Acta Psychologica 248 (2024) 104405

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Acta Psychologica
journal homepage: www.elsevier.com/locate/actpsy

Exploring the relationship between resilience and internet addiction in

Chinese college students: The mediating roles of life satisfaction
and loneliness
Rui Li a , Wangqian Fu b, * , Yuqian Liang c , Shihan Huang d , Maoyao Xu e , Rui Tu f
a
School of Education, Nanjing University, Nanjing, 210023, China
b
Faculty of Education, Beijing Normal University, Beijing, 100875, China
c
School of Social Development and Public Policy, Beijing Normal University, Beijing, 100875, China
d
School of Education, Beijing Sport University, Beijing, 100084, China
e
School of Psychology, Beijing Language and Culture University, Beijing, 100091, China
f
Faculty of Education, Shenzhen University, Shenzhen, 518060, China

A R T I C L E I N F O A B S T R A C T

Keywords: Internet addiction is of great impact on college students’ academic performance, life quality and mental health.
Resilience Although it’s well documented the association between resilience and Internet addiction among college students,
Internet addiction the mechanism underlying it are not well acknowledged. The study applied resilience scale, the Chinese Internet
Life satisfaction
Addiction Scale, Satisfaction with Life Scale and the third edition of the UCLA Loneliness Scale to explore the
Loneliness
mechanism of action between resilience and Internet addiction in college students by applied questionnaire
Chinese college students
investigation. A total of 813 college students (321 male, Mean age = 22.55) participated in the study. We found
resilience and life satisfaction of college students were negatively correlated with Internet addiction (β = − 0.85,
t = − 21.35, p < 0.001; β = − 0.08, t = − 2.23, p < 0.05), while loneliness was positively correlated with Internet
addiction (β = 0.17, t = 7.42, p < 0.01). Furthermore, mediating analyses showed life satisfaction and loneliness
played mediating role in the relationship between resilience and Internet addiction (β = − 0.90, t = − 58.76, p <
0.001). Measures such as strengthening the construction of college students’ mental health courses to improve
their resilience and life satisfaction, and providing rich community activities to reduce college students’ lone-
liness have been put forward to reduce college students’ Internet addiction.

1. Introduction addiction. Studies show that the detection rate of Internet addiction
among college students is 13.6 % (Hsieh et al., 2019; Yang et al., 2017)
Internet addiction refers to being addicted to the virtual world on the has become one of the important factors affecting the physical and
Internet and being unable to control their online behavior, thus having a mental health and social function of college students (Darnai et al.,
negative impact on individual psychology and behavior (Chern & 2019). Internet addiction usually changes the cognition of college stu-
Huang, 2018). Internet addiction is often considered a “behavioral dents, making them lose interest in things outside the Internet and show
addiction”, which has much in common with pathological gambling and negative mental outlook (Milani et al., 2009; Spada, 2014). Previous
substance use disorders (Chen et al., 2021). Therefore, Internet overuse studies have found that individuals with symptoms of pathological
can be defined as a cognitive control disorder that does not involve Internet use may cause extensive cognitive impairment, and the more
specific drugs. The cognitive ability of Internet addicts, especially the severe the pathological Internet use, the more obvious the impairment of
complex high-level executive function, may be impaired (Yuan et al., cognitive function, and the more prone the individual is to depression,
2017). According to the latest official report released by the China sadness, depression and other adverse emotions (Hwang et al., 2014)
Internet Network Information Center (CNNIC), there are >978 million and can even lead to crime (Song et al., 2015) and a higher risk of suicide
Internet users in China, among which college students are the main (Lin et al., 2014).
group (CNNIC, 2020). College students have a high incidence of Internet The adverse impact of Internet addiction on college students draws

* Corresponding author.
E-mail address: tiffanyfu001@163.com (W. Fu).

https://doi.org/10.1016/j.actpsy.2024.104405
Received 17 December 2023; Received in revised form 24 June 2024; Accepted 11 July 2024
Available online 26 July 2024
0001-6918/© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
R. Li et al. Acta Psychologica 248 (2024) 104405

