OBJECTIVE: This study aimed to investigate the intensity of needs for home health care services (HHCs) among elderly patients with chronic diseases and to identify the associated factors.
METHODS: A cross-sectional survey was conducted in Wuhou District, Chengdu, Sichuan Province, China, from April to November 2021.
METHODS: Convenient sampling was used to screen elderly patients with chronic diseases managed by Yulin Community Health Service Center. The questionnaires included general information and the Chinese version of the Community Healthy Intensity Rating Scale were completed according to patients\' conditions. The data were analyzed using descriptive statistics and binary logistic regression.
RESULTS: A total of 371 patients (10.40%) completed the survey. The mean age of the elderly patients was 84.04 years (SD = 7.07); these patients suffered from 1 to 7 kinds of chronic diseases, and the most common were hypertension (78.98%) and diabetes (40.97%). The need intensity of patients for HHCs was moderate (41.51%) or severe (58.49%). For each additional chronic disease that patients suffered from, the need intensity increases by 1.289 times (OR = 1.289; 95% CI: 1.055-1.575, p = .013); in additional, those aged more than 90 years, with a personal monthly income less than 2500 yuan ($387.00), with a poor health current status, and with only basic medical insurance presented greater need intensity (p < .05).
CONCLUSIONS: Our data analysis revealed that economic status, insurance condition, poor health status, and multiple comorbidities may be the most common factors associated with the need intensity for HHCs. These characteristics may help medical staff to identify and help those with urgent health problems.

BACKGROUND: Somatosensory game interventions have been used to rehabilitate hospitalized older adults. However, their application in prefrail older adults in the community is poorly understood, hindering the development of effective intervention strategies and exercise diversification.
OBJECTIVE: This study aimed to explore the experiences of prefrail Chinese older adults engaging in somatosensory gaming interventions and thus develop tailored intervention frameworks and support strategies.
METHODS: We conducted semistructured interviews with 12 prefrail older adults who participated in a 12-week sensory game intervention study from August to September 2022. The interviews were analyzed using Nvivo 11.0 software following Colaizzi\'s seven-step analysis method.
RESULTS: Somatosensory game intervention experiences were classified into four main themes and 11 subthemes: health intervention effects (enhanced limb muscle strength, improved reaction capacity, alleviated negative emotions), positive experiences (enhanced self-achievement, increased exercise motivation, elevated social engagement), negative experiences (frustration from unmet score expectations, initial discomfort), and intervention requirements (sustained interventions, technical support, personalized content).
CONCLUSIONS: The findings have implications for somatosensory game interventions targeting prefrail older adults in the community.

OBJECTIVE: As globalization and modernization continue to impact people\'s lives, a significant shift in lifestyle has taken place, resulting in a worldwide decrease in physical activity and an increase in unhealthy eating patterns. Physical inactivity has become the fourth leading cause of death globally. The aim of this scoping review is to analyze the concept and development of integrating physical activity into healthcare (IPAHc), based on the principles of sports and exercise medicine (SEM) and exercise is medicine (EIM).
METHODS: A systematic search was conducted of relevant published studies with full text using PubMed, Scopus, Web of Science, Academic Search Ultimate, Medline, and SPORTDiscus, via the EBSCO search platform.
UNASSIGNED: Twenty-nine studies met the inclusion criteria. The integration pathway centres around physical activity consultation and/or referral, and information technology which has been extensively utilized in IPAHc, including websites, electronic medical records, social media, wearable devices, mobile software, and referral tools. SEM and EIM face numerous implementation challenges, such as time constraints, education/training, resources, and tools.
CONCLUSIONS: The concept of IPAHc involves the integration of Physical Activity Vital Signs (PAVS) into electronic medical records to evaluate the physical activity levels of the general population. This can assist individuals in achieving fitness goals, preventing diseases, treating existing illnesses, and undergoing rehabilitation. IPAHc has been in development for many years and is now being explored in practice. Despite the widespread use of information technology in this integration process, a number of challenges still need addressing.

