BACKGROUND:The role of cardiovascular health (CVH) factors and their associated proteomic profiles in the progression and prognosis of cardiovascular-kidney-metabolic (CKM) syndrome among individuals at stages 0-3 remains unclear. METHODS:This study analyzed data from 10,351 Chinese adults (China Health and Retirement Longitudinal Study [CHARLS]), 224,352 British adults (UK Biobank [UKB]), and 20,726 American adults (National Health and Nutrition Examination Survey [NHANES]). Cox proportional hazards models were used to assess the associations of CVH score and proteomic panel with incident CVD and mortality in CKM stages 0-3 individuals. RESULTS:The median follow-up periods were 13.6 years in UKB, 9.4 years in CHARLS, and 7.5 years in NHANES. Among individuals with CKM stages 0-3, those with optimal CVH had reduced risks of overall CVD compared with those with low CVH (UKB, HR = 0.58, 95% CI: 0.55-0.62; CHARLS, HR = 0.77, 95% CI: 0.64-0.92), and all-cause mortality (UKB, HR = 0.45, 95% CI: 0.42-0.49; CHARLS, HR = 0.60, 95% CI: 0.47-0.76; NHANES, HR = 0.34, 95% CI: 0.26-0.44). These protective associations were similarly observed across CVD subtypes and cause-specific mortality. An ENM-selected panel of 722 proteins was associated with 41% lower overall CVD risk and 54% lower all-cause mortality. Meanwhile, circulating proteins mediated the associations between CVH score and CKM syndrome progression and prognosis, particularly ALPP. CONCLUSIONS:Optimal cardiovascular health behaviors and factors are key to halting the progression and improving the prognosis of CKM syndrome, with the associated proteins potentially serving as biomarkers and molecular targets for interventions.

Introduction:Coronary heart disease (CHD) is a major global health burden requiring long-term management. Despite the essential role of health information seeking behavior (HISB) in disease self-management, current levels among CHD patients remain low, and research on its influencing factors is limited. Objectives:This study aimed to explore HISB among patients with CHD and to identify factors associated with variations in HISB using the Risk Perception Attitude (RPA) framework. Methods:A cross-sectional study of 330 CHD patients was conducted in China, using convenience sampling method. Data were collected through validated questionnaires assessing sociodemographic and clinical characteristics, HISB, risk perception, and self-efficacy. K-means clustering based on the RPA framework was employed to empirically identify distinct patient subgroups. Multivariate linear regression identified factors associated with of HISB within each subgroup. Results:Four distinct subgroups were identified based on risk perception and self-efficacy: Responsive (6.7%), Proactive (41.2%), Indifference (8.2%), and Avoidance (43.9%). Multivariate regression revealed subgroup-specific factors: for Responsive, physical diagnosis and treatment risk was significant [β = 2.049, 95%CI (0.528,3.570)]; For Proactive, higher education [β = 4.725, 95%CI (2.272,7.178)], per capita monthly household income and self-efficacy were positively associated, while type of medical insurance [β = -5.814, 95%CI (-8.800, -2.828)], number of other diseases, and economic risk were negative predictors; For Indifference, only type of medical insurance was significant [β = -6.447, 95%CI (-12.503, -0.391)]; For Avoidance, older age was linked to lower HISB [β = -4.757, 95%CI (-8.525, -0.989)], whereas higher education increased it [β = 5.432, 95%CI (2.353, 8.511)]. Conclusions:This study validates the heterogeneity of CHD patients through RPA-based subgrouping, revealing that health information seeking behaviors are driven by distinct psychological and socioeconomic mechanisms across different groups. These findings underscore the limitation of uniform health education approaches and highlight the necessity of implementing subgroup-tailored strategies. By aligning clinical and public health interventions with the specific psychographic profiles of patient groups, healthcare providers can significantly enhance the precision and effectiveness of chronic disease management. Registration:www.chictr.org.cn, identifier: ChiCTR2300069238.

