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Unveiling the predictors and Predictors and

outcomes of
outcomes of TikTok addiction: TikTok
addiction
the moderating role of
parasocial relationships
Naeem Akhtar Received 13 April 2022
Revised 14 August 2022
Institute of Business and Management, University of Engineering and Technology, 16 February 2023
Lahore, Pakistan, and 11 June 2023
16 August 2023
Tahir Islam Accepted 23 August 2023
Leeds Trinity University, Leeds, UK;
Faculty of Management, Prague University of Economics and Business,
Prague, Czech Republic and
Faculty of Organization and Management, Silesian University of Technology,
Gliwice, Poland

Abstract
Purpose – Technology addiction is an increasingly severe problem. TikTok has become increasingly popular
recently, and its addiction is also a major concern. This study aims to examine the antecedents and outcomes of
TikTok addiction.
Design/methodology/approach – The authors collect 579 data from Chinese users using an online survey.
The authors use structural equation modeling with partial least squares (PLS-SEM) to analyze data and test
hypotheses.
Findings – The results illustrate that perceived enjoyment, social relationship, utilitarian need and social
influence positively affect TikTok addiction. Both social anxiety and loneliness have positive effects on TikTok
addiction. Moreover, parasocial relationships positively moderate the association between the antecedents of
self-determination theory (SDT) (perceived enjoyment, social relationship, utilitarian needs, social influence,
social anxiety and loneliness) and TikTok addiction. Meanwhile, TikTok addiction intensifies conflicts,
including technology-family conflict, technology-person conflict and technology-work conflict. These conflicts
reduce life satisfaction.
Practical implications – It offers practical implications for preventing and avoiding TikTok addiction to
create a healthy environment.
Originality/value – This study is one of the few to provide a complete process of TikTok addiction. It
systematically investigates the antecedents and outcomes of TikTok addiction.
Keywords TikTok addiction, Technology addiction, Self-determination theory, Life satisfaction
Paper type Research paper

1. Introduction
Technology addiction denotes a pathological psychological dependency on using technology
(Turel et al., 2011b). It is a broader category and exists in different forms, such as Internet
addiction (Hern
andez et al., 2019; Mo et al., 2018; Sheikh et al., 2017), smartphone addiction
(Chen et al., 2017, 2019), online game addiction (Gong et al., 2019c; Lee et al., 2020), social
networking sites (SNSs) addiction (Gong et al., 2019a) and short video addiction (Ye et al.,
2022). TikTok is one of the most popular short video applications supported by technology.
Hence, TikTok addiction is a specific example of technology addiction. In line with the prior
definition of technology addiction (Turel et al., 2011b), we describe TikTok addiction as users’ Kybernetes
pathological psychological dependency on using TikTok. It is about the excessive and © Emerald Publishing Limited
0368-492X
problematic usage of TikTok. TikTok addiction usually has the following symptoms: DOI 10.1108/K-04-2022-0551
K (1) salience: users’ behaviours and thoughts are dominated by using TikTok; (2) withdrawal:
negative emotions arise if users cannot use TikTok; (3) conflict: using TikTok affects other
tasks, such as study and work; (4) relapse and reinstatement: users cannot reduce TikTok
usage voluntarily; (5) tolerance: users must use TikTok to a great extent to produce thrill; and
(6) mood modification: using TikTok leads to mood changes (Turel et al., 2011b). For
example, if the user spends a lot of time on TikTok every day, feels uneasy and cannot
concentrate on studying or working when not using TikTok, the user can be considered
addicted to TikTok.
TikTok is a social platform for short video clips. It was initially released in 2016 in
China. By 2021, TikTok and Douyin were downloaded over 2 billion times worldwide.
According to the Global Web Index (2019), 90% of all TikTok users use the app daily. App
Annie statistics showed that TikTok users spend far more time per month than Facebook
and Instagram. Thus, TikTok has been integrated into people’s daily lives and is a highly
addictive social platform. Technology addiction may adversely affect individuals’ mental
and physical health (Zheng and Lee, 2016). For instance, scholars discussed that the
excessive use of short videos for needs satisfaction triggers the risk of addiction, and
frequent use of problematic short videos is positively related to addictive behavior
(Sharma et al., 2022). Likewise, research has identified that inappropriate short video use
causes psychological and physical issues such as anxiety, social isolation, depression and
loneliness (Smith and Short, 2022). However, the antecedents and outcomes of TikTok
addiction have not been systematically studied. Therefore, it is necessary to investigate
why individuals are addicted to TikTok and the consequences of addiction. This can
provide TikTok users and TikTok application designers with implications on how to
prevent and intervene in TikTok addiction.
The existing literature has revealed the antecedents of technology addiction. However,
there are still some gaps. First, previous research about technology addiction mainly focused
on SNSs (Cao et al., 2018; Gong et al., 2020; Tang et al., 2016; Yang et al., 2016; Zheng and Lee,
2016; Zhang et al., 2022a, b). The factors affecting SNSs addiction may vary depending on
mobile application usage. For instance, TikTok is a platform for short videos, which differs
from other SNSs (e.g. Facebook and YouTube, the platforms for connecting with real friends
and long videos, respectively). Online users usually spend more time on TikTok than
expected. Earlier research found that individuals create short videos to document their lives,
present themselves to others for recognition, improve video production, establish new
connections, acquire followers and earn money (Meng and Leung, 2021). However, the
problematic usage of short videos triggers feelings of loneliness, anxiety and stress (Sharma
et al., 2022). This aspect has not received adequate academic attention within the literature on
TikTok. Second, the extant studies argued that using technology (such as smartphones, SNSs
and online games) can increase and reduce negative moods (Lee et al., 2020). However, few
studies integrated two types of mechanisms and investigated them systematically in the
context of TikTok. Third, although the past literature demonstrated the negative impacts of
technology addiction (Kuem et al., 2020; Luqman et al., 2020; Zheng and Lee, 2016), to the best
of our knowledge, the negative influences have not been systematically investigated in the
context of TikTok addiction. Therefore, we formulate the following research question: What
are the antecedents and outcomes of TikTok addiction?
Relying on self-determination theory (SDT) (Ryan and Deci, 2000), this research examines
the antecedents and consequences of TikTok addiction. This study contributes to the theory
and practice in various ways. First, we focus on the TikTok context and explore two different
TikTok addiction mechanisms: positive and negative reinforcement. The former is explained
by intrinsic motivation (e.g. perceived enjoyment, social relationshipand utilitarian need) and
extrinsic motivation (e.g. social influence) and the need for relatedness explains the latter
(including social anxiety and loneliness). This enriches the technology addiction literature
and the application of SDT. Second, several studies present the direct and positive effects of Predictors and
parasocial relationships on SNSs addiction (Baek et al., 2013; B
erail et al., 2019), but no outcomes of
research tests the moderating role of parasocial relationships. To our best knowledge, this
research is one of the first to examine the moderating role of parasocial relationships in the
TikTok
formation of TikTok addiction. This enhances our understanding of the role of parasocial addiction
relationships in addiction. Third, we provide a complete process of TikTok addiction.
Different factors lead to TikTok addiction, which increases technology conflicts (work, family
and self) and results in poor life satisfaction. This is conducive to a systematic and
comprehensive understanding of TikTok addiction. Finally, understanding TikTok
addiction has significant practical implications. The findings provide practitioners with
insights into the intervention and prevention of TikTok or shot video addiction. This will
have significant effects on the growth of the new generation.
The remainder of this paper is organized as follows. In Section 2, we provide the literature
review. Then, Section 3 introduces SDT. Hypotheses are developed in Section 4. We describe
the methodology and data in Section 5 and report the analysis results in Section 6. Finally,
Section 7 discusses the findings, highlights theoretical contributions and managerial
implications and outlines the limitations and future research.