BACKGROUND: The study aims to validate the Whooley questions for screening postpartum depression in Chinese women in a community setting.
METHODS: The Whooley questions was translated into Chinese following Beaton\'s intercultural debugging guidelines. From December 1, 2020 to June 30, 2021, primary maternal and child health workers in Kaifu District and Changsha County in Changsha City recruited women aged 18 years or older who had recently given birth during home visits within seven days of discharge from hospital. Participants women completed the Whooley questions online and underwent a diagnostic interview for DSM-IV within 7 days of the visit. We evaluated Cronbach\'s alpha, split-half reliability, area under the ROC curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and optimal cut-off value of the Whooley questions.
RESULTS: Of the 3,004 eligible women, 1,862 completed the Whooley questions and diagnostic interviews. Sixty-two women (3.3%) were diagnosed with depressive disorders. The Cronbach\'s alpha coefficient was 0.64, the split-half reliability was 0.64. The optimal cut-off value was when at least one questions was answered \"yes\", with an AUC of 0.84 (SE=0.03, 95%CI 0.78-0.90, P<0.001), sensitivity of 0.77 (95%CI 0.65-0.87), specificity of 0.89 (95%CI 0.88-0.90), PPV of 0.20 (95%CI 0.15-0.25) and NPV of 0.99 (95%CI 0.98-1.00).
CONCLUSIONS: This study shows that the Chinese version of the Whooley questions is a reliable tool for screening postpartum depression in the community, but it may lead to many false positive cases.

The vaginal microbiome plays an essential role in the reproductive health of human females. As infertility increases worldwide, understanding the roles that the vaginal microbiome may have in infertility and in vitro fertilization (IVF) treatment outcomes is critical. To determine the vaginal microbiome composition of 1411 individuals (1255 undergoing embryo transplantation) and their associations with reproductive outcomes, clinical and biochemical features are measured, and vaginal samples are 16S rRNA sequenced. Our results suggest that both too high and too low abundance of Lactobacillus is not beneficial for pregnancy; a moderate abundance is more beneficial. A moderate abundance of Lactobacillus crispatus and Lactobacillus iners (~80%) (with a pregnancy rate of I-B: 54.35% and III-B: 57.73%) is found beneficial for pregnancy outcomes compared with a higher abundance (>90%) of Lactobacillus (I-A: 44.81% and III-A: 51.06%, respectively). The community state type (CST) IV-B (contains a high to moderate relative abundance of Gardnerella vaginalis) shows a similar pregnant ratio (48.09%) with I-A and III-A, and the pregnant women in this CST have a higher abundance of Lactobacillus species. Metagenome analysis of 71 samples shows that nonpregnant women are detected with more antibiotic-resistance genes, and Proteobacteria and Firmicutes are the main hosts. The inherent differences within and between women in different infertility groups suggest that vaginal microbes might be used to detect infertility and potentially improve IVF outcomes.

UNASSIGNED: The Sanxingdui Site in Guanghan City, Sichuan Province, China, is one of the precious heritage sites of the ancient Chinese civilization. Archaeological work at Sanxingdui is of great significance in clarifying the origins and main contents of the ancient Shu culture and the Yangtze River civilization. Since the 1920s, archaeologists have conducted extensive excavations and research at the site, with particular attention given to the large number of ivory artifacts unearthed. However, the buried ivory is influenced by soil pH, temperature, humidity, and other physical and chemical factors, along with the potential impact of microbial activities that may lead to the corrosion and decomposition of ivory. By understanding the types and activities of microorganisms, appropriate measures can be taken to protect and preserve cultural relics.
UNASSIGNED: Multi-point sampling of soil samples around the ivory of the three sacrificial pits at the Sanxingdui site was carried out, and strict aseptic operation was carried out during the sampling process. Subsequently, the microbial community structure and diversity in the buried ivory soil of Sanxingdui site were identified and analyzed by Illumina high-throughput sequencing technology.
UNASSIGNED: 16S rRNA and internal transcribed spacer sequence analysis revealed significant differences in the soil microbial community structure among different sacrificial pits. The dominant bacterial phyla were the Proteobacteria, GAL15, Actinobacteriota, Bacteroidota, and Methylomirabilota. The dominant fungal phyla were Ascomycota, Mortierellomhcota, and Basidiomycota. Most dominant bacterial and fungal communities play an indispensable role in the ivory corrosion mechanism, promoting the decay and decomposition process through various means such as decomposing organic matter and producing acidic substances.
UNASSIGNED: It is particularly important to take a series of measures to control microbial activity to effectively protect ivory. Our preliminary study of the mechanism of action of microorganisms on ivory in a buried environment provides a scientific basis to prevent and protect against microbial degradation in ancient ivory unearthed in Sanxingdui. Following the research results, suitable antibacterial agents tailored to the preservation environment and microbial characteristics of ancient ivory can be prepared. Ensure that the selected antibacterial agents meet safety and effectiveness requirements to maximize protection against microbial degradation of ancient ivory.

