The influence of parental and peer attachment on Internet usage motives and addiction
First Monday

The influence of parental and peer attachment on Internet usage motives and addiction by Patrick Chin-Hooi Soh, John P. Charlton, and Kok-Wai Chew

The impact of parental and peer attachment on four Internet usage motives and Internet addiction was compared using path modelling of survey data from 1,577 adolescent Malaysian school students. The model accounted for 31 percent of Internet addiction score variance. Lesser parental attachment was associated with greater Internet addiction risk. Psychological escape motives were more strongly related to Internet addiction than other motives, and had the largest mediating effect upon the parental attachment–addiction relationship. Peer attachment was unrelated to addiction risk, its main influence on Internet usage motives being encouragement of use for social interaction. It is concluded that dysfunctional parental attachment has a greater influence than peer attachment upon the likelihood of adolescents becoming addicted to Internet–related activities. It is also concluded that the need to relieve dysphoria resulting from poor adolescent–parent relationships may be a major reason for Internet addiction, and that parents’ fostering of strong bonds with their children should reduce addiction risk.


1. Introduction and contextual background
2. Theoretical framework
3. Methodology
4. Results
5. Discussion



1. Introduction and contextual background

With the increasing global penetration of the Internet, concerns have been expressed that some people may over–use the technology to such an extent that their behaviour might be considered pathological. For example, because of their over–engagement in Internet–related activities, children and adolescents have been shown to suffer from academic failure, difficulty in completing class assignments, lack of attentiveness in class, sleep deprivation, and depression. (Douglas, et al., 2008).

These concerns about excessive Internet use have been raised not only in affluent developed countries, but in developing nations such as Malaysia. Malaysia is a developing multiracial country in South East Asia with a population of 28 million people (Malaysia. Department of Statistics, 2009). In the early 1990s, Malaysia started formulating a national strategy for telecommunications and the Internet, and promoted Internet adoption aggressively. The result is an impressive achievement considering its gross national income per capital of US$$9,755 (Malaysia. Economic Planning Unit, 2012), with almost 17 million of its population online and an Internet penetration rate of 64 percent (International Telecommunication Union, 2009). Furthermore, 90 percent of its secondary school children in urban areas are online, with many using it for more than 20 hours a week (Soh, et al., 2012). This gives rise to valid concerns about excessive Internet use and its consequences in Malaysia.

Many studies have agreed that the Internet motives of users determine online usage and its consequences (Chou and Hisao, 2000; Choi, 2001; Huang, 2004). Nevertheless, a key question that is largely unanswered is what factors influence adolescents’ motives in using the Internet. For adolescents, the two most important socialization factors are their parents and peers (Armsden and Greenberg, 1987). However, existing research regarding parental mediation has focused only on television, and parental mediation patterns concerning adolescent Internet usage still remain relatively unknown (Lin and Yu, 2008).

Therefore, this paper aims to explore Internet use, motivations and addiction of youth in Malaysia. The researchers also investigate the roles of parents and peers in influencing youth online usage, motivations and addiction. While Internet addiction is a cross–cultural phenomenon (e.g., Young, et al., 2011), there appear to be no large–scale Malaysian studies of Internet addiction to date. In fact, in spite the popularity of the Internet, there is a scarcity of large–scale Internet usage studies in Malaysia and this paper attempts to alleviate this scarcity. Given the aforementioned situation, the literature covered below is necessarily international in scope, it being a major matter of interest in the present research as to whether international findings generalize to Malaysian adolescents.



2. Theoretical framework

2.1. Uses and gratifications theory

Uses and gratifications theory provides an audience–centred perspective on media usage that suggests that people’s needs and desires drive usage (Katz, et al., 1974). The theory assumes that (a) media behaviour is purposive, goal–directed and motivated; (b) people select media content to satisfy their needs or desires; (c) social and psychological dispositions mediate that behaviour; and, (d) “media compete with other forms of communication — or functional alternatives — such as interpersonal interaction for selection, attention and use” [1]. In uses and gratifications research, measurable constructs such as motives are used to represent abstract concepts such as needs and desires. Motives, in turn, guide media usage such as the selection of media and patterns of engagement. Specific motives have been linked to choosing media such as radio (Herzog, 1940), television (Schramm, et al., 1961), and the Internet (Papacharissi and Rubin, 2000).

The uses and gratifications framework has been deemed to be suitable for new media, particularly the Internet (Ruggiero, 2000; Newhagen and Rafaeli, 1996). Consequentially, a large number of studies on Internet usage had been framed on the users and gratifications model (e.g., Huang, 2004; Papacharissi and Rubin, 2000; Choi, 2001). These studies have generally categorized the motivations to use the Internet to be entertainment, escape, social interaction, surveillance/information and utility/monetary. However, as the Internet’s multimedia capabilities advance and become a major channel for the dissemination of sexual content, eroticism is increasingly being identified as a new Internet usage motive (Meerkerk, et al., 2006; Tsitsika, et al., 2008).

2.2. Internet addiction and its definition

The term ‘Internet addiction’ has often been used to refer to the pathological use of the Internet. The psychological literature generally uses the term ‘addiction’ to refer to a person’s physiological dependence on a stimulus (Davis, 2001). Although using the term in connection with non–substance–related behaviours has been questioned (e.g., Jaffe, 1990), there are similarities in the way in which addictive drugs and addictive behaviours act on the brain’s reward circuitry (Holden, 2001; Phillips, 2006). Nonetheless, the current edition of the American Psychiatric Association’s Diagnostic and statistical manual for mental disorders (DSM–IV; APA, 2000) avoids the term ‘addiction’, preferring the term ‘dependence’ in connection with drug use, and the term ‘pathological’ for gambling disorders. The latter is particularly relevant since Internet over–usage (however defined) is not currently listed in the DSM–IV, and the closest analogy that can be drawn between the Internet–related behaviours under discussion and any behaviour which is listed in the DSM–IV is with pathological gambling. Thus, Davis (2001) used the term ‘Pathological Internet use’. In the DSM–IV, pathological gambling is classified as a type of impulse control disorder, which are disorders where people are unable to desist from behaviours resulting in self–harm or harm to others, but which do not involve ingestion of substances. Hence it seems reasonable to say that many of the types of behaviour associated with Internet over–engagement should be described in such terms. However, the term ‘Internet addiction’ continues to be commonly used by many of the people at the forefront of research in this area (e.g., Young, et al., 2011) and, to maintain consistency, this term will be used in this paper, with Internet addiction being defined as the need to engage in Internet–related activities in the face of negative social, spiritual, mental or physical consequences, with resultant withdrawal symptoms after attempts at abstention (Young, et al., 2011).

The above analogy with pathological gambling has led to the adaptation of DSM criteria for this pathology for use in classifying people as Internet addicted. Thus, commonly used criteria are cognitive and/or behavioural salience (a mental or behavioural pre–occupation with an activity), conflict (either intra–psychic or with significant others), euphoria or mood modification (using the activity to achieve either a psychological high or psychological numbing), tolerance (the need to engage in an activity to an increasingly greater extent to achieve the same psychological high), withdrawal symptoms (the occurrence of unpleasant emotional or physical effects upon cessation of an activity), and relapse and reinstatement (engaging in an activity to the same extent as previously after an attempt to desist). These criteria have been used by authors such as Griffiths (1998) and form the basis of commonly used instruments such as Young’s (1998) Internet Addiction Test. However, factor analytic studies involving both computing activities in general (Charlton, 2002) and a specific online game (Charlton and Danforth, 2007) have suggested that the use of all of these criteria may be inappropriate since some of them (cognitive salience, tolerance and euphoria) appear to be more indicative of non-pathological high engagement than addiction. Such findings have recently been upheld in a further non–game–specific study of online game players (Seok and DaCosta, 2012). The aforementioned studies of Charlton showed that confusing criteria that may be simply indicative of high engagement with criteria for addiction can lead to overestimates of the frequency of Internet–related addiction, and that this is particularly likely to be the case when a polythetic classification scheme is used in which only a subset of a larger number of criteria are used for classification. The methodology employed by the present study took these findings into account in that it used an Internet addiction scale resulting from Charlton’s programme of work.