2. Literature review
2.1 Previous research on addiction
Previous literature identifies multiple factors affecting addiction, including social and
psychological needs (Ponnusamy et al., 2020), emotional factors (Hern
andez et al., 2019), self-
traits (Khang et al., 2013), personality traits (Andreassen et al., 2017; Tang et al., 2016), habits
(Chen et al., 2019; Gong et al., 2019c) and psychobiological factors (Alcaro et al., 2021; Giacolini
et al., 2020). Ponnusamy et al. (2020) revealed that four types of psychological needs, namely,
entertainment, recognition, information and social desires, motivate individuals to use
Instagram. Emotional factors are important predictors of addiction, such as depression
(Hern
andez et al., 2019), stress (Feng et al., 2019; Hern
andez et al., 2019), anxiety (B
erail et al.,
2019; Feng et al., 2019) and loneliness (Kuem et al., 2020). SNSs (e.g. Twitter and Facebook)
have mood regulation and susceptibility to elicit good feelings and alleviate negative
emotions (Chen et al., 2019). Similarly, self-traits have significant influences on addiction.
Individuals with low self-esteem, self-efficacy or self-control tend to experience a high level of
addiction (Andreassen et al., 2017; Chen, 2018; Hong et al., 2014; Khang et al., 2013). Past
research affirms that personality traits affect addictive behaviours as well (Andreassen et al.,
2017; Nie et al., 2019; Tang et al., 2016). For instance, Andreassen et al. (2017) found that
narcissistic personality is positively related to SNS addiction because they can show their
success and get compliments from other users. Additionally, when individuals develop a
strong habit of using technology, they tend to ignore future harmful influences and become
addicted easily (Chen et al., 2019; Gong et al., 2019c; Turel and Serenko, 2017; Yang et al., 2016).
Addiction can result in negative consequences, including work, family and personal
problems (Kuem et al., 2020; Luqman et al., 2020; Zheng and Lee, 2016). Addictive behaviours
with technology can cause work overload or task distraction and lower work or academic
performance (Cao et al., 2018; Moqbel and Kock, 2018; Turel et al., 2011a; Yu et al., 2018; Zheng
and Lee, 2016). Technology addiction can lead to family conflicts as well. For example, users
neglect family relationships and spend less time with family (Gong et al., 2019b; Turel et al.,
2011a; Zheng and Lee, 2016; Zhang et al., 2021). In addition, spending much time on
technology can negatively affect personal health, such as lack of sleep, eye fatigue and
exercise (Gong et al., 2019b; Zheng and Lee, 2016). Moreover, technology addiction can
produce negative emotions like anxiety, loneliness and depression (Wang et al., 2019a, b).
K 2.2 TikTok addiction
TikTok has only recently gained attention (Cuesta-Vali~ no et al., 2022; Montag et al., 2021;
Scherr and Wang, 2021; Smith and Short, 2022; Zhang et al., 2022a, b), but research on TikTok
addiction remains scarce. Prior literature on TikTok can broadly be divided into two streams.
Some studies focus on identifying drivers of TikTok usage or addiction, such as novelty
(Scherr and Wang, 2021), stress (Huang et al., 2021), duration of use (Huang et al., 2021) and
flow experience (Huang et al., 2021). For instance, Tian et al. (2023) focused on short-form
video features and examined the mechanisms of three features affecting TikTok addiction.
They found that immersion, social, and control features as external stimuli activate users’
feelings of withdrawal and perceived enjoyment, promoting users’ addiction. Other studies
explore the harmful effects of TikTok addiction. For example, Sha and Dong (2021) indicated
that TikTok use disorder could cause depression, anxiety, stress and memory loss. Ye et al.
(2022) pointed out that short video (e.g. TikTok) addiction reduces students’ intrinsic and
extrinsic learning motivation. For example, TikTok videos increasingly raise concerns
regarding the problematic usage of short videos and their effects on individuals’ mental
health (Zhang et al., 2019). Likewise, extensive use of short videos generally develops feelings
of loneliness, stress and heightened anxiety among viewers (Falgoust et al., 2022). TikTok is a
short video-sharing platform whose functional structure differs from other SNSs (e.g.
Facebook and Twitter). Factors affecting TikTok addiction may differ from the antecedents
of SNS addiction. Moreover, summarizing the two streams of research, there is also a lack of
systematic research on the complete process of TikTok addiction. Hence, exploring the
determinants and consequences of TikTok addiction is warranted.

2.3 Motivation of short video users

Academic attention has been directed towards understanding the motivations that drive user
engagement with the emergence of short video platforms such as TikTok. Several studies
have delved into the underlying factors that compel individuals to produce and consume
short videos on TikTok. Entertainment and amusement are primary catalysts for user
engagement with short videos on TikTok (Alhabash and Ma, 2017). The platform’s
captivating and innovative content offers users a source of carefree enjoyment, enabling them
to break away from their daily routines and embrace moments of happiness (Xie et al., 2022).
TikTok provides users a dynamic outlet for creative self-expression through short video
content (Omar and Dequan, 2020). The platform’s diverse and supportive community
motivates numerous users to exhibit their talents, share their perspectives and mold their
online identities (Scherr and Wang, 2021). The social dimension of TikTok significantly
shapes user motivation (Zhou et al., 2014). Interactive features like duets and challenges draw
users in, fostering community and connections with others (Sharma et al., 2022). For some
users, the drive to create and share content on TikTok stems from the allure of garnering
recognition and popularity. The platform’s algorithmic exposure and potential for content to
go viral offer users the chance to attain fame and social validation (Alhabash and Ma, 2017).
TikTok’s emphasis on innovative content formats and creative expression lures individuals
seeking a platform to experiment with novel ideas and storytelling techniques (Meng and
Leung, 2021). While these motivations provide valuable insights into the utilization of short
videos on TikTok, it is imperative to recognize the potential diversity in individual
motivations. Researchers continue to explore the evolving landscape of short video platforms
and their impact on user behaviour and well-being.

