Policy and Ethics

The Effect of Brain Hacking on High School Students Likelihood of Social Media Addiction, Relationship Strength, and Willingness to Participate in Precarious Behavior

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Abstract

Technology companies implement brain hacking in their apps and devices in order to make their users spend more time on apps and devices. High schoolers, who are among those who spend the most time on their technological devices, may be affected in terms of social media addiction, connectedness with others, and the willingness to engage in risky behavior. To determine the correlation between these factors, a survey that specifically looked into Snapchat – one of the most used social messaging apps among teenagers – was conducted with 48 high schoolers. There were 8 participants in each of the categories, (1 to 100 days, 101 to 200 days, 201 to 300 days, 301 to 400 days, 401 to 500 days, and 501 days or more). The survey consisted of questions addressing Snapchat’s features, the strength of the relationship between users, engagement in hazardous behavior, and social media addiction. The results show that as the streak of the participant increased, the participant had a stronger relationship with that user. Moreover, an increase in streak length, suggests that a person has a higher likelihood of attaining social media addiction. There seemed to be no relationship between streak length and potentially perilous behavior though. These results proved how brain hacking affects users psychologically and can result in a dramatic increase in health problems.

Introduction

From watching television on tablets to completing work on laptops, technology has been integrated into the daily lives of people, so much so that people have grown dependent on it. However, many are unaware of the underlying psychological crisis that is a result of technological dependency. These technological devices purposefully offer the user a limited menu of options to choose from, in an effort to gain control of one’s thoughts and actions [1]. An example of this phenomenon is noticed when someone receives an email requesting to have a meeting. In that case, a popup could show up from Google Calendar to have the meeting at 2:00, 3:30, or 4:00 pm- subconsciously limiting the options for the meeting time.

The more time a person spends on their technological devices, the more constrained they are by these “menu options”. At a time where our future generations will be raised in this environment, it is important to understand the complete effect technology can have on our society. For this reason, it is essential to be familiar with brain hacking.

Brain Hacking

Brain hacking refers to the engineering of our phones, apps, and social media to make us spend more time on our phones. Tristan Harris, a former Design Ethicist at Google, explains how tech companies knowingly use the design of an app in order to hijack the user’s mind to form a habit. Tech companies try to maximize the impact of this method by adding valueless rewards to the process. When a person refreshes their social media, which can be considered a “slot machine” in this case, they are looking to see if they received any new posts or messages, also known as the addicting rewards. Since the user does not know at what specific time the users they follow would post or message them, users are encouraged to check back on the app more frequently to increase their chances of getting a reward. These companies have created several in-app features to encourage users to spend more time on the app. One of which is a reciprocal action process, where if one person does something on the app involving another person (texting them, tagging them in a picture, mentioning them in a comment), then this forces the other user to check that notification in order to acknowledge the initial user’s actions [1]. Snapchat is one of the many social media apps in which the effects of brain hacking are prominent.

Brain Hacking within Snapchat

Today, 69 percent of teens use the social media app Snapchat [2]. Snapchat uses several brain hacking techniques and features to make its users spend more time on the app, including it’s characterizing feature: streaks. Streaks result when a user sends direct snaps, which are essentially pictures, back and forth with another user for several consecutive days. The longer you go without breaking the chain of communication, the longer your streak is. The valueless “reward” in this scenario, are the different emojis you can obtain. These emojis represent the status of your streak. Some of the milestones your streak status can reach are 100 days, 365 days, 500 days, and so on [2]. In addition to streaks, Snapchat includes many in-app features to attract teens onto the app, including a texting mechanism, and stories (where they can see what friends and celebrities post, read the news, play games, and more). It is important to understand the negative implications brain hacking can have on the current generation, and see how it would affect the future, which is why this study was conducted on high schoolers. To better understand the effects of an app’s brain hacking features, Snapchat was analyzed.