In investigating possible influences upon adolescents’ proneness to Internet addiction, the present study blended psychological theory with the uses and gratifications strand of communications research in which motivations to use the Internet for entertainment, erotic, escape and social interaction purposes are viewed as gratifications driving Internet use (LaRose, 2011). Here, motivation is defined as the “processes that account for an individual’s intensity, direction, and persistence of effort toward attaining a goal” [2]. Thus, the broad aims of this paper are to consider the extent to which parental and peer attachment drive pursuit of four different goals (use of the Internet for entertainment, social interaction, erotic and psychological escape purposes), the extent to which pursuit of these goals is related to an index of Internet addiction, and the extent to which these goals mediate relationships between parental and peer attachment and Internet addiction.

2.3. Motives for Internet use and Internet addiction

The preceding discussion has treated Internet addiction as a unitary phenomenon. However, studies have linked addiction with various specific Internet activities. Many studies have pointed to the prominence of entertainment and social interaction among activities that have been associated with Internet addiction. For example, a Greek study reported that use of the Internet for game playing and social interaction are key predictors of excessive Internet usage (Tsitsika, et al., 2008). Also, a longitudinal study on students from the Netherlands found online chatting to be a predictor of compulsive Internet use six months later (Eijnden, et al., 2008) and reports are starting to emerge of social networking addiction (e.g., Karaiskos, et al., 2010). Unsurprisingly then, a meta–synthesis of qualitative Internet addiction research for the decade 1996–2006 concluded that socialization and entertainment activities are predictors of Internet addiction (Douglas, et al., 2008).

Possibly the most salient mechanism that has been forwarded to account for this addiction to Internet–related activities, and behaviours in general, is the psychological concept of reward and reinforcement (Greenfield, 2011). Many Internet entertainment and social interaction applications provide psychological rewards according to a variable–ratio reinforcement schedule (Greenfield, 2011; Wallace, 1999). These are particularly good at motivating repetitive behaviours because, irrespective of the time since the last reward, a reward may occur as a result of the next behaviour, thus maintaining the behaviour. So, with respect to online social interaction, the behaviour is a certain type of input to the computer, such as the placement of a posting, and the reward is other users’ reactions to the input, in the form of their posting of responses (which may result in the person making the original posting receiving an accompanying neurochemically induced high in the form of increased dopamine in the brain’s reward circuit). The uncertainty of the timing and nature of responses to posts can lead people to spend large amounts of time online monitoring responses (and posting rejoinders). The same can also be true with respect to compulsive e–mail checking (Chou and Hsiao, 2000; Kandell, 1998).

The unpredictability of events in entertainment activities such as online games has similar addictive properties to those above. For example, massively multiplayer online role–playing games (MMORPGs) provide rewards (e.g., overcoming physical obstacles, solving puzzles, slaying of opponents, obtaining prestigious virtual objects) on an unpredictable basis. While such addictive properties can be found in off–line computer games (Griffiths and Davies, 2005), MMORPGs have addictive properties that are unique to the online environment. For example, as Blinka and Smahel (2011) pointed out, play takes place in a (virtual) geographic environment that is to all intents and purposes limitless and continuously changing (thus increasing the capacity for surprises), and action proceeds in a player’s absence, which can leave them at a disadvantage if they are off–line too long, resulting in an imperative to play for long durations and with high frequency (Blinka and Smahel, 2011). Finally, MMORPGs involve interaction with other players, gamers communicating with each other, and groups often being formed within the game space to collaborate in achieving common goals. This brings into operation a second major mechanism accounting for many Internet–related addictions; social reinforcement. Here, people with low self–esteem or who are socially isolated may be particularly prone to developing addictions because they are motivated to engage in online social interaction and entertainment activities in order to attain a greater sense of self–worth from positive online feedback (Morahan–Martin and Schumacher, 2000; Wallace, 1999).

Although the above emphasised addiction issues with respect to gaming activities, which is the dominant area of research into Internet entertainment, variable–ratio reinforcement and other properties are likely to interact to produce addiction in other activities too. For example, it is not difficult to appreciate the addictive potential of the huge and perpetually expanding amount of material of varying quality which is made instantaneously available at the click of a mouse on online video Web sites. From the above literature review, two hypotheses were tested:

H1: Social interaction motivations are positively related to Internet addiction.

H2: Entertainment motivations are positively related to Internet addiction.

Erotic usage has also been reported to be a driver of Internet use and addiction (Douglas, et al., 2008; Tsitsika, et al., 2008) and longitudinal evidence suggests that such usage is pre–eminent among activities associated with Internet–mediated addictions (Meerkerk, et al., 2006). Again, variable–ratio reinforcement schedules can partially explain the motivation to use the Internet for erotic purposes, and the addictive potential of such usage. The huge variety of material across and within Web sites means that there is always the possibility of encountering material that is particularly sexually stimulating or novel (sexual stimulation constituting a particularly powerful psychological reward), with the timing of when such stimuli are encountered being unpredictable (Greenfield, 2011). Additionally, the ability to obtain and view pornography anonymously in one’s own home has removed embarrassment and inhibition as major barriers to its acquisition (Joinson, 2003). The easy availability of online erotic materials also contrasts sharply with the strict censorship of traditional media in many conservative Asian countries like Malaysia (Cooper, 1998). The following hypothesis was therefore tested:

H3: Erotic motivations are positively related to Internet addiction.

2.4. Parental attachment, motives for Internet use and Internet addiction

Attachment theory notes that children’s attachments to their caregivers in their early formative years shape their underlying patterns of thought, feelings and motivations in adulthood (Bowlby, 1982). Parents provide a secure foundation for adolescent development and have an important influence upon adolescent behaviours and attitudes (Armsden and Greenberg, 1987). Secure relationships with parents are associated with psychological well–being, higher self–esteem, better scholastic achievement, lower anxiety and depression, and lesser inclinations towards delinquency, alcohol use, and drug abuse (Steinberg, 2001). Substance abuse has been said to be a coping strategy used to deal with emotional distress by insecurely attached people (Schindler, et al., 2007). It is possible that the same is true of addictive Internet usage; some adolescents may seek to escape the emotional distress that results from insecure attachment by using the Internet for the purposes of psychological numbing (i.e., escape from reality) in the same way that chemical substances are often used. Indeed, it has been claimed that escape motives are usually the central driver of Internet addictions (Young, 1998). This leads to the hypothesis:

H4: Escape motivations are positively related to Internet addiction.

Studies of parental influence suggest that parents act to reduce children’s online entertainment and social activities (Eastin, 2005) and that close parental ties are negatively predictive of children’s leisure and social online activities (Lei and Wu, 2007). Therefore, assuming that lower parental attachment results in lesser parental influence on children’s behaviour, and that parents generally aim to keep children’s Internet use within reasonable bounds, the following hypotheses were tested:

H5a: Parental attachment is negatively related to Internet entertainment motivations.