3. Theoretical background
SDT is one of the principal theories for explaining human motivation. It is applied in many
research fields, such as purchase behaviour, donation behaviour, work behaviour and
technology adoption behaviour (Bagheri et al., 2019; Bakker and Oerlemans, 2019; Koo and Predictors and
Chung, 2014; Tandon et al., 2020; Wang et al., 2019b; Wu, 2019; Wu et al., 2021). SDT identifies outcomes of
intrinsic and extrinsic motivations (Ryan and Deci, 2000). Intrinsic motivation is an inherent
tendency to do an activity for inherent interests and satisfaction driven by inner values.
TikTok
Extrinsic motivation refers to the performance of an activity to attain a separable addiction
consequence activated by external factors (e.g. rewards). In the TikTok context, intrinsic
motivation (e.g. enjoyment, social relationship and utilitarian need) and extrinsic motivation
(e.g. social influence) may lead individuals to use or even become addicted to TikTok.
SDT also suggests three innate psychological needs that motivate human behaviours.
They are the need for autonomy (the need for a sense of control), competence (the need for the
ability to do activities) and relatedness (the need for connection with others and feelings of
belongingness) (Ryan and Deci, 2000; Islam et al., 2020). TikTok can satisfy the need for
relatedness. In the context of TikTok, the need for relatedness is the need to belong and
maintain strong positive interpersonal associations. It is a pervasive, fundamental and
powerful motivation for individuals (Baumeister and Leary, 1995). The feelings of
belongingness can pertain to the involvement in and perception of belonging to TikTok.
Acquiring a sense of belonging can generate positive emotions (Baumeister and Leary, 1995),
reducing negative emotions, such as social anxiety and loneliness. This then motivates users’
behavior, like using TikTok.
SDT provides a holistic view. It applies to this study for two reasons. First, extant
literature widely used the theory to explore the determinants of consumer behaviours. For
instance, Wang et al. (2019b) used SDT and researched four extrinsic motivations responsible
for consumer behaviours in social commerce. T€orh€onen et al. (2020) employed SDT and
examined intrinsic and extrinsic motivations behind online video content creation. Second,
SDT provides theoretical and structured reasoning to examine the fundamental mechanisms
of TikTok addiction.
Extant literature has indicated that positive and negative reinforcements are crucial for
addictive behaviours (Robinson and Berridge, 2003; Wise and Koob, 2014). This work
explores the dual mechanisms affecting TikTok addiction: positive reinforcement and
negative reinforcement mechanisms. A positive reinforcement mechanism shows that
individuals may be addicted to behaviour if it helps them maintain a positive mood. Negative
reinforcement mechanism posits that individuals may become addicted to behaviour if it
helps them alleviate negative mood (Chen et al., 2019; Lee et al., 2020). In this paper, the former
means using TikTok can enhance positive mood; the latter reduces negative mood. In
accordance with SDT, we use the broad categorization of motivation in the positive
reinforcement mechanism. Intrinsic motivation includes perceived enjoyment, social
relationships and utilitarian need; extrinsic motivation includes social influence. We
consider two types of moods in the negative reinforcement mechanism: social anxiety and
loneliness.

4. Hypotheses development
4.1 Antecedents of TikTok addiction
Perceived enjoyment is a positive reinforcement mechanism articulating how TikTok is
perceived as enjoyable (Davis et al., 1992). Based on SDT, perceived enjoyment is an intrinsic
motivation to promote behaviours. In the context of TikTok, short videos provide users with
an enjoyable experience. When individuals perceive short videos as enjoyable, they tend to
consume more time on TikTok. Prior scholars have shown that perceived enjoyment is a
critical driver of addictive behaviours (Chen et al., 2017, 2019; Gong et al., 2019a, b; Turel and
Serenko, 2017; Yang et al., 2016). Thus, we propose that perceived enjoyment while using
TikTok is positively related to TikTok addiction.
K H1. Perceived enjoyment is positively associated with TikTok addiction.
The social relationship is an intrinsic motivation that reflects individuals’ needs for social
interaction, such as making new friends, maintaining relationships and sharing feelings and
ideas (Chan et al., 2012; Chen et al., 2017; Zhou et al., 2014; Islam et al., 2018). TikTok can help
users broaden their social networks and keep in touch with peers. It satisfies individuals’
needs for relatedness. Based on SDT, fulfilling relatedness needs may lead to their overuse of
TikTok. Extant research has confirmed social relationships’ positive and significant
influences on addictive behaviours (Gong et al., 2019a; Ponnusamy et al., 2020). Hence, we
hypothesize that social relationships motivate TikTok addiction.
H2. Social relationship is positively associated with TikTok addiction.
Utilitarian need refers to using technology to achieve instrumental needs or to complete
related tasks, such as getting the latest information, learning and researching (Griffin et al.,
2000; Zhou et al., 2014; Zhou et al., 2011; Islam et al., 2021a). According to SDT, it is an intrinsic
motivation that drives individuals’ behaviours. TikTok provides many functions to help
users obtain helpful information and solve practical problems. For example, users can gain
knowledge, know what is happening, search for problems they encounter and find solutions.
Users may be extremely involved when they obtain high-level practical benefits from TikTok
or fulfil desirable needs. Many studies have recognized the positive effects of functional needs
on usage and addictive behaviours (Ponnusamy et al., 2020; Zhou et al., 2014). Therefore, we
postulate the following hypothesis:
H3. Utilitarian need is positively associated with TikTok addiction.
Social influence means that individuals’ attitudes, opinions and behaviours are affected by
important others, such as friends, family and colleagues (Kelman, 1958). Social influence is an
external factor that motivates individuals to use TikTok. When individuals receive
normative pressure from significant others, they may continue using TikTok in order to gain
recognition from others and maintain relationships with them (Bagozzi and Lee, 2002;
Kelman, 1958). Hence, after satisfying their needs for relatedness, they are likely to overuse it
and become addicted. Prior studies have found that social influence positively affects the
desire for technology or continuance usage (Huang, 2019; Kulviwat et al., 2009; Yang, 2019;
Yoon and Rolland, 2015). The behaviours of continuance usage tend to result in excessive
technology use. Based on the above discussion and SDT, we suggest that social influence as
an extrinsic motivation positively affects TikTok addiction.
H4. Social influence is positively associated with TikTok addiction.
Social anxiety is defined as an individual’s fear of social interaction or performance situations
(e.g. meeting strangers, giving a report to a group and going to a party). It is often
accompanied by avoidance behaviours (Fresco et al., 2001; Schlenker and Leary, 1982).
TikTok provides a safe and comfortable environment for socially anxious people to
communicate with others. People can get informational or emotional support from others on
the TikTok application. This increases their sense of belonging (Liu et al., 2020). According to
SDT, a sense of belonging can generate positive emotions, thereby relieving social anxiety.
However, this may lead to excessive dependence on TikTok. In sum, TikTok plays a critical
role in mood regulation. TikTok can satisfy users’ needs for relatedness and allow them to
experience a sense of belonging. This then reduces feelings of social anxiety. In the end, this
promotes their addiction to TikTok. Prior empirical research has revealed that social anxiety
increases the tendency to technology addiction (B
erail et al., 2019; Chen et al., 2020; Dong et al.,
2018; Fayazi and Hasani, 2017; Karaca et al., 2020). Accordingly, this study proposes the
following hypothesis:
 H5. Social anxiety is positively associated with TikTok addiction. Predictors and
Loneliness is an adverse experience that comes from insufficiencies of one’s social network outcomes of
(Guo et al., 2018; Pittman and Reich, 2016; Rubin et al., 1985; Wang et al., 2019a). On TikTok, TikTok
individuals can interact anonymously, reducing threats and stresses. During social addiction
interaction with others on TikTok, individuals can also gain emotional support, making
them feel a sense of belonging and companionship (Morahan-Martin and Schumacher, 2003).
According to SDT, the satisfaction of relatedness needs and an increased sense of belonging
make individuals more willing to use TikTok to escape negative emotions and reduce
loneliness. As a result, they are prone to become addicted to TikTok (Caplan, 2003; Morahan-
Martin and Schumacher, 2003; Yao and Zhong, 2014; Islam et al., 2021b). Existing studies
have proved the positive effect of loneliness on technology addiction (Ang et al., 2018; Guo
et al., 2018; Lee et al., 2019). Thus, we postulate the following statement:
H6. Loneliness is positively associated with TikTok addiction.

