scholarly journals Predictors of Sleep Recall Bias in College Students

2020 ◽  
Author(s):  
Pranjal Srivastava ◽  
Mina Takegami ◽  
Ching-Hua Chen
Keyword(s):  
College Students ◽  
Sleep Quality ◽  
Quality Index ◽  
Pittsburgh Sleep Quality Index ◽  
Recall Bias ◽  
Self Assessment ◽  
Index Tests ◽  
Using Data ◽  
Sleep Amount

College students are known to have unhealthy levels of sleep. Using data from the StudentLife Dataset, we analyzed the predictors of “recall bias” regarding sleep. We compared the average of a running, daily, self-reported sleep value over a period of time to the average sleep amount perceived by the students in their PSQI (Pittsburgh Sleep Quality Index) tests. We found that the variability in the measure of self-assessment of health was related to errors in sleep recall, as were some individual parameters.

scholarly journals Sleep Habit/Sleepiness Questionnaires: A Useful Tool to Identify Correlation Between Sleep, Academic Performance and Obesity Promotion in Improving Health

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1170-1170
Author(s):  
Pratibha Gupta ◽  
Matt Collins
Keyword(s):  
College Students ◽  
Sleep Quality ◽  
Quality Index ◽  
Sleep Disturbances ◽  
Pittsburgh Sleep Quality Index ◽  
Lower Grade ◽  
Sleep Habits ◽  
Short Sleep Duration ◽  
Grade Point ◽  
Sleep Habit

Abstract Objectives Identify, compare sleep habit questionnaires for use in a study of college student's body compositions, and academic performances. Methods Decades of research supports the importance of proper sleep habits for college students for optimum academic performances and maintaining a healthy lifestyle. Instrument that can identify students who experience sleep disturbances and who do not get enough sleep is important in preventing obesity in college students during their college experience and afterwords. Some surveys were created for the clinical setting to determine if further diagnostics testing is necessary, while others were designed for use in academic research to be used individually, combined into composite measure of sleep or as covariates. Available instruments measure many different variables from day time sleepiness to chronotype and jet-lag. No single survey stands out as an all -encompassing sleep different aspect of sleep. No cross comparison of instruments measuring the same variable is therefore possible. Sleep survey is considered ensuring that the chosen survey was designed to measure the variables of interest. Following scales were used in the study: Standford Sleepiness Scale, Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, Horne-Ostberg Moringness Eveningness Questionnaire, Munich Chronotype Questionnaire. Results Students not meeting public health recommendations for sleep quality and quantity were found to have a significantly lower grade point average and individuals with sleep disturbances and short sleep duration have a significantly higher incidence of obesity. Conclusions Each instrument was created to measure a specific but different aspect of sleep. When conducting research with these tools, another questionnaire may be necessary to provide data specifically about the the subject's sleep habits. The Pittsburgh Sleep quality index has seen through use both clinically and in research. However, it requires another questionnaires to provide data on other variables. Each questionnaire effectively measures the concept it was designed to measure. Therefore, the choice of appropriate instrument should be based on the question, “which survey measures the variable that I wish to measure?”, not which survey is the best? Funding Sources NIMHD BRIC Grant 2009–2013 Central State University.

scholarly journals Availability of a Flavored Beverage and Impact on Children’s Hydration Status, Sleep, and Mood

Nutrients ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1757
Author(s):  
Michael R. Szymanski ◽  
Gabrielle E. W. Giersch ◽  
Margaret C. Morrissey ◽  
Courteney L. Benjamin ◽  
Yasuki Sekiguchi ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Quality Index ◽  
Pittsburgh Sleep Quality Index ◽  
Intervention Group ◽  
Urine Osmolality ◽  
Urine Specific Gravity ◽  
Hydration Status ◽  
Control Group ◽  
Profile Of Mood States ◽  
Urine Color

