Research That Matters (January 17 - 20, 2008)


Cabinet Room (Omni Shoreham)

Advancing a Complexity Model for Social Service Inquiry

Michael Wolf-Branigin, PhD, George Mason University.

Purpose and Background: Within social work, complexity science as a model of inquiry has not reached paradigm status (Kuhn, 1970). While the past decade has seen an increase in the number of scholarly articles discussing and applying complexity theory (Bolland & Atherton, 1999; Hudson, 2000; Trevillon, 2000; Hudson 2004), practical applications and related methodologies received minimal attention. Recent evaluation publications have enhanced this growing interest in complex systems evaluation and the related developmental evaluation (Westley, Zimmerman & Patton, 2006). Complexity theory and successful social service practice share several assumptions. These include: 1) sensitivity to initial conditions, 2) decisions should come from the client level or grass roots level, 3) attractors are instrumental in clients maintaining interest and completing interventions, 4) client and organizational feedback are vital to improving outcomes and organizational performance, and 5) self-organization leads to an emergent behavior. I discuss three social work applications using a complexity framework to measure program efforts. The methodology requires that we first deconstruct social service interventions into several components, including it being agent-based, provides a choice of options, occurs within an organization, uses feedback, allows for self-organization, and produces an emergent behavior (Morowitz, 2002). This presentation poses the research question: Can complexity provide a promising paradigm for social work inquiry?

Applications: The three applications represent the flexibility of the complexity framework as applied to social program evaluation. The first application analyzed housing patterns of persons with an intellectual or developmental disability by using a computational intensive simulation approach in order to identify how a set of variables (size of home, presence of earned income, proximity to public transportation, and level of family/advocate support) produced an emergent behavior as represented by spatial autocorrelation. The second application used a qualitative complexity framework to identify barriers toward building organizational capacity when working with victims of human trafficking. The third application applied complexity's concept of emergence to understand the successes resulting from President Kennedy's efforts on the deinstitutionalization of persons with intellectual and developmental disabilities movement in the 1960s.

Considerations for Social Program Evaluators: Applying a complexity framework appears to provide a promising overarching approach to viewing social work phenomena in a variety of settings. Given the increasing availability of evaluation tools and computing power and speed, such an approach to social work inquiry has a widening appeal and applicability to analyzing quantitative (numerical) and qualitative (non-numerical) data. Complexity models work best with longitudinal and spatial data while being applicable to non-experimental data sets. Because complexity encourages the use of an iterative process and a priori information contained in management information systems, it generates multi-dimensional perspectives. Future efforts in developing complexity applications should include defining a concise set of prompts for defining the components, outlining appropriate statistical procedures to analyze the data, and creating agent-based modeling procedures for program planners and evaluators.