scholarly journals The impact of emotional contagion on workplace safety: Investigating the roles of sleep, health, and production pressure

2021 ◽  
Author(s):  
Laura Petitta ◽  
Tahira M. Probst ◽  
Valerio Ghezzi ◽  
Claudio Barbaranelli
Keyword(s):  
Sleep Disturbances ◽  
Emotional Contagion ◽  
Workplace Safety ◽  
Health Problems ◽  
Poor Sleep ◽  
Emotional Demand ◽  
Workplace Accidents ◽  
Conditional Indirect Effects ◽  
Restorative Sleep ◽  
The Impact

AbstractUsing emotional contagion theory and the Job Demands-Resources model as a theoretical foundation, we tested the proposition that higher levels of contagion of anger (i.e., a demand) vs. higher levels of contagion of joy (i.e., a resource) will be associated respectively with more vs. fewer sleep disturbances and health problems, which in turn are related to more workplace accidents and injuries. Moreover, we examined the moderating impact of production pressure (i.e., a contextual demand) on the relationship between emotional contagion and employee poor sleep and health. Data from 1000 employees in Italy showed that the conditional indirect effects of contagion of anger, but not of joy, on accidents and injuries via sleep and health problems were intensified as levels of production pressure increased. Furthermore, contagion of anger was positively associated with both sleep disturbances and health problems whereas contagion of joy was negatively related to only sleep disturbances. These findings suggest that the effect of anger that employees absorb during social interactions at work likely persists when coming at home and represents an emotional demand that impairs the physiological functions that regulate restorative sleep and energies recharging; and, this effect is even stronger among employees who perceived higher levels of organizational production pressure.

scholarly journals 0785 Associations Between Circadian Preference And Sleep-related Thoughts: Data From The 2015 Sleep In America Poll

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A298-A299
Author(s):  
B Jeon ◽  
F S Luyster ◽  
E R Chasens
Keyword(s):  
Sleep Disturbance ◽  
Sleep Duration ◽  
Sleep Disturbances ◽  
Secondary Analysis ◽  
Logistic Models ◽  
Poor Sleep ◽  
Sleep Habits ◽  
Circadian Preference ◽  
Physical Consequences ◽  
The Impact

Abstract Introduction Evening types of sleep tend to have poorer sleep quality and sleep habits than morning types. Maladaptive beliefs or thoughts about sleep can affect one’s sleep and may differ between evening and morning types. We examined the association between the circadian preference and sleep-related thoughts in U.S adults. Methods A secondary analysis used survey data from the 2015 National Sleep Foundation’s Sleep in America Poll. Questions included normal bedtime and wake-up time for week/work days and weekend/non-work days. Circadian preference was determined by midpoint of sleep calculated as midpoint of sleep on weekends corrected for average nightly sleep duration. Participants were excluded if their sleep midpoint was from noon to midnight. Midpoint of sleep was divided into two groups using median split (“earlier” vs. “later”). Sleep-related thoughts were “worry about getting a good sleep”, “overwhelming thoughts about getting enough sleep”, “motivation to get sleep”, and “concern about serious physical consequences due to poor sleep”; responded often/always or extremely to somewhat for these items were coded as maladaptive. Logistic regression analysis controlling for socio-demographics, sleep duration, and sleep disturbance (PROMIS Scale; higher scores = greater sleep disturbance) was conducted to examine the relationships between midpoint of sleep and sleep-related thoughts. Results The sample (N = 1011) was primarily White (73.6%), male (50.9%), college educated (62.2%), married/partnered (67.6%) with a mean age of 51.65 ± 17.05 years. Mean midpoint of sleep in “earlier” type was 2:33AM and 5:29AM in “later” type. “Later” type had shorter sleep duration on weekdays and longer sleep duration on weekends than “earlier” type (p < .01), but average sleep duration was similar between two types. “Later” type had more “worry” and “overwhelming thoughts” (p < .05) about sleep. In logistic models, midpoint of sleep was significant only for “concern” (p = .02). Conclusion In this study, late chronotype was associated with increased sleep disturbances and greater variability in sleep duration. The relationship between the timing of sleep and thoughts about the impact of impaired sleep remains unclear and an area for further study with objective measures. Support  

