Smartphone dependency linked to loneliness and depression

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Young people who are hooked on their smartphones may be at an increased risk for depression and loneliness, according to a new study from the University of Arizona.

A growing body of research has identified a link between smartphone dependency and symptoms of depression and loneliness.

However, it’s been unclear whether reliance on smartphones precedes those symptoms, or whether the reverse is true: that depressed or lonely people are more likely to become dependent on their phones.

In a study of 346 older adolescents, ages 18-20, researcher Matthew Lapierre and his collaborators found that smartphone dependency predicts higher reports of depressive symptoms and loneliness, rather than the other way around.

“The main takeaway is that smartphone dependency directly predicts later depressive symptoms,” said Lapierre, an assistant professor in the Department of Communication in the College of Social and Behavioral Sciences.

“There’s an issue where people are entirely too reliant on the device, in terms of feeling anxious if they don’t have it accessible, and they’re using it to the detriment of their day-to-day life.”

In the study, which will be published in the Journal of Adolescent Health, Lapierre and his co-authors focus on smartphone dependency – a person’s psychological reliance on the device – rather than on general smartphone use, which can actually provide benefits.

“The research grows out of my concern that there is too much of a focus on general use of smartphones,” Lapierre said.

“Smartphones can be useful.

They help us connect with others. We’ve really been trying to focus on this idea of dependency and problematic use of smartphones being the driver for these psychological outcomes. ”

Understanding the direction of the relationship between smartphone dependency and poor psychological outcomes is critical for knowing how best to address the problem, said communication master’s student Pengfei Zhao, who co-authored the study with Lapierre and communication doctoral student Benjamin Custer.

“If depression and loneliness lead to smartphone dependency, we could reduce dependency by adjusting people’s mental health,” Zhao said. “But if smartphone dependency (precedes depression and loneliness), which is what we found, we can reduce smartphone dependency to maintain or improve wellbeing.”

The researchers measured smartphone dependency by asking study participants to use a four-point scale to rate a series of statements, such as “I panic when I cannot use my smartphone.”

Participants also answered questions designed to measure loneliness, depressive symptoms and their daily smartphone use. They responded to the questions at the start of the study and again three to four months later.

The study focused on older adolescents, a population researchers say is important for a couple of reasons: First, they largely grew up with smartphones. Second, they are at an age and transitional stage in life where they are vulnerable to poor mental health outcomes, such as depression.

“It might be easier for late adolescents to become dependent on smartphones, and smartphones may have a bigger negative influence on them because they are already very vulnerable to depression or loneliness,” Zhao said.

Given the potential negative effects of smartphone dependency, it may be worth it for people to evaluate their relationship with their devices and self-impose boundaries if necessary, the researchers said.

Looking for alternative ways to manage stress might be one helpful strategy, since other research has indicated that some people turn to their phones in an effort to relieve stress, Zhao said.

New research suggests a person’s reliance on his or her smartphone predicts greater loneliness and depressive symptoms, as opposed to the other way around.

“When people feel stressed, they should use other healthy approaches to cope, like talking to a close friend to get support or doing some exercises or meditation,” Zhao said.

Smartphones are still a relatively new technology, and researchers across the globe continue to study how they’re affecting people’s lives.

Lapierre said now that researchers know that there is a link between smartphone dependency and depression and loneliness, future work should focus on better understanding why that relationship exists.

“The work we’re doing is answering some essential questions about the psychological effects of smartphone dependency,” he said. “Then we can start asking, ‘OK, why is this the case?’”


A smartphone is “a mobile phone that performs many of the functions of a computer, typically having a touch screen interface, internet access, and an operating system capable of running downloaded applications” [1].

These features have made smartphone use/ ownership a prevalent social phenomenon. According to a recent survey conducted by an opinion polling organization (IPSOS-STAT), smartphone penetration across total population in Lebanon has increased tremendously from 36% in 2012 to 70% in 2014, with Lebanon having the second highest growth rate (+34% points) among five Arab countries with available data (Kuwait: +37% points, UAE: +30% points, Saudi Arabia: +16% points, Egypt: +7% points).

