Smartphone Use, Addiction, Narcissism, and Personality: A Mixed Methods Investigation

International Journal of Cyber Behavior, Psychology and Learning, 5(1), 17-32, January-March 2015 17

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ABSTRACTThere are increasing numbers of people who are now using smartphones. Consequently, there is a risk of addiction to certain web applications such as social networking sites (SNSs) which are easily accessible via smartphones. There is also the risk of an increase in narcissism amongst users of SNSs. The present study set out to investigate the relationship between smartphone use, narcissistic tendencies and personality as predictors of smartphone addiction. The study also aimed to investigate the distinction between addiction specificity and co-occurrence in smartphone addiction via qualitative data and discover why people continue to use smartphones in banned areas. A self-selected sample of 256 smartphone users (Mean age = 29.2, SD = 9.49) completed an online survey. The results revealed that 13.3% of the sample was classified as addicted to smartphones. Higher narcissism scores and neuroticism levels were linked to addiction. Three themes of social relations, smartphone dependence and self-serving personalities emerged from the qualitative data. Interpretation of qualitative data supports addiction specificity of the smartphone. It is suggested smartphones encourage narcissism, even in non-narcissistic users. In turn, this increased use in banned areas. Future research needs to gather more in-depth qualitative data, addiction scale comparisons and comparison of use with and without SNS access. It is advised that prospective buyers of smartphones be pre-warned of the potential addictive properties of new technology.

Smartphone Use, Addiction, Narcissism, and Personality:

A Mixed Methods InvestigationClaire Pearson, University of Derby, Derby, UK

Zaheer Hussain, Psychology Department, University of Derby, Derby, UK

Keywords: Addiction, Narcissism, Narcissistic Personality Disorder, Personality, Smartphone Use, Social Networking Sites

1. INTRODUCTION

Over the last two decades, the huge rise in de-mand for interpersonal, mass communication technology has boosted smartphone evolution. From 2010 to 2011, sales increased by 58% and accounted for 31% of mobile phone sales (Silva, 2012). By 2013, 51% of adults owned smartphones in the UK (Ofcom, 2013). Thanks to WI-FI smartphone functions are endless and

easily accessible. Devices boast browser access, multiple downloadable applications (apps), camera’s and organisation systems. They are a mandatory device within industrialised cultures (Kwon, Lee & Won et al., 2013). However, there is evidence to suggest that there is an over-dependence on smartphones which can lead to destructive public health inferences (Monk, Carroll, Parker & Blythe, 2004; Palen, Salzman & Youngs, 2001; Paragras, 2005;

DOI: 10.4018/ijcbpl.2015010102


18 International Journal of Cyber Behavior, Psychology and Learning, 5(1), 17-32, January-March 2015

Sarwar, 2013). Including antisocial feelings of rejection within families (Rosman, 2006) and negative clinical health implications (Shin & Dey, 2013) such as addiction (Lopez-Fernandez & Honrubia-Serrano et al., 2013).

Rosen, Cheever and Carrier (2012) defined negative relationships between psychological health and technology overuse as an ‘iDisor-der.’; which smartphone addiction could be classed as. Roos (2001) defines three factors to mobile phone addiction; phones are always switched on, will be used regardless of landline telephone availability and use causes social or financial difficulties. Smartphones provide us with an unparalleled level of connectedness; but the psychological cost is unknown. The depth of such relationships may not be equal to real-life communications; and they may be engaged in to raise self-esteem by feeling popu-lar – an indicator of narcissism (Campbell & Miller, 2011). Narcissistic Personality Disorder (NPD), an Axis II disorder in the Diagnostic and Statistical Manual: fifth edition (DSM-V), is defined by self-promotion, vanity, grandiose sense of self-importance, power fantasies and superficial relationships. Twenge and Campbell (2013) warn of ‘The Narcissism Epidemic’ and report narcissism in America has risen as much as obesity. Smartphones may influence the development of NPD and could potentially influence a dependence to online gaming or gambling. Smartphones allow access to gam-bling and gaming sites (Young, 2000). These are easily accessible via a smartphone and ease of access is a key factor in developing dependence (Griffiths & Barnes, 2008).

Many studies have investigated addic-tive internet use which evidence psychosocial implications (Whang, Lee & Chang, 2003; Siomos et al., 2012). Yao and Zhong (2014) conducted a cross-lagged panel survey with 361 students investigating causal priority between psychological health and internet addiction. It was reported that loneliness was increased by excessive internet use and online relationships are not a healthy substitute for real life interac-tions. Whilst real life interaction may reduce internet addiction, increased online interactions

due to excessive internet use can neutralise the effect. The study offers a perturbing view of a cruel circle of internet addiction and loneliness. Although, the different platforms for internet use were not investigated and no significant effect was found for depression. Yen, Yen, Wu, Huang and Ko (2011) investigated differences between real life and online hostility and whether these differences were mediated by online activities, depression and internet use. They reported that internet addiction and depression increases both real life and online hostility. However, depressed participants showed lower hostility behaviours when online; suggesting the internet as a positive pathway for depression interventions. Although, the percentage of depressed participants who suffered internet addiction was not reported.

Compulsive usage of a device which is constantly at hand is hard to resist. Even in situations where they are banned; for example whilst driving (Mccartt, Hellings & Bratiman, 2006; Patten, Kircher, Ostlund & Nilsson, 2004). Research suggests this causes 25% of road traffic accidents (Stutts, Reinfurt, Staplin & Rodgman, 2001). Overuse of mobile phones can have negative effects on psychological health including depression and chronic stress (Augner & Hacker, 2010) and increased sui-cidal ideation (Katsumata, Matsumoto, Kitani and Takeshima, 2008). Research supports the link between depression and excessive texting, social networking, gaming, viewing video clips, emailing, listening to music which can all be accessed via a smartphone (Allam, 2010; de Wit, Straten, Lamers, Cuijpers&Penninx, 2011; Huang, 2010; Kalpidou, Costin& Morris, 2011). Lee, Chang, Lin and Cheng (2014) investigated smartphone use by utilising questionnaires incorporating compulsive smartphone usage and technostress within the examination of how smartphone user’s characteristics affect stress levels. The results from a sample of 325 respondents showed that increased ‘tech-nostress’ and compulsive usage are positively related to social interaction anxiety, locus of control, materialism and a need for touch. These results suggest smartphone dependence and compulsive usage increases user stress.



