Background: In recent years, a significant shift toward remote work, virtual education, and social distancing measures was witnessed, thereby leading people to increasingly depend on digital devices for communication, work, and entertainment. This increased exposure to screens has raised concerns regarding its potential impact on cognitive function. Purpose: This study investigated the relationship between screen time and cognitive function among healthy young adults. Methods: One hundred forty-five healthy individuals (mean age 21.55 ± 2.84 years) participated in this cross-sectional study. Sociodemographic information including age, sex, height, weight, and level of education were obtained. Participants reported screen time using a screen time questionnaire. Cognitive function tests including, Paced Auditory Serial Addition Task (PASAT), Montreal Cognitive Assessment (MoCA) and Symbol Digit Modalities Test (SDMT) were conducted. Multilinear regression analyses were used to examine the associations between age, sex, level of education, screen time, and cognitive function. Results: One hundred thirty-nine participants (76 women) completed the study. Increased night screen time, bachelor’s educational level, and women were associated with lower PASAT scores (R2=0.258; p≤ 0.047). Moreover, increased night screen time was associated with lower MoCA scores (R2=0.029; p=0.035). However, no associations were found between night screen time and SDMT scores. Conclusion: Participants who had higher night screen exposure had lower cognitive scores in the information speed processing, working memory, calculation, and attention domains. Considering these findings, this study emphasizes on the importance of setting a future recommended screen time guidelines for young adults as well as to promote healthy cognitive habits in order to preserve cognitive function and reduce the risk of developing neurodegenerative disease in the future. Future prospective cohort studies involving a more diverse age range is needed.

Background: This study aimed to identify the factors that influence Breast Cancer (BC) women’s quality of life (QoL) based on the International Classification of Functioning, Disability and Health (ICF) framework.Method: A cross-sectional study was conducted among 188 women with BC. The dependent variable, QoL, was measured using the Quality of Life Index (QLI-c). The independent variables were measured using the following Arabic-validated questionnaires: Pittsburgh Sleep Quality Index (PSQI), Female Sexual Function Index (FSFI), Modified Fatigue Impact Scale (MFIS), Hospital Anxiety and Depression Scale (HADS), and the International Physical Activity Questionnaire (IPAQ).Results: There was a significant positive correlation between monthly income (r = 0.17, p = 0.016) and QoL, and significant negative correlation between the stage of disease (r = −0.221, p = 0.002) and duration of first diagnosis (r = −0.280, p = 0.004) with QoL. Poor sleep quality, sexual dysfunction, fatigue, depression, and anxiety had significant negative correlations with QoL (p < 0.01). Multiple regression analysis revealed that among the various factors that might affect QoL, sexual dysfunction, poor sleep quality, depression, and anxiety were significant predictors of QoL (p ≤ 0.05).Conclusion: The ICF provided an excellent framework to explore the factors influencing QoL among women with BC. This study has given evidence for the relationship of demographic, clinical, and body functional factors with QoL among women with BC. Interestingly, sexual dysfunction, poor sleep quality, depression, and anxiety factors are predictors of QoL. Awareness of these factors that predict QoL will guide healthcare professionals to improve the health and QoL of BC women.

Background: Gait deficits are common among people with multiple sclerosis (PwMS). Therefore, investigating factors that may influence walking in PwMS is important. Previous studies in older adults and other neurological populations demonstrated the relationship between sleep quality and gait performance. Despite the fact that the prevalence of poor sleep quality is very high among PwMS, little is known about the effect of sleep quality on gait among PwMS. Objective: This study aimed to explore the relationship between sleep quality and gait performance in PwMS. Methods: Forty-one PwMS participated in the study between February 2019 and December 2019. Participants were asked to walk at a self-selected speed over 10$$ m with an inertial measurement unit (IMU) attached over the back. Walking speed, step length (left and right), and step time were calculated. Sleep was estimated objectively using a wrist-worn triaxle-accelerometer; the derived parameters were sleep efficiency (SE) and the number of awakening after sleep onset (NASO). Results: SE significantly correlated with step length ($p=0.02$ ). Furthermore, the NASO significantly correlated with gait speed ($p=0.03$ ), and step-time ($p=0.02$ ). These correlations remained significant even after adjusting for age and disease duration. Conclusion: We observed that when corrected for disease duration and age there were relationships between NASO and SE to gait parameters; these observations warrant further investigations.

