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Background Sleep disorders are composed of a group of diseases of increasing prevalence and with social-health implications to be considered a public health problem. Sleep habits and specific sleep behaviors have an influence on the academic success of students. However, the characteristics of sleep and sleep habits of university students as predictors of poor academic performance have been scarcely analyzed. In the present study, we aimed to investigate sleep habits and their influence on academic performance in a cohort of Nursing Degree students. Methods This was a cross-sectional and observational study. An anonymous and self-administered questionnaire was used, including different scales such as the ‘Morningness and Eveningness scale’, an author-generated sleep habit questionnaire, and certain variables aimed at studying the socio-familial and academic aspects of the Nursing students. The association of sleep habits and other variables with poor academic performance was investigated by logistic regression. The internal consistency and homogeneity of the ‘sleep habits questionnaire’ was assessed with the Cronbach’s alpha test. Results Overall, 401 students (mean age of 22.1 ± 4.9 years, 74.8 % females) from the Nursing Degree were included. The homogeneity of the ‘sleep habits questionnaire’ was appropriate (Cronbach’s alpha = 0.710). Nursing students were characterized by an evening chronotype (20.2 %) and a short sleep pattern. 30.4 % of the Nursing students had bad sleep habits. Regarding the academic performance, 47.9 % of the students showed a poor one. On multivariate logistic regression analysis, a short sleep pattern (adjusted OR = 1.53, 95 % CI 1.01–2.34), bad sleep habits (aOR = 1.76, 95 % CI 1.11–2.79), and age < 25 years (aOR = 2.27, 95 % CI 1.30–3.98) were independently associated with a higher probability of poor academic performance. Conclusions Almost 1/3 of the Nursing students were identified as having bad sleep habits, and these students were characterized by an evening chronotype and a short sleep pattern. A short sleep pattern, bad sleep habits, and age < 25 years, were independently associated with a higher risk of poor academic performance. This requires multifactorial approaches and the involvement of all the associated actors: teachers, academic institutions, health institutions, and the people in charge in university residences, among others.

The purpose of this study was to determine the prevalence of sleep quality and to investigate variables predicting the risk of poor sleep quality in public workers from Murcia (Spain). A cross-sectional and prospective study was conducted from October 2013 to February 2016 in 476 public workers. The Pittsburgh Sleep Quality Index was used to measure the quality of sleep, and the reduced scale of the Horne and Österberg Morningness–Eveningness Questionnaire was applied to analyze the circadian typology. The predictive variables of self-reported poor sleep quality were identified by multivariate logistic regression. No significant differences were found according to sex in the overall sleep quality scores (5 ± 2.9 versus 5.1 ± 3, p = 0.650), but there were in the duration of sleep. Three percent of females slept <5 hours compared to 2% of men (p = 0.034). Fixed morning shifts (OR = 1.9, 95% CI 1.3–3.1; p = 0.007) and evening chronotypes (OR = 1.6, 95% CI 1.0–2.3; p = 0.017) were independent predictors of suffering from poor sleep quality. In conclusion, the frequency of self-reported poor sleep quality among public workers from Murcia was 37.4%. Being a public worker with a fixed morning shift and having an evening chronotype demonstrated to be associated with the quality of sleep.

ObjectivesMental workload is a condition which can negatively influence the overall health of workers. In this study, we aimed to investigate the risk factors for the onset of mental workload, including working conditions, cardiovascular comorbidities and lifestyle habits, in a working population.MethodsThis is a cross-sectional study including 408 workers from a risk prevention service of small/medium companies in Murcia (Spain). Workers from the secondary and tertiary sectors or primary/secondary sectors with administrative management tasks who underwent a routine medical examination between 1 January 2017 and 31 April 2017 were included. Workers from the primary sector and construction were excluded to avoid a sex and age bias.ResultsFrom 408 workers, 206 (50.5%) were females; with mean age 36.8±10.4 years. 164 (40.2%) workers had a moderate to significant risk of mental workload. Based on multivariate logistic regression analyses, independent predictors of mental workload were age ≥30 years (OR 2.42, 95% CI 1.22 to 4.80; p=0.012), working in tertiary (OR 7.89, 95% CI 3.59 to 17.31; p<0.001) or administrative sectors (OR 87.57, 95% CI 35.22 to 217.79; p<0.001) and alcohol consumption (OR 2.08, 95% CI 1.16 to 3.73; p=0.014). Smoking habit (OR 0.47, 95% CI 0.26 to 0.85; p=0.012) was found as a protective variable so non-smoking was considered as a risk factor.ConclusionIn the present study from a risk prevention service including workers of small/medium companies from the secondary and tertiary sectors and workers with administrative tasks, the labour sector, age, alcohol consumption and smoking habits, are independently associated with a higher risk of developing moderate to significant mental workload.

Aim:We aimed to develop a tool for the assessment of the risk of patient discomfort in Spanish hospital wards. Background: Several studies described tools to assess comfort but most are long and complex.Methods: Cross-sectional study performed in three phases ((a) initial design; (b) refinement and psychometric testing; and (c) internal validation of the Hospital Discomfort Risk [HDR] questionnaire). Results:A voluntary expert panel proposed the HDR questionnaire. Internal consistency and factorial analysis were investigated in 270 (53.7% men, mean age 57.33 ± 18.7 years) inpatients. Based on the Cronbach's α, three items were removed to the final 8-item version of the questionnaire. The HDR questionnaire showed a good predictive ability for identifying the risk of discomfort (c-index: .897, 95% CI 0.854-0.930; p < .001). Conclusions:The HDR questionnaire could be useful for identifying inpatients at risk of discomfort, but further prospective studies should externally validate these results. Implications in Nursing Management:Nurses are the healthcare professionals with better access to patients and the first in identifying complications of hospitalization.Patients' discomfort could be routinely assessed during hospitalizations using the HDR questionnaire. Nurse managers should play an important role in this accomplishment, by promoting its use and knowledge among the nurse staff. K E Y W O R D S comfort, hospitalization, nursing, risk assessmentReceivers operating characteristic curve confirmed that the HDR score had a good predictive ability for identifying patients at risk of discomfort, with a c-index of .897 (95% CI 0.854-0.930, p < .001; Figure 1).According to the Youden index, a score of 20 showed the best combination of sensitivity and specificity. Thus, we established the cut-off value for "at risk of discomfort" as a score >20. When we performed the ROC curve with the HDR score as categorical still showed a good predictive ability for identifying patients at risk of discomfort, with a c-index of 0.817 (95% CI 0.743-0.891, p < .001; Figure 1). The DCA TA B L E 1 Baseline characteristics N = 270 Male sex, n (%) 145 (53.7) Age (years), mean ± SD 57.33 ± 18.7 Body mass index (k/m 2 ), mean ± SD 26.5 ± 5.0 Marital status, n (%) Single 57 (21.1) Married or partner 150 (55.6) Divorced 37 (13.7) Widowed 26 (9.6) Hospitalization stay (days), mean ± SD 6.9 ± 7.8 Hospital size, n (%) Extended bed occupancy 180 (66.7) Reduced bed occupancy 90 (33.3) Main reason for hospitalization, n (%) Medical condition 169 (62.6) Surgical intervention 101 (37.4) Abbreviation: SD, standard deviation.

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