H5b: Parental attachment is negatively related to Internet social interaction motivations.

Also, children have intimacy needs that parents should fulfil (Buhrmester and Furman, 1987). When such intimacy needs are not met, children may seek involvement with sexual activities (Cortoni and Marshall, 2001). Hence, close parental and family ties have been associated with reduced viewing of online pornography in Hong Kong and Israel (Lam and Chan, 2007; Mesch, 2005). The present research sought to test the generalizability of these findings to the Malaysian situation. Therefore, the hypothesis below was proposed based upon the rationale that parents would discourage their children’s participation in sexual activities (particularly in a conservative country such as Malaysia), and that more strongly attached children would adopt their parents’ values and accede to their wishes:

H5c: Parental attachment is negatively related to erotic Internet usage motivations.

As parents play a large part in the lives of adolescents, and H4 was predicated upon the assumption that Internet addiction might result from use of the Internet to escape from difficult everyday realities (Young, 1998), this study also tested the idea that adolescents with problematic parental relationships (as signalled by low parental attachment) might have higher escape motivations. Thus the following hypothesis was proposed:

H5d: Parental attachment is negatively related to escape motivations.

As previously mentioned, close parent–child ties reduce Internet addiction tendencies (Ko, et al., 2007). To explain this, the model under test (see Figure 1) suggested that each of the four usage motivations mediates the negative parental attachment–Internet addiction relationship. Thus, the model represents lower parental attachment as resulting in greater motivation to use the Internet for erotic, social interaction, entertainment and escape purposes (for each of the reasons previously referred to in this section) with each of these motivations being related to addiction for the reasons alluded to in the subsection that developed hypotheses linking each of the Internet use motives with addiction. The indirect effects linking parental attachment with Internet addiction via the four usage motivations therefore implied the following hypothesis:

H5e: Parental attachment is negatively related to Internet addiction.


The theoretical path model
Figure 1: The theoretical path model.


2.5. Peer attachment

Friendship is important for adolescent psychological well–being (Armsden and Greenberg, 1987) and friends are powerful social influences upon adolescents’ activities such as viewing anti–social television programs (Nathanson, 2001), playing video games (Dalessandro and Chory–Assad, 2006), and using the Internet for communication (Peter, et al., 2005). Explaining such influences, Nathanson (2001) invoked the Sullivan–Piaget thesis developed by Youniss (1980) integrating work of the two eponymous researchers. This thesis suggests that in contrast to parent–child relationships where parents try to ensure that children conform to existing social rules (this being enforced by an asymmetry in power), relationships between members of a peer group are more equal, with members of the group reinforcing each other’s ideas to create “a unique social world” [3]. Further, Nathanson cites Roe (1995) as suggesting that “adolescents who share similar social or academic problems may be drawn together by media (and especially antisocial content) to create accepting social groups that validate their identities” [4]. This is likely to lead to the formation of peer groups based around specific types of activity (for example, in the present instance, computer game playing or the use of social networking media). These observations led to the following hypotheses:

H6a: Peer attachment is positively related to Internet entertainment motivations.

H6b: Peer attachment is positively related to Internet social interaction motivations.

In accordance with the Sullivan–Piaget thesis, peers also play a more dominant role than parents in influencing adolescent problematic behaviours, such as delinquency and marijuana use (Aseltine, 1995) and sexual behaviour (Debarun, 2003). However, findings on peer groups’ influence on erotic Internet use are mixed. For example, Lam and Chan (2007) found peer influence to be strongly positively correlated with online pornography use. On the other hand, both loneliness (Yoder, et al., 2005) and a lack of attachment to friends and parents (Davies, 2007) predict greater online erotic involvement. These two findings possibly indicate that close friendships satisfy intimacy needs.

Because of these divergent findings and there being reasonable rationale to suggest both a positive relationship (peer influence) and a negative relationship (unfulfilled need for intimacy) between extent of peer attachment and motivation to use the Internet for erotic purposes (with the resultant possibility that motivational factors might cancel each other out to produce a null relationship), a directional hypothesis did not seem appropriate here. Therefore the issue surrounding any relationship between peer attachment and erotic Internet usage motivations was left as an open research question. Thus, the study asked whether there is a relationship between peer attachment and erotic Internet usage, and, if so, what is the nature of this relationship?

On the other hand, since adolescents lacking in close friends may turn to the Internet for psychological escape as a means of coping with social anxiety (Peter, et al., 2005), the following hypothesis was tested:

H6c: Peer attachment is negatively related to Internet escape motivations.

Consistent with the above, a lack of close friends predicts Internet addiction (Liu and Kuo, 2007). However, peer influence is also positively correlated with Internet addiction (Deng, et al., 2007). Thus, the nature of any relationship between peer attachment and Internet addiction is likely to be complex. For example, remembering the Sullivan–Piaget thesis, if a child is strongly attached to a peer group that engages avidly in a certain activity (e.g., online communication or usage for entertainment purposes such as the playing of a certain online game), this is likely to make the child engage in it too (with the consequent possibility of addiction). But, as mentioned above, children lacking close peer attachments might also become addicted to certain activities (e.g., online communication, multiplayer online fantasy games) as a form of escape and to relieve feelings of emotional isolation. So, the model tested assumed that two presently examined motives (social interaction and entertainment) result in an increasing addiction tendency as peer attachment becomes stronger, but that escape motives result in a decreasing addiction tendency as peer attachment becomes stronger. Therefore, the direction of the overall relationship between peer attachment and Internet addiction was a matter for empirical verification.

The previously developed hypotheses linking parental and peer attachment with the four Internet usage motives and the latter with addiction imply that the motives might mediate attachment–addiction relationships. For example, given the arguments that (1) parents seek to moderate their children’s use of the Internet for entertainment and social interaction purposes and to prevent them accessing erotic material, and that securely attached adolescents do not need to use the Internet for psychological escape, and that (2) entertainment, social interaction and erotic use can lead to addiction through various mechanisms such as variable–ratio schedules and social reinforcement, and that the use of the Internet for escape as a means of psychological numbing in the face of dysphoria can be highly addictive, the motives should mediate the parental attachment–addiction relationship. Likewise, in the presence of the same mechanisms linking the motives with addiction, since greater peer attachment is likely to lead to the formation of groups based around certain entertainment and social interaction applications, and that it is also likely to result in a lesser need for psychological escape to alleviate social anxiety, the motives should mediate the peer attachment–addiction relationship. It was of particular interest to determine which motive has the greatest mediating effect for both types of attachment.

Of the 12 hypotheses forwarded, 11 are summarized by the direct links in the theoretical path model depicted in Figure 1 (the other hypothesis involved a negative, but indirect, relationship between parental attachment and addiction). The dashed link between peer attachment and erotic motives represents the open research question regarding the direction of any relationship between these two variables.



