Are you Addicted to Your Smart Phone?

Wednesday, May 15, 2024
by Dylan Tan (3rd Year UWaterloo Student and Smartphone Addiction Researcher)

There are close to 5 billion smartphone users worldwide (Statista, 2024). The average person spends 4 hours a day on their phone (Statista, 2023), and almost half of all smartphone users describe themselves as having a smartphone addiction (Ratan et al., 2022). Unsurprisingly, almost all university students have a smartphone (Huey & Giguere, 2023). In people aged 25 and under, 25% of them meet the criteria for problematic smartphone usage (Sohn et al., 2019).

You’d be hard pressed to find anyone that has never spent too much time on their phone. 71% of people spend more time on their phones than with their romantic partner (SellCell, 2021). As developers get better and better at gaining and keeping our attention, smartphone addiction has become a modern epidemic.

student with smartphone

What does smartphone addiction look like?

Some symptoms of smartphone addiction are:

  • Knowingly or unknowingly spending too much time on a phone; lying to others or yourself about your screen-time
  • Missing out on life events or opportunities because of your phone
  • Your sleep is affected by phone use
  • Using your phone as a means to escape (Addiction Center, n.d.; Parasuraman et al., 2017)

Time spent on your phone is an imperfect measure as to whether you are addicted. You can be addicted if you spend 2 hours on your phone a day or 24 (Panova & Carbonell, 2018). What’s most important is the effect it has on your life and mental wellbeing. 


What are the different types of addiction?

Researchers have narrowed down 5 categories for smartphone addiction (Brand et al., 2016; Mehmood et al., 2021):

  1. Virtual Relationships: Some people become obsessed with online relationships developed through social media platforms. Their obsession with their online persona leads to the neglect of real-world connections.  A negative by-product of the ability to recreate yourself is “catfishing” (using someone else’s image and information to create a fake profile), which makes-up 1 out of every 7 online profiles (Sharma, 2023).
  2. Information Overload: the amount of knowledge and information online is incredible, and it’s easy to feel like you’re missing or not up to date on current events. This can result in constant, sometimes mindless, scrolling. (Arnold et al., 2023; Gupta & Sharma, 2021; Brand et al., 2016)
  3. Gaming Addiction: League of Legends, RPGs, and Mobile games take advantage of unpredictable reinforcement and reward schedules, it’s hard to predict when you will level up or beat the “boss” so you keep playing (James et al., 2016).  Similar reinforcement schedules occur in slots, which use algorithms similar to slot machines in casinos - the most addictive type of game interface (Dixon et al., 2011; MacLin et al., 2007). People play online games for a variety of reasons, but the most dangerous form is gambling. Sara Ahmed, a researcher in the University of Waterloo’s Gambling Lab explored how social media platforms are used as a way to escape (Ahmed & Dixon, 2023). Here the scroll features present endless new content tailored to your interests, reliably capturing your attention, and increasing the time you spend scrolling (Ahmed & Dixon, 2023).
  4. Net Compulsions: shopping addictions, gambling, or trading are all examples of this. Winning or acquiring new items creates a dopamine release which, combined with the ease of doing everything in the palm of your hand, makes it difficult to disengage even when facing horrible financial loss (Li et al., 2022; Gainsbury, 2015).
  5. Cybersex Addiction: this involves use of online pornography, adult websites, or sexual fantasy chatrooms (Young, 2008). This can come from a place of dissatisfaction with one’s intimate relationships or the ability to remain anonymous while exploring one’s fantasies (Snagowski & Brand, 2015). The addictive aspect lies in the constant search for new and more stimulating content, which can result in a cycle that is hard to break (Weinstein et al., 2015).  The constant influx of these type of media can damage one’s body image, harm relationships, and shatter normal expectations of sexual behaviour (Weinstein et al., 2015).

Some of the current research findings

Research has shown physiological differences in people struggling with smartphone addiction; differences that are normally found in individuals with substance use disorders (Seo et al., 2020; Haynes, 2018). Although not as intense as say a hit of cocaine, the underlying reward mechanisms that trigger your dopamine pathways are similar (Sharma et al., 2020).