BACKGROUND: Sedentary behavior (SB) is deeply ingrained in the daily lives of community-dwelling older adults with type 2 diabetes mellitus (T2DM). However, the specific underlying mechanisms of the determinants associated with SB remain elusive. We aimed to explore the determinants of SB based on the behavior change wheel framework as well as a literature review.
METHODS: This cross-sectional study recruited 489 community-dwelling older adults with T2DM in Jinan City, Shandong Province, China. Convenience sampling was used to select participants from relevant communities. This study used the Measure of Older Adults\' Sedentary Time-T2DM, the Abbreviated-Neighborhood Environment Walkability Scale, the Social Support Rating Scale, the Lubben Social Network Scale 6, the Subjective Social Norms Questionnaire for Sedentary Behavior, the Functional Activities Questionnaire, the Numerical Rating Scale, the Short Physical Performance Battery, and the Montreal Cognitive Assessment Text to assess the levels of and the determinants of SB. Descriptive statistical analysis and path analysis were conducted to analyze and interpret the data.
RESULTS: Pain, cognitive function, social isolation, and social support had direct and indirect effects on SB in community-dwelling older adults with T2DM (total effects: β = 0.426, β = -0.171, β = -0.209, and β = -0.128, respectively), and physical function, walking environment, and social function had direct effects on patients\' SB (total effects: β = -0.180, β = -0.163, and β = 0.127, respectively). All the above pathways were statistically significant (P < 0.05). The path analysis showed that the model had acceptable fit indices: RMSEA = 0.014, χ 2/df = 1.100, GFI = 0.999, AGFI = 0.980, NFI = 0.997, RFI = 0.954, IFI = 1.000, TLI = 0.996, CFI = 1.000.
CONCLUSIONS: Capability (physical function, pain, and cognitive function), opportunity (social isolation, walking environment, and social support), and motivation (social function) were effective predictors of SB in community-dwelling older adults with T2DM. Deeper knowledge regarding these associations may help healthcare providers design targeted intervention strategies to decrease levels of SB in this specific population.

Objective: To investigate the risk factors for the development of mild cognitive dysfunction in hypertensive patients in the community and to develop a risk prediction model. Method: The data used in this study were obtained from two sources: the China Health and Retirement Longitudinal Study (CHARLS) and the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A total of 1121 participants from CHARLS were randomly allocated into a training set and a validation set, following a 70:30 ratio. Meanwhile, an additional 4016 participants from CLHLS were employed for external validation of the model. The patients in this study were divided into two groups: those with mild cognitive impairment and those without. General information, employment status, pension, health insurance, and presence of depressive symptoms were compared between the two groups. LASSO regression analysis was employed to identify the most predictive variables for the model, utilizing 14-fold cross-validation. The risk prediction model for cognitive impairment in hypertensive populations was developed using generalized linear models. The model\'s discriminatory power was evaluated through the area under the receiver operating characteristic (ROC) curve and calibration curves. Results: In the modeling group, eight variables such as gender, age, residence, education, alcohol use, depression, employment status, and health insurance were ultimately selected from an initial pool of 21 potential predictors to construct the risk prediction model. The area under the curve (AUC) values for the training, internal, and external validation sets were 0.777, 0.785, and 0.782, respectively. All exceeded the threshold of 0.7, suggesting that the model effectively predicts the incidence of mild cognitive dysfunction in community-based hypertensive patients. A risk prediction model was developed using a generalized linear model in conjunction with Lasso regression. The model\'s performance was evaluated using the area under the receiver operating characteristic (ROC) curve. Hosmer-Lemeshow test values yielded p = .346 and p = .626, both of which exceeded the 0.05 threshold. Calibration curves demonstrated a significant agreement between the nomogram model and observed outcomes, serving as an effective tool for evaluating the model\'s predictive performance. Discussion: The predictive model developed in this study serves as a promising and efficient tool for evaluating cognitive impairment in hypertensive patients, aiding community healthcare workers in identifying at-risk populations.

