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Over the past decade, wearable sensors for fall detection have gained significant attention due to their potential in improving the safety of elderly users and reducing fall-related injuries. This review employs a network-based visualization approach to analyze research trends, key technologies, and collaborative networks. Using studies from SCI- and SSCI-indexed journals from 2015 to 2024, we analyzed 582 articles and 65 reviews with CiteSpace, revealing a significant rise in research on wearable sensors for fall detection. Additionally, we reviewed various datasets and machine learning techniques, from traditional methods to advanced deep learning frameworks, which demonstrate high accuracies, F1 scores, sensitivities, and specificities in controlled settings. This review provides a comprehensive overview of the progress and emerging trends, offering a foundation for future advancements in wearable fall detection systems.

Background The global population of adults aged 60 and above surpassed 1 billion in 2020, constituting 13.5% of the global populace. Projections indicate a rise to 2.1 billion by 2050. While Hospital-at-Home (HaH) programs have emerged as a promising alternative to traditional routine hospital care, showing initial benefits in metrics such as lower mortality rates, reduced readmission rates, shorter treatment durations, and improved mental and functional status among older individuals, the robustness and magnitude of these effects relative to conventional hospital settings call for further validation through a comprehensive meta-analysis. Methods A comprehensive literature search was executed during April–June 2023, across PubMed, MEDLINE, Embase, Web of Science, and Cumulative Index of Nursing and Allied Health Literature (CINAHL) to include both RCT and non-RCT HaH studies. Statistical analyses were conducted using Review Manager (version 5.4), with Forest plots and I 2 statistics employed to detect inter-study heterogeneity. For I 2  > 50%, indicative of substantial heterogeneity among the included studies, we employed the random-effects model to account for the variability. For I 2  ≤ 50%, we used the fixed effects model. Subgroup analyses were conducted in patients with different health conditions, including cancer, acute medical conditions, chronic medical conditions, orthopedic issues, and medically complex conditions. Results Fifteen trials were included in this systematic review, including 7 RCTs and 8 non-RCTs. Outcome measures include mortality, readmission rates, treatment duration, functional status (measured by the Barthel index), and mental status (measured by MMSE). Results suggest that early discharge HaH is linked to decreased mortality, albeit supported by low-certainty evidence across 13 studies. It also shortens the length of treatment, corroborated by seven trials. However, its impact on readmission rates and mental status remains inconclusive, supported by nine and two trials respectively. Functional status, gauged by the Barthel index, indicated potential decline with early discharge HaH, according to four trials. Subgroup analyses reveal similar trends. Conclusions While early discharge HaH shows promise in specific metrics like mortality and treatment duration, its utility is ambiguous in the contexts of readmission, mental status, and functional status, necessitating cautious interpretation of findings.

Due to their accessibility and anonymity, web-based counseling services are expanding at an unprecedented rate. One of the most prominent challenges such services face is repeated users, who represent a small fraction of total users but consume significant resources by continually returning to the system and reiterating the same narrative and issues. A deeper understanding of repeated users and tailoring interventions may help improve service efficiency and effectiveness. Previous studies on repeated users were mainly on telephone counseling, and the classification of repeated users tended to be arbitrary and failed to capture the heterogeneity in this group of users. In this study, we aimed to develop a systematic method to profile repeated users and to understand what drives their use of the service. By doing so, we aimed to provide insight and practical implications that can inform the provision of service catering to different types of users and improve service effectiveness. We extracted session data from 29,400 users from a free 24/7 web-based counseling service from 2018 to 2021. To systematically investigate the heterogeneity of repeated users, hierarchical clustering was used to classify the users based on 3 indicators of service use behaviors, including the duration of their user journey, use frequency, and intensity. We then compared the psychological profile of the identified subgroups including their suicide risks and primary concerns to gain insights into the factors driving their patterns of service use. Three clusters of repeated users with clear psychological profiles were detected: episodic, intermittent, and persistent-intensive users. Generally, compared with one-time users, repeated users showed higher suicide risks and more complicated backgrounds, including more severe presenting issues such as suicide or self-harm, bullying, and addictive behaviors. Higher frequency and intensity of service use were also associated with elevated suicide risk levels and a higher proportion of users citing mental disorders as their primary concerns. This study presents a systematic method of identifying and classifying repeated users in web-based counseling services. The proposed bottom-up clustering method identified 3 subgroups of repeated users with distinct service behaviors and psychological profiles. The findings can facilitate frontline personnel in delivering more efficient interventions and the proposed method can also be meaningful to a wider range of services in improving service provision, resource allocation, and service effectiveness.

