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Personality and self reported mobile phone use
Computers in Human Behavior Computers in Human Behavior 24 (2008) 346–360 www.elsevier.com/locate/comphumbeh
Personality and self reported mobile phone use Sarah Butt, James G. Phillips
*
Psychology Department, Monash University, Wellington Road, Clayton, VIC 3800, Australia Available online 8 March 2007
Abstract As the mobile phone supports interpersonal interaction, mobile phone use might be a function of personality. This study sought to predict amounts and types of mobile phone use from extraversion, agreeableness, conscientiousness, neuroticism and self-esteem. One hundred and twelve mobile phone owners reported on their use of their mobile phones, and completed the NEO-FFI and the Coopersmith self-esteem inventory. Extraverts reported spending more time calling, and changing ring tone and wallpaper, implying the use of the mobile phone as a means of stimulation. Extraverts and perhaps disagreeable individuals were less likely to value incoming calls. Disagreeable extraverts also reported using the mobile phone more, and spent more time adjusting ringtone/wallpaper. The neurotic, disagreeable, unconscientious and extroverted spent more time messaging using SMS. This study concludes that psychological theory can explain patterns of mobile phone use. Crown Copyright Ó 2007 Published by Elsevier Ltd. All rights reserved. Keywords: Mobile phones; Personality; Extraversion; Agreeableness; SMS
1. Introduction Interpersonal transactions are a fundamental element of society (Argyle, 1984), and by extending the reach and immediacy of communication, the mobile phone has changed the scope of interpersonal interaction (Plant, 2000). Introduced to the Australian market in 1987, mobile phone connections exceeded the number of landline connections by 2001, and a nationwide estimate in 2004–5 revealed that at least 81% of the Australian population used a mobile phone (AMTA, 2005a). The phenomenal uptake of this technology *
Corresponding author. Tel.: +61 3 9905 3935; fax: +61 3 9905 3948. E-mail address: [email protected] (J.G. Phillips).
0747-5632/$ - see front matter Crown Copyright Ó 2007 Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.chb.2007.01.019
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indicates that it has struck a strong chord within the community in a way that some other technologies might not have (Horst, Kuttschreuter, & Gutteling, 2007). Hence a consideration of factors associated with the uptake of the mobile phone may be informative when contemplating other innovations. Nevertheless, despite having a tremendous impact on the lives of many people, the mobile phone has only recently started to attract the interest of psychologists. As a communication tool, the mobile phone is used mostly for either business or social purposes, but as it is such a personal device it is also used as an illustration of status, security and identity (Plant, 2000). It is therefore highly likely that the personality of an individual will predict types of mobile phone use (e.g. Bianchi & Phillips, 2005). The present paper addresses the psychological predispositions that might underpin mobile phone use. Previous studies have used the Five factor model of personality (Costa & McCrae, 1992) to address internet use (Landers & Lounsbury, 2006; Wyatt & Phillips, 2005). The present study considered whether personality traits such as neuroticism, extraversion, agreeableness, conscientiousness, or self- esteem will predict amount and type of mobile phone use. Plant (2000) observed that the model of the phone, the ring tone and wallpaper, are a display to others of who you are. As such the amounts of use of this communication channel, and the types of channels used may be informative (see Argyle, 1984), and may have implications for well being (Welford, 1966, 1987). The choice of communication channel (e.g. camera versus SMS) may offer information as to how much the communicator is prepared to disclose (see Luft & Ingham, 1955) or may offer information as to the types of interpersonal transactions that the communicator is prepared to engage in (Galin, Gross, & Gosalker, 2007; Guagdagno & Cialdini, 2007). In turn, the efficacy of these transactions may influence the user’s self-esteem. Hence it is likely that there will be relationships between mobile phone use and personality traits and perhaps well-being. 1.1. Self-esteem Low self-esteem has been linked with heavier amounts of internet use (Armstrong, Phillips, & Saling, 2000; Davis, 2001). Joinson (2004) tested whether self-esteem predicted the preference for different types of communication by Internet users. Users with low selfesteem expressed a significant preference for e-mail communication, while users with high self-esteem preferred face-to-face communication. According to Joinson, email offers people with low self-esteem increased control over an interaction and their own presentation (see McKenna & Bargh, 2000). These people are said to have depleted reserves of self worth to deal with rejection or negative feedback in social interactions. As SMS and e-mail operate in a similar fashion, it is therefore expected that self-esteem will predict the time spent sending and receiving SMS. For instance, Bianchi and Phillips (2005) observed that lower self-esteem was related to problems associated with mobile phone use. In addition, Reid and Reid (2004) have found that the preference for talk or text message use on the mobile phone is related to the personality of the user. Those who preferred to talk on their mobile phones favoured voice calls over receiving a text message and were significantly less socially anxious and lonely. There is comparatively little information available on the personality traits of mobile phone users, however, the five factor model potentially offers a recognised framework for researchers to employ (Costa & McCrae, 1992). The five factors used to describe personality are extroversion, neuroticism, agreeableness, conscientiousness and openness to
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experience. There are reasons to believe that some of these traits may predict mobile phone use. Extraversion is associated with traits such as warmth, gregariousness, assertiveness, activity, excitement-seeking and positive emotions (Anastasi & Urbina, 1997). Previous research into internet use has been equivocal, with qualitative studies arguing whether introverts or extraverts were more prone to heavier use (e.g. Griffiths, 1997; Shotton, 1989; Young, 1998). Longitudinal studies have observed that Internet use made Introverts more introverted (Kraut et al., 1998), whilst more extraverted types reported positive social effects (Kraut et al., 2002). This suggests that Internet use facilitates or supports pre-existing interests (Griffiths, 1996, 1998). Bianchi and Phillips (2005) observed that mobile phone users were more likely to be extraverted. This result is consistent with Amichai-Hamburger, Wainapel, and Fox (2002) findings that extraverts felt their true identity was accurately expressed through more traditional forms of social interaction. Conversely, past research suggests that greater introversion will be associated with more time spent sending and receiving SMS (Amichai-Hamburger et al., 2002; Kraut et al., 1998). But this is by no means certain, for instance, Wyatt and Phillips (2005) reported extraverts spent more time sending emails. Neuroticism is characterised by traits such as anxiety, self-consciousness and impulsiveness (Anastasi & Urbina, 1997). Hamburger and Ben-Artzi (2000) found neurotic women use the Internet for predominantly social purposes, while neurotic men were less likely to access information services. Amiel and Sargent (2004) revealed that neuroticism explained 24% of the variance in Internet motives and that those high in this trait reported using the Internet to feel part of a group and to escape loneliness. This suggests that the emotionally unstable are using the Internet as a replacement for traditional social interaction. Nevertheless, neurotic individuals were also found not to use text-messaging tools, such as email, or to take part in online discussions (Amiel & Sargent, 2004). Bianchi and Phillips (2005) did not find relationships between neuroticism and mobile phone use. Agreeableness is measured in terms of trust, altruism, compliance and modesty (Anastasi & Urbina, 1997). Studies have observed greater amounts of internet use in those who are low in agreeableness (Landers & Lounsbury, 2006; Wyatt & Phillips, 2005). This may reflect differences in interpersonal skill, or less agreeable people may just have more time on their hands (Landers & Lounsbury, 2006; Scealy, Phillips, & Stevenson, 2002). Bianchi and Phillips (2005) did not address agreeableness, but it may be of interest. For instance, there are indications that mobile phones may be used to harass or bully others (AMTA, 2003, 2005b; Charlton, Panting, & Hannan, 2002). Conscientiousness is characterised by competence, achievement, self-discipline and dutifulness (Anastasi & Urbina, 1997). Conscientiousness is of interest as Lavoie and Pychyl (2001) reported that 50.7% of Internet users sampled procrastinated through Internet use on a frequent basis. As the mobile phone is used for business and personal purposes (Bianchi & Phillips, 2005) conscientiousness may potentially predict mobile phone use. Openness to experience relates to an individual’s fantasies, ideas, actions, feelings and values (Anastasi & Urbina, 1997). Open individuals are often less conforming and have more unusual and widespread interests, which they seek using a larger variety of means. Young and Rodgers (1998) claim that dependent computer users have a need for stimulation that could lead to overuse and abuse of work access privileges. However, openness to experience appears to be related to searching behavior (Wyatt & Phillips, 2005). As searches are not one of the more accepted applications of mobile phones, openness
