The Impact of Disease-Modifying Therapy Access Barriers on People With Multiple Sclerosis: Mixed-Methods Study.

BACKGROUND: In the United States, people with relapsing-remitting multiple sclerosis (RRMS) can face difficulty accessing disease-modifying therapies (DMTs) because of insurance, pharmacy, or provider policies. These barriers have been associated with poor adherence and negative health outcomes. OBJECTIVE: The goals of this study were to describe the overall occurrence of difficulties and delays associated with gaining access to DMTs among people with RRMS, to assess DMT adherence during periods of reduced access, and to contextualize the patients\u27 journey from receipt of a prescription for DMT to obtaining and taking their medication when faced with access barriers. METHODS: We recruited US-based adults self-reporting RRMS from a Web-based health data-sharing social network, PatientsLikeMe. Individuals were invited to complete a Web-based survey if they reported a diagnosis of RRMS and were prescribed a DMT for MS. Follow-up phone interviews were conducted with 10 respondents who reported experiencing an MS-related relapse during the time they had experienced challenges accessing DMTs. RESULTS: Among 507 survey completers, nearly half were either currently experiencing an issue related to DMT assess or had difficulty accessing a DMT in the past (233/507, 46.0%). The most frequently reported reasons for access difficulty were authorization requirements by insurance companies (past issues: 78/182, 42.9%; current issues: 9/42, 21%) and high out-of-pocket costs (past issues: 54/182, 29.7%; current issues: 13/42, 31%). About half (20/39, 51%) of participants with current access issues and over a third (68/165, 41.2%) of those with past issues went without their medication until they could access their prescribed DMT. Relapses were reported during periods of reduced DMT access for almost half (56/118, 47.5%) of those with past issues and nearly half (22/45, 49%) of those with current issues. Resolving access issues involved multiple stakeholder agents often coordinated in a patient-led effort. Among those who had resolved issues, about half (57/119, 47.9%) reported that doctors or office staff were involved, under half (48/119, 40.3%) were involved themselves, and about a third (39/119, 32.8%) reported the drug manufacturer was involved in resolving the issue. Follow-up interviews revealed that the financial burden associated with obtaining a prescribed DMT led to nonadherence. Additionally, participants felt that DMT treatment delays and stress associated with obtaining the DMT triggered relapses or worsened their MS. CONCLUSIONS: This study expands current research by using a patient-centered, mixed-methods approach to describe barriers to MS treatment, the process to resolve barriers, and the perceived impact of treatment barriers on outcomes. Issues related to DMT access occur frequently, with individuals often serving as their own agents when navigating access difficulties to obtain their medication(s). Support for resolution of DMT access is needed to prevent undue stress and nonadherence

Simulation and validation of injection-compression filling stage of liquid moulding with fast curing resins

Very short manufacture cycle times are required if continuous carbon fibre and epoxy composite components are to be economically viable solutions for high volume composite production for the automotive industry. Here, a manufacturing process variant of resin transfer moulding (RTM), targets a reduction of in-mould manufacture time by reducing the time to inject and cure components. The process involves two stages; resin injection followed by compression. A flow simulation methodology using an RTM solver for the process has been developed. This paper compares the simulation prediction to experiments performed using industrial equipment. The issues encountered during the manufacturing are included in the simulation and their sensitivity to the process is explored

A Theory of Misdiagnosis: A Qualitative Analysis of the Diagnosis Journey for an Ambiguous, Visible Disease With Stigmatizing Symptoms

Thesis (Ph.D.) - Indiana University, Department of Sociology, 2018Misdiagnosis is a serious problem in health care. This dissertation aims to explain why it can take many years to receive a diagnosis for a rare disease despite multiple attempts to seek help for unresolved symptoms. Using theories from social construction, labeling theory, social support, and health care utilization, three broad research questions are answered: 1) How do patients recognize a diagnostic error? 2) How do patients challenge an incorrect diagnostic label? and 3) What are the consequences of getting the right label after going through the process of getting diagnosed? Using as my data set a podcast series of interviews with women who have been diagnosed or suspect they have Cushing's syndrome, qualitative analysis indicates that this process is embedded in social interactions that shape the possibility that a diagnostic error is recognized, challenged, and resolved. These include physician biases, patient illness-related identity, interactions between patients and physicians, and social support. The process of resolving a diagnostic error can be nonlinear and cyclical, requiring multiple attempts by a patient to find doctors familiar with their suspected correct diagnosis and to receive appropriate diagnostic testing and interpretation of tests. This often-protracted process often resulted in new and multiple stressors. These included finding ways to cope with changes in their identity as it related to their health status, managing a disease that could have ongoing uncertainty, navigating a local health care system that may be unfamiliar with how to manage the condition, and finding relevant social support. This dissertation makes both theoretical and methodological contributions to the discipline of sociology and has practical implications for the practice of medicine

Fast Mold Filling Simulation Based on the Geodesic Distance Calculation Algorithm for Liquid Composite Molding Processes

