Stepping up early treatment for help-seeking youth with at-risk mental states: Feasibility and acceptability of a real-world exercise program.

INTRODUCTION: Youth with at-risk mental states (ARMS) have low levels of physical activity (PA), reduced fitness levels and experience poor sleep quality. These lifestyle factors exacerbate mental health symptoms and increase cardiometabolic disease risk. PA interventions can help prevent this decline in physical health whilst reducing mental health symptom severity. Whether PA interventions are feasible and acceptable amongst youth with ARMS is unclear. METHODS: This study evaluated the feasibility and acceptability of headspace Active, a pragmatic PA program offered to 14 to 25 year olds with ARMS. The 12-week exercise physiologist-led intervention was conducted in adjunct to usual care. Feasibility was determined by number of referrals, attendance, engagement in exercise sessions and dropout from the intervention. Acceptability was assessed by a 10-item questionnaire. Secondary outcomes included anthropometry, cardiorespiratory fitness and strength. Subjective PA levels, symptoms of depression and anxiety, sleep, motivation and quality of life were also assessed. RESULTS: Within 12 months, 77% of referrals completed the 12-week intervention (n = 20), with six dropouts. Of the 20 "completers", 95% attended at least five sessions over the 12-week intervention. Participants found the program highly acceptable (mean = 41.2/50 on the 10-item acceptability questionnaire) and experienced significant improvements in PA, strength, motivation, depressive symptoms and sleep quality post-intervention. No changes in anthropometry were observed. CONCLUSION: Results suggest headspace Active was feasible and acceptable and was associated with improvements in physical and mental health outcomes among ARMS youth. Given the potential scalability of this real-world PA program to other youth mental health settings, these data have implications for best practice implementation of PA interventions for individuals with emerging mental illness.

Modifiable cardiometabolic risk factors in youth with at-risk mental states: A cross-sectional pilot study.

Young people experiencing psychotic illness engage in low amounts of physical activity have poor fitness levels and poor sleep quality. This study aimed to determine the prevalence of these modifiable cardiometabolic risk factors among individuals with at-risk mental states (ARMS), who are at increased risk of developing psychosis. A cross-sectional study was conducted in a community-based youth mental health service. Thirty participants (23%♀, 21.3 ± 1.7 years old) were recruited, 10 with ARMS, 10 with first-episode psychosis (FEP) and 10 healthy volunteers. Physical activity levels were assessed using self-report and objective measures. Aerobic capacity, upper body strength, hamstring flexibility, forearm grip strength and core endurance were assessed. Sleep quality, depression and anxiety were measured by self-report questionnaire. The ARMS group did not differ significantly on anthropometric measures from FEP or healthy volunteers. They engaged in significantly less physical activity (p < 0.05) and had poorer sleep quality (p < 0.05) than healthy volunteers. Our results are consistent with other studies that found that youth with ARMS are at greater cardiometabolic risk. Interventions aimed at improving these modifiable risk factors may assist with preventing the decline in physical health associated with the development of psychiatric illness.

JATSPack and JATSPAN, a packaging format and infrastructure for the NLM/NISO Journal Archiving Tag Suite (JATS).

The NISO Journal Archiving Tag Suite (JATS, formerly known as 'the NLM DTD') is a common format used in publication of scientific literature. JATSPack, a proposal based on the new EXPath Packaging System, provides a way to package schema customizations and software libraries associated with any of the JATS schemas, thus making it easier for developers to distribute JATS-related resources and easier for users to acquire, install, and use them. JATSPAN (the JATSPack Archive Network) is a website allowing users to share and collaborate on JATSPacks. A client-side command line tool, jatspan, interacts with the site and eases the task of maintaining local repositories of JATSPacks.

Predicting the start week of respiratory syncytial virus outbreaks using real time weather variables.

BACKGROUND: Respiratory Syncytial Virus (RSV), a major cause of bronchiolitis, has a large impact on the census of pediatric hospitals during outbreak seasons. Reliable prediction of the week these outbreaks will start, based on readily available data, could help pediatric hospitals better prepare for large outbreaks. METHODS: Naïve Bayes (NB) classifier models were constructed using weather data from 1985-2008 considering only variables that are available in real time and that could be used to forecast the week in which an RSV outbreak will occur in Salt Lake County, Utah. Outbreak start dates were determined by a panel of experts using 32,509 records with ICD-9 coded RSV and bronchiolitis diagnoses from Intermountain Healthcare hospitals and clinics for the RSV seasons from 1985 to 2008. RESULTS: NB models predicted RSV outbreaks up to 3 weeks in advance with an estimated sensitivity of up to 67% and estimated specificities as high as 94% to 100%. Temperature and wind speed were the best overall predictors, but other weather variables also showed relevance depending on how far in advance the predictions were made. The weather conditions predictive of an RSV outbreak in our study were similar to those that lead to temperature inversions in the Salt Lake Valley. CONCLUSIONS: We demonstrate that Naïve Bayes (NB) classifier models based on weather data available in real time have the potential to be used as effective predictive models. These models may be able to predict the week that an RSV outbreak will occur with clinical relevance. Their clinical usefulness will be field tested during the next five years.

