Evaluation of a temporal causal model for predicting the mood of clients in an online therapy

Background Self-reported client assessments during online treatments enable the development of statistical models for the prediction of client improvement and symptom development. Evaluation of these models is mandatory to ensure their validity. Methods For this purpose, we suggest besides a model evaluation based on study data the use of a simulation analysis. The simulation analysis provides insight into the model performance and enables to analyse reasons for a low predictive accuracy. In this study, we evaluate a temporal causal model (TCM) and show that it does not provide reliable predictions of clients' future mood levels. Results Based on the simulation analysis we investigate the potential reasons for the low predictive performance, for example, noisy measurements and sampling frequency. We conclude that the analysed TCM in its current form is not sufficient to describe the underlying psychological processes. Conclusions The results demonstrate the importance of model evaluation and the benefit of a simulation analysis. The current manuscript provides practical guidance for conducting model evaluation including simulation analysis

A framework for applying natural language processing in digital health interventions

BACKGROUND: Digital health interventions (DHIs) are poised to reduce target symptoms in a scalable, affordable, and empirically supported way. DHIs that involve coaching or clinical support often collect text data from 2 sources: (1) open correspondence between users and the trained practitioners supporting them through a messaging system and (2) text data recorded during the intervention by users, such as diary entries. Natural language processing (NLP) offers methods for analyzing text, augmenting the understanding of intervention effects, and informing therapeutic decision making. OBJECTIVE: This study aimed to present a technical framework that supports the automated analysis of both types of text data often present in DHIs. This framework generates text features and helps to build statistical models to predict target variables, including user engagement, symptom change, and therapeutic outcomes. METHODS: We first discussed various NLP techniques and demonstrated how they are implemented in the presented framework. We then applied the framework in a case study of the Healthy Body Image Program, a Web-based intervention trial for eating disorders (EDs). A total of 372 participants who screened positive for an ED received a DHI aimed at reducing ED psychopathology (including binge eating and purging behaviors) and improving body image. These users generated 37,228 intervention text snippets and exchanged 4285 user-coach messages, which were analyzed using the proposed model. RESULTS: We applied the framework to predict binge eating behavior, resulting in an area under the curve between 0.57 (when applied to new users) and 0.72 (when applied to new symptom reports of known users). In addition, initial evidence indicated that specific text features predicted the therapeutic outcome of reducing ED symptoms. CONCLUSIONS: The case study demonstrates the usefulness of a structured approach to text data analytics. NLP techniques improve the prediction of symptom changes in DHIs. We present a technical framework that can be easily applied in other clinical trials and clinical presentations and encourage other groups to apply the framework in similar contexts

Des Moines Area Community College Creative Writing Contest 1976-2001

Award-Winning Works For the Academic Year · 2000-2001https://openspace.dmacc.edu/creativewriting/1002/thumbnail.jp

Combining serological and contact data to derive target immunity levels for achieving and maintaining measles elimination

AbstractBackgroundVaccination has reduced the global incidence of measles to the lowest rates in history. However, local interruption of measles virus transmission requires sustained high levels of population immunity that can be challenging to achieve and maintain. The herd immunity threshold for measles is typically stipulated at 90–95%. This figure does not easily translate into age-specific immunity levels required to interrupt transmission. Previous estimates of such levels were based on speculative contact patterns based on historical data from high-income countries. The aim of this study was to determine age-specific immunity levels that would ensure elimination of measles when taking into account empirically observed contact patterns.MethodsWe combined estimated immunity levels from serological data in 17 countries with studies of age-specific mixing patterns to derive contact-adjusted immunity levels. We then compared these to case data from the 10 years following the seroprevalence studies to establish a contact-adjusted immunity threshold for elimination. We lastly combined a range of hypothetical immunity profiles with contact data from a wide range of socioeconomic and demographic settings to determine whether they would be sufficient for elimination.ResultsWe found that contact-adjusted immunity levels were able to predict whether countries would experience outbreaks in the decade following the serological studies in about 70% of countries. The corresponding threshold level of contact-adjusted immunity was found to be 93%, corresponding to an average basic reproduction number of approximately 14. Testing different scenarios of immunity with this threshold level using contact studies from around the world, we found that 95% immunity would have to be achieved by the age of five and maintained across older age groups to guarantee elimination. This reflects a greater level of immunity required in 5–9 year olds than established previously.ConclusionsThe immunity levels we found necessary for measles elimination are higher than previous guidance. The importance of achieving high immunity levels in 5–9 year olds presents both a challenge and an opportunity. While such high levels can be difficult to achieve, school entry provides an opportunity to ensure sufficient vaccination coverage. Combined with observations of contact patterns, further national and sub-national serological studies could serve to highlight key gaps in immunity that need to be filled in order to achieve national and regional measles elimination.</jats:sec