Taking notes during lectures plays a vital role in enhancing learning outcomes. With technological advancements, digital note-taking has gained popularity among university students in recent years due to its convenience, ease of storage, sharing, and searching. Different versions of digital note-taking have been introduced, including the use of styluses on tablets, which offer a blend of traditional handwriting and digital advantages. However, the use of digital devices may introduce distractions, such as access to social media, potentially disrupting focus and impacting learning effectiveness. Therefore, their impact on learning and cognition remains a topic of ongoing exploration. This study aimed to investigate the differences in cognitive functions between university students practicing either longhand or styluses digital note-taking methods in the United Arab Emirates. One hundred students participated in this cross-sectional study. Sociodemographic information, including age, sex, nationality, and study year were obtained. Participants reported the note-taking method they use (longhand vs. digital note-taking with styluses). A battery of cognitive tests was used in this study to assess different cognitive functions, including the Montreal Cognitive Assessment (MoCA), the Symbol Digit Modalities Test (SDMT), the Brief Visuospatial Memory Test-Revised (BVMT-R), and the Stroop Color and word test. The Mann-Whitney U tests were used to assess differences in different cognitive domains between participants following longhand and styluses digital note-taking. Students that used longhand note-taking demonstrated significantly higher overall cognitive scores (MoCA, p = 0.005), along with superior information processing speed, working memory (SDMT, p = 0.045), and better visual memory (BVMT-R, p = 0.01), compared to those who used styluses digital note-taking. However, students using styluses digital note-taking exhibited better inhibitory cognitive control (Stroop test, p = 0.020). Although using styluses offers a hybrid experience by combining the tactile benefits of handwriting with the digital advantages of electronic devices, students who employed longhand note-taking demonstrated significantly higher cognitive scores across several domains compared to their peers using stylus-based digital methods. However, while these differences were statistically significant, the effect size was small. Longitudinal cohort studies are needed to further examine the predictive, mediating, and confounding factors related to note-taking methods and cognitive abilities in students.

A high prevalence of obesity, sedentary behavior, and physical inactivity could affect muscle mass and strength in young adults in the United Arab Emirates (UAE). Therefore, we investigated the association of sex, body mass index (BMI), and accelerometer-measured sitting and physical activity (PA) times with skeletal muscle mass index (SMI), hand grip, and thigh muscle strength in healthy young adults in the UAE. In this cross-sectional study, 156 healthy young adults (age 21.68 ± 3.01 years, BMI 25.40 ± 4.79 kg/m², 52.6 % women) were included. BMI and muscle mass were recorded using a bioelectrical impedance analyzer. Maximum hand grip strength and thigh muscle torque were assessed using the Jamar-smart hand-dynamometer and Biodex System-4-Pro, respectively. Participants wore a triaxial Fibion accelerometer on their anterior thigh for >10 h per day for 4-7 days to measure their sitting and PA times. Multiple linear regression analyses were used. Participants spent most of their time sitting (11.37 ± 1.10 h), followed by standing (2.92 ± 0.86 h), walking (1.58 ± 0.55 h), and vigorous intensity PA (4.79 ± 5.85 min) per 16-h day. Sex (p < 0.001) and BMI (p < 0.001) were negatively associated with all muscle mass and strength variables. Men had more muscle mass and strength than women. As BMI increased, muscle mass and muscle strength decreased. Accelerometer-measured sitting and walking times were negatively associated with concentric hamstrings (p = 0.044) and quadriceps torques (p = 0.031), respectively. Sex, BMI, and accelerometer-measured sitting and walking times were associated with muscle mass and/or muscle strength in healthy young adults. Women and those with a high BMI need interventions to improve their muscle mass and strength. The paradox regarding the association of PA with muscle mass and strength in younger adults may be due to possible influences from other factors (e.g., resistance training, dietary intakes, etc.) superseding that of accelerometer-measured PA.