Poor sleep quality is associated with perinatal depression. A systematic review of last decade scientific literature and meta-analysis

2019 ◽  
Vol 47 (7) ◽  
pp. 689-703 ◽  
Author(s):  
Ernesto González-Mesa ◽  
Celia Cuenca-Marín ◽  
María Suarez-Arana ◽  
Beatriz Tripiana-Serrano ◽  
Nadia Ibrahim-Díez ◽  
...  
Keyword(s):  
Systematic Review ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Perinatal Depression ◽  
Meta Analysis ◽  
Well Being ◽  
Mental States ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
The Impact

Abstract Background Although pregnancy is frequently associated with mental states of happiness, hope and well-being, some physical and psychological changes can contribute to increased sleep disturbances and worsened sleep quality. Sleep quality has been linked to negative emotions, anxiety and depression. The main objective of this paper was to systematically review the impact of sleep during pregnancy on maternal mood, studying the association between objective and subjective measures of sleep quality and perinatal depression. Methods We performed a systematic review according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, which included studies published between January 2008 and April 2019, and met the following criteria: (i) studies on pregnant women assessing the effects of sleep quality variables on perinatal mood disorders, (ii) studies published in English and (iii) full paper published in a peer-reviewed scientific journal with full-text format available. Results A total of 36 studies published in the last decade met the inclusion criteria for qualitative review and eight of them were suitable for meta-analysis. Both confirmed the negative effects of poor sleep on perinatal mood. However, qualitative analysis showed that unrepresentative samples and low participation rates falling below 80% biased some of the studies. The standard random-effects meta-analysis showed a pooled size effect [ln odds ratio (OR) 1.49 (95% confidence interval [CI] 1.19, 1.79)] for perinatal depression in cases of poor prenatal sleep quality, although heterogeneity was moderate to high [Q 16.05, P ≤ 0.025, H2 2.45 (95% CI 1.01, 13.70)]. Conclusion Poor sleep quality was associated with perinatal mood disturbances. The assessment of sleep quality along the pregnancy could be advisable with a view to offering preventative or therapeutic interventions when necessary.

scholarly journals The relationship between Pittsburgh Sleep Quality Index subscales and diabetes control

2018 ◽  
Vol 15 (3) ◽  
pp. 210-219 ◽  
Author(s):  
Onala Telford ◽  
Clarissa J Diamantidis ◽  
Hayden B Bosworth ◽  
Uptal D Patel ◽  
Clemontina A Davenport ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Quality Index ◽  
Sleep Disturbances ◽  
Pittsburgh Sleep Quality Index ◽  
Diabetes Control ◽  
Poor Sleep ◽  
Medication Nonadherence ◽  
Mediating Factor ◽  
The Impact ◽  
The Relationship

Objectives Data suggest that poor sleep quality as measured by the Pittsburgh Sleep Quality Index (PSQI) contributes to suboptimal diabetes control. How the subscales comprising the PSQI individually relate to diabetes control is poorly understood. Methods In order to explore how PSQI subscales relate to diabetes control, we analyzed baseline data from a trial of a telemedicine intervention for diabetes. We used multivariable modeling to examine: (1) the relationship between the global PSQI and hemoglobin A1c (HbA1c); (2) the relationships between the 7 PSQI subscales and HbA1c; and (3) medication nonadherence as a possible mediating factor. Results Global PSQI was not associated with HbA1c ( n = 279). Only one PSQI subscale, sleep disturbances, was associated with HbA1c after covariate adjustment; HbA1c increased by 0.4 points for each additional sleep disturbances subscale point (95%CI 0.1 to 0.8). Although the sleep disturbances subscale was associated with medication nonadherence (OR 2.04, 95%CI 1.27 to 3.30), a mediation analysis indicated nonadherence does not mediate the sleep disturbances-HbA1c relationship. Discussion The sleep disturbances subscale may drive the previously observed relationship between PSQI and HbA1c. The mechanism for the relationship between sleep disturbances and HbA1c remains unclear, as does the impact on HbA1c of addressing sleep disturbances.