In addition, the proportion of smartphone owners with internet access on their device in Lebanon has increased by 16 percentage points between 2012 and 2014 (74% in 2012 to 90% in 2014), the second highest increase among the five Arab countries (UAE: +19% points, Saudi Arabia: +16% points, Kuwait: +12% points, Egypt: – 4% points) [2].

These technological changes have led to a revision in the very definition of addiction for it not only refers to drug or substance abuse, but now also includes behavioral addictions such as gambling, internet gaming, or even excessive smartphone use. For instance, the revised chapter of “Substance-Related and Addictive Disorders” in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) includes a behavior-related condition “pathological gambling” as a diagnosable addictive disorder rather than an “impulse control disorder” in a new category on “behavioral addictions” [3]. In addition, “Internet Gaming Disorder” is listed in DSM-5 section III as a problematic behavior pending more research before considering it as a formal addictive disorder [4].

Although evidence-based research was not sufficient for smartphone addiction to be included in the DSM-5, a growing number of studies are confirming that habitual smartphone use is associated with several addictive characteristics that are analogous to symptoms of substance-use disorder as per DSM-5 including preoccupation, tolerance, inability to control craving, impairment of daily life functions, disregard to harmful consequences, and withdrawal.

A cross-sectional study conducted among a sample of 197 company employees and university students (age range = 18–53 years; mean age = 26.1 years) from South Korea, using Smartphone Addiction Scale (SAS), revealed six smartphone addictive symptoms−daily-life disturbance, positive anticipation, withdrawal, cyberspace-oriented relationship, overuse, and tolerance [5].

Another survey of a nationally representative South Korean sample of 795 school students (elementary to high school), using Smartphone Addiction Proneness Scale (SAPS) for youth, identified four smartphone addictive symptoms − disturbance of adaptive functions, virtual life orientation, withdrawal, and tolerance [6].

Similar findings were reported in studies done in Taiwan and China. Four smartphone-related addictive symptoms − compulsive behavior, functional impairment, tolerance and withdrawal− emerged from a survey of 283 university students from Taiwan (mean age = 22.9 years), using a newly developed Smartphone Addiction Inventory Scale (SPAI) [7]. Likewise, using a composite Smartphone Addiction Index, five smartphone addiction symptoms − disregard of harmful consequences, preoccupation, inability to control craving, productivity loss, and feeling anxious and lost− emerged among a sample of 414 Chinese university students aged 19–26 years [8].

Several other studies have also investigated the prevalence of smartphone addictive behaviors among young age groups. Given that they employed different methods to assess smartphone addiction, it might be difficult to compare prevalence figures reported in these studies. In Asia, a study involving 210 Korean female university students (mean age = 22 years) revealed that 30.5% had high risk to smartphone addiction [9].

Another study done in Korea by the Korean Ministry of Gender Equality and Family in 2013 reported that 17.9% of Korean adolescents showed smartphone addiction [10]. A study conducted among 414 Chinese university students (aged 19–26 years) identified 13.5% of the sample as smartphone addicts [8].

Another study conducted in Turkey revealed that 39.8% of a sample of 319 Turkish university students (mean age = 20.5 years) were excessive smartphone users (had Smartphone Addiction Scale (SAS) scores ≥ median score) [11]. In a single study done in Lebanon, 44.6% of 249 private university Lebanese students (mean age = 20.96 years) were found to be at high risk of smartphone addiction [12]. In the US, among a sample of 200 Stanford university students 10% and 34% acknowledged full addiction and almost addiction to iPhones, respectively [13]. Likewise, 11.2% of 276 African American college students (age range = 17–30) showed high level of smartphone addiction (≥ 90th percentile SAS-SV score) [14].

