What complex factors influence sleep quality in college students? PLS-SEM vs. fsQCA
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PROVIDER: S-EPMC10485266 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:With the advancement of artificial intelligence (AI) and the Internet of Things (IoT), smart clothing, which has enormous growth potential, has developed to suit consumers' individualized demands in various areas. This paper aims to construct a model that integrates that technology acceptance model (TAM) and functionality-expressiveness-aesthetics (FEA) model to explore the key factors influencing consumers' smart clothing purchase intentions (PIs). Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the data, complemented by fuzzy-set qualitative comparative analysis (fsQCA). The PLS-SEM results identified that the characteristics of functionality (FUN), expressiveness (EXP), and aesthetics (AES) positively and significantly affect perceived ease of use (PEOU), and only EXP affects perceived usefulness (PU). PU and PEOU positively impact consumers' attitudes (ATTs). Subsequently, PU and consumers' ATTs positively influence PIs. fsQCA revealed the nonlinear and complex interaction effects of the factors influencing consumers' smart clothing purchase behaviors and uncovered five necessary and six sufficient conditions for consumers' PIs. This paper furthers theoretical understanding by integrating the FEA model into the TAM. Additionally, on a practical level, it provides significant insights into consumers' intentions to purchase smart clothing. These findings serve as valuable tools for corporations and designers in strategizing the design and promotion of smart clothing. The results validate theoretical conceptions about smart clothing PIs and provide useful insights and marketing suggestions for smart clothing implementation and development. Moreover, this study is the first to explain smart clothing PIs using symmetric (PLS-SEM) and asymmetric (fsQCA) methods.
| S-EPMC10508616 | biostudies-literature
Project description:Approximately 4 μg of DNA was isolated from blood of each of 16 subjects using the Qiagen DNEasy Blood and Tissue Kit. Of the 16 samples, 8 were from group 1 (CESD-H/TST-H; 5 female, 3 male) and 8 were from group 2 (CESD-H/TST-L; 5 female, 3 male). All DNA samples were confirmed to be of high purity (A260/280: 1.7-2.0). Pooled samples were prepared for each group by combining approximately 75 ng of DNA from each of the eight subjects. These two samples were submitted to the Yale Genomics Core for epigenome-wide methylation profiling using the Illumina Infinium HumanMethylation450 BeadChip, which measures the level of methylation β (a value ranging from 0 to 1, where 0 represents a completely unmethylated site and 1 a completely methylated site) at each of the 485,577 CpG sites on the array. Illumina’s GenomeStudio software was used to calculate the degree of differential methylation by group for each CpG site on the array, and FDR-adjusted p-values (Q-values) were calculated for each site in order to adjust for multiple comparisons. CESD=depression score; TST=sleep score
2016-08-01 | GSE80559 | GEO
Project description:Approximately 4 μg of DNA was isolated from blood of each of 16 subjects using the Qiagen DNEasy Blood and Tissue Kit. Of the 16 samples, 8 were from group 1 (CESD-H/TST-H; 5 female, 3 male) and 8 were from group 2 (CESD-H/TST-L; 5 female, 3 male). All DNA samples were confirmed to be of high purity (A260/280: 1.7-2.0). Pooled samples were prepared for each group by combining approximately 75 ng of DNA from each of the eight subjects. These two samples were submitted to the Yale Genomics Core for epigenome-wide methylation profiling using the Illumina Infinium HumanMethylation450 BeadChip, which measures the level of methylation β (a value ranging from 0 to 1, where 0 represents a completely unmethylated site and 1 a completely methylated site) at each of the 485,577 CpG sites on the array. Illuminaâs GenomeStudio software was used to calculate the degree of differential methylation by group for each CpG site on the array, and FDR-adjusted p-values (Q-values) were calculated for each site in order to adjust for multiple comparisons. CESD=depression score; TST=sleep score Blood-derived genomic DNA was isolated from 16 subjects; 8 each with high and low total sleep scores, respectively. DNA was pooled by group and genome-wide methylation profiling was performed.
