Number Of Active Days Research Articles

Condylar fracture location is correlated to exercise history in Thoroughbred racehorses.

Condylar fractures are a major cause of morbidity and mortality in Thoroughbred racehorses. Condylar fractures have a variety of fracture configurations that suggest there may be differences in aetiopathogenesis. To determine if exercise history differs with condylar fracture location in a population of Thoroughbred racehorses. Retrospective analysis of clinical and exercise data. Exercise history of Thoroughbred racehorses that had condylar fracture repair between 1 January 2018 and 28 February 2021 was compared between racehorses that had fractures located radiographically either within the parasagittal groove (PSG) or abaxial to the PSG (non-PSG). Age, sex, and last event (race, timed work) matched control groups were compared between the PSG and non-PSG groups. Additionally, exercise history variables of both groups were each compared with a group-specific control population, each consisting of three control racehorses of equivalent age and sex matched to each affected racehorse by last event (race or official timed work) before fracture. Eighty-two horses with 84 fractures (45 PSG, 39 non-PSG) met inclusion criteria. Age was not different between groups (PSG: 3.4 ± 1.3 years [mean ± SD], non-PSG: 3.7 ± 1.3, p = 0.3). Number of races (PSG: 5.3 ± 7.1, non-PSG: 11.4 ± 8.9, p < 0.001), total race furlongs (PSG: 38.2 ± 54.7, non-PSG: 79.2 ± 64, p = 0.003), and number of active days (PSG: 304 ± 224, non-PSG: 488 ± 314, p = 0.003) before fracture were greater; while mean number of layups was fewer (PSG: 1.0 ± 1.2, non-PSG: 0.5 ± 0.7, p = 0.02) in horses with non-PSG fracture. Horses with non-PSG fracture had more differences compared with their respective control group than horses with PSG fractures. Outcomes following fracture repair were not different between groups. Retrospective study, one regional racehorse population, two-dimensional imaging and potential inherent bias for fracture localisation, low statistical power for return to performance analysis. Thoroughbred racehorses with non-PSG condylar fractures have a more extensive exercise history than horses with PSG condylar fractures, suggesting differences in fracture aetiopathogenesis.

Korean Wooden Architectural Heritages at An Increased Risk of Termite Damage due to Temperature Change

Wooden architectural heritages in Korea have been severely damaged by termites, and this damage is expected to increase owing to climate change. This study aimed to evaluate the changes in termite damage risk due to climate change specifically in Korean wooden architectural heritages. A multiple regression equation was developed to estimate the daily average temperature from the location information (latitude, longitude, and elevation) for 40 years (1980-2019). The location information of 106 nationally designated wooden architectural heritages distributed across 84 cities was used to estimate the daily mean temperature of each cultural heritages. Referring to a previous study on the ecological characteristics of &lt;i&gt;R. speratus&lt;/i&gt;, a dominant termite species in Korea, the temperature at which termite activity is possible was confirmed, and the amount of wood consumed in relation to the temperature change was estimated. Based on this, the number of days available for termite activity and the amount of termite wood intake in the 1980s, 1990s, 2000s, and 2010s were estimated. Consequently, we found that the number of active days for termites increased from 243 to 249, 251, and 253 days in each decade. The wood consumption rate also increased by 9.9% over 40 years, from 6,657 to 6,777, 7,008, and 7,314 μg/ worker/year, respectively. This study was the first to estimate the activity period and wood intake of termites in Korea’s wooden architectural heritages, thereby providing valuable information for the preservation and management of these wooden heritages.

Automated Diet Capture Using Voice Alerts and Speech Recognition on Smartphones: Pilot Usability and Acceptability Study.

