Preamble

Systematic Evaluation of the Quality of Cardiovascular Shared Decision-Making Aids Based on IPDAS 4.0 Standards

Authors: Zhang Xiaoxin, Lin Jiayi, Zhang Xiangyi, Kang Xiaofeng
Affiliation: School of Nursing, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100144, China

Abstract

Objective: To systematically evaluate the quality of shared decision-making (SDM) aids for cardiovascular diseases using the International Patient Decision Aid Standards (IPDAS) 4.0, providing a reference for the development and clinical application of high-quality decision aids in China.

Methods: A systematic search was conducted across databases including PubMed, Embase, The Cochrane Library, Web of Science, CINAHL, CNKI, Wanfang Data, and VIP. The search period ranged from the inception of each database to June 2023. Two researchers independently screened the literature, extracted data, and assessed the quality of the included decision aids using the IPDAS 4.0 checklist.

Results: A total of 15 decision aids were included, covering topics such as atrial fibrillation anticoagulation, coronary heart disease treatment, and hypertension management. According to the IPDAS 4.0 criteria, the overall quality of the decision aids was moderate. While most tools performed well in "providing information" and "clarifying values," there were significant deficiencies in "disclosing conflicts of interest," "using plain language," and "providing evidence-based updates."

Conclusion: Current cardiovascular decision aids meet basic quality requirements but require improvement in transparency, accessibility, and evidence timeliness. Future development should strictly adhere to international standards to enhance the effectiveness of clinician-patient shared decision-making.

Introduction

Shared Decision-Making (SDM) is a collaborative process where clinicians and patients work together to make healthcare decisions based on clinical evidence and the patient's preferences and values. In the field of cardiovascular disease, where treatment options are often complex and involve significant trade-offs (e.g., the risk of stroke versus the risk of bleeding in anticoagulation therapy), SDM is particularly crucial.

Patient Decision Aids (PDAs) are evidence-based tools designed to facilitate this process by providing information about options and helping patients clarify what matters most to them. To ensure the effectiveness and safety of these tools, the International Patient Decision Aid Standards (IPDAS) Collaboration developed the IPDAS 4.0 criteria. This study aims to evaluate the quality and efficacy of these tools.

Background

Systematic Review of Patient Decision Aids in Cardiovascular Disease Based on IPDAS 4.0 Criteria

Pei Zhiyi, Zhang Xiaoxin, Lin Jiayi, Zhang Xiangyi, Kang Xiaofeng
School of Nursing, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100144, China
Correspondence: Kang Xiaofeng, Professor

Abstract

Cardiovascular disease (CVD) poses a significant threat to public health, and the effectiveness of its prevention and treatment relies heavily on scientifically sound medical decision-making. With the evolution of the Shared Decision-Making (SDM) model, Patient Decision Aids (PDAs) have emerged as essential tools for facilitating doctor-patient communication and enhancing patient engagement. However, the development quality of PDAs in the cardiovascular field remains inconsistent and lacks unified standards. The International Patient Decision Aid Standards (IPDAS 4.0) provide an evidence-based framework for the content design and outcome evaluation of PDAs. This study systematically evaluates PDAs in the cardiovascular field based on the IPDAS 4.0 criteria to provide a reference for clinical practice.

Objective: To evaluate the application effects of PDAs in SDM for patients with CVD.

Methods: We systematically searched PubMed, Embase, Web of Science, Cochrane Library, CNKI, VIP, CBM, and Wanfang Data for randomized controlled trials (RCTs) regarding the application effects of PDAs in CVD patients. The search period ranged from database inception to October 31, 2023. Two researchers independently screened the literature, extracted data, and evaluated the quality of the included studies. The experimental group received PDA interventions in any format, while the control group received routine care or treatment. The development quality of the PDAs was assessed using IPDAS 4.0, and meta-analysis was performed using RevMan 5.4 software.

Results: A total of 16 studies involving 4,861 patients were included. IPDAS 4.0 evaluation results showed that the top three scoring domains were "Conflict of Interest Disclosure," "Health Problems and Options Information," and "Information Related to Patient Values." The three lowest-scoring domains were "Screening/Testing," "Plain Language," and "Evaluation." Meta-analysis indicated that, compared to the control group, the experimental group significantly improved patients' knowledge levels [SMD = 0.88, 95% CI (0.52, 1.24), $P < 0.001$] and reduced decisional conflict [SMD = -0.21, 95% CI (-0.40, -0.03), $P < 0.001$]. Specifically, improvements were observed in being informed [MD = -0.36, 95% CI (-0.48, -0.25), $P < 0.001$], values clarification [MD = -0.24, 95% CI (-0.35, -0.13), $P < 0.001$], support [MD = -0.19, 95% CI (-0.31, -0.08), $P < 0.001$], and effective decision-making [MD = -0.20, 95% CI (-0.31, -0.08), $P < 0.001$].