Background:Acute stroke, particularly posterior circulation stroke, is often missed in emergency departments due to non-specific symptoms. We aimed to evaluate the diagnostic performance of the BE-FAST-V scale, which adds Vertigo assessment to the original BE-FAST, for acute stroke screening. Methods:The study included 1,094 patients presenting to a tertiary hospital's emergency department with suspected stroke. On arrival, the BE-FAST-V scale, which assesses Balance, Eyes, Face, Arm, Speech, Time, and Vertigo, was administered. Stroke diagnoses were confirmed through imaging. Diagnostic accuracy metrics, including sensitivity, specificity, and predictive values, were calculated. Results:The BE-FAST-V scale demonstrated high diagnostic accuracy, strong sensitivity, and moderate specificity. Adding vertigo improved the detection of posterior circulation strokes, which are often missed due to nonspecific symptoms. Conclusion:The BE-FAST-V tool presented a highly sensitive and practical value for stroke screening in the emergency department. Its ability to identify posterior circulation strokes, including those presenting with vertigo, addresses a critical gap in stroke diagnosis and supports early treatment initiation. Broader implementation and further validation across multiple centers could enhance its role in improving stroke outcomes globally.

OBJECTIVES:To investigate the association between accelerometer-based sleep regularity and depression, and to explore whether meeting sleep duration recommendations modifies the effects of irregular sleep patterns. METHODS:In this cross-sectional study, data were analyzed from 7402 adults who participated in the 2011-2014 NHANES and wore accelerometers. Sleep regularity patterns were quantified via the Sleep Regularity Index, and participants were classified as regular, moderately irregular, or irregular sleepers. Depressive symptoms were evaluated with the PHQ-9. Survey-weighted logistic regression, survey-weighted restricted cubic splines, and survey-weighted linear regression were employed to estimate the association between sleep regularity patterns and depression risk, with sleep duration further examined in this relationship. RESULTS:Adults with irregular sleep patterns (OR 2.65; 95% CI 1.74-4.03) exhibited a higher odds of depression compared with those with regular sleep patterns. A dose-response analysis, which treated the Sleep Regularity Index as a continuous variable, indicated a linear relationship between Sleep Regularity Index and depression. Notably, individuals with irregular sleep patterns faced a higher odds of depression (OR 2.68; 95% CI 1.59-4.53) even when they met the recommended sleep duration guidelines. However, no significant multiplicative interaction (P = .727) or additive interaction (RERI -0.31; 95% CI -1.27 to 0.65) was observed between sleep regularity and sleep duration in relation to depression risk. CONCLUSIONS:Irregular sleep patterns were associated with an elevated odds of depression, even when adults met the recommended sleep durations. Evidence-based interventions designed to enhance sleep regularity could be integrated as potential strategies for the prevention and treatment of depression.

ABSTRACT Background The growing burden of cancer necessitates continuity of care interventions linking hospital and primary health care (PHC). However, optimal approaches for improving effectiveness and for enhancing care coordination of PHC integration remain unclear. Methods A systematic review with meta‐analysis was conducted. Six databases including PubMed, Embase, Web of Science, CINAHL, CENTRAL, and PsycInfo were searched for full texts of randomized or non‐randomized controlled trials (RCTs or nRCTs) from January 2000 to January 2024. Patient‐reported outcomes (quality of care, psychological status), quality of care (adverse events, perceived continuity of care, and satisfaction), healthcare utilization (hospitalization, PHC use, length of stay and emergency visits), and cost evaluation were synthesized. A random‐effects model was used for data analysis, and exploratory subgroup analyses based on intervention characteristics were conducted. Risk of bias was evaluated by using Cochrane Collaboration's Risk of Bias handbooks of RCTs, or Cochrane Risk of Bias Assessment Tool for nRCTs. Intervention strategies aimed at addressing the continuity of care dimensions were synthesized through a deductive approach. Results Twenty eight studies from 23 unique interventions were included in the study, all conducted in high‐income countries. Information continuity demonstrated the most effective practice, while management continuity received less emphasis. The overall effect size for quality of life was insignificant (standard mean difference [SMD] 0.01, 95% CI −0.04, 0.05), whereas satisfaction with care was marginally improved in intervention groups (SMD = 0.09, 95% CI 0.01, 0.18). Potential beneficial effects in reduced healthcare utilization and economic savings warrant further study. Conclusions Continuity of care interventions by integrating PHC into cancer care is overall not inferior to specialist‐led care. Further efforts to enhance the management continuity dimension of intervention and extend initiatives beyond high‐income countries are warranted. Trial Registration PROSPERO registration number CRD42023473024