Chronic ultraviolet (UV) exposure is the primary cause of skin photoaging, leading to wrinkles, pigmentation changes, and loss of dermal elasticity. This systematic review and network meta-analysis evaluated the efficacy and safety of topical compounds for treating skin photoaging. A comprehensive search identified 23 RCTs with 3905 participants, comparing anti-aging agents. Bayesian network meta-analysis showed isotretinoin, retinol, and tretinoin significantly improved fine wrinkles, with isotretinoin ranked highest. Tazarotene was most effective for coarse wrinkles, while glycolic acid reduced roughness. Tretinoin and retinol were superior for hyperpigmentation. Safety analysis indicated tretinoin had the most favorable profile, whereas tazarotene and glycolic acid had higher adverse event risks. Isotretinoin and tretinoin emerged as the most balanced treatments across efficacy and safety. These findings provide evidence-based guidance for clinical decision-making in anti-photoaging therapy and underscore the potential for these agents to be integrated into routine dermatologic practice, particularly for patients seeking effective and well-tolerated topical interventions. However, limitations included limited racial diversity, potential commercial bias, and variability in dermatological assessments. These findings provide evidence-based guidance for clinical decision-making in anti-photoaging therapy.

Large-scale daily commuting data were combined with detailed geographical information system (GIS) data to analyze the loss of transport efficiency caused by drivers' uncoordinated routing in urban road networks. We used Price of Anarchy (POA) to quantify the loss of transport efficiency and found that both volume and distribution of human mobility demand determine the POA. In order to reduce POA, a small number of highways require considerable decreases in traffic, and their neighboring arterial roads need to attract more traffic. The magnitude of the adjustment in traffic flow can be estimated using the fundamental measure traffic flow only, which is widely available and easy to collect. Surprisingly, the most congested roads or the roads with largest traffic flow were not those requiring the most reduction of traffic. This study can offer guidance for the optimal control of urban traffic and facilitate improvements in the efficiency of transport networks.

Background In psychological services, the transition to the disclosure of ideation about self-harm and suicide (ISS) is a critical point warranting attention. This study developed and tested a succinct descriptor to predict such transitions in an online synchronous text-based counseling service. Method We analyzed two years’ worth of counseling sessions ( N  = 49,770) from Open Up, a 24/7 service in Hong Kong. Sessions from Year 1 ( N  = 20,618) were used to construct a word affinity network (WAN), which depicts the semantic relationships between words. Sessions from Year 2 ( N  = 29,152), including 1168 with explicit ISS, were used to train and test the downstream ISS prediction model. We divided and classified these sessions into ISS blocks (ISSBs), blocks prior to ISSBs (PISSBs), and non-ISS blocks (NISSBs). To detect PISSB, we adopted complex network approaches to examine the distance among different types of blocks in WAN. Results Our analyses find that words within a block tend to form a module in WAN and that network-based distance between modules is a reliable indicator of PISSB. The proposed model yields a c-statistic of 0.79 in identifying PISSB. Conclusions This simple yet robust network-based model could accurately predict the transition point of suicidal ideation prior to its explicit disclosure. It can potentially improve the preparedness and efficiency of help-providers in text-based counseling services for mitigating self-harm and suicide. Plain language summary In online counseling, the help-provider can often be engaging with several service users simultaneously. Therefore, new tools that could help to alert and assist the help-provider and increase their preparedness for getting further help for service users could be useful. In this study, we developed and tested a new tool that is designed to alert help-providers to the disclosure of self-harm and suicidal thoughts, based on the words that the service user has been typing. The tool is developed on the basis that word usage may have a specific pattern when suicidal thoughts are more likely to occur. We tested our tool using two years’ worth of online counseling conversations and we show that our approach can help to predict the confession of suicidal thoughts. As such, we are taking a step forward in helping to improve these counseling services. Xu et al. develop a model that predicts the disclosure of self-harm and suicide ideation based on data from text-based counselling services. This model could potentially improve the preparedness of crisis workers.