Unlike drugs or alcohol, smartphones are readily available and can be accessed at any time, and anywhere. This ease of access is one reason that makes this addiction so pervasive (Ahmed & Dixon, 2023), altering brain chemistry and causing horrible withdrawal symptoms when users abstain (Hartogsohn & Vudka, 2023).

One study explored the effects of abstaining from Instagram for one week. Researchers found that women who abstained from Instagram had a significant increase in life satisfaction, and those who tended to make social appearance comparisons saw an increase in positive affect (Fioravanti et al., 2020).

While there is still much to learn about smartphone addictions, researchers have isolated a number of problems that are caused, and even reinforced, by it.

  1. Poorer Grades: studies have shown that having a smartphone addiction negatively influences your GPA (Sunday et al., 2021).
  2. Poorer Sleep: many people addicted to their phones sleep less and more irregularly than their peers, there are some extreme cases of individuals being awake for over 48 hours due to phone misuse. University aged students should be getting 7-9 hours of sleep a night (Hershner & Chervin, 2014). But, over half of students sleep less than that (Estevan et al., 2021). Come exam time, we see those rates fall even further. Poor quality sleep can lead to weight gain, shorter lifespan, and increased rates of depression (Hershner & Chervin, 2014).
  3. Depression & Anxiety: phones can help individuals escape stress in the short-term. However, excessive phone use ultimately exacerbates depression and anxiety (Shoukat, 2019).

flowers with butterflies

*For those interested, CBT is available for free to students through Counselling Services, and to employees through the Employee Assistance Program and through the Homeweb.ca online CBT course. Both studentsand employee extended benefit plans also cover some counselling. BounceBack Ontario offers free online support for individuals 15+.


Do you have an idea or article you'd like to share? We'd like to hear from you. Forward your inquiry to the Community Wellness Team.


Common Treatment Approaches

One possible intervention is Cognitive Behavioural Therapy (CBT*), which is largely considered the first line of psychological treatment (Stevens et al., 2019). One study found significant improvement in self-esteem and phone addiction after CBT (Farjantoky et al., 2020). For gaming addiction, a study noted that CBT provided only short-term benefits and needed to be coupled with other therapies like music therapies to see improvements (Bong et al., 2021).

However, CBT is not for everyone. Luckily there are alternatives. Online support groups like ITAA (Internet Technology Addicts Anonymous) follow the same 12 step program as Alcoholics Anonymous (AA) groups, and have been show to be highly effective for many individuals (Erikson, 2020).

Another approach include setting your phone to grayscale mode to reduce the allure of applications on your phone  Turning off push notifications has also been effective in reducing phone use (Kim et al., 2016).

About Dylan Tan

Dylan Tan

Dylan Tan is a 3rd year student here at the University of Waterloo majoring in psychology with a minor in computer science. As a member of Dr. Mike Dixon’s Gambling Research Lab, Dylan has been given the opportunity to research gaming and gambling addictions, and specifically what we call the dark flow state. Dark flow is described as a pleasurable state of peak immersion while gaming or gambling.  In this state time perception becomes skewed (while intending to play for 10 minutes, 2 hours may go by unnoticed).  In flow states like painting, the painter is control of keeping themselves on task.  In dark flow, it is the external device/game that keeps your attention locked in. Dylan is currently writing a paper that examines the effects of audio and visual synchronization on dark flow.

Dylan’s involvement in the gambling and addiction spaces has helped him to recognize his own addictive behaviours and smartphone addiction. This inspired him to found his start-up Ceritas, through Conrad School of Entrepreneurship and Business.  This platform provides a personalized roadmap to assist people struggling with smartphone addiction. For more information about his start-up and research, please feel free to email Dylan directly.

