Developing indicators of age-friendly neighbourhood environments for urban and rural communities across 20 low-, middle-, and high-income countries

Background By 2050, the global population of adults 60 + will reach 2.1 billion, surging fastest in low- and middle-income countries (LMIC). In response, the World Health Organization (WHO) has developed indicators of age-friendly urban environments, but these criteria have been challenging to apply in rural areas and LMIC. This study fills this gap by adapting the WHO indicators to such settings and assessing variation in their availability by community-level urbanness and country-level income. Methods We used data from the Prospective Urban and Rural Epidemiology (PURE) study’s environmental-assessment tools, which integrated systematic social observation and ecometrics to reliably capture community-level environmental features associated with cardiovascular-disease risk factors. The results of a scoping review guided selection of 18 individual indicators across six distinct domains, with data available for 496 communities in 20 countries, including 382 communities (77%) in LMIC. Finally, we used both factor analysis of mixed data (FAMD) and multitrait-multimethod (MTMM) approaches to describe relationships between indicators and domains, as well as detailing the extent to which these relationships held true within groups defined by urbanness and income. Results Together, the results of the FAMD and MTMM approaches indicated substantial variation in the relationship of individual indicators to each other and to broader domains, arguing against the development of an overall score and extending prior evidence demonstrating the need to adapt the WHO framework to the local context. Communities in high-income countries generally ranked higher across the set of indicators, but regular connections to neighbouring towns via bus (95%) and train access (76%) were most common in low-income countries. The greatest amount of variation by urbanness was seen in the number of streetscape-greenery elements (33 such elements in rural areas vs. 55 in urban), presence of traffic lights (18% vs. 67%), and home-internet availability (25% vs. 54%). Conclusions This study indicates the extent to which environmental supports for healthy ageing may be less readily available to older adults residing in rural areas and LMIC and augments calls to tailor WHO’s existing indicators to a broader range of communities in order to achieve a critical aspect of distributional equity in an ageing world.

Multi-label feature selection based on fuzzy neighborhood rough sets

Multi-label feature selection, a crucial preprocessing step for multi-label classification, has been widely applied to data mining, artificial intelligence and other fields. However, most of the existing multi-label feature selection methods for dealing with mixed data have the following problems: (1) These methods rarely consider the importance of features from multiple perspectives, which analyzes features not comprehensive enough. (2) These methods select feature subsets according to the positive region, while ignoring the uncertainty implied by the upper approximation. To address these problems, a multi-label feature selection method based on fuzzy neighborhood rough set is developed in this article. First, the fuzzy neighborhood approximation accuracy and fuzzy decision are defined in the fuzzy neighborhood rough set model, and a new multi-label fuzzy neighborhood conditional entropy is designed. Second, a mixed measure is proposed by combining the fuzzy neighborhood conditional entropy from information view with the approximate accuracy of fuzzy neighborhood from algebra view, to evaluate the importance of features from different views. Finally, a forward multi-label feature selection algorithm is proposed for removing redundant features and decrease the complexity of multi-label classification. The experimental results illustrate the validity and stability of the proposed algorithm in multi-label fuzzy neighborhood decision systems, when compared with related methods on ten multi-label datasets.

Economic Policy Uncertainty and Conditional Dependence between China and U.S. Stock Markets

In this paper, we investigate the impact of economic policy uncertainty (EPU) on the conditional dependence between China and U.S. stock markets by employing the Copula-mixed-data sampling (Copula-MIDAS) framework. In the case of EPU, we consider the global EPU (GEPU), the American EPU (AEPU), and the China EPU (CEPU). The empirical analysis based on the Shanghai Stock Exchange Composite (SSEC) index in China and the S&P 500 index in the U.S. shows that the tail dependence between China and U.S. stock markets is symmetrical, and the t Copula outperforms alternative Copulas in terms of in-sample goodness of fit. In particular, we find that the t Copula-MIDAS model with EPU dominates the traditional time-varying t Copula in terms of in-sample fitting. Moreover, we observe that both the GEPU and AEPU have a significantly positive impact on the conditional dependence between China and U.S. stock markets, whereas CEPU has no significant impact. The tail dependence between China and U.S. stock markets exhibits an increasing trend, particularly in the recent years.