2016-08-01 | E-GEOD-80559 | biostudies-arrayexpress
Project description:BackgroundNowadays, sleep-related problems are a prevalent occurrence among university students. Poor sleep quality is one of the most studied aspects of sleep complaints, affecting from 10% to 50% of this population. Poor sleep quality consequences are many and have a profound impact in the student's psychobiological health. University students live through a period of psychological challenge and adaptation, since the transition from high school to professional life. Abrupt autonomy challenges students to deal with many choices, from their academic and social life to their intimate habits. Frequently, sleep hygiene is neglected, or they are unable to use proper coping mechanisms, resulting in disturbing consequences that could impact their lives as adults. Research has found a significant association between sleep quality and depression or depressive symptoms, but this relationship is still somewhat difficult to interpret.ObjectiveThe objective of this review is to appraise the current knowledge around the relationship of sleep with depression in this group of young adults. Data Source: Articles included in Medline database.MethodsAfter a careful search, the articles selected aimed mainly college students. The studies had sleep quality and depression objectively assessed, focused in the relationship between both, and addressed possible influencing factors.ResultsThe current literature still supports a bidirectional relationship between sleep and depression, however, the importance of sleep quality is becoming a very relevant variable.ConclusionEducation and the application of policies regarding sleep hygiene may prevent, in some cases, the development of depression and improve the quality of sleep in other cases. Future research should clarify the relationship between sleep problems and depression in a way they could be prevented or, at least, minimalized with effective and achievable interventions.
| S-EPMC6361309 | biostudies-literature
Project description:BackgroundOver 40% of Taiwanese College students experience sleep problems that not only impair their quality of life but also contribute to psychosomatic disorders. Of all the factors affecting the sleep quality, internet surfing is among one of the most prevalent. Female college students are more vulnerable to internet-associated sleep disorders than their male counterparts. Therefore, this study aims to investigate (1) the relationship between internet addiction and sleep quality, and (2) whether significant variations in sleep quality exist among students with different degrees of internet use.MethodsThis structured questionnaire-based cross-sectional study enrolled students from a technical institute in southern Taiwan. The questionnaire collected information on the following three aspects: (1) demography, (2) sleep quality with Pittsburgh Sleep Quality Index (PSQI), and (3) severity of internet addiction using a 20-item Internet Addiction Test (IAT). Multiple regression analysis was performed to examine the correlation between PSQI and IAT scores among the participants. Logistic analysis was used to determine the significance of association between PSQI and IAT scores.ResultsIn total, 503 female students were recruited (mean age 17.05 ± 1.34). After controlling for age, body mass index, smoking and drinking habits, religion, and habitual use of smartphone before sleep, internet addiction was found to be significantly associated with subjective sleep quality, sleep latency, sleep duration, sleep disturbance, use of sleep medication, and daytime dysfunction. Worse quality of sleep as reflected by PSQI was noted in students with moderate and severe degrees of internet addiction compared to those with mild or no internet addiction. Logistic regression analysis of the association between scores on IAT and sleep quality, demonstrated significant correlations between quality of sleep and total IAT scores (odds ratio = 1.05:1.03 ∼ 1.06, p < 0.01).ConclusionThe results of this study demonstrated significant negative association between the degree of internet addiction and sleep quality, providing reference for educational institutes to minimize adverse effects associated with internet use and improve students' sleep quality.