These results conflict with Park and Lee (2011), who examined the correlation between social relations, psychological health and smartphone use motivation. An online survey was utilised and 279 respondents were investigated. It was reported that smartphone use motivations can be grouped into six factors; information, accessibility, time passing, following trends, caring for others and communication. These factors were significantly related to perceived peer support and social relations. The results suggest that if used to fulfill a need to care for others or for supportive communications, smartphones can improve emotional and psy-chological wellbeing. Although this study did not specifically measure smartphone usage, the preliminary research implicates smartphones as either friend or foe, dependent upon motiva-tions and control of compulsive usage; similar to internet addiction.

Despite the possible relationship between smartphones, the internet and anonymity, research suggests a link between smartphone addiction and social networking sites (SNS). Survey research conducted by Standard Univer-sity on a sample of 200 students (Hope, 2010) showed that 10% admitted being addicted to the device and 41% said it would be a tragedy if they were to lose it. In addition, 15% confirmed their iPhone was turning them into a media addict and 30% saw the device as a ‘doorway into the world’. Despite such a large percent-age seeing the device as their doorway to the world, many also reported a negative effect on interpersonal relationships due to their iPhone use; with 7% admitting their partner or room-mate felt abandoned due to use.

Unlike traditional online communities and chat rooms, Facebook is not anonymous and actively encourages self-presentation. Salehan and Negahban (2013) found that the increase in mobile phone use corresponds with the rapid growth of SNS use; especially in youths. They discovered a positive correlation between SNS and mobile phone addiction, indicating SNS use as a predictor of mobile phone addiction. Barhuus & Polichar (2011) investigated how people integrate smartphones into their daily

lives via semi-structured interviews with 21 participants who completed a daily diary for three weeks. They found that use of SNSs was prominent and four participants downloaded Facebook as their first app. The study also found the smartphones ability to mix and match and interconnect apps make it desirable as this caters to individual needs. This points to possible addiction co-occurrence of the smartphone and SNS apps. Although, this was a very small study and cannot be generalised to the population.

Narcissists are most likely to use the main functions of SNS (status update and picture adding) as they are drawn to the control over self-presentation (Whang, Jackson, Zhang & Su, 2012). Rosen, Whaling, Rab, Carrier and Cheever (2013) have suggested that the increase in narcissism is down to advanced technology and the increasingly easy access to such technol-ogy. They investigated the impact of overused technologies and media on clinical symptoms of multiple mood and personality disorders and proposed that modern media, such as Facebook, increases narcissistic tendencies by encourag-ing superficial peer relationships, vanity and self-promotion. Mehdizadeh (2010) collected personality self-reports from 100 Facebook us-ers to examine the manifestation of self-esteem and narcissism on SNS. The Facebook pages of the participants were also coded based on self-promotional content features. The study found that greater online activity was related to higher levels of narcissism and lower levels of self-esteem. However, these studies do not specifically examine the effect of smartphone use on narcissism.

With so many addictive applications avail-able on the smartphone, it is difficult to decipher the cause and effect relationship of problematic use. The smartphones multi-faceted functional-ity may be addictive or it may be that users are addicted to a certain media. For example if a user is showing signs of internet addiction and smartphone overuse, is it a case of co-occurrence or addiction specificity (Sussman et al., 2011). Co-occurrence would refer to the user being ad-dicted to the internet and smartphone. Whereas addiction specificity would refer to the user



being addicted to either the internet or smart-phone. In addiction specificity, the addictive aspect would be the reason for overuse of the other; so if an individual was addicted to the internet, they may overuse their smartphone in order to have constant access. This individual may seem addicted to their smartphone, but would actually need to address their internet addiction as opposed to smartphone use. This must be investigated as it is vital clinicians understand reasons behind smartphone overuse.

Previous research suggests that narcissism is increasing in individuals and that smartphone addiction/overuse must be empirically investi-gated. There is a lack of research in the area of smartphone use, narcissism and links to addic-tion. With such rapid growth in popularity, it is vital that smartphone use and possible clinical implications are investigated to protect users. The current study aims to investigate whether or not smartphones encourage narcissism. Smart-phone addiction, co-occurrence and addiction specificity will also be investigated. As it is possible smartphone overuse may have negative clinical connotations leading to addiction and narcissism, the current study will also inves-tigate personality as a predictor of addiction. Finally, the study will attempt to decipher why people continue to use smartphones in banned areas. It was hypothesized that there will be a higher rate of narcissistic tendencies shown in participants who show a dependence equivalent to addiction to their smartphone.

2. METHOD

2.1. Participants

A total of 256 participants completed an online questionnaire. The participants were recruited via opportunity sampling from a UK University and the internet via social networking sites and smartphone forums. The sample consisted of 181 females (71%) and of 75 males (29%). The participants age range was 17 years to 68 years (M = 29.2 years; SD = 9.4 years). Most of the participants noted their occupation as student (35%), followed by health care (8%), Education

(7%), sales/marketing (5%), administration and science/technology (4%), customer service and restaurant (3%), accounting/finance, architec-ture/design, construction, consulting and social service (2%) and arts/leisure/entertainment, beauty/fashion, management, operations and production (1%). The ‘other’ option was ticked by 17% of the participants. People who did not own a smartphone were excluded from the study.

2.2. Materials

Online questionnaire software (Google Docu-ments) was utilised to design the online survey and to collect data. This was consistent with the methodology of previous research (Mehdi-zadeh, 2010; Park & Lee, 2011; Rosen et al., 2012). The online survey firstly asked basic demographic questions such as age, gender and occupation. In order to empirically investigate the phenomenon of smartphone addiction, it was decided to compare it with the same criteria and methods as addictions which are already clini-cally established. Internet Addiction is defined as an impulse control disorder which does not include an intoxicant, smartphone addiction can be defined in the same manner (Kwon et al., 2013).The online survey made use of an amended version of Young’s (1996) Diagnostic questionnaire to measure smartphone addiction. This consisted of eight close-ended questions (e.g. Do you feel preoccupied with your smart-phone? Do you use your smartphone for longer than intended? Have you repeatedly made unsuccessful attempts to control, cut back or stop smartphone use?). Participants responded with either yes or no, with yes equal to 1 and no equal to 0 for quantitative analysis. A score of 5 or more meant the participant was addicted. Kwon etal (2013) also made use of Young’s (1996) Diagnostic questionnaire to explore smartphone addiction in a Korean sample (n = 197). Their results suggested that the scale items in the questionnaire were relatively reli-able and valid.

Smartphone research has focused upon how users consume energy, as opposed to why they consume energy in that way (Oliver, 2010). For



example, how often a particular application is used, but not why or what implications this has on the user. For this reason, the current study used three open-ended questions to investigate how and why the smartphone user adopts their particular behaviour (e.g. Which applications do you most utilise? What makes these particular applications attractive? What problems, if any, does your smartphone cause in your life?).

