Doomscrolling: An Analysis of the Effects of Technology Usage on Your Mental Health
By Andrew Shim
As technology starts to ever change and evolve, the more people are seen endlessly scrolling or watching a bright screen for hours on end. This is known as doom-scrolling or an addiction to technology. This has become so bad that people are seen shut away from others and only in the company of technology. The social interactions between fellow classmates and friends have been limited to messages on the phone or calls online. Moreover apps like Tiktok, Youtube Shorts, and Instagram Reels deteriate users attention spans to the point where they cannot focus on one thing for more than 30 minutes. This then creates a habit of not focusing on important things such as class, friends, and family. This article will provide an analysis of the affects of how much technology usage will affect the brain and mental health or if there is another reason associated with these mental health deteriorations.
Stakeholders:
The stakeholders for this would be students, young adults, children, and anyone who uses technology on a daily basis. This is crucial for these people to understand and set a limit for themselves before it is too late and they become mindless zombies glued to their phone. With this analysis scientist and researchers can help likeminded people everywhere who are suffering from an addiction to their devices.
Data Collection:
To analyze the introduction above there needs to be a dataset that will view a person’s technology usage throughout multiple different devices as one does not only just stay on their phone as technology has many different ways to access a human. The dataset would also need to have a survey on their mental health or some way of describing how they are feeling someone showing a correlation between technology usage and mental health. There would also be a need to track how long users sleep as technology could take away time from these individuals to get a good nights rest therefore deteriorating their mental health. Finally there would need to be some sort of show of if it effects users real life activities or environments. This would be needed as to answer the question of does technology effect the mental health of a human being. The information that was collected was found through Kaggle: https://www.kaggle.com/datasets/waqi786/mental-health-and-technology-usage-dataset?resource=download
This information includes all sorts of columns such as the gender, age, screen time for various types of technology, stress levels, mental health state, physical activity hours, and work environment impact. For the better visibility and understanding of hours on technology the graphs will show an average time between all three usages in order to keep it neat and clean. This dataset consists of ten-thousand users and their screen times and various sorts of columns mentioned above. There was no indication of any misinformation or anything wrong with the files so the cleaning would be minimum to none.
Methods:
In order to obtain the visualizations and data researchers need, one must use different sorts of analysis such as relationships to create a correlation between certain variables. The goal is to see how different amounts of screen time will affect people in various ways.
Another method is using summary statistics in order to calculate the properties of the data set and get a better understanding of how often people view technology.
Analysis:
Using some comparative data analytic techniques to the data in order to find the results. The first part was to create random generated sets of data from the main set in order for simplicity there are thousands of users and in order for ease of view and use three smaller sample sets were created. Next was to get the summary statistics for each subset and compare it to the mental health subset. After this is done the data is then put into regression plots in order to fully visualize the data and see the comparison between screen time and mental health.
As the graph shows above there is a wide range of scores that result in a graph that has many different types of results. Although there are those whose mental heath scores are high, there can also be the same with the opposite. Many outside factors could also be played into knowing why mental health scores and screen time are so high or low. Some may conduct that screen time and mental health scores are both high due to technology giving people more dopamine and a happier mental state. Video games can create a gateway to a happier environment for some people and therefore people find themselves playing more and having a higher mental score. But the same can go the other way as people can go online and scroll for hours and their mental state starts to deteriorate and lose focus on important aspects of life. Another graph shown is the relationship between screen time and job satisfaction.
This shows a similar story to the mental state. This can also be related to outside factors such as the type of job, relationship issues, and work environment. Just as there are lots of high job satisfaction scores there are also low ones too.
Overall by analyzing this dataset there has been a conclusion that more than just screen time can create a problem with people and their health. Just because someone is staring at a screen for hours on end does not mean that they will hurt themselves. It is possible however but this study concludes that there are outside factors associated with these results.
Errors/Biases:
Although the research was done that does not mean that there is never more room for more research. This was a small subset of a much larger human population of billions of people. In order to truly get a scale of how much screen time is affecting people one must figure out everyone on this earth. This can help provide a glimpse of what the future might look like but not a full conclusion can be made. There are many outside factors that could’ve been when collecting this data.
Github Repository:
