Neural networks and dynamical systems

AbstractModels for the identification and control of nonlinear dynamical systems using neural networks were introduced by Narendra and Parthasarathy in 1990, and methods for the adjustment of model parameters were also suggested. Simulation results of simple nonlinear systems were presented to demonstrate the feasibility of the schemes proposed. The concepts introduced at that time are investigated in this paper in greater detail. In particular, a number of questions that arise when the methods are applied to more complex systems are addressed. These include nonlinear systems of higher order as well as multivariable systems. The effect of using simpler models for both identification and control are discussed, and a new controller structure containing a linear part in addition to a multilayer neural network is introduced

Enhancing the reporting of implementation research

In the 10 years since the inception of Implementation Science, we have witnessed a continued rise in the number of submissions received, reflecting the continued global interest in methods to enhance the uptake of research findings into healthcare practice and policy. We receive over 750 submissions annually, and there is now a large gap between what is submitted and what gets published. In this editorial, we restate the journal scope and current boundaries. We also identify some specific reporting issues that if addressed will help enhance the scientific reporting quality and transparency of the manuscripts we receive. We hope that this editorial acts as a further guide to researchers seeking to publish their work in Implementation Science

Observational measure of implementation progress in community based settings: The Stages of implementation completion (SIC)

<p>Abstract</p> <p>Background</p> <p>An increasingly large body of research is focused on designing and testing strategies to improve knowledge about how to embed evidence-based programs (EBP) into community settings. Development of strategies for overcoming barriers and increasing the effectiveness and pace of implementation is a high priority. Yet, there are few research tools that measure the implementation process itself. The Stages of Implementation Completion (SIC) is an observation-based measure that is used to track the time to achievement of key implementation milestones in an EBP being implemented in 51 counties in 53 sites (two counties have two sites) in two states in the United States.</p> <p>Methods</p> <p>The SIC was developed in the context of a randomized trial comparing the effectiveness of two implementation strategies: community development teams (experimental condition) and individualized implementation (control condition). Fifty-one counties were randomized to experimental or control conditions for implementation of multidimensional treatment foster care (MTFC), an alternative to group/residential care placement for children and adolescents. Progress through eight implementation stages was tracked by noting dates of completion of specific activities in each stage. Activities were tailored to the strategies for implementing the specific EBP.</p> <p>Results</p> <p>Preliminary data showed that several counties ceased progress during pre-implementation and that there was a high degree of variability among sites in the duration scores per stage and on the proportion of activities that were completed in each stage. Progress through activities and stages for three example counties is shown.</p> <p>Conclusions</p> <p>By assessing the attainment time of each stage and the proportion of activities completed, the SIC measure can be used to track and compare the effectiveness of various implementation strategies. Data from the SIC will provide sites with relevant information on the time and resources needed to implement MTFC during various phases of implementation. With some modifications, the SIC could be appropriate for use in evaluating implementation strategies in head-to-head randomized implementation trials and as a monitoring tool for rolling out other EBPs.</p

The meaning and measurement of implementation climate

<p>Abstract</p> <p>Background</p> <p>Climate has a long history in organizational studies, but few theoretical models integrate the complex effects of climate during innovation implementation. In 1996, a theoretical model was proposed that organizations could develop a positive climate for implementation by making use of various policies and practices that promote organizational members' means, motives, and opportunities for innovation use. The model proposes that implementation climate--or the extent to which organizational members perceive that innovation use is expected, supported, and rewarded--is positively associated with implementation effectiveness. The implementation climate construct holds significant promise for advancing scientific knowledge about the organizational determinants of innovation implementation. However, the construct has not received sufficient scholarly attention, despite numerous citations in the scientific literature. In this article, we clarify the meaning of implementation climate, discuss several measurement issues, and propose guidelines for empirical study.</p> <p>Discussion</p> <p>Implementation climate differs from constructs such as organizational climate, culture, or context in two important respects: first, it has a strategic focus (implementation), and second, it is innovation-specific. Measuring implementation climate is challenging because the construct operates at the organizational level, but requires the collection of multi-dimensional perceptual data from many expected innovation users within an organization. In order to avoid problems with construct validity, assessments of within-group agreement of implementation climate measures must be carefully considered. Implementation climate implies a high degree of within-group agreement in climate perceptions. However, researchers might find it useful to distinguish implementation climate level (the average of implementation climate perceptions) from implementation climate strength (the variability of implementation climate perceptions). It is important to recognize that the implementation climate construct applies most readily to innovations that require collective, coordinated behavior change by many organizational members both for successful implementation and for realization of anticipated benefits. For innovations that do not possess these attributes, individual-level theories of behavior change could be more useful in explaining implementation effectiveness.</p> <p>Summary</p> <p>This construct has considerable value in implementation science, however, further debate and development is necessary to refine and distinguish the construct for empirical use.</p

Enhancing assertive community treatment with cognitive behavioral social skills training for schizophrenia: study protocol for a randomized controlled trial

BACKGROUND: Schizophrenia leads to profound disability in everyday functioning (e.g., difficulty finding and maintaining employment, housing, and personal relationships). Medications can effectively reduce positive symptoms (e.g., hallucinations and delusions), but they do not meaningfully improve daily life functioning. Psychosocial evidence-based practices (EBPs) improve functioning, but these EBPs are not available to most people with schizophrenia. The field must close the research and service delivery gap by adapting EBPs for schizophrenia to facilitate widespread implementation in community settings. Our hybrid effectiveness and implementation study represents an initiative to bridge this divide. In this study we will test whether an existing EBP (i.e., Cognitive Behavioral Social Skills Training (CBSST)) modified to work in practice settings (i.e., Assertive Community Treatment (ACT) teams) commonly available to persons with schizophrenia results in better consumer outcomes. We will also identify key factors relevant to developing future CBSST implementation strategies. METHODS/DESIGN: For the effectiveness study component, persons with schizophrenia will be recruited from existing publicly funded ACT teams operating in community settings. Participants will be randomized to one of the 2 treatments (ACT alone or ACT + Adapted CBSST) and followed longitudinally for 18 months with assessments every 18 weeks after baseline (5 in total). The primary outcome domain is psychosocial functioning (e.g., everyday living skills and activities related to employment, education, and housing) as measured by self-report, testing, and observation. Additional outcome domains of interest include mediators of change in functioning, symptoms, and quality of services. Primary analyses will be conducted using linear mixed-effects models for continuous data. The implementation study component consists of a structured, mixed qualitative-quantitative methodology (i.e., Concept Mapping) to characterize and assess the implementation experience from multiple stakeholder perspectives in order to inform future implementation initiatives. DISCUSSION: Adapting CBSST to fit into the ACT service delivery context found throughout the United States creates an opportunity to substantially increase the number of persons with schizophrenia who could have access to and benefit from EBPs. As part of the implementation learning process training materials and treatment workbooks have been revised to promote easier use of CBSST in the context of brief community-based ACT visits. TRIAL REGISTRATION: ClinicalTrials.gov NCT02254733. Date of registration: 25 April 2014