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Women in recovery from substance use disorders (SUD) face significant barriers to achieving reproductive well-being (RWB) and disproportionately experience unintended pregnancy. Unintended pregnancy can have serious consequences in this population. Equity-informed approaches promote the integration of reproductive health care (RHC) with recovery programs to improve both access to and quality of RHC. Arizona’s largest SUD recovery program, Crossroads, Inc. recently opened an on-site, integrated primary clinic offering RHC. A one-month pilot demonstration of One Key Question (OKQ), a pregnancy desire screening tool, was implemented with fidelity at Crossroads to identify clients with RHC needs and offer care.
IRB exempt status was obtained through Arizona State University. All female-bodied clients aged 18-49 were screened following routine admission assessments. The Institute for Healthcare Improvement Triple Aim model based on Self-Determination Theory and Motivational Interviewing was used to prioritize client autonomy. The client experience of care was measured using an adapted Interpersonal Quality of Family Planning scale. The magnitude of needs and desires were summarized with descriptive statistics. Sixty-three clients were screened with OKQ. Needs were identified in 97% of clients. Of those clients, 98% accepted referrals. Ninety percent of items measuring the client experience of care were rated as “excellent.” OKQ provided an efficient structure for person-centered screening and referral conversations to integrate RHC in a large SUD recovery program with excellent care experiences reported by clients.
Hybrid system models - those devised from two or more disparate sub-system models - provide a number of benefits in terms of conceptualization, development, and assessment of dynamical systems. The decomposition approach helps to formulate complex interactions that are otherwise difficult or impractical to express. However, hybrid model development and usage can introduce complexity that emerges from the composition itself.
To improve assurance of model correctness, sub-systems using disparate modeling formalisms must be integrated above and beyond just the data and control level; their composition must have model specification and simulation execution aspects as well. Poly-formalism composition is one approach to composing models in this manner.
This dissertation describes a poly-formalism composition between a Discrete EVent System specification (DEVS) model and a Cellular Automata (CA) model types. These model specifications have been chosen for their broad applicability in important and emerging domains. An agent-environment domain exemplifies the composition approach. The inherent spatial relations within a CA make it well-suited for environmental representations. Similarly, the component-based nature of agents fits well within the hierarchical component structure of DEVS.
This composition employs the use of a third model, called an interaction model, that includes methods for integrating the two model types at a formalism level, at a systems architecture level, and at a model execution level. A prototype framework using DEVS for the agent model and GRASS for the environment has been developed and is described. Furthermore, this dissertation explains how the concepts of this composition approach are being applied to a real-world research project.
This dissertation expands the tool set modelers in computer science and other disciplines have in order to build hybrid system models, and provides an interaction model for an on-going research project. The concepts and models presented in this dissertation demonstrate the feasibility of composition between discrete-event agents and discrete-time cellular automata. Furthermore, it provides concepts and models that may be applied directly, or used by a modeler to devise compositions for other research efforts.