Relationships among sleep quality, coping styles, and depressive symptoms among college nursing students: A multiple mediator model

2018 ◽  
Vol 34 (4) ◽  
pp. 320-325 ◽  
Author(s):  
Yuan Zhang ◽  
Anya Peters ◽  
Joseph Bradstreet
Keyword(s):  
Depressive Symptoms ◽  
Nursing Students ◽  
Sleep Quality ◽  
Coping Styles ◽  
Multiple Mediator Model

scholarly journals Health status, resilience and quality of life of first and fourth year nursing students

2019 ◽  
Vol 10 (2) ◽  
pp. 1
Author(s):  
Rodrigo Marques da Silva ◽  
Ana Lucia Siqueira Costa ◽  
Fernanda Carneiro Mussi ◽  
Fernanda Michelle Santos e Silva ◽  
Keila Cristina Félis ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Nursing Education ◽  
Depressive Symptoms ◽  
Health Status ◽  
Nursing Students ◽  
Sleep Quality ◽  
Depression Scale ◽  
Poor Sleep ◽  
Cross Sectional

Objective: To compare the health status (stress, depressive symptoms and sleep quality), the resilience and quality of life in first and fourth year nursing students.Methods: This is a cross-sectional research conducted in 2016 with 86 students enrolled in first and fourth years of the nursing degree. We applied the instrument for Assessment of Stress in Nursing Students, the Center for Epidemiologic Studies Depression Scale, Pittsburg Sleep Quality Index, Wagnild and Young’s Resilience Scale; and the WHOQOL-BREF. ANOVA (Test F) was applied for data analysis.Results and conclusions: A total of 49 first-year and 37 fourth-year students were sampled for this study. Fourth- year nursing students showed higher levels of stress, lower intensity of depressive symptoms and higher quality of life and resilience levels. The poor sleep quality was prevalent in both groups. Conclusion: although the nursing education potentially contributes for students’ sickness, the experiences lived in this period may strength the resilience skills.Conclusions: Video indexing and retrieval are accomplished by using hashing and $k$-d tree methods, while visual signatures containing color, shape and texture information are estimated for the key-frames, by using image and frequency domain techniques. Experimental results with the dataset of a multimedia information system especially developed for managing television broadcast archives demonstrate that our approach works efficiently, retrieving videos in 0.16 seconds on average and achieving recall, precision and F1 measure values, as high as 0.76, 0.97 and 0.86 respectively.

scholarly journals How do the relationships among health phenomena explain the nursing students’ quality of life?

2021 ◽  
Vol 12 (5) ◽  
pp. 26
Author(s):  
Rodrigo Marques da Silva ◽  
Ana Lúcia Siqueira Costa ◽  
Margareth Heitkemper ◽  
Fernanda Carneiro Mussi ◽  
Karla Melo Batista ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Depressive Symptoms ◽  
Nursing Students ◽  
Sleep Quality ◽  
Latent Variable ◽  
Structural Equation ◽  
Protective Role ◽  
Latent Variable Analysis ◽  
One Year

Background and objective: To know the direct relationships between stress, sleep quality, depressive symptoms, resiliency, and quality of life of nursing students. Less is known about how the simultaneous relationships between these variables may explain the nursing students’ quality of life remains unclear. We assessed how the simultaneous causal relationships among stress, depressive symptoms, sleep quality, and resilience explain the nursing students’ quality of life one year after starting a nursing degree program.Methods: This was a one-year longitudinal study. Data were gathered with validated tools from first university-year nursing students enrolled in two public Brazilian universities at the beginning (n = 117) and end (n = 100) of March 2016. The latent variable analysis- a complement of the R statistical package- was used to estimate the Structural Equation Modelling.Results: The final model showed good fitness and residues quality. Stress decreased sleep quality and increased the intensity of the depressive symptoms. Both of these, directly and indirectly, reduced the quality of life. Resiliency decreased stress levels and depressive symptoms and improved sleep quality.Conclusions: The academic environment has the potential for illnesses, impacting the quality of life. On other hand, resiliency plays a protective role on nursing students by reducing stress and its negative effects. Education institutions need to rethink their curricular elements, promote resilience and create actions to promote students’ health.

scholarly journals Exploring Associations between Internet Addiction, Depressive Symptoms, and Sleep Disturbance among Saudi Nursing Students

2020 ◽  
Vol 14 (1) ◽  
pp. 29-36
Author(s):  
Mohammed AlAmer ◽  
Emad Shdaifat ◽  
Amira Alshowkan ◽  
Aleya G. Eldeen ◽  
Aysar Jamama
Keyword(s):  
Young Adults ◽  
Nursing Education ◽  
Depressive Symptoms ◽  
Nursing Students ◽  
Sleep Quality ◽  
Internet Addiction ◽  
Family Income ◽  
Smoking Status ◽  
Internet Usage ◽  
Negative Consequences