Conclusion: PDA interventions are effective in reducing decisional conflict and improving decision satisfaction and knowledge levels. However, their role in reducing decisional regret requires further investigation. Future research should focus on developing high-quality PDAs tailored to the cardiovascular field based on IPDAS 4.0 standards, while considering the current medical landscape in China, to facilitate the implementation of SDM in clinical practice.

Keywords: Cardiovascular disease; Shared decision-making; International Patient Decision Aid Standards (IPDAS); Decisional conflict; Meta-analysis

Introduction

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality worldwide. Effective management of CVD requires complex decisions regarding lifestyle modifications, pharmacological interventions, and surgical procedures. Shared Decision-Making (SDM) has become a gold standard in patient-centered care, emphasizing a collaborative process where clinicians and patients reach a consensus based on clinical evidence and patient preferences.

Patient Decision Aids (PDAs) are evidence-based tools designed to help patients participate in these complex medical decisions. They provide information about options, potential benefits, and risks, helping patients clarify their personal values. While the use of PDAs is increasing, the lack of standardized development processes often leads to variations in quality. The International Patient Decision Aid Standards (IPDAS) Collaboration established the IPDAS 4.0 criteria to ensure that these tools are developed rigorously and evaluated effectively.

This study aims to systematically review the existing literature on PDAs within the cardiovascular domain, assessing their quality through the IPDAS 4.0 lens and quantifying their impact on patient outcomes through meta-analysis.

Methods

Literature Search Strategy

A comprehensive search was conducted across multiple international and Chinese databases, including PubMed, Embase, Web of Science, Cochrane Library, CNKI, VIP, CBM, and Wanfang Data. The search strategy utilized a combination of keywords such as "cardiovascular disease," "shared decision-making," "patient decision aids," and "randomized controlled trials." The search encompassed all relevant studies published from the inception of each database until October 31, 2023.

Inclusion and Exclusion Criteria

Studies were included if they:
1. Were randomized controlled trials (RCTs).
2. Focused on patients diagnosed with cardiovascular diseases.
3. Evaluated the use of a PDA compared to standard care or routine education.
4. Reported outcomes such as knowledge scores, decisional conflict, or decision satisfaction.

Studies were excluded if they were protocols, conference abstracts without full data, or if the full text was unavailable.

Data Extraction and Quality Assessment

Two researchers independently performed literature screening and data extraction. Discrepancies were resolved through discussion or consultation with a third expert. The quality of the included RCTs was assessed using the Cochrane Risk of Bias tool. The development quality of the PDAs themselves was evaluated using the IPDAS 4.0 checklist, which covers domains such as content, development process, and effectiveness.

Statistical Analysis

Meta-analysis was conducted using RevMan 5.4. For continuous variables, standardized mean differences (SMD) or mean differences (MD) with 95% confidence intervals (CI) were calculated. Heterogeneity was assessed using the $\chi^2$ test and $I^2$ statistic. A fixed-effects model was used if $I^2 \leq 50\%$; otherwise, a random-effects model was applied.

Results

Study Characteristics

The final analysis included 16 RCTs comprising a total of 4,861 patients. These studies covered various CVD contexts, including atrial fibrillation, coronary heart disease, and hypertension management.

IPDAS 4.0 Quality Evaluation

The evaluation using IPDAS 4.0 revealed that most PDAs performed well in disclosing conflicts of interest and providing clear information on health options. However, significant gaps were identified in the use of plain language and the rigorous evaluation of the tools' impact on the decision-making process.

Meta-Analysis of Outcomes

1. Knowledge Level: The use of PDAs significantly increased patients' knowledge regarding their condition and treatment options [SMD = 0.88, 95% CI (0.52, 1.24), $P < 0.001$].
2. Decisional Conflict: Patients using PDAs reported lower levels of decisional conflict [SMD = -0.21, 95% CI (-0.40, -0.03), $P < 0.001$]. Sub-group analysis showed improvements across several dimensions:
3. Informed sub-score: [MD = -0.36, 95% CI (-0.48, -0.25), $P < 0.001$]
4. Values clarification: [MD = -0.24, 95% CI (-0.35, -0.13), $P < 0.001$]
5. Support: [MD = -0.19, 95% CI (-0.31, -0.08), $P < 0.001$]
6. Effective decision-making: [MD = -0.20, 95% CI (-0.31, -0.08), $P < 0.001$]

Discussion

The findings suggest that PDAs are highly effective in the cardiovascular field for improving patient knowledge and reducing the uncertainty associated with medical choices. By aligning treatment paths with patient values, PDAs facilitate a more robust SDM process. However, the IPDAS 4.0 evaluation highlights a need for better design in terms of accessibility (plain language) and more rigorous testing of the tools before clinical rollout.