Raking and Relabeling for Imbalanced Data

<div>We consider the binary classification of imbalanced data. A dataset is imbalanced if the proportion of classes are heavily skewed. Imbalanced data classification is often challengeable, especially for high-dimensional data, because unequal classes deteriorate classifier performance. Under sampling the majority class or oversampling the minority class are popular methods to construct balanced samples, facilitating classification performance improvement. However, many existing sampling methods cannot be easily extended to high-dimensional data and mixed data, including categorical variables, because they often require approximating the attribute distributions, which becomes another critical issue. In this paper, we propose a new sampling strategy employing raking and relabeling procedures, such that the attribute values of the majority class are imputed for the values of the minority class in the construction of balanced samples. The proposed algorithms produce comparable performance as existing popular methods but are more flexible regarding the data shape and attribute size. The sampling algorithm is attractive in practice, considering that it does not require density estimation for synthetic data generation in oversampling and is not bothered by mixed-type variables. In addition, the proposed sampling strategy is robust to classifiers in the sense that classification performance is not sensitive to choosing the classifiers.</div>

Raking and Relabeling for Imbalanced Data

<div>We consider the binary classification of imbalanced data. A dataset is imbalanced if the proportion of classes are heavily skewed. Imbalanced data classification is often challengeable, especially for high-dimensional data, because unequal classes deteriorate classifier performance. Under sampling the majority class or oversampling the minority class are popular methods to construct balanced samples, facilitating classification performance improvement. However, many existing sampling methods cannot be easily extended to high-dimensional data and mixed data, including categorical variables, because they often require approximating the attribute distributions, which becomes another critical issue. In this paper, we propose a new sampling strategy employing raking and relabeling procedures, such that the attribute values of the majority class are imputed for the values of the minority class in the construction of balanced samples. The proposed algorithms produce comparable performance as existing popular methods but are more flexible regarding the data shape and attribute size. The sampling algorithm is attractive in practice, considering that it does not require density estimation for synthetic data generation in oversampling and is not bothered by mixed-type variables. In addition, the proposed sampling strategy is robust to classifiers in the sense that classification performance is not sensitive to choosing the classifiers.</div>

Possibilities of receptive music therapy (RMT) for mothers raising children with developmental disorders as a self-help tool for overcoming stress during the COVID-19 pandemic

After the announcement of quarantine due to Covid-19 on March 16, 2020, parents of children with disabilities were left without help from educational and health professionals, while changes in routine, work and financial restrictions, isolation, exacerbations of children’s mental disorders increased the level of parental anxiety, tension, fear and anger. Research on music therapy conducted by the world scientists demonstrated the effectiveness of applying receptive music therapy (RMT) methods to cope with stress, when listening to music is used as a tool that can change the client’s state and help to reveal one’s experiences. The aim of the article is to reveal, theoretically and empirically, possibilities of remote application of receptive music therapy for mothers raising children with developmental disorders. Tasks: 1) to present a model of remote application of receptive music therapy for coping with stress; 2) to examine the possibilities of independent application of the developed therapeutic instrument for client’s self-help. Problem question: how can mothers use the therapeutic tool and skills acquired during the receptive music therapy on their own during the Covid-19 quarantine? The mixed data collection methodology was chosen for the research: 1) in-depth, semi-structured interview (content analysis method); 2) Perceived Stress Scale (PSS) questionnaire; 3) Musical Life Panorama (MLP) biographical interview; 4) Audio recordings of music therapy sessions – qualitative narrative analysis; 5) Music Listening Diary (MLD). Fours subjects were selected on a voluntary participatory basis by forming a homogenous group according to a similar experience of raising children with disabilities. The research revealed that remote application of RMT improved the study participants’ ability to recognize stressful situations better, feelings, and reactions arising during them, and helped them to understand their emotions better. The clients learned to apply the therapeutic instrument independently in order to relieve a stressful situation, adverse reactions, or the emerging emotions. With the formation of the habit of listening to music more often, not only did the ability to relax, not get upset, calm down was strengthened, but tension decreased and the general emotional background in the family improved. The application of RMT increased clients’ ability to cope with stress and reduced the risk of recurring stressful situations. Study participants confirmed the suitability of RMT both in remote sessions and in self-application of the instrument for self-help after the therapy during the COVID-19 quarantine.