concerns of the general public (Odacı & Çelik, 2017). It’s of significance of positive psychological quality possessed by an individual, and it is
to understand the mechanism of it, which contributes on reducing and also an ability of an individual to actively cope with difficulties and
blocking the formation of Internet addiction among college students. setbacks, which has a positive impact on an individual’s life satisfaction
According to the cognitive behavior theory, Internet addiction is a dy- (Jia & Wang, 2018). Studies have shown that resilience can positively
namic development process, which is influenced by remote life events, predict individual life satisfaction (Danielsen et al., 2009). In the face of
real environment and the proximal cognitive factors triggered by them difficulties and pressures, resilience can promote individuals to adopt
(Davis, 2001). Incorrect cognition, concept and evaluation can easily positive coping styles, so that individuals can avoid the troubles of
lead to negative emotions, negative attitudes and bad behaviors. It has negative emotions, and thus experience higher life satisfaction (Xu et al.,
been found that with the improvement of mental health level, the rate of 2016). As a positive psychological trait of individuals, an increase in the
mobile phone addiction will be reduced (Babadi-Akashe et al., 2014). level of resilience contributes to an increase in individual positive
Resilience, life satisfaction and loneliness are all closely related to in- emotions and life satisfaction (Dagnall et al., 2019). Therefore,
dividual cognition and psychological structure. Therefore, it is necessary improving the level of resilience of college students can not only help
to explore the impact of mental toughness on Internet addiction based individuals improve their ability to overcome difficulties, but also
on cognitive behavior theory. improve life satisfaction and happiness (Liu et al., 2013). Krause pointed
out that life satisfaction is the psychological satisfaction generated by an
1.1. Resilience and Internet addiction individual’s subjective evaluation based on objective evaluation
(Krause, 2004).
Resilience is a personality trait characterized by the ability to over- According to the theory of loss compensation for Internet addiction,
come and overcome adversity and return to normalcy (Connor & since many psychological needs of college students in real life cannot be
Davidson, 2003), as well as the individual’s good adaptation to life met, they are prone to negative emotions, while the Internet world has
adversity, trauma, tragedy, threat, or other significant stress. It means the characteristics of virtuality and openness, which can bring users a
the dynamic development process of individuals in the face of life events certain sense of satisfaction and belonging (Gao & Chen, 2006). Thus,
and setbacks (Daly, 2020; Scheffers et al., 2020). According to the dy- individuals are more inclined to meet their psychological needs through
namic model of resilience, resilience is an innate ability of individuals. online communication (Gibbs et al., 2006). Relevant studies have found
During the development process, individuals will form internal re- that both family life satisfaction and school life satisfaction significantly
sources such as control, which are crucial as protective factors for the negatively predict college students’ Internet addiction (Zhou et al.,
healthy growth of individuals (Furlong et al., 2009). Studies have found 2020). Life satisfaction is the externalization of individual psychological
that good resilience can help individuals maintain a healthy and stable needs met in reality (Huebner, 2004). Individuals with high life satis-
mental level (Zautra et al., 2010). faction have a stronger reality satisfaction of psychological needs than
In terms of coping with pressure and managing negative emotions, Internet satisfaction, so the probability of Internet addiction is lower
individuals with low level of resilience tend to vent their inner negative than that of individuals with low life satisfaction.
emotions through the Internet world due to lack of control and weak Through the analysis and explanation of the mechanism of psycho-