Abstract Background The co-occurrence of diabetes and mental disorders is an exceedingly common comorbidity with poor prognosis. We aim to investigate the impact of green space, garden space, and the natural environment on the risk of mental disorders among the population living with diabetes. Methods We performed a longitudinal analysis based on 39,397 participants with diabetes from the UK Biobank. Residential green and garden space modeled from land use data and the natural environment from Land Cover Map were assigned to the residential address for each participant. Cox proportional hazards model was used to analyze the associations between nature exposures and mental disorders of diabetes. Casual mediation analysis was used to quantify indirect effect of air pollution. Results During a mean follow-up of 7.55 years, 4513 incident mental disorders cases were identified, including 2952 depressive disorders and 1209 anxiety disorders. Participants with natural environment at 300 m buffer in the second and third tertiles had 7% (HR = 0.93, 95%CI: 0.86–0.99) and 12% (HR = 0.88, 95%CI: 0.82–0.94) lower risks of incident mental disorders compared with those in the first tertile, respectively. The risk of mental disorders incidence among diabetes patients will decrease by 13% when exposed to the third tertile of garden space at 300 m buffer. The natural environment and garden space individually prevented 6.65% and 10.18% of mental disorders incidents among diabetes patients. The risk of incident mental disorders was statistically decreased when exposed to the third tertile of green space at 1000 m buffer (HR = 0.84, 95% CI: 0.78–0.90). Protective effects of three nature exposures against depressive and anxiety disorders in diabetes patients were also observed. Air pollution, particularly nitrogen dioxide, nitrogen oxides, and fine particulate matter, significantly contributed to the associations between nature exposures and mental disorders, mediating 48.3%, 29.2%, and 62.4% of the associations, respectively. Conclusions Residential green and garden space and the natural environment could mitigate mental disorders risk in diabetes patients, with air pollution playing a vital mediator. This highlights the potential for local governments to enhance the sustainability of such interventions, grounded in public health and urban planning, through strategic planning initiatives. Graphical Abstract

INTRODUCTION:Multimorbidity is increasing globally, emphasizing the need for effective self-management strategies. The Cumulative Complexity Model (CuCoM) offers a unique perspective on understanding self-management based on workload and capacity. This study aims to validate the CuCoM in multimorbid patients and identify tailored predictors of self-management. METHODS:This multicenter cross-sectional survey recruited 1920 multimorbid patients in five primary health centres and four hospitals in China. The questionnaire assessed workload (drug intake, doctor visits and follow-up, disruption in life, and health problems), capacity (social, environmental, financial, physical, and psychological), and self-management. Data were analyzed using latent profile analysis, chi-square, multivariate linear regression, and network analysis. RESULTS:d Patients were classified into four profiles: low workload-low capacity (10.2%), high workload-low capacity (7.5%), low workload-high capacity (64.6%), and high workload-high capacity (17.7%). Patients with low workload and high capacity exhibited better self-management (β = 0.271, p < 0.001), while those with high workload and low capacity exhibited poorer self-management (β=-0.187, p < 0.001). Social capacity was the strongest predictor for all profiles. Environmental capacity ranked second for 'high workload-high capacity' (R² = 3.26) and 'low workload-low capacity' (R² = 5.32) profiles. Financial capacity followed for the 'low workload-high capacity' profile (R² = 5.40), while psychological capacity was key in the 'high workload-low capacity' profile (R² = 6.40). In the network analysis, socioeconomic factors exhibited the central nodes (p < 0.05). CONCLUSIONS:Personalized interventions designed to increase capacity and reduce workload are essential for improving self-management in multimorbid patients. Upstream policies promoting health equity are also crucial for better self-management outcomes.