4.2 The moderating role of parasocial relationships

Based on the concept in Horton and Wohl (1956), in the TikTok context, we define parasocial
relationships as one-sided interpersonal relationships that an individual develops with short
video creators. The individual is familiar with the short video creators, but the short video
creators hardly know them. Parasocial relationships are close to real-life relationships (Dibble
et al., 2016). They can compensate for the lack of real-life relationships and satisfy people’s
social interaction and belongingness (Horton and Wohl, 1956). Existing studies have proved
that parasocial relationships positively affect SNSs addiction (Baek et al., 2013; B
erail et al.,
2019; Shamim and Islam, 2022).
SDT suggests that the needs for relatedness motivate users’ behaviours. When users have
stronger parasocial relationships with short video creators, they may feel more satisfied with
relatedness and feel closer to these creators. They usually perceive more enjoyment. Close
relationships with creators can meet their social relationship and utilitarian needs. Moreover,
users usually share values with short video creators. They may accept social influence and
follow others’ behaviours to stay consistent. Solid parasocial relationships with creators can
also help individuals achieve a sense of relatedness and belonging, reducing feelings of social
anxiety and loneliness. As a result, users may become more dependent on parasocial
relationships and willing to spend more time using TikTok. This leads to TikTok addiction.
Taken together, the following hypotheses are proposed:
H7a. Followers’ parasocial relationships with short video creators positively moderate
the relationships between (i) perceived enjoyment, (ii) social relationships, (iii)
utilitarian need, (iv) social influences and TikTok addiction.
H7b. Followers’ parasocial relationships with short video creators positively moderate
the relationships between (i) social anxiety, (ii) loneliness and TikTok addiction.

4.3 Outcomes of TikTok addiction

TikTok addiction leads to three adverse outcomes: technology-family conflict, technology-
work conflict and technology-person conflict. Individuals who are addicted to TikTok spend
too much time viewing short videos, resulting in less time for family activities. The time for
face-to-face communication with family members is reduced. They ignore their family, and
eventually, technology-family conflict occurs (Gong et al., 2019b; Luqman et al., 2020; Turel
et al., 2011a). Moreover, TikTok users may become addicted to watching short videos during
work or school time. This reduces their attention. They may not complete academic or work-
related tasks, reducing academic or work performance (Samaha and Hawi, 2016). Thus,
K TikTok addiction causes technology-work conflict (Gong et al., 2019b; Luqman et al., 2020;
Zheng and Lee, 2016). In addition, devoting substantial time to using TikTok can lead to
personal problems, including psychological problems (e.g. depression, anxiety and stress)
and physical problems (e.g. eyestrain, backaches, insomnia, chronic sleep deprivation and
low sleep quality). Hence, TikTok causes technology-person conflict (Gong et al., 2019b;
Luqman et al., 2020; Zheng and Lee, 2016). According to the extant literature, the following
hypotheses are formulated:
H8a. TikTok addiction is positively associated with technology-family conflict.
H8b. TikTok addiction is positively associated with technology-person conflict.
H8c. TikTok addiction is positively associated with technology-work conflict.
Devoting much time and energy to watch short videos on TikTok can hinder daily activities.
It will lead to family, work and personal conflicts and reduce life satisfaction. Based on
existing studies, conflicts cause a decline in life quality, adversely affecting life satisfaction.
Extant research has uncovered those conflicts (e.g. work-family conflicts) negatively affect
life satisfaction (Akhtar et al., 2023; Y€ucel and Usluel, 2016). Hence, we hypothesize that
family, work and personal conflicts caused by TikTok addiction are negatively related to life
satisfaction. Figure 1 demonstrates the proposed relationships.
H9a. Technology-family conflict is negatively associated with life satisfaction.
H9b. Technology-person conflict is negatively associated with life satisfaction.
H9c. Technology-work conflict is negatively associated with life satisfaction.

5. Methodology
5.1 Measurement development
To examine our proposed framework, we designed an online survey for data collection in
China. We extracted the measurement items from prior literature (Table 1). We used a 5-point