Euhydration remains a challenge in children due to lack of access and unpalatability of water and to other reasons. The purpose of this study was to determine if the availability/access to a beverage (Creative Roots®) influences hydration in children and, therefore, sleep quality and mood. Using a crossover investigation, 46 participants were randomly assigned to a control group (CON) or an intervention group and received Creative Roots® (INT) for two-week periods. We recorded daily first morning and afternoon urine color (Ucol), thirst perception, and bodyweight of the two groups. Participants reported to the lab once per week and provided first morning urine samples to assess Ucol, urine specific gravity (USG), and urine osmolality (Uosmo). Participants also completed the questionnaires Profile of Mood States-Adolescents (POMS-a) and Pittsburgh Sleep Quality Index (PSQI). Dependent t-tests were used to assess the effects of the intervention on hydration, mood, and sleep quality. Uosmo was greater and Ucol was darker in the control group (mean ± SD) [Uosmo: INT = 828 ± 177 mOsm·kg−1, CON = 879 ± 184 mOsm·kg−1, (p = 0.037], [Ucol:INT = 5 ± 1, CON = 5 ± 1, p = 0.024]. USG, POMS-a, and PSQI were not significant between the groups. At-home daily afternoon Ucol was darker in the control group [INT = 3 ± 1, CON = 3 ± 1, p = 0.022]. Access to Creative Roots® provides a small, potentially meaningful hydration benefit in children. However, children still demonstrated consistent mild dehydration based on Uosmo, despite consuming the beverage.

scholarly journals Clinical Efficacy of a New Robot-assisted Gait Training System for Acute Stroke Patients

2021 ◽  
Author(s):  
Andy Chien ◽  
Fei-Chun Chang ◽  
Nai-Hsin Meng ◽  
Pei-Yu Yang ◽  
Ching Huang ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Acute Stroke ◽  
Quality Index ◽  
Pittsburgh Sleep Quality Index ◽  
Gait Training ◽  
Training System ◽  
Control Group ◽  
Stroke Patients ◽  
Robot Assisted ◽  
Significant Difference

Abstract Purpose Robot-assisted gait rehabilitation has been proposed as a plausible supplementary rehabilitation strategy in stroke rehabilitation in the last decade. However, its exact benefit over traditional rehabilitation remain sparse and unclear. It is therefore the purpose of the current study to comparatively investigate the clinical benefits of the additional robot-assisted training in acute stroke patients compared to standard hospital rehabilitation alone. Methods Ninety acute stroke patients (< 3 month) were recruited. All participants received the standard hospital neurorehabilitation comprises 45–60 min sessions daily for 3 weeks. Sixty patients also received an additional 30 min of robot-assisted gait training with the HIWIN MRG-P100 gait training system after each of the standard neurorehabilitation session. Outcome measures included: 1. Berg Balance Scale (BBS); 2. Brunnstrom Stage; 3. Pittsburgh Sleep Quality Index and 4. Taiwanese Depression Questionnaire (TDQ) which were assessed pre-treatment and then after every five training sessions. Results Both groups demonstrated significant improvement pre- and post-treatment for the BBS (robotic group p = 0.023; control group p = 0.033) but no significant difference (p > 0.1) between the groups were found. However, the robotic training group had more participants demonstrating larger BBS points of improvement as well as greater Brunnstrom stage of improvement, when compared to the control group. No significant within and between group statistical differences (p > 0.3) were found for Pittsburgh Sleep Quality Index and Taiwanese Depression Questionnaire. Conclusion The addition of robotic gait training on top of standard hospital neurorehabilitation for acute stroke patients appear to produce a slightly greater improvement in clinical functional outcomes, which is not transferred to psychological status.

Reliability and validity of the Hungarian version of the Pittsburgh Sleep Quality Index (PSQI-HUN): comparing psychiatric patients with control subjects

2016 ◽  
Vol 20 (3) ◽  
pp. 1045-1051 ◽  
Author(s):  
Johanna Takács ◽  
Róbert Bódizs ◽  
Péter Przemyslaw Ujma ◽  
Klára Horváth ◽  
Péter Rajna ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Quality Index ◽  
Pittsburgh Sleep Quality Index ◽  
Psychiatric Patients ◽  
Reliability And Validity ◽  
Control Subjects ◽  
Hungarian Version

Analyst relationship between five-pattern personality and Pittsburgh sleep quality index (PSQI) of insomnia patients

2017 ◽  
Vol 40 ◽  
pp. e190
Author(s):  
G.-X. Li ◽  
Y.-L. Liu ◽  
W.-D. Wang ◽  
J. Wang ◽  
Y. Birling ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Quality Index ◽  
Pittsburgh Sleep Quality Index
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