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Cellphones have come a long way from the two pound objects they use to be. They have evolved into a “tiny computer” that fits into a pocket and weighs only a few ounces. The use of smartphones has become an integral part of our lives.
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We use smartphones to keep connected with our families, to read the news, perform calculations and even to measure our heart rate as well as for entertainment purposes like streaming movies and music.
The term “smartphone” generally refers to a phone that has a touchscreen, internet access and performs many functions that a computer does as well.
The Pew Research Center found that 77% of Americans own a smartphone, out of the 95% that own a cellphone of any type. The age group with the highest percentage of owned smartphones is from ages 18-24 with a total of 94%. The number of Americans who own a smartphone has increased 35% since 2011. Since over half of the American population now own a smartphone, it is important to find out what features of a smartphone make it addicting since they have become such an integral part of our lives.
With so many Americans using smartphones, it is only obvious that new problems would arise like smartphone dependency. There are a few studies that focus on smartphone and application addiction. Personality can also play a role in the way we use our cellphones. Certain types of individuals with certain personalities tend to use their smartphones more along with the use of different applications (Stachl et al.
2017).
Kim, Chun and Lee (2013) examined smartphone adoption behavior among American college students. Their purpose was to examine participant’s phone usage behavior by combining innovation diffusion theory, the technology acceptance model, the value-based adoption model, and the social influence model. Innovation diffusion theory is a theory that is commonly used to predict how successful new technology will be. The technology acceptance model provides a methodological and strategic base for investigating technology adoption.
The value-based adoption model is the idea that perceived price and value play a role in the way college students use their devices. The social influence model is the idea that individuals let their observation of other’s influence the way they perceive their smartphone usage. All of these models played a critical role in determining the factors that influence smartphone usage.
Kim, Chun, and Lee (2013) gave participants an online survey that they were able to submit anonymously. The survey was conducted at a large university in New York for three months. Participants were gathered from an introduction communication class. These students were given extra credit for the class because of their participation. At the end of the study only 354 samples were valid. The study had 171 females and 183 males. The participants ages ranged from 18-56 years old. The questions that were asked were from the personal innovativeness questionnaire from Olmsted and Chang’s (2006) study.
The result of this study was that college smartphone users perceive cellphones as a great investment as well as a symbolic sign of their timely integration to technology.
The focus of Stachl et al’s. (2017) study was to predict the frequency and level of use of smartphones by measuring personality traits, intelligence and demographics. Stachl et al. (2017) recruited 87 women and 50 men, via social media used on campus like Blackboard, school forums, discussion boards, and flyers. The study was conducted in two stages. During the first stage, participants met in a lab setting and were given an informed consent, completed a personality inventory, subscales of the Intelligence Structure Battery, and a demographic questionnaire. A logging application was also installed on the participants cellphone. The application logged frequencies and usage of the participants cellphones for 60 days. The application was also able to work in the background of the phone, so participants no longer had to do anything else to their cellphones. Throughout the days, the data from the application was uploaded to their servers and stored. After 60 days, the participants went back to the lab to receive their compensation and the application data was stored one last time on the servers.
The results from Stachl et al’s. (2017) study show that personality, intelligence and demographics can predict mobile app usage and frequencies. They found that variations in extraversion, conscientiousness, agreeableness, intelligence, gender and age were associated with both increased and decreased usage of smartphones. For example, participants with an extraversion personality were found to use their cellphone more because they used more applications that were related to calls, photography and social media. The conscientiousness trait is a predictor trait for gaming and entertainment apps. Highly conscientious people tend to not have a lot of gaming or entertainment apps.
In conclusion, this study shows how different individual personalities can affect how we use cellphones and other technology. They found that extraversion, agreeableness, and conscientiousness were good predictors for mobile phone usage (Stachl et al, 2017).
Stachl et al’s (2017) study was conducted with the assumption that addiction to mobile phones is real. The next study focuses on the question of whether smartphone addiction meets the criteria for addiction. Panova and Carbonell (2018) investigated addiction to technology, more specifically smartphone addiction. Their specific goal was to review the literature already available on the topic of smartphone addiction and to determine if such a disorder exists. For substance addiction and smartphone addiction to be comparable they must share the same addiction symptoms of mood modification, tolerance, salience, withdrawal symptoms, conflict and relapse. If the level of harm is not severe then a problem cannot be considered an addiction, but a “problematic behavior” according to Panova and Carbonell (2018).