Rationale

It is important to analyze the effect of technology on its users, as it affects our future generations. Additionally, brain hacking affects all 248.68 million smartphone users in the US, and millions more internationally [3]. On average, each Snapchat user sends more than 34 snaps a day to other users within the app [4]. The intent of brain hacking is to make users spend more time on technological devices; however, an increase in acquired technology leads to an increase in that person’s stress levels. Today, 20 percent of people can’t go for more than three hours without checking their social media accounts. The number of hours spent can be easily increased as a user becomes sucked into the digital world. The most common reason for users to become obsessed with social media is due to the user’s need to compare themselves to the “perfect” users on the app. This obsession can contribute to the development of mental health issues like depression, paranoia, isolation, and attention deficit hyperactivity disorder​ (ADHD) [5]. Limiting the control of brain hacking is essential to preventing these consequences.

Literature Review

Nancy Cheever looks more in-depth to analyze the psychological dependence users have on wireless mobile devices (WMD), which are more commonly referred to as smartphones. The study observed what would happen to students’ anxiety levels when students are deprived of their cell phones. The participants were split into two categories, students who had their cell phone on their desk but are unable to look at the notifications, and those whose phones were completely taken away from the participants. Every 20 minutes, the State/Trait Inventory, which consists of 20 statements to assess the participant’s anxiety level, was administered to analyze how the levels changed over time. The participants who had their phone nearby had a spike in their anxiety levels every time they noticed they got a notification. Since the participants were not able to check their phones for a long period of time, cortisol (our body’s main stress hormone) levels started to increase in the participants. From this study, it was found that anxiety levels increase in both groups, yet the anxiety levels dramatically increased in students whose phones were completely taken away [6]. The only way to eliminate this anxiety was to give the participants their phones back.

On one CBS news segment designed to inform readers of the concept of brain hacking, Anderson Cooper talked to app designers, neuroscientists, and researchers from California State University. One of the featured researchers was Gabe Zichermann, an expert in gamification (using techniques from video games to insert fun and competition into applications on your smartphone), who talked about the positive implications for increasing engagement with technology. This type of technology encourages dependent behavior that can result in motivating people to work out. It goes on to talk about how creators making apps that don’t encourage a person to spend more time on their phones and specific apps are being denied permission to sell their apps on the App Store [7]. However, at the end of his segment, Zichermann admits that through his research, we still do not know what the impact of this technology use is.

Another study conducted by Dr. Virginia S. Y. Kwan, Jessica E. Bodford, and David S. Sobota analyzed how smartphone addictions have evolved from possession attachment to human attachment. Smartphone addictions can also be used to predict one’s beliefs, their clinginess to smartphones, and their compulsive need to answer their phone, even in inappropriate situations [8]. This study did a survey on college students to measure human attachment, smartphone reliance, and the user’s urge to answer. Human attachment was observed through the use of the ‘Bartholomew Relationship Scale Questionnaire’ (which refers to paragraph descriptions of three basic attachment styles in romantic relationships), while an ‘Individual Differences in Anthropomorphism Questionnaire’ was used for predicting beliefs. A three-factor scale was devised for smartphone attachment. The correlation between anxious human and smartphone attachment was slightly higher than that of a secure lifestyle [8]. This established that those who are anxiously attached to humans are also anxiously attached to their smartphones. A model was created to show how smartphone addiction would predict one’s anthropomorphism beliefs (addresses the autonomy that humans grant to pets, cars, and weather patterns), and anxious smartphone attachment positively predicted the feeling of smartphone reliance.

While Nancy Cheever’s study looks into the effect of depriving people of their access to their cell phones, it does not specifically analyze the role of brain hacking in this process. Additionally, Anderson Cooper’s segment does not delve into the impacts of brain hacking psychologically or establish if more people are affected more than others. The Bodford, Kwan, and Sobota study analyzed users’ attachment to their phone, and how technology can influence one’s beliefs and dangerous behaviors. This study was not able to prove their reasoning for their outcomes that disproved their predicted outcomes. This study does establish that cell phone attachment arises from human attachment. Encountering this gap in the research of brain hacking resulted in the following research question: How do Snapchat’s Streaks predict a high schooler’s likelihood of having social media addiction, behavior, and relationships?

Tested Variables

This study was conducted to determine if there is a correlation between the length of a Snapchat user’s streak and their likelihood of having social media addiction, how a user’s streak length would affect their decisions to participate in more dangerous behavior and to determine if there is a correlation between streak length and how connected the users are. The predicted outcomes for the social media addiction factor were that the longer the streak, the more probable one is to have social media addiction​. It was also predicted that users with longer streaks engage in more risky behavior​. Finally, looking into connectedness, the prediction was that a longer streak signifies a stronger relationship between those users​.

