BackgroundWhen oral antidiabetic drugs are insufficient to achieve glycemic control in Type 2 diabetes mellitus (T2DM), patients face the decision of whether to initiate insulin therapy. Patient decision aids (PtDAs) facilitate shared decision-making (SDM) by supporting informed, preference-congruent choices about insulin initiation. However, PtDA implementation in China remains challenging, with limited understanding of context-specific barriers.ObjectiveThis study is aimed at identifying the barriers and facilitators to implementing PtDAs for supporting informed decisions about insulin initiation in T2DM management in China, from the perspectives of key interest holders (patients, endocrinologists, nurses).MethodsA qualitative descriptive study was conducted using semistructured interviews guided by the Theoretical Domains Framework (TDF). A purposive sample of 26 participants (10 patients with T2DM, 6 physicians, and 10 nurses) was recruited from a university-affiliated hospital in Beijing. Interviews were audio-recorded, transcribed verbatim, and analyzed using a framework analysis approach assisted by NVivo.ResultsFifteen barriers and five facilitators were identified for healthcare professionals, whereas six barriers and five facilitators were identified for patients. Key barriers included a lack of knowledge about PtDAs and insufficient skills for their use among both groups. Notable barriers related to social/professional role and identity were found, with physicians often self-identifying as sole "decision-makers" and nurses expressing role ambiguity regarding SDM. The absence of reinforcement mechanisms and concerns about increased workload and limited resources were substantial organizational barriers. Facilitators included positive beliefs about PtDAs ' consequences and the readiness of nurses, whose established health education practices position them as potential champions for implementation. Patients demonstrated a positive intention to use PtDAs once their purpose was understood.ConclusionsThe implementation of a PtDA for informed decision-making about insulin initiation in T2DM patients in China is influenced by a complex array of factors. Moving beyond the common barrier of time constraints, this study highlights foundational gaps in knowledge, skills, and role alignment as primary hurdles. A multifaceted implementation strategy is essential, comprising comprehensive education and training, clear role delineation, adaptation of PtDAs to fit clinical workflows, and strong organizational commitment with integrated monitoring and support.

The CFIR-ERIC matching tool, developed by Waltz et al. in 2019 to integrate implementation strategies with theoretical frameworks, enables rapid and targeted generation of implementation strategies in healthcare. However, no comprehensive synthesis of its application exists. This scoping review addresses this gap to inform tool optimization and implementation science advancement. Following the Joanna Briggs Institute scoping review methodology and PRISMA-ScR guidelines, we searched eight databases (PubMed, Embase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed) for studies applying the CFIR-ERIC matching tool in healthcare (April 29, 2019, to February 8, 2025). Data on application purpose, process, advantages, and limitations were extracted and analyzed via descriptive and content analysis. A total of 53 studies were included. The tool was mainly used to efficiently formulate targeted implementation strategies (51/53, 96.23

