abstract: There is increasing interest in the medical and behavioral health communities towards developing effective strategies for the treatment of chronic diseases. Among these lie adaptive interventions, which consider adjusting treatment dosages over time based on participant response. Control engineering offers a broad-based solution framework for optimizing the effectiveness of such interventions. In this thesis, an approach is proposed to develop dynamical models and subsequently, hybrid model predictive control schemes for assigning optimal dosages of naltrexone, an opioid antagonist, as treatment for a chronic pain condition known as fibromyalgia. System identification techniques are employed to model the dynamics from the daily diary reports completed by participants of a blind naltrexone intervention trial. These self-reports include assessments of outcomes of interest (e.g., general pain symptoms, sleep quality) and additional external variables (disturbances) that affect these outcomes (e.g., stress, anxiety, and mood). Using prediction-error methods, a multi-input model describing the effect of drug, placebo and other disturbances on outcomes of interest is developed. This discrete time model is approximated by a continuous second order model with zero, which was found to be adequate to capture the dynamics of this intervention. Data from 40 participants in two clinical trials were analyzed and participants were classified as responders and non-responders based on the models obtained from system identification. The dynamical models can be used by a model predictive controller for automated dosage selection of naltrexone using feedback/feedforward control actions in the presence of external disturbances. The clinical requirement for categorical (i.e., discrete-valued) drug dosage levels creates a need for hybrid model predictive control (HMPC). The controller features a multiple degree-of-freedom formulation that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed loop system. The nominal and robust performance of the proposed control scheme is examined via simulation using system identification models from a representative participant in the naltrexone intervention trial. The controller evaluation described in this thesis gives credibility to the promise and applicability of control engineering principles for optimizing adaptive interventions. / Dissertation/Thesis / M.S. Electrical Engineering 2011

xiv, 183 p. : ill. (some col.) / Educators are responsible for helping students develop academic and behavior skills and for creating safe environments that promote these outcomes. Achieving these outcomes has become increasingly difficult due to disruptive, anti-social student behavior. Researchers identified Positive Behavioral Interventions and Supports (PBIS) as an evidence-based approach, integrating primary, secondary, and tertiary interventions that provide benefit for students, schools, and educational communities. However, an extensive PBIS literature and research review identified a limited application of PBIS in secondary school settings. The purpose of this dissertation was to broaden the scope of research by examining the impact of PBIS on school-wide discipline outcomes and student academic performance in a secondary school setting using case study methodology. The case study was conducted in a large, urban Pacific Northwest high school that expressed interest in improving the general school expectations and positive interactions between students and staff members. Study participants were members of a student cohort from grade 9 to grade 12. The case study provided a descriptive analysis of students’ social behavior outcomes (as measured by Office Discipline Referrals, Suspensions/ Expulsions, and Attendance Rate) and their academic performance (as measured by students’ Grade Point Averages and Course Credits). An ordered time-series display was applied to analyze behavior and achievement outcome trends. Results showed an increase in students’ Grade Point Average, Course Credits, and Attendance Rate and a decrease in students’ Office Discipline Referrals and Suspensions/ Expulsions. This study’s findings are discussed in the context of its impact on students’ social engagement and academic achievement. Evidence of students’ academic and behavior outcomes has the potential to assist in the development of material and approaches to guide, replicate, and extend current PBIS practices to secondary school settings. / Committee in charge: Dr. Gerald Tindal, Chairperson; Dr. Keith Hollenbeck, Member; Dr. Scott Baker, Member; Dr. K. Brigid Flannery, Member; Dr. Nathaniel Teich, Outside Member