tolerance (Wang et al., 2014), and escape from various stressful events logical resilience, life satisfaction and Internet addiction, we can further
in real life through the Internet world (Wang et al., 2014), thus gradually clarify how psychological resilience, as a protective factor of Internet
becoming addicted to the Internet world. Some empirical studies have addiction, adjusts individual psychological changes and prevents
revealed the relationship between psychological resilience and Internet Internet addiction. H2: Life satisfaction plays a mediating role in the
addiction (Bozoglan et al., 2013; Ceyhan & Ceyhan, 2008; Wang & Zeng, prediction of resilience and Internet addiction among college students.
2024), existing studies have shown that resilience is closely related to Relevant studies have found that both family life satisfaction and school
Internet addiction (Kubo et al., 2023; Shang et al., 2024), and influ- life satisfaction significantly negatively predict college students’ Internet
encing factors such as family support, interpersonal assistance and addiction (Zhou et al., 2020). Life satisfaction is the externalization of
emotional control in resilience significantly negatively predict Internet individual psychological needs met in reality (Huebner, 2004). In-
addiction among college students (Zhang & Zhang, 2016). Adolescents dividuals with high life satisfaction have a stronger reality satisfaction of
with low mental toughness often have to rely on the Internet for psychological needs than Internet satisfaction, so the probability of
emotional support due to their lack of good problem-solving ability and Internet addiction is lower than that of individuals with low life satis-
management of intimate relationships in real life, which leads to faction. Therefore, H2: Life satisfaction plays a mediating role in the
Internet addiction behaviors (Zhou et al., 2017). prediction of resilience and Internet addiction among college students.
Hypothesis H1 was proposed: resilience negatively predicts Internet
addiction among college students. Although the relationship between 1.3. The mediating role of loneliness
resilience and Internet addiction in college students has been estab-
lished, the underlying mechanisms that explain this relationship are Loneliness is a subjective psychological experience that occurs when
unclear. Therefore, we need further carry out relevant research to individuals feel that they lack satisfactory interpersonal relationships
explore the role of life satisfaction and loneliness. and their needs for interpersonal communication are far from their
actual level of interpersonal communication (Asher & Paquette, 2003).
1.2. The mediating role of life satisfaction It is usually accompanied by negative emotional reactions such as
helplessness, emptiness, boredom, isolation and distress (Ma & An,
Life satisfaction is the overall cognitive assessment of an individual’s 2019). Loneliness occurs when an individual’s current social participa-
living conditions for most of the time or for a certain period of time tion does not match expectations (Russell et al., 2012). Loneliness has
according to the standards chosen by them, and it is an individual’s become an increasingly common social phenomenon, widespread at all
subjective evaluation and judgment of their overall quality of life ages and affecting People’s Daily lives (Twenge et al., 2021). Loneliness
(Uchino et al., 2018). When the living conditions meet the living stan- is associated with individual attentional bias (Bangee et al., 2014),
dards set by the individual, they will be satisfied with their life (Diener, cognitive performance (Kuiper et al., 2020), depression, anxiety, sui-
1984). Life satisfaction is an important indicator reflecting individual cide, and psychosocial dysfunction (Bambra et al., 2020; Matthews
happiness, psychological adaptation and mental health (Headey et al., et al., 2022), sleep disorders, physical dysfunction, hypertension and
1993), and is also a cognitive component and important content of heart disease (Park et al., 2020), etc. It is not unusual for college students
subjective well-being (Diener et al., 1985). to indulge in the Internet world due to strong loneliness (Diehl et al.,
Resilience belongs to the category of positive psychology. It is a kind 2018).