Citations - Smartphone Addictions

Ahmed, S., & Dixon, M. J. (2023). Instagram, Depression, And Dark Flow – Using Social Media as a Maladaptive Coping Mechanism (SSRN Scholarly Paper 4391734). https://doi.org/10.2139/ssrn.4391734

Arnold, M., Goldschmitt, M., & Rigotti, T. (2023). Dealing with information overload: A comprehensive review. Frontiers in Psychology, 14, 1122200. https://doi.org/10.3389/fpsyg.2023.1122200

Bong, S. H., Won, G. H., & Choi, T. Y. (2021). Effects of Cognitive-Behavioral Therapy Based Music Therapy in Korean Adolescents with Smartphone and Internet Addiction. Psychiatry Investigation, 18(2), 110–117. https://doi.org/10.30773/pi.2020.0155

Brand, M., Young, K. S., Laier, C., Wölfling, K., & Potenza, M. N. (2016). Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neuroscience and Biobehavioral Reviews, 71, 252–266. https://doi.org/10.1016/j.neubiorev.2016.08.033

Causes and Signs of Cybersex Addiction—Sex Addiction Treatment Center | Porn Addiction Rehab | Sexual Recovery | Los Angeles CA. (2011, September 20). Sex Addiction Treatment Center |  Porn Addiction Rehab | Sexual Recovery |  Los Angeles CA. https://www.sexualrecovery.com/blog/sexual-addiction-recovery/cybersex-addiction/signs-of-cybersex-addiction/

Dixon, M. J., Harrigan, K. A., Jarick, M., MacLaren, V., Fugelsang, J. A., & Sheepy, E. (2011). Psychophysiological arousal signatures of near-misses in slot machine play. International Gambling Studies, 11(3), 393–407. https://doi.org/10.1080/14459795.2011.603134

Dong, J., Li, Y., Qu, Y., Xu, C., & Ji, H. (2024). Heterogeneity in Mobile Phone Addiction Among University Freshmen and its Relationship with Psychological Resilience: A Person-centered Approach. International Journal of Mental Health and Addiction. https://doi.org/10.1007/s11469-024-01295-z

Estevan, I., Sardi, R., Tejera, A. C., Silva, A., & Tassino, B. (2021). Should I study or should I go (to sleep)? The influence of test schedule on the sleep behavior of undergraduates and its association with performance. PLoS ONE, 16(3), e0247104. https://doi.org/10.1371/journal.pone.0247104

Farjantoky, B., Sunawan, S., & Mulawarman, M. (2020). The Effects of Cognitive-Behavioral Counseling on Self-esteem and the Tendency of Mobile Phone Addiction. Islamic Guidance and Counseling Journal, 3, 1–8. https://doi.org/10.25217/igcj.v3i1.625

Fioravanti, G., Prostamo, A., & Casale, S. (2020a). Taking a Short Break from Instagram: The Effects on Subjective Well-Being. Cyberpsychology, Behavior and Social Networking, 23(2), 107–112. https://doi.org/10.1089/cyber.2019.0400

Fioravanti, G., Prostamo, A., & Casale, S. (2020b). Taking a Short Break from Instagram: The Effects on Subjective Well-Being. Cyberpsychology, Behavior, and Social Networking, 23(2), 107–112. https://doi.org/10.1089/cyber.2019.0400

Gainsbury, S. M. (2015). Online Gambling Addiction: The Relationship Between Internet Gambling and Disordered Gambling. Current Addiction Reports, 2(2), 185–193. https://doi.org/10.1007/s40429-015-0057-8

Gupta, M., & Sharma, A. (2021). Fear of missing out: A brief overview of origin, theoretical underpinnings and relationship with mental health. World Journal of Clinical Cases, 9(19), 4881–4889. https://doi.org/10.12998/wjcc.v9.i19.4881

Hartogsohn, I., & Vudka, A. (2023). Technology and addiction: What drugs can teach us about digital media. Transcultural Psychiatry, 60(4), 651–661. https://doi.org/10.1177/13634615221105116

Haynes, T. (2018, May 1). Dopamine, Smartphones & You: A battle for your time. Science in the News. https://sitn.hms.harvard.edu/flash/2018/dopamine-smartphones-battle-time/

Hershner, S. D., & Chervin, R. D. (2014). Causes and consequences of sleepiness among college students. Nature and Science of Sleep, 6, 73–84. https://doi.org/10.2147/NSS.S62907

