tiktok addiction research paper

What Makes TikTok so Addictive?: An Analysis of the Mechanisms Underlying the World’s Latest Social Media Craze

Author: Sophia Petrillo

The health impacts of social media addiction remain somewhat unknown. Recent studies indicate variable health effects depending on the severity of the addiction, and increased social media use predicts more significant health consequences. One study investigating the impact of social media addiction on stress among employees of 13 companies in Thailand found that those with a higher degree of addiction appear to have a lower capacity for mindfulness (i.e. the ability to be fully engaged with the present moment). Social media addiction may reduce productivity and success in work, education, and other areas of life. Additionally, the study revealed that individuals experiencing addiction to social media choose emotion-focused coping to alleviate stress rather than problem-focused coping. In contrast to problem-focused coping, in which an individual takes actions targeted at the source of the problem, emotion-focused coping involves efforts to reduce the emotional severity of a situation as a means of resolving the problem. However, the employment of social media to reduce stress qualifies as unhealthy use and may increase emotional exhaustion. Those who are addicted often rely on social media to distract from real-life problems, which masks them and prevents addressing underlying issues. 1

Generally, social media has been linked with several adverse health impacts, particularly in transitional-age youths and adolescents. For example, more frequent daily social media site visits have been associated with higher odds of depression among U.S. individuals between the ages of 19 and 32, and corresponding findings have been reported internationally. 2 Furthermore, two separate studies, one on Scottish adolescents and another on U.S. college students, both indicated a relationship between increased use of social media and heightened levels of anxiety. 3,4 Associations between social media use and poor sleep and unhealthy eating habits have also been supported by nationally- and internationally-based studies. 5,6 Taken together, these findings suggest that the implications of social media addiction can be damaging to both individual and population health.

One social media platform that has seen a significant increase in popularity recently is TikTok. Reminiscent of newly-retired platforms, Vine and Musical.ly, regarding the type and format of app content, TikTok features short-form videos on every topic imaginable. At first featuring lip-synching and dancing to popular songs, current content has expanded to now include comedy, technical skill instruction, fitness inspiration, and myriad other categories. In addition, users can create original content and respond to content made by others through likes, comments, and reshares. Another key component of the app is the “For You” page, a feed specifically curated for each user by the app based on user activity and interaction with other content. Certain individuals have taken advantage of the platform as a marketing tool, establishing themselves as “influencers;” many companies also utilize the app to promote their products and messages. The global audience is heavily skewed towards younger generations, with almost half of its users under age 34, and teenagers make up nearly one-third of accounts. Overall, the platform had over 800 million users in 2019 and is expected to exceed 1 billion users by the end of 2020. Its current economic valuation of $75 million qualifies it as the world’s most valuable startup. Since its popularity spike in 2018, TikTok has surpassed other traditional social media apps such as Instagram and Facebook as the most-downloaded social media app. 7 Clearly, TikTok is well-established, rivaling other platforms for supremacy in the social-media world. 

The ‘like’ button is a hallmark of nearly all social media platforms. The action of ‘liking’ social media content has recently become so popular that Merriam Webster now lists an alternative definition of ‘like’ in the dictionary as “to electronically register one’s approval of (something such as an online post or comment) for others to see (as by clicking on an icon designed for that purpose).” 8 The button was first created in 2005 on Vimeo as an alternative way for users to react to videos that felt less concrete than ‘favoriting’ them; its later introduction to Facebook in 2009 and subsequent alterations to its functionality contributed to its establishment as a fixture of social media platforms. 9 ‘Likes’ provide information on social norms and indicate the societal view of particular media that is posted, influencing how individuals perceive it. Additionally, ‘likes’ offer information to social media companies and other websites where there are ‘like’ button plugins so they can more specifically tailor their content to users to keep them more engaged without directly asking their preferences. 10 The ‘like’ button was instrumental in the rapid growth of Facebook in 2010 and has had similar effects on TikTok over the past few years. Thus, although the platforms differ in their content and audiences, they are remarkably alike at the structural level.

In alignment with traditional mechanisms of reward-based learning and facilitation of the habit and addiction loops, ‘likes’ serve as a reward for social media users. A study utilizing a functional MRI paradigm to mimic the “Instagram experience” of viewing “liked” photos demonstrated increased neural activity in regions traditionally associated with reward, namely the nucleus accumbens, and provided evidence for the influence of virtual peer endorsement through ‘likes’ as a form of quantifiable social endorsement among users; accordingly, receipt of a ‘like’ indicates that others approve of an individual’s content. 11 This satisfies the human desire for acceptance by others, particularly those they respect and whose opinions they value; these individuals often comprise one’s ‘friends’ or ‘followers’ on social media. Dopamine release is a key part of the positive feedback loop that drives reward-based learning; increased dopaminergic activity in the brain in response to receiving a ‘like’ encourages future social media use and continued content publication in hopes that the pleasurable experience will re-occur. 12 ‘Likes’ also keep users engaged with social media platforms by representing a form of investment; ‘liking’ content elicits the psychological experience of investment in the platform, and the more invested people are, the more likely they are to care about it and return to the website or app in the future. Evidently, ‘likes’ are gratifying in multiple ways — it feels good to receive likes from other people, and it also feels good to give ‘likes’ to other people in the same way that it feels good to give people gifts. For both forms, the presence of the like button allows instant gratification, which drives habitual use and addiction through positive reinforcement. 13

Undoubtedly, the appeal and entertainment value of content posted on TikTok is a major factor in its popularity. Users are intrigued by videos posted by others and may recreate these videos or publish original content. However, the platform’s success is also heavily influenced by elements of the app itself, and it has been argued that certain app features drive the formation and sustenance of addictions to the platform. Recent reports reveal that users spend an average of 46 minutes per day on the app and open it eight times daily; considering the maximum length of videos is 15 seconds, they may watch upwards of 180 videos per day on average. 14 Like other social media platforms, the infinite scroll and variable reward pattern of TikTok likely increase the addictive quality of the app as they may induce a flow-like state for users that is characterized by a high degree of focus and productivity at the task at hand, 15 whether that be a game, one’s social media feed, or another virtual activity. Once immersed in the flow-like state, users may experience a distorted sense of time in which they do not realize how much time has passed. Furthermore, the app interface itself is straightforward and user-friendly, with only a limited number of buttons and sections of the app for users to navigate, which further enables entrance into “flow.” 16 Videos are short, which is ideal given the decreasing attention capacity of youths in the 21st century. When they play, they consume the entire device screen, which creates an immersive experience for users. 17

The personalized “For You” stream created by artificial intelligence (AI) for each user has also been identified as a key contributor to TikTok addiction. TikTok differs from other social media apps because an individual’s feed is not based on deliberate choices made about the content they want to see. Instead, AI presents individuals with content and uses their reactions to it (in the form of likes, comments, and reshares) to determine other content they might like, facilitating a continuous cycle that starts from the first use and becomes increasingly accurate with repeated engagement. 18 All of the in-app features prolong the time that users spend on the app, which increases the addictive capacity of the platform. To further support this effort, developers constantly change the app layout and add new features so that users spend more time on the app navigating and adjusting to the new design.

Although the similarity may not be immediately evident, analysis of social media apps reveals that they are designed to function like slot machines — the “swipe down” feature required to refresh one’s feed mirrors pulling a slot machine lever, and the variable pattern of reward in the form of entertaining videos on TikTok simulates the intermittent reward pattern of winning or losing on a slot machine; this pattern keeps individuals engaged under the impression that the next play might be “the one.” 19 The striking parallelism between social media apps and slot machines is intriguing given that gambling is the only behavioral addiction currently recognized by the DSM-5. Provided that social media apps are functionally akin to slot machines, it is likely that the use of these apps is just as addictive as slot machines and fosters social media addiction, much like how slot machines contribute to gambling addiction.

Taken together, specific consideration of TikTok in the larger context of social media platforms reveals that “TikTok addiction” is likely a result of a combination of effects. Like other substance and behavioral addictions, it is expected that there are dispositional factors involved in the development of addiction to TikTok. This is because certain lived experiences and personality traits are believed to predict a tendency for engagement in habitual behaviors and addiction. Although these characteristics are often unpreventable, therapeutic and medicative treatments may effectively reduce their influence on an individual’s behavior, so this driver of TikTok addiction may not be too significant.

Unfortunately, it appears that structural and contextual aspects of TikTok are greater contributors to addiction than dispositional attributes of users. Elements of app design and functionality, namely the variable reward pattern of the content stream, the simple, “flow-inducing” interface, and the capability for “endless scroll,” capitalize on classical conditioning and reward-based learning processes to facilitate the formation of habit loops and encourage addictive use. Unlike dispositional drivers of “TikTok addiction,” situational elements of the platform are engineered by app developers, and thus, could be eliminated. However, developers are unwilling to relent with the knowledge that their app’s success depends on its ability to manipulate users to continue use despite any adverse consequences. Although this behavior is conscious and deliberate, whereas dispositional factors are often unconscious and uncontrollable, changing the attitudes and behavior of those in the social media industry may pose a greater challenge to public health efforts to reduce “TikTok addiction” than simply treating misaligned personality traits; this is the reality of living in an increasingly digital and technologically-based world.

• Sriwilai, K., & Charoensukmongkol, P. (2016). Face it, don’t Facebook it: impacts of social media addiction on mindfulness, coping strategies and the consequence on emotional exhaustion. Stress and Health , 32 (4), 427-434.
•  Lin, L. Y., Sidani, J. E., Shensa, A., Radovic, A., Miller, E., Colditz, J. B., … & Primack, B. A. (2016). Association between social media use and depression among US young adults. Depression and anxiety , 33 (4), 323-331.
•  Woods, H. C., & Scott, H. (2016). # Sleepyteens: Social media use in adolescence is associated with poor sleep quality, anxiety, depression and low self-esteem. Journal of adolescence , 51 , 41-49.
•  Lee-Won, R. J., Herzog, L., & Park, S. G. (2015). Hooked on Facebook: The role of social anxiety and need for social assurance in problematic use of Facebook. Cyberpsychology, Behavior, and Social Networking , 18 (10), 567-574.
•  Levenson, J. C., Shensa, A., Sidani, J. E., Colditz, J. B., & Primack, B. A. (2016). The association between social media use and sleep disturbance among young adults. Preventive medicine , 85 , 36-41.
•  Sidani, Jaime E., Ariel Shensa, Beth Hoffman, Janel Hanmer, and Brian A. Primack. “The association between social media use and eating concerns among US young adults.” Journal of the Academy of Nutrition and Dietetics 116, no. 9 (2016): 1465-1472.
•  TikTok Revenue and Usage Statistics (2020). (2020, October 30). Retrieved from https://www.businessofapps.com/data/tik-tok-statistics/
• Dictionary by Merriam-Webster: America’s most-trusted online dictionary. (2020). Retrieved from https://www.merriam-webster.com/
•  Eranti, V., & Lonkila, M. (2015). The social significance of the Facebook Like button. First Monday , 20 .
•  Zara, C. (2019, December 18). How Facebook’s ‘like’ button hijacked our attention and broke the 2010s. Retrieved from https://www.fastcompany.com/90443108/how-facebooks-like-button-hijacked-our-attention-and-broke-the-2010s
•  Sherman, L. E., Payton, A. A., Hernandez, L. M., Greenfield, P. M., & Dapretto, M. (2016). The Power of the Like in Adolescence: Effects of Peer Influence on Neural and Behavioral Responses to Social Media. Psychological science , 27 (7), 1027–1035. https://doi.org/10.1177/0956797616645673
•  Burhan, R., & Moradzadeh, J. (2020). Neurotransmitter Dopamine (DA) and its Role in the Development of Social Media Addiction. Journal of Neurology , 11 (7), 507.
•  Ghose, T. (2015, January 27). What Facebook Addiction Looks Like in the Brain. Retrieved from https://www.livescience.com/49585-facebook-addiction-viewed-brain.html
• Flynn, Kerry, Kristina Monllos, Lara O’Reilly, and Seb Joseph. “Pitch Deck: TikTok Says Its 27m Users Open the App 8 Times a Day in the US.” Digiday . Published February 26, 2019. https://digiday.com/marketing/pitch-deck-how-tiktok-is-courting-u-s-ad-agencies/.
•  Csikszentmihalyi, M. (2002). Flow: The classic work on how to achieve happiness . Random House.
•  Montag, C., Lachmann, B., Herrlich, M., & Zweig, K. (2019). Addictive Features of Social Media/Messenger Platforms and Freemium Games against the Background of Psychological and Economic Theories. International journal of environmental research and public health , 16 (14), 2612. https://doi.org/10.3390/ijerph16142612
•  Meltzer, D. (2018, February 08). Why Short-Form Video Needs to Be Part of Your Content Strategy. Retrieved from https://www.entrepreneur.com/article/308684
•  Knowledge, V. I. (2019). The TikTok Strategy: Using AI Platforms to Take Over the World.
•  Liu, R. (2020, September 21). The psychology of why social media is so addictive [Web log post]. Retrieved from https://uxdesign.cc/the-psychology-of-why-social-media-is-so-addictive-67830266657d

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Mini review article, on the psychology of tiktok use: a first glimpse from empirical findings.