Figure 1.
Conceptual framework
Constructs Items Statements Loadings
Predictors and
outcomes of
Perceived enjoyment (PE) (CR 5 0.919, PE1 Using TikTok is enjoyable 0.942 TikTok
AVE 5 0.792, α 5 0.873) Davis et al. (1992) PE2 Using TikTok is pleasurable 0.917
PE3 Using TikTok is fun 0.804 addiction
Social relationship (SR) (CR 5 0.867, SR1 TikTok made it easy to make friends with 0.784
AVE 5 0.687, α 5 0.848) Zhou et al. (2014), new or interesting people
Chen et al. (2017), Chan et al. (2012) SR2 TikTok made me able to read about other 0.785
people’s lives
SR3 TikTok made me able to express my 0.911
feeling and share my views, thoughts, and
experience
Utilitarian need (UN) (CR 5 0.915, UN1 TikTok can help me get useful information 0.844
AVE 5 0.682, α 5 0.883) Chan et al. (2012), and broaden my knowledge base
Babin et al. (1994) UN2 TikTok can help me find out what is going 0.818
on in society and understand events that
are happening
UN3 TikTok can refine my thinking 0.788
UN4 I could do what I really needed to do in 0.821
TikTok
UN5 I accomplished just what I initially wanted 0.856
to in TikTok
Social influence (SI) (CR 5 0.876, SI1 People who are important to me think that 0.890
AVE 5 0.703, α 5 0.791) Venkatesh et al. I should use TikTok
(2003) SI2 People who influence my behaviour think 0.868
that I should use TikTok
SI3 People around me who have benefited 0.745
from using TikTok in learning or working
think that I should use TikTok
Social anxiety (SA) (CR 5 0.874, SA1 I often feel nervous even in casual get- 0.827
AVE 5 0.700, α 5 0.790) Leary (1983) togethers
SA2 I wish I had more confidence in social 0.857
situations
SA3 In general, I am a shy person 0.852
Loneliness (LL) (CR 5 0.850, LL1 In general, I feel like I lack companionship 0.728
AVE 5 0.654, α 5 0.729) Hughes et al. LL2 In general, I feel like I am often left out of 0.856
(2004) social situations
LL3 In general, I feel isolated from others 0.838
Parasocial relationships (PR) (CR 5 0.898, PR1 My favorite TikTok video creator makes 0.804
AVE 5 0.747, α 5 0.878) Rubin and Perse me feel comfortable as if I am with a friend
(1987) PR2 I see my favorite TikTok video creator as a 0.903
natural, down-to-earth person
PR3 I look forward to watching my favorite 0.884
TikTok video creator on his or her next
video
TikTok addiction (TA) (CR 5 0.914, TA1 I sometimes neglect important things 0.837
AVE 5 0.680, α 5 0.884) Charlton and because of my interest in TikTok
Danforth (2007) TA2 My social life has sometimes suffered 0.771
because of my using TikTok
TA3 Using TikTok sometimes interfered with 0.839
other activities
TA4 When I am not using TikTok, I often feel 0.796 Table 1.
agitated Measurement items,
TA5 I have made unsuccessful attempts to 0.878 composite reliability
reduce the time I spend using TikTok (CR), average variance
extracted (AVE) and
(continued ) Cronbach’s alpha (α)
K Constructs Items Statements Loadings

Technology-family conflict (TFC) TFC1 The use of TikTok keeps me from my 0.703
(CR 5 0.863, AVE 5 0.613, α 5 0.795) family and friends more than I would like
Turel et al. (2011a) TFC2 The use of TikTok takes up time that I feel 0.841
I should spend with my family and friends
TFC3 (R) The time I devote to the use of TikTok 0.738
does NOT keep me from participating
equally in my non-work related activities
TFC4 (R) I generally seem to have enough time to 0.841
use TikTok and to spend time with family
and friends
Technology-person conflict (TPC) TPC1 I experience physical problems because of 0.889
(CR 5 0.875, AVE 5 0.702, α 5 0.790) TikTok usage (e.g. backaches, eye strain,
Zheng and Lee (2016) headache, carpal tunnel syndrome and
chronic sleep deprivation)
TPC2 Using TikTok at night influences my sleep 0.862
TPC3 I lose sleep due to late-night TikTok using 0.757
Technology-work conflict (TWC) TWC1 TikTok usage influences my school work/ 0.780
(CR 5 0.864, AVE 5 0.679, α 5 0.771) profession/work
Akhtar et al. (2022) TWC2 I neglect school work/profession/work to 0.810
spend more time on TikTok usage
TWC3 My school/profession/work performance 0.880
and concentration are influenced by
TikTok usage
Life satisfaction (LS) (CR 5 0.912, LS1 In most ways, my life is close to my ideal 0.856
AVE 5 0.676, α 5 0.882) Diener et al. LS2 The conditions of my life are excellent 0.779
(1985) LS3 I am satisfied with my life 0.842
LS4 So far, I have gotten the important things I 0.788
want in life
LS5 If I could live my life over, I would change 0.841
almost nothing
Note(s): (R): Reverse coded item
Table 1. Source(s): Table by authors

scale ranging from 1 (not at all) to 5 (extremely) to measure the constructs. We also included
gender, age, monthly income, education, usage frequency and user experience as control
variables. We adapted the user experience and usage frequency measures from Gong
et al. (2019c).

5.2 Data collection

TikTok was initially released in China. Chinese TikTok users are huge and are a typical
representative sample for studying TikTok addiction (Tian et al., 2023). To some extent, it can
also provide references for other countries to understand TikTok addiction. Thus, we invited
Chinese TikTok users to complete our survey via social media channels and groups. All
participants have experience using TikTok. An online survey has been widely used for data
collection in studies of technology addiction (Byun et al., 2009; Chen et al., 2019; Gong et al.,
2019b, c; Lee et al., 2020). From February 27th to April 28th, 2023, we initiated data collection.
To express our gratitude, we gave the participants a 10-yuan cash reward. The online survey
package comprised detailed instructions, a cover letter, and an appreciation letter, which we
sent to the 692 respondents who agreed to participate in this research’s data collection
process. Out of the 692 survey respondents, we excluded 113 responses due to
incompleteness, extreme and missing values, resulting in 579 valid responses. To
determine the sample size adequacy, we applied the rule-of-thumb suggested by Cohen (1992), Predictors and
which indicates that a sample size of 454 is more than sufficient to achieve a statistical power outcomes of
of 80 at a 5% significance level. Among these respondents, 53.20% were males and 46.80%
were females. Most (69.59%) were between 19 and 30 years old. Many have a bachelor’s
TikTok
degree (37.65%) or a higher degree (30.56%). Many (30.91%) have used TikTok for over addiction
12 months. Table 2 presents the descriptive statistics of the sample.

6. Results
We used structural equation modeling with partial least squares (PLS-SEM) to evaluate our
research model. This approach can handle complex associations among variables. It can
assess all path coefficients as well as the reliability and validity of constructs simultaneously
(Sarstedt et al., 2017). Thus, it is appropriate for testing our complex model. It has been used in

Characteristics Frequency Percentage

Gender
Male 308 53.20%
Female 271 46.80%
Age (years)
19–22 172 29.70%
23–30 231 39.89%
31–40 67 11.57%
41–50 37 6.39%
51–60 39 6.73%
Over 61 33 5.70%
Education
Under high school 114 19.68%
High school 70 12.09%
Bachelor’s degree 218 37.65%
Master’s degree 116 20.03%
Doctor degree 61 10.53%
Monthly income (RMB)
Under 5,000 197 34.02%
5,001–10,000 184 31.78%
10,001–15,000 93 16.06%
15,001–20,000 59 10.19%
Over 20,000 46 7.94%
Usage experience
0–1 month 53 9.15%
1–3 months 87 15.02%
3–6 months 138 23.83%
6–9 months 74 12.78%
9–12 months 48 8.29%
Over 12 months 179 30.91%
Usage frequency
Table 2.
Up to 1–2 times a year 143 25.62% Overview of
Up to 2–3 times a month 116 20.78% respondents’
Up to 3–4 times a week 159 28.49% socioeconomic and
Daily 140 25.08% demographics
Source(s): Table by authors (n 5 579)
K many studies (Andrei et al., 2017; Chen et al., 2019; Gong et al., 2019b; Lee et al., 2020; Nicolescu
and Nicolescu, 2019; Sepehr and Head, 2018). We used SmartPLS 4.0 software to analyze data
and validate the measurement and structural models.