3. Methodology

3.1. Participants

Four urban schools were randomly selected from each of four randomly selected Peninsular Malaysian states (Penang, Kuala Lumpur, Melaka and Kelantan). Within the constraints of ensuring that a broad representation of academically strong and weak students was sampled within each school, classes of students totalling about 100 adolescents per school were then conveniently selected by each school’s principal. In Malaysia, academically strong students tend to be in the Science Stream, while the Commerce and Art Streams tend to have academically weaker students. Hence, the principals were asked to select a combination of Science and non–Science stream classes. Excluding 32 forms with missing data, the final sample was comprised of 1,577 adolescents, of which 839 were girls (53.2 percent of the sample) and 738 boys (46.8 percent), ages ranging from 15 to 17 years (M=16.07, SD=0.83). There were 62.3 percent (982) Muslims, 24.9 percent (392) Buddhists, 6.4 percent (101) Christians, 5.8 percent (92) Hindus, and 0.6 percent (10) were from other religions. The proportions from each religion were roughly representative of the Malaysian population. Seventy–eight percent or 1,230 participants had a computer at home and 345 (22 percent) did not (this data was missing for two participants), and respondents were online for a mean of 9.96 hours per week (SD=14.12 hours).

3.2. Materials

Prior to path modelling, analyses were performed to ensure the best possible reliability of all instruments used. Ranges of possible scores for each scale are given in Table 2 along with Cronbach’s alpha coefficients.

Subsequent to reliability analysis, a nine–item adapted version of Vignoli and Mallet’s (2004) 14–item scale was used to measure parental attachment, this being a shortened version of Armsden and Greenberg’s 28–item parental attachment scale which measures three correlated dimensions (communication, trust and alienation). In accordance with most of the literature, a single overall scale total was used (Vignoli and Mallet, 2004). Items assessed adolescents’ perceptions that the attachment figures (1) understood and respected their needs and desires, (2) were sensitive to their emotional states and worries, and (3) were not emotionally detached from them. Responses were on a five–point Likert scale ranging from “never true” to “always true”.

Similarly, the peer attachment measure was adapted from Armsden and Greenberg’s (1987) 28–item peer attachment scale, which, using the same type of response scaling, measures the same three dimensions as the parental attachment scale. Using pilot study data, a shortened list of 17 items was selected using a factor analytic process similar to that of Vignoli and Mallet (2004) in order to reduce the parental attachment scale, with 12 items remaining after reliability analysis. Again, a single scale total was used.

The Internet motivations questionnaire was adapted from that of Huang (2004), who derived his instrument from prior uses and gratifications research (Kaye, 1998; Rubin and Perse, 1987). Huang measured five motives; entertainment, escape/pastime, social interaction, surveillance/information, and monetary. But, since Internet addiction is likely to be a phenomenon mostly associated with non–utilitarian forms of Internet usage, only data for entertainment, social interaction and escape/pastime (henceforth abbreviated to escape) were analyzed in the interests of building a parsimonious model. After two pilot studies conducted to validate and fine–tune them and reliability analysis, the numbers of items for the subscales were as follows: entertainment, four items; social interaction, five items; escape, five items. Additionally, a new five–item erotic motivation subscale was included. Responses were on a five–point “strongly disagree” to “strongly agree” Likert scale. All questions (both in the motivations questionnaire and the addiction questionnaire described below) referred to Internet use in its totality, the means of access (e.g., via PC, laptop or mobile phone) being unspecified in item wordings.

Finally, the Internet addiction scale was adapted from Charlton and Danforth (2010). As discussed earlier, although many Internet addiction scales have been proposed, because factor analytic studies have shown that commonly used scales, such as Young’s (1998) Internet Addiction Test, may be criticised on the grounds that they fail to distinguish between criteria indicative of non–pathological high engagement and addiction (Charlton, 2002; Charlton and Danforth, 2007), the present study used an Internet addiction scale derived from Charlton’s programme of research. The aforementioned studies and the previously mentioned study by Seok and DaCosta (2012) have shown that the factor structure on which the present instrument was based is robust across changes in the type of computer–related activity studied and across samples drawn from different countries. A further study using psychometric scales derived from the above studies of Charlton has also attested to the external validity of the distinction between addiction and high engagement and to the validity of the 11 item scale on which the present measure of addiction was based (Charlton and Danforth, 2010). Furthermore, a study of attentional bias in excessive game playing has provided support for the scale’s utility (Metcalf and Pammer, 2011). Finally, it should be noted that the present methodology took heed of debates surrounding revisions to the DSM which suggest that it is more useful to place people along a continuum rather than using a classificatory approach which, among other things, may be thought to imply a qualitative separation between abnormal and normal functioning which in reality may not exist (see e.g., Widiger and Samuel, 2005). For the present study, adaptations of the initial 11 items in Charlton and Danforth’s (2010) scale consisted of replacing the name of a computer game with reference to the Internet. Again, responses were on a five–point “strongly disagree” to “strongly agree” scale. Reliability analysis of the present data set led to deletion of one item, resulting in a 10–item scale (see Table 2 for Cronbach’s alpha). Table 1 shows the list of survey questions and their constructs.


Table 1: Survey questionnaire items and their constructs.
Questionnaire itemConstruct
It is funEntertainment motive
It offers a pleasant way to fill timeEntertainment motive
It helps to relieve stressEntertainment motive
It offers entertainmentEntertainment motive
It reduces boredomEscape/pass–time motive
It offers me an enjoyable habit that I like doingEscape/pass–time motive
It gives me something else to think about other than my own problemsEscape/pass–time motive
It helps me to forget school and other thingsEscape/pass–time motive
It gives me something to occupy my timeEscape/pass–time motive
It makes me feel less lonelyEscape/pass–time motive
It helps me to keep in touch with family and friendsSocial–interaction motive
It helps me to meet new peopleSocial–interaction motive
It helps me to chat with friendsSocial–interaction motive
It helps me to talk to people of the same hobbiesSocial–interaction motive
It helps me make new friendsSocial–interaction motive
It helps me to keep updated on what is happening in my areaSurveillance/information motive
It gives detailed information about current issues and eventsSurveillance/information motive
It helps me to keep in touch with news in MalaysiaSurveillance/information motive
It helps me to learn thingsSurveillance/information motive
It carries detailed information about current issues and eventsSurveillance/information motive
It provides a convenient way to shopProduct information motive
It helps me to find things to buyProduct information motive
It gives me information about productsProduct information motive
It helps me to save timeProduct information motive
It helps me to compare pricesProduct information motive
It is exciting to flirt onlineEroticism motive
It gives me excitement to read sexual storiesEroticism motive
It helps me to understand sexEroticism motive
It lets me see sex picturesEroticism motive
I sometimes don’t do important things because of an interest on the InternetAddiction
My social life has never suffered because of my Internet activitiesAddiction
Arguments have sometimes arisen at home because of the time I spend on the InternetAddiction
I think that I am addicted to the InternetAddiction
I am sometimes late for school because of my activities on the InternetAddiction
I sometimes used the Internet to escape from spending time with family and friendsAddiction
Internet activities have sometimes interfered with my studiesAddiction
When I am not on the Internet, I often feel disturbedAddiction
I often fail to get enough sleep because of my Internet activitiesAddiction
I have made unsuccessful attempts to reduce the time I spend on the InternetAddiction
I sometimes skip meals because of my Internet activitiesAddiction
My parents respect my feelingsParent attachment
My parents sense when I am upset about somethingParent attachment
I get upset a lot more than my parents know aboutParent attachment
When we discuss things, my parents consider my point of viewParent attachment
My parents trust my judgmentParent attachment
My parents help me to understand myself betterParent attachment
I tell my parents about my problems and troublesParent attachment
My parents encourage me to talk about my difficultiesParent attachment
I don’t know whom I can depend on these daysParent attachment
I trust my parentsParent attachment
My parents don’t understand what I am going through these daysParent attachment
I can count on my parents when I need to talk about something bothering meParent attachment
I feel that my parents do not understand meParent attachment
If my parents know something is bothering me, they ask me about itParent attachment
My friends sense when I am upset about somethingPeer attachment
My friends understand mePeer attachment
My friends encourage me to talk about my difficultiesPeer attachment
I feel the need to be in touch with my friends more oftenPeer attachment
My friends don’t understand what I am going through these daysPeer attachment
I feel alone or apart when I am with my friendsPeer attachment
My friends listen to what I have to sayPeer attachment
My friends are fairly easy to talk toPeer attachment
When I am angry about something, my friends try to be understandingPeer attachment
My friends are concerned with my well–beingPeer attachment
I feel angry with my friendsPeer attachment
I can count on my friends when I need to talk about something bothering mePeer attachment
I trust my friendsPeer attachment
My friends respect my feelingsPeer attachment
I get upset a lot more than my friends know aboutPeer attachment
I tell my friends about my problems and troublesPeer attachment
If my friends know something is bothering me, they ask me about itPeer attachment


