Rationale and design: telepsychology service delivery for depressed elderly veterans

BACKGROUND: Older adults who live in rural areas experience significant disparities in health status and access to mental health care. "Telepsychology," (also referred to as "telepsychiatry," or "telemental health") represents a potential strategy towards addressing this longstanding problem. Older adults may benefit from telepsychology due to its: (1) utility to address existing problematic access to care for rural residents; (2) capacity to reduce stigma associated with traditional mental health care; and (3) utility to overcome significant age-related problems in ambulation and transportation. Moreover, preliminary evidence indicates that telepsychiatry programs are often less expensive for patients, and reduce travel time, travel costs, and time off from work. Thus, telepsychology may provide a cost-efficient solution to access-to-care problems in rural areas. METHODS: We describe an ongoing four-year prospective, randomized clinical trial comparing the effectiveness of an empirically supported treatment for major depressive disorder, Behavioral Activation, delivered either via in-home videoconferencing technology ("Telepsychology") or traditional face-to-face services ("Same-Room"). Our hypothesis is that inhome Telepsychology service delivery will be equally effective as the traditional mode (Same-Room). Two-hundred twenty-four (224) male and female elderly participants will be administered protocol-driven individual Behavioral Activation therapy for depression over an 8-week period; and subjects will be followed for 12-months to ascertain longer-term effects of the treatment on three outcomes domains: (1) clinical outcomes (symptom severity, social functioning); (2) process variables (patient satisfaction, treatment credibility, attendance, adherence, dropout); and (3) economic outcomes (cost and resource use). DISCUSSION: Results from the proposed study will provide important insight into whether telepsychology service delivery is as effective as the traditional mode of service delivery, defined in terms of clinical, process, and economic outcomes, for elderly patients with depression residing in rural areas without adequate access to mental health services. TRIAL REGISTRATION: National Institutes of Health Clinical Trials Registry (ClinicalTrials.gov identifier# NCT00324701)

People’s understanding of verbal risk descriptors in patient information leaflets : a cross-sectional national survey of 18- to 65-year-olds in England

Introduction Evidence suggests the current verbal risk descriptors used to communicate side effect risk in patient information leaflets (PILs) are overestimated. Objectives The aim was to establish how people understand the verbal risk descriptors recommended for use in PILs by the European Commission (EC), and alternative verbal risk descriptors, in the context of mild and severe side effects. Methods A cross-sectional online survey was carried out by a market research company recruiting participants aged between 18 and 65 years living in England. Data were collected between 18 March and 1 April 2016. Participants were given a hypothetical scenario regarding the risk of mild or severe medication side effects and asked to estimate how many out of 10,000 people would be affected for each of the verbal risk descriptors being tested. Results A total of 1003 participants were included in the final sample. The risks conveyed by the EC recommended verbal risk descriptors were greatly overestimated by participants. Two distinct distributions were apparent for participant estimates of side effect risks: those for ‘high risk’ verbal descriptors (e.g. ‘common’, ‘likely’, ‘high chance’) and those for ‘low risk’ verbal descriptors (e.g. ‘uncommon’, ‘unlikely’, ‘low chance’). Within these two groups, the distributions were near to identical regardless of what adverb (e.g. very, high, fair) or adjective (e.g. common, likely, chance) was used. The EC recommended verbal risk descriptors were more likely to be understood in accordance with their intended meanings when describing severe side effects. Very few demographic or psychological factors were consistently associated with how well participants understood the EC recommended verbal risk descriptors. Discussion The current verbal risk descriptors used in PILs are ineffective at best and misleading at worst. Discontinuing the use of verbal risk descriptors would limit the likelihood of people overestimating the risk of side effects

Exposure-based cognitive-behavioral treatment of PTSD in adults with schizophrenia or schizoaffective disorder: A pilot study

In an open trial design, adults (n = 20) with posttraumatic stress disorder (PTSD) and either schizophrenia or schizoaffective disorder were treated via an 11-week cognitive-behavioral intervention for PTSD that consisted of education, anxiety management therapy, social skills training, and exposure therapy, provided at community mental health centers. Results offer preliminary hope for effective treatment of PTSD among adults with schizophrenia or schizoaffective disorder, especially among treatment completers (n = 13). Data showed significant PTSD symptom improvement, maintained at 3-month follow-up. Further, 12 of 13 completers no longer met criteria for PTSD or were considered treatment responders. Clinical outcomes for other targeted domains (e.g., anger, general mental health) also improved and were maintained at 3-month follow-up. Participants evidenced high treatment satisfaction, with no adverse events. Significant improvements were not noted on depression, general anxiety, or physical health status. Future directions include the need for randomized controlled trials and dissemination efforts

Psychological factors associated with uptake of the childhood influenza vaccine and perception of post-vaccination side-effects : a cross-sectional survey in England

Objectives To identify predictors of: uptake of the childhood influenza vaccine in the 2015–2016 influenza season, parental perceptions of side-effects from the influenza vaccine and intention to vaccinate one's child for influenza in the 2016–2017 influenza season. Design Cross-sectional online survey. Setting Data were collected in England shortly after the end of the 2015–2016 immunization campaign. Participants 1001 parents or guardians of children aged between two and seven. Main outcome measures Self-reported uptake of the childhood influenza vaccine in the 2015–2016 influenza season, perception of side-effects from the influenza vaccine and intention to vaccinate one's child in the 2016–2017 influenza season. Results Self-reported uptake of the childhood influenza vaccine was 52.8%. Factors strongly positively associated with uptake included the child having previously been vaccinated against influenza, perceiving the vaccine to be effective and perceiving the child to be susceptible to flu. Factors strongly negatively associated with uptake included perceiving the vaccine to be unsafe, to cause short-term side-effects or long-term health problems and believing that yearly vaccination may overload the immune system. Predictors of intended vaccine uptake in 2016–2017 were similar. Participants who perceived side-effects after the 2015–2016 vaccination reported being less likely to vaccinate their child next year. Side-effects were more likely to be reported in first-born children, by participants who knew another child who had side-effects, those who thought that the vaccine would interact with medication that the child was currently taking, and those who believed the vaccine causes short-term side-effects. Conclusions Perceptions about the childhood influenza vaccine show strong associations with uptake, intended uptake and perception of side-effects. Attempts to improve uptake rates from their current low levels must address these perceptions

