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The associations of long-time mobile phone use with sleep disturbances and mental distress in technical college students: a prospective cohort study

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Abstract

Study Objectives To determine the longitudinal associations of long-time mobile phone use (LTMPU) with sleep disturbances and mental distress in a prospective cohort of technical college students. Methods A total of 4,333 (response rate: 91.5%) and 3,396 (response rate: 78.4%) participants were recruited at baseline and eight-month follow-up, respectively. Data were collected by a set of questionnaires including socio-demographics, lifestyle practice, duration of mobile phone use per day, sleep patterns on weekdays and weekends, as well as Insomnia Severity Index, Epworth Sleepiness Scale, reduced Morningness-Eveningness Questionnaire, Beck Depression Inventory, and Zung Self-Rating Anxiety Scale. LTMPU was defined as using mobile phone ≥ 4 hours/day. Results At baseline, 23.5% (n = 1,020) of the participants reported using mobile phone ≥ 4 hours/day. LTMPU at baseline was positively associated with the new incidences (range, adjusted odds ratio 1.31–1.53) of a series of the sleep disturbances and mental distress at follow-up. The discontinuation of LTMPU was associated with an amelioration of the risks of most of these problems. Cross-lagged analyses revealed bidirectional associations of the duration of mobile phone use with poor sleep and mental health outcomes. Conclusions LTMPU predicts the new incidences of most sleep disturbances and mental distress, while discontinuation of LTMPU is associated with amelioration of these problems. Moreover, there are bidirectional associations between the duration of mobile phone use and various sleep and mental outcomes. These findings highlight the critical role of prevention and early recognition of excessive mobile phone use and their accompanied mental and sleep problems.

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... [7]. Recent studies have shown that the usage of mobile devices in children and adolescents may be associated with depression [8][9][10][11][12][13][14][15], anxiety [8,10,15,16] and with behavioural problems [17]. Particular patterns of smartphone-related behaviour, termed as 'problematic smartphone use' may be responsible for poor mental health associations [18]. ...
... [7]. Recent studies have shown that the usage of mobile devices in children and adolescents may be associated with depression [8][9][10][11][12][13][14][15], anxiety [8,10,15,16] and with behavioural problems [17]. Particular patterns of smartphone-related behaviour, termed as 'problematic smartphone use' may be responsible for poor mental health associations [18]. ...
... Three studies looked at young children aged 2-7 years old [50][51][52]. One study that included young people aged up to 21 years old was included in the review as ~ 70% of the samples met the ≤ 18-years old criteria [8]. ...
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Growing use of mobiles phones (MP) and other wireless devices (WD) has raised concerns about their possible effects on children and adolescents’ wellbeing. Understanding whether these technologies affect children and adolescents’ mental health in positive or detrimental ways has become more urgent following further increase in use since the COVID-19 outbreak. To review the empirical evidence on associations between use of MP/WD and mental health in children and adolescents. A systematic review of literature was carried out on Medline, Embase and PsycINFO for studies published prior to July 15th 2019, PROSPERO ID: CRD42019146750. 25 observational studies published between January 1st 2011 and 2019 were reviewed (ten were cohort studies, 15 were cross-sectional). Overall estimated participant mean age and proportion female were 14.6 years and 47%, respectively. Substantial between-study heterogeneity in design and measurement of MP/WD usage and mental health outcomes limited our ability to infer general conclusions. Observed effects differed depending on time and type of MP/WD usage. We found suggestive but limited evidence that greater use of MP/WD may be associated with poorer mental health in children and adolescents. Risk of bias was rated as ‘high’ for 16 studies, ‘moderate’ for five studies and ‘low’ for four studies. More high-quality longitudinal studies and mechanistic research are needed to clarify the role of sleep and of type of MP/WD use (e.g. social media) on mental health trajectories in children and adolescents.
... A number of studies suggest that adolescents with sleep and circadian problems were found to have a higher risk of excessive daytime sleepiness (EDS), social and behavioral problems, and poor mental health (18)(19)(20)(21)(22)(23). Nevertheless, few studies have investigated the inter-relationship among EMU (especially on nighttime use), sleep and circadian problems, and SEBD (24)(25)(26). ...
... Excessive and bedtime EMU of phones were also risk factors for poor mental health, conduct problems, hyperactivity/inattention, and EDS. Adolescents with excessive EMU of phones may rely on phone calls, text messages, and social media networks for communication, which potentially reduces face-to-face interaction with family and peers (26). On the other hand, passive bedtime EMU of televisions was found, interestingly, to be a protective factor for peer relationships. ...
... The data is useful to further investigate the inter-relationship among EMU, sleep and circadian problems, and SEBD that few large-scale studies have examined. The hypothesis that EMU was indirectly related to SEBD through sleep and circadian problems (24)(25)(26) is supported by the findings that insomnia, eveningness, social jetlag, and sleep deprivation mediated the effect of excessive and bedtime EMU on SEBD. In particular, insomnia independently Frontiers in Psychiatry | www.frontiersin.org ...
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Background Electronic media use (EMU) becomes one of the most common activities in adolescents. The present study investigated the deleterious influence of excessive EMU and EMU before bedtime on social, emotional, and behavioral difficulties (SEBD) in adolescents. The role of sleep and circadian problems in mediating the association of EMU with SEBD was examined.MethodsA cross-sectional survey study was conducted with 3,455 adolescents (55.7% female, mean age = 14.8 ± 1.57 years, 36.6% monthly family income < HK$15,000) between December 2011 and March 2012 in Hong Kong. The associations of EMU with sleep and circadian problems and SEBD were analyzed using multiple binary logistic regression and path analysis. Sleep problems were measured by the Insomnia Severity Index and the reduced Horne and Östberg Morningness and Eveningness Questionnaire. Circadian problems were calculated based on established formulas. SEBD was measured using the Strengths and Difficulties Questionnaire. Participants' mental health status was assessed by the General Health Questionnaire.ResultsA longer duration of EMU, excessive EMU (daily duration ≥ 2 h), and bedtime EMU (an hour before bedtime) were associated with the risk of sleep and circadian problems, poor mental health, and SEBD (p < 0.05). Insomnia, eveningness, social jetlag, and sleep deprivation were found to mediate the associations of EMU (including bedtime EMU of computers, electronic game consoles, phones, and televisions, together with excessive EMU of computers for leisure purposes and phones) with mental health and SEBD.Conclusions The findings suggest the need for setting up guidelines and advocacy for education for appropriate EMU and intervention for the associated sleep and circadian problems to ameliorate EMU-related mental and behavioral health problems in adolescents.
... PESM is associated with various sleep problems, such as insufficient sleep, 18 poor sleep quality, [19][20][21] eveningness chronotype 19 and excessive daytime sleepiness. 21 Not only does PESM have a negative impact on sleep throughout the day, 18,21 PESM before bedtime also negatively affects sleep. ...
... PESM is associated with various sleep problems, such as insufficient sleep, 18 poor sleep quality, [19][20][21] eveningness chronotype 19 and excessive daytime sleepiness. 21 Not only does PESM have a negative impact on sleep throughout the day, 18,21 PESM before bedtime also negatively affects sleep. 19,20 It has been reported that electronic screen media use for one hour or more before bedtime is associated with both difficulty falling asleep and unrefreshing sleep. ...
... 58 In addition, screen media use before bedtime may increase the risk of insufficient sleep. 18,59,60 We also observed that college students with pre-bedtime PESM-E were 1.25 times more likely to have poor academic performance, which is consistent with previous studies showing that excessive use of electronic screen media is associated with poor academic performance. 8,10−14 A recent study reported that compared to reading a printed book, screen time was related to lower functional connectivity between the seed area and regions related to language and cognitive control. ...
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Objective: We aimed to examine the effects of sleep quality on the association between pre-bedtime electronic screen media use for entertainment and academic performance among college students. We hypothesized that sleep quality mediates the association between pre-bedtime electronic screen media entertainment use and academic performance among college students. Methods: This was a cross-sectional survey with 1385 participants (age 19.99 ± 1.4 years [range, 17-24 years] and 36.82% males) conducted at Shantou University. The levels of academic performance were based on self-reported academic class ranking from average grades of their last final major examinations. Poor sleep quality was defined as a total score of the Pittsburgh Sleep Quality Index >7. The pre-bedtime prolonged electronic screen media use for entertainment (PESM-E) was defined as the use of electronic screen media for entertainment longer than 60 minutes/night after 10:00 p.m. during the past 6 months. Results: College students with pre-bedtime PESM-E were 1.28-fold more likely to have a poor academic performance than those who used electronic screen media less than 60 minutes (95% confidence interval [CI]: 1.04-1.57, P=0.020). Furthermore, pre-bedtime PESM-E was significantly associated with poor sleep quality (adjusted odds ratio [AOR]=1.87, 95% CI: 1.27-2.74, P=0.001) after controlling for confounders. Mediation model showed that poor sleep quality accounted for 53.08% of the effect of pre-bedtime PESM-E on lower levels of academic performance (Sobel Z=2.04, P=0.041). Conclusion: Pre-bedtime PESM-E is associated with poor academic performance in college students, and this association is mediated by poor sleep quality. Our findings highlight the importance of limiting the use of electronic screen media before bedtime in college students.
... In the transition from adolescence to adulthood, university students are often exposed to heavy psychosocial pressures, making them more vulnerable to mental health problems [1,2]. Data has shown that anxiety, characterized by excessive fears or worries [3,4], has emerged as one of the most prevalent and severe mental health problems among Chinese university students, with a prevalence rate of anxiety symptoms from 7.6 to 54.4% among Chinese university students (age [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29] in the past decade [5][6][7][8][9][10]. Anxiety symptoms are linked to various adverse life outcomes, including lower educational attainment, reduced employment, and poor quality of life [11]. ...
... For example, in the sample of Chinese university students, negative associations were found between PA and anxiety symptoms [16,17]. Liu et al., observed the bidirectional longitudinal relationships between SB (e.g., longtime mobile phone use) and the severity of anxiety symptoms among Chinese university students [18]. Among Chinese students (aged [18][19][20][21][22][23][24][25], anxiety symptoms are significantly associated with sleep duration [19]. ...
... Liu et al., observed the bidirectional longitudinal relationships between SB (e.g., longtime mobile phone use) and the severity of anxiety symptoms among Chinese university students [18]. Among Chinese students (aged [18][19][20][21][22][23][24][25], anxiety symptoms are significantly associated with sleep duration [19]. Although traditional studies highlighted the independent effect of the single movement behavior and confirmed the independent roles, those studies had a poor adjustment for time spent in other movement behaviors [20], which overlooks a clear fact that individual has a fixed budget of 24 h a day that was entirely composed of PA, SB, and sleep. ...
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Background The Canadian 24-Hour Movement Guidelines for Adults was released in 2020. There is a dearth of evidence on the association between adherence to the 24 h movement guidelines and health indicators. This study aims to (a) explore the associations between potential correlates and meeting the 24 h movement guidelines using a sample of Chinese university students; and (b) examine if meeting 24 h movement guidelines is associated with the severity of anxiety symptoms. Methods Cross-sectional findings are based on 1846 Chinese university students (mean age = 20.7 years, 64.0% female). Movement behaviors (physical activity, sedentary behavior, and sleep duration), possible correlates, and anxiety symptoms were measured through self-reported online questionnaires. Logistic regression models were performed to examine the associations. Results We found that male students and those who had a mother with a master’s degree or above, more close friends and higher perceived family affluence were more likely to meet the overall 24 h guidelines. Meeting all 24 h movement guidelines presented the lower odds for severe anxiety symptoms than those meeting fewer recommendations in the 24 h movement guidelines. Conclusions As one of the first to examine the correlates of adherence to the 24 h movement guidelines and the relationship between anxiety symptoms and meeting the guidelines among Chinese university students, our findings contribute to the growing body of evidence linking movement behaviors, psychosocial correlates, and heath indicators. Schools and health providers can encourage movement behaviors that follow the guidelines on campus.
... Three studies examined the association between mobile phone use and subsequent depressive symptoms (Bickham et al., 2015;Khouja et al., 2019;Liu et al., 2019). Two studies found a significant positive association between mobile phone use and subsequent depressive symptoms (Bickham et al., 2015;Liu et al., 2019). ...