3.3. Procedure

Data collection was carried out during school time using a single booklet containing all the instruments. The researchers visited the schools, explained the purpose of the survey to the students and conducted the survey face–to–face in a classroom setting. Confidentiality was assured and participation was voluntary and anonymous.



4. Results

In reporting path analyses, we provide the four goodness–of–fit statistics recommended by Kline (2005). For cross–validation, the data file was randomly split roughly in half to form calibration (N=791) and validation (N=786) subsamples and procedures recommended by Byrne (2001) were followed. However in the interests of brevity, the cross–validation procedure is not reported fully here; suffice it to say that various runs on the two subsamples, suggested that: (1) disturbances between the four Internet usage motives should be correlated (probably because the same measurement methodology was used for all variables; Kline, 2005); (2) a direct path should be inserted between parental attachment and Internet addiction; and, (3) the entertainment–addiction, peer attachment–erotic motives, and parental attachment–social interaction paths should be deleted. As a final step in the cross–validation procedure, analysis directly assessing whether the post hoc model for the calibration sample fitted the validation sample (Byrne, 2001) found that the models were not significantly different, χ2diff (16)=12.41, p=.72. Thus, the post hoc modifications performed during the modelling process using the calibration data were robust.

To provide as accurate as possible estimates, the calibration and validation samples were re-combined (N=1,577) to perform the analysis reported below. Here, only direct effects that were robust across the calibration and validation analyses were included. Table 2 below gives descriptive statistics and reliability coefficients for the instruments used. Although alpha was slightly lower than desirable for the escape motives subscale, it was retained because of the construct’s importance.


Table 2: Descriptive statistics and Cronbach’s alphas for the seven variables in the path model.
Note: N=1,577
 MSDα PotentialActualSkew
Parental attachment30.487.50.879–459–45-.22
Peer attachment40.419.40.9112–6012–60-.08
Social interaction18.923.58.855–257–25-.62


Table 3 below gives correlations for the whole sample. Note that the large sample size resulted in the significance of some very small correlation coefficients. There may be suspicion that some relationships in Table 3 may not generalize across the 78 percent and 22 percent of participants with and without a home computer respectively. Such suspicion may be particularly strong with respect to relationships involving erotic motivations since use of computers for erotic purposes may be thought unlikely to occur in public places such as cybercafés. However, tests of differences between the correlations that erotic motivations exhibited with the two attachment variables and the Internet addiction variable across groups of participants with and without computers at home showed no significant differences in the size of correlations for the two groups. Note also that, at r=.69, the correlation between the escape and entertainment motives was quite high. However, neither this correlation nor any of the squared multiple correlations produced by predicting each variable from all of the others (which were in the range of .09 to .57) was high enough to pose statistical problems involving multicollinearity (r=.85 and R2=.90 — Kline, 2005).


Table 3: Correlations (Pearson’s r) between the seven variables in the path model.
Note: N=1,577; *p≤.05l; ** p<.01 one–tailed; atwo–tailed; df=1575.
 Parental attachmentPeer attachmentEroticSocial interactionEntertainmentEscape
Parental attachment     
Peer attachment.20**    
Social interaction-.02**.25**.24**  


For the whole sample run, CFI (.996), Standardized RMR (.020) and RMSEA (.040, 90% CI=.019–.064) were all acceptable. While chi–square was significant, indicating a lack of fit, χ2(4)=14.10, p<.01, this statistic is often significant because of large sample sizes (Kline, 2005), therefore the model was accepted. Figure 2 presents the final model together with its standardized (maximum likelihood) regression weights, and Table 4 presents unstandardized regression weights and their associated statistics. For clarity, correlations between the disturbances for the four motives are not shown on Figure 2. These were; erotic–social interaction=.26, social interaction–entertainment=.42, erotic–entertainment=.29, escape–social interaction=.41, escape–entertainment=.68, escape–erotic=.40.


The modified path model for the whole sample
Figure 2: The modified path model for the whole sample including standardized path coefficients and squared multiple correlations for endogenous variables (N=1,577). All corresponding unstandardized path coefficients are significant (p≤.01).



Table 4: Unstandardized (maximum likelihood) regression weights and their associated statistics for the direct effects in the path model.
Note: N=1,577; ap<.01;
PathEstimateSECritical ratio
Parental attachment > Erotic-.09.02-5.35a
Parental attachment > Escape-.07.01-7.07a
Parental attachment > Entertainment-.02.01-2.54a
Parental attachment > Internet addiction-.12.02-5.31a
Peer attachment > Social interaction.10.0111.17a
Peer attachment > Escape.06.017.42a
Erotic > Internet addiction.38.0410.37a
Social interaction > Internet addiction.35.056.66a
Escape > Internet addiction.69.0611.97a


Figure 2 shows that three of the four hypotheses directly linking usage motives with addiction were supported, greater social interaction (H1), erotic (H3) and psychological escape (H4) motivations all being significantly linked with greater addiction scores, but greater entertainment motivation not having a direct link with addiction (H2). Pairwise parameter comparisons for these three direct effects showed that the effect of escape on addiction was significantly greater than that for both the erotic (critical ratio=4.08, p<.01) and social interaction (critical ratio=3.77, p<.01) motives. However, the effects on addiction of the social interaction and erotic motives did not differ significantly. Together with the non–hypothesized direct parental attachment–addiction path, the three motives with a direct effect upon addiction explained 31 percent of addiction score variance (representing a medium effect size in terms of R2 — Cohen, 1988).

As hypothesized, there were direct effects whereby greater parental attachment was associated with lower entertainment (H5a), eroticism (H5c) and escape (H5d) motives, albeit that the first of these coefficients was very small. However, the hypothesized direct negative effect of parental attachment upon social interaction (H5b) went unsupported given its lack of robustness during cross–validation. Also as hypothesized, stronger peer attachment was directly related to greater entertainment (H6a) and social interaction (H6b) motivations. Given that it was not possible to forward a directional hypothesis with respect to the nature of any relationship between peer attachment and erotic motives because the literature pointed to the possibility of a relationship in either direction, the absence of a direct effect of peer attachment on erotic motives was unsurprising. However, contrary to the hypothesis of a negative peer attachment-escape motivation link (H6c), there was a positive link whereby closer peer attachment was associated with greater escape motivations.