Plusieurs enfants ayant un trouble du spectre de l’autisme (TSA) manifestent des comportements d’autostimulation. Ces comportements peuvent interférer avec l’apprentissage, la socialisation et les comportements adaptatifs. Même si les interventions comportementales sont reconnues efficaces pour réduire les comportements d’autostimulation, ces types d’intervention ne sont pas accessibles à toutes les familles. En réponse à ce problème, ce mémoire vise à évaluer les effets d’iSTIM, une application mobile conçue pour accompagner les parents dans la réduction des comportements d’autostimulation de leur enfant ayant un TSA. Une série de protocoles de recherche AB pour évaluer l’efficacité d’iSTIM sur les comportements d’autostimulation et les comportements appropriés auprès de sept familles. L’utilisation d’iSTIM par les parents a mené à une réduction des comportements d’autostimulation chez six des sept participants et une augmentation des comportements appropriés chez trois des participants. Les résultats indiquent que l’utilisation de la technologie peut être une méthode efficace, peu coûteuse et facilement accessible pour les parents dans le but de réduire les comportements d’autostimulation chez les enfants ayant un TSA. / Many children with ASD engage in stereotypy, which may interfere with learning, socialization as well as adaptive functioning. Although behavioral interventions have been known to effectively reduce stereotypy in children with ASD, these types of interventions are not accessible to all families. In response to this issue, the purpose of our study was to evaluate the effects of the iSTIM, an iOS application designed to support parents in the reduction of stereotypy in their child with ASD. We used a series of AB designs to determine the effectiveness of iSTIM on stereotypy and appropriate behavior in seven families. The use of iSTIM by the parents led to a reduction in stereotypy for six of our seven participants as well as an increase in an alternative appropriate behavior in their three children. Our results indicate that the use of technology may be a cost effective and easily accessible method for parents to reduce stereotypy in children with ASD.

No description available.

This study was designed to test the effectiveness of 2 different behavioral interventions: a high-probability request sequence and a differential reinforcement of alternative behaviors (DRA) procedure in a classroom setting. The aim of the interventions was to reduce the frequency of task refusal as well as increase the frequency of task compliance in adolescents in a general education setting. The study included 4 adolescents with the same teacher who were reported by their teacher as completing 50% or less of their course work since the beginning of the school year. The teacher implemented the interventions with the participants to test their potential effectiveness. Each student responded differently to the interventions. This was demonstrated using visual analysis of graphs as well as a comparison of descriptive statistics. Some were more compliant when the teacher implemented the high-probability request sequence; others demonstrated greater compliance with the DRA in place. Two participants also demonstrated higher levels of compliance beginning with placement of a camera (and operator) prior to the high-probability request sequence or the DRA implementation. These results indicate that each of these interventions may have the potential to increase compliance with classroom tasks for typically functioning adolescents through the mechanism of increased attention.

No description available.

Tiered intervention models have evolved in the last two decades as growing research emphasizes shifting from single-focused tiered systems such as Positive Behavioral Interventions and Support (PBIS) and Response to Intervention (RtI) to the integrated Multi-Tiered Systems of Support (MTSS) framework. In 2015, federal leaders included the general term multi-tiered systems of support in the reauthorization of the Every Student Succeeds Act. However, little is known about how states interpreted this inclusion into their plans or selected the integrated MTSS framework as a highly effective practice. The purpose of this quantitative, descriptive case study was to conduct a comprehensive review of all 52 state departments of education's ESSA Consolidated State Plans to determine the level of inclusion of MTSS in state policy. Specifically, the study identified the inclusion of MTSS as an evidence-based intervention that state educational agencies use to support school divisions in implementing to improve school conditions for learning, improve educators' skills, and provide effective transitions for students. The study examined the degree to which state leaders included technical assistance in implementing MTSS for schools identified for comprehensive or targeted support and improvement. Data collection consisted of downloading approved ESSA plans from state departments of education websites and reviewing each plan using an identical process. Data were categorized and analyzed using descriptive statistics. The analysis found inconsistency and variability in the tiered systems states selected to include in their state ESSA plan. Most states have not fully shifted from using single-focus tiered systems to the integrated MTSS framework. / Doctor of Education / Tiered intervention models have evolved in the last two decades as growing research emphasizes shifting from tiered systems focused on behavior or academics to an integrated framework called Multi-Tiered Systems of Support (MTSS). In 2015, federal leaders included the general term multi-tiered systems of support in the reauthorization of the Every Student Succeeds Act. However, little is known about how states interpreted this inclusion into their plans or included the integrated MTSS framework as an effective practice supported by state leaders. The purpose of this quantitative, descriptive case study was to conduct a comprehensive review of all 52 state departments of education's ESSA Consolidated State Plans to determine the level of inclusion of MTSS in state policy. Specifically, the study identified the inclusion of MTSS as an effective practice that state educational agencies use to support divisions in implementing to improve school conditions for learning, improve educators' skills, and provide effective transitions for students. The study examined the degree to which state leaders included targeted support in implementing MTSS for consistently underperforming schools as defined by the state. Data collection consisted of downloading approved ESSA plans from state departments of education websites and reviewing each plan using an identical process. Data were categorized and analyzed using descriptive statistics. The analysis found inconsistency and variability in the tiered systems states selected to include in their state ESSA plan. Most states have not fully shifted from using single-focus tiered systems to the integrated MTSS framework.