BACKGROUND:Systematic reviews (SRs) and realist reviews (RRs) are increasingly conducted in a coordinated manner with intersecting methodological processes, forming what we term hybrid review designs. However, little is known about how these hybrid reviews are conducted and structured. OBJECTIVES:This study aimed to characterize existing hybrid reviews by examining their features, analyzing their method intersection strategies, and synthesizing the reported advantages and challenges, thereby informing future methodological guidance. METHODS:A scoping review following the Joanna Briggs Institute approach was conducted. We searched the following databases from January 2005 to May 2025: PubMed, Web of Science (Clarivate), Embase (Ovid), PsycINFO (Ovid), and CINAHL (EBSCOhost), supplemented by citation searches. Eligible studies were hybrid reviews that explicitly integrated SRs and RRs in a coordinated manner. Data on study characteristics and methodological features were analyzed descriptively, while intersection strategies and the reported advantages and challenges were synthesized using qualitative content analysis. RESULTS:Of 129 included studies, we classified hybrid review designs into 4 types based on methodological features: SR and RR in separation (SR|RR, 48 of 129, 37.2%); SR and RR in combination (SR + RR, 15 of 129, 11.6%); realist-informed SR (47 of 129, 36.4%); and multiphase hybrid review (19 of 129, 14.7%). Within the SR|RR and SR + RR types, 8 method intersection strategies were identified, with the most common being "using SR to inform the initial program theory development of RR" in SR|RR (27 of 48, 56.3%) and "sharing search strategies" in SR + RR (11 of 15, 73.3%). Reported advantages included stronger evidence, actionable insights, aiding complex intervention/theory development, and streamlined processes; challenges included philosophical/methodological tensions and labor intensity. CONCLUSION:This review provides a foundational map and classification of hybrid reviews. The findings illuminate how SR and RR methods are integrated in practice, establishing an evidence base to inform methodological guidance and supporting researchers in designing such reviews. PLAIN LANGUAGE SUMMARY:This study looked at how 2 types of research reviews-systematic reviews, which focus on whether interventions work, and realist reviews, which focus on how and why interventions work-can be conducted in a coordinated manner. We reviewed 129 published hybrid reviews and identified 4 types of integration, as well as 8 common method strategies for linking the 2 approaches. We also summarized the reported benefits and challenges of these hybrid reviews. Our findings show that hybrid reviews have the potential to provide a more comprehensive understanding of interventions by combining evidence of effectiveness with insights into underlying mechanisms. This information can help researchers plan future reviews that better inform policy and practice and guide journals and funders in setting reporting standards for these innovative review designs.

BackgroundSedentary behavior (SB) is a modifiable risk factor for complications in older adults with type 2 diabetes mellitus (T2DM). Despite widespread adoption of digital health platforms, theory-driven telehealth interventions specifically targeting SB reduction remain limited, particularly those incorporating cultural adaptation and behavioral change frameworks. ObjectiveThis study aims to develop and evaluate the feasibility of a theory-based personalized telehealth intervention to reduce SB in older adults with T2DM in China. MethodsThe intervention was developed over 14 months (January 2022-February 2023) following the intervention mapping and Behavior Change Wheel frameworks. A panel of 19 multidisciplinary experts (90.5% response rate) refined the program through a systematic iterative process. Subsequently, a 7-week quasi-experimental study (pre-post self-controlled design) was conducted to assess feasibility. We recruited 30 community-dwelling older adults with T2DM via WeChat-based convenience sampling. The primary outcome was SB measured by the Measure of Older Adults’ Sedentary Time for Type 2 Diabetes Mellitus questionnaire. Secondary outcomes included cardiovascular risk (blood pressure), glycemic control (fasting blood glucose), Diabetes-Specific Quality of Life, social isolation, BMI, and fall incidence. Pre-post changes from baseline to 7 weeks were statistically evaluated to assess the intervention’s feasibility and preliminary impact. ResultsThe intervention comprises 5 components: an eHealth education manual, a motion graphics library, an SMS text messaging library, a WeChat Q&A group, and a material incentive package. These components address “knowledge,” “social support,” and “intention” determinants through “education,” “enablement,” and “incentivisation” functions, respectively. All components used the “service provision” policy and various behavior change techniques. Preliminary feasibility testing (n=31) showed reduced sedentary time by 1.12 hours/day (P<.001) and improved social connectivity scores (P=.001). ConclusionsThis study demonstrates the feasibility and potential impact of a systematically developed telehealth intervention for reducing SB in older adults with T2DM in China. The integration of intervention mapping with the Behavior Change Wheel provides a replicable framework for developing theory-driven digital health interventions. With significant reductions in sedentary time and improved social connectivity, this culturally adapted approach offers a scalable model for chronic disease self-management in aging populations. The systematic methodology and positive preliminary outcomes support further large-scale evaluation of evidence-based telehealth solutions for behavioral modification in diabetes care.

