Young users' social media addiction: causes, consequences and preventions

Purpose Social media addiction has been an ongoing topic of debate for platform developers, well-being and mental health experts. There is a limited understanding of the factors leading to the addiction of young social media users, the consequences of experiencing addiction, and the measures/mechanisms used by parents and platform providers to limit/prevent problematic social media use amongst young users. This systematic review aims to provide a comprehensive overview of the literature concerning these issues. Design/methodology/approach The Preferred Reporting Items for Systematic Reviews (PRISMA) protocol was used to evaluate and present the results. A total of 45 studies were screened and independently reviewed against predetermined criteria for eligibility. Findings The results revealed four categories of young users' addiction to social media networks (social, technological, behavioural and mental). Several prevention approaches directed at parents and platform providers were discussed. Originality/value This study offers important insights for health policy makers, platform providers, parents and researchers on designing interventions addressing social media addiction amongst young users. It also provides an in-depth understanding of the conceptualization of social media addiction and suggestions on possible actions to prevent it

Emotional Intelligence and Individual Visual Preferences: A Predictive Machine Learning Approach

Differences in individuals’ psychological and cognitive characteristics have been always found to play a significant role in influencing our behavior and preferences. While a number of studies have identified the impact of these characteristics on individuals’ visual design preferences, understanding how emotional intelligence (EI) would influence this process is yet to be explored. This study investigated the link between individuals’ EI dimensions (eg, emotionality, self-control, sociability, and well-being) and their eye movement behavior in an attempt to build a prediction model for visual design preferences. A total of 136 participants took part in this study. The feature selection and prediction of EI and eye movement data were performed using the genetic search method in conjunction with the bagging method. The results showed that participants high in self-control and emotionality exhibited different eye movement behaviors when performing five visual selection tasks. The prediction results (93.87% accuracy) revealed that specific eye parameters can predict the link between certain EI dimensions and preferences for visual design. This study adds new insights into human–computer interaction, EI, and rational choice theories. The findings also encourage researchers and designers to consider EI in the development of intelligent and adaptive systems

COVID-19 and people's continued trust in eHealth systems: a new perspective

Individuals’ use of eHealth services has increased significantly. However, the recent pandemic of coronavirus disease 2019 (COVID-19) has resulted in a significant reallocation of health resources and support. This study investigated the impact of service quality dimensions on individuals’ continued trust in eHealth during COVID-19. A decision-making trial and evaluation laboratory (DEMATEL) approach was used to identify and analyse the causal relationships between service quality dimensions and individuals’ continued trust in eHealth services. A total of 134 eHealth users (78 males and 56 females; aged 29–61 years) responded to the DEMATEL questionnaire. The results showed a variation in the impact of service quality factors on individuals’ continued trust in eHealth services. This study found three core factors (responsiveness, assurance and tangibility) that influence individuals’ continued trust in eHealth services. Other secondary factors (e.g. content quality, reliability, efficiency and hedonic benefits) were found to be primarily influenced by the core factors. The identified relationships in this study can aid the decision-making process of healthcare providers and increase the efficiency of healthcare delivery

Neck Health Metrics and Quality of Life: A Comparative Study in Bike Drivers with and without Neck Pain

Aafreen Aafreen,1 Abdur Raheem Khan,1 Ashfaque Khan,1 Ausaf Ahmad,2 Abdullah Hussain Alzahrani,3 Abdullah Ibrahim Alhusayni,3 Abdulaziz H Alameer,4 Ramzi Abdu Alajam,4 Bhuvanesh Babu Mondey Ganesan,4 Mohammad Abu Shaphe4 1Department of Physiotherapy, Integral University, Lucknow, India; 2Department of Community Medicine, Integral University, Lucknow, India; 3Department of Health Rehabilitation Sciences, College of Applied Medical Sciences, Shaqra University, Shaqra, Saudi Arabia; 4Department of Physical Therapy, College of Applied Medical Sciences, Jazan University, Jazan, Saudi ArabiaCorrespondence: Abdur Raheem Khan, Department of Physiotherapy, Integral University, Lucknow, India, Tel +9616739965, Email [email protected]: Neck pain is a prevalent musculoskeletal issue among bike drivers, often resulting from extended static postures, repetitive head movements, and exposure to vibrations. This study aims to assess the connection between cervical ROM, neck proprioception, CVA, and QOL in bike drivers with neck pain compared to those without neck pain so that the targeted interventions can be developed to enhance their well-being.Methods: A cross-sectional study involving 100 bike drivers aged 20– 50 years was conducted, split into two groups: those with neck pain (n=50) and those without neck pain (n=50). Cervical ROM was measured using a smartphone, neck proprioception was assessed through a head repositioning test, and CVA was determined using lateral-view photographs with a plumb line. The Short Form-36 (SF-36) questionnaire was employed to evaluate QOL. Data analysis was conducted using independent t-tests and Pearson’s correlation coefficient.Results: Bike drivers with neck pain exhibited significantly reduced cervical ROM (p-value=< 0.001), impaired neck proprioception (p-value=< 0.001), and decreased CVA (p-value=< 0.001) compared to their counterparts without neck pain. A strong negative correlation was found between neck pain and QOL, with lower scores in all eight domains of the SF-36. Cervical ROM, neck proprioception, and CVA showed moderate correlations with various QOL domains (p-value=< 0.05).Conclusion: Neck pain in bike drivers is linked to decrease cervical ROM, compromised neck proprioception, and reduced CVA. These factors correlate with a lower quality of life, both physical and mental domains. Interventions addressing these aspects may enhance the quality of life for bike drivers experiencing neck pain.Keywords: cervical range of motion, neck proprioception, craniovertebral angle, quality of life, neck pain, bike driver