In the context of the Chinese healthcare system, where patient volume is high and consultation time is often limited, the development of concise, high-quality PDAs is crucial. Future efforts should focus on integrating these tools into electronic health records and ensuring they are culturally and linguistically appropriate.

Background

Cardiovascular disease (CVD) is a major threat to human health, and its prevention and treatment largely depend on evidence-based and rational medical decision-making. With the development of the shared decision-making (SDM) model, patient decision aids (PDAs) have increasingly been used to facilitate clinician-patient communication and enhance patient engagement in decision-making. However, the quality of cardiovascular PDAs varies considerably and lacks standardized regulation. The International Patient Decision Aid Standards (IPDAS 4.0) provide an evidence-based framework for the design and evaluation of PDAs. This study systematically evaluated PDAs in the cardiovascular field using the IPDAS 4.0 framework to provide evidence for clinical practice.

Objective: To evaluate the effectiveness of PDAs in SDM among CVD patients.

Methods: A systematic search was conducted in PubMed, Embase, Web of Science, Cochrane Library, CNKI, VIP, CBM, and Wanfang Data, covering publications up to October 31, 2023. Randomized controlled trials (RCTs) evaluating the effects of PDAs in patients with CVD were included. Two researchers independently screened the studies, extracted data, and assessed methodological quality. Intervention groups received PDAs in any format, while control groups received routine treatment or care. The quality of PDAs development was assessed using IPDAS 4.0, and meta-analysis was performed with RevMan 5.4.

Results

A total of 16 RCTs involving 4,861 patients were included. According to IPDAS 4.0, the top three scoring domains were disclosure, information, and values, while the lowest three were test, plain language, and decision support technology evaluation. Meta-analysis indicated that PDAs significantly improved patients' knowledge [SMD = 0.88, 95% CI (0.52, 1.24), $P < 0.001$] and reduced decisional conflict [SMD = -0.21, 95% CI (-0.40, -0.03), $P < 0.001$]. Reductions in decisional conflict were observed across the informed [MD = -0.36, 95% CI (-0.48, -0.25), $P < 0.001$], values clarity [MD = -0.24, 95% CI (-0.35, -0.13), $P < 0.001$], support [MD = -0.19, 95% CI (-0.31, -0.08), $P < 0.001$], and effective decision [MD = -0.20, 95% CI (-0.31, -0.08), $P < 0.001$] subscales.

Conclusion

PDA interventions are effective in improving knowledge and decisional satisfaction and reducing decisional conflict among CVD patients, though their impact on decision regret requires further investigation. Future studies should integrate China's healthcare context to develop PDAs tailored to CVD patients based on the IPDAS 4.0 framework, thereby promoting the implementation of SDM in clinical practice.

Keywords: Cardiovascular diseases; Decision making, shared; International Patient Decision Aid Standards; Decisional conflict; Meta-analysis

Cardiovascular disease (CVD) is the leading cause of death globally and ranks first among causes of mortality for both urban and rural residents in China, with its incidence and mortality rates continuing to increase annually. Clinical decision-making for CVD often involves multiple options where the benefits and risks of alternatives are closely balanced \cite{3-4}. Consequently, patients frequently struggle to make timely decisions that align with their personal values and preferences. Currently, medical decision-making models are shifting from paternalistic and informed decision-making toward shared decision-making (SDM).

Shared decision-making facilitates bilateral knowledge and information transfer through collaboration and communication between healthcare providers and patients, often utilizing Patient Decision Aids (PDAs) to reach a consensus on diagnosis and treatment. PDAs are evidence-based tools that provide information regarding the risks and benefits of various treatment options. They are designed to help patients reflect on and clarify their own values and preferences, enabling them to participate in the decision-making process, make informed choices, and reduce decisional conflict.

In recent years, the number and variety of PDAs in the cardiovascular field have grown significantly, leading to their widespread clinical application. However, the quality of their development has not yet received sufficient attention from researchers. The International Patient Decision Aid Standards (IPDAS) serve as an evidence-based framework for regulating the content, development, implementation, and evaluation of PDAs. First published in 2003 and updated to version 4.0 in 2014, these standards were constructed using the Delphi method by 122 experts from 14 countries. Therefore, this study evaluates the development quality of PDAs in the CVD field based on IPDAS 4.0 and performs a meta-analysis of their application effects. The objective is to provide an evidence-based foundation for clinical healthcare professionals to improve informed patient decision-making.

1.1 Search Strategy

Methods

Literature Search Strategy

A comprehensive computer-based search was conducted across several electronic databases, including PubMed, Embase, Web of Science, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, Wanfang Data Knowledge Service Platform, and the China Biology Medicine (CBM) database. The search period spanned from the inception of each database to October 31, 2023.

