Introduction It has been proposed that women's sexual problems/dysfunctions, in the absence of personal and interpersonal distress, may have little clinical importance, as they may not necessarily affect women's sexual satisfaction. However, data are missing to support such interpretation. Aim The objective of the present study was to examine whether the presence of a sexual problem necessary affects women's satisfaction with sexual function. Method The study included 164 women who visited a general hospital because of symptoms not related to their sexual function and were asked to complete voluntarily and anonymously demographic data and two questionnaires. Main Outcome Measures Women completed the Female Sexual Function Index (FSFI)—an instrument which evaluates women sexual function—and the Symptom Checklist of Sexual Function—women version (SCSF-w), a screening tool of women's self-perception of sexual function. Results Mean patients’ age was 43 ± 12.6 (18–72) years. According to the FSFI, 48.8% of the participants had a sexual dysfunction. However, based on their self-perception of sexual function (SCSF), 80.5% of the sample declared to be satisfied with their sexual function, despite the fact that 69.5% of them reported at least one sexual problem. Of all women, only 26.2% would like to talk about their sexual problem(s) with a doctor (57.4% of those who are “bothered” by their sexual symptoms). Logistic regression analysis revealed no association between any sexual dysfunction and women's satisfaction from their sexual function. Conclusion Despite the presence of sexual problem(s), women may be satisfied with their sexual function, but half of those who are bothered would like to talk about it with their doctor. The presence of a sexual problem or its severity is not a determinant of women's help-seeking behavior. Such data strongly support current definitions of women's sexual dysfunction, where the presence of personal distress has been included as a crucial dimension.
In this study, Multifractal Detrended Fluctuation Analysis (MF-DFA) is applied to daily temperature time series (mean, maximum and minimum values) from 22 Greek meteorological stations with the purpose of examining firstly their scaling behavior and then checking if there are any differences in their multifractal characteristics. The results showed that the behavior is the same at almost all stations, i.e., time series are positive long-term correlated and their multifractal structure is insensitive to local fluctuations with large magnitude. Moreover, this study deals with the spatial distribution of the main characteristics of multifractal (singularity) spectrum: the dominant Hurst exponent, the width of the spectrum, the asymmetry and the truncation type of the spectrum. The spatial distributions are discussed in terms of possible effects from various climatic features. In general, local atmospheric circulation and weather conditions are found to affect the shape of the spectrum and the corresponding spatial distributions. Furthermore, the intercorrelation of the main multifractal spectrum parameters resulted in a well-defined group of stations sharing similar multifractal characteristics. The results indicate the usefulness of the non-linear analysis in climate research due to the complex interactions among the natural processes.
The Multifractal Detrended Fluctuation Analysis (MF-DFA) is used to examine the scaling behavior and the multifractal characteristics of the mean daily temperature time series of the ERA-Interim reanalysis data for a domain centered over Greece. The results showed that the time series from all grid points exhibit the same behavior: they have a positive long-term correlation and their multifractal structure is insensitive to local fluctuations with a large magnitude. Special emphasis was given to the spatial distribution of the main characteristics of the multifractal spectrum: the value of the Hölder exponent, the spectral width, the asymmetry, and the truncation type of the spectra. The most interesting finding is that the spatial distribution of almost all spectral parameters is decisively determined by the land-sea distribution. The results could be useful in climate research for examining the reproducibility of the nonlinear dynamics of reanalysis datasets and model outputs.
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