Huey, M., & Giguere, D. (2023). The Impact of Smartphone Use on Course Comprehension and Psychological Well-Being in the College Classroom. Innovative Higher Education, 48(3), 527–537. https://doi.org/10.1007/s10755-022-09638-1

Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model—PubMed. (n.d.). Retrieved April 24, 2024, from https://pubmed.ncbi.nlm.nih.gov/27590829/

James, R. J. E., O’Malley, C., & Tunney, R. J. (2016). Why are Some Games More Addictive than Others: The Effects of Timing and Payoff on Perseverance in a Slot Machine Game. Frontiers in Psychology, 7, 46. https://doi.org/10.3389/fpsyg.2016.00046

Jiang, Q., Huang, X., & Tao, R. (2013). Chapter 81 - Internet Addiction: Cybersex. In P. M. Miller (Ed.), Principles of Addiction (pp. 809–818). Academic Press. https://doi.org/10.1016/B978-0-12-398336-7.00081-4

Kim, S.-K., Kim, S.-Y., & Kang, H.-B. (2016). An Analysis of the Effects of Smartphone Push Notifications on Task Performance with regard to Smartphone Overuse Using ERP. Computational Intelligence and Neuroscience, 2016, 5718580. https://doi.org/10.1155/2016/5718580

Li, H., Ma, X., Fang, J., Liang, G., Lin, R., Liao, W., & Yang, X. (2022). Student Stress and Online Shopping Addiction Tendency among College Students in Guangdong Province, China: The Mediating Effect of the Social Support. International Journal of Environmental Research and Public Health, 20(1), 176. https://doi.org/10.3390/ijerph20010176

MacLin, O. H., Dixon, M. R., Daugherty, D., & Small, S. L. (2007). Using a computer simulation of three slot machines to investigate a gambler’s preference among varying densities of near-miss alternatives. Behavior Research Methods, 39(2), 237–241. https://doi.org/10.3758/bf03193153

Mehmood, A., Bu, T., Zhao, E., Zelenina, V., Alexander, N., Wang, W., Siddiqi, S. M., Qiu, X., Yang, X., Qiao, Z., Zhou, J., & Yang, Y. (2021). Exploration of Psychological Mechanism of Smartphone Addiction Among International Students of China by Selecting the Framework of the I-PACE Model. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.758610

merickso@stanford.edu, M. E. M. E. is a science writer in the O. of C. E. her at. (2015, October 1). Alcoholics Anonymous most effective path to alcohol abstinence. News Center. http://med.stanford.edu/news/all-news/2020/03/alcoholics-anonymous-most-effective-path-to-alcohol-abstinence.html

Panova, T., & Carbonell, X. (2018). Is smartphone addiction really an addiction? Journal of Behavioral Addictions, 7(2), 252–259. https://doi.org/10.1556/2006.7.2018.49

Parasuraman, S., Sam, A. T., Yee, S. W. K., Chuon, B. L. C., & Ren, L. Y. (2017). Smartphone usage and increased risk of mobile phone addiction: A concurrent study. International Journal of Pharmaceutical Investigation, 7(3), 125–131. https://doi.org/10.4103/jphi.JPHI_56_17

Phone Addiction: Warning Signs And Treatment. (n.d.). Addiction Center. Retrieved April 24, 2024, from https://www.addictioncenter.com/drugs/phone-addiction/

Ratan, Z. A., Parrish, A.-M., Alotaibi, M. S., & Hosseinzadeh, H. (2022). Prevalence of Smartphone Addiction and Its Association with Sociodemographic, Physical and Mental Well-Being: A Cross-Sectional Study among the Young Adults of Bangladesh. International Journal of Environmental Research and Public Health, 19(24), 16583. https://doi.org/10.3390/ijerph192416583

Seo, H. S., Jeong, E.-K., Choi, S., Kwon, Y., Park, H.-J., & Kim, I. (2020). Changes of Neurotransmitters in Youth with Internet and Smartphone Addiction: A Comparison with Healthy Controls and Changes after Cognitive Behavioral Therapy. AJNR: American Journal of Neuroradiology, 41(7), 1293–1301. https://doi.org/10.3174/ajnr.A6632

Sharma, B., Sharma, P., & Kumar, P. (2020). SMARTPHONE IS IT “BEHAVIOUR ADDICTION OR SUBSTANCE ABUSE DISORDER”: A REVIEW TO FIND CHEMISTRY BEHIND. 12, 1000. https://doi.org/10.13040/IJPSR.0975-8232.12(1).57-64

Sharma, S. (n.d.). Catfishing: The Truth About Online Deception. 10(2).

