Advance Care Planning Practice Preference Scale

1. Abstract

The Advance Care Planning Practice Preference Scale (ACPPPS), developed by Zhen Yang, Huan Wang, and Aiping Wang (2023), is a psychometrically validated self-report instrument engineered to evaluate advance care planning (advance care planning; ACP) practice preferences among clinical nurses. Grounded conceptually in Icek Ajzen’s Theory of Planned Behavior (TPB), the instrument was established to identify the cognitive, normative, and control-based antecedents that drive or impede nursing professionals from initiating and supporting end-of-life decision-making processes. The scale’s development emerged from an extensive literature review, semi-structured qualitative interviews, focus groups, and two successive rounds of Delphi expert consultation, condensing an initial pool of 78 items down to 24 final items. Responses are scored using a five-point Likert scale.

Psychometric evaluation demonstrates structural flexibility, allowing the instrument to be operationalized as either a six-factor first-order structure (comprising Behavioral Belief, Result Evaluation, Normative Belief, Compliance Motivation, Control Belief, and Perceived Intensity) or a hierarchical second-order three-factor framework (reflecting Behavioral Attitudes, Subjective Norms, and Perceived Behavioral Control). Content validity is supported by an Item-Content Validity Index (I-CVI) ranging from 0.857 to 1.000 and a Scale-Content Validity Index (S-CVI) of 0.958. Confirmatory factor analysis confirms excellent structural fit for the second-order model (χ²/df = 1.492, RMSEA = 0.038, CFI = 0.956, TLI = 0.950, GFI = 0.920). Internal consistency is verified by Cronbach’s α coefficients across dimensions ranging from 0.703 to 0.904 in the six-factor model and from 0.765 to 0.863 in the three-factor model, alongside satisfactory two-week test–retest reliability (0.769–0.962). The ACPPPS provides hospital administrators, nurse educators, and clinical researchers with an empirically robust diagnostic tool to identify barriers, target continuing education, and improve palliative care communication in clinical settings.

2. Keywords

Advance Care Planning, Clinical Nurses, Theory of Planned Behavior, Behavioral Attitudes, Subjective Norms, Perceived Behavioral Control, Palliative Care, End-of-Life Care, Psychometrics, Factor Analysis, Nursing Practice Preferences, Clinical Decision-Making

3. Authors

The Advance Care Planning Practice Preference Scale was developed and validated by a research team at the First Affiliated Hospital of China Medical University in Shenyang, Liaoning Province, China:

• Zhen Yang, Department of Public Service, First Affiliated Hospital of China Medical University, Shenyang, China. ORCID: 0000-0002-6197-6168.
• Huan Wang, Department of Public Service, First Affiliated Hospital of China Medical University, Shenyang, China.
• Aiping Wang (Corresponding Author), Department of Public Service, First Affiliated Hospital of China Medical University, No. 155 Nanjing North Street, Heping District, Shenyang 110001, Liaoning Province, China. Email: [email protected].

4. Purpose

Advance care planning constitutes an ongoing, interactive communication process whereby patients, together with their healthcare providers and families, articulate, define, and document their personal values, life goals, and preferences for future medical treatments in anticipation of diminished decision-making capacity (Sudore et al., 2017). While international healthcare guidelines strongly advocate for proactive ACP engagement to reduce non-beneficial interventions, minimize patient suffering, and alleviate surrogate decision-making distress, substantial translation gaps persist in daily clinical practice. Registered nurses occupy a pivotal position at the bedside, spending more time in direct communication with patients and families than any other healthcare professionals. Consequently, they are uniquely positioned to recognize patient transitions, provide timely end-of-life information, and initiate early ACP discussions.

Despite this advantageous positioning, clinical nurses globally—and across Asian healthcare systems in particular—frequently exhibit reluctance, moral hesitation, or operational anxiety regarding the initiation of ACP dialogues. Several systemic and individual hurdles impede nursing involvement, including deficits in specialized communication skills, death taboos deeply embedded in sociocultural environments, ambiguity surrounding professional roles versus physician prerogatives, fear of inflicting emotional distress on families, and acute clinical time constraints. Historically, measuring nurses’ engagement in ACP relied on heterogeneous questionnaires that conflated knowledge levels, general death anxiety, or isolated institutional practices without an organizing theoretical framework.