Pairwise parameter comparisons for the direct effects of the attachment variables upon motives within each of the two attachment variables showed that the effects of parental attachment on erotic and escape motives were not significantly different, but that this attachment variable had a greater effect on erotic motives than entertainment motives (critical ratio=4.19, p<.01). The effect of parental attachment on escape motives was also significantly greater than its effect upon entertainment motives (critical ratio=6.72, p<.01).

Peer attachment had a significantly greater effect upon social interaction motives than upon both the entertainment (critical ratio=5.10, p<.01) and escape (critical ratio=3.78, p<.01) motives, but there was no significant difference between the size of the escape and entertainment motive parameters.

The lack of hypothesized direct effects between the two attachment variables and Internet addiction in the theoretical model implied that motives should mediate attachment–addiction relationships. Where such tests were relevant given the structure of the modified model, Sobel tests for the significance of indirect effects were performed using the unstandardized estimates and standard errors in Table 4. As might be expected given hypotheses involving a mixture of negative and positive mediating influences, the peer attachment–Internet addiction correlation was negligible (r=.01, p=.81), but there was a significant positive mediating effect of the social interaction motive (Sobel test z=5.73, p<.01). On the other hand, the absence of the hypothesized peer attachment–erotic motives and entertainment motives–addiction paths meant that these two motives had no mediating effects between peer attachment and addiction as implied by the theoretical model. Also contrary to the theoretical model, rather than having a negative counter–weighting effect, the mediating effect of escape motives was also positive (here a Sobel test again showed a significant mediating effect, z=5.32, p<.01). So, rather than the escape and social interaction motives balancing each other out to produce the overall null peer attachment–addiction relationship, this nullification can be explained by various negative paths existing by virtue of peer attachment’s correlation with parental attachment in the model.

With respect to motives’ mediation of the negative parental attachment–addiction relationship (H5e), the need to include a direct path between parental attachment and Internet addiction indicated that, while significant, the mediating effects of the escape (Sobel test z=-5.98, p<.01) and erotic (Sobel test z=-4.06, p<.01) motives were not sufficient to explain the significant parental attachment–addiction correlation (r=-.20, p<.01). Because of the absence of direct effects of parental attachment upon social interaction motives and entertainment motives upon addiction, these two motives did not mediate the parental attachment–addiction relationship.

A comparison of the standardized total effects of the two attachment variables upon addiction showed that parental attachment’s effect (-.19) was greater than peer attachment’s (.09).

Finally, with regard to generalizability of results across sexes, analyses for males and females separately generally showed the four goodness of fit indices for the final model to be acceptable for both sexes (the only exception was a significant chi–square index showing a highly marginal lack of fit for females, p=.04). However, for males, parental attachment’s direct effect upon entertainment motives was non–significant. A comparison of the relevant pairs of parameters across the models for males and females showed that the female parental attachment–entertainment path coefficient was significantly greater, z=2.23, p=.03. Nevertheless, following model comparison procedures recommended by Arbuckle (2007), it was concluded that overall the path coefficients for males and females were not significantly different, χ2diff (9)=10.55, p=.31.



5. Discussion

The modified model showed that stronger parental attachment is related to lesser motivation to use the Internet for the purposes of escape (H5d), eroticism (H5c), and to a lesser extent, entertainment (H5a), but not social interaction (contrary to H5b). A possible reason for this is that attachment to parents fulfils a child’s intimacy needs and, hence, the child is less likely to seek escapism, eroticism, and entertainment in order to fulfil their intimacy needs. This is consistent with existing literature that children with a stronger attachment to parents have higher self–esteem and have fewer issues with delinquency and social problems (Armsden and Greenberg, 1987).

On the other hand, stronger peer attachment was related to increased motivation to use the Internet for social interaction (H6b), entertainment (H6a) and (contrary to the hypothesized direction) escape (H6c) purposes, but (as expected, given the forwarding of an open–ended research question rather than a directional hypothesis) not erotic purposes. This is logical, as friends like to talk with each other using the Internet as a preferred channel for communication (Lenhart, et al., 2005).

The data also showed that greater escape (H4), eroticism (H3), and social interaction (H1) motives (but not entertainment motives — H2) were associated with greater Internet addiction scores. Finally, as expected, lower parental attachment was related to higher addiction scores (H5e), but there was no relationship between peer attachment and addiction. The model accounted for 31 percent of the variance in Internet addiction scores. Therefore, despite the fact that some features of the theoretical model tested required modification (most notably, the four motives in the model did not fully mediate the parental attachment–addiction relationship and it was necessary to add a direct link between these latter two variables in the modified model), the findings suggest that the modified uses and gratifications model provides a useful framework in understanding how parental and peer attachments affect online usage motives and addiction.

Escape motives had the greatest influence upon addiction, supporting the suggestion that the need for psychological escape from everyday problems is an addictive factor in online behaviour (Young, 1998). Also, (in terms of z scores associated with Sobel tests) escape motivations’ mediation of the parental attachment–addiction relationship was the largest of the four mediating effects whereby motives mediated attachment–addiction relationships, consistent with Young’s (1998) further suggestion that escape motivations resulting from problematic relationships with parents are particularly important in explaining adolescent Internet addiction. Hence, the present data provide empirical evidence that psychological escape motives are likely to be salient in accounting for the aetiology of Internet addiction. This is important because, although such an idea has often been mooted, data testing this proposition are rare (Kwon, 2011). However, Kwon, et al. (2011) showed that Baumeister’s (1990) escape–from–self theory provides a useful account of the process by which escape is involved in Internet–related addiction. Here, path modelling represented increasing discrepancy between South Korean adolescent Internet game players’ real and ideal selves that lead to more negative moods (e.g., depression, anxiety and unhappiness), which led to increasing escape from the self (e.g., attempts to escape from negative thoughts by immersing oneself in a presently ongoing activity) which in turn led to greater Internet addiction. The current results suggest that this model might be expanded to include lesser parental attachment (but not lesser peer attachment) as an additional source of negative moods, which then lead to immersion in Internet–related activities with subsequent increasing likelihood of addiction to these activities (as a means of reducing dysphoria). The importance of escape in this study is consistent with the uses and gratifications literature in which pastime gratifications (the current escape variable was based upon Huang’s (2004) escape/past time subscale) have been linked to addictive Internet use because of their use in relieving dysphoric moods (LaRose, 2011).

While their effects were smaller than that of escape, the social interaction and erotic motives had similar sized direct effects upon addiction. However, the modified model contained no direct effect of entertainment upon addiction despite a positive entertainment motivation–addiction correlation. One major reason for this was the large correlation between the entertainment and escape motives, a partial correlation analysis (otherwise unreported for brevity) showing that the entertainment–addiction correlation dropped to zero when escape was statistically controlled. This suggests that the major explanation of previous observations connecting entertainment usage and Internet addiction is one whereby certain types of entertainment allow people to psychologically absent themselves from (often difficult) everyday realities.

The fact that erotic motives were related to Internet addiction attests to the addictive potential of using the Internet to locate highly stimulating content and its utility in allowing anonymous and private access to erotic material (Joinson, 2003). Such utility is likely to be particularly valued by curious adolescents in conservative societies such as Malaysia, where magazines, television and movies are highly censored for explicit sexual content.