... Three studies examined the association between mobile phone use and subsequent depressive symptoms (Bickham et al., 2015;Khouja et al., 2019;Liu et al., 2019). Two studies found a significant positive association between mobile phone use and subsequent depressive symptoms (Bickham et al., 2015;Liu et al., 2019). However, for one study (Bickham et al., 2015), this association was only significant for mobile phone use measured via EMA, not a recall survey or time use diary. ...
... One study examined association between depressive symptoms and subsequent mobile phone use (Liu et al., 2019). The authors found a positive association between these variables. ...
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An increase in time spent on screen-based technologies has been suggested to underlie recent increases in mental health problems among young people. However, this hypothesis has primarily been based on the findings of cross-sectional studies. The aim of the current review was to provide a comprehensive overview of longitudinal studies examining the relationship between screen time and internalising mental health symptoms. PsycINFO, PubMed/Medline and EMBASE were systematically searched for articles published up to August 2020. Thirty-five studies, with sample sizes ranging from 126 to 12,866 participants, met inclusion criteria. The association between screen time and subsequent depressive symptoms was found to be small to very small in size. There was limited evidence of any reverse association between depressive symptoms and subsequent screen time. The association between screen time and depressive symptoms varied between different devices and uses. In contrast to depressive symptoms, evidence to support longitudinal associations between screen time and other internalising mental health symptoms, including anxiety, self-esteem, and general internalising problems, was lacking. Together, these results suggest that the impact of increased screen time on the prevalence of mental health problems among young people is likely to be negligible or small. Further longitudinal studies that examine screen content and motivations underlying screen use are required to better discern any relationship between screen time and internalising mental health symptoms.
... Bedrooms are defined as rooms containing a bed and studies confirm that people spend most of their time in these rooms of the house [4]. Sleep studies have determined that the sleep environment and lifestyle factors can influence sleep [5][6][7] and insufficient sleep has many consequences affecting health across all age groups [8]. However, the dynamic nature of the spatial experience, and its possible effects on sleep habits are rarely considered in previous studies, therefore it has shaped the framework of this study. ...
... Some previous studies have shown that there is a relationship between lack of sleep and the activities taking place in the bedroom, affecting sleep quality, such as the excessive use of the mobile phone [7]. For a healthy sleep, experts suggest maintaining a dark and gadget-free bedroom and getting rid of distractions in the room that might affect sleep [26]. ...
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The purpose of this study is to evaluate the multi-functional use of the domestic sleep environment (bedroom) and present evidence on outcomes that can be identified. By looking at the sleep environment in a broader context and considering the use of the bedroom space besides sleeping, this research responds to an information gap in sleep studies. A survey with multiple-choice questionnaire items was conducted with 304 participants in Australia to investigate the relationship between occupants’ use of the bedroom space and their sleep habits. We found evidence that today’s bedrooms are used for more than just sleeping, reflecting the respondents’ multi-functional needs. Of the respondents, 60% agreed to have a consistent sleeping routine, while 49% answered they have/might have a sleep problem. The mean hours spent in a sleeping environment are 9.31, while the sleeping mean hours are 7.12. While 40% reported using the bedroom as their living space, 61% said they prefer to use it only for sleep. Age, occupation and the bedroom’s location affect bedroom use and preferences. This study provides an initial inquiry into developing design strategies and understanding on the intertwined relationship between sleep and its environment.
... Ultimately, 18 studies were included in the meta-analysis. Table 1 and Supplementary File 2 show the characteristics of the 18 included studies (35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52). Overall, the studies included 241,398 individuals, with sample sizes ranging from 435 (51) to 100,517 (49). ...
... All included studies were observational studies. Half were conducted in Europe (35,40,44,45,47,(49)(50)(51)(52), while five (38,41,42,46,48) and four (36,37,39,43) were in Asia and North America, respectively. Two studies (43,46) only included female participants, while four (36,44,45,47) reported the results for male and female participants, respectively. ...
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Background The impact of screen time on mental health, including depression, has attracted increasing attention from not only children and adolescents but also the elderly. Thus, we conducted a meta-analysis of cohort studies to evaluate the association between screen time and depression risk. Methods The PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched for cohort studies up to May 2022, and the reference lists of the included studies were also retrieved. A random-effect model was used to estimate the combined effect size. Heterogeneity was assessed with the I ² statistic. Potential publication bias was evaluated using a funnel plot and Begg’s and Egger’s tests. Results The final analysis included 18 cohort studies with a combined total of 241,398 participants. The pooled risk ratio (RR) was 1.10 (95% confidence interval: 1.05–1.14), with significant heterogeneity ( I ² = 82.7%, P < 0.001). The results of subgroup analyses showed that the pooled RRs varied according to geographic locations, gender, age group, screen time in the control group, depression at the baseline, and whether the study was conducted during the COVID-19 pandemic. No obvious evidence of publication bias was found. Conclusion This study indicates that screen time is a predictor of depressive symptoms. The effects of screen time on depression risk may vary based on the participant’s age, gender, location, and screen time duration. The findings could have important implications for the prevention of depression.
... Despite the convenience and practicability, the excessive use of mobile phone has also raised a myriad of sleep problems. [6] Similarly in India, rapidly growing digitalization and a new shift from traditional mode of working and learning to online mode has been increased rapidly. According to "Healthy living survey'' the Index rating behaviour (e.g., sleeping habits and exercise) is given a 66 percent weightage and rest account for satisfaction with health. ...
... So, ultimately people get less sleep and become victims of sleep disorders. [6] The people of this generation are giving least importance to the rest and sleep. Instead, sleep is an essential requisite for human beings. ...
... Unlike stationary televisions and computers, portable mobile phones, especially smartphones, allow for multiple activities such as social networking, entertainment, and real-time interactions and therefore continuous stimulation for young people. Mobile phone time of > 4 h/ day predicted short sleep duration < 7 h and insomnia symptoms in a prospective cohort study (Liu et al., 2019). Screen-emitted blue light as a source of artificial light at night could suppress melatonin levels and disrupt circadian rhythms (Heo et al., 2017). ...
... The possibility of reverse causation between sleep problems and screen time remains understudied. Insomnia symptoms predicted screen time in a prospective cohort of university students (Tavernier & Willoughby, 2014), but the results were not replicated in another similar longitudinal study (Liu et al., 2019). Since both studies relied on retrospective self-reported data collected at a few time points with a recall period up to one month, their discrepant findings could be due to recall bias and failures to capture day-to-day variations in sleep parameters and screen time (i.e., the within-person level). ...
Article
Objectives To explore associations of screen time (total, mobile gaming) with sleep problems in Chinese young adults. Methods This was a 4-week daily morning (completion rate=82.1%, 909/1107) and evening (completion rate=92.4%, 1061/1148) assessment study in 41 university students (22 female, mean age=22.3 [SD 4.2] years). Short sleep duration<7 hours, difficulty initiating sleep, difficulty maintaining sleep, early morning awakening, and any of these three insomnia symptoms were self-reported in the morning. Mobile gaming time was self-reported in the evening, whilst total screen time was objectively tracked. Bayesian multilevel mixed-effects modeling disaggregated between- and within-person associations. Results Between person, longer mobile gaming time predicted short sleep duration (adjusted odds ratio [AOR]=1.90, 95% CI 1.39, 2.69), any insomnia symptoms (AOR=1.59, 95% CI 1.20, 2.11), difficulty initiating sleep (AOR=3.05, 95% CI 1.51, 6.24), and difficulty maintaining sleep (AOR=2.19, 95% CI 1.18, 3.74). Short sleep duration (adjusted b=0.99, 95% CI 0.05, 1.95), any insomnia symptoms (adjusted b=1.19, 95% CI 0.24, 1.94), and difficulty initiating sleep (adjusted b=1.72, 95% CI 0.11, 3.19) reversely increased mobile gaming time. Within person, any insomnia symptoms (adjusted b=0.17, 95% CI 0.04, 0.31) and early morning awakening (adjusted b=0.28, 95% CI 0.08, 0.48) increased next-day mobile gaming time. Total screen time was not associated with sleep problems both between and within person. Conclusions Bidirectional between-person associations of mobile gaming time with short sleep duration and insomnia symptoms informed multiple-health-behavior-change interventions. Unidirectional within-person associations of insomnia symptoms with next-day mobile gaming time informed just-in-time adaptive interventions addressing daily variations in insomnia symptoms. [250/250 word limits]
... A few longitudinal studies have examined the causal relationship between the two. An 8-month follow-up survey of Chinese vocational school students reported that excessive Internet use was a contributor to insomnia (40). At present, most studies focus on sleep problems and insomnia from the perspective of Internet addiction and problematic Internet use. ...
... More than 79.7% of students with insomnia symptoms use the Internet for more than 5 h per day, in another words, prolonged Internet use has been linked to insomnia, which is consistent with a number of studies on Internet overuse, and the overuse or poor use of related electronic products (67)(68)(69)(70). The present study also found that more than 5 h of Internet use is a risk factor for chronic insomnia, it has to do with a longitudinal design for mobile excessive use of relation with insomnia results consistent, namely insomnia may be the result of excessive use of network rather than a cause (40). Similarly, two longitudinal studies in Italy found a strong association between smartphone use and insomnia, with increased use of electronic devices within 2 h of bedtime exacerbating insomnia symptoms, and reduced use time improving insomnia symptoms (57,58). ...
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There has been sufficient evidence for the relationship between lifestyle and insomnia in the general population, but for individuals who already suffer from insomnia, it is not clear whether a healthy lifestyle can also pose similar benefits. The present study investigated the roles of different aspects of lifestyle in the development of individual insomnia by tracking insomnia symptoms of college students during the COVID-19 lock-down. Two surveys were conducted on 65,200 college students in the process of home isolation in Guangdong Province of China, at the pandemic outbreak period (T1) and the initial remission period (T2), respectively. Given the objectives of the present study, a total of 1,702 college students with clinical insomnia from T1 were selected as subjects. Insomnia symptoms were assessed using the Youth Self Rating Insomnia Scale (YSIS), while demographic information, epidemic exposure, and lifestyle were all measured by self-developed questionnaire, through network survey. The 1,702 college students (mean age ± standard deviation, 20.06 ± 1.46, range 16-25; 71.9% females) with insomnia symptoms were divided into three trajectory groups: recovery group, remission group, and chronic insomnia group according to their insomnia scores in T2 phase. The results showed that there was no significant difference in demographic backgrounds or epidemic exposure among the three groups, however, there were significant differences in food intake, exercise, and Internet use. The regression results further showed that both the recovery group and the remission group adopted more regular food intake than the chronic group. The recovery group exhibited better daily exercise habits than both the remission group and the chronic group. The duration of Internet use was significantly shorter for the recovery group than for the chronic group. These findings indicate a strong relationship between the lifestyle and the recovery of insomnia for college students isolated at home during the epidemic period. Significance of the different aspects of lifestyle on the recovery of insomnia are discussed.
... Previous studies used reported 505 questionnaires to assess use of mobile communication devices for screen activities such 506 as other mobile phone uses than calling, tablet use, or laptop use. They found that 507 higher all-day device use was related to excessive daytime sleepiness(Brunetti et al., 508 2016;Liu et al., 2019;Mak et al., 2014) and higher symptoms of sleep disturbances 509(Jiang et al., 2015;Kenney and Gortmaker, 2017;Liu et al., 2019; Söderqvist et al., 510 2008) in adolescents and young adults at 10-24 years old. Moreover, the use of screen 511 devices in the evening has been related to more symptoms of sleep disturbances and less 512 objective sleep efficiency at ages between 3 and 21 years old(Akçay and Akçay, 2018; 513 Amra et al., 2017;Bartel et al., 2016;Bruni et al., 2015;Dube et al., 2017; Fobian et al., 514 2016;Johansson et al., 2016;Lemola et al., 2015;Murugesan et al., 2018; Nathanson 515 and Beyens, 2018;Olorunmoteni et al., 2018). ...
