Tag: pubmed

Soc Work Public Health. 2022 Aug 31:1-12. doi: 10.1080/19371918.2022.2118924. Online ahead of print.

ABSTRACT

The extension of the human lifespan has led to an increase in the proportion of the elderly population worldwide. This situation has also brought the issue of healthy aging to the agenda. The importance of more active participation of elderly individuals in life in the development of health is increasing. Depression and self-efficacy of the elderly people are primarily addressed to support this situation. This study is a randomized controlled intervention study in which evaluating the change in depression and self-efficacy levels of elderly individuals after the empowerment intervention. In the study, which was conducted to improve elderly individuals’ depression and self-efficacy levels, an empowerment intervention consisting of 7 sessions was applied to these individuals. In the sessions, practices were carried out to increase the functionality of the elderly in cognitive, social, emotional, physical and spiritual areas. In this study, 60 elderly individuals (intervention and control groups) who were hospitalized for physical therapy and rehabilitation in a state hospital in Turkey between September 2019 and December 2020 were included. The simple random sampling method was used for sampling. The sample size was determined by G Power analysis. Geriatric depression and self-efficacy scales were used in the study. The study data were analyzed on the IBM SPSS Statistics 25.0 software package. Descriptive statistics were used to calculate descriptive data. Pearson, Chi-Square, and Fisher Exact tests were used to compare the sociodemographic and clinical characteristics of the participants. Paired Samples t-test was used to compare the intervention and the control groups’ pretest and posttest scores. In the study, it was determined that the mean geriatric depression pretest score was 15.43 ± 7.05 in the control group and 14.46 ± 7.21 in the intervention group, and there was no significant difference between the groups’ geriatric depression pretest scores (p = .602). However, it was determined that the mean geriatric depression posttest score was 13.50 ± 9.02 in the control group and 9.23 ± 6.71 in the intervention group, and there was a significant difference between the posttest scores of the groups (p = .042). No significant difference was found between the pretest and posttest geriatric depression scale scores of the control group (t = 1.346; p = .189). The posttest geriatric depression score of the intervention group was significantly lower than the pretest score (t = 5.966; p = .0001). In the study, it was determined that the mean self-efficacy pretest score was 79.63 ± 12.62 in the control group, 75.63 ± 14.20 in the intervention group, and there was no significant difference between the pretest scores of the groups (p = .254). It was determined that the mean self-efficacy posttest score was 83.10 ± 11.35 in the control group and 84.50 ± 14.41 in the intervention group, and there was no significant difference between the posttest scores of the groups (p = .678). The posttest self-efficacy score of the intervention group was found to be significantly higher than the pretest score (p = .001). The empowerment intervention was determined to decrease the elderly individuals’ depression and increase their self-efficacy levels.

PMID:36044559 | DOI:10.1080/19371918.2022.2118924

Sci Robot. 2022 Aug 31;7(69):eabo0235. doi: 10.1126/scirobotics.abo0235. Epub 2022 Aug 31.

ABSTRACT

Learning to combine control at the level of joint torques with longer-term goal-directed behavior is a long-standing challenge for physically embodied artificial agents. Intelligent behavior in the physical world unfolds across multiple spatial and temporal scales: Although movements are ultimately executed at the level of instantaneous muscle tensions or joint torques, they must be selected to serve goals that are defined on much longer time scales and that often involve complex interactions with the environment and other agents. Recent research has demonstrated the potential of learning-based approaches applied to the respective problems of complex movement, long-term planning, and multiagent coordination. However, their integration traditionally required the design and optimization of independent subsystems and remains challenging. In this work, we tackled the integration of motor control and long-horizon decision-making in the context of simulated humanoid football, which requires agile motor control and multiagent coordination. We optimized teams of agents to play simulated football via reinforcement learning, constraining the solution space to that of plausible movements learned using human motion capture data. They were trained to maximize several environment rewards and to imitate pretrained football-specific skills if doing so led to improved performance. The result is a team of coordinated humanoid football players that exhibit complex behavior at different scales, quantified by a range of analysis and statistics, including those used in real-world sport analytics. Our work constitutes a complete demonstration of learned integrated decision-making at multiple scales in a multiagent setting.

