1.Influence of sleep hygiene on sleep quality among adult residents
Ruichen FANG ; Shuangyan LI ; Yanmei LIN ; Xuxuan MA ; Leqin FANG ; Shixu DU ; Bin ZHANG
Sichuan Mental Health 2024;37(4):364-369
Background Individuals may experience significant alterations in sleep hygiene during the major public health emergencies,consequently impacting their sleep quality.Objective To explore the relationship between sleep quality and sleep hygiene among adult residents during the major public health emergencies,so as to provide references for improving the sleep quality of residents during such a period.Methods A sample of 1 364 adult residents were enrolled as the research subjects from February 20 to 29,2020.All participants were asked to complete self-administered questionnaire to obtain basic-demographic information and sleep hygiene.Pittsburgh Sleep Quality Index(PSQI)was applied to assess sleep quality.Residents were classified into poor sleepers with PSQI score≥8 and good sleepers defined as PSQI score<8.Binary Logistic regression analysis was conducted to identify factors associated with sleep quality.Radar chart was used to visualize and compare the sleep hygiene between poor sleepers and good sleepers.Results According to PSQI score,891(65.32%)residents were good sleepers,while 473(34.68%)residents were poor sleepers.Comparison revealed that age(χ2=3.887),past medical history(χ2=27.938),awareness rate of importance of sleeping before major public health emergencies(χ2=4.337),impact of sleep quality on quality of life during the major public health emergencies(χ2=178.138),frequency of staying up late during the major public health emergencies(χ2=139.390),compensatory sleep behaviors(χ2=39.257),impact of sleep problems on daytime functioning(χ2=285.879),change of bedtime(χ2=63.031),sleep latency(χ2=168.672),wake-up time(χ2=59.221),changes in sleep duration(χ2=172.332),time spent in the bedroom(χ2=23.071),and sum of money spent on improving sleep environment(χ2=58.584)yielded statistical difference between poor sleepers and good sleepers(P<0.05 or 0.01).Logistic regression analysis denoted that past medical history(OR=1.680,95%CI:1.185~2.382),negative impact of sleep quality on quality life(OR=4.181,95%CI:2.722~6.422),staying up late 3 to 4 times per week(OR=3.145,95%CI:1.497~6.605),staying up late almost every day(OR=4.271,95%CI:1.970~9.260),negative impact of sleep problems on daytime functioning(OR=7.169,95%CI:5.188~9.907),prolonged sleep latency(OR=2.836,95%CI:2.019~3.982)and shortened sleep duration(OR=3.518,95%CI:2.144~5.772)were risk factors of poor sleep quality.The sum of money spent on improving sleep environment following the major public health emergencies≤500 RMB(OR=0.334,95%CI:0.134~0.830)was related to the incidence rate of poor sleep quality.Radar chart showed that poor sleepers were characterized by extravagant concerns,excessive cleanliness and poor sleep hygiene practices during the major public health emergencies,and poor sleepers were more likely to stay up late due to stress and emotional issues.Conclusion Some residents are facing poor sleep quality during the major public health emergencies,and poor sleep hygiene practice also contributes to poor sleep quality.
2.Validity and reliability of the Chinese version of the Pre-sleep Arousal Scale in patients with brief insomnia disorder
Aike WU ; Yiqi PU ; Yuhan ZHAO ; Leqin FANG ; Lulu YANG ; Xue LUO ; Bin ZHANG
Chinese Mental Health Journal 2024;38(2):131-137
Objective:To test the validity and reliability of the Chinese version of the Pre-sleep Arousal Scale(PSAS)in patients with brief insomnia disorder(BID).Methods:Totally 170 patients with BID and 150 normal sleepers(NS)were recruited.All participants were assessed with the PSAS,Hospital Anxiety and Depression Scale(HADS)and Insomnia Severity Index(ISI).After 3 months,72 patients with BID were retested with the PSAS,HADS and ISI.Results:The PSAS scores of BID group were characteristic of a normal distribution.The PSAS total scores were positively correlated with the scores of HADS and ISI(r=0.55,0.40,Ps<0.01).Two factors of so-matic and cognitive arousal were extracted in PSAS by the exploratory factor analysis and parallel analysis,interval variance value was 55.84%,and the load scores of items were 0.46-0.89.The scores of PSAS and its subscales were higher in the BID group than in the NS group(Ps<0.001).The best cut-off score for the overall PSAS was found at 32/33 and had high sensitivity(0.72)and specificity(0.81).The Cronbach's α coefficient and the Spearman Brown split reliability were 0.91 and 0.76,respectively,the correlation coefficients between the items and total score ranged from 0.46 to 0.89(Ps<0.01),and the test-retest reliability was 0.37(P<0.01).Addi-tionally,rate of change of PSAS scores was positively correlated with the rate of change of HADS scores and ISI scores(Ps<0.05).Conclusion:The Chinese version of PSAS is a reliable and valid instrument to assess pre-sleep arousal in patients with brief insomnia disorder.