Effective monitoring of dietary habits is critical for promoting healthy lifestyles and preventing or delaying the onset and progression of diet-related diseases, such as type 2 diabetes. Recent advances in speech recognition technologies and natural language processing present new possibilities for automated diet capture; however, further exploration is necessary to assess the usability and acceptability of such technologies for diet logging. This study explores the usability and acceptability of speech recognition technologies and natural language processing for automated diet logging. We designed and developed base2Diet-an iOS smartphone application that prompts users to log their food intake using voice or text. To compare the effectiveness of the 2 diet logging modes, we conducted a 28-day pilot study with 2 arms and 2 phases. A total of 18 participants were included in the study, with 9 participants in each arm (text: n=9, voice: n=9). During phase I of the study, all 18 participants received reminders for breakfast, lunch, and dinner at preselected times. At the beginning of phase II, all participants were given the option to choose 3 times during the day to receive 3 times daily reminders to log their food intake for the remainder of the phase, with the ability to modify the selected times at any point before the end of the study. The total number of distinct diet logging events per participant was 1.7 times higher in the voice arm than in the text arm (P=.03, unpaired t test). Similarly, the total number of active days per participant was 1.5 times higher in the voice arm than in the text arm (P=.04, unpaired t test). Furthermore, the text arm had a higher attrition rate than the voice arm, with only 1 participant dropping out of the study in the voice arm, while 5 participants dropped out in the text arm. The results of this pilot study demonstrate the potential of voice technologies in automated diet capturing using smartphones. Our findings suggest that voice-based diet logging is more effective and better received by users compared to traditional text-based methods, underscoring the need for further research in this area. These insights carry significant implications for the development of more effective and accessible tools for monitoring dietary habits and promoting healthy lifestyle choices.

Behavioural Markers of Harm and Their Potential in Identifying Product Risk in Online Gambling

Abstract Many studies have been conducted to identify potentially useful behavioural markers of harmful behaviour using online gambling data sourced from operators. However, less is known about how such markers could be used to identify higher risk products. The study examined whether certain categories and subcategories of product are more strongly associated with behavioural markers of harm than others. Analyses were based on 6 months of data (N = 100,000 individual gamblers) drawn from the population of UK users of an online gambling website in 2022. Measures included individual-level expenditure data across multiple forms of gambling and a series of literature-informed behavioural markers of harm including declined deposits, easing/removing responsible gambling settings, within-session repeat deposits (or ‘top-ups’), bonus-seeking behaviour and gambling at unusual hours. Negative binomial models examined how well the number of active days playing different products predicted behavioural markers of harm. All markers apart from easing/removing responsible gambling settings appeared to covary with the number of active days engaging in specific product types, most notably slots, in-playing betting and some most forms of combination bets on sports. These findings highlight the potential value of using measurable markers to differentiate the risk and potential harm associated with different online products.

A New Digital Health Program for Patients With Inflammatory Bowel Disease: Preliminary Program Evaluation

Inflammatory bowel disease (IBD) causes chronic inflammation of the gastrointestinal tract. IBD is characterized by an unpredictable disease course that varies greatly between individuals and alternates between the periods of relapse and remission. A low energy level (fatigue) is a common symptom, whereas stress and reduced sleep quality may be the triggering factors. Therapeutic guidelines call for effective disease assessment, early intervention, and personalized care using a treat-to-target approach, which may be difficult to achieve through typical time- and resource-constrained standard care. Providing patients with a digital health program that incorporates helpful self-management features and patient support to complement standard care may be optimal for improving the disease course. This study aimed to perform a preliminary program evaluation, analyzing engagement and preliminary effectiveness and the effect on participants' energy levels (fatigue), stress, and sleep quality, of a newly developed 16-week digital health program (SK-311 and SK-321) for patients with IBD. Adults with IBD were recruited to participate in a real-world, live, digital health program via Finnish IBD patient association websites and social media. No inclusion or exclusion criteria were applied for this study. Baseline characteristics were entered by the participants upon sign-up. Platform engagement was measured by tracking the participants' event logs. The outcome measures of stress, energy levels (fatigue), and quality of sleep were reported by participants through the platform. Of the 444 adults who registered for the digital health program, 205 (46.2%) were included in the intention-to-treat sample. The intention-to-treat participants logged events on average 41 times per week (5.9 times per day) during the weeks in which they were active on the digital platform. More women than men participated in the intervention (126/205, 88.7%). The mean age of the participants was 40.3 (SD 11.5) years, and their mean BMI was 27.9 (SD 6.0) kg/m2. In total, 80 people provided the required outcome measures during weeks 12 to 16 (completers). Treatment completion was strongly predicted by the number of active days in week 1. Analysis of the completers (80/205, 39%) showed significant improvements for stress (t79=4.57; P<.001; percentage change=-23.26%) and energy levels (t79=-2.44; P=.017; percentage change=9.48%); however, no significant improvements were observed for quality of sleep (t79=-1.32; P=.19). These results support the feasibility of a digital health program for patients with IBD (SK-311 and SK-321) and suggest that treatment completion might have a substantial positive effect on patient-reported stress and energy levels in a real-world setting. These findings are promising and provide initial support for using the Sidekick Health digital health program to supplement standard care for patients with IBD.