Students with emotional and behavioral disorders (E/BD) have academic deficits that affect their success in school; however, few researchers have investigated what strategies work best for this population, especially in the area of writing. One promising intervention to support the writing skills of students with and at-risk for E/BD is self-regulated strategy development (SRSD). SRSD is a six-stage, explicit strategy instruction model that includes procedures for goal setting, self-monitoring, self-instruction, and self-reinforcement and can be generalized to a variety of writing tasks. The purpose of this study was to determine the effects of an SRSD persuasive writing intervention on the writing achievement of 44 students in a residential school. Results of a piecewise hierarchical linear modeling growth curve analysis suggest statistically significant gains were made over the course of the intervention in writing (quality, correct word sequences, and essay elements) and academic engagement. Effects also generalized to writing achievement measures. In addition, teachers implemented the intervention with high fidelity, and both students and teachers rated the intervention as socially acceptable, with higher ratings postintervention.

Students with emotional and behavioral disorders (E/BD) have academic deficits that affect their success in school; however, few researchers have investigated what strategies work best for this population, especially in the area of writing. One promising intervention to support the writing skills of students with and at-risk for E/BD is self-regulated strategy development (SRSD). SRSD is a six-stage, explicit strategy instruction model that includes procedures for goal setting, self-monitoring, self-instruction, and self-reinforcement and can be generalized to a variety of writing tasks. The purpose of this study was to determine the effects of an SRSD persuasive writing intervention on the writing achievement of 44 students in a residential school. Results of a piecewise hierarchical linear modeling growth curve analysis suggest statistically significant gains were made over the course of the intervention in writing (quality, correct word sequences, and essay elements) and academic engagement. Effects also generalized to writing achievement measures. In addition, teachers implemented the intervention with high fidelity, and both students and teachers rated the intervention as socially acceptable, with higher ratings postintervention.

abstract: Cigarette smoking remains a major global public health issue. This is partially due to the chronic and relapsing nature of tobacco use, which contributes to the approximately 90% quit attempt failure rate. The recent rise in mobile technologies has led to an increased ability to frequently measure smoking behaviors and related constructs over time, i.e., obtain intensive longitudinal data (ILD). Dynamical systems modeling and system identification methods from engineering offer a means to leverage ILD in order to better model dynamic smoking behaviors. In this dissertation, two sets of dynamical systems models are estimated using ILD from a smoking cessation clinical trial: one set describes cessation as a craving-mediated process; a second set was reverse-engineered and describes a psychological self-regulation process in which smoking activity regulates craving levels. The estimated expressions suggest that self-regulation more accurately describes cessation behavior change, and that the psychological self-regulator resembles a proportional-with-filter controller. In contrast to current clinical practice, adaptive smoking cessation interventions seek to personalize cessation treatment over time. An intervention of this nature generally reflects a control system with feedback and feedforward components, suggesting its design could benefit from a control systems engineering perspective. An adaptive intervention is designed in this dissertation in the form of a Hybrid Model Predictive Control (HMPC) decision algorithm. This algorithm assigns counseling, bupropion, and nicotine lozenges each day to promote tracking of target smoking and craving levels. Demonstrated through a diverse series of simulations, this HMPC-based intervention can aid a successful cessation attempt. Objective function weights and three-degree-of-freedom tuning parameters can be sensibly selected to achieve intervention performance goals despite strict clinical and operational constraints. Such tuning largely affects the rate at which peak bupropion and lozenge dosages are assigned; total post-quit smoking levels, craving offset, and other performance metrics are consequently affected. Overall, the interconnected nature of the smoking and craving controlled variables facilitate the controller's robust decision-making capabilities, even despite the presence of noise or plant-model mismatch. Altogether, this dissertation lays the conceptual and computational groundwork for future efforts to utilize engineering concepts to further study smoking behaviors and to optimize smoking cessation interventions. / Dissertation/Thesis / Doctoral Dissertation Bioengineering 2014