While few studies examined the independent predictive effect of depression and anxiety on smartphone addiction in college students, they fell short of controlling, at the same time, for multiple sociodemographic, academic, lifestyle, personality traits, religious practice, and smartphone-related variables (age at first use, duration of use per weekday, purpose of using smartphone) in the studied sample [11,1517].

In other words, when investigators adjusted for the effects of confounding variables when assessing the independent contribution of depression or anxiety to smartphone addiction in university students, it was limited to isolated sociodemographic and/ or academic, or smartphone use-related variables.

Given the high penetration rate of smartphone in Lebanon; the association of smartphone use with addiction and undesirable health effects; and the likelihood that smartphone addiction may have depression or anxiety as underlying independent risk factors; hence, it becomes important to quantify smartphone addiction/ smartphone-related addictive symptoms and assess possible contribution of depression or anxiety to smartphone addiction in Lebanese students.

This study aims to 1) assess prevalence of smartphone addiction symptoms, in relation to physical, mental and social health, and 2) investigate whether depression or anxiety, independently, contributes to smartphone addiction level among a sample of Lebanese students, while simultaneously adjusting for other independent variables.

Discussion

Prevalence rates of smartphone-related compulsive behavior, functional impairment, tolerance and withdrawal symptoms were substantial. 35.9% of our sample reported that they felt tired during daytime due to late-night smartphone use, 38.1% of them acknowledged that their sleep quality is decreased, and 35.8% admitted that they slept less than four hours due to smartphone use more than once.

This is in agreement with findings from other studies done among university and high school students. In a sample of 319 Turkish university students, smartphone addiction scores showed significant positive correlation with sleep disturbance, daytime dysfunction, subjective and global sleep quality scores [11].

Likewise, findings from a survey conducted among a convenient sample of 82 mid to high level managers enrolled in MBA classes revealed that smartphone use for work at night had negative effect on daytime work engagement mediated by sleep disruption and morning depletion of self-control resources [22].

A third study carried out among a sample of 362 Swiss high school students found out that adolescents with smartphones had delayed bedtimes and reported significantly more sleep difficulties and reduced sleep duration on weekdays compared to those with conventional mobile phones[23].

Whereas gender, residence, work hours per week, major field of study, academic performance (GPA), lifestyle habits such as smoking and alcohol drinking, and religious practice did not associate with smartphone addiction score; individual’s personality type (type A vs. type B), class (year 2 vs. year 3), smartphone-related variables [age at first use, excessive use of smartphone during a weekday, reason/ purpose of using smartphone (not using smartphone to call family members, entertainment, and other vs. calling friends, texting, reading news, and study-related purposes)], and having depression or anxiety, showed statistically significant associations with smartphone addiction. Using multiple regression analyses, the most powerful independent predictor of smartphone addiction turned out to be excessive use of smartphone during a weekday (5 or more hours during a weekday), followed by depression score, non-use of smartphone to call family members, personality type, use of smartphone for entertainment purposes, and anxiety score.

Association of personality type and smartphone addiction

Individuals with type A personality are more competitive, ambitious, impatient, anxious, aggressive, and more likely to be workaholic. Individuals with type B personality are their counterparts. Type A behavior individuals are more likely to experience high stress level and have higher risk to develop ill health including cardiovascular disease and cancer, compared to type B behavior individuals.

Our finding of a positive independent association of personality type A and smartphone addiction is congruent, by and large, with the results of several other studies which examined the link between personality traits and smartphone addiction.

A survey conducted among a sample of 448 Korean university students revealed a significant positive association between neurotic personality trait and smartphone addiction severity level [10]. In another study surveying 353 Korean college students, both aggression and impulsion scores emerged as significant independent positive predictors of smartphone addiction, with impulsion being a stronger one [15]. Nonetheless, neurotic personality trait did not predict smartphone addiction in an African American sample of 276 college students [14].