In Liquid Composite Molding (LCM) processes, resin is introduced into a stationary fiber reinforcement placed in the mold, until the reinforcement gets fully saturated with resin and all volatiles are vented out of the part. Finite element based software packages have been developed to simulate the mold filling process and eliminate expensive and tedious trial and error practices to arrive at a successful mold filling without any voids. However, the non-homogeneity of the fiber reinforcement material and its placement and layup in the mold creates a large degree of variability of flow patterns during the resin impregnation process. Executing simulations for every possible permutation of flow scenarios, which is required to devise a robust process design is computationally expensive. Therefore, it is necessary to find faster approximate mold filling simulation methods so that all simulations can be performed within a reasonable time frame. In this paper, a discretized one-dimensional flow model is developed to predict the fill time based on the distance resin travels. Combined with Dijkstra’s algorithm, this model is then implemented on spatial surface meshes to calculate fill time for each node and generate flow development pattern. The computational model developed can predict the mold filling pattern for complex parts even with variable permeability or thickness of the fiber preform, and can capture the disturbed flow behavior along any difficult geometric features at a fraction of the computational cost. Case studies are presented to demonstrate the efficiency and accuracy of the distance-based model

Physics-informed neural networks for resin flow prediction in fibre textiles

Machine learning is a fast-growing area being increasingly applied to engineering problems. The balance between data driven approach and physics-based modelling makes the concept of physics-informed neural networks (PINNs) in general particularly attractive. In this work, we will adopt the PINNs to solve the differential equation system that governs the Newtonian flow in porous media, where Darcy’s law is incorporated with two-phase flow configuration. In order to enable the PINN model to consider physically meaningful parameters, the governing equations are non-dimensionalised. Numerical examples are presented for 2D problems, considering heterogeneous permeability fields that are representative of real-world scenarios. The predictions are compared against a well-established traditional numerical solver

Novel epoxy powder for manufacturing thick-section composite parts under vacuum-bag-only conditions. Part I: Through-thickness process modelling

Thick-section composite parts are difficult to manufacture using thermosetting resins due to their exothermic curing reaction. If processing is not carefully controlled, the build-up of heat can lead to warpage or material degradation. This risk can be reduced or removed with the use of a low-exotherm resin system. Material and process models are presented which describe vacuum-bag-only processing of thick-section composites using a novel, low-exotherm epoxy powder. One-dimensional resin flow and heat transfer models are presented which govern the fabric impregnation and temperature evolution, respectively. A semi-empirical equation is presented which describes the sintering of the epoxy powder. The models are coupled via laminate thickness change, which is determined for a simplified ply microstructure. The resulting system of equations are discretised and solved numerically using a finite difference code. A case study is performed on a 100-ply laminate, and the advantages and disadvantages of using epoxy powders are discussed

Relations of the German almost perfect scale-revised and short almost perfect scale with the big five personality facets

The Almost Perfect Scale-Revised (APS-R) and its short form (SAPS) are among the most-established multidimensional perfectionism measures. Yet, investigations into the APS-R/SAPS nomological networks have mainly been limited to the level of broader personality traits. This reliance on trait-level associations hampers the conceptual understanding of perfectionism traits by masking more complex relations with specific cognitive, emotional, and behavioral tendencies (personality facets). In this study, we validated German versions of the APS-R and SAPS and assessed their relations with the Big Five personality facets in two samples (NSample 1 = 305 university students; NSample 2 = 467 community adults). Both scales displayed satisfactory psychometric properties, convergent and criterion-related validity. Analyses on the level of the Big Five personality facets revealed complex and nuanced patterns of relations. These findings provide new insights into the APS-R and SAPS nomological networks and facilitate the conceptual distinction between the APS-R subscales

A non-local void dynamics modeling and simulation using the Proper Generalized Decomposition

In this work we develop a void filling and void motion dynamics model using volatile pressure and squeeze flow during tape placement process. The void motion and filling are simulated using a non-local model where their presence is reflected in the global macroscale behavior. Local pressure gradients during compression do play a critical role in void dynamics, and hence the need for a non-local model. Deriving a non-local model accounting for all the void motion and dynamics entails a prohibitive number of degrees of freedom, leading to unrealistic computation times with classical solution techniques. Hence, Proper Generalized Decomposition – PGD – is used to solve the aforementioned model. In fact, PGD circumvents the curse of dimensionality by using separated representation of the space coordinates. For example, a 2D problem can be solved as a sequence of 1D problems to find the 2D solution. The non-local model solution sheds light on the fundamental of the void dynamics including their pressure variation, motion and closure mechanisms. Finally, a post treatment of the transient compression of the voids is used to derive conclusions regarding the physics of the void dynamics

Spherical arena reveals optokinetic response tuning to stimulus location, size, and frequency across entire visual field of larval zebrafish

Many animals have large visual fields, and sensory circuits may sample those regions of visual space most relevant to behaviours such as gaze stabilisation and hunting. Despite this, relatively small displays are often used in vision neuroscience. To sample stimulus locations across most of the visual field, we built a spherical stimulus arena with 14,848 independently controllable LEDs. We measured the optokinetic response gain of immobilised zebrafish larvae to stimuli of different steradian size and visual field locations. We find that the two eyes are less yoked than previously thought and that spatial frequency tuning is similar across visual field positions. However, zebrafish react most strongly to lateral, nearly equatorial stimuli, consistent with previously reported spatial densities of red, green and blue photoreceptors. Upside-down experiments suggest further extra-retinal processing. Our results demonstrate that motion vision circuits in zebrafish are anisotropic, and preferentially monitor areas with putative behavioural relevance