6.1 Measurement model

This study calculated the reliability and validity of measures. Table 3 shows the descriptive
statistics. Cronbach’s α values of constructs exceed 0.70, which shows good internal
consistency. All composite reliability (CR) values were greater than the recommended score of
0.70 (Bagozzi and Yi, 1988), with a range of 0.850 and 0.919. As demonstrated in Table 1, most
loadings are above 0.70 and all loadings are above the threshold score of 0.50, which is
acceptable. All average variance extracted (AVE) values were larger than the threshold score
of 0.50 within the range of 0.613–0.792 (see Table 3). Thus, convergence validity is good.
Table 4 demonstrates that the AVE square-root value of a construct was above the
correlations between that construct and all other constructs (Fornell and Larcker, 1981). In
sum, discriminate validity is good.
Moreover, the Q2 values obtained through the blindfolding procedures for TikTok
addiction (Q2 5 0.313), technology-family conflict (Q2 5 0.017), technology-person conflict
(Q2 5 0.078), technology-work conflict (Q2 5 0.021) and life satisfaction (Q2 5 0.040) were
higher than zero. They were acceptable to support the predictive relevance of our model
(Geisser, 1974; Stone, 1974). Further, the model’s standardized root mean square residual
(SRMR) was 0.043, less than 0.08. It suggested a good model fit (Hair et al., 2017).

6.2 Common method bias

This research used Harman’s single-factor test to assess the common method bias (Podsakoff
et al., 2003). We performed an exploratory factor analysis on all items using SPSS. The results
demonstrated that there were ten distinct factors with eigenvalues above 1. The first factor
accounted for 19.74% of the total variance, less than 50% (Podsakoff et al., 2003).
Consequently, common method bias is not a serious concern in our study. We also tested the
collinearity diagnostic issue. The variance inflation factor (VIF) scores ranged from 1.119 to
2.983, much lower than the cutoff value of 10.0. Table 4 shows all the correlations are less than
0.80 (Mason and Perreault, 1991). Hence, the data has no issue of multicollinearity.

6.3 Structural model

The structural model was employed to test the hypotheses. We used bootstrapping with 5,000
subsamples to test the statistical significance of the path coefficients. The confidence interval
method used a bias-corrected and accelerated (BCa) bootstrap and a two-tailed significance test.
The results are shown in Figure 2 and Table 4. We expected four antecedents in the positive
reinforcement mechanism to have positive relationships with TikTok addiction. Our results
demonstrated that perceived enjoyment (βPE → TA 5 0.227***, p < 0.001), social relationship
(βSR → TA 5 0.140***, p < 0.01), utilitarian need (βUN → TA 5 0.352***, p < 0.001) and social
influence (βSI → TA 5 0.256***, p < 0.001) are positively associated with TikTok addiction.
Accordingly, H1–H4 was supported. We also expected two antecedents in the negative
reinforcement mechanism to link with TikTok addiction positively. The results revealed that
social anxiety (βSA → TA 5 0.356***, p < 0.001) and loneliness (βLL → TA 5 0.762***, p < 0.001)
are positively related to TikTok addiction. Thus, H5–H6 was also supported.
Hypothesis 8 predicted the positive effects of TikTok addiction on conflicts. The results
indicated that TikTok addiction is positively related to technology-family conflict (βTA →
TFC 5 0.203***, p < 0.001), technology-person conflict (βTA → TPC 5 0.401***, p < 0.001) and
technology-work conflict (βTA → TWC 5 0.231***, p < 0.001). Hence, H8a, H8b and H8c were
Constructs 1. PE 2. SR 3. UN 4. SI 5. SA 6. LL 7. TA 8. TFC 9. TPC 10. TWC 11. LS 12. PR

1 0.889
2 0.083 0.828
3 0.07 0.056 0.825
4 0.136 0.191 0.115 0.838
5 0.151 0.193 0.501 0.22 0.836
6 0.123 0.176 0.408 0.314 0.331 0.808
7 0.254 0.265 0.531 0.401 0.562 0.607 0.824
8
0.006
0.308
0.139
0.441
0.271
0.34
0.308 0.782
9
0.316
0.191
0.116
1.202
0.223
0.316
0.191 0.444 0.837
10
0.053
0.074
0.105
0.244
0.214
0.223
0.074 0.616 0.247 0.824
11 0.481 0.1 0.034 0.225 0.131 0.14 0.166
0.194
0.226
0.026 0.822
12 0.038 0.176 0.042 0.438 0.051 0.159 0.21
0.327
0.438
0.184
0.114 0.864
Note(s): Perceived Enjoyment (PE), Social Relationship (SR), Utilitarian Need (UN), Social Influence (SI), Social Anxiety (SA), Loneliness (LL), Parasocial Relationships
(PR), TikTok Addiction (TA), Technology-Family Conflict (TFC), Technology-Person Conflict (TPC), Technology-Work Conflict (TWC), Life Satisfaction (LS); the square
root of AVE shown on the diagonal
Source(s): Table by authors
addiction
TikTok
Predictors and
outcomes of

Square root of AVE

Table 3.

and correlations
K Direct effects Coefficients Standard deviation (STDEV) T-statistics (jO/STERRj) Results

PE → TA 0.227*** 0.031 5.020 H1: supported

SR → TA 0.140*** 0.035 2.749 H2: supported
UN → TA 0.352*** 0.038 8.721 H3: supported
SI → TA 0.256*** 0.044 5.102 H4: supported
SA → TA 0.356*** 0.046 2.991 H5: supported
LL → TA 0.762*** 0.045 4.074 H6: supported
TA → TFC 0.203*** 0.040 4.423 H8a: supported
TA → TPC 0.401*** 0.037 9.316 H8b: supported
TA → TWC 0.321*** 0.044 4.198 H8c: supported
TFC → LS
0.083** 0.050 3.816 H9a: supported
TPC → LS
0.145*** 0.044 3.589 H9b: supported
TWC → LS
0.100*** 0.060 2.566 H9c: supported

Standard deviation
Moderation effects Coefficients (STDEV) T-statistics (jO/STERRj) Results