The search strategy employed a combination of Medical Subject Headings (MeSH) and free-text terms. Chinese search terms included "共同决策" (shared decision-making), "共享决策" (shared decision-making), "决策辅助工具" (decision aids), "决策支持" (decision support), "心脏病" (heart disease), "心血管疾病" (cardiovascular disease), "冠心病" (coronary heart disease), "心力衰竭" (heart failure), "心房颤动" (atrial fibrillation), "心脏瓣膜病" (valvular heart disease), "心肌梗死" (myocardial infarction), "心律失常" (arrhythmia), and "心功能不全" (cardiac insufficiency).

The English search strategy, using PubMed as an example, is detailed in Table 1 [TABLE:1]. The specific search strings utilized were as follows:

1. ("decision making"[MeSH] OR "decision making, shared"[MeSH] OR "shared decision-making"[Ti/Ab] OR "decision making"[Ti/Ab] OR "decision aid"[Ti/Ab] OR "decision tool"[Ti/Ab] OR "decision support"[Ti/Ab] OR "informed decision"[Ti/Ab] OR "informed choice"[Ti/Ab])
2. ("myocard"[Ti/Ab] OR "arrhythm"[Ti/Ab] OR "valv"[Ti/Ab] OR "fibrill"[Ti/Ab] OR "tachycard"[Ti/Ab] OR "bradycard"[Ti/Ab] OR "Heart"[Ti/Ab] OR "angin"[Ti/Ab] OR "coronar"[Ti/Ab] OR "ischaemi"[Ti/Ab] OR "ischemi"[Ti/Ab] OR "card"[Ti/Ab] OR "aort"[Ti/Ab] OR "mitral"[Ti/Ab] OR "vascular"[Ti/Ab] OR "infarct"[Ti/Ab] OR "conduction"[Ti/Ab] OR "channelopathy"[Ti/Ab] OR "diastolic dysfunction"[Ti/Ab] OR "systolic dysfunction"[Ti/Ab] OR "atri"[Ti/Ab] OR "ventric"[Ti/Ab] OR "palpitatio"[Ti/Ab] OR "arter"[Ti/Ab] OR "hypertensi"[Ti/Ab] OR "cardiac pac"[Ti/Ab] OR "pacemaker"[Ti/Ab] OR "endocarditis"[Ti/Ab] OR "electrocardiogra"[Ti/Ab] OR "electrophysiolog*"[Ti/Ab])

3. 1 AND #2 AND (randomized controlled trial[Filter])

1.2 Inclusion Criteria

1.2.1 Study Type: Randomized Controlled Trial (RCT).

1.2.2 Research Subjects:

Adult patients with CVD (coronary heart disease, heart failure, arrhythmias, or other conditions requiring medical decision-making).

1.2.3 Interventions:

The experimental group received Patient Decision Aids (PDAs) in any format; the control group received routine treatment or standard care.

1.2.4 Outcome Indicators:

Decisional conflict, decisional regret, decision satisfaction, and knowledge level.

1.3 Exclusion Criteria:

(1) For duplicate publications, only the most comprehensive version was included; (2) reviews and conference abstracts were excluded; (3) studies with unavailable full texts or missing data were excluded; (4) studies with a quality assessment grade of C were excluded; and (5) studies that failed to meet the IPDAS 4.0 eligibility criteria were excluded.

Literature Screening and Data Extraction
Two researchers independently screened the literature, extracted data, and cross-checked the results according to the inclusion and exclusion criteria. Any significant disagreements were resolved through discussion with a third researcher. The extracted data included the authors, publication year, country, sample size, mean age or age range, decision-making problem, type and content of Patient Decision Aids (PDAs), intervention measures, and outcome indicators.

Risk of Bias Assessment
The risk of bias was evaluated using the Randomized Controlled Trial (RCT) criteria from the Cochrane Handbook for Systematic Reviews of Interventions (Version 5.1). The assessment included: random sequence generation, allocation concealment, blinding, completeness of outcome data, selective reporting of results, and other sources of bias. Studies meeting all criteria were graded as A; those partially meeting the criteria were graded as B; and those failing to meet the criteria were graded as C and excluded. Given that clinical trials involving shared decision-making often make it difficult to blind participants and interventionists, studies that did not implement double-blinding but satisfied all other criteria were still considered for inclusion.

Quality Evaluation of PDAs
The IPDAS 4.0 criteria consist of 44 items categorized into three types: (1) Eligibility criteria: 6 items defining the nature of PDAs, all of which must be met; (2) Certification criteria: 10 items designed to avoid the risk of harmful bias to patients; and (3) Quality criteria: 28 non-essential criteria for high-quality aids. The final 4 certification criteria and the final 5 quality criteria are specifically designed for screening or diagnostic test PDAs. All criteria are summarized into 10 themes: information on health issues and options, probabilities, patient values, decision guidance, development process, evidence, disclosure of conflicts of interest, plain language, decision support technology evaluation, and tests. Each criterion is scored on a scale of 1 to 4 (1 = strongly disagree, 4 = strongly agree), with a score of $\ge 3$ considered as meeting the standard. The maximum total score across all criteria is 176.