• 1 Department of Molecular Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany
• 2 The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
• 3 Faculty of Psychology, Tianjin Normal University, Academy of Psychology and Behavior, Tianjin, China
• 4 Department of Psychology, University of Toledo, Toledo, OH, United States
• 5 Department of Psychiatry, University of Toledo, Toledo, OH, United States

TikTok (in Chinese: DouYin; formerly known as musical.ly) currently represents one of the most successful Chinese social media applications in the world. Since its founding in September 2016, TikTok has seen widespread distribution, in particular, attracting young users to engage in viewing, creating, and commenting on “LipSync-Videos” on the app. Despite its success in terms of user numbers, psychological studies aiming at an understanding of TikTok use are scarce. This narrative review provides a comprehensive overview on the small empirical literature available thus far. In particular, insights from uses and gratification theory in the realm of TikTok are highlighted, and we also discuss aspects of the TikTok platform design. Given the many unexplored research questions related to TikTok use, it is high time to strengthen research efforts to better understand TikTok use and whether certain aspects of its use result in detrimental behavioral effects. In light of user characteristics of the TikTok platform, this research is highly relevant because TikTok users are often adolescents and therefore from a group of potentially vulnerable individuals.

Musical.ly was founded in September 2016 by Zhang Yiming. Beijing Bytedance Technology acquired the application musical.ly in November 2017 and renamed the app to TikTok. In a short time period, this application became the most successful app from Chinese origin in terms of global distribution ( 1 ). As of November 2020, 800 million monthly users have been reported 1 , and 738 million first-time installs in 2019 have been estimated 2 . TikTok use is allowed for those 13 years or older, but direct messaging between users is allowed only for those 16 or older (in order to protect young users from grooming) 3 . In China, the main users of TikTok are under 35 years old (81.68% (2)). Meanwhile, to protect children and adolescents from unsuitable content (such as smoking, drinking, or rude language), TikTok's engineers also developed a version of the app, which filters inappropriate content for young users ( 2 ). Of note, at the moment of writing, the app operates as TikTok on the global market and as DouYin on the Chinese market ( 3 ). Similarities and differences of the twin apps are further described with a content analysis by Sun et al. ( 4 ).

The TikTok application available for Android and Apple smartphones enables creation of short videos where users can perform playback-videos to diverse pop-songs, to name one very prominent feature of the platform. These so-called “LipSync-Videos” can be shared with other users, downloaded for non-commercial purposes, commented upon and of course attached with a “Like.” Not only are playback-videos uploaded on TikTok but also users view a large amount of video content. Users can also call out for “challenges,” where they define which performance should be created by many users. As a consequence, TikTok users imitate the content or interact with the original video.

As the large user numbers in a very short time-window demonstrate, TikTok not only represents a global phenomenon but also has been criticized with respect to data protection issues/privacy ( 5 , 6 ), spreading hate ( 7 ) and might serve as a platform engendering cyberbullying ( 8 , 9 ). Given the many young users of this platform (e.g., 81.68% of China users of Tiktok are under 35 years old—see above, and 32.5% of the US users are 19 years old and younger) 4 , it is of particular relevance to better understand the motivation to use TikTok, alongside related topics. Such an understanding might also be relevant because recent research suggests that TikTok can be a potent channel to inform young persons on health-relevant information ( 10 – 12 ), on official information release from the government ( 13 ), political discussions ( 14 ), tourism content ( 15 ), live online sales ( 16 ), and even educational content ( 17 ). There even have been video-posts analyzed in a scientific paper related to radiology ( 18 ). Clearly, young TikTok users are also confronted with harmful health content, including smoking of e-cigarettes ( 19 ). Moreover, the health information learned from TikTok videos often does not meet necessary standards—as is discussed in a paper on acne ( 20 ). Finally, there arises the problem that while creating content, children's/adolescent's private home bedrooms from which they create TikTok videos become visible to the world, posing privacy intrusions ( 21 ). The many obviously negative aspects of TikTok use are in itself important further research leads. From a psychological perspective, we take a different path with the present review and try to better understand why people use TikTok, who uses the platform, and also how people use TikTok.

Why do People Use TikTok?

This question can be answered from different perspectives. One perspective providing an initial answer and—likely being true for most social media services—has been put forward by Montag and Hegelich ( 22 ). Social media companies have created services being highly immersive, aiming to capture the attention of users as long as possible ( 23 ). As a result of a prolonged user stay, social media companies obtain deep insights into psychological features of their users ( 24 ), which can be used for microtargeting purposes ( 25 ). Such immersive platform design also likely drives users with certain characteristics into problematic social media use ( 26 ) or problematic TikTok use (addictive-like behavior), but this aspect relating to TikTok use is understudied. Nevertheless, reinforcement of TikTok usage is also very likely reached by design-elements such as “Likes” ( 27 ), personalized and endless content available ( 23 ). TikTok's “For You”-Page (the landing page) learns quickly via artificial intelligence what users like, which likely results in longer TikTok use than a user intended, which may cause smartphone TikTok-related addictive behavior ( 2 ). This said, these ideas put forward still need to be confirmed by empirical studies dealing exclusively with TikTok. In this realm, an interesting research piece recently investigated less studied variables such as first-person camera views, but also humor on key variables such as immersion and entertainment on the TikTok platform ( 28 ), again all of relevance to prolong user stay.

The other perspective one could choose to address why people use TikTok stems from uses and gratification theory ( 29 , 30 ). The simple idea of this highly influential theory is that use of certain media can result in gratification of a person's needs ( 30 ), and only if relevant needs of a person are gratified by particular media, users will continue media use—here digital platform or social media use.

A recent paper by Bucknell Bossen and Kottasz ( 31 ) provided insight that, in particular, gratification of entertainment/affective needs was the most relevant driver to understand a range of behaviors on TikTok, including passive consumption of content, but also creating content and interacting with others. In particular, the authors summarized that TikTok participation was motivated by needs to expand one's social network, seek fame, and express oneself creatively. Recent work by Omar and Dequan ( 32 ) also applied uses and gratification theory to better understand TikTok use. In their work, especially the need for escapism predicted TikTok content consumption, whereas self-expression was linked to both participating and producing behavior. A study by Shao and Lee ( 33 ) not only applied uses and gratification theory to understand TikTok use but also shed light on TikTok use satisfaction and the intention to further use TikTok. In line with findings from the already mentioned works, entertainment/information alongside communication and self-expression were discussed as relevant use motives (needs to be satisfied by TikTok use). Satisfaction with TikTok was investigated as a mediator between different motives to use TikTok and to continue TikTok use. We also mention recent work being unable to link TikTok use to well-being, whether in a positive or negative way ( 34 ). Finally, Wang et al. ( 35 ) underlined the overall relevance of uses and gratification theory to understand TikTok use and presented need variables in cognitive and affective domains as relevant to study, but also personal/social integration and relief of pressure. In this context, we also mention the view of Shao ( 2 ) who put forward that, in particular, young people use TikTok for positioning oneself in their peer group and to understand where he/she stands in the peer group. Thus, TikTok is also relevant for identity formation of young persons and obtaining feedback to oneself.

Further theories need to be mentioned, which can explain why people are using the TikTok platform: Social Impact Theory and Self-Determination Theory. To our knowledge, these theories have not been sufficiently addressed empirically so far with respect to TikTok use, but are well known to be of relevance to understand social media use in general and are therefore mentioned.

Clearly, an important driver of social media use can be power, hence, reaching out to many and influencing other persons ( 36 ). Here, the classic Social Impact Theory (SIT) by Latané ( 37 ) tries to understand how to best measure the impact of people on a single individual/individuals. This theory—originating in the pre-social-media-age—gained a lot of visibility with the rise of social media services because, in particular, in the age of filter bubbles, fake news, and misinformation campaigns ( 38 , 39 ), it is interesting to understand how individual users on social media are socially influenced by others, for instance, in the area of their (political) attitudes. The SIT postulates three highly relevant factors called strength, immediacy, and number (of sources) to predict such a social impact. Ultimately, applying this theory to better understand TikTok use also needs to take into account that users differ in terms of their active and passive use.

The Self-Determination Theory (SDT) has been proposed by Ryan and Deci ( 40 ) and belongs to the most influential motivation theories of human behavior. Hence, it clearly can also be used to explain why people are motivated to use a social media service ( 41 , 42 ). According to SDT, motivated behavior (here using TikTok) should be high, when such a platform enables users to feel competence, autonomy, and being connected with others. Design of the platform can help to trigger related psychological states (e.g., push notifications can trigger fear of missing out, hence, not being connected to significant others) ( 43 ); but clearly also, individual differences play a relevant role, and this should be discussed as the next important area in this work. As with the SIT, applying SDT to better understand TikTok use will also need to take into account different kinds of TikTok use. A sense of self-determination might rise to different levels, when users are actively or passively using TikTok—and this also represents an interesting research question.

Who Uses TikTok and Who Does Not?

The aforementioned statistics show that TikTok users are often young. Bucknell Bossen and Kottasz ( 31 ) illustrated that, in particular, young users are also those who seem to be particularly active on the platform, and thus share much information. Given that, in particular, young users often do not foresee consequences of self-disclosure, it is of high importance to better protect this vulnerable group from detrimental aspects of social media use. Beyond age, statistics suggest that more females than males use the platform 5 , something also observed with other platforms ( 44 – 46 ). First, insights from personality psychology provided further information on associations between characteristics of TikTok users and how they use it (see also the next How Do People Use TikTok? section): The widely applied Big Five Personality traits called openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism (acronym OCEAN) were all robustly linked to producing, participating, and consuming behavior on TikTok, with the exception of agreeableness only being linked to consuming behavior ( 32 ). Using a hierarchical regression model inserting both personality variables and motives from uses and gratification theory, it became apparent that the latter variables seemed to outweigh the personality variables in their importance to predict TikTok usage. Lu et al. ( 47 ) used data from China to investigate individual differences in DouYin (again the Chinese version of TikTok) use. Among others, they observed that people refraining from using DouYin did so out of fear of getting “addicted” to the application [see also ( 48 )]. This needs to be further systematically explored with the Big Five model of personality (or HEXACO, as the personality models dominating modern personality psychology at the moment). Without doubt, it will be also highly important to better understand how the variables of socio-demographics and personality interact on TikTok use, also in the realm of active/passive use of the platform. Active use would describe a high engagement toward the platform including commenting and uploading videos. Passive usage would reflect in browsing and simply consuming videos. The need to distinguish between active and passive use of social media has been also recently empirically supported by Peterka-Bonetta et al. ( 49 ).

How do People Use TikTok?

In the Why Do People Use TikTok? section, we already mentioned that users can passively view content, but also create content or interact with others. Studies comprehensively showing how many and which types of people use TikTok with respect to these behavioral categories are lacking (but TikTok likely has at least some of these insights). A recent review by Kross et al. ( 50 ) on “social media (use) and well-being” summarized that several psychological processes such as upward social comparison (perhaps also happening in so-called “challenges” on TikTok) or fear of missing out ( 43 ) are related to negative affect and might have detrimental effects on the usage experience and/or TikTok users' lives in general. Overall, the psychological impact of the TikTok platform might also be very likely, in particular, when adolescents often imitate their idols in “LipSync-Videos” ( 51 ). The kind of influence of such behavior on the development of one's own identity and self-esteem (self-confidence) ( 52 ) will be a matter of important psychological discussion, but it is too early to speculate further on potential psychological effects here, both in the positive or negative direction ( 53 ). Moreover, whether such effects will be of positive or negative nature, we mention the importance to not overpathologize everyday life behavior ( 54 ).

In sum, much of what we know with respect to platforms such as Instagram, Facebook, WhatsApp, or even WeChat ( 56 ) needs to still be investigated in the context of TikTok, to understand if psychological observations made for other social media channels can be transferred “one-on-one” to TikTok. For instance, illustrating differences between social media platforms, Bhandari and Bimo ( 57 ) suggested in their analysis of TikTok that in contrast to other platforms, “the crux of interaction is not between users and their social network, but between a user and what we call an ‘algorithmized’ version of self.” Opening TikTok immediately results in being captured by a personalized stream of videos. Therefore, we believe it to be unlikely that all insights from social media research can be easily transferred to TikTok because it is well-known that each social media platform has a unique design also attracting different user groups ( 45 ), and they elicit different immersive or “addictive” potential ( 58 ). Please note that we use the term “addictive” only in quotation marks, given the ongoing debate on the actual nature of excessive social media use ( 59 , 60 ). This said, we explicitly mention that the study of problematic social media use represents a very important topic ( 61 ), although at the moment, this condition—of relevance for the mental health sciences—is not officially recognized by the World Health Organization. Despite the ongoing controversy, nevertheless, it has been recently pointed out that social media companies are responsible for the well-being of users, too ( 55 ).