Life in a time of COVID: retrospective examination of the association between physical activity and mental well-being in western Australians during and after lockdown

BackgroundThe aim of this study was to examine physical activity and sedentary behaviours during Western Australia’s COVID-19 lockdown and their association with mental well-being.MethodsParticipants completed activity related questions approximately two months after a three-month lockdown (which formed part of a larger cross-sectional study from August to October 2020) as part of a 25-minute questionnaire adapted from the Western Australia Health and Well-being Surveillance system. Open-ended questions explored key issues relating to physical activity behaviours.ResultsDuring the lockdown period, 463 participants (female, n = 347; 75.3%) reported lower number of active days (W = 4.47 p < .001), higher non-work-related screen hours per week (W = 11.8 p < .001), and higher levels of sitting time (χ2=28.4 p < .001). Post lockdown body mass index was higher (U = 3.0 p = .003), with obese individuals reporting the highest non-work-related screen hours per week (Wald χ2= 8.9 p = .012). Inverse associations were found for mental well-being where higher lockdown scores of Kessler-10 (p = .011), Dass-21 anxiety (p = .027) and Dass-21 depression (p = .011) were associated with lower physical activity levels. A key qualitative message from participants was wanting to know how to stay healthy during lockdown.ConclusionsLockdown was associated with lower physical activity, higher non-work-related screen time and more sitting time compared to post lockdown which also reported higher body mass index. Lower levels of mental well-being were associated with lower physical activity levels during lockdown. Given the known positive affect of physical activity on mental well-being and obesity, and the detrimental associations shown in this study, a key public health message should be considered in an attempt to maintain healthy activity behaviours in future lockdowns and similar emergency situations to promote and maintain positive well-being. Furthermore, consideration should be given to the isolation of a community due to infectious disease outbreaks and to recognise the important role physical activity plays in maintaining weight and supporting good mental health.

Sensa Mobile App for Managing Stress, Anxiety, and Depression Symptoms: Pilot Cohort Study.

An increase in depression, anxiety, and stress symptoms worldwide, attributed to the COVID-19 pandemic, has been reported. If not treated, it may negatively affect a person's everyday life by altering physical and social well-being and productivity and increasing expenditure on health care. Cognitive behavioral therapy (CBT)-based interventions are gaining popularity as a means to reduce stress and alleviate anxiety and depression symptoms. Moreover, CBT delivered through a mobile app has the same elements as traditional CBT training (eg, guided discovery). However, unlike conventional training, users of mobile apps are allowed to tailor their own experience at their own speed and schedule. This study aims to analyze Sensa users' retrospective data and explore the dose-duration effect to find the optimal usage time when the user showed results. The study cohort comprised 381 consecutive community-based nonclinical users who started using Sensa between October 2021 and March 2022. All users included in the study took the Depression Anxiety Stress Scale-21 (DASS-21) assessment at least 2 times. Other parameters from the database containing all self-reported data were gender, number of active days, total time of use, and age. The primary outcome of the study was a change in the DASS-21 score. Statistical analyses were performed using GraphPad Prism (version 9, GraphPad Software). In addition, a logistic regression model was created to predict how the obtained independent parameters influenced the DASS-21 score. The main finding of our study was that the majority of participants who started using Sensa were experiencing depression, anxiety, and stress symptoms (92.13%, 80.05%, and 87.93%, respectively). There was a statistically significant decrease of the DASS-21 subdomain scores after the use of the application (anxiety: mean 7.25, SD 4.03 vs mean 6.12, SD 4.00; P=.001; depression: mean 11.05, SD 4.26 vs mean 9.01, SD 4.77; P=.001; stress: mean 11.42, SD 3.44 vs mean 9.96, SD 3.65; P<.001). Finally, the logistic regression model showed that users who were using the app for more than 24 days and had at least 12 active days during that time had 3.463 (95% CI 1.142-11.93) and 2.644 (95% CI 1.024-7.127) times higher chances to reduce their DASS-21 subdomain scores of depression and anxiety, respectively. Using the Sensa mobile app was related to decreased depression, anxiety, and stress symptoms.