This study investigates the influence of structural empowerment and psychological capital on nurse work engagement within the context of rising healthcare demands and nursing staff shortages. A cross-sectional descriptive study involving 778 registered nurses from six tertiary hospitals in Hangzhou, China, was conducted. Data were collected using multiple tools, including a demographic questionnaire, the CWEQ-II (Conditions for Work Effectiveness Questionnaire II), the PCQ (Psychological Capital Questionnaire), and the UWES-9 (Utrecht Work Engagement Scale-9). SPSS 27.0 was used for Pearson correlation and regression analyses, while structural equation modeling (SEM) in AMOS was employed to explore relationships among variables. Model fit was evaluated using chi-square, CFI, AGFI, and RMSEA indices. Structural empowerment and psychological capital were significantly and positively correlated with nurses’ work engagement. Regression analysis indicated that structural empowerment (support, resources, opportunity, and information) and psychological capital (optimism, resilience, self-efficacy, and hope) were significant positive predictors of work engagement (p < 0.01), jointly accounting for 69

BackgroundHealth portraits powered by big data integrate diverse health-related data into actionable insights, thereby facilitating precise risk prediction and personalized management of noncommunicable diseases (NCDs). Despite their promise, the adoption and application of health portraits remain fragmented, primarily due to the lack of a standardized conceptual and methodological framework necessary to fully harness their capabilities. ObjectiveThis study aimed to systematically map and categorize existing research on health portraits in the context of NCD management, evaluate how big data has been used through the lens of the 3V (volume, velocity, and variety) framework, assess the extent of external validation and comprehensiveness, and identify challenges, emerging opportunities, and future research directions in this field. MethodsA scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines and 6-step framework of Levac et al. A comprehensive search was performed in PubMed, Embase, EBSCO, Ovid, Scopus, Web of Science, and Springer Link, focusing on observational and interventional studies using big data, public databases, electronic health record systems, wearables, and sensors for NCD management from January 2014 to July 2024. Data extraction included study characteristics, modeling approaches, and external validation. Analytical synthesis was conducted using keyword analysis, the 3V framework, and visual tools such as scatter plots, heat maps, and radar charts. ResultsA total of 8707 records were identified, and 89 studies were included for full-text analysis. These studies were categorized into 4 types of health portraits: diagnostic, prognostic, monitoring, and recommender. Evaluation based on the 3V framework showed that only 17.78% of studies met all 3 criteria. In terms of volume, structured data were widely used (64.29%-100% depending on portrait type), while unstructured data usage varied significantly (19.05%-93.33%). Regarding velocity, monitoring and recommender portraits showed high reliance on digital interactive data (over 85%). For variety, only 31.11% of studies incorporated all 3 data attributes (natural, domain, and specific attributes). In terms of comprehensiveness, only 30% of studies reported the external validation, and only 10% met both the external validation and 3V criteria, with recommender portraits outperforming the other types. ConclusionsThis study provides a standardized lens through which to evaluate the development and application of health portraits in NCD management. The findings underscore the need for more robust data integration strategies and emphasize the importance of artificial intelligence–enabled approaches. Furthermore, enhancing external validation and addressing ethical and privacy considerations are critical for advancing the implementation of personalized health management solutions.

ABSTRACTAimsTo classify the unmet integrated care needs of older adults with multimorbidity and to explore the factors associated with different categories of unmet integrated care needs among the target population.DesignA cross‐sectional survey using the statistical method of latent profile analysis.MethodsFrom July 2022 to March 2023, 397 older adults with multimorbidity, aged 60 years or older, were recruited from one primary healthcare setting and from four secondary and tertiary hospitals to participate in face‐to‐face questionnaire surveys. The questionnaire used in this study to assess unmet integrated care needs among older adults with multimorbidity was self‐designed through a series of steps, including a scoping review, expert consultation and cognitive interviews. Latent profile analysis was applied to uncover distinct profiles of unmet integrated care needs, and multinomial logistic regression was employed to explore whether the profiles were further distinguished by participants' sociodemographic and health‐related covariates. The data were analysed using IBM SPSS v.29.0 and Mplus v.8.0.ResultsThe optimal solution was a four‐profile model, characterised by high unmet integration needs, high unmet system integration needs, low unmet system integration needs and low unmet integration needs, respectively. Multinomial logistic regression results indicated that profile differences were associated with place of residence, number of coresidents and the presence or absence of complex multimorbidity.ConclusionThe integrated care needs of older adults with multimorbidity have not yet been fully met. Classifying and characterising unmet integrated care needs profiles is a crucial step in the rational allocation of integrated care resources.Reporting MethodThis study was reported based on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for cross‐sectional studies.Patient or Public ContributionAll participants were older adults with multimorbidity, and they were informed that they could withdraw from the study at any time.

