BACKGROUND: In recent years, social media have filtered our life both in the professional and personal aspects. Currently, most of us suffer from poor quality of thinking, which is due to the impact of social media towards our lives, particularly in the health care arena. OBJECTIVES: In this article, cultural tension due to social media creates an unwanted risk to the youngsters and others with sleep deprivation. They become dependent on staying dynamic via social networking sites media all the time. As indicated by an ongoing report, there is a reliable connection between the measure of time spent via web-based networking media and depression among youthful grown-ups, which creates unprofessional problems and potential healthcare risk in individuals due to the usage of social media. RESULTS: This article speaks about the research gap and possible risks reforming strategies on healthcare communication in social media through statistical analysis. CONCLUSION: The experimental validation of case studies shows prominent solutions that have not been addressed in traditional methods.

Purpose The main goal of the physical education (PE) environment is that each individual trained should achieve self-fulfillment with the large group of students involved with their own efforts. Deep learning is applying transferrable knowledge in new situations to help the students master in tough circumstances. In PE training, injuries occur when working together as a team. Safety measures are taken immediately as an emergency response to reduce the potential risk in students by providing first aid. To provide safety measures for the injured student immediately, the environment is monitored in real-time using a GPS. Design/methodology/approach Theory of Humanities Education (ToHE) infers that it has less collection of theories and a wide range of applications than the state-of-the-art systems. ToHE allows students to think creatively and play a vital role in one’s health which is a critical aspect in PE. The ToHE theory focuses on two main concepts, i.e. by using a methodological approach to analyse and deep learning to solve the problem. PE motivates college students to follow a healthy and active lifestyle. Findings The proposed system is deployed in real time for monitoring the student’s performance and provides an emergency response with an accuracy rate of 90%. Originality/value The deep learning offers solutions to the injuries by using the deep convolutional neural network to provide interpretability of the consequence by training it with various injuries that occur in the playground and inappropriate use of sports equipment. A case study provided in this paper outlines an emergency response scenario to an injured student in sports training.