In order to measure narcissism, Raskin and Howard’s (1988) Narcissistic Personality Inventory (NPI), amended by Rosen et al (2012) with permission, was used. This consisted of 40 pairs of statements which belong to seven subsections. Each subsection is a known trait of narcissism. These are authority, self-sufficiency, superiority, exhibitionism, vanity, exploitative-ness and entitlement. Each statement belongs to either column A or column B. Statements from column A are typically narcissistic and score one point. For example, ‘I would prefer to be a leader’. Statements from column B are not typically narcissistic and therefore are not worth any points. For example, ‘It makes little difference to me whether I am a leader or not’. People with Narcissistic Personality Disorder (NPD) are expected to score above 20 column A answers.

The final part of the survey consisted of the mini-marker personality scale. This is a subset of Goldberg’s (1981) Big-Five personality markers and was chosen as it exhibits unusually strong characteristics for an abbreviated inven-tory (Saucier, 1994). It is a 35 item, nine-point likert scale in which participants are asked to self-report on common human personality traits (e.g. extraverted and inefficient). Participants are asked to rate each trait with 1 = Extremely Inaccurate and 9 = Extremely Accurate. These measure 5 ‘big’ traits overall: conscientious-ness, openness, agreeableness, neuroticism and extraversion. The big traits were separated into three categories. A score between 0 and 29 was categorised as low, between 30 and 33 was categorised as neutral and between 34 and 63 was categorised as high.

2.3. Design and Procedure

The study utilised a mixed methods design and made use of an online survey to collect data. The main variables under investigation were levels of smartphone addiction, extraver-sion, openness, agreeableness, neuroticism, conscientiousness, NPI score, age and length of ownership.

Invitations for participants to take part in the survey were posted online via social networking sites (i.e. Facebook and Twitter) and smartphone forums (i.e. Crackberry and Android Central). The invitation contained the aims of the study and a link to the survey. The link directed participants to the consent form and survey, participants were assured that the data would be kept confidential. Once the participants had completed the survey they were directed to a debrief form before they submitted their data. Those participants who were studying at the University were given one participation point for their participation.

3. RESULTS

3.1. Smartphone User Behaviour

The mean length of time participants had owned a smartphone was 4.07 years (SD = 2.35). The mean amount of time spent using a smartphone per day was 3.63 hours (SD = 2.83). There was no correlation between gender and daily use, r(255) = .02, p = .75. Length of time owned and daily use were positively correlated, r(255) = .14, p = .03. When asked if they used their smartphones in banned areas, 35% of participants (N = 92) said yes. A chi-square test was performed and no relationship was found between gender and banned use, X2(1, N = 254) = .65, p = .421, or occupation and banned use, X2(19, N = 254) = 18.59, p = .48. A point biserial correlation showed no relationship between age and banned use, r(254) = .08, p = .233. Participants were also asked what their three most used apps are. The most popular were SNS apps chosen by 87% of participants (N = 223). The second was instant messaging (IM) apps chosen by



52% of participants (N = 135) and the third was news apps chosen by 51% of participants (N = 132). Table 1 shows a full breakdown of participant responses.

3.2. Smartphone Addiction

According to Young’s (1996) diagnostic ques-tionnaire, 13.3% of participants (N = 34) were classified as addicted to their smartphones. A chi-square test was performed and no relation-ship was found between gender and smartphone addiction, X2 (1, N = 256) = .63, p = .43, or occupation and smartphone addiction, X2 (19, N = 256) = 17.85, p = .532. A point biserial correlation also showed no relationship be-tween age and smartphone addiction, r(256) = .11, p = .08. A pearson correlation showed a significant positive relationship for both daily use and smartphone addiction, r(255) = 0.24, p = .05, and NPI score and smartphone addiction, r(256) = .13, p = .04. However, a pearson cor-relation found no relationship between length of ownership and smartphone addiction, r(255) = -.01, p = .86.

3.3. Narcissistic Personality Disorder

Using the NPI scale, 16.8% of participants (N = 43) were classified as having NPD. A chi square test was conducted to assess whether there is a relationship between gender and NPD. The results were found to be significant in that more males had NPD (30.7%, N = 23) than females (11%, N = 20), X2(1, N = 256) = 14.6,p = < .01). A chi square test was also performed to check for correlations between occupation and NPD but no relationship was found, X2(19, N = 256) = 16.37, p = .63. A point biserial correlation did find a negative correlation between age and NPD r(256) = -.17, p = < .01; but no cor-relation between NPD and banned use r(256) = -.10, p = .105.

3.4. Personality

The big five personality traits measured by the mini markers scale were neuroticism (M = 31.78, SD = 9.95), extraversion (M = 37.67, SD = 9.44), openness (M = 43.88, SD = 8.87), agreeableness (M = 47.29, SD = 8.05) and conscientiousness (M = 44.15, SD = 8.77).For each trait, a score below 30 was classified as low, a score between 30 and 33 was classified

Table 1. The smartphone applications used most frequently by participants

Apps No of Participants Using App (%)

SNS 223 (87%)

IM 135 (52%)

News 132 (51%)

Gaming 64 (25%)

Shopping 54 (21%)

Music 51 (19%)

Photo/Video Apps 32 (12%)

TV Catch Up 9 (3%)

Dating 7 (2%)

Fitness/Diet 2 (0.7%)

Other 22 (8%)



as neutral and a score above 33 was classified as high. Table 2 shows the scores for each trait.

3.5. Smartphone Addiction Predictors

Further exploratory analysis was conducted to check which variables may be related to smart-phone addiction. The predictors of conscien-tiousness, openness, neuroticism, extraversion, agreeableness, NPI score, age and length of own-ership were used to conduct a multiple regres-sion analysis. An analysis of standard residuals was carried out, which showed no outliers in the data (Std. Residual Min = -1.95, Std. Residual Max = 3.14). Tests to check the data met the assumption of collinearity which indicated that multicollinearity was not a concern. The data also met the assumption of non-zero variances (see Table 3 for Tolerance, VIF and variance scores). The data met the assumption of inde-pendent errors (Durbin-Watson value = 1.87).

Using the enter method, it was found that the predictor variables explain a significant amount of variance in smartphone addiction scores (R2 = .15, Adjusted R2 = .12, F(8, 246) = 5.44, p = < .001). The analysis showed that neuroticism (β = .28, t(254) = 4.50, p< .05), NPI score (β = .21, t(254) = 2.86, p = .005), openness (β = -.14, t(254) = -2.12, p< .05), and age (β = -.15, t(254) = -2.45, p< .05) significantly predicted smartphone addiction. However, conscientious-ness (β = .02, t(254) = .29), agreeableness (β = .03, t(254) = .46), extraversion (β = -.06, t(254) = -.98) and length of ownership (β = .28, t(254) = .21) did not significantly predict smartphone addiction (see Table 4).