Sleep in Pregnancy

2019 ◽  
pp. 49-92
Author(s):  
Louise M. O’Brien, PhD, MS ◽  
Galit L. Dunietz, MPH, PhD
Keyword(s):  
Sleep Quality ◽  
Sleep Disturbances ◽  
Current Knowledge ◽  
Well Being ◽  
Poor Sleep ◽  
Fetal Origins ◽  
Maternal Sleep ◽  
Disturbed Sleep ◽  
The Impact ◽  
In Pregnancy

Pregnancy is the time during which one or more offspring develops inside a woman. This chapter focuses on sleep quality and emergence of sleep disorders in pregnancy, which has implications for both the fetus as well as the mother. An overview of empirical evidence of the association between disturbed sleep in pregnancy and pregnancy-related outcomes is provided along with a ion of The chapter also reviews common sleep disturbances in pregnancy, such as sleep-disordered breathing, insufficient sleep, poor sleep quality, and restless legs syndrome, and synthesizes current knowledge of the impact of poor sleep on pregnancy outcomes, with a particular emphasis on fetal well-being. Evidence is also presented on the potential for maternal sleep to influence fetal origins of chronic disease.

scholarly journals Sleep Deficiency and Sleep Health Problems in Chinese Adolescents

2012 ◽  
Vol 6 ◽  
pp. CMPed.S8407 ◽  
Author(s):  
Victor Kang ◽  
Jesus Shao ◽  
Kai Zhang ◽  
Martha Mulvey ◽  
Xue Ming ◽  
...  
Keyword(s):  
School Performance ◽  
Health Problems ◽  
Chinese Adolescents ◽  
Poor Sleep ◽  
Sleep Health ◽  
Sleep Deficiency ◽  
Sleep Length ◽  
High Level ◽  
The Impact ◽  
Inadequate Sleep

A survey of sleep schedules, sleep health, and the impact on school performance was conducted in 585 adolescents in a high school in China. A high level of early and circadian-disadvantaged sleep/wake schedules during weekdays was observed. Significantly shorter sleep duration on weekdays was reported ( P < 0.0001). Older teenagers slept significantly less than the younger teenagers ( P < 0.0001). Complaints of inadequate sleep and sleepiness during weekdays were prevalent. Night awakenings were reported in 32.2% of students. Students with a sleep length of less than 7 hours, complaint of inadequate sleep, or excessive daytime sleepiness during weekdays were more likely to report an adverse effect of poor sleep on performance. The present observations are qualitatively similar to those reported in our study in American adolescents, particularly with respect to Chinese adolescents exhibiting a similar sleep deficiency on weekdays. We concluded that sleep deficiency and sleep health problems were prevalent in the participating adolescents in China, and were perceived to adversely affect school performance.

Short sleep duration and poor sleep quality among migraineurs: A population-based study

Cephalalgia ◽  
2017 ◽  
Vol 38 (5) ◽  
pp. 855-864 ◽  
Author(s):  
Tae-Jin Song ◽  
Chang-Ho Yun ◽  
Soo-Jin Cho ◽  
Won-Joo Kim ◽  
Kwang Ik Yang ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Sleep Duration ◽  
Sleep Disturbances ◽  
Population Based ◽  
Poor Sleep ◽  
Headache Frequency ◽  
Poor Sleep Quality ◽  
Short Sleep Duration ◽  
Short Sleep ◽  
The Impact