Production of Magnetic Arsenic–Phosphorus Alloy Nanoribbons with Small Band Gaps and High Hole Conductivities

Quasi-1D nanoribbons provide a unique route to diversifying the properties of their parent 2D nanomaterial, introducing lateral quantum confinement and an abundance of edge sites. Here, a new family of nanomaterials is opened with the creation of arsenic–phosphorus alloy nanoribbons (AsPNRs). By ionically etching the layered crystal black arsenic–phosphorus using lithium electride followed by dissolution in amidic solvents, solutions of AsPNRs are formed. The ribbons are typically few-layered, several micrometers long with widths tens of nanometers across, and both highly flexible and crystalline. The AsPNRs are highly electrically conducting above 130 K due to their small band gap (ca. 0.035 eV), paramagnetic in nature, and have high hole mobilities, as measured with the first generation of AsP devices, directly highlighting their properties and utility in electronic devices such as near-infrared detectors, quantum computing, and charge carrier layers in solar cells

Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants

BACKGROUND: Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU) census. METHODS: A five-step procedure was developed to identify predictive variables. Clinical expert (CE) thought processes comprised one model. Variables from that model were used to develop two mathematical models for the decision-support tool: an artificial neural network (ANN) and a multivariate logistic regression model (MLR). The ranking of the variables in the three models was compared using the Wilcoxon Signed Rank Test. The best performing model was used in a web-based decision-support tool with a user interface implemented in Hypertext Markup Language (HTML) and the mathematical model employing the ANN. RESULTS: CEs identified 51 potentially predictive variables for extubation decisions for an infant on mechanical ventilation. Comparisons of the three models showed a significant difference between the ANN and the CE (p = 0.0006). Of the original 51 potentially predictive variables, the 13 most predictive variables were used to develop an ANN as a web-based decision-tool. The ANN processes user-provided data and returns the prediction 0–1 score and a novelty index. The user then selects the most appropriate threshold for categorizing the prediction as a success or failure. Furthermore, the novelty index, indicating the similarity of the test case to the training case, allows the user to assess the confidence level of the prediction with regard to how much the new data differ from the data originally used for the development of the prediction tool. CONCLUSION: State-of-the-art, machine-learning methods can be employed for the development of sophisticated tools to aid clinicians' decisions. We identified numerous variables considered relevant for extubation decisions for mechanically ventilated premature infants with RDS. We then developed a web-based decision-support tool for clinicians which can be made widely available and potentially improve patient care world wide

Changes in BMI During the COVID-19 Pandemic.

BACKGROUND AND OBJECTIVES: Experts hypothesized increased weight gain in children associated with the coronavirus disease 2019 (COVID-19) pandemic. Our objective was to evaluate whether the rate of change of child body mass index (BMI) increased during the COVID-19 pandemic compared with prepandemic years. METHODS: The study population of 1996 children ages 2 to 19 years with at least 1 BMI measure before and during the COVID-19 pandemic was drawn from 38 pediatric cohorts across the United States participating in the Environmental Influences on Child Health Outcomes-wide cohort study. We modeled change in BMI using linear mixed models, adjusting for age, sex, race, ethnicity, maternal education, income, baseline BMI category, and type of BMI measure. Data collection and analysis were approved by the local institutional review board of each institution or by the central Environmental Influences on Child Health Outcomes institutional review board. RESULTS: BMI increased during the COVID-19 pandemic compared with previous years (0.24 higher annual gain in BMI during the pandemic compared with previous years, 95% confidence interval 0.02 to 0.45). Children with BMI in the obese range compared with the healthy weight range were at higher risk for excess BMI gain during the pandemic, whereas children in higher-income households were at decreased risk of BMI gain. CONCLUSIONS: One effect of the COVID-19 pandemic is an increase in annual BMI gain during the COVID-19 pandemic compared with the 3 previous years among children in our national cohort. This increased risk among US children may worsen a critical threat to public health and health equity

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Sociodemographic Variation in Children's Health Behaviors During the COVID-19 Pandemic

Background: Societal changes during the COVID-19 pandemic may affect children's health behaviors and exacerbate disparities. This study aimed to describe children's health behaviors during the COVID-19 pandemic, how they vary by sociodemographic characteristics, and the extent to which parent coping strategies mitigate the impact of pandemic-related financial strain on these behaviors. Methods: This study used pooled data from 50 cohorts in the Environmental influences on Child Health Outcomes Program. Children or parent proxies reported sociodemographic characteristics, health behaviors, and parent coping strategies. Results: Of 3315 children aged 3-17 years, 49% were female and 57% were non-Hispanic white. Children of parents who reported food access as a source of stress were 35% less likely to engage in a higher level of physical activity. Children of parents who changed their work schedule to care for their children had 82 fewer min/day of screen time and 13 more min/day of sleep compared with children of parents who maintained their schedule. Parents changing their work schedule were also associated with a 31% lower odds of the child consuming sugar-sweetened beverages. Conclusions: Parents experiencing pandemic-related financial strain may need additional support to promote healthy behaviors. Understanding how changes in parent work schedules support shorter screen time and longer sleep duration can inform future interventions