Job characteristics and burnout among aging professionals in information and communications technology

The aim of this Study was to examine the relationship between job characteristics and burnout, i.e., exhaustion, cynicism and lack of professional efficacy, in a sample of 115 (49- to 61-yr.-old) information and communications technology professionals. Questionnaire survey data were collected at two time points. In 1995 (Time 1), higher quantitative overload and lower job control were associated with higher exhaustion. Job control was negatively associated with lack of professional efficacy. In 2001 (Time 2), quantitative overload and information overload were positively associated with exhaustion, but with job control negatively. Use of new information Was negatively associated with cynicism. In addition, job control and use of new information were negatively associated with lack of professional efficacy. job characteristics at Time 1 were not significantly associated with burnout at Time 2 when job characteristics at Time 2 were controlled.

Patient selection for oncology phase I trials: a multi-institutional study of prognostic factors.

PURPOSE The appropriate selection of patients for early clinical trials presents a major challenge. Previous analyses focusing on this problem were limited by small size and by interpractice heterogeneity. This study aims to define prognostic factors to guide risk-benefit assessments by using a large patient database from multiple phase I trials. PATIENTS AND METHODS Data were collected from 2,182 eligible patients treated in phase I trials between 2005 and 2007 in 14 European institutions. We derived and validated independent prognostic factors for 90-day mortality by using multivariate logistic regression analysis. Results The 90-day mortality was 16.5% with a drug-related death rate of 0.4%. Trial discontinuation within 3 weeks occurred in 14% of patients primarily because of disease progression. Eight different prognostic variables for 90-day mortality were validated: performance status (PS), albumin, lactate dehydrogenase, alkaline phosphatase, number of metastatic sites, clinical tumor growth rate, lymphocytes, and WBC. Two different models of prognostic scores for 90-day mortality were generated by using these factors, including or excluding PS; both achieved specificities of more than 85% and sensitivities of approximately 50% when using a score cutoff of 5 or higher. These models were not superior to the previously published Royal Marsden Hospital score in their ability to predict 90-day mortality. CONCLUSION Patient selection using any of these prognostic scores will reduce non-drug-related 90-day mortality among patients enrolled in phase I trials by 50%. However, this can be achieved only by an overall reduction in recruitment to phase I studies of 20%, more than half of whom would in fact have survived beyond 90 days.