PMID:36044556 | DOI:10.1126/scirobotics.abo0235

PLoS One. 2022 Aug 31;17(8):e0273859. doi: 10.1371/journal.pone.0273859. eCollection 2022.

ABSTRACT

BACKGROUND: After the first case of COVID-19 caused by the novel SARS-CoV-2 virus was discovered in Wuhan, China, in December 2019, the disease spread viciously throughout the world. Little is known about the impact of HIV infection on the clinical outcomes of patients co-infected with SARS-CoV-2. Studying the characteristics and outcomes of COVID-19 among HIV-positive patients is key to characterising the risk of morbidity and mortality of HIV-positive patients from COVID-19.

METHODS: In this retrospective cohort study, we included patients admitted to Aga Khan University Hospital, Nairobi, with laboratory-confirmed COVID-19 infection and who had consented to HIV screening. We compared the prevalence and characteristics of HIV patients with those of non-HIV patients and described the results for both groups.

RESULTS: In our sample of 582 patients, the mean age was 49.2 years (SD = 15.2), with 68% of the sample being men. The cumulative HIV prevalence was 3.7%, and the most common symptoms were cough (58.1%), fever (45.2%), difficulty in breathing (36.8%) and general body malaise (23.9%). The most common comorbidities included hypertension (28.5%), diabetes mellitus (26.1%), and heart disease (4.1%). Most participants (228 or 49.5%) had mild COVID-19, and the mortality rate was 5%. Overall, there were no statistically significant differences in demographic characteristics, clinical characteristics, and outcomes between HIV-positive and HIV-negative patients.

CONCLUSIONS: There was a 3.7% prevalence of HIV in COVID-19 positive patients. Demographic characteristics and clinical outcomes were similar between the two groups. Future studies should seek to achieve larger samples, include multiple study sites and conduct subgroup analyses based on the immunologic status of HIV-positive patients.

PMID:36044517 | DOI:10.1371/journal.pone.0273859

IEEE Trans Neural Netw Learn Syst. 2022 Aug 31;PP. doi: 10.1109/TNNLS.2022.3201160. Online ahead of print.

ABSTRACT

In this brief, the state estimation problem is investigated for a class of randomly delayed artificial neural networks (ANNs) subject to probabilistic saturation constraints (PSCs) and non-Gaussian noises under the redundant communication channels. A series of mutually independent Bernoulli distributed white sequences are introduced to govern the random occurrence of the time delays, the saturation constraints, and the transmission channel failures. A comprehensive redundant-channel-based communication mechanism is constructed to attenuate the phenomenon of packet dropouts so as to enhance the quality of data transmission. To compensate for the influence of randomly occurring time delays, the corresponding occurrence probability is exploited in the process of particle generation. In addition, an explicit expression of the likelihood function is established based on the statistical information to account for the impact of PSCs and redundant channels. By virtue of the modified operations of particle propagation and weight update, a particle-filter-based state estimation algorithm is proposed with mild restriction on the system type. Finally, an illustrative example with Monte Carlo simulations is provided to demonstrate the effectiveness of the developed state estimation scheme.

PMID:36044499 | DOI:10.1109/TNNLS.2022.3201160

IEEE J Biomed Health Inform. 2022 Aug 31;PP. doi: 10.1109/JBHI.2022.3203345. Online ahead of print.

ABSTRACT

Given that depression is one of the most prevalent mental illnesses, developing effective and unobtrusive diagnosis tools is of great importance. Recent work that screens for depression with text messages leverage models relying on lexical category features. Given the colloquial nature of text messages, the performance of these models may be limited by formal lexicons. We thus propose a strategy to automatically construct alternative lexicons that contain more relevant and colloquial terms. Specifically, we generate 36 lexicons from fiction, forum, and news corpuses. These lexicons are then used to extract lexical category features from the text messages. We utilize machine learning models to compare the depression screening capabilities of these lexical category features. Out of our 36 constructed lexicons, 14 achieved statistically significantly higher average F1 scores over the pre-existing formal lexicon and basic bag-of-words approach. In comparison to the pre-existing lexicon, our best performing lexicon increased the average F1 scores by 10%. We thus confirm our hypothesis that less formal lexicons can improve the performance of classification models that screen for depression with text messages. By providing our automatically constructed lexicons, we aid future machine learning research that leverages less formal text.