3.6. Qualitative Analysis

The qualitative data revealed the themes of social relations, dependence, and self-serving personalities. The unbeatable and varied communication opportunities provided by

Table 2. Frequency and percentage of the ‘big’ 5 personality traits, as rated by the Mini-Markers Scale; Categorised as High, Neutral and Low scores

Trait Low Neutral High

Conscientiousness 14 (5.5%) 11 (4.3%) 231 (90.2%)

Agreeableness 5 (2%) 11 (4.2%) 240 (93.8%)

Openness 13 (5.1%) 21 (8.2%) 222 (86.7%)

Extraversion 49 (19%) 27 (10.5%) 180 (70.3%)

Neuroticism 105 (41%) 46 (18%) 105 (41%)

Table 3. The multiple regression analysis tolerance and VIF scores for predictor variables

Variable Tolerance VIF Variance Mean SD

Conscientiousness .92 1.08 76.86 44.15 8.77

Agreeableness .79 1.27 64.73 47.29 8.05

Openness .76 1.32 78.75 43.88 8.87

Extraversion .81 1.23 89.09 37.67 9.44

Neuroticism .90 1.11 98.95 31.78 9.95

Age .89 1.12 89.98 29.17 9.49

Length of Ownership .93 1.08 5.52 4.07 2.35

NPI Score .67 1.48 51.91 12.93 7.21



smartphones was noted by many participants as the most endearing aspect of use; with 87% downloading SNS apps. However, many also noted that despite using their smartphone for communication, their overuse negatively im-pacted on real life interpersonal relationships. This is considered under the theme ‘social relations’. The theme ‘dependence’ expands on the feelings of addiction and reliance which was a reoccurring issue throughout the data. When participants who admitted to using their smartphone in banned areas were asked why they disregard the rules, a strong narcissistic ele-ment was identified as a frequent excuse despite quantitative analysis finding no relationship between NPD and banned use. This is discussed under the theme ‘self-serving personalities’.

3.7. Social Relations

A common theme mentioned by the majority of participants was the social access their smart-phones provided them with. SNS was the most popular app; chosen by 87% of participants. When asked why they use their favourite apps, participants stated that these apps offered them an easy means of communication with friends, family, colleagues, clients and strangers. The constant and instantaneous social connectivity provided appeared integral to staying connected with the world and an important part of partici-pants social and business lives.

Extract 1: It’s all about staying connected, whether it be friends, family, or the world (P176; male, age: 29 years. Extract 2: I like to listen to music or podcasts when travelling. Instant messaging is a vital communication tool for both work and personal life (P238; female, age: 43 years). Extract 3: Being connected anytime, anywhere I go. I can have any news, be it regional, pro-vincial, national or worldwide, tech or sciences, or about friends and family at the tip of my thumb. Great to stay informed (P157; male, age: 26 years).

The importance of this connectivity was partly related to relieving loneliness. It did not seem to be the people who were being contacted who were important – but the communication itself. It was also partially associated with know-ing exactly what friends were up to and when; although why it is important to have constant access to friend’s daily activities was omitted by participants. Another common relation was participants easily keeping in touch when away from loved ones; either short term or long term.

Extract 4: Social contact and peer information sharing. Catching up with the world. Relieving loneliness (P150; female, age: 30 years).Extract 5: Facebook for instance: catching up on friends activities, messages etc during a quite part of the day when a computer’s not accessible (P 64; male, age: 35 years).

Table 4. Multiple regression analysis of factors influencing smartphone addiction

Variable B SE β t p

Conscientiousness .004 .014 .018 .290 .772

Agreeableness .007 .016 .030 .455 .649

Openness -.031 .015 -.143 -2.121 .035

Extraversion -.013 .013 -.064 -.976 .330

Neuroticism .054 .012 .278 4.496 .000

Age -.031 .013 -.152 -2.447 .015

Length of Ownership .010 .050 .013 .206 .837

NPI Score .055 .019 .205 2.862 .005

Note: (F(8, 246) = 5.44, p = < .001, R2 = .15, Adjusted R2 = .12) p = < .05



Extract 6: Instant messaging e.g. whatsapp make keeping in touch with the family easier, also makes sharing photos and videos easier with the whole family (P54; female, age: 29 years).

Conversely, despite 46.8% of partici-pants speaking positively of improved social relations, 23.5% admitted their smartphones create communication issues within ‘real life’ relationships; when asked what problems their smartphones cause. Participants admitted to spending too much time on their smartphones whilst in the company of friends and loved ones – actually leading to less conversation and a breakdown in communication. People are not conversing when together due to connecting with others through their smartphones. Real conversation with partners and children is not seen as important as online communication; yet it is known that this is having adverse effects on interpersonal relationships.

Extract 7: Very hard to leave your phone alone in social situations. I’ve been to friends houses and we’d all be on our phones for ages without speaking Bit ridiculous (P31; female, age: 26 years).Extract 8: Distraction from my family. Lack of conversation with partner. Missing out on time with my children (P148; female, age: 30 years).Extract 9: Time Consuming; Time wasting; Distracting from work; distracting from re-lationships ;Distracting from having proper conversations with people; Can become ig-norant to people around me as I’m too busy on the phone; lack of concentration on “real” events and happenings now (P199; female, age: 23 years).

The data identified that despite the main reasoning behind smartphone use being commu-nication, it actually breaks down interpersonal relationships through lack of ‘real’ conversa-tion. The majority of participants responding in this conflicting manner were not classified as addicted to their smartphones – yet admitted

to letting it negatively influence close relation-ships with partners and children. This suggests serious implications for all smartphone users; not just those who are addicted.

3.8. Dependence

Another theme identified was the necessity of smartphones and a feeling of addiction. Partici-pants largely agreed that they could not live with as much ease without their smartphone and that not owning one would have a negative impact on daily activities and relationships. This is despite only 13.3% being classified as addicted and 61.71% complaining of severe distraction which negatively impacts on interpersonal relationships, work, hobbies and studies.

Extract 10: It’s very addictive, that’s a major problem and distraction. I find myself logging into facebook first thing when i wake up and last thing before I go to bed and several times during the day. I go way over the allowed megabites and therefore all my credit goes in less than a week or 2. it becomes automatic to check in every day, check emails, and when I run out of credit its very frustrating (P43; female, age: 23 years).Extract 11: It’s addictive! Sometimes (the smartphone) hard to stop using and be properly in the moment in the real world (P10; female, age: 39 years). Extract 12: People being able to contact you all of the time. It’s a pain when the battery dies, you realise how much you use the phone, it’s then like losing a limb! (P19; male, age: 36 years).

