A Web-Based Intervention (MotivATE) to Increase Attendance at an Eating Disorder Service Assessment Appointment: Zelen Randomized Controlled Trial.

BACKGROUND: Early assessment and treatment of eating disorder patients is important for patient outcomes. However, up to a third of people referred for treatment do not access services and 16.4% do not attend their first scheduled assessment appointment. MotivATE is a fully automated, novel, Web-based program intended to increase motivation to change eating disorder behaviors, designed for delivery at the point of invitation to an eating disorder service, with the aim of increasing service attendance. OBJECTIVE: This paper assesses the impact of MotivATE on attendance at assessment when compared with treatment-as-usual. METHODS: A Zelen randomized controlled design was used. All individuals referred to a specialist eating disorder service, Kimmeridge Court in Dorset, UK, over the course of a year (October 24, 2016-October 23, 2017) were randomized to treatment-as-usual only or treatment-as-usual plus an additional letter offering access to MotivATE. Attendance at the initial scheduled assessment appointment was documented. Logistic regression analysis assessed the impact of MotivATE on attendance at assessment. Additional analyses based on levels of engagement with MotivATE were also undertaken. RESULTS: A total of 313 participants took part: 156 (49.8%) were randomized to treatment-as-usual and 157 (50.2%) were randomized to receive the additional offer to access MotivATE. Intention-to-treat analysis between conditions showed no impact of MotivATE on attendance at assessment (odds ratio [OR] 1.35, 95% CI 0.69-2.66, P=.38). Examination of the usage data indicated that only 53 of 157 participants (33.8%) in the MotivATE condition registered with the Web-based intervention. An analysis comparing those that registered with the intervention with those that did not found greater attendance at assessment in those that had registered (OR 9.46, 95% CI 1.22-73.38, P=.03). CONCLUSIONS: Our primary analyses suggest no impact of MotivATE on attendance at the first scheduled assessment appointment, but secondary analyses revealed limited engagement with the program and improved attendance in those who did engage. It is unclear, however, if engagement with the program increased motivation and, in turn, attendance or if more motivated individuals were more likely to access the intervention. Further research is required to facilitate engagement with Web-based interventions and to understand the full value of MotivATE for users. TRIAL REGISTRATION: ClinicalTrials.gov NCT02777944; https://clinicaltrials.gov/ct2/show/NCT02777944 (Archived by WebCite at http://www.webcitation.org/75VDEFZZ4)

Coverage, Continuity and Visual Cortical Architecture

The primary visual cortex of many mammals contains a continuous representation of visual space, with a roughly repetitive aperiodic map of orientation preferences superimposed. It was recently found that orientation preference maps (OPMs) obey statistical laws which are apparently invariant among species widely separated in eutherian evolution. Here, we examine whether one of the most prominent models for the optimization of cortical maps, the elastic net (EN) model, can reproduce this common design. The EN model generates representations which optimally trade of stimulus space coverage and map continuity. While this model has been used in numerous studies, no analytical results about the precise layout of the predicted OPMs have been obtained so far. We present a mathematical approach to analytically calculate the cortical representations predicted by the EN model for the joint mapping of stimulus position and orientation. We find that in all previously studied regimes, predicted OPM layouts are perfectly periodic. An unbiased search through the EN parameter space identifies a novel regime of aperiodic OPMs with pinwheel densities lower than found in experiments. In an extreme limit, aperiodic OPMs quantitatively resembling experimental observations emerge. Stabilization of these layouts results from strong nonlocal interactions rather than from a coverage-continuity-compromise. Our results demonstrate that optimization models for stimulus representations dominated by nonlocal suppressive interactions are in principle capable of correctly predicting the common OPM design. They question that visual cortical feature representations can be explained by a coverage-continuity-compromise.Comment: 100 pages, including an Appendix, 21 + 7 figure

