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4; 95% CI = 1.4-8.6; increase per category from less then 1/month, ≥ 1/month but less then 1/week, to ≥ 1/week) and no or inconsistent condom use during anal or oral sex (OR = 3.0; 95% CI = 1.1-8.3; increase per category from using every time, occasionally, to never), adjusted for residency and time between visits. buy Pyridostatin Discussion Modifiable behaviours were associated with incident syphilis, and dissemination of prevention messages are needed. (c) 2019 The authors; licensee World Health Organization.The purpose of this study was to investigate the feasibility of using neck-surface acceleration signals to discriminate between modal, breathy and pressed voice. Voice data for five English single vowels were collected from 31 female native Canadian English speakers using a portable Neck Surface Accelerometer (NSA) and a condenser microphone. Firstly, auditory-perceptual ratings were conducted by five clinically-certificated Speech Language Pathologists (SLPs) to categorize voice type using the audio recordings. Intra- and inter-rater analyses were used to determine the SLPs' reliability for the perceptual categorization task. Mixed-type samples were screened out, and congruent samples were kept for the subsequent classification task. Secondly, features such as spectral harmonics, jitter, shimmer and spectral entropy were extracted from the NSA data. Supervised learning algorithms were used to map feature vectors to voice type categories. A feature wrapper strategy was used to evaluate the contribution of each feature or feature combinations to the classification between different voice types. The results showed that the highest classification accuracy on a full set was 82.5%. The breathy voice classification accuracy was notably greater (approximately 12%) than those of the other two voice types. Shimmer and spectral entropy were the best correlated metrics for the classification accuracy.Vocal loading tasks are often used to investigate the relationship between voice use and vocal fatigue in laboratory settings. The present study investigated the concept of a novel quantitative dose-based vocal loading task for vocal fatigue evaluation. Ten female subjects participated in the study. Voice use was monitored and quantified using an online vocal distance dose calculator during six consecutive 30-min long sessions. Voice quality was evaluated subjectively using the CAPE-V and SAVRa before, between, and after each vocal loading task session. Fatigue-indicative symptoms, such as cough, swallowing, and voice clearance, were recorded. Statistical analysis of the results showed that the overall severity, the roughness, and the strain ratings obtained from CAPE-V obeyed similar trends as the three ratings from the SAVRa. These metrics increased over the first two thirds of the sessions to reach a maximum, and then decreased slightly near the session end. Quantitative metrics obtained from surface neck accelerometer signals were found to obey similar trends. The results consistently showed that an initial adjustment of voice quality was followed by vocal saturation, supporting the effectiveness of the proposed loading task.The contextual knowledge and local expertise that researchers from low-income and middle-income countries (LMICs) contribute to studies in these settings enrich the research process and subsequent publications. However, health researchers from LMICs are under-represented in the scientific literature. Distally, power imbalances between LMICs and high-income countries, which provide funding and set priorities for research in LMICs, create structural inequities that inhibit these authors from publishing. More proximally, researchers from LMICs often lack formal training in research project management and in publishing peer-reviewed research. Though academic journals may value research from LMICs conducted by local researchers, they have limited time and financial resources to support writing, causing them to reject manuscripts with promising results if they lack development. Pre-Publication Support Service (PREPSS) is a non-profit, non-governmental organisation that works to meet this need. PREPSS provides onsite training, peer-review and copy editing services to researchers in LMICs who wish to publish their health research in peer-reviewed journals. Authors are not charged for these services. After receiving PREPSS services, authors submit their manuscript to a peer-reviewed journal. The PREPSS model is one of many interventions necessary to restructure global health research to better support health researchers in LMICs and reduce current power imbalances. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.Background Inequalities in early childhood development (ECD) tend to persist into adulthood and amplify across the life course. To date, little research on inequalities in early childhood care and development in low/middle-income countries has been available to guide governments, donors and civil society in identifying which young children and families should be targeted by policies and programmes to improve nurturing care that could prevent them from being left behind. Methods Using data from 135 Demographic and Health Surveys and Multiple Indicator Cluster Surveys between 2010 and 2018, we assessed levels and trends of inequalities in exposure to risks of stunting or extreme poverty (under age 5; levels in 85 and trends in 40 countries), early attendance of early care and education programmes (36-59 months; 65 and 17 countries), home stimulation (36-59 months; 62 and 14 countries) and child development according to the Early Childhood Development Index (36-59 months; 60 and 13 countries). Inequalities withiorest countries. Improving and applying population-level measurements on ECD in more countries over time are important for ensuring equal opportunities for young children globally. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
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