Background Sleep disturbances are closely related to migraine. Nevertheless, information regarding the impact of short sleep duration and poor sleep quality on the clinical presentation of migraine at population level is limited. Methods This study was a nationwide population-based survey on adults aged 19–69 years. Headache frequency (attacks/month) and intensity (visual analogue scale, 0–10) were documented. Short sleep duration and poor sleep quality were defined as average sleep duration <6 h/day and Pittsburgh Sleep Quality Index score >5, respectively. The association of sleep parameters with headache frequency and intensity was analysed among migraineurs. Results Of 2695 participants, 143 (5.3%) had migraine. Headache frequency was significantly higher among migraineurs with short sleep duration (2.0 [1.0–12.0] vs. 1.0 [0.3–4.0], p = 0.048) and poor sleep quality (2.0 [0.6–4.7] vs. 1.0 [0.2–3.0], p = 0.009) than among those without. However, headache intensity was similar between migraineurs with short sleep duration and poor sleep quality. Multiple linear regression analyses revealed that short sleep duration was a significant contributing factor for headache frequency (β = 0.210, p = 0.015). Conclusions Self-reported short sleep duration (<6 h per day) is associated with an increased headache frequency among migraineurs in a population-based setting.

The impact of chemotherapy on sleep quality in women undergoing cytotoxic treatment for breast, ovarian, and endometrial cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e23077-e23077
Author(s):  
Evelyn Cantillo ◽  
Lindsay Beffa ◽  
Christine Luis ◽  
Christina Raker ◽  
Katina Robison ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Post Treatment ◽  
Categorical Variables ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Time Points ◽  
Cytotoxic Treatment ◽  
The Impact

e23077 Background: To determine changes in sleep quality among women with breast, ovarian, and endometrial cancer during chemotherapy and to assess the impact of sleep quality on quality of life (QOL). Methods: A prospective cohort study was performed at The Program in Women’s Oncology among chemotherapy naïve women diagnosed with breast, ovarian, or endometrial cancer scheduled to begin treatment. Ovarian and endometrial patients were combined into one group (Gyn) for analysis. Two validated questionnaires: the Pittsburgh Sleep Quality Index (PSQI) and the Functional Assessment of Cancer Therapy (FACT), which measure sleep quality and QOL, respectively, were administered prior to-, halfway through-, completion of-, and 6 months after chemotherapy completion. Descriptive statistics were used to summarize baseline characteristics. Categorical variables were compared by Chi-square (χ2) test and continuous variables by T-test. The PSQI and FACT scores were analyzed by linear or logistic regression with GEEs. Results: Of the 99 women enrolled, 27 had ovarian, 23 had endometrial, and 49 had breast cancer. 97 were included in the analysis. The breast cohort was younger than their Gyn counterparts: 50 vs. 62, (p < .001), and more likely to identify as Hispanic (p = .012). 56% of women endorsed poor sleep quality at baseline. By mid-treatment, both cohorts reported a significant reduction in sleep quality (p = .008) and QOL (p = .0003) that did not persist at end of- or 6 months post-treatment. Increased need for sleep medications (p = .012) and reduction in sleep efficiency (p = .002) were identified mid-treatment. No significant changes in PSQI or FACT-G were seen by end of treatment. At 6 months post treatment, less Gyn patients reported poor sleep quality when compared to baseline (46 vs 53%) while experiencing a significant improvement in QOL (p = .03). Poor sleep quality was correlated with worse QOL at all time points (p < .001). Conclusions: There is a sparsity of research on sleep disturbances in gynecologic malignancies. In this study, three quarters of all women reported poor sleep quality by mid-treatment with concomitant decrease in QOL. Poor sleep was reported by nearly 50% of women at all other time points. Larger studies need to be done to further define the problem and identify areas suitable for interventions.

scholarly journals 0926 Examining Sleep In Parents And Children With Behavioral Or Clinical Sleep Disturbances

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A352-A352
Author(s):  
P Varma ◽  
M L Jackson ◽  
M Junge ◽  
R Conduit
Keyword(s):  
Sleep Quality ◽  
Sleep Disturbance ◽  
Sleep Disturbances ◽  
Sleep Problems ◽  
Poor Sleep ◽  
Clinical Group ◽  
Sleep Habits ◽  
Parents And Children ◽  
Sleep Arousal ◽  
The Impact