Use of a Web-based game to teach pediatric content to medical students.

OBJECTIVE: The aim of this study was to assess, using a Web-based format, third-year medical students' pediatric knowledge and perceptions of game playing with faculty facilitation compared with self-study computerized flash cards. METHODS: This study used a repeated-measures experimental design with random assignment to a game group or self-study group. Pediatric knowledge was tested using multiple choice exams at baseline, week 6 of the clerkship following a 4-week intervention, and 6 weeks later. Perceptions about game playing and self-study were evaluated using a questionnaire at week 6. RESULTS: The groups did not differ on content mastery, perceptions about content, or time involved in game playing or self-study. Perceptions about game playing versus self-study as a pedagogical method appeared to favor game playing in understanding content (P<.001), perceived help with learning (P<.05), and enjoyment of learning (P<.008). An important difference was increased game group willingness to continue participating in the intervention. CONCLUSIONS: Games can be an enjoyable and motivating method for learning pediatric content, enhanced by group interactions, competition, and fun. Computerized, Web-based tools can facilitate access to educational resources and are feasible to apply as an adjunct to teaching clinical medicine.

Forecasting hospital census at a tertiary care children's hospital.

Developing a forecasting tool for patient census allows for improved staffing, better resource utilization and mobilization, and improved timing of educational campaigns around the disease control process. Using a neural network approach we evaluated several different models and variables for predicting patient census prospectively. These initial studies enabled selection of a subset of predictor variables and show that different network models, and variables must be used based on the season.

Site-specific changes in the expression of fat-partitioning genes in weanling rats exposed to a low-protein diet in utero.

OBJECTIVE: Intrauterine growth restriction is associated with increased prevalence of the metabolic syndrome in adult life, including increased adiposity. The aim of this study was to investigate if maternal protein energy malnutrition is associated with changes in expression of genes involved in fat partitioning in weanling rats. RESEARCH METHODS AND PROCEDURES: Time-mated mothers were placed on one of two isocaloric diets, low protein [(LP), 8% protein] or control (20% protein). All mothers remained on the diet throughout pregnancy and lactation. A third group received control for 2 weeks and was switched to LP for the last week of pregnancy and lactation [late low protein (LLP) group]. Offspring were analyzed at weaning for serum glucose, nonesterified fatty acids, triglyceride, and insulin. Expression of the genes acetyl-coenzyme A carboxylase, fatty acid synthase, and carnitine palmitoyl transferase 1 were measured in liver, quadriceps muscle, and subcutaneous white adipose tissue using semiquantitative reverse transcription-polymerase chain reaction. RESULTS: LLP and LP offspring were shorter, weighed less, had reduced serum insulin and nonesterified fatty acids, and had increased serum glucose, serum triglycerides, and hepatic triglycerides. Hepatic gene expression of acetyl-coenzyme A carboxylase and fatty acid synthase was increased 2-fold in LLP and LP offspring (p < 0.001). These changes were not seen in muscle or subcutaneous white adipose tissue. CPT-1 gene expression was unaltered in all tissues examined. DISCUSSION: Maternal protein energy malnutrition programs gene expression of lipogenic enzymes in the liver of weanling offspring in a manner favoring fat synthesis that may predispose these offspring to fat accumulation and insulin resistance later in life.

Internet-based standardized patient simulation with automated feedback.

There exist many modalities for teaching and testing medical students. One method being explored is computer-based patient simulation. Traditionally, exposure to a variety of patients has been achieved through years of training under the supervision of experts in the field. Computerized patient simulation has been proposed as a method of creating a standardized patient care experience through algorithms and predefined patient findings. One study reported that after experience with computer-based simulation, 80% of students and mentors felt that it should be a mandatory part of medical education. Access to effective simulations with high-yield cases can be costly. Internet-based tools enjoy easy distribution and centralized maintenance. Simulations distributed via the Internet have proven successful in selected medical fields. Automated scoring of patient interactions has also been proposed as a way to eliminate the effort required for mentor evaluation.