Background:Traditional simulation-based nursing education is often constrained by high costs, resource intensity, and limited scalability. AI-powered simulations offer dynamic, scalable, and personalized alternatives. However, the empirical evidence regarding their pedagogical effectiveness and learner acceptance remains fragmented. Objective:This study aimed to systematically evaluate and synthesize evidence on the effectiveness and learner perceptions of AI-powered simulations in nursing education. Methods:Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we systematically searched 11 electronic databases (PubMed, CINAHL, Embase, Web of Science, Cochrane Library, Scopus, SinoMed, CNKI, Wanfang, VIP, and Google Scholar) for studies published between January 2014 and September 2025. Two independent reviewers performed study selection, data extraction, and quality appraisal using design-specific tools (risk of bias 2 tool [RoB 2; Cochrane Bias Methods Group] for randomized controlled trials [RCTs], Risk Of Bias in Nonrandomized Studies of Interventions [ROBINS-I; Cochrane Bias Methods Group] for nonrandomized studies, Mixed Methods Appraisal Tool [MMAT] for mixed methods, Joanna Briggs Institute [JBI] for qualitative, and Agency for Healthcare Research and Quality [AHRQ] for cross-sectional studies). Quantitative data were synthesized narratively, and qualitative findings were integrated using JBI meta-aggregation. A convergent segregated approach with joint display was used to generate meta-inferences. Results:Nineteen studies involving 1253 participants (primarily prelicensure nursing students, with some interdisciplinary cohorts) were included. AI modalities comprised generative AI/large language models (n=7), AI-driven virtual patients/mannequins (n=5), AI-enhanced virtual/mixed reality (n=5), and chatbots (n=2). Three studies were RCTs, 4 were quasiexperimental with control groups, 3 were uncontrolled pre-post studies, 4 were mixed methods, 4 were qualitative, and one was a cross-sectional survey. Quantitative synthesis showed that evidence from RCTs and controlled quasiexperimental studies indicates significant improvements in cognitive knowledge and affective outcomes, including self-efficacy and communication confidence; however, effects on complex psychomotor skills were inconsistent, with one RCT finding AI-assisted simulation inferior to standardized patient simulation. Findings from uncontrolled designs are preliminary. Qualitative meta-aggregation revealed that learners valued safe, repeatable, nonjudgmental practice environments that reduced anxiety and bridged the theory-practice gap. Persistent challenges included technical frustrations, "robotic" interactions, lack of nonverbal cues, and system instability, collectively constituting an "authenticity gap." Conclusions:AI-powered simulations show promise for developing foundational clinical reasoning and communication skills in nursing education, though the evidence base is limited by the predominance of uncontrolled designs, reliance on self-reported measures, and absence of longitudinal data on skill retention or clinical transfer. Due to current technological limitations in replicating physical and emotional authenticity, AI should be implemented as a complementary tool alongside traditional simulation methods and clinical placements, rather than as a replacement. Future research should prioritize longitudinal outcomes, standardized competency measures, RCTs with active comparators, and implementation strategies addressing technical barriers.

This paper evaluated and interpreted the best practice guideline of "Diabetic foot ulcers:prevention,assessment and management(3rd edition)" released by the Registered Nurses' Association of Ontario in Canada in October 2024.The guideline covered three themes:prevention,assessment and management,so as to provide important basis for the whole⁃process care of diabetic foot ulcers.

BackgroundChemotherapy-induced nausea and vomiting (CINV) remains a distressing adverse effect that compromises patients’ quality of life and treatment adherence. Traditional assessment methods often fail to capture the full scope of patients’ real-world experiences. Social media provides unfiltered patient-generated insights into symptom management and unmet needs. This study aimed to identify key themes in CINV-related discussions among cancer patients on Chinese social media platforms using natural language processing.MethodsA total of 8, 227 public posts and comments related to CINV were collected from three major Chinese social media platforms (Weibo, REDnote, Zhihu). The dataset included posts published from January 2020 to December 2025. Latent Dirichlet Allocation (LDA) topic modeling was employed to identify latent topics, followed by qualitative thematic analysis for in-depth interpretation.ResultsFour themes were identified: (1) Emotional Support and Positive Mindset (30.37%), emphasizing encouragement and psychological reinforcement; (2) Symptom Management and Solution Exploration (24.05%), reflecting active pursuit of dietary and behavioral strategies; (3) Drug Knowledge and Experience Sharing (20.81%), highlighting information needs about antiemetic medications; and (4) Acute Symptom Impact and Medical Help-Seeking (24.77%), capturing severe symptom distress and use of social media to seek timely medical guidance.ConclusionPatients’ online discussions reveal multidimensional CINV management needs beyond pharmacotherapy, including emotional support, practical coping strategies, and medication education. Social media functions as both a peer support platform and an informal resource for symptom monitoring and medical decision-making, highlighting gaps in current clinical care. These findings support the development of patient-centered, digitally informed interventions to optimize CINV management.