Ongoing Fixed Wing Research within the NASA Langley Aeroelasticity Branch

The NASA Langley Aeroelasticity Branch is involved in a number of research programs related to fixed wing aeroelasticity and aeroservoelasticity. These ongoing efforts are summarized here, and include aeroelastic tailoring of subsonic transport wing structures, experimental and numerical assessment of truss-braced wing flutter and limit cycle oscillations, and numerical modeling of high speed civil transport configurations. Efforts devoted to verification, validation, and uncertainty quantification of aeroelastic physics in a workshop setting are also discussed. The feasibility of certain future civil transport configurations will depend on the ability to understand and control complex aeroelastic phenomena, a goal that the Aeroelasticity Branch is well-positioned to contribute through these programs

An Analysis of Tropical Transport: Influence of the Quasi-biennial Oscillation

An analysis of over 4 years of Upper Atmosphere Research Satellite (UARS) measurements of CH4, HF, O3, and zonal wind are used to study the influence of the quasi-biennial oscillation (QBO) on constituent transport in the tropics. At the equator, spectral analysis of the Halogen Occultation Experiment (HALOE) and Microwave Limb Sounder (MLS) observations reveals QBO signals in constituent and temperature fields at altitudes between 20 and 45 km. Between these altitudes, the location of the maximum QBO amplitude roughly corresponds with the location of the largest vertical gradient in the constituent field. Thus, at 40 km where CH4 and HF have strong vertical gradients, QBO signals are correspondingly large, while at lower altitudes where the vertical gradients are weak, so are the QBO variations. Similarly, ozone, which is largely under dynamical control below 30 km in the tropics, has a strong QBO signal in the region of sharp vertical gradients (∼28 km) below the ozone peak. Above 35 km, annual and semi-annual variations are also found to be important components of the variability of long-lived tracers. Therefore, above 30 km, the variability in CH4 and HF at the equator is represented by a combination of semiannual, annual, and QBO timescales. A one-dimensional vertical transport model is used to further investigate the influence of annual and QBO variations on tropical constituent fields. QBO-induced vertical motions are calculated from observed high resolution Doppler imager (HRDI) zonal winds at the equator, while the mean annually varying tropical ascent rate is obtained from the Goddard two-dimensional model. Model simulations of tropical CH4 confirm the importance of both the annual cycle and the QBO in describing the HALOE CH4 observations above 30 km. Estimates of the tropical ascent rate and the variation due to the annual cycle and QBO are also discussed

Decreased Exercise-Induced Changes in Prefrontal Cortex Hemodynamics Are Associated With Depressive Symptoms

People with a depressed mood tend to perform poorly on executive function tasks, which require much of the prefrontal cortex (PFC), an area of the brain which has also been shown to be hypo-active in this population. Recent research has suggested that these aspects of cognition might be improved through physical activity and cognitive training. However, whether the acute effects of exercise on PFC activation during executive function tasks vary with depressive symptoms remains unclear. To investigate these effects, 106 participants were given a cardiopulmonary exercise test (CPET) and were administered a set of executive function tests directly before and after the CPET assessment. The composite effects of exercise on the PFC (all experimental blocks) showed bilateral activation changes in dorsolateral (BA46/9) and ventrolateral (BA44/45) PFC, with the greatest changes occurring in rostral PFC (BA10). The effects observed in right ventrolateral PFC varied depending on level of depressive symptoms (13% variance explained); the changes in activation were less for higher levels. There was also a positive relationship between CPET scores (VO2peak) and right rostral PFC, in that greater activation changes in right BA10 were predictive of higher levels of aerobic fitness (9% variance explained). Since acute exercise ipsilaterally affected this PFC subregion and the inferior frontal gyrus during executive function tasks, this suggests physical activity might benefit the executive functions these subregions support. And because physical fitness and depressive symptoms explained some degree of cerebral upregulation to these subregions, physical activity might more specifically facilitate the engagement of executive functions that are typically associated with hypoactivation in depressed populations. Future research might investigate this possibility in clinical populations, particularly the neural effects of physical activity used in combination with mental health interventions