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to experience is unlikely to predict phone use, and was not considered in the present study. As personality is expected to influence interpersonal transactions (Eysenck, 1994) it should also predict mobile phone use. Agreeable extraverts would be expected to use their mobile phones more often. As extraverts are sensation seeking, they might also spend more time adjusting their phones’ appearance (tone, wallpaper). Personality should also predict the types of interactions that people are prepared to engage in (e.g., preference for voice over text). As SMS offers a greater opportunity to control social interaction (McKenna & Bargh, 2000), neurotic introverts with low self-esteem might be expected to prefer SMS. In addition, the less conscientious might prefer sending SMS to working. There might also be an interplay between efficacy of communication and personality. Therefore extraverts with high self esteem might be expected to receive more phone calls, while those with low self-esteem might receive more unwanted calls. 2. Method 2.1. Participants Two hundred questionnaires in total were circulated, of which 115 were returned (a response rate of 57.5%). Of the questionnaires returned 3 were blank and 112 were completed for adequate use in the study, hence resulting in 112 participants in this study (78 females, 34 males). Age ranged from 18 to 59 years with an average age of 28.36 (SD = 9.87). The highest level of education demographic revealed that the sample were typically university graduates. Involvement was restricted to those who owned mobile phones and who were 18 years of age and over. Participants were recruited from workplaces, university campuses and the general public. 2.2. Materials This study utilised the Coopersmith self-esteem inventory, the NEO-FFI, and a mobile phone use survey. 2.2.1. The Coopersmith self-esteem inventory The Coopersmith self-esteem inventory (SEI) is a 25-item questionnaire, developed to measure the evaluative attitudes toward the self in social, academic, family and personal areas of experiences (Coopersmith, 1989). In this study the SEI was employed to analyse the personality trait of self-esteem, which has been found to be associated with individual mobile phone and Internet usage. The SEI is reported to have an alpha coefficient 0.79 for males and 0.83 for females, indicative of a good level of reliability. It also has good constructive validity (Coopersmith, 1989). Reliability analysis in this study produced a respectable alpha coefficient of .77. 2.2.2. NEO-FFI The NEO-FFI is a self-administered 60-item version of the NEO PI-R Form S (Costa & McCrae, 1992). It is designed to measure the five major dimensions of personality, as described by the Five Factor Model of Personality. It uses five 12-item scales to measure Neuroticism, Extraversion, Openness, Agreeableness and Conscientiousness. Participant
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level of statement agreement is rated on a 5-point Likert scale: (1) strongly disagree, (2) disagree, (3) neutral, (4) agree or (5) strongly agree. Costa and McCrae state acceptable alpha coefficients of .86, .77, .73, .68 and .81 corresponding to N, E, O, A, and C scales. Costa and McCrae also report good convergent validity ranging from .56 to .62 and good construct validity. Reliability analysis of the five scales in this study revealed excellent alpha coefficients of .83, .81, .76, .74, .81 for N, E, O, A and C, respectively. 2.2.3. Mobile phone use survey The mobile phone use survey contained two sections, the first addressing demographic details and the second specific individual mobile phone usage. The demographic section consisted of three questions enquiring about the participant’s age, gender and level of education. The mobile phone usage section was made up of eight questions. Questions asked the average time each week spent: making and receiving calls; writing and receiving SMS; playing games; changing ring tone/wallpaper. Questions asked for an estimate of the average weekly amount of outgoing calls, and the percentages that would be for social and business purposes. Questions asked for an estimate of the average weekly amounts of incoming calls that were perceived as: wanted (i.e. likelihood of contacting caller back is high), and unwanted (i.e. likelihood of contacting caller back is low). Questions also addressed the: preference for the use of SMS or talking on a mobile phone; the degree of interest in mobile phone new features; and the length (in years) of mobile phone ownership. 2.3. Design This study uses six separate multiple regressions for analysis and therefore is correlative in design. Scores for the SEI and NEO-FFI were totalled as per the instructions in their respective manuals. Descriptive statistics for all of the variables in the mobile phone use survey were calculated. To determine whether reported mobile phone use could be predicted from personality variables, separate multiple regressions were conducted upon each dependent variable. The predictor variables were neuroticism, extraversion, agreeableness, conscientiousness measured by the NEO-FFI, and self-esteem as measured by the SEI. Of particular interest were the dependent variables weekly average amount of time (minutes) making and receiving calls, writing and receiving SMS, changing ring tone and/ or wall paper, number of ingoing and outgoing calls, and percentage of incoming calls perceived as unwanted. 2.4. Procedure Participants were recruited by personal appeal, poster recruitment and advertisement. Those participants wanting to take part in the study contacted the researchers via telephone or e-mail. Participants were asked for a postal address for the purposes of sending out the survey and two personality measures, with the understanding that once the materials were in transit that their details along with their name was erased. To further ensure their anonymity in the study participants were asked in the explanatory statement, attached to the survey not to write identifying details on any of the study materials.
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3. Results The data from the questionnaires was entered into SPSS (version 12.0). An alpha level of 0.05 was chosen to perform analyses. A small amount of random missing values was found throughout the data. One person only received calls, and so zero was the appropriate value for outgoing calls and any percents made. One person did not respond to the ‘‘unwanted calls’’, writing in the margin ‘‘what does this mean’’. This was left as missing. Three participants did not respond to the question on SMS use, and seventeen did not respond to the question on ring tone or wallpaper. Four participants failed to provide an answer to a specific item on the SEI. For these cases, the mean value for that specific item for the sample was substituted for the corresponding item mean. The procedure is conservative, as the individual becomes more like the mean response in the sample. A missing value was also found for one participant for one question on the NEO-FFI. This was dealt with according to the questionnaire manual (Costa & McCrae, 1992), and was assigned a neutral value. 3.1. Analysis of the independent variables Totals, means and standard deviations were calculated for Neuroticism, Extraversion, Agreeableness, Conscientiousness and SEI, in conjunction with the minimum, maximum, and skew for each of the independent variables. The descriptive statistics for both personality measures are analogous to the normative data outlined in the manuals (Coopersmith, 1989; Costa & McCrae, 1992). Table 1 illustrates the totals, means, standard deviations, minimum and maximum values, and skew for the independent variables. Table 1 illustrates that the mean for SEI is moderately high suggesting that the sample averaged a healthy level of self-esteem. Out of the five NEO-FFI scales the highest mean was for conscientiousness while the lowest mean was for Neuroticism. This indicates that participants were relatively conscientious and emotionally stable. Means for agreeableness and extraversion were comparable with published norms (Costa & McCrae, 1992). An inspection of the skew of the independent variables revealed that agreeableness was negatively skewed, hence this scale was inverted by subtracting it from its maximum value plus one before transformation. A square root transformation was used on the agreeableness variable. Due to the inversion of agreeableness this variable has now been renamed ‘‘disagreeableness’’ to help interpretation.
Table 1 Totals, means, standard deviations, minimum and maximum values, and skew for SEI, neuroticism, extraversion, openness, agreeableness and conscientiousness total scores Predictors
n
M
SD
Min.
Max.
Neuroticism Extraversion Agreeableness Conscientiousness SEI
112 112 112 112 112
20.73 30.26 31.82 34.5 75.32
8.04 6.57 6.14 6.54 16.5
2 14 8 15 32
38 43 46 48 100
(N = 112).
Skew .12 .14 1.0 .45 .58
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After the data was transformed the assumption of normality was met. A cut off of z ± 3.29, p < 0.001 was employed in the search for univariate outliers. Mahalanobis distance was used to screen for multivariate outliers. Cases with distances greater than 20.15 (v2, df = 5, p < 0.001) were expelled (Tabachnick & Fidell, 2000). After the application of transformations however, no univariate or multivariate outliers were identified, so no cases had to be excluded. To test for multi-collinearity, Pearson’s correlations were run on all predictors after transformation, which are presented in Table 2. Although several significant correlations were evident all correlations were well below the selection criteria of 0.99 (Tabachnick & Fidell, 2000). Hence this assumption was met. 3.2. Analysis of the dependent variables Totals, means and standard deviations were calculated for (a) weekly average time (minutes) making and receiving calls, (b) weekly amount of incoming calls, (c) the percentage of incoming calls that are perceived as unwanted, (d) weekly amount of outgoing calls, and (e) writing and receiving SMS along with minimum and maximum values, and skew. The results are presented in Table 3. Table 3 shows that the sample reported spending more time on average making and receiving calls than writing or receiving SMS. The mean is higher for incoming calls than for outgoing calls, thus the sample reported receiving more calls than making them. The mean for unwanted incoming calls suggests that on average only 13.5% of the sample perceived their incoming calls as unwanted. The least amount of time was spent changing ring tone and wallpaper. As all the dependent variables were positively skewed a log transform was applied after +1 was added to the scores, reducing the skew to achieve the assumption of normality. 3.2.1. Calls Separate multiple regression analyses were performed for each of the dependent variables with the independent variables, extraversion, neuroticism, agreeableness, conscienTable 2 Correlations between predictors and mobile phone use 2 1 Neuroticism 2 Extraversion 3 (dis)Agreeablenessa 4 Conscientiousness 5 Self-esteem 6 Calls (time per week)b 7 Incoming calls (time per week)b 8 Unwanted percentageb 9 Outgoing calls (time per week)b 10 SMS (time per week)b 11 Tone or wallpaper (time per week)b a b * **
3 **
.32
Scores inverted and square root transformed. Scores +1 are log 10 transformed. p < .05. p < .01.
