Gathering Diverse Perspectives to Tackle “Wicked Problems”: Racial/Ethnic Disproportionality in Educational Placement

Among students receiving behavioral health and special education services, racial/ethnic minority students are consistently overrepresented in settings separate from general classrooms. Once separated, many young people struggle to improve academically and face significant difficulty upon trying to return to a general education setting. Given the complex, ongoing, and multifaceted nature of this challenge, racial/ethnic disproportionality can be identified as a “wicked problem,” for which solutions are not easily identified. Here, we describe our community-engaged research efforts, eliciting perspectives from relevant partners in an ongoing dialogue, to better integrate diverse stakeholders’ perspectives when attempting to address such disparities. We conducted focus groups and qualitative interviews with members of three stakeholder groups: community-serving organizations, individuals with lived experience of behavioral health conditions, and state-level policymakers, with a shared interest in addressing racial and ethnic disparities. Participant responses illustrated the “wickedness” of this problem and highlighted the need for additional supports for students, families, and school personnel, increased collaboration across relevant systems and agencies, and reduced barriers related to funding. Overall, this methodology bridged differing perspectives to develop, in concert with our partners, a shared language of the problem and a core set of issues to consider when seeking to effect change.     

When and why Conventions cannot Be Social Institutions

Philosophia - The paper focuses on the issue of compatibility of social institution and convention. At first, it introduces the modest account of conventionality building on five distinctive...     

Doctors' decision-making on giving information to cancer patients

Abstract

A major focus in the literature about doctor-patient communication is information-giving. In the case of cancer patients, one significant issue is which factors determine whether and how, general practitioners and oncologists give information to their patients. Whatever may be the content of information, the most important choice for the doctor is to give information or not. Our research group at the Department of Health Psychology has conducted investigations in order to identify the significant determinants of decisions concerning giving information to cancer patients. A sample of 60 doctors from Alicante province in Spain were asked their criteria for giving information about a cancer diagnosis. Results showed that perceived intelligence and emotional control in the patients were the best predicotrs of the decision by doctors to give information. Age and socio-economic status were also significantly associated with the doctors' information-giving practices. These data suggest that the criteria for giving information to cancer patients are subjective and show a strong cultural influence.     

The role of causal models in multiple judgments under uncertainty

Two studies examined a novel prediction of the causal Bayes net approach to judgments under uncertainty, namely that causal knowledge affects the interpretation of statistical evidence obtained over multiple observations. Participants estimated the conditional probability of an uncertain event (breast cancer) given information about the base rate, hit rate (probability of a positive mammogram given cancer) and false positive rate (probability of a positive mammogram in the absence of cancer). Conditional probability estimates were made after observing one or two positive mammograms. Participants exhibited a causal stability effect: there was a smaller increase in estimates of the probability of cancer over multiple positive mammograms when a causal explanation of false positives was provided. This was the case when the judgments were made by different participants (Experiment 1) or by the same participants (Experiment 2). These results show that identical patterns of observed events can lead to different estimates of event probability depending on beliefs about the generative causes of the observations.