BackgroundEvidence transformation remains a major challenge in nursing practice, as existing approaches often focus on professional-driven implementation while insufficiently incorporating patient participation, accessibility of evidence, and contextual adaptation. A comprehensive patient-centered pathway for translating evidence into practice is needed.AimsThis narrative review aimed to critically examine existing evidence transformation models and develop a Patient-Centered Evidence Transformation Framework to support sustainable evidence-based nursing practice.MethodsA narrative review approach was adopted to synthesize literature on evidence transformation, implementation science, patient-centered care, and integrative nursing practice. Existing theoretical models, including the Knowledge-to-Action Model, Social Movement Model, Promoting Action on Research Implementation in Health Services Framework, Consolidated Framework for Implementation Research, and Shared Decision-Making Model, were critically analyzed. A conceptual framework was developed through theoretical integration and synthesis of patient-centered evidence transformation principles.ResultsExisting models provide important insights into knowledge translation, implementation processes, and patient engagement but often address isolated components rather than a continuous transformation pathway. This review proposes a six-component Patient-Centered Evidence Transformation Framework, including Evidence Creation, Patient Version of Guidelines Development, Evidence-Based Science Popularization, Patient Decision Aids, Evidence Dissemination, and Application of Evidence. The framework highlights patients as active participants throughout the evidence lifecycle and provides guidance for evidence transformation in integrative Chinese and Western nursing practice.ConclusionThe proposed framework integrates evidence generation, patient empowerment, dissemination, and clinical application into a unified pathway.

BACKGROUND:Generative Artificial Intelligence (GenAI) has the potential to enhance research efficiency and reduce clinical workload for nursing postgraduates, gradually transforming the development of the healthcare and nursing sectors. Understanding nursing postgraduates' experiences and perceptions of Generative Artificial Intelligence tools is essential for promoting their proper application. AIM:To comprehensively explore Chinese nursing postgraduates' perceptions, attitudes, and needs regarding GenAI using qualitative interviews. DESIGN:A qualitative study design. METHODS:Semi-structured interviews were conducted among 16 nursing postgraduates. Purposeful sampling was used to select master's degree nursing students with experience in the use of artificial intelligence. Thematic analysis was performed to identify recurring patterns and codes. RESULTS:Five major themes emerged from the analysis: (1) performance expectancy, (2) effort expectancy, (3) social influence, (4) usage attitudes and behaviors, and (5) boundaries to Generative Artificial Intelligence adoption. The findings revealed nursing postgraduates' generally positive perceptions and usage behaviors toward Generative Artificial Intelligence, alongside the barriers and concerns they associate with its application. CONCLUSIONS:Generative Artificial Intelligence is increasingly integrated into research and practice in healthcare and nursing. Nursing students should approach Generative Artificial Intelligence tools rationally and apply them appropriately. This study demonstrates that nursing postgraduates hold a relatively positive attitude and cognitive stance toward Generative Artificial Intelligence. In light of the current lack of Generative Artificial Intelligence-related education, the study also proposes educational strategies tailored to the Chinese context.

