Exploring professional orientations to community voice in professional practice settings: The IMAP process

The tension between technical experts and the populations they seek to serve is well established in the literature examining professional social problem solving. In this piece, I examine this tension as one between the distinct discursive worlds of technical expertise and community voice. I develop an analytic process, IMAP, for exploring this tension by looking at a wide variety of professional orientations around a relatively fixed concept of community voice. IMAP involves I&barbelow;dentifying social problem solvers, M&barbelow;apping social problem solvers' claims, A&barbelow;nalyzing professional orientations that arise from this mapping, and P&barbelow;redicting, diagnosing, and remediating conflicts. IMAP can be used by analysts external to social problem solving settings or by social problem solvers themselves. The use of IMAP by external experts poses questions of expert alignment with either of the discursive worlds. I examine two cases in public health practice settings: a mobile immunization service and the efforts of a foundation to improve health in an inner-city neighborhood. I develop four modal types that can be anticipated in social problem solving settings or, more specifically, in public health practice. Understanding of these “world views” can enhance mutual understanding between public health professionals and between public health professionals and the communities they seek to serve. IMAP might also address ongoing conflicts to clarify differences in unspoken normative commitments and the impact of these on social problem solving. I discuss implications of the research for public health practice and further research in the area. ^

Procedure for the identification of population characteristics for targeting intervention services on the basis of outcome-goal priorities: Case management services for the chronic mentally ill

Although the processes involved in rational patient targeting may be obvious for certain services, for others, both the appropriate sub-populations to receive services and the procedures to be used for their identification may be unclear. This project was designed to address several research questions which arise in the attempt to deliver appropriate services to specific populations. The related difficulties are particularly evident for those interventions about which findings regarding effectiveness are conflicting. When an intervention clearly is not beneficial (or is dangerous) to a large, diverse population, consensus regarding withholding the intervention from dissemination can easily be reached. When findings are ambiguous, however, conclusions may be impossible.^ When characteristics of patients likely to benefit from an intervention are not obvious, and when the intervention is not significantly invasive or dangerous, the strategy proposed herein may be used to identify specific characteristics of sub-populations which may benefit from the intervention. The identification of these populations may be used both in further informing decisions regarding distribution of the intervention and for purposes of planning implementation of the intervention by identifying specific target populations for service delivery.^ This project explores a method for identifying such sub-populations through the use of related datasets generated from clinical trials conducted to test the effectiveness of an intervention. The method is specified in detail and tested using the example intervention of case management for outpatient treatment of populations with chronic mental illness. These analyses were applied in order to identify any characteristics which distinguish specific sub-populations who are more likely to benefit from case management service, despite conflicting findings regarding its effectiveness for the aggregate population, as reported in the body of related research. However, in addition to a limited set of characteristics associated with benefit, the findings generated, a larger set of characteristics of patients likely to experience greater improvement without intervention. ^