4 *
.21 .17
5 **
6 **
.30 .64 .27** .39** .29** .30** .33**
7 .068 .224* .245* .068 .129
8 .072 .276** .265** .072 .027 .763**
9 .089 .187* .230* .173 .157 .314** .240*
10 .036 .131 .165 .061 .065 .710** .795** .088
11 **
.272 .206* .264** .239* .198* .602** .357** .401** .301**
.305** .057 .313** .107 .315** .268** .159 .270** .060 .404**
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Table 3 Totals, means and standard deviations along with minimum, maximum and skew for weekly average time (minutes) making and receiving calls, writing and receiving SMS and the percentage of incoming calls that are perceived as unwanted DV
n
M
SD
Min.
Max.
Skew
Calls (mins) Incoming calls Unwanted (%) Outgoing calls SMS (mins) Tone/wall (mins)
112 112 111 111 105 95
149.29 30.13 13.5 22.89 104.1 10.53
222.38 45.47 19.45 30.53 229.0 62.25
2.00 1.00 .00 .00 .00 .00
1080 300 99 150 1710 600
2.498 3.37 2.232 2.290 5.688 9.242
tiousness and self- esteem. The independent variables predicted 12.2% of the variance in average amount of time spent making and receiving calls [F(5, 106) = 4.076, p = .002]. Extraverted [t(106) = 3.50, p = .001] and disagreeable [t(106) = 2.51, p = .014] people were more likely to spend more time weekly making and receiving calls. The results of this multiple regression are presented in Table 4. 3.2.2. Incoming calls The independent variables predicted 15.6% of the variance in the number of calls received weekly [F(5, 106) = 5.090, p < .001]. Extraverted [t(106) = 3.71, p < .001] and disagreeable [t(106) = 3.08, p = .003] people were more likely to report receiving more calls (see Table 5). 3.2.3. Unwanted incoming call perception The independent variables were able to predict 12% of variance in the percentage of incoming calls perceived as unwanted [F(5, 106) = 4.015, p = .002]. Extraversion predicted
Table 4 Standardised regression coefficient (b), t-value of b and significance for predictors of average time spent making and receiving calls Predictors
t
b
Neuroticism Extraversion Disagreeableness Conscientiousness SEI
.01 .34 .24 .03 .18
p .05 3.50 2.51 .34 1.43
.96 .001 .014 .73 .155
Table 5 Standardised regression coefficient (b), t-value of b and significance for predictors of amount of incoming calls Predictors Neuroticism Extraversion Disagreeableness Conscientiousness SEI
t
b .13 .36 .29 .08 .14
p 1.11 3.7 3.08 .83 1.13
.269 .000 .003 .408 .261
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unwantedness [t(106) = 3.35, p = .001] and there was a trend for disagreeableness [t(106) = 1.965, p = .052] to predict unwantedness of incoming calls. Extraverted and possibly disagreeable people were more likely to report that incoming calls were unwanted (see Table 6). 3.2.4. Outgoing calls The independent variables did not significantly predict the number of calls made weekly [F(5, 106) = 1.582, p = .171]. No significant multiple regression coefficients were produced (see Table 7). 3.2.5. SMS The independent variables significantly predicted 23.6% of the variance in average amount of time spent writing and receiving SMS [F(5,102) = 7.67, p = .000]. Extraverted [t(103) = 4.41, p = .000], neurotic [t(103) = 2.15, p = .034], unconscientious [t(103) = 2.037, p = .044] people were more likely to spend more time weekly writing and receiving SMS. Disagreeableness was also a predictor [t(103) = 2.182, p = .031] (see Table 8). 3.2.6. Ring-tone/wallpaper As Bianchi and Phillips (2005) implied that people used their mobile phones for stimulatory purposes, we also considered the self reported time spent adjusting ring tones or phone wallpaper. The independent variables significantly predicted 16.8% of the variance in average amount of time spent changing ring-tone and/or wallpaper [F(5, 89) = 4.795, p < .001]. Extraverted [t(89) = 2.16, p = .05] and disagreeable [t(89) = 2.52, p = .013] people were more likely to spend significantly more time weekly changing the ring tone and wallpaper on their mobile phones (see Table 9).
Table 6 Standardised regression coefficient (b), t-value of b and significance for predictors of percentage of incoming calls perceived as unwanted Predictors Neuroticism Extraversion Disagreeableness Conscientiousness SEI
t
b .007 .329 .188 .150 .184
p .058 3.347 1.965 1.531 1.495
.954 .001 .052 .129 .138
Table 7 Standardised regression coefficient (b), t-value of b and significance for predictors of amount of outgoing calls Predictors Neuroticism Extraversion Disagreeableness Conscientiousness SEI
t
b .12 .19 .16 .05 .15
p .98 1.86 1.6 .52 1.18
.328 .065 .112 .603 .243
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Table 8 Standardised regression coefficient (b), t-value of b and significance for predictors of average time spent writing and receiving SMS Predictors
t
b
Neuroticism Extraversion Disagreeableness Conscientiousness SEI
.241 .409 .197 .188 .108
p 2.15 4.41 2.18 2.04 .93
.034 .000 .031 .044 .356
Table 9 Standardised regression coefficient (b), t-value of b and significance for predictors of average time spent changing ring tone and/or wallpaper Predictors Neuroticism Extraversion Disagreeableness Conscientiousness SEI
t
b .21 .22 .26 .01 .17
p 1.65 2.16 2.52 .13 1.31
.10 .034 .013 .89 .19
4. Discussion The mobile phone extends the reach and immediacy of interpersonal transactions (Plant, 2000). Hence it is not surprising that personality might predict mobile phone use. We predicted that personality might predict the types of interpersonal transactions that people were prepared to engage in, and the efficacy of these transactions might have implications for self-esteem. Indeed, the present study found that disagreeable extraverts reported spending more time on their mobile phones, although they might value their incoming communications less. On the other hand, it was the extraverted, neurotic, disagreeable, and unconscientious individuals that reported spending more time writing and receiving SMS. However, there was only weak or indirect support for the expected relationships between mobile phone use and self-esteem. Personality could predict mobile phone use. Overall levels of phone use could be predicted from extraversion and disagreeableness. In particular, personality could predict some elements of the interpersonal transactions that the communicator was prepared to engage in (Argyle, 1984). The present study observed efforts by the individual to control their self-presentation. As a communication channel the mobile phone affords the user control over the range of cues provided to others (i.e. textual, aural, and visual). For instance, disagreeable extraverts focussed upon the superficial elements of their mobile phone such as ring tone and wallpaper, presumably for self stimulatory purposes (Bianchi & Phillips, 2005) or for the purposes of attracting the attention of others (Welford, 1977). On the other hand, there were indications that SMS was used by people who in some way wanted to control or limit the amounts of information (e.g. aural, visual) transmitted about themselves. SMS users were more likely to be neurotic, extraverted, disagreeable, or unconscientious. Disagreeable individuals spent more time on their phone as a ‘‘display’’, while neurotic or unconscientious persons, with their reliance upon SMS were less
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likely to use the phone to transmit more information about themselves (Argyle, 1984; Luft, 1970; McKenna & Bargh, 2000). It was expected that the quality of interpersonal transactions associated with mobile phone use would have implications for self esteem. Nevertheless, in the present data there was little direct evidence for relationships between mobile phone use and self-esteem. Disagreeable extraverts used their mobiles more, but tended to report more unwanted incoming calls. And this implies that agreeable introverts valued their incoming calls more. Those with poorer self-esteem may have tended to report more unwanted phone calls, but any relationships were weak. Instead, we observed relationships between SMS use and personality. SMS was more likely to be used by neurotic individuals. Neurotic individual’s concern as to their presentation may cause them to limit the information they reveal about themselves. As neuroticism is more likely to be associated with negative emotions such as depression (Anastasi & Urbina, 1997), there are indications that self-esteem could be a predictor of mobile phone use. There was some suggestion that people with low self-esteem might potentially spend less time fiddling with ring tones or wallpaper, or prefer SMS, but other variables such as agreeableness were better predictors. Hence the present data appear to contrast with that of Bianchi and Phillips (2005) who found relationships between self-esteem and self reported mobile phone use. However, the relationships observed by Bianchi and Phillips (2005) actually involved problem use. Individuals with low self-esteem were more likely to report problems associated with their mobile phone use. But there was little direct evidence to suggest that mobile phone use was associated with differences in self-esteem in the present study. 4.1. Extraverts Extraverts are recognised for having an extensive social network (Costa & McCrae, 1992), therefore it is not surprising to find that extraverts received more incoming calls. As extraversion did not predict the number of outgoing calls, it cannot be assumed that extraverts receive more calls simply because they have more friends. Instead it suggests the possibility that people feel more comfortable calling extraverts because their optimistic and talkative character seems to reassure many individuals (Gotlib & Hammen, 1992). Alternatively, extraverts may not want incoming calls, because they are supervisory in nature. Extraverts are sensation seekers and risk takers (Eysenck, 1994; Trimpop, 1994). Incoming calls may be from individuals who wish to monitor the activities of extraverts (Geser, 2004). The mobile phone potentially makes a mobile phone owner continuously available, and this may be used to the advantage of the caller. For instance mobile phones allow women to monitor their husband’s or children’s activities. 4.2. Agreeableness Agreeableness is a trait that is most concerned with interpersonal relationships, that are based on the equal and honest exchange of information (DeRaad, 2000). However, disagreeableness predicted incoming phone calls, and this is surprising as one might expect people would prefer to phone agreeable people. Disagreeable people score low on trust, straightforwardness, altruism, compliance, modesty and tender-mindedness. The disagreeable individual as described by Costa and McCrae (1992) is principally selfish, uncooper-