As healthcare shifts toward disease prevention and whole-life-cycle health management, artificial intelligence (AI) offers key technological enablers for proactive health management. However, medical education lacks systematic curriculum models that integrate real-world proactive health challenges with AI applications. This study aims to develop and iteratively refine an interdisciplinary curriculum framework, titled "AI-Empowered Proactive Health," based on a "Teacher–Student–AI" tripartite educational ecosystem. To address this gap, this study aims to develop and iteratively refine an interdisciplinary curriculum framework, titled “AI-Empowered Proactive Health,” based on a “Teacher–Student–AI” tripartite educational ecosystem. A sequential, three-phase iterative curriculum development method was conducted from March to December 2025. In Phase 1, an initial curriculum framework was developed via expert panel meetings using the Modified Nominal Group Technique (NGT). In Phase 2, semi-structured interviews were conducted with senior nursing undergraduates for formative evaluation. In Phase 3, two rounds of expert meetings were held to review feedback item-by-item, leading to the refinement of the 25-credit-hour curriculum content, real-world project workflows, multidimensional assessment schemes, and the online digital learning platform architecture. The finalized curriculum is grounded in a "1-2-3-4-5" framework: guided by active health competencies (1 Leading Force), driven by healthcare transformation and AI advancement (2 Driving Forces), executed through instructor–student–AI collaboration (3 Roles), spanning four project phases (Problem Definition, Evidence Integration, Knowledge Graph & Agent Development, and Outcome Presentation), and integrating across five interdisciplinary domains. Student feedback resulted in reducing projects from 11 to 6 and extending contact hours from 18 to 25. The digital platform incorporates ten integrated modules (e.g., Evidence-Based Practice Workbench, Knowledge Graph Laboratory, Intelligent Agent Laboratory) to support seamless workflow execution. Assessment spans process tracking (40%), project outcomes (45%), and critical AI literacy (15%). Grounded in a tripartite educational ecosystem, the interdisciplinary "AI-Empowered Proactive Health" course provides a structured, practice-oriented model that bridges medical knowledge, evidence-based methodologies, and AI technology. This curriculum framework offers a valuable reference for cultivating proactive health professionals and reforming medical education in the digital era. the Ethics Committee of Beijing University of Chinese Medicine (Ethics Approval No.: 2025BZYLL0103)

BackgroundSurvivors of breast cancer often face challenges in maintaining physical activity (PA) and reducing sedentary behavior (SB), which are crucial for recovery and long-term health. Digital behavior change interventions (DBCIs) have emerged as promising tools to address these behavioral targets. ObjectiveThis systematic review and meta-analysis aimed to assess the effectiveness of DBCIs in promoting PA and reducing SB among survivors of breast cancer. MethodsA comprehensive search of 10 databases—PubMed, Embase, PsycINFO, the Cochrane Library, CINAHL, Web of Science, the China National Knowledge Infrastructure database, the Wanfang database, the VIP database, and the Sedentary Behavior Research Database—was conducted to identify eligible randomized controlled trials that investigated the effectiveness of DBCIs in promoting PA and reducing SB among survivors of breast cancer. Study quality was assessed using the Cochrane Risk-of-Bias tool. Data synthesis was conducted via Review Manager. Owing to anticipated heterogeneity, a random-effects meta-analysis was used. The evidence quality was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation approach. ResultsA total of 29 randomized controlled trials involving 2229 participants met the inclusion criteria. Most DBCIs were delivered at the interpersonal level using common behavior change techniques, including social support (unspecified), instruction on how to perform the behavior, demonstration of the behavior, action planning, and problem-solving. Meta-analysis revealed that DBCIs significantly improved shoulder range of motion across all planes (flexion: standardized mean difference [SMD]=2.08, 95% CI 1.14-3.01; P<.001; extension: SMD=1.74, 95% CI 0.79-2.70; P<.001; abduction: SMD=2.32, 95% CI 1.35-3.28; P<.001; external rotation: SMD=2.29, 95% CI 0.96-3.62; P<.001; internal rotation: SMD=2.98, 95% CI 1.08-4.87; P=.002; adduction: SMD=2.09, 95% CI 1.16-3.02; P<.001), finger climbing wall height (SMD=1.65, 95% CI 1.35-1.95; P<.001), upper-extremity function (SMD=−0.96, 95% CI −1.50 to −0.42; P<.001), quality of life (SMD=1.83, 95% CI 0.44-3.22; P=.01), and reduced pain (SMD=−0.58, 95% CI −0.93 to −0.22; P=.002). However, no significant differences were found in steps (P=.69), time spent in light PA (P=.51), time spent in moderate to vigorous PA (P=.43), sedentary time (P=.18), or physical function (P=.71 or .11). ConclusionsDBCIs effectively improve upper-body mobility, function, quality of life, and pain management in survivors of breast cancer. Future research should explore multilevel DBCIs specifically designed to address whole-body PA and SB reduction, with effectiveness evaluated through methodologically rigorous, large-scale trials. Trial RegistrationPROSPERO CRD42023448098; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023448098