PMID:36044503 | DOI:10.1109/JBHI.2022.3203345

IEEE Trans Med Imaging. 2022 Aug 31;PP. doi: 10.1109/TMI.2022.3203309. Online ahead of print.

ABSTRACT

Multi-class segmentation of cardiac magnetic resonance (CMR) images seeks a separation of data into anatomical components with known structure and configuration. The most popular CNN-based methods are optimised using pixel wise loss functions, ignorant of the spatially extended features that characterise anatomy. Therefore, whilst sharing a high spatial overlap with the ground truth, inferred CNN-based segmentations can lack coherence, including spurious connected components, holes and voids. Such results are implausible, violating anticipated anatomical topology. In response, (single-class) persistent homology-based loss functions have been proposed to capture global anatomical features. Our work extends these approaches to the task of multi-class segmentation. Building an enriched topological description of all class labels and class label pairs, our loss functions make predictable and statistically significant improvements in segmentation topology using a CNN-based post-processing framework. We also present (and make available) a highly efficient implementation based on cubical complexes and parallel execution, enabling practical application within high resolution 3D data for the first time. We demonstrate our approach on 2D short axis and 3D whole heart CMR segmentation, advancing a detailed and faithful analysis of performance on two publicly available datasets.

PMID:36044487 | DOI:10.1109/TMI.2022.3203309

PLoS One. 2022 Aug 31;17(8):e0270186. doi: 10.1371/journal.pone.0270186. eCollection 2022.

ABSTRACT

BACKGROUND: The burden of non-communicable diseases like diabetes and hypertension is increasing worldwide including low-and middle-income countries. Good knowledge of such diseases among young people will make them adopt a healthy lifestyle from an early age, which will, in turn, prevent them from developing such non-communicable diseases. This study aimed to assess the knowledge, attitude, and practice of rural and urban school students regarding diabetes and hypertension. We also aimed to see the differences in the knowledge, attitude, and practice of students from rural vs. urban communities.

METHODS: A school-based cross-sectional study was conducted from May 1 2021 to June 30, 2021, in four schools in Nepal (1 from a metropolitan city, 2 from an urban municipality, and 1 from a rural municipality). The study was conducted among the secondary-level students of classes 9 and 10 in each school. The data were collected from the participants via pre-tested questionnaires and analyzed in the Statistical Packages for Social Sciences (SPSS) version 20.0. Logistic regression analysis was carried out to determine the determinants of knowledge and attitude regarding diabetes and hypertension.

RESULTS: Of 380 respondents, 35.5% were residents of metropolitan city, 37.4% were from the urban municipality and 27.1% were from the rural municipality. The mean age of respondents was 15.61±0.99 years and 51.1% were male. Respondents having a family history of diabetes and hypertension were 21.1% and 37.9% respectively. Respondents from the metropolitan city had significantly higher mean knowledge scores than the respondents from the urban and rural municipality (p<0.001) while there was no significant difference in mean attitude scores. There was significantly higher daily consumption of fruits and vegetables among the participants from rural municipality (p<0.01) while no significant difference was seen in salt consumption and time spent on physical activity. In univariate regression analysis, place of residence, family occupation, parental education, and family history of diabetes and hypertension were significantly associated with good knowledge level. In multivariate analysis, only a higher grade of study (grade 10 in comparison to grade 9) was an independent predictor of a student’s good attitude level.

CONCLUSION: In general, there was a good attitude towards diabetes and hypertension despite poor knowledge. The mean knowledge scores were lower in urban municipality and rural municipality compared to metropolitan city. Low knowledge scores on diabetes and hypertension among the students show an urgent need for school-based interventional programs focusing on non-communicable diseases and lifestyle modification with more emphasis on rural communities.