Online health community for change: Analysis of self-disclosure and social networks of users with depression.

A key research question with theoretical and practical implications is to investigate the various conditions by which social network sites (SNS) may either enhance or interfere with mental well-being, given the omnipresence of SNS and their dual effects on well-being. We study SNS' effects on well-being by accounting for users' personal (i.e., self-disclosure) and situational (i.e., social networks) attributes, using a mixed design of content analysis and social network analysis. We compare users' within-person changes in self-disclosure and social networks in two phases (over half a year), drawing on Weibo Depression SuperTalk, an online community for depression, and find: ① Several network attributes strengthen social support, including network connectivity, global efficiency, degree centralization, hubs of communities, and reciprocal interactions. ② Users' self-disclosure attributes reflect positive changes in mental well-being and increased attachment to the community. ③ Correlations exist between users' topological and self-disclosure attributes. ④ A Poisson regression model extracts self-disclosure attributes that may affect users' received social support, including the writing length, number of active days, informal words, adverbs, negative emotion words, biological process words, and first-person singular forms. We combine social network analysis with content analysis, highlighting the need to understand SNS' effects on well-being by accounting for users' self-disclosure (content) and communication partners (social networks). Authentic user data helps to avoid recall bias commonly found in self-reported data. A longitudinal within-person analysis of SNS' effects on well-being is helpful for policymakers in public health intervention, community managers for group organizations, and users in online community engagement.

Abstract P519: Reduced Liver Fat and Improved Cardiometabolic Health in Individuals With Non Alcoholic Fatty Liver Disease After a 12 Week Digital Intervention - A Feasibility Study

Introduction: Cardiovascular disease is the most common cause of death among people with non-alcoholic fatty liver disease (NAFLD) and lifestyle changes can improve health outcomes. A NAFLD digital intervention was designed and here we report retention, engagement and satisfaction results in addition to the program's potential clinical impact on markers of liver- and cardiometabolic health. Hypothesis: We assessed the hypothesis that a digital intervention is feasible for individuals with metabolic derangements and NAFLD to improve cardiometabolic health. Methods: A prospective, open label, single arm, 12 week long study was conducted in Iceland.The intervention was delivered through the Sidekick app, with focus on disease education, low carbohydrate diet, increasing activity levels, reducing stress and healthy lifestyle coaching. Individuals with either BMI&gt;30, metabolic syndrome or type 2 diabetes were screened for NAFLD with a FibroScan assessment. Other potential reasons for liver steatosis were excluded. Following recruitment and collection of demographic data, anthropometric and clinical measurements, MRI-PDFF for liver fat content, dual-energy X-ray absorptiometry for body composition and blood tests, were carried out at baseline and after 12 weeks. Primary outcomes were engagement and retention as measured in-app, and user satisfaction (mHealth App Usability Questionnaire); secondary outcomes were changes in weight, liver fat content and other cardiovascular risk factors. Results: In total, 38 individuals were included in the study and 34 (89%) completed the program (defined as being active 9/12 weeks). The median age was 59.5 [IQR 46.0,69.0] years and 23 (60.5%) were females. The median number of active days was 81 [IQR 45.8, 84.0] and the median user satisfaction score was 6.3 out of 7. The mean weight loss was 3.5 kg (SD=3.7) (p&lt;0.001) with 5.0% (SD=7.0) reduction in fat mass (p&lt;0.001), the average relative liver fat reduction was 19.3% (SD=23.9) (p&lt;0.001). Systolic blood pressure reduced by 6.0 mmHg on average (SD=13.5) (p=0.009), diastolic blood pressure by 1.2 mmHg (SD=7.7) (p=0.357), triglyceride levels by 0.3 mmol/L (SD=0.6) (p=0.003) and waist circumference by 4.1 cm (SD=5.2) (p&lt;0.001). In addition, participants who were active in-app at least 5 days per week on average achieved 3.8 kg (SD=3.7) (p&lt;0.001) more weight loss and 19.3% (SD=23.9) (p=0.011) higher reduction in absolute liver fat percentage, compared to those who used the app less. Conclusion: This study suggests that a holistic digital intervention may improve liver-specific and cardiometabolic health in individuals with NAFLD, as indicated by the reduction in liver fat, systolic blood pressure and improvements in body composition. Together with the excellent program engagement, completion and satisfaction, this approach could provide a new tool to improve health outcomes in NAFLD.