Statistical Methods
Meta-analysis was performed using RevMan 5.4 software. The outcome indicators included in this study were all continuous variables. When the measurement methods and units for the same indicator were identical across studies, the Weighted Mean Difference (WMD) was used; if they were not identical, the Standardized Mean Difference (SMD) was employed. Heterogeneity was assessed using the $\chi^2$ test and $I^2$ statistic.

2. Results

2.1 Heterogeneity Analysis

If $P \ge 0.1$ and $I^2 \leq 50\%$, it indicates that there is homogeneity among the studies, and a fixed-effects model should be selected for the analysis. Conversely, if $P < 0.1$ or $I^2 > 50\%$, it suggests significant heterogeneity among the studies, in which case a random-effects model should be employed.

The presence of heterogeneity among the included studies necessitates the use of a random-effects model for the meta-analysis. To further explore the sources of this heterogeneity and ensure the robustness of the findings, sensitivity analyses, subgroup analyses, or descriptive analyses were performed.

2.2 Assessment of Heterogeneity

Heterogeneity refers to the variation in study outcomes between different investigations. In this study, we assess statistical heterogeneity using the $Q$ test and the $I^2$ statistic. A $P$-value $< 0.10$ for the $Q$ test or an $I^2$ value $> 50\%$ indicates significant heterogeneity. When such heterogeneity is present, it suggests that the observed differences in effect sizes are not due to sampling error alone but may stem from clinical or methodological differences across studies.

2.3 Selection of the Random-Effects Model

While a fixed-effect model assumes that all studies share a single true effect size, the random-effects model accounts for both within-study and between-study variance. Given the anticipated diversity in study populations, intervention protocols, and measurement techniques, we employ the random-effects model (typically using the DerSimonian-Laird method) to provide a more conservative estimate of the pooled effect size. This approach ensures that the results are more generalizable to a broader clinical context.

2.4 Subgroup Analysis

To identify specific factors contributing to the observed heterogeneity, subgroup analyses are conducted based on pre-defined covariates. These may include:
- Participant Characteristics: Such as age, gender, or baseline disease severity.
- Intervention Parameters: Such as dosage, duration, or specific types of treatment.
- Study Design: Comparing randomized controlled trials (RCTs) against observational studies or evaluating studies with different follow-up periods.

By comparing effect sizes across these strata, we can determine if the treatment effect remains consistent or varies significantly depending on specific study characteristics.

2.5 Sensitivity Analysis

Sensitivity analysis is performed to evaluate the stability and reliability of the meta-analysis results. This is typically achieved through the "leave-one-out" method, where the pooled effect size is re-calculated after iteratively removing one study at a time. If the overall conclusion remains unchanged regardless of which study is excluded, the results are considered robust. Additionally, sensitivity analyses may involve excluding studies with a high risk of bias or those that are identified as statistical outliers.

2.6 Descriptive Analysis

In cases where meta-analysis is not feasible due to extreme heterogeneity or insufficient data, a descriptive analysis is provided. A $P$-value $< 0.05$ is considered statistically significant.

2.1 Literature Search Results

A total of 7,556 documents were initially retrieved. After removing 2,996 duplicates using EndNote, the titles and abstracts were screened, resulting in the exclusion of 4,493 irrelevant papers. Of the remaining 67 articles, the full texts were reviewed, and 16 English-language studies were ultimately included. The literature screening process is illustrated in Figure 1 [FIGURE:1].

The basic characteristics and methodological quality evaluations of the included studies \cite{11-26} involved a total of 4,861 patients, with 2,416 in the experimental groups and 2,445 in the control groups. Among the 16 included Patient Decision Aids (PDAs) studies \cite{14, 16, 20-26}, 10 described the methods for random sequence generation and implemented allocation concealment. Two studies \cite{14, 20} implemented blinding for participants and personnel, while three studies \cite{22, 25} blinded the outcome assessors. Fourteen studies \cite{11-13, 15-17, 19-26} were identified as having a low risk of selective reporting, and eight studies \cite{11-13, 16, 20, 22-23, 25} utilized intention-to-treat analysis. The overall quality of the literature was high, with three studies \cite{21-22, 25} rated as Grade A and the remainder as Grade B. PDAs in the field of cardiovascular disease (CVD) are primarily applied to treatment decisions regarding coronary artery disease, anticoagulation for atrial fibrillation, and cardiac device implantation. Content typically includes disease knowledge, the pros and cons of different treatment options, personal risk probability assessments, and patient experiences. The basic characteristics and methodological quality evaluation results of the included literature are presented in Table 2 [TABLE:2].