Diabetes, particularly type 2 diabetes, is a significant global health issue, with insulin therapy being crucial for glycemic control. Psychological insulin resistance (PIR) often hinders effective treatment, impacting treatment outcomes and patient quality of life. This systematic review and meta-analysis aimed to comprehensively analyze the influencing factors of PIR among patients with type 2 diabetes, providing insights for developing targeted interventions to enhance insulin therapy acceptance and improve diabetes management. Following PRISMA guidelines, we conducted a systematic search across multiple databases, including PubMed, the Cochrane library, CINAHL, Embase, APA PsycInfo, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Database, China Science and Technology Journal Database (VIP), and Sinomed, from inception to July 2025. Studies were included if they focused on type 2 diabetes patients and PIR, with exclusion of non-original research and republished literature. Quality assessment was performed using Newcastle-Ottawa Scale for cohort and case-control studies, and AHRQ standards for cross-sectional studies. A total of 22 studies involving 5,965 patients were included. The prevalence of PIR ranged from 27.1 to 82.9

INTRODUCTION:Embodied conversational agents (ECAs) are computer-based dialogue systems designed to simulate face-to-face interactions by incorporating human-like physical attributes. Their capacity to establish and maintain an empathic relationship in patient interactions positions them as innovative tools that facilitate shared decision-making (SDM). To systematically synthesise the existing evidence concerning the development and application of ECAs in promoting SDM, this protocol delineates a scoping review designed to identify and present the available evidence within this domain. Specifically, the protocol outlines a review that will concentrate on the key features of ECAs in the context of SDM, including their appearance, dialogue mechanisms and emotional models, within the framework, as well as their implementation and evaluation in clinical settings. METHODS AND ANALYSIS:The framework established by Arksey and O'Malley will be employed to guide the scoping review process. This protocol outlines the systematic retrieval of seven databases, including PubMed, EMBASE, PsycINFO, Web of Science, the Cumulative Index to Nursing and Allied Health Literature, Institute of Electrical and Electronics Engineers (IEEE) Xplore Digital Library and Association for Computing Machinery (ACM) Digital Library. The search strategy has been developed and will be conducted across each database, from its inception to September 2024. Two researchers will conduct literature screening and data extraction independently. The results will be systematically organised and presented through narrative abstracts, tables and/or figures. ETHICS AND DISSEMINATION:Ethical approval is not necessary for this review, as it uses data that have been previously collected. Furthermore, the obtained results will be reported in a peer-reviewed journal. TRIAL REGISTRATION NUMBER:Open Science Framework Registries (https://doi.org/10.17605/OSF.IO/BN3CM).

Objective. This qualitative study explores the barriers and facilitators to implementing shared decision making (SDM) for breast reconstruction (BR) from multistakeholder perspectives in the Chinese health care context. Methods. A qualitative study was conducted from November 2021 to January 2022, involving 36 participants, including patients, doctors, nurses, and hospital administrators from 3 tertiary hospitals in Beijing, Hebei, and Guangzhou. Purposeful and snowball sampling was used until data saturation. In-depth semi-structured interviews were analyzed using thematic analysis. Results. Findings from 36 stakeholders (20 patients, 16 health care providers/administrators) revealed 5 key dimensions influencing SDM implementation: decision making, patient, health care professional (HCP), organizational, and societal levels. Notable factors include patient self-efficacy, information needs, HCPs’ role recognition and SDM competencies, team coordination, SDM convenience, availability of support tools, and cultural influences. Limitations. The limitations of this study primarily stem from the narrow sample source, which includes only 3 regions in mainland China. Conclusion. Successful SDM implementation in China requires optimizing clinical workflows, utilizing technological tools, providing professional training, and integrating SDM with traditional Chinese medicine philosophies. These strategies enhance decision-making quality and align SDM practices with Chinese cultural values. Practice Implications. Integrating culturally sensitive SDM into clinical workflows, supported by decision tools, training, and robust policies, is essential for BR SDM in China. Highlights Identified barriers and facilitators on shared decision making for breast reconstruction from multistakeholder perspectives in China’s health care context. Explored cultural influences on shared decision making for breast reconstruction in Chinese patients. Emphasized the importance of integrating shared decision making into existing clinical workflows. Proposed integrating traditional Chinese medicine diagnostics with shared decision making for culturally sensitive care.