User Engagement and Weight Loss Facilitated by a Mobile App: Retrospective Review of Medical Records.

Intermittent fasting (IF) has gained popularity in recent years for its effect on weight loss and supposed additional health benefits, such as a positive effect on body composition and metabolic markers. Mobile apps can act as platforms that help deliver dietary interventions by improving adherence and motivation. Although the effect of IF on weight loss has been demonstrated in earlier trials, there is not much research about the engagement and weight loss results with IF apps. Our main objective was to compare how a nudging platform (including smart scales) influences engagement (the extent to which users interact with the app measured by the number of active days) with the app among users who had obesity at the beginning of use. The secondary objectives were to evaluate the body weight changes among active and nonactive users and, finally, to evaluate the body composition changes of users possessing smart scales during app usage. Through this study, we hope to provide (1) more insight into how nudging (using smart scales as a nudging platform) is associated with engagement with the mobile app, (2) how engagement with the mobile app is associated with weight loss, and (3) how IF is associated with body composition. We performed a retrospective analysis of data from 665 users with obesity (BMI≥30) who started using the IF app DoFasting. Of them, 244 used body composition scales that estimated body fat and body muscle values. Users were stratified into engagement groups in accordance with their activity ratio (number of active days divided by the total time of use). Baseline and final users' weight (in kg), body fat (in %), and body muscle (in %) were compared. Our findings suggest an association between the nudging platform (smart scales) and better engagement with the app. Smart scale users had a significantly higher activity ratio than regular users. Additionally, active DoFasting users lost significantly more weight. Further, body composition analysis showed that app usage might be related to body fat loss and an increase in muscle mass. We found a possible association between the nudging and gamified elements and higher app engagement. Additionally, increased app engagement is associated with increased weight loss. Thus, nudging and gamified elements of mobile health apps, such as interactive tools, goals, challenges, and progress tracking, are suggested to affect engagement positively and should be investigated further in future research. Finally, the IF regime delivered through the DoFasting app might be related to the body muscle mass gain and reduced fat mass.

The Climate Characteristics of the Northeast China Cold Vortex against the Background of Global Warming

In this study, by using the ERA5 data of the atmospheric circulation field that was re-analyzed by the ECMWF (European Centre for Medium-Range Weather Forecasts), we revealed the features of the Northeast China Cold Vortex (NCCV) from 1950 to 2020 (including active days, occurrence time of NCCV processes, and process durations). This study focused on a comparative analysis of the differences in the NCCV’s climate characteristics in the cold and warm periods to help future predictions. The results revealed the following: From 1950 to 2020, the NCCV occurred 2961 times on 9782 days. The average annual occurrence time of NCCV processes, annual average of cold vortex days, and average process duration of the NCCVs were 41.7 times, 137.8 days, and 3.6 days, respectively. These indicators of the NCCVs showed an increasing trend, but the trend was not significant. The NCCVs occurred most frequently in May, followed by June, and were located at the southernmost point in June. Therefore, it had the most active days and a relatively long process duration in May and June, significantly impacting Northeast China. During the cold period (1950–1980), the annual occurrence time of NCCV processes, number of cold vortex days, and the process duration of the NCCVs all showed an increasing trend, while in the warm period, these showed a decreasing trend. In addition, the durations of the NCCVs decreased significantly in the warm period, which indicated that the NCCV processes continued to weaken after climate warming. During the warm period (1981–2020), the frequency and active days of the NCCVs throughout the year and most months increased, and its general location was more southerly than in the cold period. Moreover, the annual average occurrence time of NCCV processes, number of active days, and average duration of the NCCV in the warm period were more than those in the cold period. Finally, the NCCVs continued for longer in autumn and winter than in spring and summer, and the durations of the NCCVs increased in warm periods.