| S-EPMC6582255 | biostudies-literature
Project description:Background:Chinese college students are at high risk of sleep problems, and smartphone use is common among this population. However, the relationship between smartphone use characteristics and sleep problems in Chinese college students has been inadequately studied. In this preliminary study, we examined the association of poor sleep quality with smartphone use in a sample of Chinese college students from a health vocational college in Changsha, China. Methods:A total of 439 college students completed a self-report questionnaire containing the Pittsburgh Sleep Quality Index (PSQI) and questions regarding demographic information, psychosocial factors, physical health, smartphone use characteristics, and mobile phone addiction (MPA). Results:The results showed that the prevalence of poor sleep quality (PSQI > 7) in Chinese college students was 9.8%. In multiple logistic regression analysis, poor sleep quality was significantly associated with male gender (OR: 2.80, P: 0.022), not having good physical health (OR: 2.61, P: 0.020), headache (OR: 2.47, P: 0.014), more severe depressive symptoms (OR: 2.17, P: 0.049), > four years of smartphone use (OR: 3.38, P: 0.001), > five hours of daily smartphone use (OR: 2.19, P: 0.049), and more severe inability to control MPA craving (OR: 2.04, P: 0.040). Conclusion:Our findings suggest that excessive smartphone use and MPA are associated with poor sleep quality in a sample of Chinese college students from a health vocational college. Because of the limited sample representativeness and cross-sectional design of this study, large-scale prospective representative studies are warranted to confirm these associations.
| S-EPMC7218048 | biostudies-literature
Project description:BACKGROUND:Sleep problems are widespread among college students around the globe, especially in China. This study was designed to investigate the prevalence of poor sleep quality and identify associated factors among college students in Jilin Province, China. METHODS:A total of 6284 participants were completely collected by stratified cluster sampling in 2016. Information on basic demographics, lifestyles, social and family support, and subjective sleep quality was collected by questionnaire. The Pittsburgh Sleep Quality Index (PSQI) is a self-administered questionnaire used to assess sleep for one month. RESULTS:1951 (31.0%) participants were classified into poor sleep quality group, as defined by a PSQI score > 5. Males scored significantly higher than females on sleep duration and use of sleep medication, while females scored significantly higher than males on PSQI total and sleep disturbances. The results of the multivariate logistic regression show the following factors to be significant predictors of poor sleep quality: freshman (OR = 1.523, 95% CI: 1.168-1.987), alcohol use (OR = 1.634, 1.425-1.874), gambling behaviors (OR = 1.167, 95% CI: 1.005-1.356), exercised for more than 30 min a week on less than one day (OR = 1.234, 95% CI: 1.016-1.498), the feelings of satisfied with parental love (OR = 1.849, 95% CI: 1.244-2.749), and harmonious/neutral relationship with classmates (OR = 2.206, 95% CI: 1.312-3.708; OR = 1.700, 95% CI: 1.414-2.045),. No study pressure of this academic year (OR = 0.210, 95% CI: 0.159-0.276), no truancy in the past month (OR = 0.510, 95% CI: 0.354-0.735), never had self-injurious behaviors (OR = 0.413, 95% CI: 0.245-0.698), very harmonious family relationship (OR = 0.377, 95% CI: 0.219-0.650), frequent communication with parents (OR = 0.524, 95% CI: 0.312-0.880), the feelings of satisfied with maternal love (OR = 0.432, 95% CI: 0.257-0.725), and frequent excursions to gymnasium (OR = 0.770, 95% CI: 0.659-0.899) were the protective factors. CONCLUSIONS:The implication of the present study may be that college students must be made aware of the consequences of inadequate sleep quality and risk factors could be improved if students tried to change their behavior and subjective consciousness.