Incorporating temporal-bounded CBR techniques in real-time agents

Nowadays, MAS paradigm tries to move Computation to a new level of abstraction: Computation as interaction, where large complex systems are seen in terms of the services they offer, and consequently in terms of the entities or agents providing or consuming services. However, MAS technology is found to be lacking in some critical environments as real-time environments. An interaction-based vision of a real-time system involves the purchase of a responsibility by any entity or agent for the accomplishment of a required service under possibly hard or soft temporal conditions. This vision notably increases the complexity of these kinds of systems. The main problem in the architecture development of agents in real-time environments is with the deliberation process where it is difficult to integrate complex bounded deliberative processes for decision-making in a simple and efficient way. According to this, this work presents a temporal-bounded deliberative case-based behaviour as an anytime solution. More specifically, the work proposes a new temporal-bounded CBR algorithm which facilitates deliberative processes for agents in real-time environments, which need both real-time and deliberative capabilities. The paper presents too an application example for the automated management simulation of internal and external mail in a department plant. This example has allowed to evaluate the proposal investigating the performance of the system and the temporal-bounded deliberative case-based behaviour. 2010 Elsevier Ltd. All rights reserved.This work is supported by TIN2006-14630-C03-01 projects of the Spanish government, GVPRE/2008/070 project, FEDER funds and CONSOLIDER-INGENIO 2010 under Grant CSD2007-00022.Navarro Llácer, M.; Heras Barberá, SM.; Julian Inglada, VJ.; Botti Navarro, VJ. (2011). Incorporating temporal-bounded CBR techniques in real-time agents. Expert Systems with Applications. 38(3):2783-2796. https://doi.org/10.1016/j.eswa.2010.08.070S2783279638

A quantitative analysis of complexity of human pathogen-specific CD4 T cell responses in healthy M. tuberculosis infected South Africans

Author Summary: Human pathogen-specific immune responses are tremendously complex and the techniques to study them ever expanding. There is an urgent need for a quantitative analysis and better understanding of pathogen-specific immune responses. Mycobacterium tuberculosis (Mtb) is one of the leading causes of mortality due to an infectious agent worldwide. Here, we were able to quantify the Mtb-specific response in healthy individuals with Mtb infection from South Africa. The response is highly diverse and 66 epitopes are required to capture 80% of the total reactivity. Our study also show that the majority of the identified epitopes are restricted by multiple HLA alleles. Thus, technical advances are required to capture and characterize the complete pathogen-specific response. This study demonstrates further that the approach combining identified epitopes into "megapools" allows capturing a large fraction of the total reactivity. This suggests that this technique is generally applicable to the characterization of immunity to other complex pathogens. Together, our data provide for the first time a quantitative analysis of the complex pathogen-specific T cell response and provide a new understanding of human infections in a natural infection setting

Constraints on perception of information from obstacles during foot clearance in people with chronic stroke

The aim of this study was to examine effects of different types of task constraints on coupling of perception and action in people with chronic stroke when crossing obstacles during a walking task. Ten participants with hemiplegic chronic stroke volunteered to walk over a static obstacle under two distinct task constraints: simple and dual task. Under simple task constraints, without specific instructions, participants walked at their preferred speed and crossed over an obstacle. Under dual task constraints the same individuals were required to subtract numbers whilst walking. Under both distinct task constraints, we examined emergent values of foot distance when clearing a static obstacle in both affected and unaffected legs, measured by a 3D motion tracking system. Principal Component Analysis was used to quantify task performance and discriminant analysis was used to compare gait performance between task constraints. Results suggested that patients, regardless of affected body side, demonstrated differences in perception of distance information from the obstacle, which constrained gait differences in initial swing, mid-swing and crossing phases. Further, dual task constraints, rather than hemiplegic body side, was a significant discriminator in patients' perceptions of distance and height information to the obstacle. These findings suggested how performance of additional cognitive tasks might constrain perception of information from an obstacle in people with chronic stroke during different phases of obstacle crossing, and thus may impair their adaptive ability to successfully manoeuvre around objects

Inferring learning from big data:The importance of a transdisciplinary and multidimensional approach