Conclusions and Outlook

Although user numbers are high and TikTok represents a highly successful social media platform around the globe, we know surprisingly less about psychological mechanisms related to TikTok use. Most research has been carried out so far yielding insights into user motives applying uses and gratification theory. Although this theory is of high importance to understand TikTok use, it is still rather broad and general. In particular, when studying a platform such as TikTok—receiving attention at the moment from a lot of young users—more specific needs or facets of the broad dimensions of uses and gratification theory (such as social usage) being more strongly related to the needs of adolescents might need more focus. One such focus could be a stronger emphasis on the study of self-esteem ( 62 ) in the context of TikTok use. Work beyond this area, e.g., investigating potential detrimental aspects, are scarce, but will be important. In particular, we deem this to be true, as TikTok attracts very young users, being more vulnerable to detrimental aspects of social media use ( 63 ). We believe that it is also high time for researchers to put research energy in the study of TikTok and to do so in a comprehensive manner. Among others, it needs also to be studied how active and passive use impact on the well-being of the users. This means that the here-discussed how-, why- , and who- questions need to be studied together in one framework, and this needs to be done against the data business model and its immersive platform design. The key ideas of this review to understand TikTok use and related aspects such as well-being of the users are presented in Figure 1 .

Figure 1 . In order to understand the relationship between a social media service such as TikTok and human psychological processes and behavior, one needs to answer the who-, why-, and how-questions, also against the background of the social media platform design. Please note that the platform design itself is driven by the data business model. Social media usage and its association with psychological/behavioral variables such as well-being, online-time, and so on can be best understood by investigating these variables in one model, at best also investigating potential interactions of variables. These ideas have also been described in parts in Montag and Hegelich ( 22 ), Kross et al. ( 50 ), and Montag et al. ( 55 ). The figure does not exclusively mention TikTok because we are convinced that the presented details are true for all research agendas aiming at a better understanding of the relationship between social media use and well-being.

Author Contributions

CM wrote the first draft of this review article. HY screened the Chinese literature and added relevant work from a Chinese perspective to the review. Finally, JDE critically worked over the complete draft. All authors agreed upon the final version of the article.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

1. ^ https://www.omnicoreagency.com/tiktok-statistics/ (accessed March 9, 2021).

2. ^ https://www.statista.com/statistics/1089420/tiktok-annual-first-time-installs/ (accessed March 9, 2021).

3. ^ https://www.heise.de/newsticker/meldung/Ab-16-TikTok-fuehrt-Mindestalter-fuer-Direktnachrichten-ein-4703887.html (accessed March 9, 2021).

4. ^ https://www.statista.com/statistics/1095186/tiktok-us-users-age/ (accessed March 9, 2021).

5. ^ https://www.statista.com/statistics/1095196/tiktok-us-age-gender-reach/ (accessed March 9, 2021).

1. Xiong Y, Ji Y. From content platform to relationship platform: analysis of the attribute change of Tiktok short video. View Publish. (2019) 4:29–34. (Citation has been translated from Chinese language.)

Google Scholar

2. Shao Z. Analysis of the characteristics, challenges and future development trends of Tik Tok. Mod Educ Tech. (2018) 12:81–7. (Citation has been translated from Chinese language.)

3. Kaye DBV, Chen X, Zeng J. The co-evolution of two Chinese mobile short video apps: Parallel platformization of Douyin and TikTok. Mobile Media Commun. (2020). doi: 10.1177/2050157920952120. [Epub ahead of print].

CrossRef Full Text | Google Scholar

4. Sun L, Zhang H, Zhang S, Luo J. Content-based analysis of the cultural differences between TikTok and Douyin. arXiv[Preprint].arXiv:2011.01414. (2020). Available online at: https://arxiv.org/pdf/2011.01414v1.pdf

5. Neyaz A, Kumar A, Krishnan S, Placker J, Liu Q. Security, privacy and steganographic analysis of FaceApp and TikTok. Int J Comp Sci Sec (IJCSS) . (2020) 14:38–59. Available online at: https://www.cscjournals.org/library/manuscriptinfo.php?mc=IJCSS-1552

6. Wang J. From Banning to Regulating TikTok: Addressing Concerns of National Security, Privacy, and Online Harms . (2020). Available online at: https://www.fljs.org/sites/www.fljs.org/files/publications/From%20Banning%20to%20Regulating%20TikTok.pdf

7. Weimann G, Masri N. Research note: spreading hate on TikTok. Stud Conf Terror. (2020) 20:1–14. doi: 10.1080/1057610X.2020.1780027

8. Anderson KE. Getting acquainted with social networks and apps: It is time to talk about TikTok. Library Hi Tech News. (2020) 37:7–12. doi: 10.1108/LHTN-01-2020-0001

9. Kumar VL, Goldstein MA. Cyberbullying and adolescents. Curr Pediatr Rep. (2020) 8:86–92. doi: 10.1007/s40124-020-00217-6

10. Basch CH, Hillyer GC, Jaime C. COVID-19 on TikTok: Harnessing an emerging social media platform to convey important public health messages. Int J Adolesc Med Health. (2020). doi: 10.1515/ijamh-2020-0111. [Epub ahead of print].

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Comp G, Dyer S, Gottlieb M. Is TikTok the next social media frontier for medicine? AEM Educ Train . (2020). doi: 10.1002/aet2.10532. [Epub ahead of print].

12. Ostrovsky AM, Chen JR. TikTok and its role in COVID-19 information propagation. J Adolesc Health. (2020) 67:730. doi: 10.1016/j.jadohealth.2020.07.039

13. Jiang J, Wang W. Research on Government Douyin for public opinion of public emergencies: comparison with government microblog. J Intellig. (2020) 39:100–106. (Citation has been translated from Chinese language.)

14. Medina Serrano JC, Papakyriakopoulos O, Hegelich S. Dancing to the Partisan Beat: a first analysis of political communication on TikTok. In: 12th ACM Conference on Web Science . (2020). p. 257–266. doi: 10.1145/3394231.3397916

15. Du X, Liechty T, Santos CA, Park J. ‘I want to record and share my wonderful journey’: Chinese Millennials' production and sharing of short-form travel videos on TikTok or Douyin. Curr Issues Tour. (2020) 20:1–13. doi: 10.1080/13683500.2020.1810212

16. Li L, Gao S. TikTok marketing strategies from the perspective of audience psychology. J Xiamen Univer Technol. (2020) 28:18–23. (Citation has been translated from Chinese language.)

17. Hayes C, Stott K, Lamb KJ, Hurst GA. “Making every second count”: utilizing TikTok and systems thinking to facilitate scientific public engagement and contextualization of chemistry at home. J Chem Educ. (2020) 97:3858–66. doi: 10.1021/acs.jchemed.0c00511

18. Lovett JT, Munawar K, Mohammed S, Prabhu V. Radiology content on TikTok: current use of a novel video-based social media platform and opportunities for radiology. Curr Prob Diag Radiol . (2021) 50, 126–31. doi: 10.1067/j.cpradiol.2020.10.004

19. Tan ASL, Weinreich E. #PuffBar: How do top videos on TikTok portray Puff Bars? Tobacco Control . doi: 10.1136/tobaccocontrol-2020-055970

20. Zheng DX, Ning AY, Levoska MA, Xiang L, Wong C, Scott JF. Acne and social media: a cross-sectional study of content quality on TikTok. Pediatr Derm . (2020). doi: 10.1111/pde.14471. [Epub ahead of print].

21. Kennedy M. ‘If the rise of the TikTok dance and e-girl aesthetic has taught us anything, it's that teenage girls rule the internet right now’: TikTok celebrity, girls and the Coronavirus crisis. Eur J Cult Stud. (2020) 23:1069–76. doi: 10.1177/1367549420945341

22. Montag C, Hegelich S. Understanding detrimental aspects of social media use: will the real culprits please stand up? Front Sociol . (2020) 5:94. doi: 10.3389/fsoc.2020.599270

23. Montag C, Lachmann B, Herrlich M, Zweig K. Addictive features of social media/messenger platforms and freemium games against the background of psychological and economic theories. Int J Environ Res Public Health. (2019) 16:2612. doi: 10.3390/ijerph16142612

24. Marengo D, Montag C. Digital phenotyping of big five personality via Facebook data mining: a meta-analysis. Dig Psychol. (2020) 1:52–64. doi: 10.24989/dp.v1i1.1823

25. Matz SC, Kosinski M, Nave G, Stillwell DJ. Psychological targeting as an effective approach to digital mass persuasion. Proc Natl Acad Sci USA. (2017) 114:12714–9. doi: 10.1073/pnas.1710966114

26. Sindermann C, Elhai JD, Montag C. Predicting tendencies towards the disordered use of Facebook's social media platforms: On the role of personality, impulsivity, social anxiety. Psychiatry Res. (2020) 285:112793. doi: 10.1016/j.psychres.2020.112793

27. Marengo D, Montag C, Sindermann C, Elhai JD, Settanni M. Examining the Links between Active Facebook Use, Received Likes, Self-Esteem and Happiness: A Study using Objective Social Media Data. Telem Inform. (2020) 10:1523. doi: 10.1016/j.tele.2020.101523

28. Wang Y. Humor and camera view on mobile short-form video apps influence user experience and technology-adoption intent, an example of TikTok (DouYin). Comp Hum Behav. (2020) 110:106373. doi: 10.1016/j.chb.2020.106373

29. Ahlse J, Nilsson F, Sandström N. It's Time to TikTok: Exploring Generation Z's Motivations to Participate in #Challenges . (2020). Available online at: http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-48708

30. Katz E, Blumler JG, Gurevitch M. Uses and gratifications research. Public Opin Q. (1973) 37:509–23.

31. Bucknell Bossen C, Kottasz R. Uses and gratifications sought by pre-adolescent and adolescent TikTok consumers. Young Cons. (2020) 21:463–78. doi: 10.1108/YC-07-2020-1186

32. Omar B, Dequan W. Watch, Share or Create: The Influence of Personality Traits and User Motivation on TikTok Mobile Video Usage . International Association of Online Engineering. (2020). Available online at: https://www.learntechlib.org/p/216454/

33. Shao J, Lee S. The effect of chinese adolescents' motivation to use Tiktok on satisfaction and continuous use intention. J Converg Cult Technol. (2020) 6:107–15. doi: 10.17703/JCCT.2020.6.2.107

34. Masciantonio A, Bourguignon D, Bouchat P, Balty M, Rimé B. Don't put all social network sites in one basket: Facebook, Instagram, Twitter, TikTok, and their relations with well-being during the COVID-19 pandemic. PsyArXiv . (2020). doi: 10.31234/osf.io/82bgt

35. Wang Y, Gu T, Wang S. Causes and characteristics of short video platform internet community taking the TikTok short video application as an example. In: 2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW) Yilan. (2019). p. 1–2. doi: 10.1109/ICCE-TW46550.2019.8992021

36. Sariyska R, Lachmann B, Cheng C, Gnisci A, Sergi I, Pace A, et al. The motivation for Facebook use – is it a matter of bonding or control over others? J Individ Differ. (2018) 40:26–35. doi: 10.1027/1614-0001/a000273

37. Latané B. The psychology of social impact. Am Psychol. (1981) 36:343–56. doi: 10.1037/0003-066X.36.4.343

38. Sindermann C, Cooper A, Montag C. A short review on susceptibility to falling for fake political news. Curr Opin Psychol. (2020) 36:44–8. doi: 10.1016/j.copsyc.2020.03.014

39. Sindermann C, Elhai JD, Moshagen M, Montag C. Age, gender, personality, ideological attitudes and individual differences in a person's news spectrum: How many and who might be prone to “filter bubbles” and “echo chambers” online? Heliyon. (2020) 6:e03214. doi: 10.1016/j.heliyon.2020.e03214

40. Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. (2000) 55:68–78. doi: 10.1037/0003-066X.55.1.68

41. Ferguson R, Gutberg J, Schattke K, Paulin M, Jost N. Self-determination theory, social media and charitable causes: An in-depth analysis of autonomous motivation. Eur J Soc Psychol. (2015) 45:298–307. doi: 10.1002/ejsp.2038

42. Miller LM, Prior DD. Online social networks and friending behaviour: A self-determination theory perspective. In: ANZMAC 2010: Proceedings : Doing More with Less. Australian and New Zealand Marketing Academy Conference . (2010). Available online at: https://researchers.mq.edu.au/en/publications/online-social-networks-and-friending-behaviour-a-self-determinati

43. Elhai JD, Yang H, Montag C, Elhai JD, Yang H, Montag C. Fear of missing out (FOMO): overview, theoretical underpinnings, and literature review on relations with severity of negative affectivity and problematic technology use. Brazil J Psychiatry. (2020). doi: 10.1590/1516-4446-2020-0870. [Epub ahead of print].