BACKGROUND:The definition of China's integrated delivery system remains abstract since it was proposed in 2021, lacking detailed clarification on essential concepts such as specific contents and main providers of services for older adults with multimorbidity. AIM:To develop an integrated care conceptual framework for older adults with multimorbidity within China's integrated delivery system. METHODS:A scoping review, semi-structured interviews and a modified e-Delphi study were used to explore specific contents of integrated care for older adults with multimorbidity. A social network analysis was conducted to identify healthcare providers with the greatest potential to play a central role in the integrated care for older adults with multimorbidity. Finally, an integrated care conceptual framework was established based on specific contents and main providers. RESULTS:The center of the framework represents the people-centered and need-oriented connotation of China's integrated delivery system. The first circle reflects three significant characteristics of the integrated delivery system, namely care comprehensiveness, care coordination, and care continuity. The second circle includes main providers of integrated care, which are expected to play a central role in professional collaboration and information diffusion. The outermost circle consists of specific contents of integrated care, including clinical practice, human workforce, organisational collaboration, information technology, regulations and policies. CONCLUSION:The framework derived from this study is expected to promote the understanding and implementation of integrated care for older adults with multimorbidity within the Chinese context. The service content of integrated care related to clinical practice also offers valuable references for other countries.

Aim. To develop a scale for measuring nurse's perceived work environment during the public health emergencies (PHEs) and assess its reliability and validity. Background. Although there is extensive research on instruments for measuring nursing work environments in regular healthcare settings, there is a lack of specific scales tailored to address the unique work conditions experienced by nurses during PHEs. Design. This study employed a cross-sectional design for psychometric evaluation and adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement. Methods. A self-report scale, the Chinese Nursing Work Environment Scale for Public Health Emergencies (C-NWE-PHE), was developed, integrating situational characteristics. Data on demographics, adapted scale scores, and subjective evaluations of nursing management performance were collected from 1156 nurses through online surveys conducted between January 2023 and March 2023. Confirmatory factor analysis, Pearson correlations, and Cronbach's alpha analyses were conducted to evaluate the psychometric properties of the scale. Results. The adapted C-NWE-PHE scale comprised 28 items organized into five subscales: Workforce and Deployment Support, Leadership and Emergency Management, Autonomy and Empowerment, Teamwork and Collaboration, and Logistics and Humanistic Care. Structural equation modelling showed satisfactory factor loadings for each subscale and a good model fit, confirming construct validity. The content validity and reliability of the total scale were confirmed. Conclusion. This study provides empirical evidence for understanding and assessing the nursing work environment during PHEs with a psychometrically sound scale. Implications for Nursing Management. The C-NWE-PHE scale, along with its five identified constructs, provides a nuanced comprehension of working conditions amid PHEs. Implementing this scale could foster specific enhancements, support nurse retention efforts, and enhance the effectiveness of responses during challenging emergency situations.

