Impact of depressive symptoms on subjective well-being: the importance of patient-reported outcomes in schizophrenia

Objective: The subjective experience of psychotic patients toward treatment is a key factor in medication adherence, quality of life, and clinical outcome. The aim of this study was to assess the subjective well-being in patients with schizophrenia and to examine its relationship with the presence and severity of depressive symptoms. Methods: A multicenter, cross-sectional study was conducted with clinically stable outpatients diagnosed with schizophrenia. The Subjective Well-Being under Neuroleptic Scale - short version (SWN-K) and the Calgary Depression Scale for Schizophrenia (CDSS) were used to gather information on well-being and the presence and severity of depressive symptoms, respectively. Spearman's rank correlation was used to assess the associations between the SWN-K total score, its five subscales, and the CDSS total score. Discriminative validity was evaluated against that criterion by analysing the area under the curve (AUC). Results: Ninety-seven patients were included in the study. Mean age was 35 years (standard deviation = 10) and 72% were male. Both the total SWN-K scale and its five subscales correlated inversely and significantly with the CDSS total score (P < 0.0001). The highest correlation was observed for the total SWN-K (Spearman's rank order correlation [ rho] = -0.59), being the other correlations: mental functioning (-0.47), social integration (-0.46), emotional regulation (-0.51), physical functioning (-0.48), and self-control (-0.41). A total of 33 patients (34%) were classified as depressed. Total SWN-K showed the highest AUC when discriminating between depressive severity levels (0.84), followed by emotional regulation (0.80), social integration (0.78), physical functioning and self-control (0.77), and mental functioning (0.73). Total SWN-K and its five subscales showed a significant linear trend against CDSS severity levels (P < 0.001). Conclusion: The presence of moderate to severe depressive symptoms was relatively high, and correlated inversely with patients' subjective well-being. Routine assessment of patient-reported measures in patients with schizophrenia might reduce potential discrepancy between patient and physician assessment, increase therapeutic alliance, and improve outcome.

Joan Robinson Was Almost Right: Output under Third-Degree Price Discrimination

In this paper, we show that in order for third-degree price discrimination to increase total output, the demands of the strong markets should be, as conjectured by Robinson (1933), more concave than the demands of the weak markets. By making the distinction between adjusted concavity of the inverse demand and adjusted concavity of the direct demand, we are able to state necessary conditions and sufficient conditions for third-degree price discrimination to increase total output.

A Note on Wavelet Correlation and Cointegration

In a recent paper Leong-Huang:2010 {Journal of Applied Statistics 37, 215–233} proposed a wavelet-correlation-based approach to test for cointegration between two time series. However, correlation and cointegration are two different concepts even when wavelet analysis is used. It is known that statistics based on nonstationary integrated variables have non-standard asymptotic distributions. However, wavelet analysis offsets the integrating order of nonstationary series so that traditional asymptotics on stationary variables suffices to ascertain the statistical properties of wavelet-based statistics. Based on this, this note shows that wavelet correlations cannot be used as a test of cointegration.

Fluorescence cross-correlation spectroscopy to study hemodynamics

[EN] In the recent years a series of optical correlation techniques have been developed in order to be able to measure flow velocity with high spatial resolution while being non-invasive in order to be employed in-vivo on biological organisms. The technique employed in my thesis work, scanning laser image correlation (SLIC), is a powerful approach for the detection of flow motions because it overcomes some limitations of the classical spectroscopy techniques. SLIC method consists in repeated laser scans over a linear pattern and on the cross correlation of the signal emitted by the excited fluorophores in different positions along the scan line. Therefore, the resulting measurements for flow velocity are really accurate.