PR 3 PE → TA 0.163*** 0.030 3.278 H7a(i):

supported
PR 3 SR → TA 0.138*** 0.041 2.240 H7a(ii):
supported
PR 3 UN → TA 0.067** 0.041 0.268 H7a(iii):
supported
PR 3 SI → TA 0.231*** 0.037 2.396 H7a(iv):
supported
PR 3 SA → TA 0.532*** 0.046 1.099 H7b(i):
supported
PR 3 LL → TA 0.301*** 0.046 2.449 H7b(ii):
supported
Table 4. Note(s): ***p < 0.001, **p < 0.01 and *p < 0.05
Hypotheses tests Source(s): Table by authors

supported. Hypothesis 9 proposed that conflicts have negative influences on life satisfaction. We
found that technology-family conflict (βTFC → LS 5
0.083**, p < 0.01), technology-person conflict
(βTPC → LS 5
0.145***, p < 0.001) and technology-work conflict (βTWC → LS 5
0.100***,
p < 0.001) are negatively related to life satisfaction. H9a, H9b and H9c were supported.
Moreover, this study confirmed each endogenous construct’s predicting power (R2).
Classically, the score of R2 displays the total variance in the endogenous constructs described
by all exogenous constructs. The present outcomes demonstrated 68.4% of the total change
in TikTok addiction, 4.1% in technology-family conflict, 16.1% in technology-person conflict,
10.3% in technology-work conflict and 6.9% in life satisfaction. According to Cohen (1988),
effect size (f2) defines the classifications as 0.02 (small), 0.15 (medium) and 0.35 (large),
respectively. The f2 value (utilitarian need→TikTok addiction) was 0.213, which had the most
significant medium effect. The study’s results had minor to medium effects since other f2
values ranged from 0.005 to 0.192.
We proposed that parasocial relationships positively moderate the links between six
antecedents and TikTok addiction. All variables included in interaction terms were mean-
centered. Table 4 and Figures 3–8 demonstrate the moderation results for each relationship.
We confirmed that parasocial relationships positively moderate the association between
perceived enjoyment (βPR 3 PE → TA 5 0.163***, p < 0.001) and TikTok addiction. When
followers’ parasocial relationships with short video creators are more substantial, the positive
relationship between perceived enjoyment and TikTok addiction is more substantial.
Predictors and
outcomes of
TikTok
addiction

Figure 2.
Path coefficients and
significance
K

Figure 3.
Moderation effects:
PR 3 PE → TA

Likewise, parasocial relationships positively moderate the associations between a social

relationship (βPR 3 SR→TA 5 0.138***, p < 0.001), utilitarian need (βPR 3 UN→TA 5 0.067**,
p < 0.01), social influence (βPR 3 SI→TA 5 0.231***, p < 0.001) and TikTok addiction. H7a was
fully supported. In addition, we found that parasocial relationships play a positive
moderating role in the links between social anxiety (βPR 3 SA→TA 5 0.532***, p < 0.001),
loneliness (βPR 3 LL→TA 5 0.301*, p < 0.001) and TikTok addiction. Therefore, H7b was also
supported.

7. Discussions
The abrupt increase in digitalization has brought about substantial changes in individual
behaviour, and TikTok stands out as one of the most common digital platforms today. With
its charming short videos and addictive features, TikTok has grown an enormous global user
base. However, worries surrounding TikTok excessive usage and its influence on individual
users’ behavior have developed. To broadly recognize the influence of TikTok addiction, it is
authoritative to conduct empirical research that discovers its underlying mechanism on
individual users. Thus, this study empirically validated TikTok addiction research,
highlighting its significance of imminent it through the scientific lens of the SDT. Our
findings illustrated that positive and negative reinforcement mechanisms are responsible for
TikTok addiction. Its addiction can yield various antecedents and outcomes on users’
personalities. Our results found that some users may experience positive effects such as
perceived enjoyment, social relationship, utilitarian need and social influence (Gong et al.,
2019b; Ponnusamy et al., 2020; Zhou, 2017), while others may chance meeting with adverse
outcomes such as life dissatisfaction. Thoughtful differences in the underlying mechanism
 Predictors and
outcomes of
TikTok
addiction

Figure 4.
Moderation effects:
PR 3 SR → TA

are critical to growing a comprehensive understanding of TikTok addiction and its influence
on users.
Moreover, the SDT provides a valued theoretical framework for understanding the
underlying mechanism of TikTok addiction in individual users. Drawing on the SDT theory,
three basic emotional needs determine the individual’s individual autonomy, competence and
relatedness. In the digitalization context, some users may have enlarged independence
through self-expression and imagination on TikTok, which will lead to positive
consequences. Others may notice a weakening in autonomy as they become reliant on the
SNSs platform, subsequent in negative outcomes. Similarly, TikTok can improve individual
users’ sense of capability or weaken it, depending on user experiences. The SDT theory also
highlights the significance of relatedness, signifying that TikTok can advance societal
connections for some individuals while leading to social withdrawal or isolation for others.
Therefore, empirical investigation is necessary to advance a comprehensive understanding
of SNSs addiction (TikTok) and its influence on users. This study can shed light on the
underlying mechanisms contributing to the existing literature and the potential long-term
effects of excessive TikTok use.
Furthermore, it can benefit recognizing the antecedents and consequences and
psychological features of users more prone to negative outcomes related to TikTok
addiction. Our research findings from such research can update the development of evidence-
based interventions and strategies to encourage responsible and healthy TikTok usage. The
results are aligned with prior literature findings (Chen et al., 2020; Kuem et al., 2020). In other
words, people become addicted to TikTok because TikTok can help them increase or reduce
negative moods. Our findings revealed that TikTok addiction plays the main role in creating
K

Figure 5.
Moderation effects:
PR 3 UN → TA

technology conflicts, including technology-family conflict, technology-person conflict and

technology-work conflict. These are consistent with the results in the online social games
context (Gong et al., 2019b). These conflicts can reduce life satisfaction. Moreover, we
confirmed the moderating effects of parasocial relationships. When followers have stronger
parasocial relationships with short video creators, the positive relationship between
perceived enjoyment and TikTok addiction is more robust. These are new findings.
In conclusion, the requirement of TikTok addiction research lies in the diverse
mechanism it has on users’ behavior. The SDT delivers a respected conceptual framework
to recognize these relations, diagnosing that TikTok can have both positive and negative
consequences, depending on individual preferences. Based on SDT, this study advances
insights into TikTok addiction’s underlying mechanisms, identifies potential risks and
progresses interventions to endorse responsible usage. It is crucial to approach TikTok
addiction research with scientific rigor to ensure that our understanding of this
phenomenon aligns with the users’ experiences and the needs to foster a healthy
relationship with the platform.