The Advance Care Planning Practice Preference Scale was engineered to resolve these diagnostic and evaluative limitations. Specifically, the scale achieves several clinical and academic objectives:

• Diagnostic Profiling: It provides a standardized assessment of the internal motivational, normative, and environmental factors that govern clinical nurses’ willingness to engage in ACP practices.
• Educational Needs Assessment: By dissecting preferences across behavioral attitudes, subjective social pressures, and self-efficacy constructs, hospital educators can identify whether a clinical unit requires ethical clarification, systemic institutional support, or communication simulation training.
• Intervention Evaluation: It serves as a sensitive pre- and post-intervention outcome measure to evaluate the efficacy of continuing education programs, clinical workshops, and hospital policy transitions focused on palliative care delivery.
• Cross-Cultural Research: The instrument establishes a psychometrically validated baseline within acute and chronic clinical environments, facilitating comparative studies exploring how traditional beliefs, legal frameworks, and organizational support structures shape nursing behavior.

5. Psychological Construct

The psychological construct measured by the ACPPPS is Advance Care Planning Practice Preference, defined as a professional nurse’s internalized propensity, behavioral inclination, and perceived capability to initiate, facilitate, and sustain advance care planning conversations with patients and their families. Grounded in the structural logic of social cognitive decision-making, the construct can be operationalized across two congruent psychometric configurations: an in-depth six-factor model and a consolidated three-factor higher-order framework.

The Six First-Order Dimensions

• Behavioral Belief (BB): Reflects the nurse’s cognitive appraisal regarding the intrinsic advantages and clinical outcomes of ACP. It encompasses beliefs that early ACP facilitates dignified end-of-life transitions, preserves patient autonomy, optimizes symptom relief, and minimizes surrogate bereavement conflict. Nurses with elevated behavioral beliefs recognize ACP as a core clinical benefit rather than an administrative burden.
• Result Evaluation (RE): Denotes the affective value or subjective weight the nurse attaches to the perceived positive outcomes of ACP. While Behavioral Belief assesses the likelihood that an outcome will occur (e.g., “ACP clarifies patient treatment goals”), Result Evaluation measures how deeply the nurse values that consequence (e.g., “Achieving goal-concordant end-of-life care is an essential clinical imperative”).
• Normative Belief (NB): Represents the nurse’s perception of expectations held by salient social and professional referents. This includes expectations from attending physicians, head nurses, institutional leadership, interdisciplinary team members, and patients’ family members concerning whether nurses should actively participate in ACP conversations.
• Compliance Motivation (CM): Refers to the nurse’s psychological readiness and internal drive to conform to the expectations of those professional and familial referents. High compliance motivation indicates that a nurse values interprofessional alignment and actively seeks approval from clinical leaders and families when executing end-of-life care plans.
• Control Belief (CB): Measures the nurse’s perception of the presence or absence of specific facilitating factors and operational barriers. These include availability of institutional standard operating procedures, access to private discussion environments, dedicated clinical time, legal protection, and specialized communication toolkits.
• Perceived Intensity (PI): Captures the nurse’s appraisal of how strongly these facilitating resources or practical impediments influence their daily clinical practice. It reflects the degree of perceived difficulty or empowerment experienced when attempting to integrate ACP into routine ward workflows.

The Three Higher-Order Latent Constructs

In accordance with cognitive behavioral modeling, the six primary factors converge into three overarching latent domains:

• Behavioral Attitudes (BA): Formed by the interaction of Behavioral Beliefs and Result Evaluations ($\sum b_i e_i$). This construct represents the nurse’s overall positive or negative affective and cognitive evaluation of personally engaging in ACP practice.
• Subjective Norms (SN): Formed by the interaction of Normative Beliefs and Compliance Motivation ($\sum n_j m_j$). This reflects perceived social and institutional pressure to engage in or abstain from advance care planning behaviors.
• Perceived Behavioral Control (PBC): Formed by the interaction of Control Beliefs and Perceived Intensity ($\sum c_k p_k$). This captures the nurse’s perceived ease or difficulty of performing ACP tasks, encapsulating self-efficacy and external resource adequacy.

