scholarly journals Disproportionality analysis of adverse neurological and psychiatric reactions with the ChAdOx1 (Oxford-AstraZeneca) and BNT162b2 (Pfizer-BioNTech) COVID-19 vaccines in the United Kingdom

2021 ◽  
Author(s):  
Santiago Perez-Lloret ◽  
Nikolai Petrovsky ◽  
Abdallah Alami ◽  
James Crispo ◽  
Donald Mattison ◽  
...  
Keyword(s):  
Adverse Event ◽  
United Kingdom ◽  
Sleep Quality ◽  
Adverse Reactions ◽  
Poor Sleep ◽  
Protective Effects ◽  
Disproportionality Analysis ◽  
Poor Sleep Quality ◽  
P Values ◽  
The United Kingdom

Objective: The information on neurologic or psychiatric adverse reactions to the COVID-19 vaccines is limited. Our objective was to examine the odds of neurological and psychiatric adverse reactions to BNT162b2 (Pfizer-BioNTech) and ChAdOx1 (Oxford-AstraZeneca) COVID-19 vaccines. Methods: We analyzed all Adverse Vaccine Reaction reports to the United Kingdom Medicines and Healthcare products Regulatory Agency between December 9, 2020 and June 30, 2021 that mentioned the BNT162b2 or ChAdOx1 vaccines. We compared the rates of adverse neurological and psychiatric reactions with ChAdOx1 to those with BNT162b2. P-values were obtained by a Bonferroni-adjusted Z-test for proportions. Results: As of June 30, 2021, 53.2 M doses of ChAdOx1 and 46.1 M doses of BNT162b2 had been administered. We extracted information from 300,518 distinct reports. The number of individual adverse neurologic or psychiatric reaction reports were less than 200/M doses administered, except headache which was reported in 1,550 and 395 cases/M doses of ChAdOx1 and BNT162b2, respectively. Compared to BNT162b2, cerebral hemorrhagic or thrombotic events, headaches and migraines, Guillain-Barre syndrome and paresthesias, tremor and freezing, delirium, hallucinations, nervousness, poor sleep quality, and postural dizziness were more frequently reported with ChAdOx1. Reactions more frequently reported with BNT162b2 than ChAdOx1 were Bell's palsy, facial paralysis, dysgeusia, anxiety, and presyncope or syncope. Conclusion: Significant differences in the neurologic and psychiatric adverse event profiles of the ChAdOx1 and BNT162b2 vaccines may exist, emphasizing the need for additional research. The beneficial and protective effects of the COVID-19 vaccines far outweigh the low potential risk of neurologic and psychiatric reactions.

064 Higher Resting HRV Enhances Protective Effects of Self-Reported Resilience Against the Impact of Poor Sleep Quality on PTSS

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A26-A27
Author(s):  
Alisa Huskey ◽  
Daniel Taylor ◽  
Bruce Friedman
Keyword(s):  
Sleep Quality ◽  
Protective Factor ◽  
Stressful Life Events ◽  
Regulatory Control ◽  
Poor Sleep ◽  
Protective Effects ◽  
Poor Sleep Quality ◽  
Resilience Scale ◽  
Negative Impacts ◽  
The Impact