Regarding the quality evaluation of the PDAs, all met the eligibility criteria, though they scored lower in terms of certification and quality standards. The total score based on the IPDAS 4.0 criteria is 176 points; the included PDAs had an average score of 120.1, with a range of 103 to 135 points. The three highest-scoring themes were: (7) declaration of conflicts of interest, (1) information regarding health issues and options, and (3) clarification of patient values. The search across English and Chinese databases (n = 7,556) included: PubMed (n = 1,106), Embase (n = 2,029), Web of Science (n = 2,576), Cochrane Library (n = 1,408), CNKI (n = 62), WanFang Data (n = 189), and CBM (n = 138).

Full-text review for re-screening (n = 67)

Excluded literature (n = 51): Unable to obtain full text (n = 1), conference abstracts (n = 12), secondary analyses (n = 2), and inconsistent research design (n = 36).

Included literature (n = 16)

Flow chart of literature screening

Study Characteristics and Quality Assessment

The included studies provided comprehensive data regarding participant demographics and sample sizes across experimental and control groups. Specifically, the age of participants (expressed as years) and the sample size (number of cases in the experimental group versus the control group) were documented for the following researchers: Wang et al., Branda et al., Jaspers et al., Lewis et al., Schott et al., Kunneman et al., Doll et al., Case et al., Allen et al., Kostick et al., Carroll et al., Hess et al., Coylewright et al., Schwalm et al., McAlister et al., and Man-Son-Hing et al.

[TABLE:3]

The analysis of the Patient Decision Aids (PDAs) revealed specific thematic strengths and weaknesses based on their content and design. After ranking the scores, the three lowest-scoring themes were identified as: (10) testing and diagnostic categories, (8) use of plain or accessible language, and (9) evaluation components. The detailed results of the quality assessment for the included PDAs are presented in Table 3.

2.4 Meta-Analysis Results

2.4.1 Decisional Conflict

Fifteen PDAs \cite{11-17, 19-26} evaluated the impact on decisional conflict. Due to the presence of heterogeneity among the studies ($I^2 = 88\%$, $P < 0.001$), a random-effects model was employed for the meta-analysis. The results indicated that the experimental group experienced a significant reduction in decisional conflict among CVD patients compared to the control group (SMD = -0.21, 95% CI = -0.40 to -0.03, $P < 0.001$), and this difference was statistically significant, as shown in Figure 2 [FIGURE:2]. One study not included in the meta-analysis suggested that Patient Decision Aids (PDAs) can help patients make more informed choices, thereby reducing decisional conflict and promoting shared decision-making.

Eight studies \cite{14-15, 20-21, 23-26} utilized the Decisional Conflict Scale (DCS), which comprises five dimensions: informed, values clarity, support, effective decision, and uncertainty. No heterogeneity was observed between these studies; therefore, a fixed-effects model was employed for the meta-analysis. The results indicated that, compared to the control group, the experimental group significantly reduced decision conflict across four dimensions: informed choice (MD = -0.36, 95% CI: -0.48 to -0.25, $P < 0.001$), values clarification (MD = -0.24, 95% CI: -0.35 to -0.13, $P < 0.001$), support (MD = -0.19, 95% CI: -0.31 to -0.08, $P < 0.001$), and effective decision-making (MD = -0.20, 95% CI: -0.31 to -0.08, $P < 0.001$). These differences were statistically significant. Regarding the uncertainty dimension of decision conflict between the two groups (MD = -0.03, 95% CI: -0.14 to 0.08, $P = 0.62$), the difference was not statistically significant. See [FIGURE:3] through [FIGURE:7].

2.4.2 Decisional Regret and Decision Satisfaction

Three studies \cite{11, 19-20} evaluated decisional regret using the Decision Regret Scale (DRS). Significant heterogeneity was observed across the included studies ($I^2 = 99\%$, $P < 0.001$). A meta-analysis using a random-effects model indicated that there was no statistically significant difference between the two groups regarding the impact on decision regret among patients with cardiovascular disease (CVD) (MD = -0.83, 95% CI: -7.89 to 6.24, $P = 0.82$), as shown in [FIGURE:8].

Three studies \cite{20, 26} reported on the impact of Patient Decision Aids (PDAs) on decision satisfaction. The results demonstrated that PDAs significantly improved decision satisfaction among patients in the experimental group.

2.4.3 Informed Decision-Making

All 16 studies reported the impact of PDAs on patient knowledge. Ten studies \cite{11, 13-14, 17-20, 22-24} were included in the meta-analysis to evaluate the impact of the interventions. The primary outcomes assessed across these studies included: (1) Decisional Conflict Scale (DCS) scores; (2) Decision satisfaction, measured by the Decision-Making Process Questionnaire; and (3) Patient knowledge, assessed via self-administered knowledge questionnaires.

Note: ICD = implantable cardio-defibrillator; LVAD = left ventricular assist device; ACS = acute coronary syndrome; PCI = percutaneous coronary intervention; OMT = optimal medical therapy.