Abstract Introduction Sleep problems, such as insomnia are frequently reported in children. These sleep disturbances have either a behavioral (e.g. difficulties initiating or maintaining sleep) or clinical etiology (e.g. autism, asthma and T1 diabetes). Unlike clinical populations, outcomes in parents of children with behavioral sleep problems are underexamined. This study aimed to examine sleep in parents and children with behavioral or clinical sleep disturbances. Methods 290 parents (parents Mage = 35.9±5.2y, children Mage = 4.1± 2.3y) were recruited. Child’s sleep was reported using Child’s sleep habits questionnaire (CSHQ). Parent sleep was assessed using Pittsburgh sleep quality index (PSQI), Pre-sleep arousal scale (PSAS), and Glasgow sleep effort scale (GSES). A demographic question on the nature of child’s sleep disturbance was used to categorize parents into a) behavioral (n=206) or b) clinical group (n=84). Results Overall, 71% of parents and 67% of children had clinically significant sleep disturbance (PSQI ≥ 5 and CSHQ ≥ 41 respectively). Significant associations were observed between CSHQ and a) PSQI (r=0.47, p&lt;.001), b) GSES (r=0.21, p&lt;.001), and c) PSAS (r=0.46, p&lt;.001). Step-wise regression reported that CSHQ was the strongest predictor of PSQI, accounting for 22% variance in scores (p&lt;.001), followed by PSAS (7%). Independent groups t-tests found no differences in parents’ sleep quality (p=.06) and pre-sleep arousal (p=.38) between clinical and behavioral groups. However, 47% of parents in the clinical group took longer than 30 minutes to fall asleep, as opposed to 30% of parents in behavioral group (t(289)=-2.39, p=.01). Conclusion Parents report having poor sleep irrespective of the nature of child’s sleep difficulties. It is possible that parents in the clinical group may underreport their sleep problems due to increased attention towards child’s symptoms and diagnosis. Nevertheless, if any sleep related issues occur in children, the impact on parental sleep should be considered during assessment. Support N/A

scholarly journals The Impact of Mobile Devices on Sleep Quality among Subjects of Primary Health Care Settings in Riyadh, Saudi Arabia

2021 ◽  
Vol 18 (3) ◽  
pp. 567-574
Author(s):  
Ibrahim Muhaydib Al-Muhaydib ◽  
Bader AbdulAziz Al-Tulihi ◽  
Osamah Saleh Alnafisah ◽  
Abdulrahman Muhaidib Almuhaidib ◽  
Ammar Abdulkareem Al-Sayegh ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Sleep Disturbances ◽  
Sampling Technique ◽  
Positive Association ◽  
Smartphone Addiction ◽  
Short Version ◽  
Poor Sleep ◽  
Significant Positive Association ◽  
Cross Sectional ◽  
The Impact

Introduction: Smartphone use has been related to health problems. Studies have indicated that the use of smartphones is associated with Sleep disturbances. However, little is known about the association between Smartphone addiction and sleep quality in Saudi Arabia.Objective: To determine the relationship between sleep quality and the use of a smartphone, specifically before sleep.Method: A cross-sectional study was conducted at four primary healthcare centers with a total of 205 patients participated in the study using a convenience sampling technique. The Pittsburgh Sleep Quality Index (PSQI) and Smartphone Addiction Scale – Short Version (SAS-SV) were used to measure association of Sleep Quality and Smartphone addiction.Results: Two-hundred-fiveparticipants enrolled in the study, of which 99 were female (51%) with a response rate of 84%. Mean age was 36 ±13 years for all participants. Mean PSQI scores were higher among females, single, frequent smartphone users, and unemployed sub- categories; thus, they indicated poorer sleep quality. There was also a significant negative association between age and PSQI scores t(193)= -2.45, p=0.015. Finally, there was a significant positive association between mean SAS-SV score and categorical global PSQI scores t(193)= 3.4, p=0.001.Conclusion: Our study showsahigh prevalence of smartphone addiction and poor sleep quality. Younger age, being single, heavy usage hours of smartphones, and high SAS-SV are significant factors associated with poorer sleep quality.

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.

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