... Previous studies used reported 505 questionnaires to assess use of mobile communication devices for screen activities such 506 as other mobile phone uses than calling, tablet use, or laptop use. They found that 507 higher all-day device use was related to excessive daytime sleepiness(Brunetti et al., 508 2016;Liu et al., 2019;Mak et al., 2014) and higher symptoms of sleep disturbances 509(Jiang et al., 2015;Kenney and Gortmaker, 2017;Liu et al., 2019; Söderqvist et al., 510 2008) in adolescents and young adults at 10-24 years old. Moreover, the use of screen 511 devices in the evening has been related to more symptoms of sleep disturbances and less 512 objective sleep efficiency at ages between 3 and 21 years old(Akçay and Akçay, 2018; 513 Amra et al., 2017;Bartel et al., 2016;Bruni et al., 2015;Dube et al., 2017; Fobian et al., 514 2016;Johansson et al., 2016;Lemola et al., 2015;Murugesan et al., 2018; Nathanson 515 and Beyens, 2018;Olorunmoteni et al., 2018). ...
Article
Objective To investigate the association of estimated all-day and evening whole-brain radiofrequency electromagnetic field (RF-EMF) doses with sleep disturbances and objective sleep measures in preadolescents. Methods We included preadolescents aged 9–12 years from two population-based birth cohorts, the Dutch Generation R Study (n = 974) and the Spanish INfancia y Medio Ambiente Project (n = 868). All-day and evening overall whole-brain RF-EMF doses (mJ/kg/day) were estimated for several RF-EMF sources including mobile and Digital Enhanced Cordless Telecommunications (DECT) phone calls (named phone calls), other mobile phone uses, tablet use, laptop use (named screen activities), and far-field sources. We also estimated all-day and evening whole-brain RF-EMF doses in these three groups separately (i.e. phone calls, screen activities, and far-field). The Sleep Disturbance Scale for Children was completed by mothers to assess sleep disturbances. Wrist accelerometers together with sleep diaries were used to measure sleep characteristics objectively for 7 consecutive days. Results All-day whole-brain RF-EMF doses were not associated with self-reported sleep disturbances and objective sleep measures. Regarding evening doses, preadolescents with high evening whole-brain RF-EMF dose from phone calls had a shorter total sleep time compared to preadolescents with zero evening whole-brain RF-EMF dose from phone calls [-11.9 min (95%CI -21.2; −2.5)]. Conclusions Our findings suggest the evening as a potentially relevant window of RF-EMF exposure for sleep. However, we cannot exclude that observed associations are due to the activities or reasons motivating the phone calls rather than the RF-EMF exposure itself or due to chance finding.
... These psychological processes may extend to the pre-sleep period, resulting in unpleasant intrusive thoughts, dysfunctional beliefs and attitudes about sleep, selective attention and monitoring to sleep-related threat, and misperception of sleep deficit. They may cause difficulty in initiating sleep and delayed sleep phase (45). Depressive symptoms are characterized by social withdrawal (46), poor interpersonal skills (47) and difficulty in coping with peer/family stressors (48). ...
... Thirdly, all the questionnaires in this study were self-reported. Although the self-report questionnaires provide a rapid access to a large number of college students' mental health status data via the Internet (45), the data may be prone to social desirability bias (55). ...
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Background: This study investigates the mediating effect of rumination on the associations between depressive symptoms and insomnia. Methods: This is a cross-sectional study. Insomnia Severity Index (ISI), Ruminant Response Scale (RRS) and Beck Depression Inventory (BDI) were determined in 12,178 college students in Qinghai province by a questionnaire network platform. Results: The prevalence of insomnia was 38.6% in the participants. Insomnia symptoms [interquartile range: 6 (3, 9)], depressive symptoms [interquartile range: 5 (1, 9)], and rumination [interquartile range: 22 (20, 26)] were positively correlated (r = 0.25–0.46, p < 0.01). Mediation effect analysis showed that the depressive symptoms affected insomnia directly and indirectly. The direct effect and the indirect effect through rumination account for 92.4 and 7.6% of the total effect, respectively. Conclusion: The study shows that insomnia, depressive symptoms, and rumination are related constructs in college students in Qinghai province. It demonstrates the direct effects and the rumination-mediated indirect effects between depressive symptoms and insomnia; the direct effects seem to be dominant.
... Disturbed sleep, whether due to quality and timing or duration can have many adverse health consequences. The most obvious concerns include fatigue and cognitive focus, also, mood can be greatly affected [25]. Based on previous studies sleep disturbance is a negative outcome of problematic smartphone use among university students [8]. ...
... Accordingly, Polman et al. found that in confrontation with a frustrating situation, college students who reported the overuse of smartphones and insufficient sleep time, because of the lack of affect control and frustration tolerance, had significantly higher levels of aggression, compared with those with enough sleep time [21]. A plausible explanation for the mediating effects of sleep disturbance may be that problematic smartphone use can disrupt university students' normal sleep patterns; this contributes to a high risk of aggression [25]. Another explanation is that sleep deprivation results in poor prefrontal cortical functioning. ...
Article
Background: Despite several benefits, research has found that problematic smartphone use is positively associated with behavioral problems. However, the internal mechanisms underlying this relationship need further investigation. So, the current study aimed to investigate the mediating role of sleep disturbance in the relationship between problematic smartphone use and aggression. Methods: The research design was descriptive-correlational. Also, the study population included the male university students of the Islamic Azad University of South Tehran Branch in the academic year of 2019-2020. Using the convenience sampling method, a total number of 213 participants from two faculties (Faculty of Human Sciences and Faculty of Law and Political Sciences) were selected and tested by Buss-Perry Aggression Questionnaire, Smartphone Addiction Scale-Short Version, and Pittsburgh Sleep Quality Index. Then, the Pearson correlation and path analysis were conducted to analyze the data. Results: The results revealed the significant and direct effects of problematic smartphone use on aggression (β=0.12, P
... In the domain of hopelessness, a factor related to anxiety and depression, Tao et al. (47) drew the same trend in college students, which implied that after quarantine, hopelessness was reduced. Combining previous studies' results, we estimate that less time spent on mobile phones and more physical activities can reduce anxiety, depression, and sleep disturbance and further dilute the bidirectional relationship (42,48). ...
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Object: Repeated quarantine policies over the past 3 years have led to poor psychological consequences for the public. Previous studies have proved that the quarantine policy leaves individuals vulnerable to anxiety, depression, and insomnia, especially among college students. This study aims to explore whether psychological problems during isolation continue with the release of isolation. Methods: Overall, 2,787 college students both answered a web-based survey during and after the closure management was lifted. The Patient Health Questionnaire, Generalized Anxiety Disorder Scale, and Youth Self-rating Insomnia Scale were measured. The cross-lagged path model was used to explore the influence of psychological impact during isolation on the individual after the release. Results: We found that anxiety and sleep disturbance levels alleviated significantly after quarantine, except for depression. As expected, a bidirectional relationship exists between anxiety, depression, and sleep disturbance. Moreover, depression and sleep disturbance can predict post quarantine depression, sleep disturbance, and anxiety, yet anxiety cannot predict sleep disturbance afterward. Conclusion: Timely and effective intervention for anxiety, depression, and insomnia during isolation is essential for individuals to repair themselves quickly after the release.
... Recent research has shown that PSU severity was moderately correlated with anxiety and depression severity [61], and that this association extends to adults of all ages [62]. PSU and depression interrelationships found in prospective cohort studies are likely to be significantly bi-directional [63,64]. On the one hand, PSU is associated with a lack of social support, which can induce emotional disorders such as anxiety and depression [65]. ...
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Background This study aimed to categorize different subgroups of problematic smartphone use in Chinese college students. Differences in gender and psychosocial characteristics of the categorized groups were also examined. Methods A total of 1123 participants completed the Mobile Phone Addiction Index Scale, the Center for Epidemiologic Studies Depression Scale, the Perceived Social Support Scale, and the Perceived Stress Scale. Using latent profile analysis, we identified different subgroups of problematic smartphone use in college students. Multivariate logistic regression analysis was implemented to examine the relationship between latent classes and demographic and psychosocial covariates. Results The four following latent classes were identified: a low-risk group, a moderate-risk with no evasiveness group, a moderate-risk with evasiveness group, and high-risk group that accounted for 11%, 24.1%, 35.5%, and 29.4% of the total sample, respectively. Further analysis revealed that female participants were more likely to be in the moderate-risk with evasiveness and high-risk groups, and individuals with depressed mood were more likely to be in the moderate-risk and high-risk groups. Conclusions Classifying college students according to the features of problematic smartphone use is potentially useful for understanding risk factors and developing targeted prevention and intervention programs.
... Thus, to improve health and wellness in adolescents, individuals should set boundaries on smartphone use, especially at bedtime [86]. Given that people use smartphones in bed, there is a bidirectional relation between the duration of smartphone use and various sleep disturbances [87]. Findings show that screen time is associated with poor sleep. ...
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Smartphones have become an integral part of people’s everyday lives. Smartphones are used across all household locations, including in the bed at night. Smartphone screens and other displays emit blue light, and exposure to blue light can affect one’s sleep quality. Thus, smartphone use prior to bedtime could disrupt the quality of one’s sleep, but research lacks quantitative studies on how smartphone use can influence sleep. This study combines smartphone application use data from 75 participants with sleep data collected by a wearable ring. On average, the participants used their smartphones in bed for 322.8 s (5 min and 22.8 s), with an IQR of 43.7–456. Participants spent an average of 42% of their time in bed using their smartphones (IQR of 5.87–55.5%). Our findings indicate that smartphone use in bed has significant adverse effects on sleep latency, awake time, average heart rate, and HR variability. We also find that smartphone use does not decrease sleep quality when used outside of bed. Our results indicate that intense smartphone use alone does not negatively affect well-being. Since all smartphone users do not use their phones in the same way, extending the investigation to different smartphone use types might yield more information than general smartphone use. In conclusion, this paper presents the first investigation of the association between smartphone application use logs and detailed sleep metrics. Our work also validates previous research results and highlights emerging future work.
... Similar results were found in previous research (Al Battashi et al., 2020;Çagan & Koca, 2020;Nursalam, Octavia, Tristiana, & Efendi, 2019). Use of the smartphone for over five hours a day was found to be significantly associated with both shorter sleeping duration and bad quality of sleep (Alosaimi, Alyahya, Alshahwan, Al Mahyijari, & Shaik, 2016;Liu et al., 2019;Tamura, Nishida, Tsuji, & Sakakibara, 2017). The crucial issue is that the level of smartphone use is very high among university students (Alsayed, Bano, & Alnajjar, 2020), affecting the prevalence of insomnia in the same group. ...
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Background Insomnia is the most predominant sleep disorder affecting the general population and is a significant health concern. Objective: The aim of this study was to explore the prevalence and predictors of insomnia among Omani university students. Methods A cross-sectional descriptive design was used. Six hundred and thirty-two university students were recruited through convenience sampling and completed four self-reported surveys: (1) Depression, Anxiety and Stress scale; (2) Smartphone Addiction scale; (3) Insomnia Severity Index, and (4) demographics sheets, accessed through the Google Forms link posted on Twitter. Results Almost two thirds of the participants suffered from insomnia, of whom a third part suffered from sub-threshold insomnia, another third had moderate insomnia, and a tenth part suffered from severe insomnia. A multivariate regression analysis revealed that age, preparing for exams, smartphone addiction, and stress were significant associated factors of insomnia. Conclusion Although the study identified high level of insomnia and significant associations between insomnia and exam preparation, smartphone addiction, and stress; insomnia is a far more complex phenomenon. We therefore recommend further studies to follow up the development of this population and to identify actions to combat this high level of insomnia. Nurses, public health workers, health coaches, and other clinically active professionals could collaborate to build programs to promote healthy use of smartphones in young individuals in order to combat insomnia.
... This result was in line with a previous study reporting that adolescents' prolonged smartphone use of ≥5 h on the weekend was associated with an increased risk of depressive symptoms (71). A prospective cohort study re-reported that smartphone use of ≥ 4 h/day could predict mental health problems in a college student sample (45,(72)(73)(74). The possible mechanism underlying this relationship remains to be clarified. ...
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Background The COVID-19 pandemic has had a wide range of behavioral and psychological effects on the general population. This study examined the relationship between fear of COVID-19, daily smartphone use, sleep disturbance, and depression in the general population during the early stage of COVID-19. Methods An online nation-wide survey was conducted from March 20 to April 10, 2020. Sociodemographic information, including age, gender, educational attainment, vocation, and duration of self-isolation, was collected; fear of COVID-19 and other objective exposures, daily hours of smartphone use, night sleep duration, sleep disturbance, and depressive symptoms were measured with structured questions and PHQ-9. There were 1,280 questionnaires in total, and 1,250 valid questionnaires remained. Results The prevalence of sleep disturbance and depression were found to be 13.1 and 10.7%, respectively. Feelings of extreme fear, longer smartphone use, difficulty initiating sleep, and early morning awakening were significant risk factors for depression. Daily hours of smartphone use, difficulty initiating sleep, and early morning awakening partially mediated the association between feeling extremely scared of the pandemic and depression. Conclusion Psychological interventions in a major public health crisis should focus more on the subjective perception of pandemic fear. At the same time, daily smartphone use and sleep disturbances could serve as targets for monitoring and intervention for depression during a pandemic.