6. Theoretical Framework

The conceptual foundation of the Advance Care Planning Practice Preference Scale is built upon the Theory of Planned Behavior, formulated by social psychologist Icek Ajzen (1991) as an extension of the Theory of Reasoned Action (Fishbein & Ajzen, 1975). The TPB posits that human social behavior is guided by three distinct varieties of considerations: beliefs about the likely consequences of the behavior (behavioral beliefs), beliefs about the normative expectations of significant others (normative beliefs), and beliefs about the presence of factors that may facilitate or impede performance of the behavior (control beliefs).

In their aggregate, behavioral beliefs produce a favorable or unfavorable attitude toward the behavior; normative beliefs result in perceived social pressure or subjective norm; and control beliefs give rise to perceived behavioral control. In combination, attitude toward the behavior, subjective norm, and perception of behavioral control lead to the formation of a behavioral intention. Because intention is the immediate antecedent of action, individuals are expected to carry out their intentions when presented with adequate actual control over the behavior.

Yang, Wang, and Wang (2023) translated this structural architecture directly into the domain of clinical end-of-life nursing. Advance care planning is not merely a technical clinical task; it is a morally loaded, interpersonally sensitive, and legally complex behavior occurring within multidisciplinary hospital ecologies. Consequently:

• Nurses do not practice ACP in an attitudinal vacuum; their willingness depends on whether they perceive tangible patient benefit (Behavioral Attitude). If a nurse believes discussing mortality causes psychological trauma to a patient without altering medical management, their attitude remains unfavorable, depressing practice preference.
• Nurses operate within hierarchical institutional networks. The subjective norm construct reflects how medical authority, nursing supervisory hierarchy, and family expectations dictate the boundaries of acceptable nursing intervention. If institutional policy implicitly reserves prognosis discussions for senior medical staff, the nurse experiences negative subjective norms toward initiating ACP.
• Even when attitudes and social norms are favorable, complex clinical demands require tangible self-efficacy and institutional resources (Perceived Behavioral Control). If nurses lack private conference rooms, validated documentation systems, or legal clarification regarding living wills, their perceived behavioral control declines, inhibiting practice preference.

By capturing both the underlying belief-evaluation substructures (first-order factors) and the core socio-cognitive domains (second-order factors), the ACPPPS operationalizes the TPB with fidelity, providing a robust theoretical blueprint for behavior change interventions.

7. Validity

The Advance Care Planning Practice Preference Scale was subjected to rigorous psychometric validation protocols encompassing content validity, construct validity, convergent validity, and discriminant validity.

Content Validity

The initial scale draft, comprising 78 candidate items, was synthesized from systematic literature extraction and qualitative thematic findings derived from semi-structured interviews with clinical bedside nurses. To assess relevance, representativeness, and clarity, a two-round Delphi expert consultation was conducted involving multidisciplinary specialists across palliative medicine, clinical nursing management, bioethics, and psychometrics. The expert panels demonstrated outstanding engagement, yielding a 100% response rate across both rounds. Quantitative assessment yielded an Item-Content Validity Index (I-CVI) ranging from 0.857 to 1.000 across retained items, surpassing the conventional psychometric threshold of 0.78. The overall Scale-Content Validity Index (S-CVI/Ave) reached 0.958, demonstrating superior content representativeness.

Construct Validity

Construct validity was examined through item analysis and structural equation modeling (SEM). Critical ratio tests and correlation analysis systematically refined the measure, leading to the extraction and retention of 24 highly discriminative items. Exploratory factor analysis (EFA) demonstrated clean factor structures for both first-order and second-order models, explaining significant proportions of total variance. Subsequent confirmatory factor analysis (CFA) cross-validated these structures in independent clinical samples, corroborating both the six-factor first-order paradigm and the three-factor second-order hierarchical construct.