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ative, and not afraid to look out for number one. Indeed, Costa and McCrae (1990) have revealed there to be an association between low agreeableness and Narcissistic and Antisocial Personality Disorders. The greater use of the mobile phone by disagreeable people could be attributed to tendencies for disagreeable people not to care what others think. Disagreeable people would possibly choose not to adhere to the mobile phone standards of etiquette, answering their phones during a face-to-face conversation, making and taking calls in inappropriate places such as during meetings, lectures or movies (Bianchi & Phillips, 2005). However, it was more surprising that disagreeable people reported more incoming phone calls. It is possible that people would rather phone a disagreeable person than be in the same room with them. There are certainly relationships between poorer interpersonal skills and internet use (Kraut et al., 1998; Scealy et al., 2002). Alternatively, people might phone a disagreeable person to argue or remind them of their interpersonal obligations. 4.3. Neuroticism Bianchi and Phillips (2005) suggested that people who score high on neuroticism do not find the mobile phone appealing. They may not be using their mobile phone the most, but this does not mean that they do not use the phone at all. This study supported the expectation that neuroticism could explain time spent SMSing. This is consistent with the findings of Reid and Reid (2004) that people who are more socially anxious and lonely prefer to use SMS as a means of communication due to feeling that they can better express their true selves. Amichai-Hamburger et al. (2002) have also presented similar findings for email preference. SMS does not require face-to-face communication, thus it may be favoured by the emotionally unstable. Like Internet e-mail, mobile phone text messaging is not visually based and therefore has been suggested to make people feel more comfortable when communicating because it is disinhibiting (Griffiths, 2001; Suler, 2004). As has been found with low self-esteem e-mailers, it is also possible that SMS eases a neurotic individual’s anxiety about misinterpretation by allowing the time to construct how they want to be portrayed and exactly what they want to say in a message (Joinson, 2004). SMS allows more control over the communication and what it reveals (see McKenna & Bargh, 2000). Although the use of mobile phones for business purposes led to expectations that conscientiousness might predict mobile phone use, this study found that unconscientious individuals were spending more time writing and receiving SMS. This supports the findings of Lavoie and Pychyl (2001) who revealed that unconscientious people are more likely to use the Internet at work to procrastinate. It seems that SMS may be a favoured mobile phone function of the less self disciplined individual that could be used to procrastinate or perhaps serve as a source of distraction. Since conscientiousness did not predict time spent making or receiving calls it is possible that casual or personal use is kept exclusively to SMS. SMS might be favoured over other channels such as email, due to the increasingly depersonalised (SPAM) and documented (Gottschalk, 2005) nature of email. 5. Implications A consideration of factors contributing to mobile phone acceptance may offer insights as to other forms of applications such as E-government or I-gaming (Griffiths, 2003). In
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contrast with the widespread acceptance of mobile phones, E-government does not enjoy the same levels of acceptance (Horst et al., 2007). In contrast to E-government services as delivered over a desktop link, the mobile phone has more features that attract and capture attention (Griffiths, 2003). The mobile phone is extrinsically rewarding, as it delivers immediate access to people or services. The mobile phone is also intrinsically rewarding, as it offers opportunities to customise, control and manipulate the interface (Griffiths, 2003). In particular, the immediacy and frequency of signalling has attention capturing properties (Griffiths, 2003; Wood, Griffiths, Chappell, & Davies, 2004) that promote regular monitoring. It remains to be seen whether factors like extraversion, disagreeableness or unconscientiousness can predict the success of programs such as I-gaming (Griffiths, 2003). But the present data implies that there is a section of the community that might abuse such services. 6. Future research This study chose to use self-report measures owing to convenience, instead of behavioural measures, which are known to provide more accurate measurements. Higgins, McClean, and Conrath (1985) determined that self reported use of telephone communications, obtained through self-recording diary entries, under recorded received calls. It was concluded that when there is an absence of objective data self-report measures provide usable information, although are inherently prone to bias. Even though users would receive itemised bills, it is possible that incoming calls were under-reported by the sample, thus influencing the potential accuracy of the results. Future research could consider exploring mobile phone behaviour using objective measures to gain a more accurate and realistic account of individual use. For example researchers could supply mobile phones to their participants, or use SMS to collect data. 7. Conclusion Personality traits can explain patterns of mobile phone use. Disagreeable extraverts reported spending the more time using the mobile phone, specifically receiving more calls and changing their phones’ appearance. But while extraverts received more calls, they valued them less. Whilst it appears that unconscientious, emotionally unstable, disagreeable extraverts are spending more time SMSing. Unexpectedly self esteem did not correlate well with amounts or types of mobile phone use, suggesting that disagreeableness is a more important predictor of amounts and types of mobile phone use. Personality can predict the amounts of phone use, and the preference for a specific style of communication channel. Acknowledgement The authors acknowledge the perspective and ideas of Dr. Peter Ostojic of Telstra Research Laboratories. References Amichai-Hamburger, Y., Wainapel, G., & Fox, S. (2002). On the Internet no one knows I’m an introvert: extroversion, neuroticism, and Internet interaction. CyberPsychology & Behavior, 5, 125–128.
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Amiel, T., & Sargent, S. L. (2004). Individual differences in Internet usage motives. Computers in Human Behaviour, 20, 711–726. AMTA (2003). Cameras and mobile phones. http://www.amta.org.au/default.asp?Page=211. AMTA (2005a). Australian Mobile Telecommunications Association, Annual report 2005. http://www.amta.org.au/amta/site/amta/downloads/pdfs_2005/AMTA05.pdf. AMTA (2005b). What you need to know to get the bullies off your back. http://www.amta.org.au/ default.asp?Page=495. Anastasi, A., & Urbina, S. (1997). Psychological testing (7th ed.). New Jersey: Prentice-Hall. Argyle, M. (1984). The psychology of interpersonal behaviour. Middlesex, England: Penguin Books. Armstrong, L., Phillips, J. G., & Saling, L. L. (2000). Potential determinants of heavier Internet usage. International Journal of Human-Computer Studies, 53, 537–550. Bianchi, A., & Phillips, J. G. (2005). Psychological predictors of problem mobile phone use. CyberPsychology & Behavior, 8, 39–51. Charlton, T., Panting, C., & Hannan, A. (2002). Mobile telephone ownership and usage among 10- and 11-year olds: Participation and exclusion. Emotional and Behavioral Difficulties, 7, 152–163. Coopersmith, S. (1989). Self-esteem inventories. Palo Alto, CA: Consulting Psychologists Press. Costa, P. T., Jr., & McCrae, R. R. (1992). NEOPI-R professionai manual. Odessa: Psychological Assessment Resources, Inc. Costa, P. T., Jr., & McCrae, R. R. (1990). Personality disorders and the five-factor model of personality. Journal of Personality Disorders, 4, 362–371. Davis, R. (2001). A cognitive-behavioral model of pathological internet use. Computers in Human Behavior, 17, 187–195. DeRaad, B. (2000). The big five personality factors: The psycholexical approach to personality. Seattle, Toronto: Gohrefe & Huber Publishers. Eysenck, H. J. (1994). Personality: biological foundations. In P. A. Vernon (Ed.), The neuropsychology of individual differences (pp. 151–207). San Diego: Academice Press. Geser, H., 2004. Towards a sociological theory of the mobile phone. Retrieved August 30, 2005, http://socio.ch/ mobile/index_mobile.htm. Galin, A., Gross, M., & Gosalker, G. (2007). E-negotiation versus face-to-face negotiation what has changed if anything? Computers in Human Behavior, 23, 787–797. Gotlib, I. H., & Hammen, C. L. (1992). Psychological aspects of depression: Toward a cognitive-interpersonal integration. West Sussex, England: John Wiley & Sons. Gottschalk, J. (2005). The risks associated with the business use of email. Intellectual Property & Technology Law Journal, 17(7), 16–18. Griffiths, M. (1996). Gambling on the Internet: a brief note. Journal of Gambling Studies, 12, 471–473. Griffiths, M. D. (1997). Psychology of computer use: XL III Some comments on ‘‘Addictive use of the Internet’’ by Young. Psychology Reports, 80, 81–82. Griffiths, M. D. (1998). Internet addiction: Does it really exist? In J. Gackenbach (Ed.), Psychology and the Internet: Interpersonal and transpersonal applications (pp. 61–75). New York: Academic Press. Griffiths, M. (2001). Sex on the Internet: observations and implications for Internet sex addiction [Electronic version]. The Journal of Sex Research, 38, 333–342. Griffiths, M. D. (2003). Internet gambling: issues, concerns and recommendations. CyberPsychology & Behavior, 6(6), 557–568. Guagdagno, R. E., & Cialdini, R. B. (2007). Persuade him by email but see her in person: Online persuasion revisited. Computers in Human Behavior, 23(2), 999–1015. Hamburger, Y. A., & Ben-Artzi, E. (2000). The relationship between extraversion and neuroticism and the different uses of the Internet [Electronic version]. Computers in Human Behavior, 16, 441–449. Higgins, C. A., McClean, R. J., & Conrath, D. W. (1985). The accuracy and biases of diary communication data. Social Networks, 7(2), 173–187. Horst, M., Kuttschreuter, M., & Gutteling, J. M. (2007). Perceived usefulness, personal experiences, risk perception and trust as determinants of adoption of e-government services in The Netherlands. Computers in Human Behavior, 23, 1838–1852. Joinson, A. N. (2004). Self-esteem, interpersonal risk, and preference for e-mail to face-to-face communication. CyberPsychology & Behavior, 7, 472–478. Kraut, R., Kiesler, S., Boneva, B., Cummings, J., Helgeson, V., & Crawford, A. (2002). Internet paradox revisited [Electronic version]. Journal of Social Issues, 58, 49–74.
