WHOQOL-BREF as a measure of quality of life in older patients with depression

Objective: To assess the reliability and validity of a brief measure of quality of life recently developed by the World Health Organization, the WHOQOL-BREF, and to examine its association with a variety of clinical and sociodemographic factors in older depressed patients. Design: Cross-sectional study. Methods: Older depressed patients (N=41) underwent diagnostic assessment using the Composite International Diagnostic Interview (CIDI) and were independently assessed on a variety of measures including the WHOQOL-BREF (a 26-item self-report questionnaire generating four domain scores), Hamilton Depression Rating Scale (HAM-D); Geriatric Depression Scale (GDS); Mini-mental State Examination (MMSE); Modified Barthel Index (MBI); Instrumental activities of daily living (IADL), and measures of physical health status and social relationships. Estimates of inter-rater and test-retest reliability, and concurrent validity were made. Results: 39 subjects completed the study. The majority of subjects (94.9%) received a diagnosis of DSM-IV Major Depressive Disorder. Levels of comorbidity were high. Three of the four domains of the WHOQOL-BREF (Physical, Psychological and Environment domains) demonstrated satisfactory reliability and validity. However, the Social Relationships domain exhibited poor validity. Quality of life scores were strongly correlated with severity of depression, number of self-reported physical symptoms and self-assessed general health status. There was no relationship between diagnostic comorbidity and quality of life scores. Conclusions: The WHOQOL-BREF was successfully administered to older depressed patients although the concurrent validity of one of its four domains was poor. Quality of life scores were strongly correlated with severity of depression, raising the issue of measurement redundancy.

Generation of macroscopic superposition states with small nonlinearity

We suggest a scheme to generate a macroscopic superposition state (Schrodinger cat state) of a free-propagating optical field using a beam splitter, homodyne measurement, and a very small Kerr nonlinear effect. Our scheme makes it possible to reduce considerably the required nonlinear effect to generate an optical cat state using simple and efficient optical elements.

Cognitive fit between conceptual schemas and internal problem representations: The case of geospatio-temporal conceptual schema comprehension

Geospatio-temporal conceptual models provide a mechanism to explicitly represent geospatial and temporal aspects of applications. Such models, which focus on both what and when/where, need to be more expressive than conventional conceptual models (e.g., the ER model), which primarily focus on what is important for a given application. In this study, we view conceptual schema comprehension of geospatio-temporal data semantics in terms of matching the external problem representation (that is, the conceptual schema) to the problem-solving task (that is, syntactic and semantic comprehension tasks), an argument based on the theory of cognitive fit. Our theory suggests that an external problem representation that matches the problem solver's internal task representation will enhance performance, for example, in comprehending such schemas. To assess performance on geospatio-temporal schema comprehension tasks, we conducted a laboratory experiment using two semantically identical conceptual schemas, one of which mapped closely to the internal task representation while the other did not. As expected, we found that the geospatio-temporal conceptual schema that corresponded to the internal representation of the task enhanced the accuracy of schema comprehension; comprehension time was equivalent for both. Cognitive fit between the internal representation of the task and conceptual schemas with geospatio-temporal annotations was, therefore, manifested in accuracy of schema comprehension and not in time for problem solution. Our findings suggest that the annotated schemas facilitate understanding of data semantics represented on the schema.