44. Chen Q, Hu Y. Users' self-awareness in TikTok's viewing context. J Res. (2020) 169:79–96. (Citation has been translated from Chinese language.)

45. Marengo D, Sindermann C, Elhai JD, Montag C. One social media company to rule them all: associations between use of Facebook-owned social media platforms, sociodemographic characteristics, and the big five personality traits. Front. Psychol. (2020) 11:936. doi: 10.3389/fpsyg.2020.00936

46. Montag C, Błaszkiewicz K, Sariyska R, Lachmann B, Andone I, Trendafilov B, et al. Smartphone usage in the 21st century: who is active on WhatsApp? BMC Res Notes. (2015) 8:331. doi: 10.1186/s13104-015-1280-z

47. Lu X, Lu Z, Liu C. Exploring TikTok use and non-use practices and experiences in China. In: Meiselwitz G, editor. Social Computing and Social Media. Participation, User Experience, Consumer Experience, and Applications of Social Computing . Springer International Publishing (2020).p. 57–70. doi: 10.1007/978-3-030-49576-3_5

48. Gu X. College students' short videos production and dissemination in the we-media era. J Anshan Nor Univer. (2020) 22:60–62. (Citation has been translated from Chinese language.)

49. Peterka-Bonetta J, Sindermann C, Elhai JD, Montag C. How objectively measured twitter and instagram use relate to self-reported personality and tendencies towards internet use/smartphone use disorder. Hum Behav Emer Technol. (2021). doi: 10.1002/hbe2.243. [Epub ahead of print].

50. Kross E, Verduyn P, Sheppes G, Costello CK, Jonides J, Ybarra O. Social media and well-being: Pitfalls, progress, next steps. Trends Cogn Sci. (2021) 25:55–66. doi: 10.1016/j.tics.2020.10.005

51. Kumar VD, Prabha MS. Getting glued to TikTok ® – Undermining the psychology behind widespread inclination toward dub-mashed videos. Arch Mental Health. (2019) 20:76. doi: 10.4103/AMH.AMH_7_19

52. Palupi ND, Meifilina A, Harumike YDN. The effect of using Tiktok applications on self-confidence levels. J Stud Acad Res. (2020) 5:66–74. doi: 10.35457/josar.v5i2.1151

53. Wang J, Li H. Reflections on the popularity of Tiktok on University Campus and behavioral guidance. Soc Sci J. (2020) 32:60–64. (Citation has been translated from Chinese language.)

54. Billieux J, Schimmenti A, Khazaal Y, Maurage P, Heeren A. Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research. J Behav Addic. (2015) 4:119–23. doi: 10.1556/2006.4.2015.009

55. Montag C, Hegelich S, Sindermann C, Rozgonjuk D, Marengo D. On corporate responsibility when studying social-media-use and well-being. Trends Cogn Sci. (2021). doi: 10.1016/j.tics.2021.01.002

56. Montag C, Becker B, Gan C. The multipurpose application WeChat: a review on recent research. Front Psychol. (2018) 9:2247. doi: 10.3389/fpsyg.2018.02247

57. Bhandari A, Bimo S. Tiktok And The “Algorithmized Self”: A New Model Of Online Interaction . AoIR Selected Papers of Internet Research. (2020). doi: 10.5210/spir.v2020i0.11172. Available online at: https://journals.uic.edu/ojs/index.php/spir/article/view/11172

58. Rozgonjuk D, Sindermann C, Elhai JD, Montag C. Comparing smartphone, WhatsApp, Facebook, Instagram, and Snapchat: which platform elicits the greatest use disorder symptoms? Cyberpsychol Behav Soc Netw . (2020). doi: 10.1089/cyber.2020.0156. [Epub ahead of print].

59. Carbonell X, Panova T. A critical consideration of social networking sites' addiction potential. Addic Res Theor. (2017) 25:48–57. doi: 10.1080/16066359.2016.1197915

60. Montag C, Wegmann E, Sariyska R, Demetrovics Z, Brand M. How to overcome taxonomical problems in the study of Internet use disorders and what to do with “smartphone addiction”? J Behav Addic . (2021) 9:908–14. doi: 10.1556/2006.8.2019.59

61. Schivinski B, Brzozowska-Wo,ś M, Stansbury E, Satel J, Montag C, Pontes HM. Exploring the role of social media use motives, psychological well-being, self-esteem, and affect in problematic social media use. Front Psychol. (2020) 11:617140. doi: 10.3389/fpsyg.2020.617140

62. Bos AER, Muris P, Mulkens S, Schaalma HP. Changing self-esteem in children and adolescents: a roadmap for future interventions. J Psychol. (2006) 62:26–33. doi: 10.1007/BF03061048

63. Best P, Manktelow R, Taylor B. Online communication, social media and adolescent wellbeing: A systematic narrative review. Child Youth Serv Rev. (2014) 41:27–36. doi: 10.1016/j.childyouth.2014.03.001

Keywords: TikTok, DouYin, musical.ly, personality, uses and gratification, social media, social media addiction, problematic social media use

Citation: Montag C, Yang H and Elhai JD (2021) On the Psychology of TikTok Use: A First Glimpse From Empirical Findings. Front. Public Health 9:641673. doi: 10.3389/fpubh.2021.641673

Received: 14 December 2020; Accepted: 18 January 2021; Published: 16 March 2021.

Reviewed by:

Copyright © 2021 Montag, Yang and Elhai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Christian Montag, christian.montag@uni-ulm.de

This article is part of the Research Topic

Adverse Health Consequences of Excessive Smartphone Usage

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Research on Adolescents Regarding the Indirect Effect of Depression, Anxiety, and Stress between TikTok Use Disorder and Memory Loss

Associated data.

The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.

This research involved the participation of 3036 Chinese students in the first and second years of senior high school. The adolescents were active users of TikTok. The mediating effect of depression, anxiety, and stress between TikTok use disorder and memory loss was investigated. A forward and backward digit span test was applied to measure memory loss. Structural equation modeling (SEM) was established, and SPSS Amos was used for analysis. The results show a partial mediation effect of depression and anxiety between TikTok use disorder and forward digit span. A partial mediation effect of depression, anxiety, and stress between TikTok use disorder and backward digit span is also shown. These results also show gender differences. Attention should be given to male students, who have more depression, anxiety, and stress than female students; they also have more memory loss.

1. Introduction

1.1. internet, smartphone, or tiktok use disorder.

The concept of “non-chemical addiction” was introduced in 1990 [ 1 ]. At that time, engaging in excessive online activities such as online sex and Internet games was initially called Internet addiction [ 2 ]. In 1990, only about 250 behavioral addiction papers were published, while in 2013, 2563 papers were published. General information, social networking, email, chat, videos, and films were reported to be the most popular online activities of Internet users [ 3 ]. Internet use disorder has a strongly negative influence on normal psychological development, and it can lead to syndromes such as stress [ 4 ]. Some researchers have investigated Internet communication in terms of the use of social networking sites such as WhatsApp and Facebook [ 5 , 6 ]. Easy access to the Internet with smartphones increased the popularity of social networks [ 7 ]. Very early research on the addictive use of the Internet was published in 1996 [ 8 ]. Many researchers prefer to use the term “Internet use disorder” [ 5 , 9 ] or “smartphone use disorder” [ 10 , 11 , 12 ], instead of “addiction”; however, these terms have still not been accepted by ICD-11 or DSM-5 [ 13 ].

TikTok is the most popular smartphone application of Chinese origin in the world. The total number of active TikTok users worldwide is 1.5 billion, and most of them are teenagers [ 14 ]. According to a report at the end of 2020, the number of monthly active TikTok users worldwide was 800 million. About 81% of Chinese users were young people under 35 years old [ 15 ]. The gratification of entertainment is the main driver for TikTok users. Adolescent groups are more active on the application because of their identity-creation and social contact needs [ 16 ]. Some researchers have indicated that self-expression and use satisfaction are associated with the motivations of TikTok users [ 17 ].

1.2. Internet or Smartphone Use Disorder and Depression, Anxiety, and Stress

According to a report by the WHO [ 18 ], the prevalence of depression and anxiety was 4.4% and 3.6%, respectively. Generally, females have a higher prevalence of depression and anxiety than males. In adolescence, the prevalence of depression and anxiety reaches the highest point [ 19 ]. Junior high school students, because of the high academic pressure and their monotonous life, are vulnerable to mental health problems such as depression [ 20 ].

Depression and social anxiety in junior high school students can be used as a mediator to explain the relationship between Internet use disorder and maladaptive cognition [ 21 ]. In research on adolescents [ 22 ], stress was highly associated with social anxiety. Social anxiety can act as a mediator between Internet use disorder and stress. Research on junior college students with an average age of 17 years [ 23 ] investigated the relationship between problematic Internet use, depression, anxiety, and stress. The more problematic the Internet use, the heavier the depression, anxiety, or stress. Moreover, depression, anxiety, and stress were positively associated with each other.

The relationship between anxiety, depression, and smartphone use disorder has been researched [ 24 ]. Depression and anxiety were shown to be highly correlated, and a positive correlation was found between anxiety and smartphone use disorder, but not between depression and smartphone use disorder. Some studies [ 25 , 26 , 27 , 28 , 29 ] showed that the use of social networking sites was positively linked to depression. However, other studies [ 30 ] showed that there was no correlation between the use of social networking sites and depression. Between users and non-users of Facebook, no differences were found with regard to depression, anxiety, and stress [ 31 ]. Internet use expectancies and dysfunctional cognition, such as suppression, maladaptive problem-solving, and avoidance, can be regarded as mediators between Internet use disorder and psychopathological aspects such as depression and social anxiety [ 32 ].

1.3. Depression, Anxiety, Stress, and Working Memory Capacity

The influence of depression on memory has been researched [ 33 ]. In this research, the influence of depression on memory varied by age and gender. The relationship between anxiety and working memory capacity, as an element of fluid cognition, has been researched [ 34 ]. The causal pathways from anxiety to low working memory were established. Furthermore, low working memory was found to have an effect on cognitive vulnerability, which has a feedback effect on anxiety. The relationship between anxiety, working memory, and gender has been researched [ 35 ]. State anxiety was found to vary by gender. However, a gender effect on trait anxiety was not found. Visual working memory was positively linked to math anxiety. However, there was no significant correlation between visual working memory and state anxiety or trait anxiety. A positive correlation between anxiety and stress was found [ 36 ]. Both anxiety and stress were negatively linked to visuospatial working memory, but they were not linked to verbal working memory, although there was a strong correlation between visuospatial and verbal working memory. The relationship between stress and working memory capacity has been researched [ 37 ]. Stress was found to be negatively linked to working memory. However, a correlation between state anxiety and working memory was not found. Some researchers [ 38 ] found a correlation between depression, anxiety, and working memory capacity, but found that situational stress had no influence on working memory capacity.

A correlation between forward and backward digit span was reported. Difficulties with forward and backward digit span in children were linked to learning disorders [ 39 ]. Brener [ 40 ] conducted an experimental investigation of memory span, including a list of materials with increasing difficulty. Digit span had a lower difficulty level than consonants, colors, and words. The influence of depression on reading span and word span has been researched [ 41 ]. A lower capacity of reading and word span by depressed patients was shown, and reading span was shorter than word span for both depressed and non-depressed persons. Digit span as a subtest of WAIS-IV was used to search its relationship with depression and anxiety. However, no significant correlation was found in this study [ 42 ]. Some researchers [ 43 ] did not find any correlations between forward or backward digit span and state anxiety, trait anxiety, or stress.

1.4. Internet or Smartphone Use Disorder and Working Memory Capacity

Correlations between use disorder, smartphone use disorder, and working memory have been researched [ 44 ]. Smartphone use disorder was found to be highly linked with Internet use disorder. Both Internet and smartphone use disorder were found to be negatively linked with working memory. The correlation between smartphone use disorder and working memory was found to be stronger than the correlation between Internet use disorder and working memory. However, this research did not find a gender effect on Internet or smartphone use disorder and working memory capacity. The mediating effect of depression, anxiety, and stress between problematic social media use and memory capacity was researched [ 45 ]. In this research, the Memory Awareness Rating Scale (MARS-MPS) was used to evaluate memory performance. The PROCESS macro in SPSS was used to analyze the pathways. This study was based on adults with an average age of about 30, and there were 466 valid participants. The results showed that only anxiety had a partial mediating effect between problematic social media use and memory performance.