BACKGROUND: China\'s older population is facing serious health challenges, including malnutrition and multiple chronic conditions. There is a critical need for tailored food recommendation systems. Knowledge graph-based food recommendations offer considerable promise in delivering personalized nutritional support. However, the integration of disease-based nutritional principles and preference-related requirements needs to be optimized in current recommendation processes.
OBJECTIVE: This study aims to develop a knowledge graph-based personalized meal recommendation system for community-dwelling older adults and to conduct preliminary effectiveness testing.
METHODS: We developed ElCombo, a personalized meal recommendation system driven by user profiles and food knowledge graphs. User profiles were established from a survey of 96 community-dwelling older adults. Food knowledge graphs were supported by data from websites of Chinese cuisine recipes and eating history, consisting of 5 entity classes: dishes, ingredients, category of ingredients, nutrients, and diseases, along with their attributes and interrelations. A personalized meal recommendation algorithm was then developed to synthesize this information to generate packaged meals as outputs, considering disease-related nutritional constraints and personal dietary preferences. Furthermore, a validation study using a real-world data set collected from 96 community-dwelling older adults was conducted to assess ElCombo\'s effectiveness in modifying their dietary habits over a 1-month intervention, using simulated data for impact analysis.
RESULTS: Our recommendation system, ElCombo, was evaluated by comparing the dietary diversity and diet quality of its recommended meals with those of the autonomous choices of 96 eligible community-dwelling older adults. Participants were grouped based on whether they had a recorded eating history, with 34 (35%) having and 62 (65%) lacking such data. Simulation experiments based on retrospective data over a 30-day evaluation revealed that ElCombo\'s meal recommendations consistently had significantly higher diet quality and dietary diversity compared to the older adults\' own selections (P<.001). In addition, case studies of 2 older adults, 1 with and 1 without prior eating records, showcased ElCombo\'s ability to fulfill complex nutritional requirements associated with multiple morbidities, personalized to each individual\'s health profile and dietary requirements.
CONCLUSIONS: ElCombo has shown enhanced potential for improving dietary quality and diversity among community-dwelling older adults in simulation tests. The evaluation metrics suggest that the food choices supported by the personalized meal recommendation system surpass autonomous selections. Future research will focus on validating and refining ElCombo\'s performance in real-world settings, emphasizing the robust management of complex health data. The system\'s scalability and adaptability pinpoint its potential for making a meaningful impact on the nutritional health of older adults.

OBJECTIVE: The aim of the study is to develop a model using a machine learning approach that can effectively identify the quality of home care in communities.
METHODS: A cross-sectional design.
METHODS: In this study, we evaluated the quality of home care in 170 community health service centres between October 2022 and February 2023. The Home Care Service Quality Questionnaire was used to collect information on home care structure, process and outcome quality. Then, an intelligent and comprehensive evaluation model was developed using a convolutional neural network, and its performance was compared with random forest and logistic regression models through various performance indicators.
RESULTS: The convolutional neural network model was built upon seven variables, which encompassed the qualification of home nursing staff, developing and practicing emergency plan to cope with different emergency rescues in home environment, being equipped with medication and supplies for first aid according to specific situations, assessing nutrition condition of home patients, allocation of the number of home nursing staff, cases of new pressure ulcers and patient satisfaction rate. Remarkably, the convolutional neural network model demonstrated superior performance, outperforming both the random forest and regression models.
CONCLUSIONS: The successful development and application of the convolutional neural network model highlight its ability to leverage data from community health service centres for rapid and accurate grading of home care quality. This research points the way to home care quality improvement.
CONCLUSIONS: The model proposed in this study, coupled with the aforementioned factors, is expected to enhance the accuracy and efficiency of a comprehensive evaluation of home care quality. It will also help managers to take purposeful measures to improve the quality of home care.
UNASSIGNED: The reporting of this study (Observational, cross-sectional study) conforms to the STROBE statement.
UNASSIGNED: No patient or public contribution.
UNASSIGNED: The application of this model has the potential to contribute to the advancement of high-quality home care, particularly in lower-middle-income communities.