OBJECTIVES:The objective of this study was to explore the phenomenon and determinants of healthcare service utilization in Chinese older adults with multimorbidity.METHODS:We adopted a mixed-methods explanatory design from July 2022 to May 2023. The quantitative research was a social network analysis to explore the phenomenon of healthcare service utilization in target participants. The quantitative results were further interpreted as the participant's propensity for healthcare services and the potential for information sharing between healthcare providers through shared patients. Logistic regression was conducted to identify individual determinants for healthcare service utilization. The quantitative research was followed by qualitative interviews with stakeholders to deeply understand the phenomenon of interest from the individual, healthcare system, and societal perspectives.RESULTS:We recruited 321 participants for the quantitative study. They preferred using medication services from primary healthcare providers, pharmacists at private pharmacies, and hospital specialists, and preferred using other services from hospital specialists. Dense relationships arose from shared patients among healthcare providers across various professions and settings, making it possible to share patient information. Primary healthcare providers were particularly important in the process, as they were closely related to others through patient sharing. Health status was identified through logistic regression and qualitative interviews as an individual determinant for healthcare service utilization. More determinants were explored in qualitative interviews with 30 stakeholders, including trust, resource allocation, healthcare accessibility, medical treatment process, and healthcare awareness.DISCUSSION:Strategies should be proposed to intervene with patients' nonoptimal propensity toward healthcare services and promote information sharing among healthcare providers.

AIMS:Adherence to diet and exercise recommendations is crucial among metabolic syndrome (MetS) individuals. However, no studies have focused on comprehensive behavioural changes of diet and exercise among individuals with MetS. The present study aimed to explore determinants of adherence to diet and exercise behaviours among people with MetS based on the Capability, Opportunity, Motivation, and Behaviour (COM-B) model.METHODS AND RESULTS:A cross-sectional study was conducted in a health promotion centre of a large and general university hospital in Zhejiang Province, China, in 2021. A total of 241 individuals with MetS completed all scales. The mediation model was tested using structural equation modelling with bootstrapped samples. In the regression-based path analysis, MetS knowledge (β = 0.140), socioeconomic status (β = 0.162), and social support (β = 0.143) directly positively influenced diet behaviour. In addition, social support indirectly positively influenced exercise behaviour through coping and adaptation (β = 0.090). The final theoretical model showed a good fit (root mean square error of approximation = 0.057, comparative fit index = 0.946).CONCLUSION:Factors associated with diet behaviour were knowledge of MetS, socioeconomic status, and social support. Adaptation may be a mediator between social support and exercise behaviour. Intervention programmes targeting increased adherence to diet and exercise could include these factors for individuals with MetS.

Background: The association between sedentary behavior and health-related outcomes has been well established, whereas it is inconclusive whether a sedentary behavior pattern is an additional risk factor for health-related out-comes independent of total sedentary time and physical activity.Objectives: To determine sedentary behavior patterns and their association with risks of noncommunicable dis-eases and all-cause mortality and to assess whether this association is independent of total sedentary time and physical activity.Design: This was a systematic review and meta-analysis.Methods: Studies were obtained by searching the Web of Science Core Collection, PubMed/Medline, the Cochrane Library, Embase, CINAHL, and SPORTDiscus up to April 2023. All observational studies published in English or Chinese were included if they explored sedentary behavior patterns and their association with risks of abdominal obesity, metabolic syndrome, diabetes, cardiovascular disease, cancer, and all-cause mortality among individuals who had never experienced the outcome event before the baseline assessment. Data extraction using a standardized form and quality appraisal using two authoritative tools were then performed. All these steps were completed by two independent reviewers from December 2022 to May 2023. If data were sufficiently homogenous, meta-analyses were performed; otherwise, narrative syntheses were employed. Harvest plots were also used to visually represent the distribution of evidence.Results: Eighteen studies comprising 11 prospective cohort studies and seven cross-sectional studies were included. The findings suggested that prolonged sedentary time and usual sedentary bout duration were two metrics that reflected the nonlinear dose-response effect of prolonged sedentary behavior patterns. Only extremely high levels of prolonged sedentary behavior patterns significantly increased the risk of adverse health outcomes, independent of physical activity. Whether prolonged sitting was an additional risk factor for adverse health outcomes, independent of total sedentary time, was inconclusive due to an insufficient number of primary studies that included total sedentary time as one of the potential covariates. There was some evidence that supported a sedentary bout that significantly increased the risk of adverse health outcomes was 30-60 min. The threshold of prolonged sedentary time differed with outcomes, and future studies are needed to make this threshold more precise.Conclusion: A prolonged sedentary behavior pattern was associated with increased risks of several major noncommunicable diseases and all-cause mortality. People, especially those who do not reach the recommended level of moderate-to-vigorous physical activity, are encouraged to interrupt sedentary bouts every 30 to 60 min and limit prolonged sedentary time per day as much as possible.Tweetable abstract: Breaking up consecutive sedentary bouts >30 to 60 min and substituting them with brief bouts of physical activity.& COPY; 2023 Elsevier Ltd. All rights reserved.