Panova and Carbonell’s conclusion was that because of the vague criteria for smartphone addiction and because of the lack of physical and psychological consequences associated with addiction, smartphone addiction does not exist. Even though similarities exist between actual addictions and high use of smartphones, the level of severity impairment is low for cellphone use. Level of impairment is an important factor when determining if someone indeed has an addiction or if their behavior is just problematic. They also gave the example of the problematic behavior of nail biting, and how it fits all the criteria for addiction but just because it fits the criteria it does not make it an addiction, but a problematic behavior.
Under the criteria of physical consequences, they found no serious impairments, besides “mild tendinitis.” It is also important to note that, universities have not reported the need to provide a psychological treatment to “phone addicts,” which also means that the severity of impairments are not high at all when compared to drug addiction. If students were suffering severely from smartphone usage, universities would feel compelled to make some help available. Panova and Carbonell did state that smartphone users found themselves thinking about their phones constantly, when they were not using them. They also state that the emotional stress that is felt when a smartphone is missing is not abnormal since a device could contain sensitive information. This would not be considered “withdrawal.”
High levels of smartphone use are however correlated with mental health illnesses like anxiety and depression according to Panova and Carbonell (2018). The fear of missing out and the need for human touch are elements that can explain the correlation between anxiety and depression and problematic smartphone use (Elhai, Levine, Dvorak, & Hall 2016). In conclusion, Panova and Carbonell found that the methodologies, questionnaires, and definitions used across different studies lacked inter-rater reliability. They believe that “addiction” is not the correct term to use when discussing “smartphone addiction.”
Davazdahemami, Hammer, and Soror (2016) attempted to determine whether it is the mobile devices themselves or their applications that encourage addiction in consumers. They first began with properly defining their concepts. They defined mobile phone addiction as “a psychological state of maladaptive dependency on the use of a mobile phone to such a degree that some of the following six behavioral addiction symptoms arise to any degree: salience, conflict, withdrawal, relapse, tolerance, and mood modification” (p. 1468) They then defined mobile application addiction as “a psychological state of maladaptive dependency on a specific dominant life activity context to such a degree that the following behavioral symptoms arise to any degree: salience, withdrawal, conflict, relapse, tolerance, and mood modification (p.1469)”
Researchers first invited 700 undergraduate students to take an online survey over participants mobile phone usage. Researchers gathered 333 valid responses at the conclusion of the study. About 98.2% of the participants indicated that they use their mobile phones for personal use and the other 1.8% indicated that they only use them for work. To investigate the addiction to applications, researchers first questioned participants about six highly addiction life activity contexts (LAC). Participants were asked whether they had at least one application that represented LAC. The more applications that participants had on their phone (that represented LACs), the higher their addiction level was rated.
The results of the online survey indicated that the public’s addiction to mobile phones cannot be fully explained by application addiction. Frequency of usage did exert significant effect over perceived usefulness of mobile phones, however. As someone uses their phone, they naturally become more dependent on the device. Therefore, its importance in their life increases and its usefulness is consequently perceived more highly than a device that is not used often (Davazdahemami, Hammer, & Soror 2016).
Kim and Sundar (2014), examined whether screen size of smartphones matters for a users’ perception, since cell phone screens only seem to be getting bigger throughout the years. They conducted an experiment with two different conditions that involved small and large screened cellphones. One hundred thirty undergraduate students from South Korea were analyzed.
After beginning the experiment with the two different conditions, participants were told to visit a website (on the smartphones), that the researchers had created, to find the time that the shuttle busses departed to their other campus. After finishing the task, they were then asked to fill out an online survey on a desktop computer. All questions were measured on a 7-point Likert scale, with responses ranging from 1(disagree strongly) to 7(agree strongly).
Kim and Sundar (2014) found that a large screen cellphone does enhance utilitarian and hedonic experiences for the user, when compared to a small screen cellphone. This also suggests that there is a positive influence of feelings towards the attitude and ease of use of the large screen device.
Factors Affecting Smartphone Addiction. (2021, Dec 14). Retrieved from https://studymoose.com/factors-affecting-smartphone-addiction-essay
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