... In fact, excessive smartphone use has been linked with impaired cognitive functions and mental health problems among children, adolescents, and young adults [10,11]. Some longitudinal studies have found that more frequent mobile phone use among teenagers (11-21 y.o.) predicted a higher incidence of depressive and anxiety symptoms [12,13] as well as higher hyperactivity/inattention and conduct problems [14,15]. Similarly, some cross-sectional studies have shown that greater mobile phone use among children and adolescents (5-19 years) was particularly related to concentration problems, attention problems, hyperactivity symptoms, and conduct problems [10,11]. ...
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There is existing evidence on how excessive screen exposure can be detrimental to cognitive health, and in recent years there has been an increase in the usage of mobile phones by adolescents. We aimed to examine the association between mobile phone screen exposure and cognitive function among a young healthy population. We carried out a cross-sectional study conducted in 632 adolescents (13.89 ± 0.52 years old). Exposure data were collected through self-reported questionnaires, and cognitive outcomes were assessed by different computer-based neuropsychological tests. Compared to students in the lowest tertile (<9 min/day) of mobile phone screen exposure (MPSE), those in the medium tertile (9–20 min/day) showed significantly higher hit reaction time standard error (HRT-SE, higher inattentiveness) = (14.9 ms, 95% CI = 0.6; 29.3), as did as those in the highest tertile (>20 min/day) = (11.1 ms, 95% CI = 2.8; 25.0). When adjusting for confounders, the association held for the medium-MPSE tertile (17.6 ms, 95% CI = 3.4; 31.7). When further adjusting for intermediate factors, an increase in inattentiveness scores was also observed in both groups, with higher HRT-SE values for participants in the medium (15.8 ms, 95% CI = 1.4; 30.3) and highest MPSE tertiles (14.97 ms, 95% CI = 0.9; 29.1). There were no significant associations with fluid intelligence or working memory scores. Overall, our study shows that healthy teenagers reporting higher screen exposure may be affected in their attention performance. However, more studies are needed to determine the causality of these associations and to better shape the screen exposure recommended guidelines for brain health during adolescence.
... Specifically, a series of cross-sectional research revealed that mobile phone addiction is positively associated with depressive symptoms among college students in Turkey, Japan, South Korea, Austrian, and Lebanon (20)(21)(22)(23)(24)(25). A prospective cohort study found that a bidirectional longitudinal relationship between duration of mobile phone use and severity of depression (26). A meta-analysis of 40 studies provided solid evidence that mobile phone addiction was positively correlated with depressive symptoms and sleep disturbances among University students (27). ...
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Background With the continuous updating of mobile phone functions, the phenomenon of mobile phone addiction among University students is becoming more and more serious. It is important to identify the potential risk factors for mobile phone addiction. The aim of the study was to examine whether there is a relationship between mobile phone addiction and depression symptoms in University students, and to investigate whether sleep disturbances play a mediating role between mobile phone addiction and depression symptoms, as well as the moderating role of gender. Methods A cross-sectional study, carried out between September to December 2021, recruited 973 students (478 males) from seven comprehensive universities in western China. The Mobile Phone Addiction Index (MPAI), the Patient Health Questionnaire-9 (PHQ9), and the Pittsburgh Sleep Quality Index (PSQI) were used to complete measures of mobile phone addiction, depressive symptoms, and sleep disturbances. For statistical analyses, descriptive statistics, correlation, regression, mediation and moderated mediation analyses were used. Furthermore, we tested the mediation model and moderated mediation model using the SPSS macro PROCESS. Results In this study, it was found that there were positive correlations between mobile phone addiction and depressive symptoms among Chinese University students. Mediation analyses revealed that this relationship was partially mediated by sleep disturbances, but the mediating role was not moderated by gender. Conclusion Sleep disturbances have a partial mediating role in the relationship between mobile phone addiction and depressive symptoms. Our results highlight the critical role of prevention and early identification of mobile phone addiction among University students, especially those with sleep disturbances.
... According to a cross-national study of undergraduate students, 10.4% of them had significant nocturnal sleep issues in the previous month, with Indonesia (32.9%) having the highest percentage and Thailand (3.0%) having the lowest (Peltzer & Pengpid, 2015). Sleep problems have been linked to smartphone addiction and numerous indicators of problematic smartphone usage among university students and teenagers, including prolonged smartphone use, late-night smartphone use, using a smartphone right before bedtime, and severe smartphone use (Demirci et al., 2015;Huang et al., 2020;Liu et al., 2019;Sahin et al., 2013;Shoval et al., 2020). ...
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Online learning and the lack of social interactions during lockdown pushed numerous college students to live employing the internet and social media. This study investigates students' well-being and its associated factors in relation to smartphone use and sleep quality among Indonesian university students during the pandemic. A sample of 327 undergraduate students (68 males and 259 females) anonymously completed the Smartphone Addiction Scale – Short Version (SAS-SV), WHO-Five Wellbeing Index (WHO-5), and Pittsburgh Sleep Quality Index (PSQI), along with several socio-demographic data via an online survey. The data was then analyzed with hierarchical linear regression. The results indicate that gender, perceived physical health, smartphone use, and sleep quality were associated with well-being in university students. The final model predicted 23.4 percent of the WHO-5 scores with a significant increase in predictive value by adding perceived physical health and sleep quality. Therefore to enhance well-being among Indonesian university students, suitable physical activities, good sleeping habits, and controlled smartphone use is needed.
... Adolescents with SMD were found to sleep less than their counterparts without SMD on average, and especially on weekdays. Since adolescents attend school, delays in onset of sleep due to social media activities would likely result in sleep loss during the weekdays (Liu et al., 2019). Night-time use of social media, in particular, could lead to postponed sleep or render individuals cognitively stimulated such that they experience protracted latency before the onset of sleep. ...
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Social Media Disorder (SMD) is characterised by the intense and excessive use of social media. Although previous studies have shown that SMD was associated with poor mental health, research across types of usage and platforms remain limited. Here, we conducted an initial investigation of social media usage across platforms and its relation to anxiety, sleep and loneliness in female adolescents. Forty one 16- to 19-year-old British female adolescents were administered online questionnaires. Intensity of social media activity across Facebook, Instagram, Snapchat and Twitter was measured with the Social Media Disorder Scale. Anxiety was indicated by the Beck Anxiety Inventory Trait, loneliness was examined via a short three-point questionnaire and sleep quality was measured via both the Pittsburgh Sleep Quality Index and self-reported seven-day sleep diaries. Results showed that, compared to those without SMD, users with SMD experienced elevated levels of loneliness and had less sleep on average, and during the weekdays in particular. Only frequency of posting on Facebook, but not general usage, was associated with poorer sleep quality. These preliminary findings showed that social media disorder across platforms and usage could potentially have different associations to mental health and sleep.
... However, the key changes in their psychological and brain development have not yet been completed, making them more vulnerable to the impact of smartphone addiction (9). Extensive use of smartphones may lead to sleep disorders (13) and may also affect emotions and cognition. A high level of smartphone addiction is associated with anxiety, depression, impulsivity, and other types of mental distress among university students (14). ...
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Learning at home during the COVID-19 confinement might affect students' relationships with their peers, teachers, and schools and increase the possibility of smartphone addiction. We hypothesized that attachment anxiety directly and indirectly affects smartphone addiction, with teacher–student relationships, student–student relationships, and school connectedness as mediators. The participants were 999 university students from different regions of China. The results showed that six of the paths were significant except the one between student–student relationships and smartphone addiction. Also, the association between attachment anxiety and smartphone addiction was mediated by teacher–student relationships and school connectedness not but student–student relationships. The current study highlights the mediating effect of school connectedness and teacher–student relationships in the multiple mediation model, and suggests that universities can alleviate the risk of smartphone addiction in distance teaching by cultivating good teacher–student relationships and strengthening students' sense of belonging to their schools.
... Another clinical classification considering sleep disorders is the so-called 'circadian desynchrony', which occurs when sleep/wake schedules are discordant with the individual inner biological clock [58]. This condition is a 'side effect' of shift work but could also possibly be due to the excessive use of the mobile phone which could affect physiological sleep/wake patterns independently from work activities [59]. The presence of circadian desynchrony was linked to an increased risk for metabolic and cardiovascular comorbidities [60e62] and also identified as a probable risk factor for cancer onset [63]. ...
Article
Introduction: Many factors may be hidden behind the global fertility decline observed in Western countries. Alongside the progressively increased age of infertile couples, environmental and behavioural factors, including non-optimal lifestyle habits, should be considered. Among these, sleep disorders have been suggested to be linked to human fertility. Methods: This is a narrative review, describing first sleep physiology, its disturbances, and the tools able to quantify sleep dysfunction. Then, we consider all available studies aimed at investigating the connection between sleep disorders and human fertility, providing a comprehensive view on this topic. Results: Forty-two studies investigating the relationship between sleep habits and human reproduction were included. All the published evidence was grouped according to the aspect of human fertility considered, i.e. i) female reproductive functions, ii) male reproductive functions, iii) natural conception and iv) assisted reproduction. For each of the sub-groups considered, the connection between sleep dysregulation and human fertility was classified according to specific sleep characteristics, such as sleep duration, quality, and habits. In addition, possible physio-pathological mechanisms proposed to support the link between sleep and fertility were summarized. Conclusion: This review summarizes the most relevant findings about the intricate and still largely unknown network of molecular pathways involved in the regulation of circadian homeostasis, to which sleep contributes, essential for reproductive physiology. Thus, many mechanisms seem correlate sleep disorders to reproductive health, such as adrenal activation, circadian dysregulation, and genetic influences. This review highlights the need to properly designed trials on the topic.
... During the pandemic, people search online to access news about COVID-19, and excessive attention to such information could cause an increase in anxiety [2]. Meanwhile, the increased screen time may aggravate the lack of social interaction and physical activity caused by home quarantine, resulting in anxiety symptoms [20,21]. Given the possible impact of screen time changes during COVID- 19, we consider that excessive screen time would contribute to higher anxiety levels. ...
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Under the burden caused by COVID-19 and rapid lifestyle changes, many people increased their screen time due to psychological needs and social requirements. The current study investigated the relationship between screen time changes and anxiety symptoms during the pandemic of COVID-19. Furthermore, we examined whether sleep and physical activity would mediate the association between screen time changes and anxiety. The self-developed questionnaire was delivered online to collect people's changes in anxiety, sleep patterns, and screen time during COVID-19. 970 participants (74.4% female) with an average age of 23 years were involved in this study. After adjusting demographic variables, the ordinal logistic regression analyses revealed that a significant increase in screen time was linked with anxiety. Slightly increased screen time, slightly and significantly decreased screen time did not predict anxiety symptoms during the pandemic. The level of anxiety was significantly higher among respondents who reported decreased sleep quality. Sleep quality directly mediated the association between screen time changes and anxiety, while sleep latency did not. The longer sleep latency caused by increased screen time would amplify anxiety by affecting sleep quality. In addition, the relationship between screen time changes and anxiety was also mediated by physical activity. We concluded that the fluctuation of screen time in a modest range does not affect the anxiety level substantially. The significantly increased screen time would contribute to poor sleep (including longer sleep latency and worse sleep quality) and lack of physical activity, which would lead to higher levels of anxiety.
... Second, both smartphone use and sleep quality are typically measured through survey questions. These self-reported data may be susceptible to recall and/or social desirability biases, as well as underestimation bias due to an internalised unawareness of the intensity and nature of one's smartphone habits (Chen et al., 2016;Fossum et al., 2014;Liu et al., 2019). ...
... Sleep patterns were collected, including habitual bedtimes and wake-up times on weekdays and weekends. Weekend sleep compensation was calculated as the difference between time in bed on weekends and weekdays, and long weekend sleep compensation was defined as compensation ≥2 h (21). ...