Background: Excessive internet usage is a worldwide problematic issue among young adults and college students. Previous studies showed that Saudi young adults are involved in this problem. Objectives: To determine the prevalence of Internet Addiction (IA), and to find out its relation with depressive symptoms, sleep quality, and demographic variables. Methods: This study used a cross-sectional design. Data were collected from 341 nursing students in Saudi Arabia using three scales: Young’s Internet Addiction Test, Central Epidemiologic Scale for Depression and Pittsburgh Sleep Quality Index. Results: The results showed that 35.1% of students were suffering from frequent problems and 0.9% were suffering from significant problems due to heavy internet usage. The correlation results found a positive moderate correlation between IA and depression (r = 0.401, p < 0.001) and a positive weak correlation with sleep quality (r = 0. 196, p = 0.002). Sleeping and depression were weakly correlated (r = 0.274, p < 0.001). Regression analysis revealed that IA was associated with: smoking status, high family income, duration of usage (3-6 hours and >6 hours), and depressive symptoms. The depressive level was associated with duration of usage (>6 hours), students’ grading point average (GPA), IA, and sleep quality. Sleep quality was found to be associated with duration of usage (>6 hours) and having depressive symptoms. Conclusion: The findings illustrate the need for proper management of internet usage, as well as developing plans to avoid the negative consequences of internet addiction on psychological wellbeing by incorporating nursing education programs about appropriate internet usage.

Association of severity of depressive symptoms with sleep quality, social support and stress among Pakistani medical and dental students: A cross-sectional study

2019 ◽  
Vol 2 (2) ◽  
pp. 211-220
Author(s):  
Ahmed Waqas ◽  
Aqsa Iftikhar ◽  
Zahra Malik ◽  
Kapil Kiran Aedma ◽  
Hafsa Meraj ◽  
...  
Keyword(s):  
Social Support ◽  
Depressive Symptoms ◽  
Medical Students ◽  
Sleep Quality ◽  
Severe Depression ◽  
Dental Students ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Cross Sectional ◽  
Medical And Dental Students

AbstractObjectivesThis study has been designed to elucidate the prevalence of stress, depression and poor sleep among medical students in a Pakistani medical school. There is a paucity of data on social support among medical students in Pakistan; an important predictor of depressive symptoms. Therefore, this study was also aimed to demonstrate the direct and indirect impact of social support in alleviating depressive symptoms in the study sample.MethodsThis observational cross-sectional study was conducted in Lahore, Pakistan, where a total of 400 students at a medical school were approached between 1st January to 31st March 2018 to participate in the study. The study sample comprised of medical and dental students enrolled at a privately financed Pakistani medical and dental school. The participants responded to a self-administered survey comprising of five parts: a) demographics, b) Pittsburgh Sleep Quality Index (PSQI), c) Patient Health Questionnaire-9 (PHQ-9), d) Multidimensional Scale of Perceived Social Support (MSPSS) and e) Perceived Stress Scale-4 (PSS-4). All data were analysed using SPSS v. 20. Linear regression analysis was used to reveal the predictors of depression.ResultsIn total, 353 medical students participated, yielding a response rate of 88.25%. Overall, poor sleep quality was experienced by 205 (58.1%) students. Mild to severe depression was reported by 83% of the respondents: mild depression by 104 (29.5%), moderate depression by 104 (29.5%), moderately severe depression by 54 (15.3%) and severe depression by 31 (8.8%) respondents. Subjective sleep quality, sleep latency, daytime dysfunction and stress levels were significantly associated with depression symptoms. Social support was not significantly associated with depressive symptoms in the regression model (Beta = -0.08, P < 0.09); however, it acted as a significant mediator, reducing the strength of the relationship between depressive symptoms and sleep quality and stress.ConclusionsAccording to our study, a large proportion of healthcare (medical and dental) students were found to be suffering from mild to moderate depression and experienced poor sleep quality. It is concluded that social support is an important variable in predicting depressive symptomatology by ameliorating the effects of poor sleep quality and high stress levels.

753 The role of circadian activity rhythms in depressive symptoms among female nursing students

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A293-A294
Author(s):  
Xin Zhang ◽  
Shih-Yu Lee
Keyword(s):  
Nursing Education ◽  
Depressive Symptoms ◽  
Nursing Students ◽  
Conceptual Model ◽  
Depression Scale ◽  
Psychological Problems ◽  
Circadian Activity ◽  
Activity Rhythms ◽  
Wrist Actigraphy ◽  
Insomnia Symptoms

Abstract Introduction Depression is prevalent among nursing students. Rumination and sleep-wake rhythms are associated to mental illness; however, no clear path has been found. This exploratory study aimed to examine the associations among circadian activity rhythms (CAR), rumination, and depressive symptoms in female nursing students; further, to test a hypothesized CAR conceptual model. Methods A total of 148 female nursing junior students in China completed a battery of questionnaires, including Athens Insomnia Scale (AIS), Ruminative Responses Scale (RRS), and Self-rating Depression Scale (SDS). Wrist actigraphy was used to collect total sleep time, CAR, and acrophase (time of the peak of the fitted activity curve). The path analysis was explored by using SPSS and AMOS. Results The mean age of the students was 20.64 years (SD = 0.86). About 58.8% of the participants were either mild or moderate depressed. About 93.9% of the students reported significant insomnia symptoms (AIS scores &gt;6). Rumination was measured by the RRS (M= 2.01, SD = 0.54), and students scored higher in brooding than that of reflective pondering (2.07 vs. 1.95). The average of TST was 394.59 minutes (SD = 51.92). The CAR ranged from 0.40 to 0.98, with a mean of 0.75 (SD = 0.11). The acrophase ranged from 12:46 to 20:14 (median 16:30), with a later acrophase indicates of a more delayed circadian phase. The final model shows satisfactory fit (χ2= 2.238, p= .327); a better CAR can indirectly reduce depressive symptoms by directly reducing brooding (B = -1.149) and improving insomnia symptoms (B = -6.6443). Conclusion In order to prevent psychological problems of nursing students, ruminating and CAR should be part of health screening. The novel conceptual model provides a basis for reforming nursing education to prevent psychological problems. Support (if any) Chinese National Natural Science Foundation [71603279]