1.5. Hypotheses

In this present study, the hypotheses are as follows ( Figure 1 ):

Structural model of hypotheses.

TikTok use disorder (TTUD) is positively linked to memory loss.

TTUD is positively linked to depression, anxiety, and stress.

Depression, anxiety, and stress are positively linked to memory loss.

Depression, anxiety, and stress have a mediating effect between TTUD and memory loss.

2. Materials and Methods

2.1. participants.

The participants in the study were 3036 Chinese students in the first and second year of senior high school. Their participation was voluntary and anonymous ( Table 1 ).

Participants’ information.

2.2. Measurement Instruments

The Smartphone Addiction Scale, Short Version (SAS-SV) [ 46 ] was used in this study. TTUD was adapted from the SAS-SV, in which “smartphone” was changed to “TikTok”. This questionnaire consists of 10 items, rated on a 6-point Likert-type scale, ranging from “strongly disagree” coded as 1, to “strongly agree” coded as 6. Higher scores indicate a higher risk of TikTok use disorder. In this study, the Cronbach’s alpha coefficient of TTUD was 0.91.

The Depression Anxiety Stress Scales 21 (DASS-21) [ 47 , 48 ] was used in this study. This questionnaire consists of 21 items rated on 4-point Likert scale, from 0 for “did not apply to me at all” to 3 for “applied to me very much”. Groups of 7 items are used to measure depression, anxiety, and stress. Higher scores indicate more severe symptoms. Cronbach’s alpha of depression was 0.88, anxiety was 0.86, and stress was 0.87.

Forward and backward digit spans were tested to measure memory loss. A number was given at random, beginning with a 2-digit number. The digits were increased until a wrong answer was given. A number was not repeated until a 10-digit number was reached; for example, 112 or 121, in which 1 was repeated, would not happen. The result was regarded as valid for the forward digit span test when the answer was a 3-digit to 11-digit number, and for the backward digit span test when the answer was a 2-digit to a 9-digit number.

2.3. Statistic Software

For this study, SPSS Amos 24.0 and SPSS 26.0 (IBM: New York, NY, USA) were used.

Descriptive information divided by gender is shown in Table 2 .

Descriptive statistics divided by gender.

TTUD, TikTok use disorder; DSF, forward digit span; DSB, backward digit span.

Pearson’s correlations between the research variables are shown in Table 3 .

Pearson’s correlations between research variables.

** p < 0.01.

The results of pathway analysis are shown directly in Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 and Figure 7 . First, the results of forward and backward digit span tests of all participants, male and female, were calculated ( Figure 2 and Figure 3 ). Second, the tests of male participants were calculated ( Figure 4 and Figure 5 ). Finally, the tests of female participants were calculated ( Figure 6 and Figure 7 ). Pathway coefficients shown in the figures are unstandardized.

Structural model of forward digit span test for male and female participants. TTUD, TikTok use disorder; DSF, forward digit span. *** p < 0.001.

Structural model of backward digit span test for male and female participants. DSB, backward digit span. ** p < 0.01, *** p < 0.001.

Structural model of forward digit span test for male participants. ** p < 0.01, *** p < 0.001.

Structural model of backward digit span test for male participants. ** p < 0.01, *** p < 0.001.

Structural model of forward digit span test for female participants. ** p < 0.01, *** p < 0.001.

Structural model of backward digit span test for female participants. * p < 0.05, *** p < 0.001.

For all participants, male and female, based on the forward digit span test, depression and anxiety have a partial mediating effect between TTUD and forward digit span memory capacity. Based on the backward digit span test, depression, anxiety, and stress have a partial mediating effect between TTUD and backward digit span memory capacity. For male participants, based on both types of digit span tests, only depression and anxiety showed partial mediating effects. For female participants, the partial mediating effects were the same as for all participants.

The criteria for good model fit were as follows: Chi-square/df < 5, RMSEA < 0.08, CFI > 0.95, and TLI > 0.95 [ 49 ]. Model fit information of the structural models in this study is shown in Table 4 .

Model fit information.

4. Discussion

This study was aimed at examining the mediating effect of depression, anxiety, and stress between TTUD and memory loss, focused on adolescents and divided by gender. TTUD was higher for female participants than male participants. This was the same as in early research on smartphone use disorder [ 12 ]. TTUD is positively linked with memory loss (H1). The greater the memory loss, the smaller the digit span. This result is gender independent. In this study, male participants showed more depression, anxiety, and stress than female participants. Kessler [ 50 ] indicated that throughout the lifespan, the prevalence of depression and anxiety in women is 1.5 times higher than in men. Taking a closer look at the gender effect on these symptoms, it did not differ between these results. This study was cross-sectional; prevalence throughout the lifespan was totally independent.

Some researchers have indicated that the gender effect could vary by factors such as age [ 51 ], anamnesis [ 52 ], or other mediating effects [ 53 ]. Gao [ 54 ] investigated college students and found no significant difference in depression or stress in first-year students and no significant difference in depression, anxiety, or stress in third-year students of different genders. TTUD is positively linked to depression, anxiety, and stress (H2). This result agrees with those of other researchers [ 23 ]. Depression, anxiety, and stress are positively linked to memory loss (H3). However, this hypothesis was not proven with regard to stress on the forward digit span test; it was proven with the backward digit span test, except for stress on male participants. Depression, anxiety, and stress have a mediating effect between TTUD and memory loss (H4). The partial mediating effect of depression and anxiety was proven with the forward digit span test, and stress had no mediating effect. However, with the backward digit span test, all three symptoms had a partial mediating effect, except for stress on male participants.

This research investigated a homogeneous group of participants from a normal senior high school in China. This sample was not representative of all adolescents. Generalizing the results will depend on further research. However, attention should be given to male students at senior high schools in China. Although their TTUD scores were lower than those of female students, they suffered more depression, anxiety and stress and had more memory loss than female students. For further studies, longitudinal research would be interesting. Because of the limitation of the cross-sectional design, a conclusion could not be made, as the more severe memory loss in male students resulted from the additional depression, anxiety, and stress they suffered. Furthermore, due to the cross-sectional study design, causal relationships between research variables could not be determined. To determine causal relationships, more information or more research would be needed. Some researchers [ 6 ] regarded depression, anxiety, and stress as independent variables and Internet use disorder as the dependent variable. The effects within or causal relationships between these variables may be reciprocal.

5. Conclusions

TikTok use disorder (TTUD) is positively linked to memory loss, and it is also positively linked to depression, anxiety, and stress. Depression, anxiety, and stress are positively linked to memory loss. Furthermore, depression, anxiety, and stress have a mediating effect between TTUD and memory loss.

A partial mediation effect of depression and anxiety between TTUD and forward digit span is shown. A partial mediation effect of depression, anxiety, and stress between TTUD and backward digit span is also shown. These results also show gender differences. Attention should be given to male students, who have more depression, anxiety, and stress than female students; they also have more memory loss.

Author Contributions

Conceptualization, analysis, investigation, writing, P.S.; supervision, X.D. All authors have read and agreed to the published version of the manuscript.

This research was funded by China Postdoctoral Science Foundation, special funded project: 2019T120799.

Institutional Review Board Statement

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Ethics committee of School of Journalism and Communication, Southwest University (Project identification code: 2019-01-21-sha).

Informed Consent Statement

Informed consent was received from all the authors and participants before research and publication.

Data Availability Statement

Conflicts of interest.

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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TikTok Addiction Behaviour Among Users: A Conceptual Model and Research Propositions

Social media addiction has become a serious problem and deserve urgent attention. TikTok, one of the emerging social media platforms, has gained popularity among social media users and scholars anticipate that the phenomenon of TikTok addiction is expanding especially among adolescents. Despite this alarming concern, less research attention has been paid to the dark side of TikTok compulsive behaviour. The present article aims to propose a conceptual model to depict the external and internal factors determining addiction behaviour among young users of TikTok. We propose a causal-chain framework originated from the Stimuli-Organism-Response (SOR) paradigm to delineate the role of information quality and system quality (i.e.: the external factors as the stimuli), and flow experience (i.e.: the internal factors as organism) in explaining TikTok addiction behaviour (as the response). By adopting SOR framework and employing the flow theory as a guide, this study develops a conceptual model of TikTok addiction behaviour. The model posits that users experience with the system leads to TikTok addiction behaviour. This article contributes to our understanding of TikTok addiction among adolescence and suggests possible solutions to curb this prevailing social problem in society. Theoretical and managerial implications are subsequently discussed in light of the conclusion.

Keywords: TikTok , information system , flow , addiction behaviour

Introduction

With the development of technology, short-form video media has gradually become a new favourite of people, which has dramatically changed the way people communicate and interact ( Ngai et al., 2015 ). TikTok, known as Douyin in China, has 1.5 billion active users so far, and downloaded more than 1 billion times around the world, and is already ahead of competitors like Netflix, YouTube, Snapchat and Facebook ( Omar & Dequan, 2020 ; Weimann & Masri, 2020 ).

TikTok is also the most popular social media platform among millennials in China ( Jung & Zhou, 2019 ). The characteristics of younger group users is short attention span and easily to get immersed in the content they like. According to the features and preferences of this age group, designers build a special algorithm (Feed for You) to customize video content for each user ( Figliola, 2020 ).

When adolescent user exposed with more and more matched content, they will extend the using time, and immersed in TikTok. According to statistics, active TikTok users open the app 8 times per day on average, about 22% of TikTok users use the app for more than an hour a day ( Iqbal, 2020 ). During the COVID-19 outbreak globally, Chinese government has implemented the lockdown. people stay at home without going outside, the average time spent per day by TikTok users rose to 122.3 minutes, that's almost double the 68.8 minutes recorded in 2019, and the number of daily active users increased by 19.4% during the period ( Iqbal, 2020 ) and most of them were active between 9 p.m. and 12 a.m., when about 26.3 percent of its users are online ( Mou, 2020 ).

Problem Statement

But excessive immersion leads to users' attachment and addiction to social media ( Cao et al., 2020 ; Weimann & Masri, 2020 ), it then caused depression, anxiety, insomnia, poor eyesight, academic problem, low work performance, etc. ( Beyens et al., 2016 ; Enez Darcin et al., 2016 ; Fu et al., 2020 ; Weinstein & Lejoyeux, 2010 ). These adverse outcomes are well-known indicators of addiction ( Gao et al., 2017 ).

Thus, similar to Facebook addiction, short-form video app addiction may be another sub-category of Internet addiction ( Zhang et al., 2019 ). Some scholars believe that the phenomenon of TikTok addiction is expanding ( Zhang et al., 2019 ).

The existing literature on social media use behaviour, while very commendable, most of the researches only considered single factors such as the technology characteristic ( Rahi et al., 2020 ), website design quality ( Ma et al., 2019 ), perceived usefulness and perceived ease of use ( Ifinedo, 2018 ), IS quality ( Idemudia et al., 2018 ), satisfaction and attitude ( Zhang et al., 2016 ), the user personality ( Omar & Dequan, 2020 ), cognitive factors ( Liao et al., 2009 ), etc.,. In addition, when explaining social media use behaviour, they over-rely on use and gratification theory (U&G), theory of planed behaviour (TPB), technology continuance theory (TCT) and expectation conformation theory (ECM) models and other models. Further research needs to combine both media factors (external factors) and user factors (internal factors) to comprehensively investigate user behaviour.

Research Questions

This research is guided by the following research questions:

RQ1: How do the external factors (information quality and system quality) affect internal factors (flow experience)?

RQ2: Do internal factors (flow experience) have a significant effect on the TikTok addiction behaviour?

RQ3: Do internal factors (flow experience) mediate the effect between external factors and TikTok addiction behaviour?

Purpose of Statement

The current conceptual paper aims to develop theoretical framework by proposing the relationship between information quality, system quality, flow, and addictive behaviour. More importantly, to support theoretical framework, two theories were employed including SOR and flow theory. Because So far, there is no comprehensive effort to integrate the factors that induce users to use social media into a single model. This requires further research to develop a wholistic cause and chain framework to help gain more explanatory power and illuminate social media use behaviour.

Literature Review and propositions development

Current research on the short-form video app TikTok has focused on user adoption ( Omar & Dequan, 2020 ), and the business and social value created (such as job opportunity) ( Hu, 2020 ; Xu et al., 2019 ). Recently, scholars have gradually begun to use SOR to explain user behaviour through the combination of internal and external factors, but most studies focus on its negative consequences, like depression, anxiety, insomnia, poor vision, academic problems, low job performance ( Cao & Sun, 2018 ; Fu et al., 2020 ; Luqman et al., 2017, 2020; Moqbel, 2020 ; Whelan et al., 2020 ).

