Development of goal-sensitive health-related utility assessment procedures.

Purpose: To measure the degree to which people express willingness to trade life or health for nonmedical goals.

Method: In 3 studies, outpatients provided important life goals. In study 1, patients performed time-tradeoff between life-years and goal achievement and chose between states that varied in goal achievement, life expectancy, and disability; in study 2, patients made choices that traded off health state and goal achievement; in study 3, patients performed time-tradeoff assessments in 3 different goal achievement contexts.

A randomized controlled trial to increase physical activity and reduce obesity in a predominantly African American group of women with mobility disabilities and severe obesity.

Objective: This randomized controlled trial tested a tailored, telephone-based physical activity coaching intervention for a predominantly African American group of women with severe obesity and mobility disability.

Methods: We recruited 92 clinic patients from the University of Illinois at Chicago Medical Center referred by their physicians during 2004-2007 and randomized participants to one of three groups--awareness(informational brochure, no coaching), lower support (phone coaching only) and higher support (phone coaching plus monthly exercise support group)--to determine the efficacy of a tailored coaching intervention on key health outcomes, which included body weight and body mass index, blood pressure, cholesterol, physical activity (barriers and self-reported activity), movement and mobility, general health, and social support.

Results: The higher support group had the greatest reduction in Body Mass Index (BMI) (7.

Placebo surgery research: a blinding imperative.

In placebo surgery research, intervention group subjects receive a real surgical procedure, and control subjects receive a sham surgical procedure. The sham procedure is designed to recapitulate enough of the real procedure to blind participants to group assignment. Placebo surgery designs are used to control for placebo effects, and to eliminate the bias that might result if participants and investigators were aware of group assignment when outcomes are measured.

Predictors of urinary tract infection based on artificial neural networks and genetic algorithms.

Background: Among women who present with urinary complaints, only 50% are found to have urinary tract infection. Individual urinary symptoms and urinalysis are not sufficiently accurate to discriminate those with and without the diagnosis.

Methods: We used artificial neural networks (ANN) coupled with genetic algorithms to evolve combinations of clinical variables optimized for predicting urinary tract infection.

By-person factor analysis in clinical ethical decision making: Q methodology in end-of-life care decisions.

Objective: To determine the usefulness of Q methodology to locate and describe shared subjective influences on clinical decision making among participant physicians using hypothetical cases containing common ethical issues.

Design: Qualitative study using by-person factor analysis of subjective Q sort data matrix.

Setting: University medical center.

Implementation and evaluation of a low-literacy diabetes education computer multimedia application.

Objective: To evaluate a clinic-based multimedia intervention for diabetes education targeting individuals with low health literacy levels in a diverse population.

Research Design And Methods: Five public clinics in Chicago, Illinois, participated in the study with computer kiosks installed in waiting room areas. Two hundred forty-four subjects with diabetes were randomized to receive either supplemental computer multimedia use (intervention) or standard of care only (control).

Do physicians know when their diagnoses are correct? Implications for decision support and error reduction.

Objective: This study explores the alignment between physicians' confidence in their diagnoses and the "correctness" of these diagnoses, as a function of clinical experience, and whether subjects were prone to over-or underconfidence.

Design: Prospective, counterbalanced experimental design.

Setting: Laboratory study conducted under controlled conditions at three academic medical centers.

Use of genetic algorithms for neural networks to predict community-acquired pneumonia.

Background: Genetic algorithms have been used to solve optimization problems for artificial neural networks (ANN) in several domains. We used genetic algorithms to search for optimal hidden-layer architectures, connectivity, and training parameters for ANN for predicting community-acquired pneumonia among patients with respiratory complaints.

Methods: Feed-forward back-propagation ANN were trained on sociodemographic, symptom, sign, comorbidity, and radiographic outcome data among 1044 patients from the University of Illinois (the training cohort), and were applied to 116 patients from the University of Nebraska (the testing cohort).

Prediction of community-acquired pneumonia using artificial neural networks.

Background: Artificial neural networks (ANN) have been used in the prediction of several medical conditions but have not been previously used to predict pneumonia. The authors used ANN to predict the presence or absence of pneumonia among patients presenting to the emergency department with acute respiratory complaints and compared the results with those obtained using logistic regression modeling.

Methods: Feed-forward back-propagation ANN were trained on sociodemographic, symptom, sign, comorbidity, and radiographic outcome data among 1,044 patients from the University of Illinois (the training cohort) and were applied to 116 patients from the University of Nebraska (the testing cohort).

Token swap test revisited.

The token swap test measures the association between row and column variables of a 2 x 2 table in sample misclassification space, and makes no assumptions about repeated, random sampling from a source population. Despite its conceptual usefulness, the token swap test is not implemented by standard statistical software packages. Here the author describes 'tokenSwaps', a Mathematica program that performs a token swap test.

Exploring the boundaries of plausibility: empirical study of a key problem in the design of computer-based clinical simulations.

All clinical simulation designers face the problem of identifying the plausible diagnostic and management options to include in their simulation models. This study explores the number of plausible diagnoses that exist for a given case, and how many subjects must work up a case before all plausible diagnoses are identified. Data derive from 144 residents and faculty physicians from 3 medical centers, each of whom worked 9 diagnostically challenging cases selected from a set of 36.

Parametric receiver operating characteristic curve analysis using mathematica.

Several computer programs have been written to perform receiver operating characteristic (ROC) curve analysis, and are available in the public domain. Here, the author provides the theory and description for 'rocMath', a Mathematica program that performs parametric ROC curve analysis. The 'rocMath' program has some advantages over other ROC curve programs, including the ability to provide, through optional arguments: (a) user-specified pointwise confidence limits, as well as default 95% limits, on ROC curve area and on true-positive rates; (b) ROC curve plots with data points, a fitted curve, and user-specified pointwise confidence bands; and (c) ROC curve areas, tables, and plots based on a logistic distribution as well as on a standard normal distribution.