engleski

Lapses of reaction times during cognitive and psychomotor testing are the most delicate indicator of poor sleep assessed with Pittsburgh Sleep Quality Index in students

Introduction: Numerous studies have supported the idea that sleep has an important role in regulation of cognitive and affective brain functions. Even though the overall sleep quality contributes to cognitive performance, distinction of various components of subjective sleep quality might provide more precise insight into the aforementioned association, specifically in student population. The aim of this study was to elucidate the relationship between components of sleep quality and reaction times in solving simple and complex cognitive and psychomotor tasks in medical students. We hypothesized that sleep quality components are more precise indicators of sleep than general subjective sleep quality in students and that poor sleep can be detected even by subtle deteriorations in cognitive performance. Methods: A total of 164 students (49 men) enrolled in the Basic neuroscience course at the University of Split School of medicine, participated in the study. All subjects completed Pittsburgh Sleep Quality Index (PSQI), a self-reported general measure of sleep quality and disturbances over the past one-month period. From the 19 items of the PSQI questionnaire, 7 components are created indicating subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medications, and daytime dysfunction. Cognitive and psychomotor abilities were assessed using Complex Reactionmeter Drenovac (CRD-series), a battery of computer supported neuropsychological tests, measuring reaction times and speed of information processing. Three CRD-series test were used: CRD11, assessing solving simple arithmetic operations, CRD311, assessing discrimination of the light signal position, and CRD411, assessing complex psychomotor coordination of limbs. In each single test, several variables were analyzed: total test solving time (TTST), minimum single task solving time (MinT), maximum single task solving time (MaxT) and start to end ballast ratio (SB/EB). Results: There was no significant correlation between TTST and MinT with the total PSQI score on CRD11 (P=0.633 and P=0.881), CRD311 (P=0.446 and P=0.951) and CRD411 tests (P=0.464 and P=0.412). However, SB/EB ratio was correlated with total PSQI score on the CRD311 test (r=0.201, P=0.01). Regression analysis using 7 components of the PSQI questionnaire as predictors revealed that there was an association between use of sleeping medication and MaxT on CRD11 test (β=0.167, P=0.037). On CRD311 test, prolonged MaxT was associated with increased sleep latency (β=0.379, P<0.001), prolonged sleep duration (β=-0.439, P<0.001), decreased habitual sleep efficiency (β=0.404, P<0.001), and less frequent sleep disturbances (β=-0.370, P<0.001). On the CRD411 test, prolonged MaxT was associated with shorter sleep duration (β=0.174, P=0.03) and less frequent reports on daytime dysfunctions (β=-0.165, P=0.039). Conclusions: Our results suggest that precise analysis of sleep quality components might provide a better insight into sleep of students in comparison to analysis of general subjective sleep quality. Maximum single task solving time, as a measure of cognitive performance on the tests of simple arithmetic operations, discrimination of the light signal position, and complex psychomotor coordination was associated with the sleep quality components. Thus, one might presume that this measure, possibly indicating lapses of concentration, is the most sensitive to discriminate impairments of sleep quality components.

reaction times ; cognitive ; psychomotor testing ; sleep quality

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