Patient assessment of engagement with students in an interprofessional student-run free clinic for individuals experiencing homelessness

The development and validation of a patient exit interview tool, the Interprofessional Clinic Homeless Satisfaction with Student Engagement Survey (ICHSES), and its incorporation in the administration of an interprofessional, co-curricular program, the Community Homeless Interprofessional Program (CHIP) is described. Incorporation of patient satisfaction with student engagement during interprofessional training experiences serving individuals who are homeless has not been previously published. At CHIP, medical, pharmacy and social work students engage with individuals experiencing homelessness in a church and faculty-supervised environment. The students provide basic health assessment, education, and referrals to community resources. Once the interaction with the students is complete, patients are asked to participate in an exit-interview using the ICHSES. Questions in the ICHSES focus on engagement with the students and the patient’s perception of the assistance they received. Based on survey responses by 220 patients, the 5 question ICHSES showed high reliability (Cronbach’s alpha?=?0.77). The ICHSES survey could be utilized in similar clinics engaged in serving the homeless.     

Using the Multiple-Choice Procedure to Measure the Relative Reinforcing Efficacy of Gambling: Initial Validity Evidence Among College Students

The multiple choice procedure (MCP) is used to assess the relative reinforcing value of concurrently available stimuli. The MCP was originally developed to assess the reinforcing value of drugs; the current within-subjects study employed the MCP to assess the reinforcing value of gambling behavior. Participants (N = 323) completed six versions of the MCP that presented hypothetical choices between money to be used while gambling ($10 or $25) versus escalating amounts of guaranteed money available immediately or after delays of either 1 week or 1 month. Results suggest that choices on the MCP are correlated with other measures of gambling behavior, thus providing concurrent validity data for using the MCP to quantify the relative reinforcing value of gambling. The MCP for gambling also displayed sensitivity to reinforcer magnitude and delay effects, which provides evidence of criterion validity. The results are consistent with a behavioral economic model of addiction and suggest that the MCP could be a valid tool for future research on gambling behavior.     

‘The times,are they a‐changing?’ As the world enters a new millennium are we as paediatricians keeping up with the changing needs of children?

This paper describes changes that are occurring in paediatric practice in a variety of settings. The ‘new morbidity’ demands focused training of paediatricians of the twenty‐first century. Areas that include advocacy, public health, adolescence, chronic illness, health promotion, behavioural issues, parenting and family dynamics, social influences, health and social inequalities, managerial decision making and technological advances should be a part of paediatric training. These factors assume different importance in developing nations where priorities may be more focused on public health, nutrition and health promotion. Partnership with others who have children's interests at heart, for example mental health services, public health, social sciences, education and social services is imperative in planning service development informed by good information systems incorporating measures of mortality and morbidity. Copyright © 2000 John Wiley & Sons, Ltd.     

Categorizing Mistaken False Positives in Regulation of Human and Environmental Health

One of the concerns often voiced by critics of the precautionary principle is that a widespread regulatory application of the principle will lead to a large number of false positives (i.e., over-regulation of minor risks and regulation of nonexisting risks). The present article proposes a general definition of a regulatory false positive, and seeks to identify case studies that can be considered authentic regulatory false positives. Through a comprehensive review of the science policy literature for proclaimed false positives and interviews with authorities on regulation and the precautionary principle we identified 88 cases. Following a detailed analysis of these cases, we found that few of the cases mentioned in the literature can be considered to be authentic false positives. As a result, we have developed a number of different categories for these cases of "mistaken false positives," including: real risks, "The jury is still out," nonregulated proclaimed risks, "Too narrow a definition of risk," and risk-risk tradeoffs. These categories are defined and examples are presented in order to illustrate their key characteristics. On the basis of our analysis, we were able to identify only four cases that could be defined as regulatory false positives in the light of today's knowledge and recognized uncertainty: the Southern Corn Leaf Blight, the Swine Flu, Saccharin, and Food Irradiation in relation to consumer health. We conclude that concerns about false positives do not represent a reasonable argument against future application of the precautionary principle.     

LOCATION OF PARTICULAR POINTS IN NON-PARAMETRIC REGRESSION ANALYSIS

In the random-design non-parametric regression model, the locations of particular values of the regression function or its derivatives are estimated. This paper investigates several stochastic modes of convergence and finds their rate of convergence under regularity assumptions, for a wide class of non-parametric estimators. The approach finds two natural fields of application: estimation of zeros/extrema and non-parametric absolute calibration.     

Source Data Perturbation and consistent sets of safe tables

When tables are generated from a data file, the release of those tables should not reveal too detailed information concerning individual respondents. The disclosure of individual respondents in the microdata file can be prevented by applying disclosure control methods at the table level (by cell suppression or cell perturbation), but this may create inconsistencies among other tables based on the same data file. Alternatively, disclosure control methods can be applied at the microdata level, but these methods may change the data permanently and do not account for specific table properties. These problems can be circumvented by assigning a (single and fixed) weight factor to each respondent/record in the microdata file. Normally this weight factor is equal to 1 for each record, and is not explicitly incorporated in the microdata file. Upon tabulation, each contribution of a respondent is weighted multiplicatively by the respondent's weight factor. This approach is called Source Data Perturbation (SDP) because the data is perturbed at the microdata level, not at the table level. It should be noted, however, that the data in the original microdata is not changed; only a weight variable is added. The weight factors can be chosen in accordance with the SDC paradigm, i.e. such that the tables generated from the microdata are safe, and the information loss is minimized. The paper indicates how this can be done. Moreover it is shown that the SDP approach is very suitable for use in data warehouses, as the weights can be conveniently put in the fact tables. The data can then still be accessed and sliced and diced up to a certain level of detail, and tables generated from the data warehouse are mutually consistent and safe.     

Survival estimation and the effects of dependency among animals

Survival models assume that fates of individuals are independent, yet the robustness of this assumption has been poorly quantified. We examine how empirically derived estimates of the variance of survival rates are affected by dependency in survival probability among individuals. We used Monte Carlo simulations to generate known amounts of dependency among pairs of individuals and analyzed these data with Kaplan-Meier and Cormack-Jolly-Seber models. Dependency significantly increased these empirical variances as compared to theoretically derived estimates of variance from the same populations. Using resighting data from 168 pairs of black brant ( Branta bernicla nigricans ), we used a resampling procedure and program RELEASE to estimate empirical and mean theoretical variances. We estimated that the relationship between paired individuals caused the empirical variance of the survival rate to be 155% larger than the empirical variance for unpaired individuals. Monte Carlo simulations and use of this resampling strategy can provide investigators with information on how robust their data are to this common assumption of independent survival probabilities.