The feeling of addiction appeared partly due to the multiple communication abilities of the smartphone and partly due to the escap-ism other apps allowed (i.e. gaming apps). Participants admitted feeling addicted to and wasting excessive time on their smartphones. The constant availability of the smartphone was also noted to impact on overuse as it is always accessible. This means it is the first thing a user reaches for when wanting communication, distraction or organisation; leaving participants



reliant upon the device and unsure what to do without it. It is apparent from the data that the addictive nature of the smartphone is due to its’ multi-functionality as opposed to specific downloadable apps.

Extract 13: Facebook is addictive. You’d be lost in it for hours without even realising the time. Game apps are just as addictive. Something to do in waiting rooms (P32; female, age: 26 years).Extract 14: I think I rely on my smartphone too much - as I would feel a little lost without it as it is my main device for communication (P4; female, age: 22 years). Extract 15: Go on to check something briefly and end up looking at stuff I didn’t intend to; Sometimes the convenience of finding info quick is a problem e.g. Watching a film and trying to remember the name of a film someone has been in. Too easy to check it on your phone then become distracted from the film (P83; female, age: 32 years).

Interestingly, only two of the participants quoted throughout this theme were classified as addicted to their smartphones according to the Young’s (1996) diagnostic questionnaire.

3.9. Self-Serving Personalities

When asked if they continue to use their smart-phones in areas which they know the devices are banned (e.g. whilst driving), 35% of participants answered ‘yes’. These participants were asked why they acted in this manner and a common theme identified was a self-serving personality. Many participants had a disregard for the rules; or simply disagreed and so continued smart-phone use regardless of safety advice. Many responses were provided with an egotistical edge, in that these participants assumed they knew better than whomever made the rules.

Extract 16: Yes for texting/phoning whilst driv-ing. All time in hospital as I work in one and know they don’t really interfere with crucial machines. Never on flights (P88; female, age: 37 years).

Extract 17: Yes, because it’s my phone and I’ll go on it when I like, nobody has the right to stop me (P22; male, age: 21 years).

Many participants described a compromise between using their smartphone in banned areas; but in a manner that they personally deemed safe. These participants were aware of safety advice and partially followed it. For example, smartphone use whilst driving is against the law, but a lot of participants deemed it safe to use in a stationary vehicle and so continued smartphone use when stopped at traffic lights. The legality of the situation did not seem important to these participants; they had decided they were using the device in a safe manner and so disregarded the law. Another common example was using the smartphone quickly or for only one thing. For these participants, they deemed using the smartphone for a short period of time safe; and therefore disregarded the rules.

Extract 18: Occasionally in the car, but I really try not to when in motion. Typically at stop signs and stop lights; It is there and the draw of it is sometimes too much to overcome (P165; male, age: 45 years).Extract 19: Not really. Sometimes I will send a quick reply to a BBM or SMS while driving, but no conversations. Rules are there for a rea-son: using a smartphone increases the danger while driving, interfere with medical material in hospital, etc (P157; male, age: 26 years).Extract 20: I search on the gps while driving and use voice chat apps (Coco) because all I have to do is hit one button to listen and respond to a whole message (P136; female, age: 26 years).

Many participants also weighed up the risks of smartphone use in banned areas against their specific need to use the smartphone; stating they would break the rules for a good enough reason. These reasons ranged from emergencies only to reasons of high personal importance. From these participants, it was clear that rules could be ignored if they thought their personal rationale was significant enough to enable them to be above the rules.



Extract 21: No, not if I’ve been explicitly asked not to… though I suppose if it was an emergency……. then probably (P256; female, age: 20 years).Extract 22: I use the smartphone in banned areas for podcasts, music, dictionaries, texting my girlfriend if possible (she lives abroad so it’s the only thing we have, to make the most of any means and moment) (P255; male, age: 25 years).

The majority of participants reasoning for using their smartphone in areas deemed unsafe by authorities was that they knew better. Some-times this was shown in an upfront and clearly narcissistic manner, but mostly it was hidden behind secret compromise with authorities or personal logic regarding the weighing up of rules versus reason for smartphone use (e.g. emergency). It is not the legality of the use that is important, but the participant’s view of their own intelligence or needs being higher than the authorities or other people in the vicinity.

4. DISCUSSION

The main aim of the current study was to examine the relationship between narcissism, personality and smartphone addiction. Results indicated that 13.3% of participants showed a dependence on their smartphone and could be classified as addicted to smartphone use. A significant positive relationship was found between narcissism levels and smartphone addiction. This suggests that the more narcis-sistic a person is, the more likely they are to be addicted to their smartphone. This finding supports previous research that links narcissism with addictive disorders (Lakey et al., 2008; Rose, 2007; Stinson et al., 2009). These results build upon previous research in the area of smartphone addiction which has shown that 10% of participants were addicted to smartphones and 34% displayed addictive symptoms (Hope, 2010). The results also revealed a significant positive relationship between daily use and smartphone addiction. This indicates that daily

smartphone users are more likely to be addicted and is consistent with previous research (Shin & Dey, 2013). The qualitative results supported the idea that smartphones create narcissistic traits in people who otherwise do not show high levels of narcissism; as the majority of those showing self-serving personalities did not have NPD. This supports the theory that the ‘Narcissism Epidemic’, described by Twenge and Campbell (2013), is influenced by advanced technologies; such as smartphones (Rosen et al., 2013). In addition, SNS apps were found to be the most popular; which fits with the nar-cissism theory as research suggests SNS apps significantly encourage narcissism (Keating, 2014: Mehdizadeh, 2010).

Furthermore, the results indicated that young males were most likely to have NPD. This is supported by a plethora of previous research indicating NPD as a predominantly male disorder (Stinson et al., 2008). Despite there being no correlation found between gender and banned use or gender and addiction, this indicates that males are at a higher risk of the narcissism inducing aspects of the smartphone. A positive relationship was found between daily use and length of ownership. Yet, there was no correlation between length of owner-ship and addiction. This suggests that although length of ownership has no direct influence on smartphone addiction, the longer a user owns their smartphone the more daily use increases; and the more likely they are to become ad-dicted. This is an aspect for future research to investigate further. It may be that the appeal of the smartphone and its’ many features become harder to resist over time. If future explorations could define a clinically safe amount of daily use which may prevent addiction, users could then be pre-warned and be pro-active in protecting themselves from becoming addicted.