Men who have sex with men (MSM) make up the majority of new human immunodeficiency virus (HIV) diagnoses among young people in China. Understanding HIV transmission dynamics among the MSM population is, therefore, crucial for the control and prevention of HIV infections, especially for some newly reported genotypes of HIV. This study presents a metapopulation model considering the impact of pre-exposure prophylaxis (PrEP) to investigate the geographical spread of a hypothetically new genotype of HIV among MSM in Guangdong, China. We use multiple data sources to construct this model to characterize the behavioural dynamics underlying the spread of HIV within and between 21 prefecture-level cities (i.e. Guangzhou, Shenzhen, Foshan, etc.) in Guangdong province: the online social network via a gay social networking app, the offline human mobility network via the Baidu mobility website, and self-reported sexual behaviours among MSM. Results show that PrEP initiation exponentially delays the occurrence of the virus for the rest of the cities transmitted from the initial outbreak city; hubs on the movement network, such as Guangzhou, Shenzhen, and Foshan are at a higher risk of ‘earliest’ exposure to the new HIV genotype; most cities acquire the virus directly from the initial outbreak city while others acquire the virus from cities that are not initial outbreak locations and have relatively high betweenness centralities, such as Guangzhou, Shenzhen and Shantou. This study provides insights in predicting the geographical spread of a new genotype of HIV among an MSM population from different regions and assessing the importance of prefecture-level cities in the control and prevention of HIV in Guangdong province. This article is part of the theme issue ‘Data science approach to infectious disease surveillance’.

PurposeThe risk of death from suicide after self-poisoning has been known to be significantly higher as compared to the general population. Nevertheless, the change in suicide risk before and after self-poisoning is still unclear.MethodsThe database of territory-wide medical records collected by the Hospital Authority of Hong Kong was used to identify inpatients who have survived the first-ever self-poisoning but died by suicide between January 1, 2001, and December 31, 2010. A self-controlled case series (“SCCS”) design controlling for time-invariant patient confounders was used to explore the temporal change in suicide risk after the first self-poisoning episode.ResultsDuring the study period, 227 people in the database died from suicide after surviving one episode of self-poisoning. A significant increase of the risk of suicide in the first 12 months after the first lifetime self-poisoning—Risk Ratio (“RR”) 2.88 (95% CI 1.74–4.76)—was detected. The RR gradually returned to baseline levels after the second post-poisoning period.ConclusionBy within-person comparison, the net increase of the suicide risk caused by the first self-poisoning was quantitatively modeled, demonstrating that the first lifetime self-poisoning event itself is a modifiable risk factor of subsequent suicide death.

We present the opportunities and challenges of Open Up, a free, 24/7 online text-based counselling service to support youth in Hong Kong. The number of youths served more than doubled within the first three years since its inception in 2018 in response to increasing youth suicidality and mental health needs. Good practice models are being developed in order to sustain and further scale up the service. We discuss the structure of the operation, usage pattern and its effectiveness, the use of AI to improve users experience, and the role of volunteer in the operation. We also present the challenges in further enhancing the operation, calling for more research, especially on the identification of the optimal number of users that can be concurrently served by a counsellor, the effective approach to respond to a small percentage of repeated users who has taken up a disproportional volume of service, and the way to optimize the use of big data analytics and AI technology to enhance the service. These advancements will benefit not only Open Up but also similar services across the globe.

[Objective] To develop standardized cultivation technique for Saussurea lappa by covering plastic mulch in Lijiang Prefecture of Yunnan Provience. [Method] The standardized cultivation technique for S. lappa by covering plastic mulch in whole growth period was summarized on the basis of several years trial research. The reasons for increase in yied of S. lappa by covering plastic mulch were also discussed simultaneously. [ Results] Through the cultivation technique for S. lappa by covering plastic mulch, the germination percentage was more than 90% , the length of biennial taproot was 20.36 -42.71 cm and the maximum diameter was 3. 37 -5.40 cm, the drying rate was 31. 60% -34.74% and the production peak was 10 032 kg/hm ; the sulphated ash weight was less than 4% ; the acid insoluble ash weight was less than 2% . [ Conclusions] The standardized cultivation for S. lappa on the production in Yunnan could be realized by this technique, the industrial development of S. lappa in Yunnan would also be promoted in Lijiang and its circumjacent areas. [PUBLICATION ABSTRACT]