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Regardless of resilience’s status as a stable trait or changeable state, attention of major universities and even the whole society (Odacı &
it has been shown to be an effective and important feature in the pre- Çelik, 2017), and how to prevent Internet addiction among college
diction of recovery and healing from stress and trauma-based conditions students has become a key issue that needs to be solved urgently
(Afifi et al., 2016; Rangel, 2024). Individuals with high levels of resil- (Khazaei et al., 2017). Even though the negative influence of college
ience are able to actively adapt to adversity and recover from challenges students’ Internet addiction is examined, while the psychological
and setbacks, while those with low levels of resilience are less resilient to mechanism among resilience, life satisfaction and loneliness still need to
stress (Rutter, 2012; Zhao et al., 2015). Psychological resilience can be further explored. Besides, most studies pay attention on the internet
effectively resist the negative effects of risks by mobilizing individuals’ addiction among Western college students, while the students in Chinese
positive emotions and creating supportive social networks (Cui et al., university experience different context in the collectivism culture and
2012; Tugade & Fredrickson, 2004). Studies have shown that resilience university management system in China. Their status of internet
can negatively predict the degree of loneliness, and the higher the addiction and the psychological mechanism may contribute to under-
resilience, the lower the degree of loneliness (Eglit et al., 2018; Luo stand in a cross-culture perspective. To address the gaps, this study aims
et al., 2014; Nian & Liu, 2009). to explore the mechanism of action between resilience and Internet
Some empirical studies have revealed the relationship between addiction in Chinese college students, especially the influence of life
loneliness and Internet addiction (Bozoglan et al., 2013; Ceyhan & satisfaction and loneliness. It is expected that the research results can
Ceyhan, 2008; Esen et al., 2013; Odacı & Kalkan, 2010), previous provide some basis for actively blocking Internet addiction and main-
studies have found that an individual’s loneliness significantly positively taining the physical and mental health of Chinese college students.
predicts his Internet addiction, that is, the lonelier an individual feels,
the higher the possibility of Internet addiction (Ostovar et al., 2016). 2. Methods
Individuals who feel strongly lonely and do not develop good social
skills will develop compulsive Internet use behaviors that prevent them 2.1. Participants
from establishing healthy social relationships and interactions in their
daily lives (Kim & Davis, 2009), thus increasing their risk of Internet In this study, online questionnaires were distributed to the heads of
addiction. Therefore, this study hypothesized that H3: loneliness plays a >60 universities in 16 provinces including Beijing, China, and the data
mediating role in the prediction of resilience and Internet addiction of were collected by means of the heads of colleges and universities, and
college students. the students chose their own time. All the students participated in the
survey voluntarily and signed online informed consent. Finally, 813
1.4. The chain-mediated role of life satisfaction and loneliness college students majoring in education, science and engineering
participated in, including 321 male students and 492 female students.
Need to belong theory posits that humans have a fundamental need Among them, freshmen accounted for 35.8 %, sophomores for 15.6 %,
to connect (Baumeister & Leary, 1995). The social perception (e.g. life juniors for 20.8 %, seniors for 3.1 %, graduate students for 24.6 %. The
satisfaction) influenced the psychological status (e.g. loneliness) (Hall age range of college students participating in this survey was 16–26
et al., 2023). Life satisfaction is one of the key indicators for individuals years old (M = 22.55; SD = 1.43). The survey mainly covered college
to evaluate their quality of life and subjective well-being, and it is the students majoring in engineering (29.0 %), education (23.6 %), and
cognitive result of individual profile, evaluation of their overall life science (20.8 %), as well as medical (11.3 %), humanities (5.0 %), and
status or major aspects of life (Huebner, 2004). Individuals with low life interdisciplinary (1.8 %), including undergraduate and graduate
satisfaction tend to adopt negative coping styles when encountering students.
some adverse events (Proctor et al., 2008), and are more likely to have
negative emotions or bad behaviors (Koivumaa-Honkanen et al., 2001; 2.2. Measurements
Sun & Shek, 2012). Some studies have shown that life satisfaction
negatively predicts individual loneliness (Tümkaya et al., 2008; Tuzgöl- 2.2.1. The Loneliness Scale
Dost, 2007). Cohen (2002) believes that happy people with high life In this study, the third edition of the UCLA Loneliness Scale (Uni-
satisfaction are more sociable and thus less lonely. In addition, other versity of California at Los Angels) compiled by Russell et al. (1989) and
studies have pointed out that the negative life experiences experienced translated to Chinese version by Ren et al. (2019) was applied. This scale
by college students will reduce their life satisfaction, which will cause is a self-rating scale, which mainly evaluates the loneliness caused by the
them to fall into negative emotions such as despair and loneliness gap between the desire for social communication and the actual level.
(McCullough et al., 2000). In general, the relationship between life There are 20 items in the scale, including 9 items in reverse score. For
satisfaction and loneliness has been widely concerned, and the example, “Do you often feel in harmony with the people around you?”,
improvement of individual life satisfaction can help reduce the level of “Do you often feel that no one can be trusted?”, “Do you often feel that
loneliness (Ozben, 2013; Tümkaya et al., 2008). you lack a partner?” The scale uses a four-point scale ranging from 1
According to the socio-psycho-physiological model of Internet (never felt this way) to 4 (always felt this way). The higher the score, the
addiction, Internet addiction is a complex social and psychological higher the loneliness. In this study, the Cronbach’s α coefficient of the
phenomenon, which is impacted by social, psychological and physio- total quantity table was 0.888.
logical factors (Liu & Zhang, 2004). It is crucial to determine the in-
fluence mechanism of psychological factors on Internet addiction, 2.2.2. Internet addiction questionnaire
including the protective factor path road. In this study, the Chinese Internet Addiction Scale (CIAS) compiled
by Chen (2003) was adopted, which has been tested well by Su et al.
1.5. The current study (2005). The scale is divided into five dimensions, namely compulsive
symptoms (the compulsive desire to surf the Internet), withdrawal
Existing studies shown internet addiction has many adverse effects symptoms (the sudden forced to leave the computer, prone to frustrated
on the formation and development of college students’ healthy per- emotional repetition), tolerance symptoms (It means that as the expe-
sonality (Wu et al., 2016), which can not only lead to physical problems, rience of Internet use increases, the person must invest more Internet
social isolation, family, psychological and academic problems (Caplan, content or a longer period of time to get the same degree of satisfaction
2005; Chou & Hsiao, 2000; Young, 1998), and even lead to college as the original enjoyment of the Internet), interpersonal health problems
students committing crimes (Song et al., 2015). The adverse impact of (the problems on the relationship with others) and time management
Internet addiction on college students has gradually attracted the problems (it’s hard to control the time spend on Internet), with a total of