The secondary aim of the present study was to examine personality as a predictor of smartphone addiction. The study found that agreeableness, conscientiousness and extraver-sion are not predictors of smartphone addiction; but neuroticism and openness are predictors. The results suggest that the more neurotic an



individual is, the more likely they are to be addicted to their smartphone. This is a worry-ing finding as neuroticism has been linked to severe mental health issues including mood disorders, substance abuse, eating disorders and affective disorders (Widiger, 2011). Further research which identifies neurotic smartphone users, through the mini-markers neuroticism scale, and examines their psychopathology (i.e. mood, affective and substance use disorder his-tory), reasons for smartphone use and level of smartphone addiction may provide more insight into the depth of the clinical implications for this finding.

The study also attempted to decipher between addiction specificity and addiction co-occurrence via qualitative analysis. Participants were asked the reasons behind their choice of apps. The analysis identified ‘social relations’ to be a prominent theme for both addicts and non-addicts. Participants used multiple apps for communications with family and peers (e.g. SNS, IM), which was by far the most common reason given. This was supported by SNS be-ing the most popular choice of app and agrees with previous research (Barhuus & Polichar, 2011; Salehan & Negahban, 2013). The multi-functionality of the device offers many different methods of communication and it was apparent that participants found this very hard to resist; suggesting support for addiction specificity of the smartphone itself. Future research which ex-amines social relations via extended one-on-one interviews would gather rich data; which may reveal in-depth themes and allow researchers to more clearly decipher between specificity and co-occurrence. These further qualitative investigations may also benefit from examining smartphone use of previously identified addicts.

Participants placed high value upon the communication functions of smartphones and their ability to keep them in touch with the world. However, the majority of participants (N =158) also admitted their smartphone use causes distraction from many aspects of their lives; including employment, hobbies and stud-ies in a similar way to internet addiction, this supports previous research (Rosman, 2006). Se-

vere distraction from interpersonal relationships leading to a negative impact in familial com-munications was also specified by 60 of these participants. This is despite many participants noting the communicative aspect of the smart-phone was a main influence for smartphone use, which supports the theory that smartphone use increases narcissism. Interestingly, many non-addicts were included in the large number of participants who admitted smartphone use is a distraction from important real life events and relationships. This suggests that users do not have to be addicted for smartphone use to negatively affect many aspects of their lives.

Furthermore supporting the idea that smart-phone use encourages narcissism, the theme ‘self-serving personalities’ was also identified in response to the question ‘Why do you use your phone in banned areas?’. Most partici-pants did not admit to using their smartphones in banned areas; although 92 confirmed they did. The majority of these participants (N = 60) advised either that they knew better than authorities (Extract 16) or secretly compromised with an action which they personally deemed safe (Extract 17). Also, if their own reasons for use were deemed more important than the authorities’ reasons for banning the device, then the device would be used regardless of the rules. These participants held their own intel-ligence and personal need in higher regard than the safety of others and the law or authorities’ rules. This is yet another significant indicator of narcissism (Whang et al., 2012). This is an extremely serious issue to public health due to 25% of road traffic accidents being caused by mobile phone use (Stutts et al., 2001). Cam-paigns to raise awareness of the risks of using phones in banned areas are needed.

There are a number of limitations to the present study. The online self-report data used in this study suffers from the issue of reli-ability, participants may have over-estimated their smartphone use. However, the issue of reliability of responses is not limited to online studies as it affects all types of self-report research (Wood, Griffiths & Eatough, 2004). The study made use of an amended version of



Young’s (1996) Diagnostic Questionnaire to measure for smartphone addiction. A specific measure of smartphone addiction is needed as the effectiveness of the YDQ for measur-ing smartphone use is unknown as it has not previously been used for this purpose. The qualitative data provided interesting insights in to smartphone use. However, the use of an online survey method restricted the amount of detail that could be gathered from participant responses. It is also important to note that the majority of the sample was female, the findings may reveal more about the views and behaviours of female smartphone users. Future research in this area should attempt to recruit an equal number of male and female participants.

There were interesting, preliminary themes identified in the present data which paves the way for more in-depth qualitative investiga-tions. Future research could also look at com-paring narcissism levels between smartphone users and non-smartphone users. Twenge et al (2008) claim that narcissism has influenced the way we use technology. Further research needs to investigate this claim to discover why people are becoming more narcissistic and what the motivations are for narcissism. The current study revealed a relationship between smartphone addiction, NPD, neuroticism and interpersonal relationships; but more research is required in order to comprehensively examine the multi-functionality of the smartphone and its psychological effects. Public marketing and promotion of smartphones should consider psychological wellbeing and prospective buyers should be warned of possible addiction issues. With smartphone use appearing, at the very least, to be a co-conspirator of narcissism, and users aware of adverse consequences but still insisting smartphones enrich their lives, action to protect users from overuse may be warranted. If adverse effects of smartphones are well advertised, users might realise that despite using the device for improving communications, it can easily lead to narcissistic actions which can potentially breakdown familial relationships. Users need to know that even if not clinically addicted, smartphone overuse can negatively affect

interpersonal relationships and psychological wellbeing. This way, consumers can make an informed choice of their technology use and be aware of measures to protect themselves.

REFERENCES

Allam, M. F. (2010). Excessive Internet Use and Depression: Cause-Effect Bias? Psychopathol-ogy, 43(5), 121–126. doi:10.1159/000319403 PMID:20664310

Anderson, C. (2000). Video Games and Aggressive Behavior in the Laboratory and in Life. Journal of Personality and Social Psychology, 78(4), 772–790. doi:10.1037/0022-3514.78.4.772 PMID:10794380

Angres, D., & Bettinardi-Angres, K. (2008). The Dis-ease of Addiction: Origins, Treatment and Recovery. Disease-a-Month, 54(10), 696–721. doi:10.1016/j.disamonth.2008.07.002 PMID:18790142

Augner, C., & Hacker, G. (2010). Associations be-tween problematic mobile phone use and psychologi-cal parameters in young adults. International Journal of Public Health, 57(2), 437–441. doi:10.1007/s00038-011-0234-z PMID:21290162

Barkhuus, L., & Polichar, V. E. (2011). Empower-ment through seamfulness: Smart phones in everyday life. Personal and Ubiquitous Computing, 15(6), 629–639. doi:10.1007/s00779-010-0342-4

Benfield, J. A., & Szlemko, W. J. (2006). Internet-based data collection: Promises and realities. Journal of Research Practice, 2(2), Article-D1.

