scholarly journals Detrimental Associations of Cumulative Trauma, COVID-19 Infection Indicators, Avoidance, and Loneliness With Sleep and Negative Emotionality in Emerging Adulthood During the Pandemic

2021 ◽  
pp. 216769682110225
Author(s):  
Jennifer A. Harriger ◽  
Nataria T. Joseph ◽  
Janet Trammell
Keyword(s):  
Sleep Quality ◽  
Emerging Adults ◽  
Behavioral Outcomes ◽  
Negative Emotionality ◽  
Avoidant Coping ◽  
Poor Sleep ◽  
Cumulative Trauma ◽  
The Subject ◽  
Prior Trauma ◽  
Behavioral And Emotional Risk

While effects of COVID-19 on physical health are the subject of much research, it is also important to understand risk factors for negative psychosocial and behavioral outcomes. Undergraduates ( N = 490, M age = 20.4) completed measures regarding prior trauma, COVID-19 infection indicators, stressors and trauma, coping, loneliness, social support, sleep behaviors, and negative emotionality. Results demonstrate that pre-existing trauma, COVID-19 stressors, loneliness, and avoidant coping exhibit independent and synergistic associations with poor sleep quality and negative emotionality. Associations between both COVID-19 stressors and avoidant coping with sleep quality were the strongest among those with higher levels of cumulative trauma. Avoidant coping was most strongly associated with higher levels of negative emotions among those reporting COVID infection indicators. Findings suggest a comprehensive set of specific pandemic and general life factors associated with worse outcomes, contributing to the development of a conceptual model of pandemic behavioral and emotional risk for emerging adults.

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.

THE RELATIONSHIP BETWEEN SMART PHONE USAGE AND SLEEP DISTURBANCES AND PSYCHOLOGICAL DISSTRESS AMONG STUDENTS

2017 ◽  
pp. 125-130
Author(s):  
Minh Tam Nguyen ◽  
Phuc Thanh Nhan Nguyen ◽  
Thi Thuy Hang Nguyen
Keyword(s):  
High School ◽  
High School Students ◽  
University Students ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Public Health Problem ◽  
Smartphone Addiction ◽  
Poor Sleep ◽  
School Students ◽  
The Relationship

The increasing use of smartphone among young people is creating negative effects and is an important public health problem in many countries. Smartphone abuse and addiction may cause physical and psychological disorders among users. However, the awarenes on this issue has been inadequate due to lacking of evidence. Objectives: To describe the current situation of smartphone using among students at highschools and universities in Hue city and to examine the relationship between smartphone using and sleep disturbances and psychological disstress among participants. Methods: A cross-sectional study with a randomly selected sample of 1,150 students at highschools and universities in Hue city. SAS-SV scale was used to evaluate phone addiction status, K10 scale was used for psychological distress assessment and PSQI scale was used to examine the sleep quality. Results: The proportion of students at highschools and universities having smartphones was 78.0%. The rate of smartphone addiction among high school students was 49.1% and that among university students was 43.7%. There was 57.3% of high school students had poor sleep quality, and that of university students was 51.6%. There was a statistically significant association between smartphone addiction and sleep disturbances and psychological disstress among participants (p <0.05). Conclusion: The prevalence of smartphone addiction among students at highschools and universities is alarming and is related to sleep disturbances and psychological disstress among participants. There is a strong call to develop intervention to help students to aware and manage the use of smartphone effectively.

scholarly journals Impact and Correlates of Poor Sleep Quality in Japanese White-Collar Employees

SLEEP ◽  
2003 ◽  
Vol 26 (4) ◽  
pp. 467-471 ◽  
Author(s):  
Yuriko Doi ◽  
Masumi Minowa ◽  
Toshiro Tango
Keyword(s):  
Sleep Quality ◽  
White Collar ◽  
Poor Sleep ◽  
Poor Sleep Quality

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 Measuring Subjective Sleep Quality: A Review

2021 ◽  
Vol 18 (3) ◽  
pp. 1082
Author(s):  
Marco Fabbri ◽  
Alessia Beracci ◽  
Monica Martoni ◽  
Debora Meneo ◽  
Lorenzo Tonetti ◽  
...  
Keyword(s):  
Construct Validity ◽  
Sleep Quality ◽  
Psychometric Properties ◽  
Internal Consistency ◽  
Self Report ◽  
Measurement Properties ◽  
Poor Sleep ◽  
Daily Routine ◽  
Factorial Structure ◽  
Poor Sleep Quality

Sleep quality is an important clinical construct since it is increasingly common for people to complain about poor sleep quality and its impact on daytime functioning. Moreover, poor sleep quality can be an important symptom of many sleep and medical disorders. However, objective measures of sleep quality, such as polysomnography, are not readily available to most clinicians in their daily routine, and are expensive, time-consuming, and impractical for epidemiological and research studies., Several self-report questionnaires have, however, been developed. The present review aims to address their psychometric properties, construct validity, and factorial structure while presenting, comparing, and discussing the measurement properties of these sleep quality questionnaires. A systematic literature search, from 2008 to 2020, was performed using the electronic databases PubMed and Scopus, with predefined search terms. In total, 49 articles were analyzed from the 5734 articles found. The psychometric properties and factor structure of the following are reported: Pittsburgh Sleep Quality Index (PSQI), Athens Insomnia Scale (AIS), Insomnia Severity Index (ISI), Mini-Sleep Questionnaire (MSQ), Jenkins Sleep Scale (JSS), Leeds Sleep Evaluation Questionnaire (LSEQ), SLEEP-50 Questionnaire, and Epworth Sleepiness Scale (ESS). As the most frequently used subjective measurement of sleep quality, the PSQI reported good internal reliability and validity; however, different factorial structures were found in a variety of samples, casting doubt on the usefulness of total score in detecting poor and good sleepers. The sleep disorder scales (AIS, ISI, MSQ, JSS, LSEQ and SLEEP-50) reported good psychometric properties; nevertheless, AIS and ISI reported a variety of factorial models whereas LSEQ and SLEEP-50 appeared to be less useful for epidemiological and research settings due to the length of the questionnaires and their scoring. The MSQ and JSS seemed to be inexpensive and easy to administer, complete, and score, but further validation studies are needed. Finally, the ESS had good internal consistency and construct validity, while the main challenges were in its factorial structure, known-group difference and estimation of reliable cut-offs. Overall, the self-report questionnaires assessing sleep quality from different perspectives have good psychometric properties, with high internal consistency and test-retest reliability, as well as convergent/divergent validity with sleep, psychological, and socio-demographic variables. However, a clear definition of the factor model underlying the tools is recommended and reliable cut-off values should be indicated in order for clinicians to discriminate poor and good sleepers.

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