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R. Li et al. Acta Psychologica 248 (2024) 104405

26 items. The higher the score, the more serious the degree of addiction 3.2. College students Internet addiction detection rate
to the Internet. For example, “I find myself spending more and more
time online,” “I can’t control my urge to use the Internet.” The ques- Among the measured 813 college students, the total Internet addic-
tionnaire uses a four-point scale from 1 (very inconsistent) to 4 (very tion scores was (57.02 ± 12.10). There were 225 students (26.68 %)
consistent). The higher the score, the more Internet addiction tendency, with Internet addiction scale scores >63 were of Internet addiction.
and the score >63 indicates Internet addiction behavior (Ko et al., Among them, there were 85 male students with a detection rate of 26.48
2009). In this study, the Cronbach’s α coefficient of the total question- % and 140 female students with a detection rate of 28.46 %.
naire was 0.956, the Cronbach’s α coefficient of obsessivity symptom
dimension was 0.834, the Cronbach’s α coefficient of withdrawal 3.3. Comparison of the variables between Internet addiction group and
symptom dimension was 0.838, and the Cronbach’s α coefficient of non-Internet addiction group
tolerance symptom dimension was 0.790. The Cronbach’s α coefficient
of interpersonal health problems was 0.880, and the Cronbach’s α co- According to the discriminant criteria of the Chinese version of the
efficient of time management was 0.824. Internet Addiction Scale (CIAS), the tested college students were divided
into the Internet addiction group (score >63) and the non-Internet
2.2.3. Life Satisfaction Scale addiction group (score less than or equal to 63), and the independent
This study adopted the Satisfaction with Life Scale (SWLS) compiled sample t-test was conducted. The results showed that the scores of
by Diener et al. (1985), and the Chinese version was revised by Xiong resilience, life satisfaction and loneliness were significantly different
and Xu (2009). The scale consists of five items, designed to measure a between the Internet addiction group and the non-Internet addiction
person’s overall cognitive judgment of life satisfaction, and the scale has group, and the total score of resilience and life satisfaction in the
no reverse scoring questions. For example, “For the most part, my life is Internet addiction group was significantly lower than that in the non-
close to my ideal”, “My living conditions are good”, “I am very satisfied Internet addiction group, while the total score of loneliness was signif-
with my life”. The scale uses the subjects’ feelings, reactions and degree icantly higher than that in the non-Internet addiction group (Table 1).
of agreement as evaluation indicators, using a five-point score from 1
(strongly disagree) to 7 (strongly agree). A scale score of 20 was rated as 3.4. Description and correlation among variables
neutral, 19 or below as dissatisfied, and 21 or above as satisfied. In this
study, the Cronbach’s α coefficient of the total volume table was 0.846. The correlation results among the variables are shown in Table 2. It
can be seen that Internet addiction is significantly negatively correlated
2.2.4. Resilience Scale with resilience and life satisfaction, while it is significantly positively
The resilience questionnaire compiled by Gucciardi et al. (2015) and correlated with loneliness. Resilience was positively correlated with life
translated into Chinese by Cao et al. (2021) was adopted. The scale is a satisfaction and negatively correlated with loneliness. Life satisfaction
self-rating scale, which mainly assesses a person’s tendency to cope with was significantly negatively correlated with loneliness. The overall
the demands of stressors. The scale has 8 items. For example, “I can correlation coefficient was between − 0.43 and 0.41 (P < 0.01).
effectively use my knowledge to achieve my goals,” “I continue to strive
for success,” “I am able to express my emotions in the way I want.” This
3.5. The mediation of life satisfaction and loneliness
scale uses a five-point scale from 1 (very inconsistent) to 5 (very
consistent). In this study, the Cronbach’s α coefficient of the total
According to the results of correlation analysis, it was shown that
quantity table was 0.931.
there is a significant correlation between the variables, which conforms
to the premise of mediation effect test. Through the SPSS macro program
2.3. Data analysis
PROCESS Model6 (Model6 is a chain mediation model) compiled by
Hayes (2012), resilience was taken as the independent variable, Internet
SPSS25.0 software and SPSS-PROCESS plug-in were used for data
addiction was taken as the dependent variable, and life satisfaction and
sorting and statistical analysis. Psychological resilience, life satisfaction,
loneliness were taken as the intermediary variables to test whether the
loneliness and Internet addiction were taken as continuous variables,
chain mediation model was valid.
and the total score of each variable was used for description analysis,
The deviation-corrected non-parametric percentile Bootstrap
correlation test and mediation effect test. The mean and standard de-
method was used to test the mediating effect. Samples were repeatedly
viation were used for descriptive analysis. Harman single factor test was
sampled 5000 times to test the above paths, and 95 % confidence
used to test the common method deviation. t-test was used to test the
difference of mental toughness, loneliness and life satisfaction between
Table 1
the Internet addiction group and the non-Internet addiction group. The
Comparison of resilience, life satisfaction and loneliness between Internet
Person product difference correlation method was used to check the
addiction group and non-Internet addiction group (N = 813).
correlation of each variable. The mediating role of life satisfaction and
Variables Internet addiction Non-Internet t P
loneliness was examined by using bias corrected percentile Bootstrap
group addiction group
method (5000 Bootstrap samples were extracted) and Model6 in the
SPSS macro compiled by Hayes. Resilience 28.40 ± 5.46 30.09 ± 5.38 − 3.96 <0.001
Life 18.28 ± 5.33 19.68 ± 5.41 − 3.33 <0.01
satisfaction
3. Results Loneliness 49.20 ± 7.51 44.83 ± 8.50 6.77 <0.001