Campbell, W., & Miller, J. (2011). The Hand-book of Narcissism and Narcissistic Personal-ity Disorder. New Jersey: John Wiley & Sons. doi:10.1002/9781118093108

Chak, K., & Leung, L. (2004). Shyness and Locus of Control as Predictors of Internet Addiction and Internet Addiction. CyberPsychology&Behaviour, 7(5), 559–570. doi:10.1089/cpb.2004.7.559 PMID:15667051

Chuang, Y. (2006). Massively Multiplayer Online Role-Playing Game-Induced Seizures: A Neglected Health Problem in Internet Addiction. Cyberpsy-chology & Behavior, 9(4), 451–456. doi:10.1089/cpb.2006.9.451 PMID:16901249

http://dx.doi.org/10.1159/000319403

http://www.ncbi.nlm.nih.gov/pubmed/20664310

http://dx.doi.org/10.1037/0022-3514.78.4.772


http://dx.doi.org/10.1016/j.disamonth.2008.07.002

http://dx.doi.org/10.1016/j.disamonth.2008.07.002


http://dx.doi.org/10.1007/s00038-011-0234-z

http://dx.doi.org/10.1007/s00038-011-0234-z


http://dx.doi.org/10.1007/s00779-010-0342-4

http://dx.doi.org/10.1002/9781118093108

http://dx.doi.org/10.1089/cpb.2004.7.559







de Wit, L., Straten, A., Lamers, F., Cujipers, P., & Penninx, B. (2011). Are sedentary television watching and computer use behaviors associated with anxiety and depressive disorders? Psychiatry Research, 186(2-3), 239–243. doi:10.1016/j.psy-chres.2010.07.003 PMID:20692047

Griffiths, M., & Barnes, A. (2008). Internet Gam-bling: An Online Empirical Study Among Student Gamblers. International Journal of Mental Health and Addiction, 6(2), 194–204. doi:10.1007/s11469-007-9083-7

Hope, D. (2010). iphone addictive, survey reveals. Live Science. http://www.livescience.com/6175-iphone-addictive-survey-reveals.html. Accessed June 19, 2014

Huang, C. (2011). Internet Use and Psychological Well-being: A meta-analysis. Cyberpsychology, Behavior, and Social Networking, 13(2), 241–249. PMID:20557242

Kalpidou, M., Costin, D., & Morris, J. (2011). The Re-lationship Between Facebook and the Well-Being of Undergraduate College Students. Cyberpsychology, Behavior, and Social Networking, 14(4), 183–189. doi:10.1089/cyber.2010.0061 PMID:21192765

Katsumata, Y., Matsumoto, T., Kitani, M., & Takeshi-ma, T. (2008). Electronic media use and suicidal ide-ation in Japanese adolescents. Psychiatry and Clinical Neurosciences, 62(6), 744–746. doi:10.1111/j.1440-1819.2008.01880.x PMID:19068014

Kwon, M., Lee, J., Won, W., Park, J., Min, J., & Hahn, C. et al. (2013). Development and Validation of a Smartphone Addiction Scale (SAS). PLoS ONE, 8(2), e56936. doi:10.1371/journal.pone.0056936 PMID:23468893

Lakey, C., Rose, P., Campbell, W., & Goodie, A. (2008). Probing the Link Between Narcissism and Gambling: The Mediating Role of Judgment and Decision-Making Biases. Journal of Behavioral De-cision Making, 21(2), 113–137. doi:10.1002/bdm.582

Lane, W., & Manner, C. (2011). The impact of personality traits on smartphone ownership and use. International Journal of Business and Social Science, 2(17), 22–28.

Lee, Y., Chang, C., Lin, Y., & Cheng, Z. (2014). The dark side of smartphone usage: Psychological traits, compulsive behaviour and technostress. Computers in Human Behavior, 31, 373–383. doi:10.1016/j.chb.2013.10.047

Lopez-Fernandez, O., Honrubia-Serrano, L., Freixa-Blanxart, M., & Gibson, W. (2013). Prevalence of Problematic Mobile Phone Use in British Adoles-cents. Cyberpsychology, Behavior, and Social Net-working, 17(2), 91–98. doi:10.1089/cyber.2012.0260 PMID:23981147

Mccartt, A., Hellinga, L., & Bratiman, K. (2006). Cell Phones and Driving: Review of the Re-search. Traffic Injury Prevention, 7(2), 89–106. doi:10.1080/15389580600651103 PMID:16854702

Mehdizadeh, S. (2010). Self-Presentation 2.0: Narcissism and Self-Esteem on Facebook. Cy-berpsychology, Behavior, and Social Networking, 13(4), 357–364. doi:10.1089/cyber.2009.0257 PMID:20712493

Monk, A., Carroll, J., Parker, S., & Blythe, M. (2004). Why are mobile phones annoying? Behaviour & Information Technology, 23(1), 33–41. doi:10.1080/01449290310001638496

Muir, H. (2004). The Violent Video Games People Play. New Scientist, 184(7), 26.

Ofcom. (2013). Communications market report. Key Points: The Market in Context, 10, 4–5.

Oliver, E. (2010, June). The challenges in large-scale smartphone user studies. In Proceedings of the 2nd ACM International Workshop on Hot Topics in Planet-scale Measurement (p. 5). ACM. doi:10.1145/1834616.1834623

Palen, L., Salzman, M., & Youngs, E. (2001). Dis-covery and integration of mobile communications in everyday life. Personal and Ubiquitous Computing, 5(2), 109–122. doi:10.1007/s007790170014

Paragras, F. (2005). Being mobile with the mobile: Cellular telephony and renegotiations of public transport as public sphere. Mobile Communications, 31(2), 113–129. doi:10.1007/1-84628-248-9_8

Park, N., & Lee, H. (2011). Social Implications of Smartphone Use: Korean College Students’ Smart-phone Use and Psychological Well-being. Cyberpsy-chology (Brno), 15(9), 491–497. PMID:22817650

Patten, C., Kircher, A., Ostlund, J., & Nilsson, L. (2004). Using mobile telephones: Cognitive workload and attention resource allocation. Accident; Analysis and Prevention, 36(3), 341–350. doi:10.1016/S0001-4575(03)00014-9 PMID:15003578

http://dx.doi.org/10.1016/j.psychres.2010.07.003

http://dx.doi.org/10.1016/j.psychres.2010.07.003


http://dx.doi.org/10.1007/s11469-007-9083-7

http://dx.doi.org/10.1007/s11469-007-9083-7

http://www.livescience.com/6175-iphone-addictive-survey-reveals.html

http://www.livescience.com/6175-iphone-addictive-survey-reveals.html


http://dx.doi.org/10.1089/cyber.2010.0061


http://dx.doi.org/10.1111/j.1440-1819.2008.01880.x

http://dx.doi.org/10.1111/j.1440-1819.2008.01880.x


http://dx.doi.org/10.1371/journal.pone.0056936


http://dx.doi.org/10.1002/bdm.582

http://dx.doi.org/10.1016/j.chb.2013.10.047




http://dx.doi.org/10.1080/15389580600651103




http://dx.doi.org/10.1080/01449290310001638496

http://dx.doi.org/10.1080/01449290310001638496

http://dx.doi.org/10.1145/1834616.1834623

http://dx.doi.org/10.1007/s007790170014

http://dx.doi.org/10.1007/1-84628-248-9_8


http://dx.doi.org/10.1016/S0001-4575(03)00014-9

http://dx.doi.org/10.1016/S0001-4575(03)00014-9




Raskin, R., & Howard, T. (1988). A principal-components analysis of the Narcissistic Personality Inventory and further evidence of its construct valid-ity. Journal of Personality and Social Psychology, 54(5), 890–902. doi:10.1037/0022-3514.54.5.890 PMID:3379585

