Brian Castellani

A comparison of pathological gamblers to alcoholics and cocaine misusers on impulsivity, sensation seeking, and craving.

Consecutive admissions (N = 843) to the Brecksville Veterans Addiction Recovery Center with a primary diagnosis of pathological gambler, alcoholic, or cocaine misuser were compared for differences on impulsivity, sensation seeking, and craving. In contrast to alcoholics and cocaine misusers, gamblers scored significantly higher on impulsivity and inability to resist craving; however, gamblers were not significantly higher than either alcoholics or cocaine misusers on sensation seeking. These findings suggest a need to address high impulsivity and inability to resist cravings in treatment and relapse prevention for gamblers.

Sociology and Complexity Science

SACS Toolkit#x2014 Theoretical Framework.- SACS Toolkit#x2014 Assemblage.- Overview of SACS.- Environmental Forces.- Five Areas of Research.- The System of SACS.- SACS Today.- Conclusion.- Mapping Complexity.

The increasing complexities of professionalism.

Organized medicines modern-day professionalism movement has reached the quarter-century mark. In this article, the authors travel to an earlier time to examine the concept of profession within the work of Abraham Flexner. Although Flexner used the concept sparingly, it is clear that much of his writing on reforming medical education is grounded in his views on physicians as professionals and medicine as a profession. In the first half, the authors explore Flexners views of profession, which were (1) empirically (as opposed to philosophically) grounded, (2) case based and comparatively framed, (3) sociological in orientation, and (4) systems based, with professionalism conceptualized as dynamic, evolving, and multidimensional. In the second half, the authors build on Flexners systems perspective to introduce a complexity science understanding of professionalism. They define professionalism as a complex system, introduce a seven-part typology of professionalism, and explore how the organization of physician work and various flash points within medicine today reveal not one but several competing forms of professionalism at work. The authors then develop a tripartite model of professionalism with analysis at the micro, meso, and macro levels. They conclude with observations on how best to frame professionalism as a force for change in 21st-century medical education. Flexners reforms were grounded in his vision of two particular types of professional—the physician clinician and the full-time academic physician–scientist. The authors propose reform grounded in professionalism as a complex system composed of competing types.

A Bi-Directional Theory of Addiction: Examining Coping and the Factors Related to Substance Relapse

The results from this study supported a bi-directional theory of addiction for a sample of Black, inner-city, working-class, male substance abusers. Using structural equations modeling, at 6 months posttreatment we found that (a) the reciprocal effect emotional and psychological distress and substance relapse had on one another existed within the context of their bi-directional relationship with social instability, and (b) effective coping skills and resources moderated the negative effects that emotional and psychological distress, social structure, and substance relapse had on one another. These findings led us to three suggestions treatment professionals can use to counteract recidivism.

A sociological framing of medicine's modern-day professionalism movement

There is a great deal to learn from Martimiakis et al.’s conscientious and insightful look at the Sociological Interpretations of Professionalism. If nothing else, we need to seriously consider the research and pedagogical implications of their conclusion that professionalism is a ‘distributed attribute’ and therefore, like competence, something that is best understood as a product of interaction embedded in ‘systemic considerations’ rather than as a reflection of individuals and their motives.

Physician Views on Practicing Professionalism in the Corporate Age

Arnold Relman argues that medical education does not prepare students and residents to practice their profession in today’s corporate health care system. Corporate health care administrators agree: Physicians enter the workforce unskilled in contract negotiation, evidence-based medicine, navigating bureaucratic systems, and so forth. What about practicing physicians? Do they agree as well? According to this study, they do. Feeling like decentered double agents and unprepared, physicians find themselves professionally lost, struggling to balance issues of cost and care and expressing lots of negativity toward the cultures of medicine and managed care. However, physicians are resilient. A group of physicians, who may be called proactive, are meeting the professional demands of corporate health care by becoming sophisticated about its bureaucratic organization and the ways in which their professional and personal commitments fit within the system. Following the lead of proactive physicians, the authors support Relman’s thesis that education for both students and physicians requires a major overhaul.

Data Mining: Qualitative Analysis with Health Informatics Data

The new computational algorithms emerging in the data mining literature—in particular, the self-organizing map (SOM) and decision tree analysis (DTA)—offer qualitative researchers a unique set of tools for analyzing health informatics data. The uniqueness of these tools is that although they can be used to find meaningful patterns in large, complex quantitative databases, they are qualitative in orientation. To illustrate the utility of these tools, the authors review the two most popular: the SOM and DTA. They provide a basic definition of health informatics, focusing on how data mining assists this field, and apply the SOM and DTA to a hypothetical example to demonstrate what these tools are and how qualitative researchers can use them.