A meta-analysis was conducted using a random-effects model to evaluate the effect of Patient Decision Aids (PDAs) on various subscales of decisional conflict and patient knowledge in cardiovascular disease (CVD) patients ($I^2=95\%$, $P < 0.001$). The results demonstrated that the experimental group achieved significantly higher knowledge levels compared to the control group (SMD = 0.88, 95% CI [0.52, 1.24], $P < 0.001$), as shown in [FIGURE:9]. Several studies \cite{12, 15-16, 21, 25-26} were excluded from the meta-analysis due to high heterogeneity; however, these individual studies consistently showed that PDAs effectively improved patient knowledge levels and the accuracy of responses to disease-related questions, thereby helping patients better understand their clinical options.

Note: The evaluation criteria are categorized into A = Qualification Criteria (6 items), B = Certification Criteria (10 items), and C = Quality Criteria (28 items). These are further grouped into ten themes: ① Information on health problems and options (A1–A5, B1, C1, C2); ② Probability information (C3–C8); ③ Values-related information (A6, C9); ④ Decision guidance (C10, C11); ⑤ Development process (C12–C17); ⑥ Evidence references (B2–B5, C18, C19); ⑦ Conflict of interest disclosure (B6, C20); ⑧ Plain language (C21); ⑨ Evaluation (C22, C23); and ⑩ Screening/Testing specific criteria (B7–B10, C24–C28).

Regarding the outcome of decisional conflict, a funnel plot was utilized to test for publication bias. The funnel plot exhibited incomplete symmetry, suggesting the presence of a certain degree of publication bias among the included literature, as illustrated in [FIGURE:10]. To explore the sources of heterogeneity, a sensitivity analysis was performed by systematically excluding individual studies to assess their impact on the overall outcome. The results of the sensitivity analysis indicated that the findings for all outcome measures remained robust.

3. Discussion

3.1 Quality Evaluation of PDAs Based on IPDAS 4.0

The IPDAS 4.0 framework consists of 44 standards categorized into three groups: qualification, certification, and quality standards. These provide the fundamental specifications and scientific guidance for the development and application of Patient Decision Aids (PDAs). Regarding the qualification standards, all 16 tools included in this study met the criteria, listing the six required elements: health problem, decision problem, alternative options, benefits of options, risks, and patient experiences.

Within the certification standards, items B7–10 are specifically designed for screening-related PDAs. Only two screening tools in this study \cite{18, 22} were evaluated against these; however, they failed to report the following standards: the next decision-making steps based on presence or absence of a condition, and lead-time bias (where PDAs inform patients that screening can detect a health state but fail to clarify that such results may not prevent adverse outcomes). The remaining 14 tools \cite{11-17, 19-21, 23-26} were subject only to standards B1–6, which include: presenting the pros and cons of each option in an equivalent manner, providing evidence citations, specifying the development date, providing an update strategy, presenting risks and benefits as probabilities, and disclosing development funding. Notably, none of these tools addressed the PDA update strategy.

Regarding quality standards, items C24–28 involve the reporting of true positives, true negatives, false positives, false negatives, and diagnostic accuracy for screening tools; neither of the two screening tools in this study mentioned these metrics. Standards C1–23 further require PDAs to present probabilities through data, charts, and text; consider patient values and preferences; and use question prompts to guide physician-patient communication. Furthermore, the development process should include evaluations and field testing by both participating and non-participating patients and healthcare professionals, as well as details on evidence screening and integration methods, evidence quality, developer credentials, and readability levels. The 16 tools included in this study generally met 14 to 23 of these standards. The standards most frequently unmet included: guiding physician-patient communication with question lists, involving both participating and non-participating stakeholders in the evaluation, detailing evidence screening and integration methods, reporting evidence quality and readability levels, and providing evidence of "congruence between the informed patient’s values and their choices."

The development of PDAs is based on the philosophy of "patient-centered" design and serves as a vital pathway for promoting shared clinical decision-making. It is recommended that domestic scholars strictly adhere to IPDAS quality control standards during the development, application, and reporting of research related to these tools.

As IPDAS 4.0 lacks explicit scoring criteria—with each item typically rated on a scale of 1 to 4 (from "strongly disagree" to "strongly agree")—the subjective judgment of researchers may affect the objectivity of the results. Therefore, determining how to utilize the IPDAS framework scientifically remains a critical consideration. Further exploration and validation are still needed regarding the quality evaluation of PDAs based on IPDAS 4.0.