Convergent and Discriminant Validity

Convergent validity was evaluated using Composite Reliability (CR) and Average Variance Extracted (AVE) metrics, while discriminant validity was established using the Fornell–Larcker criterion:

• First-Order Factor Model (6 Factors): The AVE values across all six constructs ranged from 0.594 to 0.794, comfortably exceeding the standard benchmark of 0.50. The corresponding Composite Reliability (CR) values ranged from 0.846 to 0.934, indicating excellent internal convergent strength. In accordance with the Fornell–Larcker standard, the square root of the AVE for each construct ranged from 0.771 to 0.868, values that were uniformly greater than the inter-factor correlation coefficients between the respective constructs, demonstrating strong discriminant validity.
• Second-Order Factor Model (3 Factors): The AVE values for the higher-order constructs of Behavioral Attitudes, Subjective Norms, and Perceived Behavioral Control ranged from 0.537 to 0.580, with CR values spanning 0.887 to 0.919. The square root of the AVE values ranged from 0.733 to 0.762, all exceeding the inter-construct correlation estimates, thereby confirming robust discriminant boundaries at the higher-order structural level.

8. Reliability

Reliability of the ACPPPS was evaluated across three distinct psychometric dimensions: internal consistency, split-half reliability, and temporal stability (test–retest reliability).

Internal Consistency

Internal consistency was assessed using Cronbach’s alpha (α) coefficients across both structural conceptualizations:

• Six-Factor Model: Cronbach’s α coefficients across the individual subscales ranged from 0.703 to 0.904. Each subscale met or exceeded the generally accepted psychometric standard of 0.70, indicating high item homogeneity within specific belief and evaluation domains.
• Three-Factor Model: When collapsed into the broader Theory of Planned Behavior constructs (Behavioral Attitudes, Subjective Norms, and Perceived Behavioral Control), Cronbach’s α coefficients ranged from 0.765 to 0.863, demonstrating solid internal consistency for higher-order aggregation.

Split-Half Reliability

Split-half coefficients were computed by dividing scale items into odd and even halves:

• Six-Factor Model: Split-half reliability coefficients ranged from 0.624 to 0.903 across the six dimensions.
• Three-Factor Model: Split-half reliability coefficients ranged from 0.653 to 0.680 across the three broader constructs.

Test–Retest Reliability

To determine temporal stability, a randomly selected subsample of clinical nurses completed the instrument again following a two-week interval under matching clinical conditions:

• Six-Factor Model: Test–retest correlation coefficients across the six subscales ranged from 0.771 to 0.910.
• Three-Factor Model: Test–retest reliability coefficients for the three higher-order domains ranged from 0.769 to 0.962.

These temporal metrics confirm that the scale is stable over time and not prone to daily state-dependent fluctuations, making it suitable for longitudinal tracking and interventional trials.

9. Factor Analysis

The structural framework of the ACPPPS was determined through sequential exploratory and confirmatory factor analytic procedures conducted on separate validation cohorts.

Exploratory Factor Analysis (EFA)

Following item screening from the initial 78-item candidate pool, exploratory factor analysis was performed to uncover the latent structural dimensionality. Principal component analysis with varimax orthogonal rotation supported the emergence of either a detailed first-order six-factor solution or a second-order three-factor solution:

• The first-order six-factor model explained 77.933% of the cumulative total variance, reflecting substantial capture of the variance across the 24 items.
• The second-order three-factor model accounted for 57.305% of the cumulative variance, representing an acceptable and parsimonious summary of the primary cognitive domains.