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Objective This study aimed to investigate the chronotypes and their relationship with sleep disturbances and mental distress among college students. Methods Students from a university in Guangzhou, China, were recruited through a cross-sectional online survey. Data were collected by self-reported questionnaires including socio-demographics, lifestyles and health conditions, sleep patterns on weekdays and weekends, as well as the reduced Morningness-Eveningness Questionnaire (rMEQ), the Insomnia Severity Index, the Epworth Sleepiness Scale, the Beck Depression Inventory-13, and the Zung Self-Rating Anxiety Scale. Multivariate analyses were performed to examine the associations of chronotypes with sleep compensation, sleep disturbances, and mental distress. Results A total of 1,607 questionnaires were received, among which 1,569 (97.6%) were valid for further analysis. Among these participants [mean age 19.86 ± 1.16 (15–27) years], morning types (M-types), intermediate types (I-types), and evening types (E-types) accounted for 14.9, 71.5, and 13.6%, respectively. The regression analysis revealed that E-types were positively associated with long sleep compensation on weekends (adjusted OR 2.443, 95%CI 1.740-3.429) compared with I-types, while M-types were the opposite (adjusted OR 0.623, 95%CI 0.392–0.990). E-types were also positively correlated with insomnia symptoms (adjusted OR 2.000, 95%CI 1.428–2.801), depressive symptoms (adjusted OR 2.068, 95%CI 1.496–2.858), and anxiety symptoms (adjusted OR 2.188, 95%CI 1.387–3.451). However, no significant association was found between chronotypes and excessive daytime sleepiness. Conclusion Our study found that E-types were associated with long sleep compensation on weekends and insomnia, depression, and anxiety symptoms. Our findings emphasized the importance of early recognition and intervention of E-types and their accompanied sleep problems and mental distress.
... Although the correlation between the former two was not significant, we still found that Chinese working youth who engaged in digital activities would sleep less on workdays and more on free days, which was similar to the previous literature. 54,55 This could be explained by two possible reasons. First, youth sleep is more closely influenced by their work schedules on workdays or weekdays; thus, they must shorten their sleep duration to wake up on time the next day, although they did not sleep during the preceding night. ...
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Purpose: The study aims to examine whether and how digital activities influence sleep issues among working Chinese youth. Methods: This study used data from the China Family Panel Studies (CFPS) a Chinese population-based survey, and employed the multilevel ordinal logistic regression model (MOLRM) to test the associations between digital engagement (whether to engage in digital activity, frequency, and duration) and sleep issues (bedtime, sleep duration, and quality) among Chinese working youth. Additionally, the restricted cubic spline model (RCSM) was adopted to fit the MOLRM to evaluate the nonlinear relationship between digital activity duration and sleep quality, and thus determine the optimal range of digital activity duration. Results: The analysis included 7849 working young adults. The digital usage rate was 84.11%. Digital use was not significantly associated with average, workday, or free-day sleep duration, after controlling for all potential confounders. However, most digital activity indicators could significantly predict bedtime and sleep quality. Furthermore, the RCSM indicated a non-linear relationship pattern between digital activity duration and sleep quality, with a weekly peak point of 25 h. Age significantly moderated the relationship between digital activity, sleep duration and bedtime. Younger youth who used digital media more frequently and for a longer time tended to sleep later and had shorter sleep duration than older youth. Conclusion: Digital usage significantly predicted later bedtime among Chinese working youth; however, it was not linked with sleep duration on workdays or free days. In parallel, a nonlinear correlation between digital activity duration and sleep quality indicated that appropriate digital activity duration (less than 25 h weekly) may contribute to good sleep quality.
... Consistent with the previous literature [14,27,49], we found an increased risk of poor sleep quality associated with IA. A prospective cohort study showed that the overuse of phones (more than 4 hours per day) was associated with the incidence of sleep disturbance and mental health problems among college students during eight months of follow-up [50]. The addictive use of light-emitting gadgets (e.g., smartphones, tabs) before bedtime may extend sleep initiation time, delay the circadian clock, suppress levels of the sleep-promoting hormone melatonin, reduce the amount of rapid eye movement sleep (REMS), and decrease alertness in the morning [51,52]. ...
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Background Internet Addiction (IA) is often shown to be associated with health issues, but no study explicitly examined a possible gradient in the association between different levels of IA and health. This study aimed to examine if the levels of IA had a graded relationship with poor sleep quality, psychological distress, and self-rated health among university students in Bangladesh. Methods In this cross-sectional study, a sample of 625 students from six universities/colleges responded to an online survey that contained measures of internet addiction test (IAT), general health questionnaire (GHQ-12), sleep quality, and self-rated health. Modified Poisson regression models were fitted to estimate the adjusted risk ratios (RR) and confidence intervals (CI) of the associations between IA and health outcomes. Results The IA levels were associated with each of the three health outcomes in a linear fashion. Compared to the lowest IA quintile, the highest quintile remained associated with an increased risk of poor-quality sleeping (RR: 1.77; 95% CI: 1.26, 2.48), psychological distress (RR: 2.09; 95% CI: 1.55, 2.82), and worse self-rated health (RR: 1.46; 95% CI: 1.09, 1.96) after adjusting for socio-demographic covariates. There were also dose-response associations between IAT z-scores and health outcomes. The association between IAT z-scores and psychological distress was significantly stronger in males compared to females (p-value for interaction<0.05). Conclusions The study found strong gradients between levels of addiction to internet and health outcomes, suggesting that increased health risks may exist even at lower levels of internet addiction. The findings highlight the need for departure of current research from a focus on the classic dichotomy of problematic versus not problematic internet use and a move toward recognizing the potential hierarchical effects of IA on health.
... Several studies have shown a positive relationship between PMPU and depression in adolescents (Demirci, Akgonul, & Akpinar, 2015;Lapierre, Zhao, & Custer, 2019;Liu et al., 2019;Park, Yang, Shin, Jang, & Park, 2019). Another study found no association (Casiano, Kinley, Katz, Chartier, & Sareen, 2012), whereas a systematic review by Elhai et al. (Elhai, Dvorak, Levine, & Hall, 2017) reported a significant association between problematic or general smartphone use and the severity of depression among different adolescents and adults. ...
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Background and aim Problematic mobile phone use (PMPU) is prevalent and increases the risk for a variety of health problems. However, few studies have explored the neural mechanisms that might render adolescents more or less vulnerable. Here, we aimed to identify whether PMPU is associated with depressive symptoms and whether this relationship is moderated by intrinsic functional connectivity (iFC) which is associated with PMPU. Methods In this longitudinal study, we included 238 students (mean age = 19.05, SD = 0.81) that came from a university in Hefei, China. They all finished MRI scans at baseline and completed questionnaires both at baseline and 1 year later. A self-rating questionnaire for adolescent problematic mobile phone use and depression anxiety stress scale-21 were used to assess PMPU and depressive symptoms. We first assessed the relationship between PMPU and depressive symptoms using an autoregressive cross-lagged model. Then, we detected the brain regions that were associated with PMPU. Moreover, the neuroimaging results were extracted to explore whether the iFC of these brain regions moderated the relationship between PMPU and depression. Results Consistent with our hypotheses, PMPU was positively associated with depressive symptoms, and the relationship between PMPU and depressive symptoms was moderated by iFC of the left parahippocampal gyrus-right middle temporal gyrus both at baseline and after 1 year ( β = 0.554, P = 0.003; β = 0.463, P = 0.016, respectively). Conclusions These results advance the understanding of PMPU and suggest that iFC of the left parahippocampal gyrus-right middle temporal gyrus may be a neurobiological contributor to its relationship with depressive symptoms.
... Recent research shows that PSU severity was moderately correlated with anxiety and depression severity [26,66,67] and that this association could extend to adults of all ages [68]. PSU and depression interrelationships found in prospective cohort studies are likely to be signi cantly bi-directional [69,70]. On the one hand, PSU is associated with a lack of social support, which can induce emotional disorders such as anxiety and depression [71]. ...
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Background: This study aimed to categorize different subgroups of problematic smartphone use among Chinese college students. Differences in gender and psychosocial characteristics of the categorized groups were also examined. Methods: A total of 1,123 participants completed the Mobile Phone Addiction Index Scale (MPAI), the Center for Epidemiologic Studies Depression Scale (CES-D), the Perceived Social Support Scale, and the Perceived Stress Scale. Using latent profile analysis (LPA), we identified different subgroups of problematic smartphone use among college students. Multivariate logistic regression analysis was implemented to examine the relationship between latent classes and demographic, psychosocial covariates. Results: Four latent classes were identified: a low-risk group, a moderate-risk with no evasiveness group, a moderate-risk with evasiveness group, and high-risk group that accounted for 11.0%, 24.1%, 35.5%, and 29.4% of the total sample, respectively. Further analysis revealed that compared with the “low-risk” class, the other three classes differed significantly with respect to gender and prevalence of depression. Conclusions: Classifying college students based on features of problematic smartphone use is potentially useful for understanding risk factors and developing targeted prevention and intervention programs.
... Screen time may interrupt sleep, but individuals who struggle with falling asleep may simply spend more time on screen-based activities than their sleeping counterparts. There may also be a reciprocal relationship; people who are unable to fall asleep at night may engage in screen-based activities, further disrupting sleep (46). We have employed an overall screen-time measure, and have not investigated possible differences across different types of technology and activities. ...
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The aim of this study was to assess the relationship between daily screen time and sleep, evening screen time and sleep, and between social media addiction and sleep in a student population. This cross-sectional study is based on data from a national survey of all college and university students in Norway (the SHoT2018 study; n = 49,051). The sleep outcomes were sleep duration, sleep onset latency, sleep efficiency, and insomnia operationalized according to formal DSM-5 criteria. The results show a strong negative association between time spent on screen-based devices and sleep quality and quantity, and where screen use in bed had more consistent negative associations with sleep. Furthermore, there were higher rates of insomnia among those with higher levels of addiction, and curvilinear relationships with sleep duration, sleep onset latency, and sleep efficiency. Those with higher levels of addiction also had more evening screen time. The findings suggest that screen use plays an important role in students' sleep quantity and quality, where evening screen time has a stronger relationship with sleep compared to total daily screen time. The results also suggest a role of social media addiction, and addictive social media use may be a target for intervention in order to reduce evening screen time.
... There were also links reported between PSU and psychological distress (38,39), where Sangmin Jun et al. found that the relationship between mobile phone addiction and depressive symptoms may present a vicious circle using a longitudinal data (38). Moreover, smartphone addiction was found to mediate the relationship between negative affect and sleep quality among Chinese university students (23). ...
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Background: Sleep problems and eating disorders (EDs) are both serious public health concerns often seen in young adults. Yet, the underlying mechanisms for such associations are largely unknown. This study aims to examine potential serial multiple mediation effects of problematic smartphone use (PSU) and psychological distress (i.e., depressive and anxiety symptoms) in the relationship between sleep quality and disordered eating behaviors/attitudes (DEBs). Methods: A total of 4,325 students from two Tibet universities in China (2,657 females and 1,668 males) completed an online survey that included the following measurements: Eating Attitude Test-26 for disordered eating behaviors/attitudes, the Chinese Version of Pittsburgh Sleep Quality Index (CPSQI), Smartphone Addiction Scale—Short Version (SAS-SV) for problematic smartphone use, Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) for psychological distress. Results: While the direct path linking sleep quality and DEBs was not found to be significant (Standardized β = 0.006, 95% CI = −0.0667~0.0970), both PSU (Standardized β = 0.016, 95% CI = 0.0256~0.0591) and anxiety symptoms (Standardized β = 0.014, 95% CI = 0.0203~0.0526) may mediate a link between sleep quality and DEBs; serial multiple mediation analysis revealed that a serial indirect pathway of “sleep quality -> PSU -> anxiety symptoms -> DEBs” existed(Standardized β = 0.001, 95% CI = 0.0002~0.0012). Similarly, while the direct path linking sleep quality and DEBs was not found to be significant (Standardized β = 0.006, 95% CI = −0.0667~0.0970), both PSU (Standardized β = 0.020, 95% CI = 0.0337~0.0692) and depressive symptoms (Standardized β = 0.015, 95% CI = 0.0139~0.0652) may mediate a link between sleep quality and DEBs; serial multiple mediation analysis revealed that a serial indirect pathway of “sleep quality -> PSU -> depressive symptoms -> DEBs” existed (Standardized β = 0.001, 95% CI = 0.0006~0.0038). Conclusions: Psychological and behavioral factors may comprehensively work together, leading to flow-on effects from sleep problems to disordered eating behaviors among university students. Appropriate interventions that target problematic smartphone use could thus potentially reduce anxiety and depression levels, which in turn will provide a buffer against the negative impact of poor sleep quality on eating disorder symptoms.