7.1 Theoretical implications

This work offers various theoretical contributions. First, our research contributes to
technology addiction literature by systematically investigating the antecedents and
outcomes of TikTok addiction. Prior literature on addiction mainly focused on SNSs and
online games (Cao et al., 2018; Gong et al., 2019b, c; Lee et al., 2020; Zheng and Lee, 2016).
Limited research paid attention to TikTok. To the best of our knowledge, our study is among
the first to investigate the antecedents and outcomes of TikTok addiction, filling the literature
 Predictors and
outcomes of
TikTok
addiction

Figure 6.
Moderation effects:
PR 3 SI → TA

gap. In addition, it offers a framework for demonstrating the complete process of addiction,
from the antecedents to addiction and then the negative consequences of the addiction. This
research deepens the comprehensive understanding of TikTok addiction.
Second, this study advances the technology addiction literature by examining two
different formation mechanisms of TikTok addiction: positive and negative reinforcement
mechanisms. To the best knowledge, our study is a unique initiative to integrate the two
mechanisms in the TikTok context. Moreover, this research uses SDT to explain the
formation mechanisms of TikTok addiction, which can advance the understanding of
psychological mechanisms. It also enriches the application of SDT in technology addiction. In
addition, extant studies mainly focused on how belongingness causes positive effects and
rarely examined the adverse effects (Den Hartog et al., 2007; Liu et al., 2020). We contribute to
the technical literature by considering how belongingness can lead to adverse impacts.
Third, this work deepens our understanding of parasocial relationships in the TikTok
context because it is an essential feature of the SNSs. According to Uzuno glu and Kip (2014),
one-sided sensitive associates shaped by individual users in the digital planetary, like
celebrities, influencers or content creators, consider these relationships. In today’s
interrelated technological world, SNSs deliver a platform for users to involve with others
and grow these relationships. Most existing studies demonstrated that parasocial
relationships have direct and positive effects on technology addiction (Baek et al., 2013;
B
erail et al., 2019), ignoring the moderating role in the process of technology addiction. The
moderating role of parasocial relationships in the context of TikTok addiction needs to be
further investigated. This article explores the moderating role of parasocial relationships
during the TikTok addiction process. The significance of parasocial relationships lies in their
K

Figure 7.
Moderation effects:
PR 3 SA → TA

capability to accomplish several emotional and social desires. The findings demonstrate that
followers’ parasocial associations with short video creators can promote the positive effects
of perceived enjoyment of TikTok addiction.
Moreover, SNSs ease establishing and keeping these relationships by providing digital
platforms for the individual user to relate, consume content and occupy with the lives of those
they follow. It provides further insights into the development of technology addiction from
parasocial relationships. Finally, this research empirically validated TikTok addiction’s
positive and dark side and explained the underlying mechanism to the readers and scholars.
This study extends the literature on SNSs addiction and specifically tests the particular
application of addiction on the individual psychological consequences. For instance, Pantic
(2014) found that extreme SNSs consumption can damage one’s mental health. Similarly,
Donnelly and Kuss (2016) researched and found that spending unnecessary time on the
digital platform can contribute to feelings of depression, anxiety and low self-esteem.
Furthermore, the obsessive nature of TikTok, with its unlimited usage and algorithm-driven
content, can disorder sleep designs, impair productivity and contribute to an inactive
lifestyle, further worsening well-being issues. This study specifically empirically examined
the single largest application with a unique idea of providing billions of users with creativity
and entertainment, and it is mandatory to examine the underlying mechanism and its
potential negative effects on individual users.

7.2 Practical implications

We propose numerous practical implications for short video applications and their users.
First, our findings suggest that perceived enjoyment, social anxiety and loneliness can foster
 Predictors and
outcomes of
TikTok
addiction

Figure 8.
Moderation effects:
PR 3 LL → TA

TikTok addiction. TikTok can help users increase happiness or reduce social anxiety and
loneliness. Users may encounter different glitches in real life, such as work pressure,
loneliness, study pressure and test failure. They usually spend substantial time on TikTok to
escape real problems and make themselves happy. Therefore, users must focus on other
social and healthy activities, like family parties, swimming, and running. Users can
communicate with real friends, get social support and reduce anxiety and loneliness. In
addition, users are recommended to participate in parties and other social activities to
make new friends and meet their needs for social relationships. Second, this study indicates
that social influence positively affects TikTok addiction. Hence, users should take action to
reduce abnormal social influence. For example, individuals can temporarily reduce
interaction and communication with friends addicted to TikTok or short video
applications. They can also ask for help from family and friends who do not use TikTok
or short video applications. These important people can supervise users and prevent them
from getting addicted to TikTok or short video applications. Doing so can also lead to positive
social influence. Users will likely follow their behaviours of not using TikTok or short video
applications.
Third, we find that parasocial relationships play a positive moderating role in forming
TikTok addiction. Thus, addicted individuals should be conscious of the contrary influences
of close interaction with short video creators and reduce the time spent viewing their short
videos as soon as possible. We recommend communicating and interacting with real friends.
Family and friends can also persuade addicted users to avoid short video creators
temporarily. Moreover, users should keep their devices away when studying or working.
K Finally, our study shows that TikTok addiction negatively affects family, personal or work
outcomes. Hence, setting up information reminders to remind users about the negative
consequences of short video addiction is crucial. Information reminders can enhance users’
awareness of short video addiction’s dangers and promote personal self-monitoring and self-
regulation. For example, educational institutions should frequently organize activities to tell
students and parents about the serious consequences of excessively using short video
applications (e.g. TikTok). In addition, short video applications should actively provide
reminders about the length of time users have spent on the application and the harmful
effects of excessive use on their health, family and work. It is recommended that short video
applications should develop a time-limit function. Users can set the maximum usage time per
day, the maximum usage time each time, the time that can be used and the time that cannot be
used. Furthermore, binding with friends’ accounts is also necessary so that friends can help
monitor their own usage time. If the time is exceeded, they can control and manage it
remotely.

7.3 Limitations and future research

This research offers various future opportunities for scholars that stem from the limitations.
First, we collected data from a single country (China), which may restrict the generalizability
of the current findings. Forthcoming studies can collect larger samples from other countries
to analyze the cultural differences. Second, we used a cross-sectional survey to test the
hypotheses. Causal relationships among variables cannot be verified. Future studies should
design experiments and use longitudinal data to assess the causality among variables and
obtain a more comprehensive understanding of TikTok addiction. For example, future
research can collect survey data at different times. Third, we did not control the effects of
social desirability bias in this research. TikTok addiction is a negative phenomenon.
Participants may hesitate to show their addictive behaviours, influencing their answers.
Future studies can consider measuring and controlling social desirability bias in the model.
Finally, this study may ignore other key factors affecting TikTok addiction. Additional
antecedents (e.g. personality) need to be explored and tested in future studies to improve the
understanding of TikTok addiction. Future research needs to explain the role of parasocial
relationships further. Moreover, future works can further explore TikTok addiction in
different demographic groups.

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Further reading
Ghazali, E., Mutum, D.S. and Woon, M.-Y. (2019), “Exploring player behavior and motivations to
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constructs and social support on social commerce intentions”, Information Technology and
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Corresponding author
Tahir Islam can be contacted at: kktahir@hotmail.com

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