Shoukat, S. (2019). Cell phone addiction and psychological and physiological health in adolescents. EXCLI Journal, 18, 47–50.

Should I study or should I go (to sleep)? The influence of test schedule on the sleep behavior of undergraduates and its association with performance—PMC. (n.d.). Retrieved April 24, 2024, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7946303/

Snagowski, J., & Brand, M. (2015). Symptoms of cybersex addiction can be linked to both approaching and avoiding pornographic stimuli: Results from an analog sample of regular cybersex users. Frontiers in Psychology, 6, 653. https://doi.org/10.3389/fpsyg.2015.00653

Sohn, S. Y., Rees, P., Wildridge, B., Kalk, N. J., & Carter, B. (2019). Prevalence of problematic smartphone usage and associated mental health outcomes amongst children and young people: A systematic review, meta-analysis and GRADE of the evidence. BMC Psychiatry, 19(1), 356. https://doi.org/10.1186/s12888-019-2350-x

Staff, S. (2021, February 11). Smartphone Relationship Survey: 71% of People Spend More Time With Their Phone Than Their Romantic Partner. SellCell.Com Blog. https://www.sellcell.com/blog/smartphone-relationship-survey/

Statista. (2024). Number of smartphone users 2014-2029. Retrieved April 22, 2024, from https://www.statista.com/forecasts/1143723/smartphone-users-in-the-world

Statista. (2023). Time spent with nonvoice activities on mobile phones every day in the United States from 2019 to 2024. Retrieved April 22, 2024, from https://www.statista.com/statistics/1045353/mobile-device-daily-usage-time-in-the-us/

Stevens, M. W. R., King, D. L., Dorstyn, D., & Delfabbro, P. H. (2019). Cognitive-behavioral therapy for Internet gaming disorder: A systematic review and meta-analysis. Clinical Psychology & Psychotherapy, 26(2), 191–203. https://doi.org/10.1002/cpp.2341

Su, P., & He, M. (2024). The mediating role of loneliness in the relationship between smartphone addiction and subjective well-being. Scientific Reports, 14(1), 4460. https://doi.org/10.1038/s41598-024-54546-3

Sunday, O. J., Adesope, O. O., & Maarhuis, P. L. (2021). The effects of smartphone addiction on learning: A meta-analysis. Computers in Human Behavior Reports, 4, 100114. https://doi.org/10.1016/j.chbr.2021.100114

van Deursen, A. J. A. M., Bolle, C. L., Hegner, S. M., & Kommers, P. A. M. (2015). Modeling habitual and addictive smartphone behavior: The role of smartphone usage types, emotional intelligence, social stress, self-regulation, age, and gender. Computers in Human Behavior, 45, 411–420. https://doi.org/10.1016/j.chb.2014.12.039

Weinstein, A. M., Zolek, R., Babkin, A., Cohen, K., & Lejoyeux, M. (2015). Factors Predicting Cybersex Use and Difficulties in Forming Intimate Relationships among Male and Female Users of Cybersex. Frontiers in Psychiatry, 6. https://doi.org/10.3389/fpsyt.2015.00054

Yip, S. W., Kiluk, B., & Scheinost, D. (2020). Toward addiction prediction: An overview of cross-validated predictive modeling findings and considerations for future neuroimaging research. Biological Psychiatry. Cognitive Neuroscience and Neuroimaging, 5(8), 748–758. https://doi.org/10.1016/j.bpsc.2019.11.001

Young, K. S. (2008). Internet Sex Addiction: Risk Factors, Stages of Development, and Treatment. American Behavioral Scientist, 52(1), 21–37. https://doi.org/10.1177/0002764208321339