... Women who used mobile phone within an hour before sleep were five times at higher risk of poor sleep quality and nine times at higher risk for inadequate duration of sleep. Various studies have been done on the effect of mobile phone and the quality of sleep among various age-group populations which showed that long term use of mobile phone and TV will have an adverse effect on the duration of sleep and the sleep quality; [25][26][27] however, this phenomenon has yet to be studied among pregnant women, and therefore, this finding provides a further direction of research into mobile phone usage and maternal health outcomes. ...
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Introduction: Sleep is a basic essential, and sleep disturbances are common during pregnancy, which is linked to poor maternal and fetal outcomes. Materials and methods: A cross-sectional study was conducted among antenatal women attending a rural maternity hospital in Ramnagara District, Karnataka using consecutive sampling. A predesigned, face-validated structured questionnaire and Pittsburgh Sleep Quality Index (PSQI) were administered. Mean PSQI score of !5 was considered as poor sleep quality. Results: Of the 200 pregnant women in the study, 54.5% had poor sleep quality and 76.5% had inadequate duration of sleep (<8!hours a day). The factors found to be signi"cantly associated with poor quality sleep in this study were increased maternal age, joint family, lower socioeconomic status, increased parity, increasing gestational age, presence of complications in the current pregnancy, previous bad obstetric history, exposure to passive smoking, not sleeping on a bed and mattress, use of mobile phone and TV at bedtime, lack of physical activity, and lack of afternoon naps. Women who used mobile phones at bedtime had nine times higher risk of inadequate sleep and "ve times higher risk of poor sleep quality. Women who did not sleep on a bed with mattress had 10 times higher risk and those exposed to passive smoking had four times greater risk of poor sleep quality. Conclusion: The quality and the duration of sleep among pregnant women were inadequate. There is a need to educate women about the importance of quality sleep during pregnancy and it should be assessed during routine antenatal care.
... This likely leads to an underestimation of the effects (dilution of the effects) of radiation exposure in INTERPHONE and COSMOS studies. A relatively in small size, prospective cohort study on 3,396 adult students from China has examined the effects of using mobile phone, for over 4 h per day, on sleep parameters [39]. Conclusion of the study was that use of mobile phone for over 4 h per day caused sleep disturbance and that lessening the use of the mobile phone ameliorated the sleep problem. ...
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Part of the population considers themselves as sensitive to the man-made electromagnetic radiation (EMF) emitted by powerlines, electric wiring, electric home appliance and the wireless communication devices and networks. Sensitivity is characterized by a broad variety of non-specific symptoms that the sensitive people claim to experience when exposed to EMF. While the experienced symptoms are currently considered as a real life impairment, the factor causing these symptoms remains unclear. So far, scientists were unable to find causality link between symptoms experienced by sensitive persons and the exposures to EMF. However, as presented in this review, the executed to-date scientific studies, examining sensitivity to EMF, are of poor quality to find the link between EMF exposures and sensitivity symptoms of some people. It is logical to consider that the sensitivity to EMF exists but the scientific methodology used to find it is of insufficient quality. It is time to drop out psychology driven provocation studies that ask about feelings-based non-specific symptoms experienced by volunteers under EMF exposure. Such research approach produces only subjective and therefore highly unreliable data that is insufficient to prove, or to disprove, causality link between EHS and EMF. There is a need for a new direction in studying sensitivity to EMF. The basis for it is the notion of a commonly known phenomenon of individual sensitivity, where individuals' responses to EMF depend on the genetic and epigenetic properties of the individual. It is proposed here that new studies, combining provocation approach, where volunteers are exposed to EMF, and high-throughput technologies of transcriptomics and proteomics are used to generate objective data, detecting molecular level biochemical responses of human body to EMF.
... can be partially explained by the puberty-related hormonal mechanisms among females, which gets compounded with excessive popularity and use of the internet among females [15,16]. Internet addiction was reported as a contributing factor in impairing the circadian rhythm [17]. ...
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This commentary is aimed to discuss the impact of social media or the internet and engagement on youth development and comprehend these complex interrelationships. The discussion will serve as an important basis for designing targeted interventions to promote the judicious use of social media and meaningful engagement among youth. Problematic social media use (SMU) among adolescents may be associated with sleep deprivation, emotional distress, and adoption of maladaptive behaviors. Depression and stress are most notably connected to online harassment from SMU or cyberbullying. Degradation, threats, fake profiles, cyberstalking and unwanted comments are some examples of cyberbullying. Given the critical developmental stage of adolescents, online social rejection triggers a response with higher emotional intensity. The growing use of social media (SM) among youth warrants further investigation to identify its impact on mental health. The influence of SM or the internet on the emotional and social development of adolescents is undergoing a continuous transformation. While digital platforms help to promote social inclusion among adolescents, the risk associated with their excessive or problematic use cannot be overlooked. Understanding relationships between social media use, psychological health, and sleep deprivation among adolescents is essential in deciphering the intricate mechanisms or factors surrounding the youth development cycle.
... Regarding the temporal relationships, stress/affective distress and the aforementioned behavior have all been reported to persist over time (eg, ≥3 mo [37][38][39][40], whereas objective sleep parameters can change over weeks to months 41 or remain stable for ≥3 months. 42 Thus, in a trade-off to best capture the expected persistence of behavior and permit sufficient time to elapse to observe a significant change in sleep, we selected the 2 assessment points (T1 and T2) to be 3 months apart; and we used the T1 predictors as predictors of the sleep parameters at T2. ...
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Background: Several behaviors have been reported to interfere with sleep in otherwise healthy adults, including low physical activity (PA) levels. However, few studies have compared low PA with the other behavioral risk factors of objective sleep impairment, despite the behavior tending to cooccur in highly stressed and affectively distressed individuals. Thus, the authors compared objective and subjective measures of PA and other potential sleep disrupting behaviors as predictors of objective sleep (sleep onset latency, actual sleep time, total sleep duration, awake time, and sleep efficacy) at baseline (T1) and 3 months later (T2). Methods: A community-derived sample of 161 people aged 18-65 years were asked about PA, other behavior (ie, night eating, electronic device use, watching television, caffeine and alcohol use), stress, affective distress (ie, anxiety, depression), and demographics including shift work and parenting young children in an online questionnaire at T1 and T2. PA and sleep were also monitored for 24 hours each at T1 and T2 using actigraphy. Results: Multiple regression analyses indicated that sleep at T1 was associated with PA (ie, total number of steps, metabolic equivalents/time, time spent travelling) after controlling mean ambient temperature and relevant demographics. At T2, longer sleep onset latency was predicted by parenting young children and night time television viewing; shorter sleep duration was predicted by female gender; and awake time and sleep efficacy were predicted by alcohol intake after controlling T1 sleep measures, demographics, and mean ambient temperature. Conclusion: The risk factors for objective sleep impairment included parenting young children and watching television at night, whereas better sleep outcomes were associated with greater engagement with PA.
... Furthermore, there was an association between excessive screen time and problems in sleep onset (66), insufficient sleep (67), and insomnia (68). Longterm problematic mobile use predicted new incidences of sleep disturbances and mental distress, which was ameliorated by its discontinuation (69). Excessive mobile phone use correlated with disturbed sleep pattern and quality (70) Excessive smartphone use was associated with poorer sleep quality and higher perceived stress (71,72), lowered physical activity, lower muscle mass and higher fat mass (73). ...
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Background and Aims: This present paper will review the existing evidence on the effects of excessive smartphone use on physical and mental health. Results: Comorbidity with depression, anxiety, OCD, ADHD and alcohol use disorder. Excessive smartphone use is associated with difficulties in cognitive-emotion regulation, impulsivity, impaired cognitive function, addiction to social networking, shyness and low self-esteem. Medical problems include sleep problems, reduced physical fitness, unhealthy eating habits, pain and migraines, reduced cognitive control and changes in the brain's gray matter volume. In Conclusion: Excessive smartphone use is associated with psychiatric, cognitive, emotional, medical and brain changes that should be considered by health and education professionals.
... Some previous studies have discovered the association between worry and depression, which is consistent with our finding (29,30). In regards to the relationship between time spent on pandemic information and acute stress symptoms, the association has not been reported yet, despite a previous study reveals bidirectional associations between the duration of mobile phone use and various sleep and mental outcomes such as depression and anxiety (31). Several mechanisms may explain the association. ...
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The prevalence and related factors of mental health impact among medical staffs who experienced the second wave of the COVID-19 pandemic in China is unknown. Therefore, this survey was conducted to investigate the prevalence and related factors of depressive, anxiety, acute stress, and insomnia symptoms in medical staffs in Kashi, Xinjiang, China during the second wave of the COVID-19 pandemic. A cross-sectional online survey was conducted among medical staffs working in First People's Hospital of Kashi, Xinjiang. The questionnaire collected demographic data and self-design questions related to the COVID-19 pandemic. The Impact of Events Scale-6, the Insomnia Severity Index, the Patient Health Questionnaire-9, the Generalized Anxiety Disorder Scale-7, the Perceived Social Support Scale, the Chinese Big Five Personality Inventory-15, and the Trait Coping Style Questionnaire were used to measure psychological symptoms or characteristics. Binary logistic regression was carried out to examine the associations between socio-demographic factors and symptoms of depression, anxiety, stress, and insomnia. In total, data from 123 participants were finally included, among which the prevalence rate of depressive, anxiety, acute stress, and insomnia symptoms is 60.2, 49.6, 43.1, and 41.1%, respectively. The regression model revealed that minority ethnicity, being worried about infection, spending more time on following pandemic information, and neurotic personality were positively associated with the mental health symptoms, while extraversion personality, higher education level, and better social support were negatively associated. In our study, the prevalence of mental health impact was high among medical staffs in Kashi, China who experienced the second wave of the COVID-19 pandemic. Several factors were found to be associated with mental health conditions. These findings could help identify medical staffs at risk for mental health problems and be helpful for making precise mental health intervention policies during the resurgence. Our study may pave way for more research into Xinjiang during the COVID-19 pandemic.
... Additionally, some negative feeling, expressed by individuals on social media causes public anxiety because of the nature of emotional contagion [36]. What is more, spending too much time consuming COVID-19 information, especially before bedtime, may deprive sleep time and affect sleep quality [37]. Taken together, time spent hearing about COVID-19 outbreak was relevant to sleep quality. ...
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Objective Rapidly increasing numbers of confirmed cases and deaths during the 2019 coronavirus disease outbreak (COVID-19) resulted in widespread psychological problems in the Chinese population. The purpose of this study was to investigate the sleep quality and changes in sleep patterns before and during the outbreak in the general population in China and to determine factors related to sleep quality. Methods This cross-sectional study was conducted using an online questionnaire from 20 February to 29 February 2020 in China. Socio-demographic data, self-designed COVID-19-related characteristics, sleep patterns, and Pittsburgh Sleep Quality Index (PSQI) scores were obtained. Single factor analysis and multivariate binary logistic regression analysis were used. Results A total of 1,897 individuals were included in our study, and 30.0% of participants reported suffering poor sleep quality (PSQI≥8). Logistic regression analysis found that the factors related to sleep quality included poor physical health (OR=3.382, p<0.001), respiratory disease (OR=1.629, p=0.008), other diseases (OR=2.504, p=0.012), suspected case of COVID-19 in the same community (OR=1.928, p=0.002), confirmed case of COVID-19 in the same community (OR=2.183, p=0.007), worry about being infected (OR=2.336, p<0.001), ≥1 hour/day spent hearing COVID-19 information (OR=1.960, p<0.001), time difference in midpoint time in bed (OR=1.230, p<0.001), and time difference in time in bed (OR=0.711, p<0.001). Conclusions Our study revealed that more than one-fourth of the participants suffered poor sleep quality during the COVID-19 outbreak. In addition to the poor health status and COVID-19-related anxiety, delayed sleep phase and reduced time in bed impacted sleep quality in the general population in China.