This scoping review systematically examines the application of Intervention Mapping (IM) in knowledge translation (KT) processes, focusing on its effectiveness, completeness, advantages and challenges. Following Joanna Briggs Institute (JBI) guidelines, we conducted a scoping review of 57 studies (1998–2024) from PubMed, Embase, Web of Science, and Chinese databases. The data extracted encompass the basic information of the studies, the objectives of the research, the part of the IM steps, as well as the main results and the methods used for evaluating. IM demonstrated broad applicability across 18 healthcare domains, with the highest prevalence in maternal and child health (12.3

Objective: This scoping review aims to summarize the steps for adapting patient decision aids (PDAs) based on current research and to explore related methodologies. Methods: A systematic search of the PubMed, Cochrane Library, EMBASE, CINAHL, Web of Science, CNKI, WANFANG, VIP, and SinoMed databases and grey literature was conducted up to January 2024. The search terms focused on patient decision aids and their adaptation. The results were integrated through statistical and thematic analysis. Results: Twenty-five studies were included. Eight steps for adapting PDAs were identified, including defining decision problems and options; assessing local cultural backgrounds; translating; adjusting PDA language style, content, and presentation; creating an initial version of the PDA; conducting acceptability testing; conducting feasibility testing; and PDA revisions. Only a few studies followed a rigorous process for adapting PDAs, and most research did not undertake steps such as local cultural background assessment and feasibility testing due to challenges related to sample size acquisition, cultural diversity, and complexity. Conclusion: This study focused on the steps of language style, content, presentation adjustment, and acceptability testing in the overall process of formulating the steps for adapting decision support tools, adapting these tools, and identifying specific methods for acceptability testing. This study enhanced the quality assessment indicators for PDA language style, content, and presentation adjustments to provide a reference for subsequent research. However, gaps still exist in the evaluation standards for the language style, content, and presentation of PDAs that should be addressed by future research.

Objective:To systematically and comprehensively search the studies describing healthcare personnel's perceptions about reducing low-value care. Design:Scoping review. Methods:Evidence sources included PubMed, ProQuest and CINAHL databases from inception to 13th September 2023, along with grey literature, expert suggestions and reference lists from the included articles. Studies were included if they contained information about healthcare personnel's perceptions and involvement in reducing low-value care. The extracted data included general study characteristics, the type of low-value care of interest, clinical settings, and main findings related to healthcare personnel's perceptions. Three frameworks were used to guide the data synthesis. First, the main findings from the included studies were mapped onto the Process of De-adoption Framework to capture the aspects of low-value care that healthcare personnel focused on, including the identification of low-value care, barriers and facilitators to reducing low-value care, and intervention strategies. The identified barriers and facilitators were then mapped onto the relevant domains of the Theoretical Domains Framework. Finally, the intervention strategies, as informed by healthcare personnel's perceptions, were mapped to the Cochrane Effective Practice and Organization of Care taxonomy framework. Results:The 37 included studies were those published since 2011. Of these, 15 studies were conducted in the United States. Most included studies (n = 19) described low-value care not specific to a care measure. Twelve of the included studies described healthcare personnel's perceptions regarding the identification of low-value care, 34 studies described healthcare personnel's perceptions regarding influence factors to reducing low-value care and 18 studies described healthcare personnel's perceptions regarding intervention strategies to reduce low-value care. "Knowledge" (n = 16) and 'environmental context and resources' (n = 16) were the most common influence factors of reducing low-value care. "Education" was the most commonly discussed intervention strategy for reducing low-value care (n = 14). Conclusion:Healthcare personnel's perceptions focused on identifying low-value care, barriers and facilitators of reducing low-value care and intervention strategies to reduce low-value care. Education was potentially the main effect of the intervention strategies in addressing lack of knowledge, which is the main barrier to reducing low-value care. Future research should develop and implement intervention strategies to reduce low-value care based on healthcare personnel's perceptions.