Methodology and Survey Structure

The best methodology for this study was determined to be through a survey. A survey collects data from high schooler’s directly, which would give the most accurate data to analyze to give the most accurate conclusions. In this survey, there were 48 voluntary participants. The only requirement to participate in the survey was that the participant must be a 9th to 12th grader with a Snapchat account that had at least one streak.

The survey was regulated in a way to ensure there was an equal amount of participants in each category. These categories were based on the participant’s maximum streak length and ended up consisting of eight participants for each of the six streak length categories. The categories consisted of streak lengths from 1 to 100, 101 to 200, 201 to 300, and so on until it reached the last category of 500+.

The first variable in the survey- dangerous behavior- was analyzed by presenting various ways one could engage in risky behavior through Snapchat, as seen in Appendix B. The participant would then go through the list of actions and check off anything they have done in the past. For the following section of connectedness within relationships, the questions included in Appendix C, asked the participants for their viewpoints on how strong their relationship was with Snapchat users they had the longest streaks with. The survey also analyzed if Snapchat’s usage helped the participant build a stronger relationship, either in-person or online. The variable of social media addiction, which is a specific type of Internet addiction, was analyzed through an ‘Internet Addiction Test’ made by Dr. John M. Grohol [9]. These statements, included in Appendix D, asked the user to rate how often they experienced the cited statement. For the purposes of this study, 18 statements, which were slightly modified to be specific to Snapchat, were integrated.

In addition to examining these tested variables, the survey also included a demographic section and an app feature section at the beginning of the survey. The demographic section took note of the participant’s grade, gender, Snap score (which is the total number of snaps that the user has received and sent), and how long the participant had Snapchat. The app feature section consisted of several in-app Snapchat features, which can be seen in Appendix A, that the users would then rate on a scale from 1 to 5. The app feature section was implemented to test the impact brain hacking had on the users through users’ attractiveness to the features.

Results

First looking into app features, the results show that a majority of the participants like all of the features that Snapchat provides, with more than 75 percent of participants giving the

Snapchat features a score of 3 or more on the 1 to 5 scale. This is with the exception of one of the features on Snapchat: Snapchat games. However, this feature is relatively new, only being added to the app in early April 2019 [10]. Since a majority of users do not like this feature on the app, this feature will probably be removed soon. These results align with the concept of brain hacking, showing that these features are supposed to appeal to the users so that users are more willing to spend time on the app.

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Figure. 2. Most participants favored the brain hacking features within the Snapchat application

Looking into the first tested variable, of Social Media Addiction, there seemed to be a direct relationship between the streak length and the social media addiction score. As the user’s streak length increased, their social media addiction test score typically increased as well.

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Figure. 3. There seems to be a direct relationship between the length of a Snapchat streak and the score on the Social Media Addiction test.

When participants have more streaks, users go onto their Snapchat more often to make sure there is no hourglass emoji, which indicates a streak is about to end, attached to any of the streaks. Although the user may initially log into their Snapchat for this purpose, users get distracted by the other features of the app that encourages the user to spend more time on the app. This causes users to be more attached to the app, which would result in higher chances of social media addiction.

The results for the next tested variable, hazardous behavior, did not indicate any correlation with the length of the user’s streaks. This result was contradictory to the studies’ initial prediction. The data shows that no matter what the user’s streak length was, the majority of participants participated in 2 to 3 acts of risky behavior. The acts of risky behavior usually consisted of letting a stranger add the user on Snapchat and sharing the Snapchat account password with another user to take care of streaks for the user. The data table with the dangerous behaviors a participant took a part of can be seen in Appendix A.

For the last tested variable, connectedness, 84 percent of the participants talked to all the people they have streaks with, but participants with longer streaks didn’t talk to all those that they had streaks with. 76 percent of the participants believe they have a stronger relationship with the people they have a longer streak with. Furthermore, 70 percent of participants have built a stronger relationship with someone through Snapchat, as seen by the pie charts below. This corresponds to the threatening behavior portion of this study. Snapchat users are willing to dedicate more resources to increase their chances to reach one of the streak milestones (100, 365, 500 days, etc), so they attempt to start a streak with more users.