Despite SOR contributes the body of literature on addiction behaviour, the researchers believe that it still ignores the formation of addictive behaviour. To explore the factors of TikTok addictive behaviour in the emerging short-form video medium, SOR model was adopted in this study, and IS model and flow theory were integrated into SOR to develop a comprehensive theoretical framework and expand our understanding of adolescent TikTok addictive behaviour. Drawing on these theories, the conceptual framework of this paper will be reviewed and propositions.

The SOR model, also known as the environmental psychological model, was developed by Mehrabian and Russell ( 1974 ). In the SOR framework, it is assumed that environmental cues would stimulate individual’s emotional and cognitive state, which leads to certain behavioural ( Lee et al., 2018 ; Mehrabian & Russell, 1974 ).

As a meta-theory to explain human behaviour process, SOR is used to predict the cognitive judgment and subsequent behaviour or intention of network users. The model has been successfully used to explain consumer behaviours, social media applications, virtual experiences, gamification studies ( Cho et al., 2019 ; Kamboj et al., 2018 ; Sun et al., 2018 ; Triantoro et al., 2019 ; Xu et al., 2019 ). It can explain the internal psychological change and interruption response of individuals when they face the environmental stimulus produced by media. For example, both technological environments and virtual psychological experiences have significant effects on the behaviour of social network users ( Luqman et al., 2017 ). Short-form video applications have a lot in common with social media and SNS. However, as an emerging platform, the current research is still in the initial stage, and we could borrow the theoretical framework from social media research.

Stimuli: External factors: IS mode

In the SOR framework, a stimulus refers to "the environment that an individual encounter ( Mehrabian & Russell, 1974 ). In previous studies, the technical aspects of virtual space have been treated as environmental stimuli ( Animesh et al., 2011 ; Zhang et al., 2015 ). A study in the field of information systems (IS) used this framework to explain how information technology attributes relate to the user's internal state and subsequent adoption behaviour ( Benlian, 2015 ). Application quality is divided into information quality and system quality ( Almahamid et al., 2016 ), this site quality structure is a major factor in assessing site users' expectations and perceptions of site quality ( DeLone & McLean, 2003 ; Liang & Chen, 2009 ).

Information Quality

Information quality refers to the accuracy, completeness, and freshness of website content, which IS the user's evaluation of IS's performance in providing information based on their experience in using the system ( McKinney et al., 2002 ). It reflects the relevance, timeliness and adequacy of the information provided by the platform ( Kim et al., 2003 ). This assessment is based on the content of the IS website and needs to be personalized, complete, relevant, and easy to use and provide security aspects to encourage online use ( DeLone & McLean, 2003 ). Recently, the IS success model has been used to understand mobile user behaviour. For example, Gao and Bai ( 2014 ) used the IS model to explain the continuous intention of users of mobile social network services and found that information quality was positively correlated with user experience of using mobile social network services.

System Quality

System quality refers to the degree to which a website functions, such as accessibility, reliability, and response time ( DeLone & McLean, 2003 ). It represents the technical capability of a website to provide users with simple and quick access to information while ensuring reliability and security ( Teo et al., 2008 ). A well-designed system is necessary to reap organizational benefits, such as reduced costs, improved process efficiency, and increased revenue. Conversely, a poorly designed system may be disruptive to the organization, leading to increased product costs and organizational inefficiency ( Ghasemaghaei & Hassanein, 2015 ; Gorla et al., 2010 ).

Organism: Flow as international factors

The next element of the SOR framework is the organism component, consisting of cognitive and affective mediating states, expressed in the process of regulating the relationship between stimuli and individual responses ( Chen & Chang, 2008 ; Mehrabian & Russell, 1974 ). According to Gao and Bai ( 2014 ), the Organism is a customer's cognitive judgment of the online consumer experience, presented as a stream experience. In this study, we also consider flow as organism component.

Flow theory

SOR model provides a theoretical basis for the mediating effect of flow experience. Studies using SOR framework have shown that consumer internal states (organisms) can play a mediating role between timulus and consumer response behaviour ( Gao & Bai, 2014 ; Ha & Lennon, 2010 ). Computer-mediated communication is a typical situation in which users can experience a psychological state of flow ( Lee et al., 2018 ).

The flow theory was first proposed by Csikszentmihalyi ( 1975 ). It refers to a state of deep immersion in a pleasingly optimal psychological experience ( Novak et al., 2000 ), which is a key driver of persistence ( Chang, 2013 ; Khang et al., 2013 ). Individuals experiencing flow may become so completely lost in the activities they are doing that they lose awareness of time and their surroundings ( Csikszentmihalyi, 1975 ).

Since the short-form video application is an experience product, the user's value mainly comes from their experience during the use process, they can feel great fun. Therefore, based on the SOR model, combined with previous mediation effect on internal cognitive status of research, we have reason to believe that flow in the information system quality and the intermediary role between user reaction, affect the user's internal mental process, which affect their behavioural responses, the flow theory is applied to study the short-form video application addictive behaviour of users.

Response: TikTok addiction behaviour

The response component in the SOR framework refers to the result, final action or reaction, including psychological reaction such as attitude or behaviour, which can be divided into approach behaviour and avoidance behaviour ( Mehrabian & Russell, 1974 ). Approaching behaviour is a positive response and avoiding behaviour is a negative response.

More recently, as algorithmic technology has been upgraded, users have been given more matched content, and using these features has led to varying degrees of immersion, which in turn has induced addictive behaviour. In social media, users are exposed to various technical features or functions, such as user-provided experience, technical stress, exhaustion, and user profiles, which all affect users' participation in social media. As mentioned above, behaviour is closely related to the psychological experience of using social networks ( Zhang et al., 2016 ). TikTok is an emerging short-form video app that offers customized content to users based on their preferences. These fun features and personalized content have addictive entertainment value for very young users. Then, we use addictive behaviour as response to immersive experiences associated with the use of smartphone-based short-form video media.

Proposition development

Information system quality to flow experience.

According to the previous research ( Zhou et al., 2010 ), information quality has a significant impact on users' flow experience, which in turn determines users' loyalty. There are many factors that affect flow, Jung et al. ( 2009 ) point out that content quality affects the flow experience of mobile TV users. Zhou ( 2014 ) confirmed the impact of system quality and information quality on user flow experience of mobile Internet sites as well.

TikTok has its unique way of improving the user experience compared to other social media. For example, offer a variety of special effects filters, fun stickers, and video editing tools to help users spice up their videos. TikTok also offers customized content to users based on their preferences. These fun features and personalized content have addictive entertainment value for very young users. Therefore, this study believes that in order to enable users to have flow experience in TikTok, the positive cognition of the two attributes (information quality and system quality) provided by the platform makes users to immerse themselves in the use process and thus to have flow experience. Therefore, it is very easy for users, especially teenagers who lack self-control, to become addicted to short-form video apps. From this we derive the proposition:

Preposition 1: Information quality has a positive influence on user flow experience.

Preposition 2: System quality has a positive influence on user flow experience.

Flow experience to TikTok addiction

Recent research provides some empirical support that flow can have negative outcomes. For example, Chou and Ting ( 2003 ) found that flow significantly affects online game addiction. Previous studies have shown that smartphone users may experience flow while playing games on their devices ( Joo, 2016 ) and browsing the Internet ( Kim & Han, 2014 ). When people want to have a positive experience of flow, they are also easily addicted to media platforms ( Salehan & Negahban, 2013 ). In this study, we propose that flow may influence the addictive use of short-form video apps in a similar way. We predict that flow may be an important stage prior to users' addictive behaviour ( Khang et al., 2013 ). Therefore, we believe that people who experience flow during the use of short-form video apps are more likely to engage in addictive behaviour. We now raise the proposition:

Preposition 3: Flow experience has a positive influence on TikTok addiction behavioural.

The rest of this paper describes the theoretical background of SOR model, IS theory, flow theory and addictive behaviour in detail. Then, the conceptual framework and three propositions are used to study the influence of the combination of internal and external factors on addictive behaviour.

Research Methods

This paper is a conceptual work that outlines some research prepositions to understand TikTok addition behaviour. This proposed conceptual model should be tested empirically. To statistically validate our conceptual model, users’ perception of information and system qualities as well as their experience with flow and addiction behaviour need to be gauged. Hence, a survey research is the most suitable method to gauge users’ perceptions and behaviours. This is consistent with past research which also used survey method to examine TikTok usage behaviour ( Omar & Dequan, 2020 ). It involves identifying sampling technique, measurement, and data analysis.

With regards to sampling technique, adolescents or young people is the targeted sample. According to Mou ( 2020 ), the largest age group of TikTok users is 6-17 years old, accounting for 31.59%, followed by 18-24 years old (30.14), 25-30 years old (20.85%), 31-35 years old (8.66%), and over 35 years old (8.76). Hence, individuals between the ages of 14 and 18 who have used TikTok in the past year could be an appropriate sample for study. Researchers can adopt non-probability sampling such as virtual snowballing sampling or network sampling to reach out to the TikTok users online.

As for the measurement of constructs, the items can be adopted from past research. Measures for information quality and system quality can be drawn from Kim et al. ( 2003 ) and Zhang et al. ( 2016 ). Meanwhile, the measurement of flow experience can be taken from Zaman et al. ( 2010 ) and Zhang et al. ( 2014 ). Similarly, the TikTok addiction behaviour’s measurement is found in Khang et al. ( 2013 ); Kim et al. ( 2003 ). Table, 1 presents the various constructs in the current framework and strategies for their measurement.

In terms of data analysis, partial least squares (PLS-SEM) analysis is the most option to test the proposed model. This is because PLS-SE< is suitable for the identification of complex critical structural models ( Hair et al., 2019 ). As suggested by Hair et al., ( 2019 ), the study model should be tested in two steps. Firstly, the measurement model should be evaluated to establish the validity and reliability of the questionnaire. Then, in the second step, the structural model should be tested using the bootstrapping technique in order to test the proposed research prepositions.

This study has conceptualized the addictive behaviour of users of short-form video applications, in a word, it is a negative behavioural result of users' flow experience under the influence of external factors of the information system. In this context, this paper proposes a conceptual model that provides theoretical and practical benefits from the perspective of SOR model and flow theory.

Theoretical implications

Theoretically, this study will contribute to the media literature by confirming the SOR model in the context of TikTok addictive behaviour. It will provide strong evidence that internal factors (flow experience) and external factors (IS quality) can lead to adolescents' addiction to TikTok. This study advances the understanding of adolescent addiction behaviour in TikTok through IS quality and flow factors by applying the modified SOR model ( Belk, 1975 ). Previous literature conducted on social media were heavily rely on theory of planed behaviour (TPB), technology continuance theory (TCT) and expectation conformation theory (ECM) models. These studies analyse the causes of addiction from the perspective of the individual, ignoring external environmental stimuli. Therefore, this study overcomes the defects mentioned before. Based on previous literature, we combine the internal factors (flow) with external factors (information quality and system quality) to revaluate the relationship between information system, flow, and addiction behaviour.

Practical implications

This research also has practical contributions. Social media addiction can have many negative effects on young users and the society, so it is necessary for scholars and practitioners to solve this problem. As for TikTok adolescents’ users, excessive immersion on media platform can actively trigger addictive behaviours, which can lead many problems such as depression and anxiety. Therefore, This could raise legal liability and ethical issues for TikTok operator ( Gong et al., 2020 ; Zheng & Lee, 2016 ). Adolescents are at a critical stage of development, media operators should cultivate user with healthy social media use habits, instead of inducing them to become addicted. Therefore, when facing addiction issue, the operators should help users to get rid of it. For example, adolescent mode can be set to limit the content provided to adolescents and control the duration of their use (excessive use of the reminder or disconnection system), this method has been proven to be an effective way to control addictive behaviours ( Chen et al., 2017 ).

Limitations and future research

Although this article presents diverse theoretical and practical implications, limitations are still existing for future research. First, the conceptual framework and propositions must be tested. Due to the current epidemic, the work and life of TikTok users are in an abnormal state. The life at home leads to the prolonged use of smartphone, which may exaggerate the effect of addiction. Therefore, the proposed theoretical model can be used as a reference for subsequent empirical research. Second, the formation of addiction is a complex problem, only adopt quantitative methods may lead to research bias. Future studies could combine qualitative and quantitative method to gain depth of understanding of short-form video application addiction behaviour.

