What Can the Systems Community Contribute to Ensure the Survival of Civilization

Much of what we need to plan for our survival is already known, but what we know, how we know, and who knows is divided up between disciplines. Thus much of the problem of ensuring our survival is a matter of learning across the disciplines. We identify four modes through which we bring disciplinary knowledge together: the unity of science, integrated assessment, heuristic models, and distributed learning networks. Although none of them are perfect, we can learn how to put our knowledge together across the disciplines much better than we do.     

A maximum likelihood hierarchical disaggregate model for predicting choices of individuals

The absence of operational disaggregate lexicographic decision models and Tversky's observation that choice behavior is often inconsistent, hierarchical, and context dependent motivate the development of a maximum likelihood hierarchical (MLH) choice model. This new disaggregate choice model requires few assumptions and accommodates the three aspects of choice behavior noted by A. Tversky (1972, Journal of Mathematical Psychology, 9, 341–367). The model has its foundation in a prototype model developed by the authors. Unlike the deterministic prototype, however, MLH is a probabilistic model which generates maximum likelihood estimators of the aggregate “cutoff values.” The model is formulated as a concave programming problem whose solutions are therefore globally optimal. Finally, the model is applied to data from three separate studies where it is demonstrated to have superior performance over the prototype model in its predictive performance.     

On optimal smoothing and derivative estimation from noisy displacement data in biomechanics

Estimating derivatives from noisy displacement data is a notoriously ill-posed problem in signal processing and biomechanics. Following the work of Wood and Jennings (1978) and Hatze (1979, 1981), the present paper describes the use of optimally regularized, natural quintic splines for estimating smoothed positions, velocities, and accelerations from equidistantly sampled, noisy position measurements. It appears that the nature of the boundary conditions of the data is of some importance, since various algorithms used hitherto result in artefacts throughout the data if the true derivatives at the record ends differ significantly from zero. Natural quintic splines do not suffer from this disadvantage below the third derivative.The ill-posed character of movement analysis has some interesting implications for movement synthesis and optimization, similar to the indeterminacy of muscular co-contraction from merely external, biomechanical measurements.     

New assessment systems for residential treatment,management, research,and evaluation: A symposium

An introduction and overview are presented to new observational assessment systems for ongoing assessment and monitoring of both staff and resident (client or patient) functioning in residential treatment programs for emotionally disturbed and mentally retarded adults.Preparation of articles and the research and development on which the articles are based was supported, in part, by Public Health Service Grants MH-15553 and MH-25464 from the National Institute of Mental Health, and by grants from the Joyce Foundation and the Illinois Department of Mental Health and Developmental Disabilities.A symposium presented at the 87th Annual Meetings of the American Psychological Association, New York City, September 1979.     

Systems use to objectify program evaluation,clinical, and management decisions

The utility of the observational assessment systems at different levels — from local clinical to systemwide management — is outlined. An overview is provided of TSBC information applied to individualized problem identification and programming/monitoring, discharge and competency determinations, and both absolute and comparative program evaluation. The utility of SRIC information for prgoramming/monitoring and for staff training and evaluation is outlined in addition to the applied uses of the information of the assessment systems in combination. Once implemented, the continuous data from the systems allow for empirically based self-corrective improvements in the quality of mental health services while automatically providing a basis for legal documentation and accurate cost/effectiveness comparisons of mental health programs.Preparation of this article and the research and development on which the article is based were supported, in part, by Public Health Service Grants MH-15553 and MH-25464 from the National Institute of Mental Health, and by grants from The Joyce Foundation and the Illinois Department of Mental Health and Developmental Disabilities.Presented at the 87th Annual Meetings of the American Psychological Association, New York City, September 1979, as part of a symposium on New assessment systems for residential treatment, management, research, and evaluation.     

Practical Implementation Science: Developing and Piloting the Quality Implementation Tool

According to the Interactive Systems Framework for Dissemination and Implementation, implementation is a major mechanism and concern in bridging research and practice. The growing number of implementation frameworks need to be synthesized and translated so that the science and practice of quality implementation can be furthered. In this article, we: (1) use the synthesis of frameworks developed by Meyers et al. (Am J Commun Psychol, 2012) and translate the results into a practical implementation science tool to use for improving quality of implementation (i.e., the Quality Implementation Tool; QIT), and (2) present some of the benefits and limitations of the tool by describing how the QIT was implemented in two different pilot projects. We discuss how the QIT can be used to guide collaborative planning, monitoring, and evaluation of how an innovation is implemented.