KetoCycle mobile app for ketogenic diet: a retrospective study of weight loss and engagement

BackgroundThe ketogenic diet is one of the oldest diets that has been used for more than a centennial in the clinical setting, and it is gaining popularity as a measure to fight obesity, which is a major predisposing factor for many diseases to manifest, including diabetes mellitus, chronic heart disease, cancer, and others. Thus, we designed this retrospective investigation to determine if users of the mobile application KetoCycle achieved statistically significant weight loss outcomes.MethodsThe initial study cohort comprised 12,965 consecutive users who started using KetoCycle between January 2020 and December 2020. The final cohort comprised 10,269 users. The main parameters obtained from the database containing all self-reported data were gender, number of active days (AD), total time of use (TT), height, initial weight, and last recorded weight. The primary outcome of the study was weight loss. Statistical analyses were performed using IBM SPSS Statistics, version 26 (IBM Corp., Armonk, NY, USA). In addition, a standard multiple regression model was created to predict weight loss from significant actions.ResultsA retrospective analysis of KetoCycle user data showed that 87.3% of KetoCycle users lost some of their initial weight. Of those, 1645 users (18.3%) lost more than 10% of their initial body weight, 3528 (39.3%) users lost between 5 and 10% of their initial body weight, and 3796 (42.3%) users lost less than 5% of their body weight. When user activity was taken into account, it was found that active users lost statistically significantly more weight than non-active users (p < 0.05). App engagement was also associated with losing > 5% of initial weight. Using water tracking, weight tracking, and creation of a meals list within KetoCycle statistically significantly predicted weight loss in a multiple regression model.ConclusionsWe concluded that KetoCycle appeared as a promising mobile application suited for weight loss and weight control.Trial registrationThis retrospective chart review study was approved by BRANY IRB in January 2022 (registration ID.: 21-08-564-939).

Applying Collective Intelligence in Health Recommender Systems for Smoking Cessation: A Comparison Trial

Background: Health recommender systems (HRSs) are intelligent systems that can be used to tailor digital health interventions. We compared two HRSs to assess their impact providing smoking cessation support messages. Methods: Smokers who downloaded a mobile app to support smoking abstinence were randomly assigned to two interventions. They received personalized, ratable motivational messages on the app. The first intervention had a knowledge-based HRS (n = 181): it selected random messages from a subset matching the users’ demographics and smoking habits. The second intervention had a hybrid HRS using collective intelligence (n = 190): it selected messages applying the knowledge-based filter first, and then chose the ones with higher ratings provided by other similar users in the system. Both interventions were compared on: (a) message appreciation, (b) engagement with the system, and (c) one’s own self-reported smoking cessation status, as indicated by the last seven-day point prevalence report in different time intervals during a period of six months. Results: Both interventions had similar message appreciation, number of rated messages, and abstinence results. The knowledge-based HRS achieved a significantly higher number of active days, number of abstinence reports, and better abstinence results. The hybrid algorithm led to more quitting attempts in participants who completed their user profiles.

Applying the DSM-5 Criteria for Gambling Disorder to Online Gambling Account-Based Tracking Data: An Empirical Study Utilizing Cluster Analysis