We suppose that the positive relationship between personality type A and smartphone addiction severity is both direct and indirect, influenced by perceived high stress level. In a study carried out among a sample of 387 university students from Taiwan, high stress level (emotional, family, interpersonal, academic, or all combined) showed significant positive correlation with smartphone addiction [24]. In another survey of a sample of 274 adults (67.9% students), stress level showed significant positive association with smart device addiction [25].

Associations of depression and anxiety and smartphone addiction

In our sample, depression and anxiety scores emerged as independent positive predictors of smartphone addiction, with depression score being a more powerful predictor compared to anxiety score. Our findings resonate well with prior results from multiple studies which looked at the relationship between psychological traits (depression, anxiety, social phobia, loneliness) and smartphone addiction.

In a sample of 353 Korean college students, depression emerged as a significant independent positive predictor of smartphone addiction [15]. Mood regulation (defined as avoiding/ reducing negative feelings-loneliness, anxiety, depression, stress) had significant positive effect on smartphone addiction among a convenient sample of 394 Chinese university students [17].

Depressive state emerged as an independent predictor of immersion in Internet communication score in a survey of 126 Japanese medical university students [16]. In a survey of 414 Chinese university students, loneliness, which is highly positively associated with depression, emerged as the strongest independent predictor of smartphone addiction score [8].

Likewise, loneliness score showed significant positive correlation with smartphone addiction score and emerged as an independent predictor of cyberspace- oriented relationship score, in a sample of 367 Turkish university students [26]. Mean depression and anxiety scores were significantly higher among high versus low smartphone users, and emerged as independent predictors of smartphone addiction severity as per findings from a survey of 319 Turkish university students [11].

Social interaction anxiety, and social phobia, emerged as independent positive predictors of smartphone addiction in surveys of 276 African American [14], and 367 Turkish university students’ samples [26], respectively.

The link between depression or anxiety and smartphone addiction may not just be established among young adults/ university students; rather it may be applicable to the general adult population. In a mixed sample of 274 adults aged 16–59 years, depression and anxiety had significant positive correlation with smart device addiction [25].

Findings from a study among a sample of 325 Taiwanese adults (age range = 17–97 years), comparable in terms of age and gender to nationally representative sample, revealed a statistically significant positive effect of social interaction anxiety on smartphone-related compulsive use [27].

Study strengths and limitations

While published literature took into account few of the important confounders when examining the independent association between depression/ anxiety and smartphone addiction, our study examined this association while controlling simultaneously for the effects of all these confounding variables (sociodemographic, academic, lifestyle habits, personality type, and smartphone-related variables).In addition, the tools that we employed for assessing smartphone addiction and screening depression and anxiety have been used and were validated among samples of university students.

The study employed a cross-sectional design hence identified significant relationships between tested independent variables and the dependent variable (smartphone addiction) cannot be inferred as causal In addition, data on many tested independent variables were self-reported and may possibly bear some inaccuracies for not wanting to reveal vulnerabilities (even if data collection forms did not bear student’s personal identifiers) or because of recall bias (time spent and reason for using smartphone during a weekday, age at first use of smartphone).

Conclusion

In conclusion, prevalence of smartphone addiction symptoms was substantial among our sample of university students. Several independent risk factors for smartphone addiction emerged including excessive use of smartphone, personality type A, depression, anxiety, and a possible lack of family social support (indicated by not calling family members). We posit that many of the identified risk factors may share an underlying causal variable which is high stress level It could be that young adults with personality type A experiencing high stress level and low mood may lack positive stress coping and mood management techniques and are highly susceptible to smartphone addiction.


Source:
University of Arizona
Media Contacts:
Alexis Blue – University of Arizona
Image Source:
The image is in the public domain.

Original Research: Closed access
“Short-Term Longitudinal Relationships Between Smartphone Use/Dependency and Psychological Well-Being Among Late Adolescents”. Matthew A. Lapierre, Ph.D., Pengfei Zhao, M.A., Benjamin E. Custer, M.A.
Journal of Adolescent Health doi:10.1016/j.jadohealth.2019.06.001.

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