Background: Dance interventions are considered beneficial for older patients with mild cognitive impairment in many aspects. We conducted a comprehensive systematic review and meta-analysis to assess the effects of dance on different aspects (cognitive function, emotions, physical function, and quality of life) of this population.Methods: A systematic search of PubMed, Web of Science, the Cochrane Central Register of Controlled Trials, Embase, American Psychological Association PsycInfo, ProQuest, Scopus, Cumulative Index to Nursing and Allied Health Literature, the Chinese BioMedical Literature Database, the VIP Database for Chinese Technical Periodicals, China National Knowledge Infrastructure, and Wanfang Data database was performed. Two reviewers independently assessed the study quality.Results: Fourteen studies were retrieved from the databases for analysis. The pooled results showed that dance interventions significantly improved global cognition (standardized mean difference [SMD] = 0.73, 95% confidence interval [CI]: 0.47 to 0.99, P < 0.00001), rote memory (mean difference [MD] = −2.12, 95% CI: −4.02 to −0.21, P = 0.03), immediate recall (SMD = 0.54, 95% CI: 0.30 to 0.78, P < 0.0001), delayed recall (SMD = 0.56, 95% CI: 0.26 to 0.86, P = 0.0002) and attention (SMD = 0.38, 95% CI: 0.13 to 0.64, P = 0.003). No significant improvement was found in executive function, language, depression, anxiety, dementia-related behavioral symptoms, motor function, and quality of life.Conclusion: Dance interventions benefit most aspects of cognitive functions. The evidence for the effects of dance on psycho-behavioral symptoms, motor function and quality of life remains unclear. More trials with rigorous study designs are necessary to provide this evidence.

Objectives To examine the diagnostic performance of the Tilburg Frailty Indicator (TFI), 11-factor modified frailty index (mFI-11), and 5-factor modified frailty index (mFI-5) for frailty defined by Frailty Phenotype (FP), as well as to compare the predictive ability of TFI, mFI-11, and mFI-5 for adverse outcomes in hospital among elderly patients undergoing gastric cancer surgery. Design A prospective cohort study. Setting Hospitalization setting, Nanjing, China. Participants We recruited 259 elderly patients undergoing gastric cancer surgery from a tertiary hospital. Measurements Frailty was assessed by the FP, TFI, mFI-11, and mFI-5 before surgery, respectively. The receiver operating characteristic (ROC) curves were plotted to compared the diagnostic performance of TFI, mFI-11, and mFI-5 using FP as the reference. ROC curves were used to examine the performance of TFI, mFI-11, and mFI-5 in predicting adverse outcomes. The area under the curve (AUC)>0.70 was regarded as an indicator of good performance. Results The prevalence of frailty ranged from 8.5% (mFI-11) to 45.9% (TFI). The AUCs of TFI (AUC: 0.764, p<0.001) was significantly greater than that of mFI-11 (AUC: 0.600, p=0.033) and mFI-5 (AUC: 0.600, p=0.0311) in the detection of frailty defined by FP, with quite different sensitivity and specificity at their original cutoffs. TFI and mFI-11 both had statistically significant but similarly inadequate predictive accuracy for adverse outcomes in hospital, including total complications (AUCs: 0.618; 0.621), PLOS (AUCs: 0.593; 0.639), increased hospital costs (AUCs: 0.594; 0.624), and hypoproteinemia (AUCs: 0.573; 0.600). For the mFI-5, only the predictive ability for hypoproteinemia was statistically significant, with poor accuracy (AUC: 0.592, p<0.0055). Conclusion The TFI performed slightly better than mFI-11 and mFI-5 in our study. Moreover, future studies are needed to further determine an optimal frailty instrument with great diagnostic and predictive accuracy.