Objective: To explore breast cancer (BC) patients' participation in breast reconstruction (BR) decision-making and specific decisional needs, especially the manifestations and causes of decisional conflicts, in China. Methods: A mixed-methods study was conducted using triangulation of data from interviews and a questionnaire survey with health care professionals (HCPs) and BC patients with BR decision-making experience at 5 Beijing centers. The Ottawa Decision Support Framework guided (ODSF) the qualitative and quantitative data analyses. Results: A total of 82.53% of Chinese BC patients would consider BR. Seven themes captured patients' BR decisional needs per the ODSF: inadequate support/resources (100%, 58.82%) and knowledge (75%, 52.94%) were most frequently cited. Health beliefs (unclear values) reflected Chinese characteristics. Patients had inadequate knowledge (M=19.99/50, SD=8.67) but positive BR attitudes (M=59.48/95, SD=10.45). Conclusions: BR decisions for Chinese BC patients are complex and often accompanied by decisional conflicts. Inadequate knowledge and inadequate support and resources contribute to these conflicts, emphasizing the need for culturally tailored information and support to promote SDM. Practice implications: HCPs need specialized training in SDM to guide patients in decision-making. It is essential to provide relevant resources and support that are culturally and clinically appropriate for Chinese patients.

目的 探讨现实主义综述评估复杂护理干预的现状,为引入该方法提供参考.方法 采用范围综述方法,系统检索国内外数据库中护理领域的现实主义综述,检索时限为建库至2022年3月,由2名研究者独立筛选、提取资料,采用描述性分析及主题分析法对提取结果进行整理.结果 共纳入47篇文献,其中35篇发表于近5年.研究主题以社区/公共卫生护理和老年护理居多.构建初始项目理论、检索和筛选证据、评价证据、资料提取、综合与分析5个关键步骤中对核心过程项目理论构建与完善的报告不充分.结论 现实主义综述可揭示复杂护理干预发挥作用的机制,国内需借鉴国外的应用经验并加以规范与完善,为发展我国护理理论和实践研究提供新思路.

Objective:This study aimed at culturally adapting pan-Canadian Oncology Symptom Triage and Remote Support (COSTaRS) Cancer-related fatigue (CRF) Practice Guide to enable its use in China. This article focuses on presenting the key cultural adaptation step: supplementing traditional Chinese medicine (TCM) nursing recommendations for CRF symptom management according to evidence.Methods:Guided by A Guideline Adaptation and Implementation Planning Resource (CAN-IMPLEMENT), the process for cultural adaptation of the CRF guide in the COSTaRS project included translation, expert committee review, acceptability and feasibility assessment, and targeted adaptation to include TCM nursing techniques for CRF management via the Delphi method.Results:First, an expert committee of nurses, nurse leaders, and researchers was established. The practice guide was translated and verified by the members of the expert committee. Nurses then rated the practice guide for acceptability and feasibility. Concurrently, 83 stakeholders (nurses and patients) identified five relevant TCM nursing techniques: acupuncture, moxibustion, acupressure therapy, Taijiquan, and auricular acupoint embedding. A systematic review of literature identified three clinical practice guidelines and four systematic reviews. Through two rounds of Delphi expert consultation, five TCM care strategies were added into the culturally adapted COSTaRS practice guide.Conclusions:Cultural adaptation of the Canadian CRF practice guide involved not only language translation but also the addition of relevant TCM evidence. Combining TCM evidence and the Delphi method was a novel aspect of the cultural adaptation process. Further research is needed to investigate the implementation of the guide in appropriate settings in China.