The direct effects of parental attachment on the erotic and escape motives were greater than that of entertainment. Lesser parental attachment was associated with greater entertainment motivation for females but not for males. This might be because using computers for entertainment (e.g., gaming) is a stereotypically male activity and that, in females, low parental attachment results in rebellion in the form of pursuing stereotypically male pursuits (but, of course, causality might also be reversed, lack of female orthodoxy resulting in lower parental attachment). This general pattern of parental attachment–motivation findings is plausible in that using the Internet for psychological escape and erotic purposes are likely to signal psychological remoteness from parents and their values respectively, whereas (the previously discussed possible rebelliousness of some females aside) usages for entertainment and social interaction do not necessarily signal anything about the parent–child relationship (the assumption underlying the relevant hypotheses being simply that parents aim to ensure that their children’s Internet use stays within reasonable limits).

On peer attachment, the modified model showed that the major influence of peer attachment on Internet usage motives is to encourage its use for social interaction, and to a lesser extent for entertainment. Also, rather than there being a direct effect whereby stronger peer attachment was associated with weaker escape motivations, the direct effect in the modified model linked greater peer attachment with stronger escape motivations. This finding may indicate that there is something unique about the Malaysian situation since it differs from Dutch and Taiwanese studies showing that adolescents lacking in close friends use the Internet as a means of escape (Liu and Kuo, 2007; Peter, et al., 2005). On the other hand, the findings could indicate that those who have stronger escape motivations use the Internet in order to build closer online relationships giving rise to stronger escape motivations resulting in closer peer attachment as reported by Sudzina and Razmerita (2012). Given the statistically positive relationships between peer attachment and the social interaction and entertainment motives, the Sullivan–Piaget thesis (Youniss, 1980) might explain the present unexpected result in terms of a culture of escape (e.g., from problematic relationships in the home — Young, 1998) arising within groups of like–minded adolescents strongly bonded around various specific types of Internet activity.

Overall, the negative parental attachment–Internet addiction relationship was greater than the positive peer attachment–addiction relationship (with respect to both bivariate correlations and total effects in the modified model). This is encouraging in the sense that it suggests that parents can actively influence the likelihood of children’s addiction to Internet-mediated activities and that this influence can more than counterbalance any negative effects of adolescent peers. In particular, the present results suggest that fostering warm parent–child relationships to prevent adolescents from developing a need for psychological escape (along with measures such as installation of software to prevent access to adult material) would assist in minimizing addiction risk.

5.1. Limitations and suggestions for further research

Although the present observation that erotic motives are a less powerful proximal driver of addiction than psychological escape motives might well generalize beyond Malaysian adolescents to adolescents in general, it would be useful to perform further research comparing the relative addictive power of these two types of motive upon other statistical populations such as adult males. Also, in a cross–sectional part of Meerkerk, et al.’s (2006) two–wave longitudinal study of adult heavy Internet users, correlations between use of the Internet for chatting and compulsive Internet use tended to be higher than usage for gaming and erotic purposes, but only erotic usage was a significant predictor of an increase in compulsive Internet use one year later. Thus, while the present study implies that escape motives are the most prominent driver of Internet addiction among the motives studied, one of the limitations of this study was that it was cross–sectional in nature and a future longitudinal study might test whether eroticism is a more salient long–term driver of addiction in Malaysian adolescents.

With respect to the fact that there was no direct effect of peer attachment upon erotic motivations, it is unknown whether the counterbalancing reasons cited in support of the two–tailed hypothesis (tendencies of adolescents to encourage each other in anti-social behaviour in general and the viewing of cyberpornography in particular vs. loneliness and the absence of close peer attachments) were responsible for this result, or whether this might simply be attributable to the possibility that this (particularly personal) online activity is pursued in solitary situations rather than in the presence of peers. Further research might consider these possibilities.



6. Conclusion

The present study has shown that a modified uses and gratifications framework is useful in explaining how significant others might influence adolescent Internet usage motives and addiction. Escape, social interaction and erotic motives are key drivers of adolescent Internet addiction, with escape being the most important motive. Perhaps most importantly, the results suggest that dysfunctional parental attachment and a consequent need for psychological escape are likely to be more highly implicated in the aetiology of Internet–related addiction than peer attachment. End of article


About the authors

Patrick Chin–Hooi Soh (Ph.D.) teaches in the Faculty of Management, Multimedia University, Malaysia and is a visiting scholar in the Singapore Internet Research Centre, Nanyang Technological University. His research interests include Internet usage, addiction, electronic commerce and business. He received his Ph.D. in Internet usage from Multimedia University and Master’s of Science Degree in Information Systems at Malaysia University of Science and Technology.
E–mail: chsoh [at] mmu [dot] edu [dot] my

John P. Charlton (Ph.D.) is a former Reader in Psychology with research interests in computer–related behaviour and attitudes at the University of Bolton, United Kingdom. He now holds the title of Honorary Research Fellow at the University while running Focus Research Editing & Statistics.
E–mail: john [dot] charlton [at] focus–statistics [dot] co [dot] uk

Kok–Wai Chew (Ph.D.) is an Associate Professor, Faculty of Management, Multimedia University, Malaysia and a Singapore Internet Research Center Associate, Nanyang Technological University, Singapore. His research interests are management, generation issues, and e–commerce.
E–mail: kwchew [at] mmu [dot] edu [dot] my



The study was funded by Multimedia University, Malaysia while scholarly resources and guidance was provided by Nanyang Technological University, Singapore.



1. Rubin, et al., 2003, p. 129.

2. Robbins and Judge, 2011, p. 238.

3. Nathanson, 2001, p. 253.

4. Nathanson, 2001, p. 267.



American Psychiatric Association (APA), 2000. Diagnostic and statistical manual of mental disorders: DSM–IV–TR. Fourth edition. Washington, D.C.: American Psychiatric Association.

James Arbuckle, 2007. Amos 16.0 user’s guide. Chicago: SPSS Inc.

Gay C. Armsden and Mark T. Greenberg, 1987. “The inventory of parent and peer attachment: Individual differences and their relationship to psychological well–being in adolescence,” Journal of Youth and Adolescence, volume 16, number 5, pp. 427–454.
doi:, accessed 25 June 2014.

Robert H. Aseltine, Jr., 1995. “A reconsideration of parental and peer influences on adolescent deviance,” Journal of Health and Social Behavior, volume 36, number 2, pp. 103–121.

Roy F. Baumeister, 1990. “Suicide as escape from self,” Psychological Review, volume 9, number 1, pp. 90–113.
doi:, accessed 25 June 2014.

Lukas Blinka and David Smahel, 2011. “Addiction to online role–playing,” In: Kimberly S. Young and Cristiano Nabuco de Abreu (editors). Internet addiction: A handbook and guide to evaluation and treatment. Hoboken, N.J.: Wiley, pp. 73–90.
doi:, accessed 25 June 2014.

John Bowlby, 1982. Attachment and loss. Volume 1: Attachment. Second edition. New York: Basic Books.

Barbara M. Byrne, 2001. Structural equation modelling with AMOS: Basic concepts, applications, and programming. Mahwah, N.J.: Lawrence Erlbaum Associates.

Duane Buhrmester and Wyndol Furman, 1987. “The development of companionship and intimacy,” Child Development, volume 58, number 4, pp. 1,101–1,113.
doi:, accessed 25 June 2014.

John P. Charlton, 2002. “A factor analytic investigation of computer addiction and engagement,” British Journal of Psychology, volume 93, number 3, pp. 329–344.
doi:, accessed 25 June 2014.

John P. Charlton and Ian D.W. Danforth, 2010. “Validating the distinction between computer addiction and engagement: Online game playing and personality,” Behaviour & Information Technology, volume 29, number 6, pp. 601–613.
doi:, accessed 25 June 2014.