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Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukapadhyay, T., & Scher1is, W. (1998). Internet-paradox: a social technology that reduces social involvement and psychological well being? [Electronic version]. American Psychologist, 53, 1017–1031. Landers, R. N., & Lounsbury, J. W. (2006). An investigation of big five and narrow personality traits in relation to Internet usage. Computers in Human Behavior, 22, 283–293. Lavoie, J., & Pychyl, T. (2001). Cyber-s1acking and the procrastination superhighway: a web based survey of online procrastination, attitudes, and emotions. Social Science Computer Review, 19, 431–444. Luft, J. (1970). Group processes: An introduction to group dynamics. Palo Alto, CA: National Press Books. Luft, J. & Ingham, H. (1955). The Johari-window: A graphic model for interpersonal relations. University of California, Western Training Laboratory. McKenna, K. Y. A., & Bargh, J. A. (2000). Plan 9 from Cyberspace: the implications of the Internet for personality and social psychology. Personality and Social Psychology Review, 4, 57–75. Plant, S. (2000). ‘On The Mobile: The Effect of Mobile Telephones on Social and Individual Life’[WWW document]. Retrieved September 10,2005, from, http://www.motorola.com. Reid, D., & Reid, F. (2004). Insights into the social and psychological effects of SMS text messaging. Retrieved June 25, 2005, from, http://socio.ch/mobile/index_mobile.htm. Scealy, M., Phillips, J., & Stevenson, R. (2002). Shyness and anxiety as predictors of patterns of Internet usage. CyberPsychology & Behavior, 5(6), 507–515. Shotton, M. (1989). Computer addiction? A study of computer dependency. New York: Taylor and Francis. Suler, J. (2004). The online disinhibition effect. CyberPsychology & Behavior, 7(3), 321–326. Tabachnick, B. G., & Fidell, L. S. (2000). Using multivariate statistics (4th ed.). Boston: Allyn & Bacon. Trimpop, R. M. (1994). The psychology of risk taking behavior. Amsterdam: North-Holland. Welford, A. T. (1966). The ergonomic approach to social behaviour. Ergonomics, 9, 357–369. Welford, A. T. (1977). Desire for attention. Australian and New Zealand Journal of Psychiatry, 11(3), 157–161. Welford, A. T. (1987). Ergonomics of human relations. Ergonomics, 30, 3–8. Wood, T. A., Griffiths, M. D., Chappell, D., & Davies, M. N. O. (2004). The structural characteristics of video games: a psycho-structural analysis. CyberPsychology & Behavior, 7, 1–10. Wyatt, K. & Phillips, J.G. (2005). Internet use and misuse in the workplace. Paper presented at OZCHI2005, Canberra, November 2005. Young, K. (1998). Internet addiction: the emergence of a new clinical disorder. CyberPsychology & Behavior, 1(3), 237–244. Young, K. & Rodgers, R. (1998). Internet addiction: personality traits associated with its development. Paper presented at the 69 Annual Meeting of the Eastern Psychological Association.
Personality and self reported mobile phone use Sarah Butt, James G. Phillips
*
Psychology Department, Monash University, Wellington Road, Clayton, VIC 3800, Australia Available online 8 March 2007
Abstract As the mobile phone supports interpersonal interaction, mobile phone use might be a function of personality. This study sought to predict amounts and types of mobile phone use from extraversion, agreeableness, conscientiousness, neuroticism and self-esteem. One hundred and twelve mobile phone owners reported on their use of their mobile phones, and completed the NEO-FFI and the Coopersmith self-esteem inventory. Extraverts reported spending more time calling, and changing ring tone and wallpaper, implying the use of the mobile phone as a means of stimulation. Extraverts and perhaps disagreeable individuals were less likely to value incoming calls. Disagreeable extraverts also reported using the mobile phone more, and spent more time adjusting ringtone/wallpaper. The neurotic, disagreeable, unconscientious and extroverted spent more time messaging using SMS. This study concludes that psychological theory can explain patterns of mobile phone use. Crown Copyright Ó 2007 Published by Elsevier Ltd. All rights reserved. Keywords: Mobile phones; Personality; Extraversion; Agreeableness; SMS
1. Introduction Interpersonal transactions are a fundamental element of society (Argyle, 1984), and by extending the reach and immediacy of communication, the mobile phone has changed the scope of interpersonal interaction (Plant, 2000). Introduced to the Australian market in 1987, mobile phone connections exceeded the number of landline connections by 2001, and a nationwide estimate in 2004–5 revealed that at least 81% of the Australian population used a mobile phone (AMTA, 2005a). The phenomenal uptake of this technology *
Corresponding author. Tel.: +61 3 9905 3935; fax: +61 3 9905 3948. E-mail address: [email protected] (J.G. Phillips).
0747-5632/$ - see front matter Crown Copyright Ó 2007 Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.chb.2007.01.019
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indicates that it has struck a strong chord within the community in a way that some other technologies might not have (Horst, Kuttschreuter, & Gutteling, 2007). Hence a consideration of factors associated with the uptake of the mobile phone may be informative when contemplating other innovations. Nevertheless, despite having a tremendous impact on the lives of many people, the mobile phone has only recently started to attract the interest of psychologists. As a communication tool, the mobile phone is used mostly for either business or social purposes, but as it is such a personal device it is also used as an illustration of status, security and identity (Plant, 2000). It is therefore highly likely that the personality of an individual will predict types of mobile phone use (e.g. Bianchi & Phillips, 2005). The present paper addresses the psychological predispositions that might underpin mobile phone use. Previous studies have used the Five factor model of personality (Costa & McCrae, 1992) to address internet use (Landers & Lounsbury, 2006; Wyatt & Phillips, 2005). The present study considered whether personality traits such as neuroticism, extraversion, agreeableness, conscientiousness, or self- esteem will predict amount and type of mobile phone use. Plant (2000) observed that the model of the phone, the ring tone and wallpaper, are a display to others of who you are. As such the amounts of use of this communication channel, and the types of channels used may be informative (see Argyle, 1984), and may have implications for well being (Welford, 1966, 1987). The choice of communication channel (e.g. camera versus SMS) may offer information as to how much the communicator is prepared to disclose (see Luft & Ingham, 1955) or may offer information as to the types of interpersonal transactions that the communicator is prepared to engage in (Galin, Gross, & Gosalker, 2007; Guagdagno & Cialdini, 2007). In turn, the efficacy of these transactions may influence the user’s self-esteem. Hence it is likely that there will be relationships between mobile phone use and personality traits and perhaps well-being. 1.1. Self-esteem Low self-esteem has been linked with heavier amounts of internet use (Armstrong, Phillips, & Saling, 2000; Davis, 2001). Joinson (2004) tested whether self-esteem predicted the preference for different types of communication by Internet users. Users with low selfesteem expressed a significant preference for e-mail communication, while users with high self-esteem preferred face-to-face communication. According to Joinson, email offers people with low self-esteem increased control over an interaction and their own presentation (see McKenna & Bargh, 2000). These people are said to have depleted reserves of self worth to deal with rejection or negative feedback in social interactions. As SMS and e-mail operate in a similar fashion, it is therefore expected that self-esteem will predict the time spent sending and receiving SMS. For instance, Bianchi and Phillips (2005) observed that lower self-esteem was related to problems associated with mobile phone use. In addition, Reid and Reid (2004) have found that the preference for talk or text message use on the mobile phone is related to the personality of the user. Those who preferred to talk on their mobile phones favoured voice calls over receiving a text message and were significantly less socially anxious and lonely. There is comparatively little information available on the personality traits of mobile phone users, however, the five factor model potentially offers a recognised framework for researchers to employ (Costa & McCrae, 1992). The five factors used to describe personality are extroversion, neuroticism, agreeableness, conscientiousness and openness to
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experience. There are reasons to believe that some of these traits may predict mobile phone use. Extraversion is associated with traits such as warmth, gregariousness, assertiveness, activity, excitement-seeking and positive emotions (Anastasi & Urbina, 1997). Previous research into internet use has been equivocal, with qualitative studies arguing whether introverts or extraverts were more prone to heavier use (e.g. Griffiths, 1997; Shotton, 1989; Young, 1998). Longitudinal studies have observed that Internet use made Introverts more introverted (Kraut et al., 1998), whilst more extraverted types reported positive social effects (Kraut et al., 2002). This suggests that Internet use facilitates or supports pre-existing interests (Griffiths, 1996, 1998). Bianchi and Phillips (2005) observed that mobile phone users were more likely to be extraverted. This result is consistent with Amichai-Hamburger, Wainapel, and Fox (2002) findings that extraverts felt their true identity was accurately expressed through more traditional forms of social interaction. Conversely, past research suggests that greater introversion will be associated with more time spent sending and receiving SMS (Amichai-Hamburger et al., 2002; Kraut et al., 1998). But this is by no means certain, for instance, Wyatt and Phillips (2005) reported extraverts spent more time sending emails. Neuroticism is characterised by traits such as anxiety, self-consciousness and impulsiveness (Anastasi & Urbina, 1997). Hamburger and Ben-Artzi (2000) found neurotic women use the Internet for predominantly social purposes, while neurotic men were less likely to access information services. Amiel and Sargent (2004) revealed that neuroticism explained 24% of the variance in Internet motives and that those high in this trait reported using the Internet to feel part of a group and to escape