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Experiencing peer phubbing is likely to affect adolescents’ quality of life negatively. The current study adopted structural equation modeling to explore the relationship between peer phubbing, individual mental health (i.e., psychological distress), behavior problems (i.e., problematic smartphone use), and physical functioning (i.e., daytime sleepiness and subjective sleep quality). The total sample contained 742 children and adolescents (395 females; Mean age = 15.39, SD = 1.66, range = 12–19). The results indicated that peer phubbing, psychological distress, and problematic smartphone use were positively related to daytime sleepiness but negatively correlated with subjective sleep quality. When age and gender were controlled, the link between peer phubbing and daytime sleepiness/subjective sleep quality was mediated sequentially by psychological distress and problematic smartphone use and sequentially by problematic smartphone use and psychological distress. The direct effect of peer phubbing was significant on daytime sleepiness but not subjective sleep quality. These findings suggested that peer phubbing could cause psychological distress to children and adolescents, increase their problematic smartphone use and daytime sleepiness, and decrease their subjective sleep quality. Interventions for children and adolescents with daytime sleepiness or poor subjective sleep quality should pay attention to their problematic smartphone use and the phubbing from their peers.
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Adolescents and young adults have progressively become smartphone and internet-dependent. Its addiction is affecting them mentally and physically. Due to its overutilization, it is causing a detrimental effect on them. These dilemmas need to be acknowledged. Furthermore, the goal is to reduce overutilization and overreliance, and the task is to reduce the heavy toll on their mental and psychological condition. We need to review the evidence linking smartphone and social media use with psychological morbidities among adolescents and young adults. The aim of this study is to summarize the present situation and the correlation between smartphones and mental health. Cognitive, emotional difficulties, poor cognitive function, impulsivity, shyness, social networking addiction, low self-esteem, and some medical issues like insomnia, anxiety, depression, and a lack of cognitive control have been linked to excessive smartphone use.
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Background Recent years have seen an increased incidence of social anxiety due to increasing intensive use of social media, especially among young adults. Objective The present study aimed to translate the original English version of Social Anxiety Scale for Social Media User (SAS-SMU) into Chinese, examine its applicability among Chinese College students via reliability and validity indexes, and investigate the influencing factors contributing to SAS-SMU. Methods A cross-sectional study was conducted among a cohort of 1307 Chinese college students, 486 males and 821 females, aged 20.75 ± 3.13 years old. The original version of SAS-SMU was translated into Chinese using the backward and forward translation procedure. An exploratory factor analysis (EFA) and a confirmatory factor (CFA) analysis were used for construction of underlying factor structure. Criterion-related validity was assessed using Interaction anxiousness scale (IAS) and the “extraversion” domain of Eysenck Personality Short Scale (EPQ-R-S). Cronbach's alpha coefficient was computed for evaluation of internal consistency. A multivariate stepwise linear regression analysis was conducted for determining the potential correlates of SMU-related social anxiety. Results The final Chinese version of SAS-SMU had 21 items. Item analysis, exploratory factor, EFA, and CFA jointly supported a three-factor structure of the translated version, defined as social recognition anxiety, interaction anxiety, and privacy concern anxiety, respectively. The three-factor structure of this scale showed configural, metric, scalar measurement invariance across gender. Cronbach's alpha coefficient of the scale and its three subscales were 0.96, 0.93, 0.94, and 0.91, respectively. The mean SAS-SMU overall score for each college student was 51.63 ± 16.32, with 21.64 ± 7.24 (recognition anxiety), 17.10 ± 6.30 (interaction anxiety), 12.90 ± 4.61 (privacy concern anxiety) for each subscale, respectively. IAS score, mobile phone addiction index (MPAI) score, EPQ-E score, time spent on social media per week, relationship with parents, childhood life status, whether being an only child, and cyber bullying experience can explain 51.1% of the variance of SMU related social anxiety. Conclusion Based on the data, the Chinese version of SAS-SMU has shown to be satisfactory in psychometric properties. Subjects prone to interaction anxiousness, addictive smartphone use, extraversion personality trait, bad relationship with parents, unfortunate childhood life, only-child status, and having cyberbullying experience tend to have a higher level of SMU related social anxiety.
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Mobile phone addiction (MPA) is a widespread problem in China, and college students face an especially high risk of its associated consequences. This study aimed to examine the interactions between level of mobile phone addiction and duration of mobile phone use and their impacts on psychological health, physical health, and sleep status of Chi-nese college students. Our study was a cross-sectional questionnaire-based survey which applied stratified random sampling method to recruit 946 participants. The level of mobile phone addiction was measured by Mobile Phone Addiction Index Scale. Sleep status was assessed by Pittsburg Sleep Quality Index. Designed questions were asked to evaluate the psychological and physical health status of the previous month of participants. The prevalence of MPA among Chinese undergraduates was estimated to be 36.6%. Severe MPA was significantly associated with psychological problems (anxiety symptoms, depressive symptoms, loneliness, social anxiety, impaired concentration, and sad or hopeless), physical problems (palpitation, nausea, and asphyxia), and sleep problems (sleep quality, sleep latency, sleep disturbances, sleep duration, and sleep dysfunctions). Interaction analysis indicated that college students with severe MPA who used their phones for more than 4 hours everyday were more likely to develop above problems. The findings reveal that relieving the MPA and controlling duration of phone use can ameliorate the psychological, physical, and sleep-related issues. Keywords Mobile phone addiction · Health risk · Physical state · Psychological state · Sleep state Smartphones are advanced electronic media devices which are capable of processing more information than other phones. Smartphones include many features such as games, videos,
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The adoption to digital media by individuals has increased multifold during the Covid 19 pandemic. The increased digital screen time may affect the sleep quality of the individuals which would lead to other health issues. India has imposed lockdown owing to the second wave of the pandemic and individuals of different demographic classes have been exposed to increased digital screen time. While several global studies have examined the health problems caused due to increased screen time, there is minimal evidence of its effect on all demographic groups in the Indian context. Hence this study aims to investigate the relation between digital screen usage and insomnia during Covid 19 pandemic among all demographic groups of individuals. Structured questionnaire was employed to capture the demographic characteristics, screen time during weekdays and weekends and Insomnia levels. The survey responses from 253 participants were analyzed using ANOVA tests. Younger adults were found to have more screen time during weekdays and weekends. The findings also revealed that there was association of the higher screen time exposure during weekdays and weekends and insomnia levels of the individuals.
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Purpose: NOMOPHOBIA (NO MObile PHone PhoBIA) or problematic smartphone use is a psychological disorder in which people are afraid of being cut off from their mobile phones. Currently, there has been no direct assessment of mobile phone screen size in the home setting and its effect on nomophobia and related symptoms, such as insomnia. Thus, we investigated the association between nomophobia, insomnia, and mobile phone screen size in a young adult population in Bahrain. Patients and methods: Using a descriptive, cross-sectional design, we surveyed participants aged 18 to 35 between August and September 2020 using an online questionnaire. Participants completed demographic questions and questions about personal mobile phones, the Nomophobia Questionnaire (NMP-Q), and the Insomnia Severity Index (ISI). The mobile phone screen size was determined using an open-source online database. Crude and adjusted regression analyses were fitted to examine the associations between the study variables. Results: A total of 549 individuals, 54% females, were included in the final analyses. One hundred and fourteen participants (21%) had severe nomophobia, and 81 (14%) had clinical insomnia. A strong positive pair-wise linear association was observed between NMP-Q and ISI β 0.15, P = 0.001. Age, sex, BMI, and mobile phone screen size showed no association with the NMP-Q. Conclusion: Nomophobia is very prevalent in young adult men and women, and it is closely associated with insomnia, regardless of mobile phone screen size, suggesting that mobile phone screen size should not be used as a proxy for hazardous usage.
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The COVID-19 pandemic has had impact on life on a global scale, however, one of the most affected aspects are the teaching and learning practices. Advances in technology have made distance learning a good alternative option for on-site learning, as students can both interact with one another and with the tutor, use audio, video, text to learn, as well as use the internet for research purposes. However, this mode of education will extend throughout 2020 and early 2021, which could have negative implications on the health and body functions of university students. This review aims to shed light on the negative consequences of the prolonged technology-based, remote online learning on the students' wellbeing. Therefore, in this review we will discuss some of the physiological functions and body systems which could be affected during the COVID-19 pandemic in an attempt to suggest preventive measures in advance for safe technology-based learning.
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The coronavirus disease 2019 (COVID-19) pandemic has imposed both physical and psychological burdens on healthcare workers (HCWs). What is more, few studies have focused on the gender differences in mental health problems (MHPs) among HCWs during such an outbreak. Thus, the current study investigated the prevalence and gender differences of various MHPs among HCWs in China during the COVID-19 outbreak. This nationwide survey was conducted online from January 29 to February 3, 2020. General information was collected by questions about socio-demographics, work-related factors, and living situations. Depressive, anxiety, stress, and insomnia symptoms were assessed by the Patient Health Questionnaire-9, the Generalized Anxiety Disorder-7, the Impact of Event Scale-Revised, and the Insomnia Severity Index, respectively. Among the 2,198 contacted HCWs, 1,563 (71.1%) responded with valid data, of whom 1,293 (82.7%) were females. The prevalences of depressive, anxiety, stress, and insomnia symptoms in participants were 50.7%, 44.7%, 52.5%, and 36.1%, respectively. Female HCWs had significantly higher scores in all four scales (p <0.001) and higher prevalences in all MHPs involved (range, odds ratio [OR] 1.55–1.97). After adjusting for potential confounders, female HCWs still had higher risks for all MHPs involved than males (range, adjusted OR 1.36–1.96). HCWs present high prevalences of depressive, anxiety, stress, and insomnia symptoms during the COVID-19 outbreak. Furthermore, female HCWs are more vulnerable to all MHPs involved. These findings highlight the need for timely, special care and support for HCWs during the outbreak, especially for females.
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Background Identifying factors associated with recommended physical activity (PA) levels are critical in efforts to combat the obesity epidemic and related comorbidities. Methods We conducted cross-sectional analyses of college students (n = 490) enrolled in a large southern state university in October of 2014. Our aim was to identify sociodemographic characteristics, technology use, and sleep patterns among college students and their independent relationship to recommended PA. An online survey was sent to all enrolled students. Logistic regression predicted achieving recommended ≥150 min per week of moderate-vigorous PA (MVPA) versus not (≤149 min MVPA). Results Approximately 69% of study participants were males, 18% were Hispanic, and more than half (60%) were within the normal body mass index (12% were obese). The average age of students was 21 years. On a daily average, individuals used smartphones most often (nearly 4.4 h), followed by laptops at 4.0 h, desktops at 1.2 h, and tablets at 0.6 h. The mean number of hours individuals reported sleeping was 6.7. Sociodemographic factors associated with reporting ≥150 min of MVPA included being male (OR = 4.0, 95% CI 2.2–7.1) versus female, being non-Hispanic White (OR = 1.8, CI 1.1–3.2) versus being a member of minority race group. Behavioral factors associated with reporting ≥150 min of MVPA included technology use (being moderate-heavy (OR = 2.3, CI 1.1–4.8) or heavy (OR = 3.4, CI 1.6–7.5) users of technology), and receiving low-moderate (OR = 1.9, 1.01–3.7) levels of sleep versus the lowest level of sleep. Conclusions In the current study, minority status and being female were the strongest sociodemographic factors associated with inadequate PA levels, while high technology use (primarily driven by smartphone use) were associated with recommended PA levels. Identifying factors associated with being physically active will allow for targeted interventions to improve the health of young adults.