The emergence of online gambling has raised concerns about potential gambling-related harm, and various measures have been implemented in order to minimise harm such as identifying and/or predicting potential markers of harm. The present study explored how the nine DSM-5 criteria for gambling disorder can be operationalised in terms of actual online gambling behaviour using account-based gambling tracking data. The authors were given access to an anonymised sample of 982 gamblers registered with an online gambling operator. The data collected for these gamblers consisted of their first three months’ gambling activity. The data points included customer service contacts, number of hours spent gambling, number of active days, deposit amounts and frequency, the number of times a responsible gambling tool (such as deposit limit) were removed by the gamblers themselves, number of cancelled withdrawals, number of third-party requests, number of registered credit cards, and frequency of requesting bonuses through customer service (i.e., the number of instances of ‘bonus begging’). Using these metrics, most of the DSM-5 criteria for gambling disorder can be operationalized (at least to some extent) using actual transaction data. These metrics were then applied to a sample of online gamblers, and through cluster analysis four types of online gambler based on these metrics (non-problem gamblers, at-risk gamblers, financially vulnerable gamblers, and emotionally vulnerable gamblers) were identified. The present study is the first to examine the application of the DSM-5 criteria of gambling disorder to actual gambling behaviour using online gambling transaction data and suggests ways that gambling operators could identify problem gamblers online without the need for self-report diagnostic screening instruments.

Daily physical activity, human development index and insomnia in a representative sample of Brazilian adolescents: a cross-sectional analysis.

Although there is a growing body of research pointing towards the need to investigate how different movement behaviors, such as physical activity and sleep, influence each other, the joint relationship between these factors and insomnia has been little explored among adolescents in developing countries. To investigate the association between daily physical activity and insomnia in a national sample of Brazilian adolescents, according to the Human Development Index (HDI) of each Brazilian region. Cross-sectional study on 102,072 Brazilian students aged 11 to 19 years, selected from all regions of the country. Information on insomnia and physical activity was self-reported by adolescents. Our analyses revealed that girls who accumulated at least 60 minutes/day of physical activity on up to three days/week were less prone to present insomnia. This pattern of association was maintained only for those who lived in high HDI regions (odds ratio, 0.87; 95% confidence interval, 0.75-0.99). For boys, there was a positive association between the number of active days and protection against insomnia, especially for those who lived in high HDI regions. Even amounts of physical activity that were lower than the weekly guidelines, were associated with better sleep quality for Brazilian adolescents, especially girls, and even for those who lived in regions with greater social and economic vulnerability.

Interactions Between Race/Ethnicity and Gender on Physical Activity Among US High School Students: Youth Risk Behavior Survey 2011–2017

Background/purposeMost adolescents do not meet the recommended amount of physical activity. Female, Black, and Hispanic students have significantly less physical activity than White male students. Physical activity of Asian or Multiple Race students have not been reported. The purpose of this research is to estimate differences in physical activity by race/ethnicity and gender among US high school students to examine whether Black Hispanic, Asian and multiple race female students and 11th grade and 12th grade female students have significantly lower physical activity levels. Design/methodsThis study is a secondary analysis of cross-sectional data from the high school Youth Risk Behavior Survey, a biennial, nationally representative survey of US high school students. Four waves of data were pooled from 2011 to 2017 YRBS (N = 59,397). Dependent variables were the number of active days per week a student was physically active, and whether the student was physically active for zero, 5 or more, or 7 days per week. Data were analyzed using R software. ResultsAsian students and students in grade 12 had the fewest number of physically active days per week. Female students were less physically active than male students. Significant negative interactions were measured in female gender by race/ethnicity (Black or Hispanic) and female gender by grade levels for the number of physically active days per week and for zero physically active days per week. The gender disparity in physical activity was significantly more pronounced among Black and Hispanic students. The reduction in physical activity by grade level was also significantly greater among female students. DiscussionEfforts to increase physical activity are especially needed among Asian, Black, and Hispanic, and upper-grade female students. Practical implicationsFurther research is needed to identify explanations and solutions for the significantly lower physical activity among Asians, female minority students, and students in upper grades.