3.1. Common method bias testing

Table 2
Harman single factor was applied to inspect common method biases. Description and correlation among variables (N = 813).
We applied exploratory factor analysis to extract the characteristic root Variables M SD 1 2 3 4
factor >1, and a total of 19, the biggest factor variance explained at a 1 Internet addiction 57.02 12.10 1
rate of 23.57 % (<40 %). Therefore, there was no significant common 2 Resilience 29.62 5.45 − 0.22** 1
methodological bias in the measurements. 3 Life satisfaction 19.29 5.42 − 0.21** 0.41** 1
4 Loneliness 46.04 8.46 0.34** − 0.43** − 0.43** 1
**
P < 0.01.

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Table 3
The mediation of life satisfaction and loneliness.
Predictive variable Model 1: Internet addiction Model 2: life satisfaction Model 3: loneliness Model 4: Internet addiction

β SE t β SE t β SE t β SE t

Resilience − 0.90 0.03 − 58.76*** 0.92 0.01 67.33*** − 0.54 0.09 − 9.15*** − 0.85 0.07 − 21.35***
Life satisfaction − 0.23 0.12 − 3.81** − 0.08 0.09 − 2.23*
Loneliness 0.17 0.03 7.42***
R2 0.81 0.85 0.57 0.82
F 41.78*** 45.84*** 35.03*** 43.10***

Note: ① All variables in the model are brought into the regression equation with standardized variables; ② n = 813.
*
p < 0.05.
**
p < 0.01.
***
p < 0.001.

Fig. 1. The path load of the mediation of life satisfaction and loneliness.

intervals were estimated. The results were shown in Table 3. OLS not contain 0, showed that the three effects all reached a significant level
regression analysis showed resilience can significantly negatively pre- (Table 4). The relative effect size of the total mediating effect was 5.00
dict Internet addiction (β = − 0.90, t = − 58.76, p < 0.001), and the total %, that was, 5.00 % of the effect of resilience to Internet addiction was
effect of life satisfaction and loneliness is significant (β = − 0.90, t = mediated by the multiple mediating of life satisfaction and loneliness.
− 58.76, p < 0.001), which makes a new contribution to the prediction This study included three specific indirect effects of three paths, “resil-
of Internet addiction. The amount of variation explained increased by 1 ience→ life satisfaction → Internet addiction”, “ resilience → loneliness
%. According to Eqs. (2) and (3), resilience can positively predict life → Internet addiction”, “ resilience → life satisfaction → loneliness →
satisfaction (β = 0.92, t = 67.33, p < 0.001) and negatively predict Internet addiction”, the upper and lower limits of the bootstrap95%
loneliness (β = − 0.54, t = − 9.15, p < 0.001). Eq. (4) shows that life confidence interval of the three indirect effects did not contain 0. The
satisfaction can negatively predict loneliness (β = − 0.23, t = − 3.81, p < indirect effects of the three paths were significant. Among them, the
0.01), and negatively predict Internet addiction (β = − 0.08, t = − 2.23, relative effect values of the three intermediary paths were − 8.75 %,
p < 0.05). Loneliness positively predicted Internet addiction (β = 0.17, t 10.00 % and 3.75 %, respectively. Among the specific indirect effects,
= 7.42, p < 0.01). According to the above results, a chain mediation the relative effect value of the path “resilience → loneliness → Internet
model of resilience and Internet addiction was constructed, as shown in addiction” was higher than the other two specific indirect effects.
Fig. 1.
The results of mediation effect analysis showed that the upper and 4. Discussion
lower limits of bootstrap 95 % confidence interval of the direct effect,
total indirect effect and total effect of resilience on Internet addiction did This study explored the correlation between resilience and Internet
addiction, and the mediating effects of life satisfaction and loneliness on
the relationship between resilience and Internet addiction. The results
Table 4 showed that resilience was positively correlated with life satisfaction,
Total effect, direct effect and intermediate effect (N = 813). while life satisfaction was negatively correlated with Internet addiction,
Effect analogy Effect Boot Boot CI Boot CI Relative resilience was negatively correlated with loneliness, and loneliness was
SE lower limit upper limit effect size positively correlated with Internet addiction. Therefore, the hypothesis
Direct effect − 1.52 0.07 − 1.66 − 1.38 95.00 %
that Chinese college students’ resilience, life satisfaction, loneliness and
Total indirect − 0.08 0.06 − 0.20 − 0.03 5.00 % Internet addiction are related is accepted. In addition, previous studies
effect have paid little attention to the influencing factors of Internet addiction
Total effect − 1.60 0.03 − 1.66 − 1.55 100.00 % among Chinese college students and the influencing mechanism of
Specific
resilience on Internet addiction. Our results provide implications for the
indirect
effects relationship between mental resilience, life satisfaction, loneliness and
Indirect 0.14 0.06 0.03 0.26 − 8.75 % Internet addiction among college students. These results provide po-
effect 1 tential intervention strategies to reduce the probability of Internet
Indirect − 0.16 0.03 − 0.22 − 0.11 10.00 % addiction among Chinese college students.
effect 2
Indirect − 0.06 0.02 − 0.10 − 0.03 3.75 %
effect 3 4.1. The relationship between resilience and Internet addiction
Note: Non-standardized effect sizes are reported; Indirect effect 1 was resilience
→ life satisfaction → Internet addiction; Indirect effect 2 was resilience → This study confirmed that resilience can negatively associated with
loneliness → Internet addiction; Indirect effect 3 is resilience → life satisfaction Internet addiction (H1 was proved), which is consistent with previous
→ loneliness → Internet addiction. studies on the relationship between resilience and Internet addiction