PMID:36044457 | DOI:10.1371/journal.pone.0270186

PLoS One. 2022 Aug 31;17(8):e0273691. doi: 10.1371/journal.pone.0273691. eCollection 2022.

ABSTRACT

BACKGROUND: COVID-19 is spreading rapidly worldwide, and the population is generally susceptible to SARS-CoV-2, especially those with cancer. Hence, our study aims to design a protocol for a systematic review and meta-analysis of the clinical characteristics and prognoses of lung cancer patients with COVID-19.

METHODS: The protocol is prepared following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The literature will be searched in Embase, Pubmed, the Cochrane Library, LitCovid, and CNKI for potentially eligible articles. The quality of the articles will be used in the Newcastle-Ottawa Quality Assessment Scale (NOS) and Cochrane Handbook for Systematic Reviews of Interventions. Statistical analysis will be performed through RevMan 5 software. This review protocol has been registered in PROSPERO (CRD42022306866).

DISCUSSION: To clarify whether COVID-19 affects the clinical symptoms and prognoses of lung cancer patients. Further study is needed to establish the best evidence-based for the management of lung cancer patients with COVID-19.

CONCLUSION: The definitive conclusion will be important to physicians effectively manage lung cancer patients with COVID-19.

PMID:36044455 | DOI:10.1371/journal.pone.0273691

PLoS One. 2022 Aug 31;17(8):e0272460. doi: 10.1371/journal.pone.0272460. eCollection 2022.

ABSTRACT

Recovery activities during short breaks taken between work tasks are solutions for preventing the impairing effects of accumulated strain. No wonder then that a growing body of scientific literature from various perspectives emerged on this topic. The present meta-analysis is aimed at estimating the efficacy of micro-breaks in enhancing well-being (vigor and fatigue) and performance, as well as in which conditions and for whom are the micro-breaks most effective. We searched the existent literature on this topic and aggregated the existing data from experimental and quasi-experimental studies. The systematic search revealed 19 records, which resulted in 22 independent study samples (N = 2335). Random-effects meta-analyses shown statistically significant but small effects of micro-breaks in boosting vigor (d = .36, p < .001; k = 9, n = 913), reducing fatigue (d = .35, p < .001; k = 9, n = 803), and a non-significant effect on increasing overall performance (d = .16, p = .116; k = 15, n = 1132). Sub-groups analyses on performance types revealed significant effects only for tasks with less cognitive demands. A meta-regression showed that the longer the break, the greater the boost was on performance. Overall, the data support the role of micro-breaks for well-being, while for performance, recovering from highly depleting tasks may need more than 10-minute breaks. Therefore, future studies should focus on this issue.

PMID:36044424 | DOI:10.1371/journal.pone.0272460

Alzheimers Dement. 2022 Aug 31. doi: 10.1002/alz.12764. Online ahead of print.

ABSTRACT

BACKGROUND: An ample literature documents the growing prevalence of dementia and associated costs. Less attention has been paid to decreased dementia incidence in some countries.

METHODS: We analyzed trends in age-standardized dementia, stroke, and ischemic heart disease (the triple threat) incidence rates and population attributable fraction of death and disability attributable to 12 risk factors in 204 countries and territories and 51 regions using Global Burden of Disease 2019 data.

RESULTS: During 1990 to 2019, dementia incidence declined in 71 countries; 18 showed statistically significant declines, ranging from -12.1% (95% uncertainty intervals -16.9 to -6.8) to -2.4% (-4.6 to -0.5). During 2010 to 2019, 16 countries showed non-significant declines. Globally, the burden of the triple threat attributable to air pollution, dietary risks, non-optimal temperature, lead exposure, and tobacco use decreased from 1990 to 2019.

CONCLUSION: The declining incidence of dementia in some countries, despite growing prevalence, is encouraging and urges further investigation.

PMID:36044376 | DOI:10.1002/alz.12764