Active Days around Solar Minimum and Solar Cycle Parameter

Utilizing a new version of the sunspot number and group sunspot number dataset available since 2015, we have statistically studied the relationship between solar activity parameters describing solar cycles and the slope of the linear relationship between the monthly sunspot numbers and the monthly number of active days in percentage (AD). As an effort of evaluating possibilities in use of the number of active days to predict solar activity, it is worthwhile to revisit and extend the analysis performed earlier. In calculating the Pearson’s linear correlation coefficient r, the Spearman’s rank-order correlation coefficient rs, and the Kendall’s τ coefficient with the rejection probability, we have calculated the slope for a given solar cycle in three different ways, namely, by counting the spotless day that occurred during the ascending phase and the descending phase of the solar cycle separately, and during the period corresponding to solar minimum ± 2 years as well. We have found that the maximum solar sunspot number of a given solar cycle and the duration of the ascending phase are hardly correlated with the slope of a linear function of the monthly sunspot numbers and AD. On the other hand, the duration of a solar cycle is found to be marginally correlated with the slope with the rejection probabilities less than a couple of percent. We have also attempted to compare the relation of the monthly sunspot numbers with AD for the even and odd solar cycles. It is inconclusive, however, that the slopes of the linear relationship between the monthly group numbers and AD are subject to the even and odd solar cycles.

Duration Estimation Models for Open Source Software Projects

For software organizations that rely on Open Source Software (OSS) to develop customer solutions and products, it is essential to accurately estimate how long it will take to deliver the expected functionalities. While OSS is supported by government policies around the world, most of the research on software project estimation has focused on conventional projects with commercial licenses. OSS effort estimation is challenging since OSS participants do not record effort data in OSS repositories. However, OSS data repositories contain dates of the participants’ contributions and these can be used for duration estimation. This study analyses historical data on WordPress and Swift projects to estimate OSS project duration using either commits or lines of code (LOC) as the independent variable. This study proposes first an improved classification of contributors based on the number of active days for each contributor in the development period of a release. For the WordPress and Swift OSS projects environments the results indicate that duration estimation models using the number of commits as the independent variable perform better than those using LOC. The estimation model for full-time contributors gives an estimate of the total duration, while the models with part-time and occasional contributors lead to better estimates of projects duration with both for the commits data and the lines of data.

A Data Extraction Algorithm from Open Source Software Project Repositories for Building Duration Estimation Models: Case Study of Github

Software project estimation is important for allocating resources and planning a reasonable work schedule. Estimation models are typically built using data from completed projects. While organizations have their historical data repositories, it is difficult to obtaintheir collaboration due to privacy and competitive concerns. To overcome the issue of public access to private data repositories this study proposes an algorithm to extract sufficient data from the GitHub repository for building duration estimation models. More specifically, this study extracts and analyses historical data on WordPress projects to estimate OSS project duration using commits as an independent variable as well as an improved classification of contributors based on the number of active days for each contributor within a release period. The results indicate that duration estimation models using data from OSS repositories perform well and partially solves the problem of lack of data encountered in empirical research in software engineering.

Characteristics of complete tibial fractures in California racehorses.

Tibial fractures cause ~3% of racehorse deaths. Pre-existing stress fractures have been associated with multiple racing and training fractures, but not complete tibial fractures. To describe racehorse tibial fractures and compare signalment and exercise histories of affected and control racehorses. Retrospective analysis of necropsy reports. Racehorses that had a complete tibial fracture (1990-2018) were retrospectively reviewed. Signalment and exercise histories of affected horses were compared to 1) racehorses that died because of non-tibial musculoskeletal injuries or 2) non-musculoskeletal cause and 3) age, sex, event-matched control racehorses. Tibial fracture prevalence was described relative to California racehorses that had at least one official work or race. Age, sex and limb distributions were compared between affected and control horses (Chi-square, Fisher's Exact test). Exercise history data were reduced to counts and rates of official high speed works, races and layups (periods without an official high speed work or race >60days). Variables were compared among groups using matched logistic regression (P≤.05). Tibial fractures in 115 horses (97% unilateral; 50% left, 47% right) occurred most commonly during training (68%) and in 2- to 3-year-old horses (73%). Fractures were predominantly comminuted (93%), diaphyseal (44%) and oblique (40%). Of 61 cases examined for callus, 64% had periosteal callus associated with fracture, most commonly in proximal (65%) and distal diaphyseal (27%) locations. Of 28 racehorses with known exercise history, 57% never raced and 36% had a layup. Affected horses had fewer official-timed works and events (official high speed works and races), number of active days and accumulated less distance in events and works (P<.05) than control horses. Retrospective review of necropsy reports by multiple pathologists over 28years. Tibial fractures were associated with pre-existing stress fracture early in career. Most fractures were associated with proximolateral stress fractures.