scholarly journals The prevalence and risk factors for depressive symptoms in frontline nurses under COVID-19 pandemic based on a large cross-sectional study using the propensity score-matched method

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hongyan Wang ◽  
Xiaoling Dai ◽  
Zichuan Yao ◽  
Xianqing Zhu ◽  
Yunzhong Jiang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Depressive Symptoms ◽  
Sleep Quality ◽  
Psychological Capital ◽  
Cross Sectional Study ◽  
Poor Sleep ◽  
Sectional Study ◽  
Poor Sleep Quality ◽  
Related Factors ◽  
Cross Sectional

Abstract Introduction To explore the prevalence of depressive symptoms and the associated risk factors in frontline nurses under COVID-19 pandemic. Methods This cross-sectional study was conducted from February 20, 2020 to March 20, 2020 and involved 562 frontline nurses. The effective response rate was 87.68%. After propensity score matched, there were 498 participants left. Extensive characteristics, including demographics, dietary habits, life-related factors, work-related factors, and psychological factors were collected based on a self-reported questionnaire. Specific scales measured the levels of sleep quality, physical activity, depressive symptoms, perceived organization support and psychological capital. Adjusted odds ratios and 95% confidence intervals were determined by binary paired logistic regression. Results Of the nurses enrolled in the study, 50.90% had depressive symptoms. Three independent risk factors were identified: poor sleep quality (OR = 1.608, 95% CI: 1.384–1.896), lower optimism of psychological capital (OR = 0.879, 95% CI: 0.805–0.960) and no visiting friend constantly (OR = 0.513, 95% CI: 0.286–0.920). Conclusions This study revealed a considerable high prevalence of depressive symptoms in frontline nurses during the COVID-19 outbreak, and identified three risk factors, which were poor sleep quality, lower optimism of psychological capital, and no visiting friend constantly. Protecting mental health of nurses is important for COVID-19 pandemic control and their wellbeing. These findings enrich the existing theoretical model of depression and demonstrated a critical need for additional strategies that could address the mental health in frontline nurses for policymakers.

scholarly journals Association between socioeconomic status and longitudinal sleep quality patterns mediated by depressive symptoms

SLEEP ◽  
2021 ◽  
Author(s):  
Ga Bin Lee ◽  
Hyeon Chang Kim ◽  
Ye Jin Jeon ◽  
Sun Jae Jung
Keyword(s):  
Socioeconomic Status ◽  
Depressive Symptoms ◽  
Sleep Quality ◽  
Household Income ◽  
Pittsburgh Sleep Quality Index ◽  
Multinomial Logistic Regression ◽  
Mental Healthcare ◽  
Mediation Effect ◽  
Multinomial Logistic Regression Model ◽  
Mediating Role

Abstract Study Objectives We aimed to examine whether associations between socioeconomic status (SES) and longitudinal sleep quality patterns are mediated by depressive symptoms. Methods We utilized data on 3347 participants in the Korean Genome and Epidemiology Study aged 40–69 years at baseline from 2001 to 2002 who were followed up for 16 years. A group-based modeling approach was used to identify sleep quality trajectories using the Pittsburgh Sleep Quality Index (years 2, 6, 8, 10, and 12). Educational attainment (college graduated or less), monthly household income (≥$2500 or less), and occupation (unemployed, manual labor, and professional labor) at baseline (year 0) were used for analyses. Depressive symptoms were assessed using Beck’s Depression Inventory at year 4. Associations between SES and sleep quality patterns were examined using a multinomial logistic regression model. The mediation effect of depressive symptoms was further examined using PROC CAUSALMED. Results We identified five distinct sleep quality trajectories: “normal-stable” (n = 1697), “moderate-stable” (n = 1157), “poor-stable” (n = 320), “developing to poor” (n = 84), and “severely poor-stable” (n = 89). Overall, associations between SES levels and longitudinal sleep patterns were not apparent after full adjustment for sociodemographic and lifestyle factors measured at baseline. Depressive symptoms, however, tended to fully mediate associations between SES levels and sleep quality patterns (odds ratio range for indirect effects of depressive symptoms: for education, 1.05-1.17; for income, 1.05-1.15). Conclusion A significant mediating role for depressive symptoms between SES levels and longitudinal sleep quality warrants consideration among mental healthcare professionals.

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