The Advance Care Planning Practice Preference Scale<\/strong> (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<\/a>; ACP) practice preferences among clinical nurses. Grounded conceptually in Icek Ajzen\u2019s Theory of Planned Behavior<\/a> (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<\/a>, condensing an initial pool of 78 items down to 24 final items. Responses are scored using a five-point Likert scale<\/a>.<\/p>\n 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<\/span>.<\/p>\n 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<\/p>\n 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:<\/p>\n 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<\/a>). 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.<\/p>\n 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.<\/p>\n 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:<\/p>\n The psychological construct measured by the ACPPPS is Advance Care Planning Practice Preference<\/em>, 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.<\/p>\n In accordance with cognitive behavioral modeling, the six primary factors converge into three overarching latent domains:<\/p>\n The conceptual foundation of the Advance Care Planning Practice Preference Scale is built upon the Theory of Planned Behavior<\/a>, formulated by social psychologist Icek Ajzen<\/a> (1991) as an extension of the Theory of Reasoned Action<\/a> (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).<\/p>\n In their aggregate, behavioral beliefs produce a favorable or unfavorable attitude toward the behavior<\/em>; normative beliefs result in perceived social pressure or subjective norm<\/em>; and control beliefs give rise to perceived behavioral control<\/em>. 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.<\/p>\n 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:<\/p>\n 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.<\/p>\n The Advance Care Planning Practice Preference Scale was subjected to rigorous psychometric validation protocols encompassing content validity, construct validity, convergent validity, and discriminant validity.<\/p>\n 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.<\/p>\n 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.<\/p>\n Convergent validity was evaluated using Composite Reliability (CR) and Average Variance Extracted (AVE<\/a>) metrics, while discriminant validity was established using the Fornell–Larcker criterion<\/a>:<\/p>\n Reliability of the ACPPPS was evaluated across three distinct psychometric dimensions: internal consistency, split-half reliability, and temporal stability (test–retest reliability).<\/p>\n Internal consistency was assessed using Cronbach’s alpha<\/a> (α) coefficients across both structural conceptualizations:<\/p>\n Split-half coefficients were computed by dividing scale items into odd and even halves:<\/p>\n To determine temporal stability, a randomly selected subsample of clinical nurses completed the instrument again following a two-week interval under matching clinical conditions:<\/p>\n 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.<\/p>\n The structural framework of the ACPPPS was determined through sequential exploratory and confirmatory factor analytic procedures conducted on separate validation cohorts.<\/p>\n 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:<\/p>\n Confirmatory factor analysis using maximum likelihood estimation evaluated the fit of both configurations on independent cross-validation samples:<\/p>\n The Advance Care Planning Practice Preference Scale is structured as an objective, self-administered survey tool. Its operational specifications are summarized below:<\/p>\n The Advance Care Planning Practice Preference Scale was developed and published in 2023<\/strong>. Essential administrative and licensing details include:<\/p>\n The official, complete 24 items of the Advance Care Planning Practice Preference Scale (ACPPPS) are proprietary and protected under academic copyright by the original authors and the publishing journal. Consequently, the verbatim questionnaire statements are not reproduced in the open public domain.<\/p>\n Items are rated using a Likert five-point scoring system.<\/p>\n The 24 items are organized across the following operational subscales, which can be interpreted within either a 6-factor first-order framework or a 3-factor second-order framework:<\/p>\n Researchers, healthcare organizations, and clinicians seeking access to the complete, authenticated 24-item questionnaire, scoring keys, and administrative guidelines should contact the corresponding author, Prof. Aiping Wang (Department of Public Service, First Affiliated Hospital of China Medical University; Email: jianghaoran88@hotmail.com<\/em>) or access the publication through the Journal of Advanced Nursing<\/em> (Yang, Wang, & Wang, 2023).<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":" The Advance Care Planning Practice Preference Scale (ACPPPS), developed by Yang, Wang, and Wang (2023), is a 24-item psychometric instrument evaluating clinical nurses’ advance care planning practice preferences grounded in the Theory of Planned Behavior.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","categories":[19657,24600,30],"tags":[24601,24602,5563,24603,2011,6,208],"class_list":["post-8234","psych_scale","type-psych_scale","status-publish","hentry","category-nursing-assessment-tools","category-palliative-end-of-life-measures","category-psychological-scales","tag-advance-care-planning","tag-clinical-nurses","tag-end-of-life-care","tag-nursing-preferences","tag-palliative-care","tag-psychometrics","tag-theory-of-planned-behavior"],"_links":{"self":[{"href":"https:\/\/ashadocs.org\/index.php?rest_route=\/wp\/v2\/psych_scale\/8234","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ashadocs.org\/index.php?rest_route=\/wp\/v2\/psych_scale"}],"about":[{"href":"https:\/\/ashadocs.org\/index.php?rest_route=\/wp\/v2\/types\/psych_scale"}],"author":[{"embeddable":true,"href":"https:\/\/ashadocs.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ashadocs.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=8234"}],"version-history":[{"count":0,"href":"https:\/\/ashadocs.org\/index.php?rest_route=\/wp\/v2\/psych_scale\/8234\/revisions"}],"wp:attachment":[{"href":"https:\/\/ashadocs.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8234"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ashadocs.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8234"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ashadocs.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8234"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}2. Keywords<\/h2>\n
3. Authors<\/h2>\n
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4. Purpose<\/h2>\n
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5. Psychological Construct<\/h2>\n
The Six First-Order Dimensions<\/h3>\n
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The Three Higher-Order Latent Constructs<\/h3>\n
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6. Theoretical Framework<\/h2>\n
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7. Validity<\/h2>\n
Content Validity<\/h3>\n
Construct Validity<\/h3>\n
Convergent and Discriminant Validity<\/h3>\n
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8. Reliability<\/h2>\n
Internal Consistency<\/h3>\n
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Split-Half Reliability<\/h3>\n
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Test–Retest Reliability<\/h3>\n
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9. Factor Analysis<\/h2>\n
Exploratory Factor Analysis (EFA)<\/h3>\n
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Confirmatory Factor Analysis (CFA)<\/h3>\n
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10. Instrument \/ Measurement Tool<\/h2>\n
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11. Permissions & Fee and Test Year<\/h2>\n
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12. References<\/h2>\n
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13. Items of the Scale<\/h2>\n
Response Format<\/h3>\n
Subscale Architecture and Operational Breakdown<\/h3>\n
First-Order Six-Factor Model:<\/h4>\n
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Second-Order Three-Factor Model:<\/h4>\n
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Acquiring the Official Instrument<\/h3>\n