Confirmatory Factor Analysis (CFA)

Confirmatory factor analysis using maximum likelihood estimation evaluated the fit of both configurations on independent cross-validation samples:

• Second-Order Three-Factor Model Fit: The hierarchical model yielded excellent fit indices across all standard psychometric criteria:
  • Relative Chi-Square (χ²/df) = 1.492 (well below the conservative threshold of 2.0–3.0).
  • Root Mean Square Error of Approximation (RMSEA) = 0.038 (indicating close fit, < 0.05).
  • Comparative Fit Index (CFI) = 0.956 (> 0.95, indicating superior fit).
  • Tucker–Lewis Index (TLI) = 0.950 (≥ 0.95).
  • Incremental Fit Index (IFI) = 0.956.
  • Goodness-of-Fit Index (GFI) = 0.920 (> 0.90).
  • Adjusted Goodness-of-Fit Index (AGFI) = 0.902 (> 0.90).
  • Parsimony Goodness-of-Fit Index (PGFI) = 0.745.
  • Parsimonious Normed Fit Index (PNFI) = 0.773.
• Alternative Model Fit Comparisons: The standalone first-order six-factor model yielded χ²/df = 1.512, whereas the direct first-order three-factor model yielded χ²/df = 1.778. Both alternatives demonstrated adequate fit, confirming the operational flexibility of the scale while demonstrating that the second-order model provides the optimal balance of parsimony and structural fidelity.

10. Instrument / Measurement Tool

The Advance Care Planning Practice Preference Scale is structured as an objective, self-administered survey tool. Its operational specifications are summarized below:

• Tool Name: Advance Care Planning Practice Preference Scale (ACPPPS).
• Alternate Names: ACP Practice Preference Scale.
• Original Authors: Zhen Yang, Huan Wang, and Aiping Wang (2023).
• Primary Target Population: Clinical registered nurses practicing in adult inpatient wards, intensive care units, oncology departments, geriatric care units, and palliative/hospice settings.
• Age Demographics: Adults (18 years and older; predominantly young adult and mid-career clinical nurses aged 18–39 years).
• Language Available: Chinese (original validation); can be culturally adapted following standard forward-backward translation protocols.
• Item Count: 24 standardized items.
• Response Scale: Items are rated using a Likert five-point scoring system.
• Subscale Structural Options:
  • Six-Factor Architecture: Behavioral Belief, Result Evaluation, Normative Belief, Compliance Motivation, Control Belief, Perceived Intensity.
  • Three-Factor Architecture: Behavioral Attitudes, Subjective Norms, Perceived Behavioral Control.
• Scoring Procedures: Item scores within each subscale are summed or averaged to generate dimension-specific composite indices. Total scale scores provide an overarching metric of overall ACP practice preference. Higher numerical scores denote stronger behavioral attitudes, greater supportive subjective norms, higher perceived behavioral control, and a stronger overall preference to practice ACP in daily clinical nursing care.
• Administration Time: Approximately 8 to 12 minutes.

11. Permissions & Fee and Test Year

The Advance Care Planning Practice Preference Scale was developed and published in 2023. Essential administrative and licensing details include:

• Copyright & Ownership: The scale is copyrighted by the original authors (Yang, Wang, & Wang) and John Wiley & Sons Ltd., the publisher of the Journal of Advanced Nursing.
• Commercial Use: Non-commercial. The tool was developed for academic, scientific, and healthcare quality improvement initiatives. It is not licensed for commercial exploitation without prior written consent.
• Fee: Free of charge for non-commercial academic research, institutional clinical audits, and educational evaluations.
• Permissions & Access: Researchers and clinical administrators wishing to utilize the complete Chinese questionnaire or pursue cultural adaptation/translation into other languages must contact the corresponding author, Prof. Aiping Wang, via email at [email protected]. Formal permission requests should describe the study objectives, target population, and institutional setting.

12. References

• Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
• Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
• Sudore, R. L., Lum, H. D., You, J. J., Hanson, L. C., Meier, D. E., Pantilat, S. Z., Reb, A. M., Swetz, K. M., Fink, R. M., & Heyland, D. K. (2017). Defining advance care planning for adults: A consensus definition from a multidisciplinary Delphi panel. Journal of Pain and Symptom Management, 53(5), 821–832.e1. https://doi.org/10.1016/j.jpainsymman.2016.12.331
• Yang, Z., Wang, H., & Wang, A. (2023). Development and validation of the advance care planning practice preference scale for clinical nurses. Journal of Advanced Nursing, 79(7), 2695–2708. https://doi.org/10.1111/jan.15641

13. Items of the Scale