Background: Cancer has emerged as a considerable global health concern, contributing substantially to both morbidity and mortality. Recognizing the urgent need to enhance the overall well-being and quality of life (QOL) of cancer patients, a growing number of researchers have started using online mindfulness-based interventions (MBIs) in oncology. However, the effectiveness and optimal implementation methods of these interventions remain unknown. Objective: This study evaluates the effectiveness of online MBIs, encompassing both app- and website-based MBIs, for patients with cancer and provides insights into the potential implementation and sustainability of these interventions in real-world settings. Methods: Searches were conducted across 8 electronic databases, including the Cochrane Library, Web of Science, PubMed, Embase, SinoMed, CINAHL Complete, Scopus, and PsycINFO, until December 30, 2022. Randomized controlled trials involving cancer patients aged ≥18 years and using app- and website-based MBIs compared to standard care were included. Nonrandomized studies, interventions targeting health professionals or caregivers, and studies lacking sufficient data were excluded. Two independent authors screened articles, extracted data using standardized forms, and assessed the risk of bias in the studies using the Cochrane Bias Risk Assessment Tool. Meta-analyses were performed using Review Manager (version 5.4; The Cochrane Collaboration) and the meta package in R (R Foundation for Statistical Computing). Standardized mean differences (SMDs) were used to determine the effects of interventions. The Reach, Effectiveness, Adoption, Implementation, and Maintenance framework was used to assess the potential implementation and sustainability of these interventions in real-world settings. Results: Among 4349 articles screened, 15 (0.34%) were included. The total population comprised 1613 participants, of which 870 (53.9%) were in the experimental conditions and 743 (46.1%) were in the control conditions. The results of the meta-analysis showed that compared with the control group, the QOL (SMD 0.37, 95% CI 0.18-0.57; P<.001), sleep (SMD −0.36, 95% CI −0.71 to −0.01; P=.04), anxiety (SMD −0.48, 95% CI −0.75 to −0.20; P<.001), depression (SMD −0.36, 95% CI −0.61 to −0.11; P=.005), distress (SMD −0.50, 95% CI −0.75 to −0.26; P<.001), and perceived stress (SMD −0.89, 95% CI −1.33 to −0.45; P=.003) of the app- and website-based MBIs group in patients with cancer was significantly alleviated after the intervention. However, no significant differences were found in the fear of cancer recurrence (SMD −0.30, 95% CI −1.04 to 0.44; P=.39) and posttraumatic growth (SMD 0.08, 95% CI −0.26 to 0.42; P=.66). Most interventions were multicomponent, website-based health self-management programs, widely used by international and multilingual patients with cancer. Conclusions: App- and website-based MBIs show promise for improving mental health and QOL outcomes in patients with cancer, and further research is needed to optimize and customize these interventions for individual physical and mental symptoms. Trial Registration: PROSPERO CRD42022382219; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=382219

Palliative care is essential for enhancing quality of life in patients with life-threatening illnesses. However, its accessibility remains inconsistent across populations and regions. This review systematically examines and quantifies factors influencing accessibility of palliative care. We conducted a comprehensive literature search in PubMed, Web of Science, CINAHL, Embase, the Cochrane Library, CNKI, Wanfang, and VIP databases, covering the period from January 2014 to July 2024. The search aimed to identify observational studies on factors influencing accessibility of palliative care. Keywords related to accessibility were derived from the five dimensions defined by Penchansky and Thomas: availability, accessibility, accommodation, affordability, and acceptability. Study quality was assessed using the Joanna Briggs Institute (JBI) tools, and a meta-analysis was conducted using Review Manager 5.3. A total of 20 studies were included in the analysis, with 15 using a retrospective design with secondary data analysis, two employing a cross-sectional design, and three using a cohort design. There were no studies on availability, one study on accessibility, two studies on affordability, one study on accommodation, and sixteen studies on acceptability. The influencing factor for accessibility is geographic location. The influencing factors for affordability and accommodation are mainly demographic characteristics, including race, religion, and employment status. The most influential factors for acceptability are categorized as sociodemographic, healthcare service, disease-related factors. Meta-analysis results indicated that female gender (OR = 1.18, 95% CI: 1.14–1.23), higher income level (OR = 1.11, 95% CI: 1.08–1.14), and larger hospital bed capacity (OR = 1.22, 95% CI: 1.14–1.32) facilitated accessibility to palliative care (P < 0.05). Conversely, residing in rural areas (OR = 0.80, 95% CI: 0.67–0.95) and being of African descent (OR = 0.78, 95% CI: 0.68–0.90) were barriers to accessibility (P < 0.05). This review highlights a relationship between key sociodemographic characteristics, healthcare service, disease-related factors and the accessibility of palliative care. However, the limited number of studies focusing on specific dimensions, such as availability, affordability, accessibility, and accommodation, creates gaps in understanding. Further research is needed to clarify the underlying mechanisms and potential causality of these associations. Recognizing the significant implications of limited accessibility of palliative care can help identify underserved populations and develop targeted interventions to improve the access to the service for these groups. • Adopting a Comprehensive Framework to Evaluate Accessibility of Palliative Care: This study applies the Healthcare Supply-Demand Adaptation Model by Penchansky and Thomas. It considers five dimensions of accessibility: availability, accessibility, affordability, acceptability, and accommodation. This approach provides a holistic view of palliative care access. • Exploring Barriers and Facilitators to Accessibility of Palliative Care: Key facilitators of palliative care accessibility include female gender, higher income, and larger hospital bed capacity. Barriers include rural residency and African descent. These findings offer new insights into accessibility patterns. • Detecting Imbalance in the Number of Studies Across Five Dimensions: Acceptability is the most frequently discussed dimension in the literature. However, other dimensions, such as availability, affordability, accessibility, and accommodation, remain underexplored. This imbalance highlights an important gap in current research and emphasizes the need for deeper investigation into these underrepresented areas. • Conducting Multi-Level Analysis of Influencing Factors: This study integrates meso-level factors, such as healthcare institutions, and micro-level factors, such as sociodemographic and cultural influences. This approach provides a more nuanced understanding of palliative care accessibility, addressing both systemic and individual barriers