Advance Care Planning Practice Preference Scale

Abstract

The Advance Care Planning (ACP) Practice Preference Scale is an original 24-item psychometric instrument developed by Yang, Wang, and Wang (2023). Its primary function is to assess the specific practice preferences regarding Advance Care Planning among clinical nurses. The data collected from this instrument is designed to inform and facilitate the creation of effective, targeted educational interventions for improving ACP implementation in healthcare settings. Scale development followed a rigorous methodology, including an extensive literature review, semi-structured interviews, and two rounds of Delphi expert consultation. Subsequent item analysis and factor analysis confirmed a robust structure, allowing for interpretation using either a 6-factor or a 3-factor model. Comprehensive evidence supporting the scale’s reliability and validity has been reported.

Keywords

Advance Care Planning Practice Preferences, Behavioral Attitudes, Behavioral Belief, Clinical Nurses, Clinical Nursing, Compliance Motivation, Control Belief, Normative Belief, Perceived Behavioral Control, Perceived Intensity, Result Evaluation, Subjective Norms, Clinical Practice, Health Personnel Attitudes, Hospice, Nurses, Nursing, Preferences, Treatment Planning, Health Care Personnel Measures.

Authors

Yang, Zhen, Wang, Huan, Wang, Aiping

Purpose

The core purpose of the Advance Care Planning Practice Preference Scale is to systematically quantify and evaluate the attitudes, beliefs, and perceived control that clinical nurses hold regarding the practice of Advance Care Planning (ACP).

By measuring these preferences, the instrument provides essential diagnostic data for health administrators and educators. This data is crucial for designing and implementing focused educational programs aimed at overcoming barriers and enhancing nurses’ engagement and competence in facilitating ACP discussions and documentation within clinical environments.

Construct

The scale measures the underlying factors influencing a clinical nurse’s intention and willingness to engage in Advance Care Planning activities. The constructs are organized into two hierarchical factor models, reflecting different levels of behavioral influence:

The broader 3-factor model aligns closely with components of the Theory of Planned Behavior, assessing core behavioral determinants: Behavioral attitudes, Subjective norms, and Perceived behavioral control. The more granular 6-factor model breaks these determinants down into specific components: Behavioral belief, Result evaluation, Normative belief, Compliance motivation, Control belief, and Perceived intensity. These factors collectively capture the complex psychological landscape governing nurses’ clinical practice preferences related to end-of-life care planning.

Validity

The scale demonstrates strong evidence across multiple facets of validity testing, ensuring that it accurately measures the intended constructs.

Regarding Content validity, the scale was rigorously developed using a 100% expert response rate during the Delphi expert consultation phase. The statistical indices confirmed high relevance and coverage, with the Item-Content Validity Index (I-CVI) ranging from 0.857 to 1.000, and the overall Scale-Content Validity Index (S-CVI) achieving 0.958.

Construct validity was supported by robust factor analysis results, confirming that the internal structure of the scale aligns with the proposed theoretical models (both 6-factor and 3-factor). Furthermore, Convergent and Discriminant validity were established by examining the Average Variance Extracted (AVE) and Composite Reliability (CR) values in both the first-order and second-order factor models. In all cases, the square root of AVE consistently exceeded the correlation coefficients between corresponding factors, providing strong statistical evidence for both convergent and discriminant validation.

Reliability

The scale exhibits robust reliability across various measurement methods, confirming its consistency and stability.

For Internal consistency, the Cronbach’s α coefficients indicated excellent reliability across both structural models. In the Six-factor model, coefficients ranged from 0.703 to 0.904. In the Three-factor model, coefficients ranged from 0.765 to 0.863, all demonstrating sufficient to good internal consistency.

Split-half reliability coefficients were also satisfactory, ranging from 0.624 to 0.903 for the six-factor model and 0.653 to 0.680 for the three-factor model. Test–retest reliability, assessed over a 2-week interval, confirmed temporal stability, with coefficients ranging from 0.771 to 0.910 for the six-factor model and 0.769 to 0.962 for the three-factor model.

Factor Analysis

The development utilized both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) to optimize the scale structure. The process began with an initial pool of 78 items, which was reduced to a final, parsimonious set of 24 items following detailed item analysis.

The Exploratory Factor Analysis (EFA) indicated strong explanatory power for the derived structures. The first-order factor model accounted for 77.933% of the total variance, while the second-order factor model explained 57.305% of the total variance. The Confirmatory Factor Analysis (CFA) results confirmed the structural validity of the final model. The Second-order factor model demonstrated a particularly good model fit, with key indices reported as: χ²/df = 1.492, GFI = 0.920, AGFI = 0.902, RMSEA = 0.038, TLI = 0.950, and CFI = 0.956.

Instrument

Test Type: Original inventory/questionnaire

Format: Items are rated using a Likert five-point scoring system.

Language Available: Chinese

Population Group: Human (Male and Female)

Age Group: Adulthood (18 years & older), Young Adulthood (18-29 years), Thirties (30-39 years)

Population Details: The study sample consisted exclusively of clinical nurses in China.

Test Methodology: The validation process included comprehensive assessment of Test Validity (Construct Validity, Content Validity, Convergent Validity, Discriminant Validity), Test Reliability (Internal Consistency, Split-Half Reliability, Test-Retest Reliability), and rigorous Factor Analysis (Confirmatory Factor Analysis, Exploratory Factor Analysis).

Keywords

Advance Care Planning Practice Preferences, Behavioral Attitudes, Behavioral Belief, Clinical Nurses, Clinical Nursing, Compliance Motivation, Control Belief, Normative Belief, Perceived Behavioral Control, Perceived Intensity, Result Evaluation, Subjective Norms, Clinical Practice, Health Personnel Attitudes, Hospice, Nurses, Nursing, Preferences, Treatment Planning, Health Care Personnel Measures.

Authors

Author ORCID Identifier: Yang, Zhen – 0000-0002-6197-6168

Affiliation Email addresses: [email protected]

Correspondence Address: Wang, Aiping: First Affiliated Hospital of China Medical University, Department of Public Service, No.155, Nanjing North Street, Heping District, Liaoning Province, Shenyang, China, [email protected]

Permissions & Fee and Test Year

Permissions: Contact Corresponding Author

Commercial: No

Fee: No

Test Year: 2023

Reference’s

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

Items of the Advance Care Planning Practice Preference Scale

• Number of items: This is a 24-item measure.

• Test Items Available: No data is Available.

• Factors and Subscales:

  • Six-factor model: Behavioral belief, Result evaluation, Normative belief, Compliance motivation, Control belief, Perceived intensity.

  • Three-factor model: Behavioral attitudes, Subjective norms, Perceived behavioral control.