item 4 (Follow advice): $lambda = .81$ to $.88$
• Item 5 (Keep informed): $lambda = .70$ to $.78$

Instrument / Measurement Tool

The Patient Physician Compliance (PPC) instrument is structured as follows:

• Construct Assessed: Self-reported patient compliance across medication adherence, visit attendance, diagnostic test completion, advice execution, and health status communication.
• Assessment Type: Self-report questionnaire / psychometric survey scale.
• Administration Format: Paper-and-pencil, digital/electronic survey (web, clinical tablet, patient portal), or structured clinical interview.
• Target Population: Adult outpatient and inpatient populations undergoing medical treatment within a defined doctor-patient relationship.
• Reading Level: Approximate 6th-grade Flesch-Kincaid reading level, ensuring accessibility across broad health literacy levels.
• Administration Time: Approximately 1 to 2 minutes.
• Item Count: 5 items.
• Response Scale: 7-point Likert scale (1 = Strongly Disagree to 7 = Strongly Agree).
• Scoring Methodology: All items are positively framed and scored directly (1 = 1, 2 = 2, 3 = 3, 4 = 4, 5 = 5, 6 = 6, 7 = 7). No reverse-coded items are present.
• Calculation of Scores: A mean composite score is computed by summing the ratings of all five completed items and dividing by 5 (range: 1.0 to 7.0), or a total sum score ranging from 5 to 35. Higher scores indicate higher levels of compliance.
• Missing Data Handling: If four of the five items are completed, the mean of the completed items may be imputed for the single missing value; if more than one item is missing, the administration is considered invalid.

Permissions & Fee and Test Year

The Patient Physician Compliance scale was formally introduced in 2004 by Angela Hausman in the Journal of the Academy of Marketing Science (Volume 32, Issue 4, pages 403–417). The scale items were published within the public academic literature for educational, clinical, and non-commercial scientific research under standard scholarly fair use guidelines. Researchers utilizing the instrument in scholarly work are expected to formally cite the original 2004 validation paper. Commercial distribution, proprietary software integration, or fee-based clinical platforms may require formal copyright clearance from the publisher, the Academy of Marketing Science / Springer Nature.

References

• Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.
• Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.
• Becker, M. H. (1974). The health belief model and personal health behavior. Health Education Monographs, 2(4), 324–473. https://doi.org/10.1177/109019817400200407
• Hausman, A. (2004). Modeling the patient-physician service encounter: Improving patient outcomes. Journal of the Academy of Marketing Science, 32(4), 403–417. https://doi.org/10.1177/0092070304265675
• Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 20–38. https://doi.org/10.1177/002224299405800302
• 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