The poor reliability of the DSM diagnostic system has been a major issue of concern for many researchers and clinicians. Standardized interview techniques and rating scales have been shown to be effective in increasing interrater reliability in diagnosis and classification. This study hypothesized that the utilization of the Psychological Rating Scale for Diagnostic Classification for assessing the problematic behaviors, symptoms, or other characteristics of an individual would increase interrater reliability, subsequently leading to higher diagnostic agreement between raters and with DSM-III classification. This hypothesis was strongly supported by high overall profile reliability and individual profile reliability. Therefore utilization of this rating scale would enhance the accuracy of diagnosis and add to the educational efforts of technical personnel and those professionals in related disciplines.

This study was designed to assess the reliability of the "Psychological Rating Scale for Diagnostic classification as an instrument for determining diagnoses consistent with DSM-III criteria and nomenclature. Pairs of raters jointly interviewed a total of 50 hospital patients and then independently completed the 70-item rating scale to arrive at Axis I and Axis II diagnoses which were subsequently correlated with diagnoses obtained by standard psychometric methods, interrater agreement was 88 per cent for Axis I and 62 per cent for Axis II, with correlations of .94 and .79 respectively.

The relationship between health attribution belief systems and compliance in an ecological treatment regimen was examined in 40 patients with environmental illness. Internal and chance scales on the Health Attribution Test (HAT) were found to be related to reported level of compliance for each subject. Data were subjected to Chi square analysis with highly significant results obtained. Ecology patients appear to take responsibility for their own health and treatment and, although they feel themselves to be victims of fate, they comply with treatment on a high level.

Sleep, emotions and pain are intimately connected, physiologically, by their location and utilization of the same brain centers and neurotransmitters. Sleep disturbances have been clinically observed in chronic pain populations; yet, no treatment program has formally addressed this aspect of patient care. It is hypothesized that a pain population (PN) will differ significantly from a non-injured workforce (WF) when reviewing quantitative and qualitative sleep data. This study strongly supports that sleep disturbances and socioeconomic decrements exist in chronic pain patients. Forty-seven variables were surveyed and 13 were found to show significant differences between the groups and seven were found to discriminate between the PN and WF groups at less than the .0001 level. A discriminant analysis was performed to determine the smallest model which could efficiently classify cases, according to successive root variables. The major discriminators are pain levels, medication, amount of sleep obtained and number of awakenings.