Sleep dependent consolidation of gross motor sequence learning with motor imagery

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

Despite the prevalence of sleep complaints among psychiatric patients, few questionnaires have been specifically designed to measure sleep quality in clinical populations. The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire which assesses sleep quality and disturbances over a 1-month time interval. Nineteen individual items generate seven "component" scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for these seven components yields one global score. Clinical and clinimetric properties of the PSQI were assessed over an 18-month period with "good" sleepers (healthy subjects, n = 52) and "poor" sleepers (depressed patients, n = 54; sleep-disorder patients, n = 62). Acceptable measures of internal homogeneity, consistency (test-retest reliability), and validity were obtained. A global PSQI score greater than 5 yielded a diagnostic sensitivity of 89.6% and specificity of 86.5% (kappa = 0.75, p less than 0.001) in distinguishing good and poor sleepers. The clinimetric and clinical properties of the PSQI suggest its utility both in psychiatric clinical practice and research activities.

An English language self-assessment Morningness-Eveningness questionnaire is presented and evaluated against individual differences in the circadian vatiation of oral temperature. 48 subjects falling into Morning, Evening and Intermediate type categories regularly took their temperature. Circadian peak time were identified from the smoothed temperature curves of each subject. Results showed that Morning types and a significantly earlier peak time than Evening types and tended to have a higher daytime temperature and lower post peak temperature. The Intermediate type had temperatures between those of the other groups. Although no significant differences in sleep lengths were found between the three types, Morning types retired and arose significantly earlier than Evening types. Whilst these time significatly correlated with peak time, the questionnaire showed a higher peak time correlation. Although sleep habits are an important déterminant of peak time there are other contibutory factors, and these appear to be partly covered by the questionnaire. Although the questionnaire appears to be valid, further evaluation using a wider subject population is required.