Roos, J. P. (2001, August). Postmodernity and mobile communications. Paper presented at the European Sociological Association 5th Conference of the ESA, Helsinki, Finland.

Rose, P. (2007). Mediators of the association between narcissism and compulsive buying. Psychology of Ad-dictive Behaviors, 21(14), 567–581. PMID:18072841

Rosen, L. D., Cheever, N. A., & Carrier, L. M. (2012). iDisorder: Understanding our obsession with tech-nology and overcoming its hold on us. New York: Palgrave Macmillan.

Rosen, L. D., Whaling, K., Rab, S., Carrier, L., & Cheever, N. (2013). Is Facebook Creating iDisorders? The link between clinical symptoms of psychiatric disorders and technology use, attitudes and anxiety. Computers in Human Behavior, 29(3), 1243–1254. doi:10.1016/j.chb.2012.11.012

Rosman, K. (2006). Blackberry orphans: the growing use of e-mail gadgets is spawning a generation of resentful children: a look at furtive thumb-typers, the signs of compulsive use and how kids are fighting back. Wall Street Journal, W1.

Salehan, M., & Negahban, A. (2013). Social network-ing on smartphones: When mobile phones become addictive. Computers in Human Behavior, 29(6), 2632–2639. doi:10.1016/j.chb.2013.07.003

Sarwar, M. (2013). Impact of Smartphones on Society. European Journal of Scientific Research, 98(2), 216–266.

Saucier, G. (1994). Mini-Markers: A Brief Version of Goldberg’s Unipolar Big-Five Markers. Jour-nal of Personality Assessment, 63(3), 506–516. doi:10.1207/s15327752jpa6303_8 PMID:7844738

Shin, C., & Dey, A. K. (2013, September). Automati-cally detecting problematic use of smartphones. In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing (pp. 335-344). ACM. doi:10.1145/2493432.2493443

Silva, V. (2012). iPhone sales boost smartphone market in 2011. Gartner.Retrieved from: http://www.cio-asia.com/tech/mobile-and-wireless/iphone-sales-boost-smartphone-market-in-2011-gartner/. Accessed on: 24th October 2013.

Siomos, K., Floros, G., Fisoun, V., Evaggelia, D., Farkonas, N., & Sergentani, E. et al. (2012). Evolution of Internet addiction in Greek adolescent students over a two-year period: The impact of parental bonding. European Child & Adolescent Psychiatry, 21(4), 211–219. doi:10.1007/s00787-012-0254-0 PMID:22311146

Stinson, F., Dawson, D., Goldstein, R., Chou, S., Huang, B., & Smith, S. et al. (2009). Prevalence, Correlates, Disability, and comorbidity of DSM-IV Narcissistic Personality Disorder: Results from the Wave 2 National Epidemiological Survey on Alcohol and Related Conditions. The Journal of Clinical Psychiatry, 69(7), 1033–1045. doi:10.4088/JCP.v69n0701 PMID:18557663

Twenge, J., & Campbell, W. (2013). Living in the Age of Entitlement: The Narcissism Epidemic. New York: Atria Books.

Wang, J., Jackson, L., Zhang, D., & Su, Z. (2012). The relationships among the Big Five Personality factors, self-esteem, narcissism and sensation-seeking to Chi-nese University Students’ uses of social networking sites (SNSs). Computers in Human Behavior, 28(6), 2313–2319. doi:10.1016/j.chb.2012.07.001

Whang, L., Lee, S., & Chang, G. (2003). Internet Over-User’s Psychological Profiles: A Behav-iour Sampling Analysis on Internet Addiction. Cyberpsychology & Behavior, 6(2), 143–150. doi:10.1089/109493103321640338 PMID:12804026

Widiger, T. (2011). Personality and Psychopathol-ogy. World Psychiatry; Official Journal of the World Psychiatric Association (WPA), 10(2), 103–106. PMID:21633679

Wood, R. T. A., Griffiths, M. D., & Eatough, V. (2004). Online data collection from video game players: Methodological issues. Cyberpsychology & Be-havior, 7(5), 511–518. doi:10.1089/cpb.2004.7.511 PMID:15667045

Wu, A., Cheung, V., Ku, L., & Hung, E. (2013). Psychological risk factors of addiction to social networking sites among Chinese smartphone us-ers. Journal of Behavioral Addictions, 10(6), 1–7. PMID:25215198

Yao, M., & Zhong, Z. (2014). Loneliness, social contacts and Internet addiction: A cross-lagged panel study. Computers in Human Behavior, 30, 164–170. doi:10.1016/j.chb.2013.08.007

Young, K. (1996). Internet Addiction: The emergence of a new clinical disorder. Cyberpsychology & Be-havior, 1(3), 237–244. doi:10.1089/cpb.1998.1.237

http://dx.doi.org/10.1037/0022-3514.54.5.890





http://dx.doi.org/10.1207/s15327752jpa6303_8


http://dx.doi.org/10.1145/2493432.2493443

http://www.cio-asia.com/tech/mobile-and-wireless/iphone-sales-boost-smartphone-market-in-2011-gartner/



http://dx.doi.org/10.1007/s00787-012-0254-0


http://dx.doi.org/10.4088/JCP.v69n0701

http://dx.doi.org/10.4088/JCP.v69n0701



http://dx.doi.org/10.1089/109493103321640338










Young, K. S. (2000). Therapeutic issues with internet addicted clients. New Therapist, 7, 12–13.

Young, K., Griffin-Shelley, E., Cooper, A., O’mara, J., & Buchannon, J. (2000). Online Infidelity: A new dimension in couple relationships with implications for evaluation and treatment. Sexual Addiction & Compulsivity. The Journal of Treatment & Preven-tion, 7(1-2), 59–74.

Smartphone Use, Addiction, Narcissism, and Personality: A Mixed Methods Investigation

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