Almahamid, S. M., Tweiqat, A. F., & Almanaseer, M. S. (2016). University website quality characteristics and success: Lecturers’ perspective. International Journal of Business Information Systems, 22(1), 41–61. DOI:

Animesh, A., Pinsonneault, A., Yang, S. B., & Oh, W. (2011). An odyssey into virtual worlds: Exploring the impacts of technological and spatial environments on intention to purchase virtual products. MIS Quarterly: Management Information Systems, 35(3), 789–810. DOI:

Belk, R. W. (1975). Situational Variables and Consumer Behavior. Journal of Consumer Research, 2(3), 157. DOI:

Benlian, A. (2015). Web personalization cues and their differential effects on user assessments of website value. Journal of Management Information Systems, 32(1), 225–260. DOI:

Beyens, I., Frison, E., & Eggermont, S. (2016). “I don’t want to miss a thing”: Adolescents’ fear of missing out and its relationship to adolescents’ social needs, Facebook use, and Facebook related stress. Computers in Human Behavior, 64, 1–8. DOI:

Cao, X., Gong, M., Yu, L., & Dai, B. (2020). Exploring the mechanism of social media addiction: an empirical study from WeChat users. Internet Research, 30(4), 1305–1328. DOI:

Cao, X., & Sun, J. (2018). Exploring the effect of overload on the discontinuous intention of social media users: An S-O-R perspective. In Computers in Human Behavior (Vol. 81, pp. 10–18). DOI:

Chang, C. C. (2013). Examining users′ intention to continue using social network games: A flow experience perspective. Telematics and Informatics, 30(4), 311-321.

Chen, C., Zhang, K. Z. K., Gong, X., Zhao, S. J., Lee, M. K. O., & Liang, L. (2017). Understanding compulsive smartphone use: An empirical test of a flow-based model. International Journal of Information Management, 37(5), 438–454. DOI:

Chen, S. W., & Chang, H. H. (2008). The impact of online store environment cues on purchase intention: Trust and perceived risk as a mediator. Online Information Review, 32(6), 818–841.

Cho, W. C., Lee, K. Y., & Yang, S. B. (2019). What makes you feel attached to smartwatches? The stimulus–organism–response (S–O–R) perspectives. Information Technology and People, 32(2), 319–343. DOI:

Chou, T. J., & Ting, C. C. (2003). The Role of Flow Experience in Cyber-Game Addiction. Cyberpsychology and Behavior, 6(6), 663–675. DOI:

Csikszentmihalyi, M. (1975). Play and intrinsic rewards. Journal of Humanistic Psychology, 15, 41–63.

DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30.

Enez Darcin, A., Kose, S., Noyan, C. O., Nurmedov, S., Yılmaz, O., & Dilbaz, N. (2016). Smartphone addiction and its relationship with social anxiety and loneliness. Behaviour and Information Technology, 35(7), 520–525. DOI:

Figliola, P. (2020). TikTok: Technology Overview and Issues (CRS Report Number: R46543).

Fu, S., Chen, X., & Zheng, H. (2020). Exploring an adverse impact of smartphone overuse on academic performance via health issues: a stimulus-organism-response perspective. In Behaviour and Information Technology. DOI:

Gao, L., & Bai, X. (2014). An empirical study on continuance intention of mobile social networking services: integrating the IS success model, network externalities and flow theory. 26(2), 168–189.

Gao, W., Liu, Z., & Li, J. (2017). How does social presence influence SNS addiction? A belongingness theory perspective. Computers in Human Behavior, 77, 347–355. DOI:

Ghasemaghaei, M., & Hassanein, K. (2015). Online information quality and consumer satisfaction: The moderating roles of contextual factors - A meta-analysis. Information and Management, 52(8), 965–981. DOI:

Gong, M., Yu, L., & Luqman, A. (2020). Understanding the formation mechanism of mobile social networking site addiction: evidence from WeChat users. Behaviour and Information Technology, 39(11), 1176–1191. DOI:

Gorla, N., Somers, T. M., & Wong, B. (2010). Organizational impact of system quality, information quality, and service quality. Journal of Strategic Information Systems, 19(3), 207–228. DOI:

Ha, Y., & Lennon, S. J. (2010). Online visual merchandising (VMD) cues and consumer pleasure and arousal: Purchasing versus browsing situation. Psychology and Marketing, 27(2), 141–165. DOI:

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. DOI:

Hu, Y. (2020). Research on the commercial value of Tiktok in China. Academic Journal of Business & Management, 2(7), 57–64. DOI:

Idemudia, E. C., Raisinghani, M. S., & Samuel-Ojo, O. (2018). The contributing factors of continuance usage of social media: An empirical analysis. Information Systems Frontiers, 20(6), 1267–1280. DOI:

Ifinedo, P. (2018). Determinants of students’ continuance intention to use blogs to learn: an empirical investigation. Behaviour and Information Technology, 37(4), 381–392. DOI:

Iqbal, M. (2020). TikTok revenue and usage statistics. In Business of Apps. https://www.businessofapps.com/data/tik-tok-statistics/

Joo, J. (2016). Exploring Korean Collegians’ Smartphone Game Behavior: Focusing on Conciseness, Perceived Ease of Use, Perceived Enjoyment, Flow, and Intent to Use. Journal of Digital Convergence, 14(1), 379–386. DOI:

Jung, H., & Zhou, Q. (2019). Learning and Sharing Creative Skills with Short Videos: A Case Study of User Behavior in TikTok and Bilibili. International Association of Societies of Design Research Conference, 10, 25–50. https://www.researchgate.net/publication/335335984

Jung, Y., Perez-Mira, B., & Wiley-Patton, S. (2009). Consumer adoption of mobile TV: Examining psychological flow and media content. Computers in Human Behavior, 25(1), 123–129. DOI:

Kamboj, S., Sarmah, B., Gupta, S., & Dwivedi, Y. (2018). Examining branding co-creation in brand communities on social media: Applying the paradigm of Stimulus-Organism-Response. International Journal of Information Management, 39, 169–185. DOI:

Khang, H., Kim, J. K., & Kim, Y. (2013). Self-traits and motivations as antecedents of digital media flow and addiction: The Internet, mobile phones, and video games. Computers in Human Behavior, 29(6), 2416–2424. DOI:

Kim, H. W., Xu, Y., Koh, J., Kim, J., Lee, J., & Choi, D. (2003). A Comparison of Online Trust Building Factors between Potential Customers and Repeat Customers. Journal of the Association for Information Systems, 5(6), 392–420.

Kim, Y. J., & Han, J. (2014). Why smartphone advertising attracts customers: A model of Web advertising, flow, and personalization. Computers in human behavior, 33, 256-269.

Lee, C. H., Chiang, H. S., & Hsiao, K. L. (2018). What drives stickiness in location-based AR games? An examination of flow and satisfaction. Telematics and Informatics, 35(7), 1958-1970. DOI:

Liang, C. J., & Chen, H. J. (2009). A study of the impacts of website quality on customer relationship performance. Total Quality Management and Business Excellence, 20(9), 971–988. DOI:

Liao, C., Palvia, P., & Chen, J. L. (2009). Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT). International Journal of Information Management, 29(4), 309–320. DOI:

Luqman, A., Cao, X., Ali, A., Masood, A., & Yu, L. (2017). Empirical investigation of Facebook discontinues usage intentions based on SOR paradigm. Computers in Human Behavior, 70, 544–555. DOI:

Luqman, A., Masood, A., Weng, Q., Ali, A., & Rasheed, M. I. (2020). Linking Excessive SNS Use, Technological Friction, Strain, and Discontinuance: The Moderating Role of Guilt. Information Systems Management, 37(2), 94–112. DOI:

Ma, Y., Ruangkanjanases, A., & Chen, S. C. (2019). Investigating the impact of critical factors on continuance intention towards cross-border shopping websites. Sustainability (Switzerland), 11(21). DOI:

McKinney, V., Yoon, K., & Zahedi, F. (2002). The measurement of Web-customer satisfaction: An expectation and disconfirmation approach. Information Systems Research, 13(3), 296–315. DOI:

Mehrabian, A., & Russell, J. A. (1974). An Approach to Environmental Psychology. 266.

Moqbel, M. (2020). Understanding the Relationship between Smartphone Addiction and Well-Being: The Mediation of Mindfulnessand Moderation of Hedonic Apps. Proceedings of the 53rd Hawaii International Conference on System Sciences, 3, 6083–6092. DOI:

Mou, J. B. (2020). Study on Social Media Marketing Campaign Strategy-TikTok and Instagram. MIT Sloan School of Management, 3(8), 1–41.

Ngai, E. W. T., Tao, S. S. C., & Moon, K. K. L. (2015). Social media research: Theories, constructs, and conceptual frameworks. International Journal of Information Management, 35(1), 33–44. DOI:

Novak, T. P., Hoffman, D. L., & Yung, Y. F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19(1), 22–42. DOI:

Omar, B., & Dequan, W. (2020). Watch, share or create: The influence of personality traits and user motivation on TikTok mobile video usage. International Journal of Interactive Mobile Technologies, 14(4), 121–137. DOI:

Rahi, S., Khan, M. M., & Alghizzawi, M. (2020). Extension of technology continuance theory (TCT) with task technology fit (TTF) in the context of Internet banking user continuance intention. International Journal of Quality and Reliability Management. DOI:

Salehan, M., & Negahban, A. (2013). Social networking on smartphones: When mobile phones become addictive. Computers in Human Behavior, 29(6), 2632–2639. DOI:

Sun, W., Cai, Z., Li, Y., Liu, F., Fang, S., & Wang, G. (2018). Data processing and text mining technologies on electronic medical records: A review. Journal of Healthcare Engineering, 2018. DOI:

Teo, T. S. H., Srivastava, S. C., & Jiang, L. (2008). Trust and electronic government success: An empirical study. Journal of Management Information Systems, 25(3), 99–132. DOI:

Triantoro, T., Gopal, R., Benbunan-Fich, R., & Lang, G. (2019). Would you like to play? A comparison of a gamified survey with a traditional online survey method. International Journal of Information Management, 49, 242–252. DOI:

Weimann, G., & Masri, N. (2020). Research Note: Spreading Hate on TikTok. In Studies in Conflict and Terrorism. DOI:

Weinstein, A., & Lejoyeux, M. (2010). Internet addiction or excessive internet use. American Journal of Drug and Alcohol Abuse, 36(5), 277–283. DOI:

Whelan, E., Islam, A. K. M. N., & Brooks, S. (2020). Applying the SOBC paradigm to explain how social media overload affects academic performance. Computers and Education, 143(August 2019), 103692. DOI:

Xu, L., Yan, X., & Zhang, Z. (2019). Research on the Causes of the “Tik Tok” App Becoming Popular and the Existing Problems. Journal of Advanced Management Science, 7(2), 59–63. DOI:

Zaman, M., Anandarajan, M., & Dai, Q. (2010). Experiencing flow with instant messaging and its facilitating role on creative behaviors. Computers in Human Behavior, 26(5), 1009–1018. DOI:

Zhang, H., Lu, Y., Gupta, S., & Zhao, L. (2014). What motivates customers to participate in social commerce? the impact of technological environments and virtual customer experiences. Information and Management, 51(8), 1017–1030. DOI:

Zhang, H., Lu, Y., Wang, B., & Wu, S. (2015). The impacts of technological environments and co-creation experiences on customer participation. Information and Management, 52(4), 468–482. DOI:

Zhang, K., Min, Q., Liu, Z., & Liu, Z. (2016). Understanding microblog continuance usage intention: an integrated model. Aslib Journal of Information Management, 68(6), 772–792. DOI:

Zhang, X., Wu, Y., & Liu, S. (2019). Exploring short-form video application addiction: Socio-technical and attachment perspectives. Telematics and Informatics, 42(April), 101243. DOI:

Zheng, X., & Lee, M. K. O. (2016). Excessive use of mobile social networking sites: Negative consequences on individuals. Computers in Human Behavior, 65, 65–76. DOI:

Zhou, T. (2014). Understanding continuance usage intention of mobile internet sites. Universal Access in the Information Society, 13(3), 329–337. DOI:

Zhou, T., Li, H., & Liu, Y. (2010). The effect of flow experience on mobile SNS users’ loyalty. Industrial Management and Data Systems, 110(6), 930–946. DOI:

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Publication date.

31 January 2022

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https://doi.org/10.15405/epsbs.2022.01.02.19

978-1-80296-122-5

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1st Edition

Communication, Media, Disruptive Era, Digital Era, Media Technology  

Cite this article as:

Yao, Q., & Omar, B. (2022). TikTok Addiction Behaviour Among Users: A Conceptual Model and Research Propositions. In J. A. Wahab, H. Mustafa, & N. Ismail (Eds.), Rethinking Communication and Media Studies in the Disruptive Era, vol 123. European Proceedings of Social and Behavioural Sciences (pp. 231-243). European Publisher. https://doi.org/10.15405/epsbs.2022.01.02.19

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Using TikTok for public and youth mental health - A systematic review and content analysis

Affiliation.