OBJECTIVES:To develop a Chinese version of the Long-Term Conditions Questionnaire (LTCQ) and to test its reliability and validity in Chinese patients with chronic diseases. METHODS:With the consent of the original authors, a Chinese version of LTCQ was developed according to the cultural adjustment guidelines. A questionnaire survey was conducted on 319 patients with chronic diseases in Sir Run Run Shaw Hospital, Wuyi County First People's Hospital and Hangzhou Gongchen Bridge Street Health Service Center. The questionnaire was evaluated by item analysis (including frequency analysis, total question correlation method and critical ratio method), reliability analysis (Cronbach's alpha coefficient) and validity analysis [including content validity (expert scoring method) and structural validity (exploratory factor analysis)]. RESULTS:The Chinese version of the LTCQ included 20 entries, with a Cronbach's alpha coefficient of 0.926, a retest reliability of 0.829, a split-half reliability of 0.878, an entry content validity index of 1, and a content validity index at the questionnaire level of 1. Four common factors were extracted by exploratory factor analysis, namely physical state and daily life, psychological state, support and coping, and safe environment, with a cumulative variance contribution rate of 67.244%. Discussion: The Chinese version of the LTCQ developed in this study has good reliability and validity and it may be used to assess the long-term conditions of patients with chronic diseases in China.

目的 构建基于K最近邻(KNN)算法和logistic回归的代谢综合征预测模型并比较两种模型对代谢综合征的预测效能.方法 纳入6 793例研究对象进行数据分析,构建基于KNN算法和logistic回归的预测模型,对模型进行内部验证及外部验证,采用多维度指标对预测性能进行评估,对比两种预测模型的预测效能.结果 基于KNN算法预测模型的内部验证曲线下面积(AUC)为0.776(95％CI:0.764～0.788)、校准截距为 0.028(95％CI:-0.031～0.089)、校准斜率为 1.181(95％CI:1.106～1.257)、布里尔分数为 0.157;外部验证 AUC 为 0.780(95％CI:0.768～0.791)、校准截距为 0.262(95％CI:0.207～0.317)、校准斜率为 1.053(95％CI:0.990～1.117)、布里尔分数为0.167.基于logistic回归预测模型内部验证AUC为0.783(95％CI:0.772～0.795)、校准截距为-0.008(95％CI:-0.088～0.073)、校准斜率为 0.995(95％CI:0.934～1.058)、布里尔分数为0.156;外部验证 AUC为0.782(95％CI:0.771～0.793)、校准截距为-0.045(95％CI:—0.113～0.022)、校准斜率为1.006(95％CI:-0.011～1.063)、布里尔分数为0.164.结论 在代谢综合征的风险预测上,logistic回归预测模型表现优于基于KNN算法预测模型.

OBJECTIVES:To explore the factors that influence self-management behavior in cancer patients based on the theoretical domain framework.METHODS:Studies in Chinese and English about factors influencing self-management behavior in cancer patients were searched from Wanfang database, CNKI, VIP, SinoMed, PubMed, Embase, CINAHL, Web of Science Core Collection, Cochrane library and Medline from inception to June 2022. Two investigators independently identified, extracted data, and collected characteristics and methodology of the studies. Factors were analyzed with Nvivo12, and the theoretical domain framework was mapped to the theoretical domain. Then the secondary node was generalized by theme analysis. Finally, the specific influencing factors were summarized and analyzed.RESULTS:Thirty-four studies were included for analysis. A total of 194 factors were mapped to 13 theoretical domains, and 31 secondary nodes were summarized. Theoretical domains environmental context and resources, social/professional role and identity, and beliefs about consequences were the most common factors. Knowledge, age, self-efficacy, disease stage, social support, gender, economic status and physical status were the most influential factors for self-management in cancer patients.CONCLUSIONS:The influencing factors of self-management of cancer patients involve most of the theoretical domains, are intersectional, multi-source and complex.

