The aims of this study were to identify the most important diagnostic questions that warrant assessment in psychogeriatric patients and to select and validate objective screening procedures for those areas. Four areas were identified by surveying the records of 87 psychogeriatric patients: organicity, depression, prognosis, and global psychopathology. Relevant assessment instruments, selected on the basis of a comprehensive literature survey, were administered to 61 psychogeriatric inpatients, and criterion ratings were obtained in each of the four diagnostic areas. The Mental Status Questionnaire correlated -.87 with the organicity criterion and also shoed the highest correlations with the other three criterion variables. A canonical correlation analysis showed that the organicity and depression criteria could be reliably separated by the predictors, and multiple regression analysis showed that each could be reliably predicted independently. It is noted that the population studied was largely chronic in nature, so that the findings are not necessarily applicable to other kinds of settings.

This study was designed to assist an employee‐counseling program in a medical hospital by assessing the life quality and life stressors of its employees. 246 employees completed a written questionnaire which included a life events inventory and the Perceived Quality of Life (PQOL) Inventory (Andrews & Withey, 1976). Items on both inventories covered the areas of job, family/support, and financial affairs. Items measuring self‐efficacy from the PQOL scale served as the criterion for potential counseling service utilization. Results indicated that family‐support concerns were the most predictive of perceptions of self‐efficacy. In addition, negatively perceived life changes were more powerful predictors of life quality than were life changes per se. Finally, employees who were identified as less satisfied in the various quality of life areas were separated from their spouses, over 55 years of age, and had lower education levels, large families, and low incomes.