loneliness. This suggests that the emotionally unstable are using the Internet as a replacement for traditional social interaction. Nevertheless, neurotic individuals were also found not to use text-messaging tools, such as email, or to take part in online discussions (Amiel & Sargent, 2004). Bianchi and Phillips (2005) did not find relationships between neuroticism and mobile phone use. Agreeableness is measured in terms of trust, altruism, compliance and modesty (Anastasi & Urbina, 1997). Studies have observed greater amounts of internet use in those who are low in agreeableness (Landers & Lounsbury, 2006; Wyatt & Phillips, 2005). This may reflect differences in interpersonal skill, or less agreeable people may just have more time on their hands (Landers & Lounsbury, 2006; Scealy, Phillips, & Stevenson, 2002). Bianchi and Phillips (2005) did not address agreeableness, but it may be of interest. For instance, there are indications that mobile phones may be used to harass or bully others (AMTA, 2003, 2005b; Charlton, Panting, & Hannan, 2002). Conscientiousness is characterised by competence, achievement, self-discipline and dutifulness (Anastasi & Urbina, 1997). Conscientiousness is of interest as Lavoie and Pychyl (2001) reported that 50.7% of Internet users sampled procrastinated through Internet use on a frequent basis. As the mobile phone is used for business and personal purposes (Bianchi & Phillips, 2005) conscientiousness may potentially predict mobile phone use. Openness to experience relates to an individual’s fantasies, ideas, actions, feelings and values (Anastasi & Urbina, 1997). Open individuals are often less conforming and have more unusual and widespread interests, which they seek using a larger variety of means. Young and Rodgers (1998) claim that dependent computer users have a need for stimulation that could lead to overuse and abuse of work access privileges. However, openness to experience appears to be related to searching behavior (Wyatt & Phillips, 2005). As searches are not one of the more accepted applications of mobile phones, openness
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to experience is unlikely to predict phone use, and was not considered in the present study. As personality is expected to influence interpersonal transactions (Eysenck, 1994) it should also predict mobile phone use. Agreeable extraverts would be expected to use their mobile phones more often. As extraverts are sensation seeking, they might also spend more time adjusting their phones’ appearance (tone, wallpaper). Personality should also predict the types of interactions that people are prepared to engage in (e.g., preference for voice over text). As SMS offers a greater opportunity to control social interaction (McKenna & Bargh, 2000), neurotic introverts with low self-esteem might be expected to prefer SMS. In addition, the less conscientious might prefer sending SMS to working. There might also be an interplay between efficacy of communication and personality. Therefore extraverts with high self esteem might be expected to receive more phone calls, while those with low self-esteem might receive more unwanted calls. 2. Method 2.1. Participants Two hundred questionnaires in total were circulated, of which 115 were returned (a response rate of 57.5%). Of the questionnaires returned 3 were blank and 112 were completed for adequate use in the study, hence resulting in 112 participants in this study (78 females, 34 males). Age ranged from 18 to 59 years with an average age of 28.36 (SD = 9.87). The highest level of education demographic revealed that the sample were typically university graduates. Involvement was restricted to those who owned mobile phones and who were 18 years of age and over. Participants were recruited from workplaces, university campuses and the general public. 2.2. Materials This study utilised the Coopersmith self-esteem inventory, the NEO-FFI, and a mobile phone use survey. 2.2.1. The Coopersmith self-esteem inventory The Coopersmith self-esteem inventory (SEI) is a 25-item questionnaire, developed to measure the evaluative attitudes toward the self in social, academic, family and personal areas of experiences (Coopersmith, 1989). In this study the SEI was employed to analyse the personality trait of self-esteem, which has been found to be associated with individual mobile phone and Internet usage. The SEI is reported to have an alpha coefficient 0.79 for males and 0.83 for females, indicative of a good level of reliability. It also has good constructive validity (Coopersmith, 1989). Reliability analysis in this study produced a respectable alpha coefficient of .77. 2.2.2. NEO-FFI The NEO-FFI is a self-administered 60-item version of the NEO PI-R Form S (Costa & McCrae, 1992). It is designed to measure the five major dimensions of personality, as described by the Five Factor Model of Personality. It uses five 12-item scales to measure Neuroticism, Extraversion, Openness, Agreeableness and Conscientiousness. Participant
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level of statement agreement is rated on a 5-point Likert scale: (1) strongly disagree, (2) disagree, (3) neutral, (4) agree or (5) strongly agree. Costa and McCrae state acceptable alpha coefficients of .86, .77, .73, .68 and .81 corresponding to N, E, O, A, and C scales. Costa and McCrae also report good convergent validity ranging from .56 to .62 and good construct validity. Reliability analysis of the five scales in this study revealed excellent alpha coefficients of .83, .81, .76, .74, .81 for N, E, O, A and C, respectively. 2.2.3. Mobile phone use survey The mobile phone use survey contained two sections, the first addressing demographic details and the second specific individual mobile phone usage. The demographic section consisted of three questions enquiring about the participant’s age, gender and level of education. The mobile phone usage section was made up of eight questions. Questions asked the average time each week spent: making and receiving calls; writing and receiving SMS; playing games; changing ring tone/wallpaper. Questions asked for an estimate of the average weekly amount of outgoing calls, and the percentages that would be for social and business purposes. Questions asked for an estimate of the average weekly amounts of incoming calls that were perceived as: wanted (i.e. likelihood of contacting caller back is high), and unwanted (i.e. likelihood of contacting caller back is low). Questions also addressed the: preference for the use of SMS or talking on a mobile phone; the degree of interest in mobile phone new features; and the length (in years) of mobile phone ownership. 2.3. Design This study uses six separate multiple regressions for analysis and therefore is correlative in design. Scores for the SEI and NEO-FFI were totalled as per the instructions in their respective manuals. Descriptive statistics for all of the variables in the mobile phone use survey were calculated. To determine whether reported mobile phone use could be predicted from personality variables, separate multiple regressions were conducted upon each dependent variable. The predictor variables were neuroticism, extraversion, agreeableness, conscientiousness measured by the NEO-FFI, and self-esteem as measured by the SEI. Of particular interest were the dependent variables weekly average amount of time (minutes) making and receiving calls, writing and receiving SMS, changing ring tone and/ or wall paper, number of ingoing and outgoing calls, and percentage of incoming calls perceived as unwanted. 2.4. Procedure Participants were recruited by personal appeal, poster recruitment and advertisement. Those participants wanting to take part in the study contacted the researchers via telephone or e-mail. Participants were asked for a postal address for the purposes of sending out the survey and two personality measures, with the understanding that once the materials were in transit that their details along with their name was erased. To further ensure their anonymity in the study participants were asked in the explanatory statement, attached to the survey not to write identifying details on any of the study materials.
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3. Results The data from the questionnaires was entered into SPSS (version 12.0). An alpha level of 0.05 was chosen to perform analyses. A small amount of random missing values was found throughout the data. One person only received calls, and so zero was the appropriate value for outgoing calls and any percents made. One person did not respond to the ‘‘unwanted calls’’, writing in the margin ‘‘what does this mean’’. This was left as missing. Three participants did not respond to the question on SMS use, and seventeen did not respond to the question on ring tone or wallpaper. Four participants failed to provide an answer to a specific item on the SEI. For these cases, the mean value for that specific item for the sample was substituted for the corresponding item mean. The procedure is conservative, as the individual becomes more like the mean response in the sample. A missing value was also found for one participant for one question on the NEO-FFI. This was dealt with according to the questionnaire manual (Costa & McCrae, 1992), and was assigned a neutral value. 3.1. Analysis of the independent variables Totals, means and standard deviations were calculated for Neuroticism, Extraversion, Agreeableness, Conscientiousness and SEI, in conjunction with the minimum, maximum, and skew for each of the independent variables. The descriptive statistics for both personality measures are analogous to the normative data outlined in the manuals (Coopersmith, 1989; Costa & McCrae, 1992). Table 1 illustrates the totals, means, standard deviations, minimum and maximum values, and skew for the independent variables. Table 1 illustrates that the mean for SEI is moderately high suggesting that the sample averaged a healthy level of self-esteem. Out of the five NEO-FFI scales the highest mean was for conscientiousness while the lowest mean was for Neuroticism. This indicates that participants were relatively conscientious and emotionally stable. Means for agreeableness and extraversion were comparable with published norms (Costa & McCrae, 1992). An inspection of the skew of the independent variables revealed that agreeableness was negatively skewed, hence this scale was inverted by subtracting it from its maximum value plus one before transformation. A square root transformation was used on the agreeableness variable. Due to the inversion of agreeableness this variable has now been renamed ‘‘disagreeableness’’ to help interpretation.