Disparities in ACL Reconstruction: the Influence of Gender and Race on Incidence, Treatment, and Outcomes

Purpose of Review Anterior cruciate ligament (ACL) rupture is a common injury that has important clinical and economic implications. We aimed to review the literature to identify gender, racial and ethnic disparities in incidence, treatment, and outcomes of ACL injury. Recent Findings Females are at increased risk for ACL injury compared to males. Intrinsic differences such as increased quadriceps angle and increased posterior tibial slope may be contributing factors. Despite lower rates of injury, males undergo ACL reconstruction (ACLR) more frequently. There is conflicting evidence regarding gender differences in graft failure and ACL revision rates, but males demonstrate higher return to sport (RTS) rates. Females report worse functional outcome scores and have worse biomechanical metrics following ACLR. Direct evidence of racial and ethnic disparities is limited, but present. White athletes have greater risk of ACL injury compared to Black athletes. Non-White and Spanish-speaking patients are less likely to undergo ACLR after ACL tear. Black and Hispanic youth have greater surgical delay to ACLR, increased risk for loss to clinical follow-up, and less physical therapy sessions, thereby leading to greater deficits in knee extensor strength during rehabilitation. Hispanic and Black patients also have greater risk for hospital admission after ACLR, though this disparity is improving. Summary Females have higher rates of ACL injury with inconclusive evidence on anatomic predisposition and ACL failure rate differences between genders. Recent literature has suggested inferior RTS and functional outcomes following ACLR in females. Though there is limited and mixed data on incidence and outcome differences between races and ethnic groups, recent studies suggest there may be disparities in those who undergo ACLR and time to treatment.

Integration of Arts and Health Sciences in Developing an Opera on Veteran Resilience and Recovery

There is an emerging literature on research interviews to inform arts projects, but little on opera. This case study illustrates how research data informed an opera on Veteran recovery. Deidentified interviews were selected from 280 adults with a history of depression at 10-year follow-up to a randomized trial. Interviews were used to inform characters, storyline, and libretto. Ethical strategies included: changing details and merging stories and characters to create two Veterans and one spouse as leads, a storyline, and choral passages, with a focus on recovery from post-traumatic stress and homelessness. To engage a broad audience and address stigma, accessible composition techniques (melody, harmony) were used. We found that qualitative/mixed data can inform libretto and composition for an opera on Veteran recovery, through integrating art and health science.

Customized Fiber Post Improves the Bond Strength and Dentinal Penetrability of Resin Cementation System to Root Dentin

SUMMARY Objective: This study aimed to evaluate the effect of fiber post customization on the bond strength (24 hours and 6 months), resin cement thickness, and dentinal penetrability of Adper Scotchbond Multi-Purpose – RelyX ARC (AS-RA), RelyX U200 (R2), and Scotchbond Universal – RelyX Ultimate (SU-RU) cementation systems to root dentin from the cervical-, middle-, and apical-thirds of the post space. Methods: One hundred twenty bovine incisors were endodontically treated. After post space preparation, the roots were divided into six groups, according to the luting protocols (AS–RA, R2, SU– RU) and the type of fiber post [noncustomized post (NC) and customized post (C)]. Customization procedures were peformed using a resin composite (Z350 XT). 24 hours (n=60) or 6 months later (n=60), specimens from the cervical-, middle-, and apical-thirds of the post space were submitted to cementation system thickness measurement, bond strength evaluation, and dentinal penetrability analysis with Confocal Laser Scanning Microscopy (CLSM). Failure mode was classified as adhesive, cohesive, or mixed. Data were submitted to ANOVA and Tukey tests (α=0.05). Results: Cementation protocols with customized fiber posts presented the lowest cementation system thickness, regardless of the cementation system or post space-third (p&lt;0.05), and the highest bond strength values (p&lt;0.05), regardless of the third space (p&gt;0.05), for both periods (24 hours or 6 months). The comparison of push-out bond strength values between 24 hours and 6 months showed a reduction in all groups for the cervical-third (p&lt;0.05). For the middle-third, only noncustomized groups showed reduction (p&lt;0.05). For the apical-third, no reduction was observed (p&gt;0.05). Conclusions: Anatomical customization favored both the bond strength of cements to dentin and the dentinal penetrability, but with lower cementation system thickness, regardless of cement composition and adhesive strategy.