Modeling complex systems macroscopically: Case/agent-based modeling, synergetics, and the continuity equation

Recently, the continuity equation (also known as the advection equation) has been used to study stability properties of dynamical systems, where a linear transfer operator approach was used to examine the stability of a nonlinear equation both in continuous and discrete time (Vaidya and Mehta, IEEE Trans Autom Control 2008, 53, 307–323; Rajaram et al., J Math Anal Appl 2010, 368, 144–156). Our study, which conducts a series of simulations on residential patterns, demonstrates that this usage of the continuity equation can advance Hakens synergetic approach to modeling certain types of complex, self-organizing social systems macroscopically. The key to this advancement comes from employing a case-based approach that (1) treats complex systems as a set of cases and (2) treats cases as dynamical vsystems which, at the microscopic level, can be conceptualized as k dimensional row vectors; and, at the macroscopic level, as vectors with magnitude and direction, which can be modeled as population densities. Our case-based employment of the continuity equation has four benefits for agent-based and case-based modeling and, more broadly, the social scientific study of complex systems where transport or spatial mobility issues are of interest: it (1) links microscopic (agent-based) and macroscopic (structural) modeling; (2) transforms the dynamics of highly nonlinear vector fields into the linear motion of densities; (3) allows predictions to be made about future states of a complex system; and (4) mathematically formalizes the structural dynamics of these types of complex social systems.

Anatomy and histology as socially networked learning environments: some preliminary findings.

Purpose An exploratory study to better understand the “networked” life of the medical school as a learning environment. Method In a recent academic year, the authors gathered data during two six-week blocks of a sequential histology and anatomy course at a U.S. medical college. An eight-item questionnaire captured different dimensions of student interactions. The student cohort/network was 48 first-year medical students. Using social network analysis (SNA), the authors focused on (1) the initial structure and the evolution of informal class networks over time, (2) how informal class networks compare to formal in-class small-group assignments in influencing student information gathering, and (3) how peer assignment of professionalism role model status is shaped more by informal than formal ties. In examining these latter two issues, the authors explored not only how formal group assignment persisted over time but also how it functioned to prevent the tendency for groupings based on gender or ethnicity. Results The study revealed an evolving dynamic between the formal small-group learning structure of the course blocks and the emergence of informal student networks. For example, whereas formal group membership did influence in-class questions and did prevent formation of groups of like gender and ethnicity, outside-class questions and professionalism were influenced more by informal group ties where gender and, to a much lesser extent, ethnicity influence student information gathering. Conclusions The richness of these preliminary findings suggests that SNA may be a useful tool in examining an array of medical student learning encounters.

Cases, Clusters, Densities: Modeling the Nonlinear Dynamics of Complex Health Trajectories

In the health informatics era, modeling longitudinal data remains problematic. The issue is method: health data are highly nonlinear and dynamic, multilevel and multidimensional, comprised of multiple major/minor trends, and causally complex – making curve fitting, modeling and prediction difficult. The current study is fourth in a series exploring a case-based density (CBD) approach for modeling complex trajectories; which has the following advantages: it can (1) convert databases into sets of cases (k dimensional row vectors; i.e., rows containing k elements); (2) compute the trajectory (velocity vector) for each case based on (3) a set of bio-social variables called traces; (4) construct a theoretical map to explain these traces; (5) use vector quantization (i.e., k-means, topographical neural nets) to longitudinally cluster case trajectories into major/minor trends; (6) employ genetic algorithms and ordinary di.erential equations to create a microscopic (vector field) model (the inverse problem) of these trajectories; (7) look for complex steady-state behaviors (e.g., spiraling sources, etc) in the microscopic model; (8) draw from thermodynamics, synergetics and transport theory to translate the vector field (microscopic model) into the linear movement of macroscopic densities; (9) use the macroscopic model to simulate known and novel case-based scenarios (the forward problem); and (10) construct multiple accounts of the data by linking the theoretical map and k dimensional profile with the macroscopic, microscopic and cluster models. Given the utility of this approach, our purpose here is to organize our method (as applied to recent research) so it can be employed by others.