Table 1 Totals, means, standard deviations, minimum and maximum values, and skew for SEI, neuroticism, extraversion, openness, agreeableness and conscientiousness total scores Predictors
n
M
SD
Min.
Max.
Neuroticism Extraversion Agreeableness Conscientiousness SEI
112 112 112 112 112
20.73 30.26 31.82 34.5 75.32
8.04 6.57 6.14 6.54 16.5
2 14 8 15 32
38 43 46 48 100
(N = 112).
Skew .12 .14 1.0 .45 .58
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After the data was transformed the assumption of normality was met. A cut off of z ± 3.29, p < 0.001 was employed in the search for univariate outliers. Mahalanobis distance was used to screen for multivariate outliers. Cases with distances greater than 20.15 (v2, df = 5, p < 0.001) were expelled (Tabachnick & Fidell, 2000). After the application of transformations however, no univariate or multivariate outliers were identified, so no cases had to be excluded. To test for multi-collinearity, Pearson’s correlations were run on all predictors after transformation, which are presented in Table 2. Although several significant correlations were evident all correlations were well below the selection criteria of 0.99 (Tabachnick & Fidell, 2000). Hence this assumption was met. 3.2. Analysis of the dependent variables Totals, means and standard deviations were calculated for (a) weekly average time (minutes) making and receiving calls, (b) weekly amount of incoming calls, (c) the percentage of incoming calls that are perceived as unwanted, (d) weekly amount of outgoing calls, and (e) writing and receiving SMS along with minimum and maximum values, and skew. The results are presented in Table 3. Table 3 shows that the sample reported spending more time on average making and receiving calls than writing or receiving SMS. The mean is higher for incoming calls than for outgoing calls, thus the sample reported receiving more calls than making them. The mean for unwanted incoming calls suggests that on average only 13.5% of the sample perceived their incoming calls as unwanted. The least amount of time was spent changing ring tone and wallpaper. As all the dependent variables were positively skewed a log transform was applied after +1 was added to the scores, reducing the skew to achieve the assumption of normality. 3.2.1. Calls Separate multiple regression analyses were performed for each of the dependent variables with the independent variables, extraversion, neuroticism, agreeableness, conscienTable 2 Correlations between predictors and mobile phone use 2 1 Neuroticism 2 Extraversion 3 (dis)Agreeablenessa 4 Conscientiousness 5 Self-esteem 6 Calls (time per week)b 7 Incoming calls (time per week)b 8 Unwanted percentageb 9 Outgoing calls (time per week)b 10 SMS (time per week)b 11 Tone or wallpaper (time per week)b a b * **
3 **
.32
Scores inverted and square root transformed. Scores +1 are log 10 transformed. p < .05. p < .01.
4 *
.21 .17
5 **
6 **
.30 .64 .27** .39** .29** .30** .33**
7 .068 .224* .245* .068 .129
8 .072 .276** .265** .072 .027 .763**
9 .089 .187* .230* .173 .157 .314** .240*
10 .036 .131 .165 .061 .065 .710** .795** .088
11 **
.272 .206* .264** .239* .198* .602** .357** .401** .301**
.305** .057 .313** .107 .315** .268** .159 .270** .060 .404**
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Table 3 Totals, means and standard deviations along with minimum, maximum and skew for weekly average time (minutes) making and receiving calls, writing and receiving SMS and the percentage of incoming calls that are perceived as unwanted DV
n
M
SD
Min.
Max.
Skew
Calls (mins) Incoming calls Unwanted (%) Outgoing calls SMS (mins) Tone/wall (mins)
112 112 111 111 105 95
149.29 30.13 13.5 22.89 104.1 10.53
222.38 45.47 19.45 30.53 229.0 62.25
2.00 1.00 .00 .00 .00 .00
1080 300 99 150 1710 600
2.498 3.37 2.232 2.290 5.688 9.242
tiousness and self- esteem. The independent variables predicted 12.2% of the variance in average amount of time spent making and receiving calls [F(5, 106) = 4.076, p = .002]. Extraverted [t(106) = 3.50, p = .001] and disagreeable [t(106) = 2.51, p = .014] people were more likely to spend more time weekly making and receiving calls. The results of this multiple regression are presented in Table 4. 3.2.2. Incoming calls The independent variables predicted 15.6% of the variance in the number of calls received weekly [F(5, 106) = 5.090, p < .001]. Extraverted [t(106) = 3.71, p < .001] and disagreeable [t(106) = 3.08, p = .003] people were more likely to report receiving more calls (see Table 5). 3.2.3. Unwanted incoming call perception The independent variables were able to predict 12% of variance in the percentage of incoming calls perceived as unwanted [F(5, 106) = 4.015, p = .002]. Extraversion predicted
Table 4 Standardised regression coefficient (b), t-value of b and significance for predictors of average time spent making and receiving calls Predictors
t
b
Neuroticism Extraversion Disagreeableness Conscientiousness SEI
.01 .34 .24 .03 .18
p .05 3.50 2.51 .34 1.43
.96 .001 .014 .73 .155
Table 5 Standardised regression coefficient (b), t-value of b and significance for predictors of amount of incoming calls Predictors Neuroticism Extraversion Disagreeableness Conscientiousness SEI
t
b .13 .36 .29 .08 .14
p 1.11 3.7 3.08 .83 1.13
.269 .000 .003 .408 .261
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unwantedness [t(106) = 3.35, p = .001] and there was a trend for disagreeableness [t(106) = 1.965, p = .052] to predict unwantedness of incoming calls. Extraverted and possibly disagreeable people were more likely to report that incoming calls were unwanted (see Table 6). 3.2.4. Outgoing calls The independent variables did not significantly predict the number of calls made weekly [F(5, 106) = 1.582, p = .171]. No significant multiple regression coefficients were produced (see Table 7). 3.2.5. SMS The independent variables significantly predicted 23.6% of the variance in average amount of time spent writing and receiving SMS [F(5,102) = 7.67, p = .000]. Extraverted [t(103) = 4.41, p = .000], neurotic [t(103) = 2.15, p = .034], unconscientious [t(103) = 2.037, p = .044] people were more likely to spend more time weekly writing and receiving SMS. Disagreeableness was also a predictor [t(103) = 2.182, p = .031] (see Table 8). 3.2.6. Ring-tone/wallpaper As Bianchi and Phillips (2005) implied that people used their mobile phones for stimulatory purposes, we also considered the self reported time spent adjusting ring tones or phone wallpaper. The independent variables significantly predicted 16.8% of the variance in average amount of time spent changing ring-tone and/or wallpaper [F(5, 89) = 4.795, p < .001]. Extraverted [t(89) = 2.16, p = .05] and disagreeable [t(89) = 2.52, p = .013] people were more likely to spend significantly more time weekly changing the ring tone and wallpaper on their mobile phones (see Table 9).