Figure. 4. Most participants use Snapchat’s features to enhance in-person relations.

Figure. 5. Most participants devote more time to strengthen their virtual relations with participants they have a strong in-person relationship with.

Figure. 6. The brain hacking features in Snapchat helped promote new relationships between users.

Data Analysis

For the data analysis of the Social Media Addiction test, each participant was given a score based on their responses to the test. Every participant started with a score of 0 points, and each time the participant chose the answer choice of “Never/Rarely” for a statement, 0 points were added to the score. Similarly, if the participant chose “Sometimes”, 1 point would be added to the score, and selecting “Always/ Regularly” would earn 2 points. At the end of the survey, the individual’s summed up score would be cross-applied to a scale that was provided with Dr. John M. Grohol’s Internet Addiction Test to determine the level of Social Media Addiction a person had. The utilized scale is provided below.

Figure. 7. Scale for social media addiction levels

To analyze connectedness and dangerous behavior, a comparative analysis, where each streak category was examined to identify any trends or similarities, was conducted. With this, the trends were then compared with the other categories for any patterns. Within dangerous behavior, the number of actions the participant engaged in was tracked, as well as which ones they participated in. For connectedness, how the user would score their relationship strength would be compared with if the user knew all of the people on their Snapchat.

Implications and Limitations

A limitation that was not taken into consideration before distributing the survey was that streaks break very often. Because of this, there were a few outliers in the data, which would better fit in with the data of a higher streak length. In the case that this study is replicated, it is advised to alter this part to look into the longest streak length a user ever had, compared to the longest streak length at the moment. This would reduce the outlying data, and would result in more accurate data collection. Another limitation was my small sample size. Due to the initial struggle to get people to sign up for the survey, the sample size was cut down to make sure there was time to collect the necessary data. The sample of 48 high schoolers cannot represent the Snapchat experience of all high schoolers. If there were more participants, the data would take into consideration the situations of more high schoolers to get more precise data. For future study, it is also suggested that a validated, and potentially related, measure for connectedness between users and dangerous behavior should be utilized for more valid analysis, rather than simply a comparative analysis.

Along with limitations, this study also had several inferences. There is a strong correlation between the one’s streak length and their likelihood of having social media addiction, as well as one’s streak length and the strength of that relationship in-person. Finally, through this study, the full psychological impact of brain hacking on high schoolers is recognized, suggesting a need to assemble a plan to manage the influence of digital devices on users.

Conclusion

This paper delved into the effects of brain hacking on high schoolers through the social media application, Snapchat. After analyzing the effect of brain hacking on social media addiction, precarious behavior, and connectedness, the survey results demonstrate there is a direct relationship between social media addiction and involvement in brain hacking strategies and brain hacking techniques that promote users to engage more with other users. However, there seems to be no direct relationship between brain hacking techniques and hazardous behavior. Regardless of involvement with brain hacking techniques, a majority of users take part in a couple of risky behaviors. This research supports two of the three components within the initial predictions. These results reflect the significant impact brain hacking techniques can have on social media users’ lives, and it is important to understand the long-term consequences of this environment. In fact, as many of the survey participants took the survey, several of them were able to realize the true value of their Snapchat and the impact it had on them. While brain hacking techniques have the potential to improve the social component of a user’s lives, lack of careful consideration for these techniques could result in significant harm to the users mental wellbeing.

References

1. Harris, Tristan. “How Technology Is Hijacking Your Mind - from a Former Insider.” Medium. Thrive Global, October 16, 2019. https://medium.com/thrive-global/how-technology-hijacks-peoples-minds-from-a-magician-and-google-s-design-ethicist-56d62ef5edf3.

2. Lorenz, Taylor. “Teens Explain the World of Snapchat’s Addictive Streaks, Where Friendships Live or Die.” Business Insider. Business Insider, April 14, 2017. https://www.businessinsider.com/teens-explain-snapchat-streaks-why-theyre-so-addictive-and-important-to-friendships-2017-4.

3. Iqbal, Mansoor. “Snap Inc. Revenue and Usage Statistics (2018).” Business of Apps, October 30, 2018. http://www.businessofapps.com/data/snapchat-statistics/.