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Background Short sleep duration and poor sleep quality have been demonstrated to be associated with childhood obesity. It has been suggested that electronic entertainment and communication devices (EECDs) including TVs, computers, tablets, video games and cell phones interfere with sleep in children and youth. The aim of this study was to assess the impact that the use of EECDs in the hour before bedtime has on sleep and weight status to inform sleep promotion interventions and programs to prevent childhood obesity. Methods A provincially representative sample of 2334 grade 5 children and their parents in Alberta, Canada was surveyed. Parents reported their child’s bedtime and wake-up time along with how often their child snored, felt sleepy during the day, woke-up at night and woke-up in the morning feeling unrefreshed. Sleep duration, sleep quality and sleep efficiency were derived from these indicators. Parents also reported on the presence of EECDs in their child’s bedroom, while children reported use of EECDs during the day and frequency of using each of these devices during the hour before sleep. The height and weight of children were measured. Multivariable mixed effect linear and logistic regression models were used to determine how sleep duration, sleep quality, sleep efficiency and weight status are influenced by (i) access to EECDs in children’s bedrooms, (ii) use of EECDs during the hour before sleep, and (iii) calming activities specifically reading during the hour before sleep. Results Sleep duration was shorter by −10.8 min (cell phone), −10.2 min (computer) and −7.8 min (TV) for those with bedroom access to and used these EECDs during the hour before sleep compared to no access and no use. Good sleep quality was hindered by bedroom access to and use of all EECDs investigated during the hour before sleep, particularly among users of cell phones (OR = 0.64, 95% CI: 0.58–0.71) and computers (OR = 0.72, 95% CI: 0.65–0.80). Very good sleep efficiency was decreased by access to and frequent use of a TV (54%), cell phone (52%), tablet (51%) and video games (51%). Odds of obesity were doubled by bedroom access to and use of a TV and computer during the hour before sleep. Children who rarely read a printed book in the bedroom during the hour before sleep had a shorter sleep duration and poorer sleep quality and sleep efficiency compared to their peers. Having access to an EECD in the bedroom was associated with increased obesity despite frequently reading during the hour before sleep. Conclusions Our findings suggest that sleep duration, sleep quality, sleep efficiency and weight status are better among children who do not have EECDs in the bedroom and frequently read a book during the hour before sleep as opposed to those who use EECDs during this hour. Education of limits against EECD use by parents may improve sleep outcomes. These findings will inform health promotion messages and may give rise to national recommendations regarding EECD use. Trial registration ClinicalTrials.gov NCT01914185. Registered 31 July 2013 Retrospectively registered.
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The aim of this study was to investigate the relationship between mobile phone use and insomnia and depression in adolescents. A cross-sectional study was conducted on 295 high school students aged 15–19 in Japan. Insomnia and depression were assessed using Athene Insomnia Scales (AIS) and the Center for Epidemiologic Studies Depression Scale (CES-D), respectively. Mobile phones were owned by 98.6% of students; 58.6% used mobile phones for over 2 h per day and 10.5% used them for over 5 h per day. Overall mobile phone use of over 5 h per day was associated with shorter sleep duration and insomnia (OR: 3.89 [95% CI: 1.21–12.49]), but not with depression. Mobile phone use of 2 h or more per day for social network services (OR: 3.63 [1.20–10.98]) and online chats (OR: 3.14 [1.42–6.95]), respectively, was associated with a higher risk of depression. Mobile phone overuse can be linked to unhealthy sleep habits and insomnia. Moreover, mobile phone overuse for social network services and online chats may contribute more to depression than the use for internet searching, playing games or viewing videos.
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Problematic mobile phone use (PMPU) is a risk factor for both adolescents’ sleep quality and mental health. It is important to examine the potential negative health effects of PMPU exposure. This study aims to evaluate PMPU and its association with mental health in Chinese college students. Furthermore, we investigated how sleep quality influences this association. In 2013, we collected data regarding participants’ PMPU, sleep quality, and mental health (psychopathological symptoms, anxiety, and depressive symptoms) by standardized questionnaires in 4747 college students. Multivariate logistic regression analysis was applied to assess independent effects and interactions of PMPU and sleep quality with mental health. PMPU and poor sleep quality were observed in 28.2% and 9.8% of participants, respectively. Adjusted logistic regression models suggested independent associations of PMPU and sleep quality with mental health (p < 0.001). Further regression analyses suggested a significant interaction between these measures (p < 0.001). The study highlights that poor sleep quality may play a more significant role in increasing the risk of mental health problems in students with PMPU than in those without PMPU.
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Objectives We examined the relationships between screen time (ST) and mental health problems and also increment of ST and progression of mental health problems in a college-based sample of Chinese youth. Methods We assessed 2521 Chinese college freshmen from October 2013 to December 2014. At baseline, the mean age of participants was 18.43 years (SD 0.96 years), and 1215 (48.2%) participants reported ST >2 h/day. We estimated multivariable-adjusted ORs by using logistic regression models for the risk of developing mental health problems (anxiety, depression and psychopathological symptoms) and/or progression of these problems, according to baseline ST exposure and changes in exposure at follow-up. Results At baseline, when ST >2 h/day was compared with ST ≤2 h/day, the OR was 1.38 (95% CI 1.15 to 1.65) for anxiety, 1.55 (95% CI 1.25 to 1.93) for depression and 1.49 (95% CI 1.22 to 1.83) for psychopathological symptoms. The results remained unchanged for depressive and psychopathological symptoms but not for anxiety, after additional adjustment for sex, age, residential background, body mass index, perceived family economy, sleep quality, smoking, alcohol intake, exercise after school and physical activity. When participants who had increased their ST exposure to >2 h/day were compared with those with no change and ST ≤2 h/day, the OR was 1.78 (95% CI 1.12 to 2.83) for anxiety, 1.92 (95% CI 1.23 to 2.83) for depression and 1.93 (95% CI 1.16 to 3.21) for psychopathological symptoms. These associations also remained after additional adjustment. Conclusions The overall effects are consistent yet small for ST/ST increment on mental health problems and its progression. Given the small effect size of the current results, it remains unclear the degree to which ST is a practically significant risk factor for mental health outcomes. Future studies of high quality are necessary to further examine this association and the direction of causality.
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Importance: Sleep is vital to children's biopsychosocial development. Inadequate sleep quantity and quality is a public health concern with an array of detrimental health outcomes. Portable mobile and media devices have become a ubiquitous part of children's lives and may affect their sleep duration and quality. Objective: To conduct a systematic review and meta-analysis to examine whether there is an association between portable screen-based media device (eg, cell phones and tablet devices) access or use in the sleep environment and sleep outcomes. Data sources: A search strategy consisting of gray literature and 24 Medical Subject Headings was developed in Ovid MEDLINE and adapted for other databases between January 1, 2011, and June 15, 2015. Searches of the published literature were conducted across 12 databases. No language restriction was applied. Study selection: The analysis included randomized clinical trials, cohort studies, and cross-sectional study designs. Inclusion criteria were studies of school-age children between 6 and 19 years. Exclusion criteria were studies of stationary exposures, such as televisions or desktop or personal computers, or studies investigating electromagnetic radiation. Data extraction and synthesis: Of 467 studies identified, 20 cross-sectional studies were assessed for methodological quality. Two reviewers independently extracted data. Main outcomes and measures: The primary outcomes were inadequate sleep quantity, poor sleep quality, and excessive daytime sleepiness, studied according to an a priori protocol. Results: Twenty studies were included, and their quality was assessed. The studies involved 125 198 children (mean [SD] age, 14.5 [2.2] years; 50.1% male). There was a strong and consistent association between bedtime media device use and inadequate sleep quantity (odds ratio [OR], 2.17; 95% CI, 1.42-3.32) (P < .001, I2 = 90%), poor sleep quality (OR, 1.46; 95% CI, 1.14-1.88) (P = .003, I2 = 76%), and excessive daytime sleepiness (OR, 2.72; 95% CI, 1.32-5.61) (P = .007, I2 = 50%). In addition, children who had access to (but did not use) media devices at night were more likely to have inadequate sleep quantity (OR, 1.79; 95% CI, 1.39-2.31) (P < .001, I2 = 64%), poor sleep quality (OR, 1.53; 95% CI, 1.11-2.10) (P = .009, I2 = 74%), and excessive daytime sleepiness (OR, 2.27; 95% CI, 1.54-3.35) (P < .001, I2 = 24%). Conclusions and relevance: To date, this study is the first systematic review and meta-analysis of the association of access to and the use of media devices with sleep outcomes. Bedtime access to and use of a media device were significantly associated with the following: inadequate sleep quantity, poor sleep quality, and excessive daytime sleepiness. An integrated approach among teachers, health care professionals, and parents is required to minimize device access at bedtime, and future research is needed to evaluate the influence of the devices on sleep hygiene and outcomes.
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Method: We conducted a systematic review of the relationship between problematic use with psychopathology. Using scholarly bibliographic databases, we screened 117 total citations, resulting in 23 peer-reviewer papers examining statistical relations between standardized measures of problematic smartphone use/use severity and the severity of psychopathology. Results: Most papers examined problematic use in relation to depression, anxiety, chronic stress and/or low self-esteem. Across this literature, without statistically adjusting for other relevant variables, depression severity was consistently related to problematic smartphone use, demonstrating at least medium effect sizes. Anxiety was also consistently related to problem use, but with small effect sizes. Stress was somewhat consistently related, with small to medium effects. Self-esteem was inconsistently related, with small to medium effects when found. Statistically adjusting for other relevant variables yielded similar but somewhat smaller effects. Limitations: We only included correlational studies in our systematic review, but address the few relevant experimental studies also. Conclusions: We discuss causal explanations for relationships between problem smartphone use and psychopathology.
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This study evaluated the mediating role of interpersonal problems in the link between mobile phone addiction levels and negative emotions among mobile phone addicts and possible-mobile phone addicts respectively. The purpose of this study was to address two gaps in research. First, previous research has revealed that a positive association existed between mobile phone addiction levels and negative emotions, especially among those with interpersonal problems. The present study extended research by exploring the mechanisms underlying these associations. Second, Mobile phone addicts as a particular group has received much attention, however, research concerning the possible mobile phone addicts as another particular group is limited. A total of 1089 young adults in China were surveyed by using cluster sampling. Results showed that compared with nonaddicts, mobile phone addicts or possible mobile phone addicts spent more money and time on mobile phone use and were more vulnerable to have negative emotions. The effects of the possible mobile phone addiction on negative emotions were significant but weaker than those of the mobile phone addiction. Further, interpersonal problem was a significant mediator between mobile phone addiction levels and negative emotions. Findings and their implications are discussed.
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Recent advances in the developmental epidemiology, neurobiology, and treatment of pediatric anxiety disorders have increased our understanding of these conditions and herald improved outcomes for affected children and adolescents. This article reviews the current epidemiology, longitudinal trajectory, and neurobiology of anxiety disorders in youth. Additionally, we summarize the current evidence for both psychotherapeutic and psychopharmacologic treatments of fear-based anxiety disorders (e.g., generalized, social, and separation anxiety disorders) in children and adolescents. Current data suggest that these disorders begin in childhood and adolescence, exhibit homotypic continuity, and increase the risk of secondary anxiety and mood disorders. Psychopharmacologic trials involving selective serotonin reuptake inhibitors (SSRIs) and selective serotonin norepinephrine reuptake inhibitors (SSNRIs) are effective in pediatric patients with anxiety disorders and have generally demonstrated moderate effect sizes. Additionally, current data support cognitive behavioral therapy (CBT) for the treatment of these conditions in youth and suggest that the combination of psychotherapy + an SSRI may be associated with greater improvement than would be expected with either treatment as monotherapy.
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To determine the longitudinal and cross-sectional associations between different types of electronic media use (mobile phones, TV, computers, video games, and music) and young adolescents' depressive symptoms, and to explore the potential for household media rules to reduce young people's depression. 126 young adolescents were recruited from the Northeastern USA. Each type of media use was assessed using survey questions, time use diaries, and ecological momentary assessment. The Beck Depression Index for Primary Care was administered at baseline and 1 year later as part of a questionnaire that also included items assessing the presence of household rules about TV and video games. Baseline use of mobile phones and TV viewing were associated with higher levels of depression 1 year later controlling for demographic information and baseline depression score. Having household rules about TV at baseline predicted lower levels of depression at follow-up. Both TV viewing and mobile phone use may contribute to the development of depressive symptoms. Implementing household rules about the duration and content of TV could help reduce depression in young adolescents.
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This statement describes the possible negative health effects of television viewing on children and adolescents, such as violent or aggressive behavior, substance use, sexual activity, obesity, poor body image, and decreased school performance. In addition to the television ratings system and the v-chip (electronic device to block programming), media education is an effective approach to mitigating these potential problems. The American Academy of Pediatrics offers a list of recommendations on this issue for pediatricians and for parents, the federal government, and the entertainment industry.
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There are limited data on the long-term outcome of childhood insomnia. We explored the longitudinal course, predictors, and impact of childhood insomnia in a community-based cohort. 5-year prospective follow-up. Community-based. 611 child