Table 6 Standardised regression coefficient (b), t-value of b and significance for predictors of percentage of incoming calls perceived as unwanted Predictors Neuroticism Extraversion Disagreeableness Conscientiousness SEI
t
b .007 .329 .188 .150 .184
p .058 3.347 1.965 1.531 1.495
.954 .001 .052 .129 .138
Table 7 Standardised regression coefficient (b), t-value of b and significance for predictors of amount of outgoing calls Predictors Neuroticism Extraversion Disagreeableness Conscientiousness SEI
t
b .12 .19 .16 .05 .15
p .98 1.86 1.6 .52 1.18
.328 .065 .112 .603 .243
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Table 8 Standardised regression coefficient (b), t-value of b and significance for predictors of average time spent writing and receiving SMS Predictors
t
b
Neuroticism Extraversion Disagreeableness Conscientiousness SEI
.241 .409 .197 .188 .108
p 2.15 4.41 2.18 2.04 .93
.034 .000 .031 .044 .356
Table 9 Standardised regression coefficient (b), t-value of b and significance for predictors of average time spent changing ring tone and/or wallpaper Predictors Neuroticism Extraversion Disagreeableness Conscientiousness SEI
t
b .21 .22 .26 .01 .17
p 1.65 2.16 2.52 .13 1.31
.10 .034 .013 .89 .19
4. Discussion The mobile phone extends the reach and immediacy of interpersonal transactions (Plant, 2000). Hence it is not surprising that personality might predict mobile phone use. We predicted that personality might predict the types of interpersonal transactions that people were prepared to engage in, and the efficacy of these transactions might have implications for self-esteem. Indeed, the present study found that disagreeable extraverts reported spending more time on their mobile phones, although they might value their incoming communications less. On the other hand, it was the extraverted, neurotic, disagreeable, and unconscientious individuals that reported spending more time writing and receiving SMS. However, there was only weak or indirect support for the expected relationships between mobile phone use and self-esteem. Personality could predict mobile phone use. Overall levels of phone use could be predicted from extraversion and disagreeableness. In particular, personality could predict some elements of the interpersonal transactions that the communicator was prepared to engage in (Argyle, 1984). The present study observed efforts by the individual to control their self-presentation. As a communication channel the mobile phone affords the user control over the range of cues provided to others (i.e. textual, aural, and visual). For instance, disagreeable extraverts focussed upon the superficial elements of their mobile phone such as ring tone and wallpaper, presumably for self stimulatory purposes (Bianchi & Phillips, 2005) or for the purposes of attracting the attention of others (Welford, 1977). On the other hand, there were indications that SMS was used by people who in some way wanted to control or limit the amounts of information (e.g. aural, visual) transmitted about themselves. SMS users were more likely to be neurotic, extraverted, disagreeable, or unconscientious. Disagreeable individuals spent more time on their phone as a ‘‘display’’, while neurotic or unconscientious persons, with their reliance upon SMS were less
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likely to use the phone to transmit more information about themselves (Argyle, 1984; Luft, 1970; McKenna & Bargh, 2000). It was expected that the quality of interpersonal transactions associated with mobile phone use would have implications for self esteem. Nevertheless, in the present data there was little direct evidence for relationships between mobile phone use and self-esteem. Disagreeable extraverts used their mobiles more, but tended to report more unwanted incoming calls. And this implies that agreeable introverts valued their incoming calls more. Those with poorer self-esteem may have tended to report more unwanted phone calls, but any relationships were weak. Instead, we observed relationships between SMS use and personality. SMS was more likely to be used by neurotic individuals. Neurotic individual’s concern as to their presentation may cause them to limit the information they reveal about themselves. As neuroticism is more likely to be associated with negative emotions such as depression (Anastasi & Urbina, 1997), there are indications that self-esteem could be a predictor of mobile phone use. There was some suggestion that people with low self-esteem might potentially spend less time fiddling with ring tones or wallpaper, or prefer SMS, but other variables such as agreeableness were better predictors. Hence the present data appear to contrast with that of Bianchi and Phillips (2005) who found relationships between self-esteem and self reported mobile phone use. However, the relationships observed by Bianchi and Phillips (2005) actually involved problem use. Individuals with low self-esteem were more likely to report problems associated with their mobile phone use. But there was little direct evidence to suggest that mobile phone use was associated with differences in self-esteem in the present study. 4.1. Extraverts Extraverts are recognised for having an extensive social network (Costa & McCrae, 1992), therefore it is not surprising to find that extraverts received more incoming calls. As extraversion did not predict the number of outgoing calls, it cannot be assumed that extraverts receive more calls simply because they have more friends. Instead it suggests the possibility that people feel more comfortable calling extraverts because their optimistic and talkative character seems to reassure many individuals (Gotlib & Hammen, 1992). Alternatively, extraverts may not want incoming calls, because they are supervisory in nature. Extraverts are sensation seekers and risk takers (Eysenck, 1994; Trimpop, 1994). Incoming calls may be from individuals who wish to monitor the activities of extraverts (Geser, 2004). The mobile phone potentially makes a mobile phone owner continuously available, and this may be used to the advantage of the caller. For instance mobile phones allow women to monitor their husband’s or children’s activities. 4.2. Agreeableness Agreeableness is a trait that is most concerned with interpersonal relationships, that are based on the equal and honest exchange of information (DeRaad, 2000). However, disagreeableness predicted incoming phone calls, and this is surprising as one might expect people would prefer to phone agreeable people. Disagreeable people score low on trust, straightforwardness, altruism, compliance, modesty and tender-mindedness. The disagreeable individual as described by Costa and McCrae (1992) is principally selfish, uncooper-
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ative, and not afraid to look out for number one. Indeed, Costa and McCrae (1990) have revealed there to be an association between low agreeableness and Narcissistic and Antisocial Personality Disorders. The greater use of the mobile phone by disagreeable people could be attributed to tendencies for disagreeable people not to care what others think. Disagreeable people would possibly choose not to adhere to the mobile phone standards of etiquette, answering their phones during a face-to-face conversation, making and taking calls in inappropriate places such as during meetings, lectures or movies (Bianchi & Phillips, 2005). However, it was more surprising that disagreeable people reported more incoming phone calls. It is possible that people would rather phone a disagreeable person than be in the same room with them. There are certainly relationships between poorer interpersonal skills and internet use (Kraut et al., 1998; Scealy et al., 2002). Alternatively, people might phone a disagreeable person to argue or remind them of their interpersonal obligations. 4.3. Neuroticism Bianchi and Phillips (2005) suggested that people who score high on neuroticism do not find the mobile phone appealing. They may not be using their mobile phone the most, but this does not mean that they do not use the phone at all. This study supported the expectation that neuroticism could explain time spent SMSing. This is consistent with the findings of Reid and Reid (2004) that people who are more socially anxious and lonely prefer to use SMS as a means of communication due to feeling that they can better express their true selves. Amichai-Hamburger et al. (2002) have also presented similar findings for email preference. SMS does not require face-to-face communication, thus it may be favoured by the emotionally unstable. Like Internet e-mail, mobile phone text messaging is not visually based and therefore has been suggested to make people feel more comfortable when communicating because it is disinhibiting (Griffiths, 2001; Suler, 2004). As has been found with low self-esteem e-mailers, it is also possible that SMS eases a neurotic individual’s anxiety about misinterpretation by allowing the time to construct how they want to be portrayed and exactly what they want to say in a message (Joinson, 2004). SMS allows more control over the communication and what it reveals (see McKenna & Bargh, 2000). Although the use of mobile phones for business purposes led to expectations that conscientiousness might predict mobile phone use, this study found that unconscientious individuals were spending more time writing and receiving SMS. This supports the findings of Lavoie and Pychyl (2001) who revealed that unconscientious people are more likely to use the Internet at work to procrastinate. It seems that SMS may be a favoured mobile phone function of the less self disciplined individual that could be used to procrastinate or perhaps serve as a source of distraction. Since conscientiousness did not predict time spent making or receiving calls it is possible that casual or personal use is kept exclusively to SMS. SMS might be favoured over other channels such as email, due to the increasingly depersonalised (SPAM) and documented (Gottschalk, 2005) nature of email. 5. Implications A consideration of factors contributing to mobile phone acceptance may offer insights as to other forms of applications such as E-government or I-gaming (Griffiths, 2003). In
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contrast with the widespread acceptance of mobile phones, E-government does not enjoy the same levels of acceptance (Horst et al., 2007). In contrast to E-government services as delivered over a desktop link, the mobile phone has more features that attract and capture attention (Griffiths, 2003). The mobile phone is extrinsically rewarding, as it delivers immediate access to people or services. The mobile phone is also intrinsically rewarding, as it offers opportunities to customise, control and manipulate the interface (Griffiths, 2003). In particular, the immediacy and frequency of signalling has attention capturing properties (Griffiths, 2003; Wood, Griffiths, Chappell, & Davies, 2004) that promote regular monitoring. It remains to be seen whether factors like extraversion, disagreeableness or unconscientiousness can predict the success of programs such as I-gaming (Griffiths, 2003). But the present data implies that there is a section of the community that might abuse such services. 6. Future research This study chose to use self-report measures owing to convenience, instead of behavioural measures, which are known to provide more accurate measurements. Higgins, McClean, and Conrath (1985) determined that self reported use of telephone communications, obtained through self-recording diary entries, under recorded received calls. It was concluded that when there is an absence of objective data self-report measures provide usable information, although are inherently prone to bias. Even though users would receive itemised bills, it is possible that incoming calls were under-reported by the sample, thus influencing the potential accuracy of the results. Future research could consider exploring mobile phone behaviour using objective measures to gain a more accurate and realistic account of individual use. For example researchers could supply mobile phones to their participants, or use SMS to collect data. 7. Conclusion Personality traits can explain patterns of mobile phone use. Disagreeable extraverts reported spending the more time using the mobile phone, specifically receiving more calls and changing their phones’ appearance. But while extraverts received more calls, they valued them less. Whilst it appears that unconscientious, emotionally unstable, disagreeable extraverts are spending more time SMSing. Unexpectedly self esteem did not correlate well with amounts or types of mobile phone use, suggesting that disagreeableness is a more important predictor of amounts and types of mobile phone use. Personality can predict the amounts of phone use, and the preference for a specific style of communication channel. Acknowledgement The authors acknowledge the perspective and ideas of Dr. Peter Ostojic of Telstra Research Laboratories. References Amichai-Hamburger, Y., Wainapel, G., & Fox, S. (2002). On the Internet no one knows I’m an introvert: extroversion, neuroticism, and Internet interaction. CyberPsychology & Behavior, 5, 125–128.
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