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(Esen et al., 2013; Odacı & Kalkan, 2010). In the face of setbacks and form social cognitive biases that lead to social withdrawal, make nega-
difficulties in life, individuals with worse resilience have weaker ability tive understanding of others’ behaviors more easily, and adopt behav-
to control their emotions, and lack the strength to fight hard and be ioral strategies such as avoidance and withdrawal in interpersonal
positive in adversity. In life, they are more inclined to adopt negative interaction, and rarely provide help to others. That is, loneliness reduces
ways of self-blame, fantasy and rationalization to deal with them. an individual’s tendency to act altruistically (Griese & Buhs, 2013;
Internet addiction is more likely after exposure to the Internet (Zhang & Hawkley & Cacioppo, 2010; Woodhouse et al., 2011). Moreover, lone-
Zhang, 2016). However, adolescents with high psychological resilience liness can also damage an individual’s social cognition and social
may not indulge themselves to escape and vent on the Internet after connection (Baumeister et al., 2002). A number of studies have
encountering negative life events, but actively adopt effective coping confirmed that in order to avoid or alleviate loneliness, students with
methods to solve problems (Campbell-Sills et al., 2006; Pan et al., 2024), high loneliness tend to indulge in the Internet world (Bozoglan et al.,
including (problem-solving skills, emotional regulation). The tolerant, 2013), expecting to satisfy the need of belonging through online social
respectful and supportive attitude of family members can help college networking, so as to temporarily relieve the feeling of being left out by
students develop control and adjustment of mood swings and pessimism, society (Kara et al., 2020). Therefore, the possibility of Internet addic-
establish dialectical views on difficulties and optimistic attitude and tion is higher.
other psychological toughness qualities, which can effectively improve
college students’ correct cognition and active use of the Internet (Sun 4.4. The chain-mediated role of life satisfaction and loneliness
et al., 2012), and avoid them being trapped in the Internet world. In
conclusion, resilience can negatively predict college students’ Internet This study confirmed the negative correlation between life satisfac-
addiction (Ceyhan & Ceyhan, 2008). tion and loneliness, which is consistent with previous studies on the
relationship between life satisfaction and loneliness (Liu et al., 2020). As
4.2. The mediating role of life satisfaction an internal experience and endogenous resource, life satisfaction can
positively predict an individual’s mental health level, and individuals
The results of this study show that life satisfaction plays an inter- with high life satisfaction usually have higher happiness and lower
mediary role in the psychological toughness and Internet addiction of loneliness (Zhang et al., 2022). When college students are more satisfied
college students. Resilience is an individual’s own protective factor with their lives, they tend to have a higher acceptance of the real-life
under stressful situations. It shows that hypothesis 2 is proved. A high environment and interpersonal status, a stronger ability to self-adjust
level of resilience can reduce individual psychological stress and its and self-please, and less pressure, anxiety and loneliness (Park, 2004).
negative effects, and improve individual quality of life and subjective Individuals with low life satisfaction cannot meet their practical and
well-being (Lin & Yang, 2018; Liu & Bu, 2019), resilience can positively psychological needs in daily life in a timely manner, and their sense of
predict individual subjective well-being (Satici, 2016). Since life satis- belonging is reduced and their loneliness is deepened (Hall et al., 2023;
faction is a cognitive component of subjective well-being, psychological Mellor et al., 2008). By helping individuals alleviate the impact of
resilience has a positive predictive and protective effect on life satis- adverse life events through positive cognition, good emotional control,
faction (Chen & Wang, 2014). Some studies have proved that psycho- and external forces such as family support and help from relatives and
logical resilience is closely related to life satisfaction, and the increase of friends, individuals can positively evaluate their living conditions,