Abstract Introduction Poor sleep quality is a well-established risk for posttraumatic symptoms (PTSS; Casement et al., 2012; Germain et al., 2004; 2005). Conversely, self-reported resilience is a well-established protective factor against PTSS (Mealer et al., 2012; Wrenn et al., 2011) and has also been shown to moderate the negative impacts of stressful life events on sleep quality (Li et al., 2019). Fewer studies have investigated whether autonomic indices of regulatory control moderate the impacts of resilience and sleep quality on PTSS. Resting heart rate variability (HRV) is a widely supported measure of top-down regulation of cognitive, behavioral and autonomic outcomes (Thayer & Ruiz-Padial, 2006). Higher HRV has been linked with increased capacity for stress coping as well as regulation of affect and attention (Bornstein & Suess, 2000). This study investigates whether resting HRV moderates the relationship between resilience, sleep quality, and PTSS. Methods Participants completed the PTSD Checklist for DSM-5 criteria (PCL-5), the Pittsburg Sleep Quality Index (PSQI), and the Connor-Davidson Resilience Scale (CD-RISC-10). A resting baseline assessment of electrocardiogram was used to derive resting-state HRV. Participants (N = 42; 86% women; 76% Caucasian) were recruited from college courses and the surrounding community. Results Individuals were grouped into higher and lower HRV. In the lower HRV group, resilience was not related to PTSS, but poorer sleep quality predicted higher PTSS severity (B=.79). Specific components of sleep quality that predicted PTSS in the lower HRV group were sleep disturbance (B=.38) and daytime dysfunction (B=.76). In the higher HRV group, greater resilience predicted lower PTSS severity (B=-.63), but sleep quality was not related to PTSS. Sleeping medication was the only component that predicted PTSS in the higher HRV group, such that less sleep medication was related to higher PTSS (B=-.751). Conclusion These findings suggest that higher HRV in combination with a self-perception of greater resilience are protective factors against PTSS as well as the effects of poorer sleep quality on PTSS. Resting HRV provides an index of regulatory control that may also be a physiological component of resilience. Support (if any) This project was funded by the Dean’s Discovery Fund at Virginia Tech.

scholarly journals The treatment of sleep problems in autistic adults in the United Kingdom

Autism ◽  
2021 ◽  
pp. 136236132110072
Author(s):  
Elizabeth Halstead ◽  
Emma Sullivan ◽  
Zoe Zambelli ◽  
Jason G Ellis ◽  
Dagmara Dimitriou
Keyword(s):  
United Kingdom ◽  
Sleep Quality ◽  
Online Survey ◽  
Sleep Problems ◽  
Management Strategies ◽  
Self Management ◽  
Poor Sleep ◽  
The United Kingdom ◽  
Autistic Adults ◽  
Sleep Treatment

Sleep problems are one of the most common complaints in autistic adults. This study aimed to report the perspectives of autistic adults in the United Kingdom on treatment of their sleep problems. A total of 288 autistic adults living in the United Kingdom completed an online survey including assessments of their sleep quality using the Pittsburgh Sleep Quality Index, reporting their experiences and preferences of sleep treatment with UK healthcare professionals and, their experiences of self-management of their sleep. Self-report data revealed 58% of participants had not attended a consultation with a healthcare professional regarding their sleep problem despite 90% meeting the criteria for poor sleep quality (based on the Pittsburgh Sleep Quality Index). Of the participants who attended a consultation for their sleep, 72% were prescribed medication and 60% were not satisfied with the outcome. Self-management of sleep problems was not effective for 80% of participants; 41% reported a preference for non-medication options such as education, advice and talking therapies for sleep treatment. This report highlights the need for a fundamental shift in the consideration of sleep problems in autistic adults given the high levels of co-morbidity. The development of successful management strategies in adulthood that importantly considering autistic adults’ preferences could reduce sleep problems and overall improve quality of life for autistic adults. Long term this could also reduce the need for prescribed medication in this population. Lay abstract Sleep problems are one of the most common complaints by autistic adults. This study aimed to report the perspectives of autistic adults on treatment of their sleep problems; 288 autistic adults living in the United Kingdom completed an online survey which assessed their sleep quality. We also gathered data on experiences and preferences of sleep treatment with UK healthcare professionals and their experiences of self-management of their sleep; 58% of autistic adults never had a visit with a healthcare professional regarding their sleep problem, despite 90% meeting the criteria for poor sleep quality. Some of those who attended a consultation for their sleep were prescribed medication (72%), but 60% were not satisfied with the outcome. The participants also reported that sleep self-management was not effective (80%); 41% reported a preference for non-medication including education, advice and talking therapies for sleep treatment. This report highlights the need for a fundamental shift in treatment of sleep problems in autistic adults. The current treatments are not resolving sleep issues; hence, it is imperative to develop management strategies that considers autistic adults’ preferences, reduces sleep problems and thus improves quality of life for autistic 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.

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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