• 1 8818Dublin City University, Dublin, Ireland.
• PMID: 35689365
• PMCID: PMC9902978
• DOI: 10.1177/13591045221106608

Globally, TikTok is now the fastest growing social media platform among children and young people; but it remains surprisingly under-researched in psychology and psychiatry. This is despite the fact that social media platforms have been subject to intense academic and societal scrutiny regarding their potentially adverse effects on youth mental health and wellbeing, notwithstanding the inconsistent findings across the literature. In this two part study, we conducted a systematic review concerning studies that have examined TikTok for any public health or mental health purpose; and a follow-up content analysis of TikTok within an Irish context. For study 1, a predetermined search strategy covering representative public and mental health terminology was applied to six databases - PSYCINFO, Google Scholar, PUBMED, Wiley, Journal of Medical Internet Research, ACM - within the period 2016 to 2021. Included studies were limited to English-speaking publications of any design where TikTok was the primary focus of the study. The quality appraisal tool by Dunne et al., (2018) was applied to all included studies. For study 2, we replicated our search strategy from study 1, and converted this terminology to TikTok hashtags to search within TikTok in combination with Irish-specific hashtags. As quantified by the app, the top two "most liked" videos were selected for inclusion across the following three targeted groups: official public health accounts; registered Irish charities; and personal TikTok creators. A full descriptive analysis was applied in both studies. Study 1 found 24 studies that covered a range of public and mental health issues: COVID-19 ( n = 10), dermatology ( n = 7), eating disorders ( n = 1), cancer ( n = 1), tics ( n = 1), radiology ( n = 1), sexual health ( n = 1), DNA ( n = 1), and public health promotion ( n = 1). Studies were predominately from the USA, applied a content analysis design, and were of acceptable quality overall. In study 2, 29 Irish TikTok accounts were analysed, including the accounts of public health authorities ( n = 2), charity or non-profit ( n = 5), and personal TikTok creators ( n = 22). The overall engagement data from these accounts represented a significant outreach to younger populations: total likes n = 2,588,181; total comments n = 13,775; and total shares n = 21,254. TikTok has been utilised for a range of public health purposes, but remains poorly engaged by institutional accounts. The various mechanisms for connecting with younger audiences presents a unique opportunity for youth mental health practitioners to consider, yet there were distinct differences in how TikTok accounts used platform features to interact. Overall, there is an absence of high quality mixed methodological evaluations of TikTok content for public and mental health, despite it being the most used platform for children and young people.

Keywords: Review; children; psychology; qualitative; tiktok.

Publication types

• Systematic Review
• Biomedical Research*
• Drug-Related Side Effects and Adverse Reactions*
• Mental Health
• Social Media*

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Is Social Media Addictive? Here’s What the Science Says.

A major lawsuit against Meta has placed a spotlight on our fraught relationship with online social information.

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By Matt Richtel

A group of 41 states and the District of Columbia filed suit on Tuesday against Meta , the parent company of Facebook, Instagram, WhatsApp and Messenger, contending that the company knowingly used features on its platforms to cause children to use them compulsively, even as the company said that its social media sites were safe for young people.

“Meta has harnessed powerful and unprecedented technologies to entice, engage and ultimately ensnare youth and teens,” the states said in their lawsuit filed in federal court. “Its motive is profit.”

The accusations in the lawsuit raise a deeper question about behavior: Are young people becoming addicted to social media and the internet? Here’s what the research has found.

What Makes Social Media So Compelling?

Experts who study internet use say that the magnetic allure of social media arises from the way the content plays to our neurological impulses and wiring, such that consumers find it hard to turn away from the incoming stream of information.

David Greenfield, a psychologist and founder of the Center for Internet and Technology Addiction in West Hartford, Conn., said the devices lure users with some powerful tactics. One is “intermittent reinforcement,” which creates the idea that a user could get a reward at any time. But when the reward comes is unpredictable. “Just like a slot machine,” he said. As with a slot machine, users are beckoned with lights and sounds but, even more powerful, information and reward tailored to a user’s interests and tastes.

Adults are susceptible, he noted, but young people are particularly at risk, because the brain regions that are involved in resisting temptation and reward are not nearly as developed in children and teenagers as in adults. “They’re all about impulse and not a lot about the control of that impulse,” Dr. Greenfield said of young consumers.

Moreover, he said, the adolescent brain is especially attuned to social connections, and “social media is all a perfect opportunity to connect with other people.”

Meta responded to the lawsuit by saying that it had taken many steps to support families and teenagers. “We’re disappointed that instead of working productively with companies across the industry to create clear, age-appropriate standards for the many apps teens use, the attorneys general have chosen this path,” the company said in a statement.

Does Compulsion Equal Addiction?

For many years, the scientific community typically defined addiction in relation to substances, such as drugs, and not behaviors, such as gambling or internet use. That has gradually changed. In 2013, the Diagnostic and Statistical Manual of Mental Disorders, the official reference for mental health conditions, introduced the idea of internet gaming addiction but said that more study was warranted before the condition could be formally declared.

A subsequent stud y explored broadening the definition to “internet addiction.” The author suggested further exploring diagnostic criteria and the language, noting, for instance, that terms like “problematic use” and even the word “internet” were open to broad interpretation, given the many forms the information and its delivery can take.

Dr. Michael Rich, the director of the Digital Wellness Lab at Boston Children’s Hospital, said he discouraged the use of the word “addiction” because the internet, if used effectively and with limits, was not merely useful but also essential to everyday life. “I prefer the term ‘Problematic Internet Media Use,” he said, a term that has gained currency in recent years.

Dr. Greenfield agreed that there clearly are valuable uses for the internet and that the definition of how much is too much can vary. But he said there also were clearly cases where excessive use interferes with school, sleep and other vital aspects of a healthy life. Too many young consumers “can’t put it down,” he said. “The internet is a giant hypodermic, and the content, including social media like Meta, are the psychoactive drugs.”

Matt Richtel is a best-selling author and Pulitzer Prize-winning reporter based in San Francisco. He joined The Times in 2000, and his work has focused on science, technology, business and narrative-driven storytelling around these issues. More about Matt Richtel

A Parent’s Guide to Kids and Social Media

Does your child have an unhealthy relationship with social media? This is what problematic use could look like .

We asked experts for one practical strategy that parents can use with their kids to help mitigate the harms of social media. Here’s what they told us .

There are many tools that allow parents to monitor and set limits on their children’s screen time. Here’s what to know about them .

If you’ve already given your teen full access to social media, these three strategies can help them cut back .

Is social media addictive? Here is what the science says .

A new book argues that banning social media isn’t the answer to online safety. Instead, the author says parents should emphasize the importance of digital literacy and privacy .

To revist this article, visit My Profile, then View saved stories .

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How to Use Your Phone Addiction to Actually Learn Stuff

I swear I used to have more time than I do now. Sometimes I wonder how much of the reason why is my phone.

It's so easy to lose a half hour here and there to mindless scrolling. Now, it's OK if you don't feel guilty about your phone usage—we all get to decide how we want to spend our time on earth, and no one should feel guilty for scrolling if that's what gives them joy. I, however, frequently find myself feeling absolutely nothing while scrolling. I'm getting nothing out of an activity I'm dedicating hours to daily. I wish I was using that time to learn things instead.

As it turns out, I'm not the first person to think this. There are plenty of apps that can put your phone addiction to work, allowing you to learn new things during what would be downtime.

I live in a town with a large Spanish-speaking population. I studied Spanish in college, and even used it for work during a summer job at a nursery, but I pretty much forgot everything I knew about the language as soon as I left college. I wish I could still speak it, though, which is why I started using Duolingo . The app offers quick lessons, and I'm regaining my ability to read and speak the language.

What I really find fascinating, though, is how many design cues Duolingo takes from video game design in order to make learning addictive. For example, there's an XP system, which is used to rank you against other learners. This already hooks me—I'm an RPG gamer at heart, meaning if there's an XP stat, I want to see that number go up. But the design hooks go deeper: If you practice during the morning you get a double XP boost, which you can use that evening. Practicing in the evening gives you a double XP boost, which you can use the following morning. This little loop helped me build a Spanish learning habit.

There are other great language learning apps , of course. Brilliant offers interactive math and computer science lessons that are designed to be done in 15-minute chunks, which makes it a great replacement for your Twitter/X habit. Or there's Wonderium , which offers courses on a variety of subjects. (It's the streaming service offered by the company that created the Great Courses.) You could also look into the various online classes that are actually worth taking , including MasterClass , Skillshare , and Coursera . All offer online lessons and classes about almost any subject you can imagine.

And there are apps to learn music . There are apps for learning meditation . There are also apps that can help you learn about the world around you: Merlin Bird ID , for example, can help you identify what bird is singing outside your window right now. And don't forget, there are all kinds of free digital resources you can find at the library .

Martin Cizmar

Julian Chokkattu

The point is to find some kind of app that helps you learn—ideally one that helps you build a pattern of learning. Then put that app prominently on your phone's home screen, so you reflexively click it.

Once you've filled your home screen with apps that can teach you something, consider taking another stop: hiding the time-sink ones. You don't have to uninstall these apps—you can just remove them from the home screen and then find them in the App Drawer (Android) or App Library (iOS). Simply tap-and-hold, then remove the app from your home screen.

Or, if you prefer, you can leave your apps on the home screen but use the app One Sec to add a little bit of friction. This free app shows up every time you open an application you find to be a distraction and makes you wait a few seconds. The idea, backed by research, is that you'll be less likely to reflexively open such apps if you stop and reflect on why you're opening it.

Social networks can be a great way to connect with people you care about and possibly even learn something, but let's be honest: Most of time you're just mindlessly scrolling. This is by design . Silicon Valley companies are spending millions to ensure that people open up their apps as frequently as possible. Willpower, up against a force like that, just isn't useful. So I'm trying to redirect my addiction, and I recommend you also give it a shot.

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Restrictions on social media data harming research, says paper

Charges and prohibitions introduced by the likes of x and tiktok are limiting academics’ ability to use sites to gain valuable insights into human behaviour.

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Restrictions placed on researchers’ ability to access data by social media companies including X and TikTok is a “threat to open science”, according to a new paper.

Changes made in 2023 to application programming interfaces (APIs) – used by researchers to measure the behaviour and attitudes of social media users – have included restricting access or introducing charges .

Previously this data had been highly useful to academics in their research, a paper published in  Nature Human Behaviour   says .

“For example, these data can be used to examine where conflict is likely to occur, where to allocate aid in the event of natural disasters, how online polarisation or misinformation is impacting voting patterns,” the paper says.

It warns that changes to API access will make this type of research harder to conduct.

X (formerly Twitter) was criticised earlier this year for introducing charges for its API that many researchers said would force them to abandon their work on the platform.

In August 2023, it granted academic researchers permission to distribute an unlimited number of tweets “if they are doing so on behalf of an academic institution and for the sole purpose of non-commercial research”.

However, the authors argue that this is too restrictive because it still prevents access to the raw data. Furthermore, the terms of X state “one cannot infer anything on an individual level regarding, for example, health, political stance or demographics”, the paper notes.

“Currently, X’s API is both expensive and restrictive regarding data collection, sharing, and thus impeding replication attempts, especially with large datasets”, it adds.

TikTok initially allowed access to its data only to US academics, but in July  expanded its research API to Europe . However, the researchers believe its terms remain too restrictive to be compatible with research, stating that scholars must “refresh research API data at least every 15 days, and delete data [that is no longer available]”.

“The changes are adversely affecting academics who want to study the impact of social media on mental health, on misinformation, political views and so on,” said one of the paper’s authors, Brit Davidson, senior lecturer in the University of Bath ’s School of Management. “It also inadvertently impacts app developers that have built their service on this source of information.

“It’s critical that research on people and society can access these large-scale datasets as there can be policy implications and far-reaching consequences if we get it wrong. Over time, we have many cases of where the lack of open science impacts our ability to verify and check for science credibility. We’ve seen science discredited, which causes concern as to whether work can be reproduced or replicated.”

Some of the changes to APIs have been necessary following the Cambridge Analytica scandal in 2018, said co-author Joanne Hinds, associate professor in management, information, decisions and operations at Bath.

“This led social media platforms to implement strict measures to prevent third-party users from gaining access to personal data without consent. They then enabled users to revoke app permissions, which gave users more control over their data to protect user privacy,” she said.

“However, this wave of changes is pushing researchers to abandon projects or to consider gathering data outside official means,” she added, “and that will, unless addressed, mean that we just simply can’t study important questions about these platforms which are used by millions of people every day.”

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