The use of big data in higher education has evolved rapidly with a focus on the practical application of new tools and methods for supporting learning. In this paper, we depart from the core emphasis on application and delve into a mostly neglected aspect of the big data conversation in higher education. Drawing on developments in cognate disciplines, we analyse the inherent difficulties in inferring the complex phenomenon that is learning from big datasets. This forms the basis of a discussion about the possibilities for systematic collaboration across different paradigms and disciplinary backgrounds in interpreting big data for enhancing learning. The aim of this paper is to provide the foundation for a research agenda, where differing conceptualisations of learning become a strength in interpreting patterns in big datasets, rather than a point of contention

Beating the blues after Cancer: randomised controlled trial of a tele-based psychological intervention for high distress patients and carers

Background: The diagnosis and treatment of cancer is a major life stress such that approximately 35% of patients experience persistent clinically significant distress and carers often experience even higher distress than patients. This paper presents the design of a two arm randomised controlled trial with patients and carers who have elevated psychological distress comparing minimal contact self management vs. an individualised tele-based cognitive behavioural intervention. Methods/design: 140 patients and 140 carers per condition (560 participants in total) will been recruited after being identified as high distress through caller screening at two community-based cancer helplines and randomised to 1) a single 30-minute telephone support and education session with a nurse counsellor with self management materials 2) a tele-based psychologist delivered five session individualised cognitive behavioural intervention. Session components will include stress reduction, problem-solving, cognitive challenging and enhancing relationship support and will be delivered weekly. Participants will be assessed at baseline and 3, 6 and 12 months after recruitment. Outcome measures include: anxiety and depression, cancer specific distress, unmet psychological supportive care needs, positive adjustment, overall Quality of life. Discussion: The study will provide recommendations about the efficacy and potential economic value of minimal contact self management vs. tele-based psychologist delivered cognitive behavioural intervention to facilitate better psychosocial adjustment and mental health for people with cancer and their carers

Patients with Complex Chronic Diseases: Perspectives on Supporting Self-Management

A Complex Chronic Disease (CCD) is a condition involving multiple morbidities that requires the attention of multiple health care providers or facilities and possibly community (home)-based care. A patient with CCD presents to the health care system with unique needs, disabilities, or functional limitations. The literature on how to best support self-management efforts in those with CCD is lacking. With this paper, the authors present the case of an individual with diabetes and end-stage renal disease who is having difficulty with self-management. The case is discussed in terms of intervention effectiveness in the areas of prevention, addiction, and self-management of single diseases. Implications for research are discussed

A Space-based Observational Strategy for Characterizing the First Stars and Galaxies Using the Redshifted 21 cm Global Spectrum

© 2017. The American Astronomical Society. All rights reserved. The redshifted 21 cm monopole is expected to be a powerful probe of the epoch of the first stars and galaxies (10 < z < 35). The global 21 cm signal is sensitive to the thermal and ionization state of hydrogen gas and thus provides a tracer of sources of energetic photons-primarily hot stars and accreting black holes-which ionize and heat the high redshift intergalactic medium (IGM). This paper presents a strategy for observations of the global spectrum with a realizable instrument placed in a low-altitude lunar orbit, performing night-time 40-120 MHz spectral observations, while on the farside to avoid terrestrial radio frequency interference, ionospheric corruption, and solar radio emissions. The frequency structure, uniformity over large scales, and unpolarized state of the redshifted 21 cm spectrum are distinct from the spectrally featureless, spatially varying, and polarized emission from the bright foregrounds. This allows a clean separation between the primordial signal and foregrounds. For signal extraction, we model the foreground, instrument, and 21 cm spectrum with eigenmodes calculated via Singular Value Decomposition analyses. Using a Markov Chain Monte Carlo algorithm to explore the parameter space defined by the coefficients associated with these modes, we illustrate how the spectrum can be measured and how astrophysical parameters (e.g., IGM properties, first star characteristics) can be constrained in the presence of foregrounds using the Dark Ages Radio Explorer (DARE)