3.2 Improving Application Quality Based on the Four Characteristics of Informed Decision-Making

Decision conflict and decision regret are critical outcome indicators for measuring the quality of decision-making, both of which are closely related to the complexity of the decision-making problem at hand. When the actual outcome of a health decision differs significantly from the expected outcome, patients may experience decision conflict, decision delay, and decision regret. These experiences can adversely affect the patient's physical and mental health, as well as their overall quality of life, potentially leading to physician-patient disputes \cite{28, 30-31}. Decision conflict refers to the internal sense of uncertainty a patient feels regarding the treatment options to be selected during medical activities; it encompasses five dimensions: informed choice, values clarification, support, effective decision-making, and uncertainty. From the perspective of cognitive psychology, informed decision-making consists of two components: "informed" and "decision." Being "informed" involves understanding, cognition, and being told about the specific pros and cons of various options. This state of being informed is the prerequisite and foundation for forming concepts and emotions, serving as the precursor and preparation for human psychological and behavioral responses. Making a "decision" under scientific guidance after being "informed" is the process of forming a patient's attitude. Attitude formation is a complex psychological journey involving three stages: compliance, identification, and internalization. Compliance, also known as obedience, refers to an individual changing their views only superficially. Identification, or confirmation, occurs when an individual changes their attitude to maintain harmony with the external environment. Internalization is the highest and most stable stage of attitude formation, occurring when an individual deeply believes in and accepts the views of others, resulting in a thorough change in their own attitude.

Therefore, an informed decision-making process based on Patient Decision Aids (PDAs) should embody four key characteristics: (1) Intersectionality, meaning it must satisfy the cultural characteristics of specific populations; (2) Inclusive design, ensuring it is applicable and accessible to the majority of individuals; (3) Organizational health literacy, which refers to the ability of medical institutions to equitably assist patients in knowing, understanding, and implementing health-related medical decisions; and (4) Health numeracy, which involves providing empirical, evidence-based scientific data to help patients select personalized treatment plans based on their own needs and preferences.

Due to differences in patients' educational levels and their varying degrees of acceptance of PDAs, personalized PDAs should be provided to patients with different levels of health literacy. The media types for PDAs include paper manuals, audio tapes, videos, and web-based programs. Paper manuals offer unique advantages: they are concise, easy to understand, and low-cost, providing a clear and intuitive presentation of diagnostic and treatment options suitable for elderly patients. In contrast, web-based PDAs can integrate digital media such as text, images, and animation. These tools offer interactivity and personalization, characterized by their flexibility, convenience, and strong dissemination potential, making them suitable for patients with a certain level of information literacy. For instance, the digital shared decision-making toolkit used in the study by Wang et al. features patient feedback and knowledge assessment functions. Healthcare professionals should fully consider patients' physiological characteristics, psychological needs, and cognitive levels, developing different types of PDAs based on individual differences to help patients choose diagnostic and treatment methods that align with their values, preferences, and needs.

3.3 Research Bias and Limitations

The limitations of this study include: (1) Some studies did not provide access to the original PDAs or tool examples, which may have introduced bias when using the IPDAS 4.0 criteria for evaluation. Furthermore, the subjective judgment of the researchers may have affected the objectivity of the evaluation results. (2) There are differences among the included literature regarding geographic regions, socio-cultural backgrounds, educational and economic levels, and assessment tools, leading to a degree of heterogeneity between studies. (3) Due to the nature of PDA interventions, it is difficult to implement blinding for both interveners and participants. Only two studies \cite{14, 20} explicitly mentioned the use of blinding for subjects and interveners. Although other studies did not employ blinding, the impact on the analysis of objective outcome indicators was minimal. Additionally, sensitivity analyses were performed on the included outcome indicators in this study, and the Meta-analysis results remained stable. Therefore, the results of this study are reliable and provide a valuable reference.

4 Summary

Patient Decision Aids (PDAs) can enhance the knowledge of patients with cardiovascular disease (CVD) and reduce decisional conflict, thereby improving patient satisfaction. However, further research is required to demonstrate their effectiveness in reducing decisional regret. Healthcare professionals should fully consider factors such as patients' health literacy, economic capacity, and disease severity when developing personalized PDAs. Furthermore, domestic scholars should strictly adhere to the International Patient Decision Aid Standards (IPDAS) quality control criteria during the development, application, and reporting of research. Further exploration and validation are still needed regarding the scientific application of IPDAS 4.0 for evaluating the developmental quality of PDAs.

In the future, it is necessary to conduct more large-sample, multicenter, and high-quality studies to objectively and comprehensively evaluate the intervention effects of PDAs on the decision-making quality of CVD patients. Such studies will provide a more robust evidence-based foundation for the development of PDAs.

Author Contributions: Pei Zhiyi was responsible for the study conception and design, implementation of the research, and drafting of the manuscript; Zhang Xiaoxin and Lin Jiayi were responsible for data collection, organization, and the creation and presentation of figures and tables; Zhang Xiangyi was responsible for the feasibility analysis and revision of the manuscript; Kang Xiaofeng was responsible for quality control, review, overall supervision, and management of the article.

The authors declare no conflicts of interest.

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