| S-EPMC7329462 | biostudies-literature
Project description:Caffeinated beverages are a part of daily life. Caffeinated beverages such as coffee, tea, energy drinks, and soft drinks are easy to purchase and are frequently consumed by young college students. Moreover, smoking influences the consumption of caffeinated beverages. The concentration of caffeine in these products is an attractive factor for individuals that desire the effects of caffeine; however, abusing such products may lead to poor sleep quality. The motivations that drive caffeinated beverage consumption were investigated in this study through a survey. Self-reported questionnaires were distributed on campus to students enrolled at a university in Korea. The motivations of the students for consuming each caffeinated beverage and their sleep quality were investigated. The results of exploratory factor analysis showed the motivations for caffeinated beverage consumption were alertness, taste, mood, socialization, health benefits, and habit. The motivations for consuming each caffeinated beverage product were different. For instance, coffee consumption was motivated by a desire for alertness (B = .107, SE = .049, t = 2.181, p < 0.05) and by habit (B = .345, SE = .046, t = 7.428, p < 0.001), whereas tea consumption was influenced by socialization (B = .142, SE = .060, t = 2.357, p < 0.05). Energy drink consumption was motivated by a desire for alertness (B = .100, SE = .034, t = 2.966, p < 0.01) and health benefits (B = .120, SE = .051, t = 2.345, p < 0.05), while the consumption of soft drinks was not motivated by any specific factors. Caffeinated beverage consumption did not show a significant relationship with sleep quality, although the general sleep quality of the respondents was poor. Smoking status showed significant differences in coffee and tea consumption as well as sleep quality. Smokers had a higher intake of coffee and a lower intake of tea than non-smokers. No interaction effect between smoking and coffee on sleep quality was found. Labeling detailing the amount of caffeine in products is necessary and a cautionary statement informing consumers that smoking cigarettes enhances the effects of caffeine should be included.
| S-EPMC7231156 | biostudies-literature
Project description:Introduction:Social media (SM) usage has increased markedly among young adults. It is linked to poor sleep quality (PSQ), a risk factor for mental and physical health concerns. This study identified the determinants of PSQ in SM users among freshman college students. Material and Methods:A cross-sectional design was used and 842 students completed a self-administered questionnaire. Analyses were performed using the ? 2 test to examine differences in the characteristics of poor and good sleepers and logistic regression to estimate the risk of PSQ with reference to SM usage patterns. Results:Around 75.40% (n = 635) of the participants had PSQ. There was a significant difference in the PSQ rate between males (66.3%) and females (79.3%, p < 0.001), those who were physically active (67.2%) and those who were not (82.4%, p < 0.001), those who were mentally depressed (86.5%) and those who were not (61.5%, p < 0.001), and those with anxiety (87.8%) and those without (64.3%, p < 0.001). The risk of PSQ was lower among students who used SM for education (OR = 0.65, CI = 0.42 to 0.99, p = 0.048), had higher laptop usage (OR = 0.67, CI = 0.47 to 0.96, p = 0.03), and had higher SM usage during daytime (OR = 0.46, CI = 0.32 to 0.67, p < 0.001). The risk of PSQ was higher among those who reported SM usage at bedtime (OR = 1.69, CI = 1.01 to 2.81, p = 0.046). Discussion:Among SM users, PSQ was related to sociodemographic features, lifestyle characteristics, and health-risk factors. Further research is required to confirm these findings.
| S-EPMC7237109 | biostudies-literature
Project description:BackgroundThe prevalence of sleep quality problems and depression in the college student population has attracted widespread attention. However, the factors influencing this are still unclear. The objective of this study was to investigate the associations between self-compassion (S-C), sleep quality (SQ), and depression (DEP) among college students and examine the mediating effects of coping style (CS) between the variables.MethodsA total of 1,038 Chinese university students were recruited for the study. The study used the Self-Compassion Scale (SCS), Simplified Coping Style Questionnaire (SCSQ), Depression Anxiety Stress Scale 21 (DASS-21), and Pittsburgh Sleep Quality Index (PSQI) to conduct the survey.ResultsThe self-compassion and coping style showed significant negative correlations with sleep quality and depression. Coping style partially mediated the relationship between self-compassion and sleep quality. The coping style also fully mediated the relationship between self-compassion and depression.ConclusionThis study reveals the associations between self-compassion and sleep quality and depression, and the mediating role of coping style among college students. This study provides valuable insights for improving sleep quality and alleviating depression problems among college students. It emphasizes the importance of self-compassion and positive coping style.
| S-EPMC11190380 | biostudies-literature