psychological resilience can predict the increase of life satisfaction effectively improve life satisfaction and happiness, and thus feel less
(Fredrickson et al., 2008; Hu et al., 2015). For example, a study on lonely (Xie et al., 2014).
minority left-behind children found that, in addition to the significant
positive correlation, interpersonal assistance, positive cognition and 5. Limitations
family support in psychological resilience factors can significantly pre-
dict the life satisfaction of minority left-behind children (Dong & Zhang, There were still some limitations in the current study. First, all
2013a, 2013b). Individuals with high life satisfaction are hardly questionnaires used in this study rely on self-reported questionnaires,
addicted to the online world and are less likely to become addicted to the which may have potential bias on the sample representativeness and
Internet (Bozoglan et al., 2013). This is because individuals with high social desirability effect. Further research could consider using multiple
life satisfaction can have more positive cognition and evaluation of the methods or gathering multiple sources to reduce these biases. Second,
external world, and have more harmonious interpersonal relationship the study is a cross-sectional design, which makes it difficult to clarify
and problem-solving ability (Martin & Dowson, 2009; Proctor et al., causal or temporarily correlated relationships between variables.
2008), can harvest more positive emotional experiences in the real Therefore, we should focus on the longitudinal study of this subject in
world (She et al., 2019; Wang & Cai, 2019), less use of the Internet to the future.
reduce their psychological pressure.
6. Practical implication
4.3. The mediating role of loneliness
The findings of this study have important implications for college
The results of this study show that loneliness plays a mediating role students with low levels of resilience and those involved in Internet
in resilience and Internet addiction of college students. As a protective addiction. First of all, resilience is an important predictor of Internet
factor for mental health, resilience helps individuals better adapt to addiction (Bozoglan et al., 2013), and it’s important to strengthen the
pressure and frustration, and can effectively reduce individual negative mental health courses to learn and grow from setbacks. It is necessary to
emotions (Bitsika et al., 2013). When an individual’s level of psycho- improve emotional regulation ability (Webb et al., 2012), promote
logical resilience is low, he or she will perceive more pressure and will positive personality (Zhang et al., 2021), develop resilience, and
not actively seek help from the outside world, which will make it diffi- improve self-efficacy (Caprara et al., 2020). Improving college students’
cult to resolve negative emotions and lead to loneliness (Anyan & resilience, reducing stressful life events (Wei et al., 2018) and improving
Hjemdal, 2016). Improving the level of individual resilience can help academic performance (Gong et al., 2021) can reduce Internet addic-
individuals effectively reduce their negative emotion level (Liu & Bu, tion. Secondly, universities can provide various community activities to
2019; Nam et al., 2016), when an individual has fewer negative emo- enhance the social connection with other and reduce college students’
tions, the communication with the outside world will gradually increase, sense of alienation from others (Qiu & An, 2012), which is an effective
which will make the individual feel less lonely (Lijster et al., 2018). way to reduce loneliness of college students and protect them from
According to the loneliness model, loneliness will cause individuals to Internet addiction.

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Further Reading
satisfaction in junior Middle School students: The mediating role of psychological
resilience. Chinese Journal of Clinical Psychology, 22(4), 676–679. Chen, S., Weng, L., Su, Y., Wu, H., & Yang, P. (2003). Development of the Chinese
Xiong, C. Q., & Xu, Y. L. (2009). Reliability and validity of the satisfaction with life scale Internet Addiction Scale and its psychometric characteristics. Chinese Journal of
for Chinese demos. China Journal of Health Psychology, 17(8), 948–949. Psychology, 45(3), 279–294.
Xu, M., Wan, P., & Yang, X. (2016). Correlation between positive cognitive emotion
regulation of mental resilience and suicidal ideation in left-behind middle school
students. Modern Preventive Medicine, 22, 4143–4146.