BackgroundMetabolic syndrome (MetS) is a common public health challenge. Health-promoting behaviors such as diet and physical activity are central to preventing and controlling MetS. However, the adoption of diet and physical activity behaviors has always been challenging. An individualized mobile health (mHealth)–based intervention using the Behavior Change Wheel is promising in promoting health behavior change and reducing atherosclerotic cardiovascular disease (ASCVD) risk. However, the effects of this intervention are not well understood among people with MetS in mainland China. ObjectiveWe aimed to evaluate the effects of the individualized mHealth-based intervention using the Behavior Change Wheel on behavior change and ASCVD risk in people with MetS. MethodsWe conducted a quasi-experimental, nonrandomized study. Individuals with MetS were recruited from the health promotion center of a tertiary hospital in Zhejiang province, China. The study involved 138 adults with MetS, comprising a control group of 69 participants and an intervention group of 69 participants. All participants received health education regarding diet and physical activity. The intervention group additionally received a 12-week individualized intervention through a WeChat mini program and a telephone follow-up in the sixth week of the intervention. Primary outcomes included diet, physical activity behaviors, and ASCVD risk. Secondary outcomes included diet self-efficacy, physical activity self-efficacy, knowledge of MetS, quality of life, and the quality and efficiency of health management services. The Mann-Whitney U test and Wilcoxon signed rank test were primarily used for data analysis. Data analysis was conducted based on the intention-to-treat principle using SPSS (version 25.0; IBM Corp). ResultsBaseline characteristics did not differ between the 2 groups. Compared with the control group, participants in the intervention group showed statistically significant improvements in diet behavior, physical activity behavior, diet self-efficacy, physical activity self-efficacy, knowledge of MetS, physical health, and mental health after a 12-week intervention (P=.04, P=.001, P=.04, P=.04, P=.001, P=.04, P=.04, and P<.05). The intervention group demonstrated a statistically significant improvement in outcomes from pre- to postintervention evaluations (P<.001, P=.03, P<.001, P=.04, P<.001, P<.001, and P<.001). The intervention also led to enhanced health management services and quality. ConclusionsThe individualized mHealth-based intervention using the Behavior Change Wheel was effective in promoting diet and physical activity behaviors in patients with MetS. Nurses and other health care professionals may incorporate the intervention into their health promotion programs.

BACKGROUND Metabolic Syndrome (MetS) is a serious public health issue. Dietary changes form the core of MetS treatment. The adherence to dietary recommendations is critical for reducing the severity of MetS components and preventing complications. However, the adherence to dietary recommendations was not adequate among adults with MetS. This study utilizes the Behaviour Change Wheel (BCW) to develop an individualized WeChat mini program-based behavioural change intervention aimed at strengthening adherence to dietary recommendations in people with MetS. METHODS The BCW theory was used to design an individualized WeChat mini program-based behavioural change intervention. A descriptive qualitative study was conducted to identify the determinants of adherence to dietary recommendations in individuals with MetS. The study was conducted at the health promotion centre of a prominent general university hospital in Zhejiang, China. Subsequently, the intervention functions (IFs) and policy categories were selected following the identified determinants. Afterwards, behaviour change techniques (BCTs) were chosen to translate into potential intervention strategies, and the delivery mode was determined. RESULTS Our study identified fifteen barriers to improve the adherence to dietary recommendations in this population. These were linked with six IFs: education, training, persuasion, enablement, modelling, and environmental restructuring. Then, twelve BCTs were linked with the IFs and fifteen barriers. The delivery mode was a WeChat mini program. After these actions, an individualized WeChat mini program-based behavioural change intervention was developed to enhance adherence to dietary recommendations for individuals with MetS. CONCLUSIONS The BCW theory helped scientifically and systematically develop an individualized WeChat mini program-based behavioural change intervention for individuals with MetS. In the future, our research team will refine and upgrade the WeChat mini program and then test the usability and effectiveness of the individualized WeChat mini program-based behavioural change intervention program.