4. Aslam, Salman. “Snapchat By The Numbers (2018): Stats, Demographics & Fun Facts.” Omnicoreagency.Com, 2018. https://www.omnicoreagency.com/snapchat-statistics/.

5. Fader, Sarah. “Social Media Obsession and Anxiety.” Anxiety and Depression Association of America, 2018. https://adaa.org/social-media-obsession.

6. Cheever, Nancy A., Larry D. Rosen, L. Mark Carrier, and Amber Chavez. “Out of Sight Is Not out of Mind: The Impact of Restricting Wireless Mobile Device Use on Anxiety Levels among Low, Moderate and High Users.” Computers in Human Behavior. Pergamon, June 6, 2014. https://www.sciencedirect.com/science/article/abs/pii/S0747563214002805.

7. Cooper, Anderson. “What Is ‘Brain Hacking’? Tech Insiders on Why You Should Care.” CBS News. CBS Interactive, April 9, 2017. https://www.cbsnews.com/news/brain-hacking-tech-insiders-60-minutes/.

8. Jessica, Bodford E, Virginia S Y Kwan, and David S Sobata. “Fatal Attractions: Attachment to Smartphones Predicts Anthropomorphic Beliefs and Dangerous Behaviors.” Cyberpsychology, behavior and social networking. U.S. National Library of Medicine, 2017. https://pubmed.ncbi.nlm.nih.gov/28498047/.

9. Team, Psych Central Research. “Internet Addiction Test: Are You Addicted to Your Smartphone?” Psychology Tests & Quizzes, July 29, 2018. https://psychcentral.com/quizzes/internet-addiction-quiz/.

10. IIA. “Research Peek of the Week: Smartphone Users in the US Expected to Reach Over 270 Million by 2022.” Internet Innovation Alliance, June 5, 2018. https://internetinnovation.org/general/research-peek-of-the-week-smartphone-users-in-the-us-expected-to-reach-over-270-million-by-2020/.

Additional References

Bosker, Bianca. “What Will Break People’s Addictions to Their Phones?” The Atlantic. Atlantic Media Company, January 6, 2017. https://www.theatlantic.com/magazine/archive/2016/11/the-binge-breaker/501122/.

Moon, Angela. “Snap Adds Games to Snapchat App to Hold on to Young Users.” Reuters. Thomson Reuters, April 4, 2019. https://www.reuters.com/article/us-snap-event-games/snap-adds-games-to-snapchat-app-to-hold-on-to-young-users-idUSKCN1RG2G6.

Hou, Yubo, Dan Xiong, Tonglin Jiang, Lily Song, and Qi Wang. “Social Media Addiction: Its Impact, Mediation, and Intervention.” Cyberpsychology, February 21, 2019. https://cyberpsychology.eu/article/view/11562.

Magid, Larry. “Magid: Facebook Slips, Snapchat Grows among Teens.” The Mercury News. The Mercury News, June 1, 2018. https://www.mercurynews.com/2018/05/31/facebook-slips-and-snapchat-grows-among-teen-social-media-users/.

Bormann, Sara. “Our Minds on Tech: How Technology Affects the Human Brain.” CHM, March 18, 2018. https://computerhistory.org/blog/our-minds-on-tech-how-technology-affects-the-human-brain/.

Appendix A:

Demographics and App Features-

Questions regarding participant’s demographics and likability of app features are shown in the first row and survey responses are shown below that

Appendix B:

Dangerous Behavior-

This section was presented as a question where participants would check the boxes of all the precarious activities that applied. Each row signifies a different participant’s response.

Appendix C:

Connectedness-

The first row shows the questions implemented to analyze connectedness in the survey. All of the following rows are different participant’s responses.

Appendix D:

Social Media Addiction-

Modified questions from Dr. Grohol’s ‘Internet Addiction Test’ are shown in the first row and survey responses are shown below that

About the Author

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Anika Attaluri is a junior at Hamilton High School, AZ. She has taken several college level courses, including AP Seminar, AP Research, AP Biology, AP Chemistry, and AP Psychology. She has participated in several research projects that are affiliated with Arizona State University and other research laboratories. She is currently working on scientific research projects for AZSEF.

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