3.Association of mobile phone overuse with sleep disorder and unhealthy eating behaviors in college students of a medical university in Guangzhou.
Leqin FANG ; Xiaoheng XU ; Xiaomin LIN ; Yanlin CHEN ; Fuying ZHENG ; Yanrou BEI ; Lu ZHANG ; Bin ZHANG
Journal of Southern Medical University 2019;39(12):1500-1505
OBJECTIVE:
To investigate the association of mobile phone use with sleep disorder and unhealthy eating behavior among college students of a medical university in Guangzhou.
METHODS:
Mobile Phone Involvement Questionnaire (MPIQ), Pittsburgh Sleep Quality Index (PSQI) and the Three Factor Eating Questionnaire Revised 21 Item (TFEQ-R21) were used to survey 2122 undergraduates of the medical university. One-sample t test, One-way ANOVA and multiple linear regression analysis were used to analyze the data.
RESULTS:
Age, body mass index (BMI), phone use before sleep, phone use frequency, sleep quality (assessed by total PSQI score) and the dimension scores of TFEQ-R21 for uncontrolled eating, cognitive restraint, and emotional eating were all significantly correlated with the total score of MPIQ ( < 0.05). Phone use before sleep, high frequency of mobile phone use, poor sleep quality and emotional eating were associated with high MPIQ scores, while lower cognitive restraint and emotional eating tendency were correlated with lower scores of MPIQ. Bivariate analysis revealed that age (=0.088, < 0.001), BMI (=0.055, < 0.05), PSQI scores (=0.204, < 0.001), TFEQ-UE scores (=0.199, < 0.001), TFEQ-CR scores (=-0.076, < 0.001), TFEQ-EE scores (=0.170, < 0.001), phone use before sleep (=0.429, < 0.001), and phone use frequency (=0.316, < 0.001) were all significantly correlated with MPIQ scores; multiple linear regression analysis showed that model 4 incorporating the scores of TFEQ-UE, TFEQ-CR, and TFEQ-EE explained up to 21.8% of the main effect (adjusted R= 21.5%).
CONCLUSIONS
Mobile phone overuse is associated with poor sleep quality and unhealthy eating behaviors, and education and interventions for mobile phone use is essential among college students.
Cell Phone
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Feeding Behavior
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Humans
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Sleep Wake Disorders
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Students
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Universities
4.Validity and reliability of the Chinese version of Mobile Phone Involvement Questionnaire in college students.
Lianhong LIN ; Xiaoheng XU ; Leqin FANG ; Likai XIE ; Xiaomin LING ; Yanlin CHEN ; Fuying ZHENG ; Yanrou BEI ; Lu ZHANG ; Bin ZHANG
Journal of Southern Medical University 2020;40(5):746-751
OBJECTIVE:
To test the validity and reliability of the Chinese version of Mobile Phone Involvement Questionnaire (MPIQ) in college students.
METHODS:
We assessed the degree of phone dependence using the MPIQ among 2122 college students. One month later, 60 students were randomly selected for assessment with the MPIQ, and the ROC curve was generated to evaluate the true positive rate (sensitivity) and false positive rate at different cutoff values to determine the optimal cutoff score of the MPIQ.
RESULTS:
Among 98.9% of the participants who finished all the items, their MPIQ scores show a positive skew distribution and a one-factor structure. The load scores of the items ranged from 0.54 to 0.77. The Cronbach's α coefficient and the Spearman Brown split reliability were 0.84 and 0.83, respectively, the correlation coefficients between the items and total score ranged from 0.54 to 0.76, and the test-retest reliability was 0.48 ( < 0.001). At the optimal cut-off score of 32, the sensitivity and the specificity of the MPIQ were 0.634 and 0.652, respectively.
CONCLUSIONS
At the optimal cut-off score of 32, the MPIQ has good validity and reliability for assessing phone dependence among college students.
Cell Phone
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Humans
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Reproducibility of Results
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Students
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Surveys and Questionnaires