John P. Charlton and Ian D.W. Danforth, 2007. “Distinguishing addiction and high engagement in the context of online game playing,” Computers in Human Behavior, volume 23, number 3, pp. 1,531–1,548.
doi:, accessed 25 June 2014.

Yong Jun Choi, 2001. “Investigating Koreans’ Internet use patterns and motivations, and exploring vulnerability of Internet dependency,” Ph.D dissertation at the University of Southern Mississippi.

Chien Chou and Ming–Chun Hsiao, 2000. “Internet addiction, usage, gratification, and pleasure experience: The Taiwan college students’ case,” Computers & Education, volume 35, number 1, pp. 65–80.
doi:, accessed 25 June 2014.

Jacob Cohen, 1988. Statistical power analysis for the behavioral sciences. Second edition. Hillsdale, N.J.: L. Erlbaum Associates.

Alvin Cooper, 1998. “Sexuality and the Internet: Surfing into the new millennium,” CyberPsychology & Behavior, volume 1, number 2, pp. 187–193.
doi:, accessed 25 June 2014.

Franca Cortoni and William L. Marshall, 2001. “Sex as a coping strategy and its relationship to juvenile sexual history and intimacy in sexual offenders,” Sexual Abuse, volume 13, number 1, pp. 27–43.
doi:, accessed 25 June 2014.

Anthony M. Dalessandro and Rebecca M. Chory–Assad, 2006. “Comparative significance of parental vs. peer mediation of adolescents’ antisocial video game play,” paper presented at the annual meeting of the International Communication Association, (Dresden, Germany).

John Davies, 2007. “Peer influences on sexual media use,” paper presented at the annual meeting of the International Communication Association conference (San Francisco).

Richard A. Davis, 2001. “A cognitive–behavioral model of pathological Internet use,” Computers in Human Behavior, volume 17, number 2, pp. 187–195.
doi:, accessed 25 June 2014.

Majumdar Debarun, 2003. “Understanding the dimensions of parental and peer influence on risky sexual behavior among adolescents,” paper presented at the annual meeting of the American Sociological Association (Atlanta).

Yan–xia Deng, Ming Hu, Guo–qing Hu, Le–san Wang, Zhen–qiu Sun, 2007. “An investigation of the prevalence of Internet addiction disorder in middle school students of Hunan province,” Zhonghua Liu Xing Bing Xue Za Zhi, volume 28, number 5, pp. 445–448.

Alecia C. Douglas, Juline E. Mills, Mamadou Niang, Svetlana Stepchenkova, Sookeun Byun, Celestino Ruffini, Seul Ki Lee, Jihad Loutfi, Jung–Kook Lee, Mikhail Atallah and Marina Blanton, 2008. “Internet addiction: Meta–synthesis of qualitative research for the decade 1996–2006,” Computers in Human Behavior, volume 24, number 6, pp. 3,027–3,044.
doi:, accessed 25 June 2014.

Matthew S. Eastin, 2005. “Teen Internet use: Relating social perceptions and cognitive models to behavior,” CyberPsychology & Behavior, volume 8, number 1, pp. 62–75.
doi:, accessed 25 June 2014.

Regina J.J.M. van den Eijnden, Gert–Jan Meerkerk, Ad A. Vermulst, Renske Spijkerman and Rutger C.M.E. Engels, 2008. “Online communication, compulsive Internet use, and psychosocial well–being among adolescents: A longitudinal study,” Developmental Psychology, volume 44, number 3, pp. 655–665.
doi:, accessed 25 June 2014.

David Greenfield, 2011. “The addictive properties of Internet usage,” In: Kimberly S. Young and Cristiano Nabuco de Abreu (editors). Internet addiction: A handbook and guide to evaluation and treatment. Hoboken, N.J.: Wiley, pp. 135–153.
doi:, accessed 25 June 2014.

Mark Griffiths, 1998. “Internet addiction: Does it really exist?” In: Jayne Gackenbach (editor). Psychology and the Internet: Intrapersonal, interpersonal, and transpersonal implications. San Diego, Calif.: Academic Press, pp. 61–75.

Mark Griffiths and Mark N.O. Davies, 2005. “Does video game addiction exist?” In: Joost Raessens and Jeffrey H. Goldstein (editors). Handbook of computer game studies. Cambridge, Mass.: MIT Press, pp. 359–368.

Herta Herzog, 1940. “Professor quiz: A gratification study,” In: Paul F. Lazarsfeld (editor). Radio and the printed page: An introduction to the study of radio and its role in the communication of ideas. New York: Duell, Sloan and Pearce, pp. 64–93.

Constance Holden, 2001. “‘Behavioral’ addictions: Do they exist?” Science, volume 294, number 5544, pp. 980–982.
doi:, accessed 25 June 2014.

Anthony Shih–Chieh Huang, 2004. “The bright and dark side of cyberspace: The paradoxical media effects of Internet use on gratifications, addictions, social and psychological well–being among Taiwan’s Net–Generation,” Ph.D. dissertation, Southern Illinois University, Carbondale.

International Telecommunication Union, 2009. “Malaysia case study,” at, accessed 25 June 2014.

Jerome H. Jaffe, 1990. “Trivializing dependence,” British Journal of Addiction, volume 85, number 11, pp. 1,425–1,427.
doi:, accessed 25 June 2014.

Adam N. Joinson, 2003. Understanding the psychology of Internet behaviour: Virtual worlds, real lives. Basingstoke, Hampshire, England: Palgrave Macmillan.

Jonathan J. Kandell, 1998. “Internet addiction on campus: The vulnerability of college students,” CyberPsychology & Behavior, volume 1, number 1, pp. 11–17.
doi:, accessed 25 June 2014.

Dimitris Karaiskos, Elias Tzavellas, G. Balta and T. Paparrigopoulos, 2010. “Social network addiction: A new clinical disorder?” European Psychiatry, volume 25, supplement 1, p. 855.
doi:, accessed 25 June 2014.

Elihu Katz, Jay G. Blumler and Michael Gurevitch, 1974. “Utilization of mass communication by the individual,” In: Jay G. Blumler and Elihu Katz (editors). The uses of mass communications: Current perspectives on gratifications research. Beverly Hills, Calif.: Sage, pp. 19–32.

Barbara K. Kaye, 1998. “Uses and gratifications of the World Wide Web: From couch potato to Web potato,” New Jersey Journal of Communication, volume 6, number 1, pp. 21–40.
doi:, accessed 25 June 2014.

Rex B. Kline, 2005. Principles and practice of structural equation modeling. Second edition. New York: Guilford Press.

Chih–Hung Ko, Ju–Yu Yen, Cheng–Fang Yen, Huang–Chi Lin and Ming–Jen Yang, 2007. “Factors predictive for incidence and remission of Internet addiction in young adolescents: A prospective study,” CyberPsychology & Behavior, volume 10, number 4, pp. 545–551.
doi:, accessed 25 June 2014.

Jung–Hye Kwon, 2011. “Toward the prevention of adolescent Internet addiction,” In: Kimberly S. Young and Cristiano Nabuco de Abreu (editors). Internet addiction: A handbook and guide to evaluation and treatment. Hoboken, N.J.: Wiley, pp. 223–243.
doi:, accessed 25 June 2014.

Jung–Hye Kwon, Chung–Suk Chung and Jung Lee, 2011. “The effects of escape from self and interpersonal relationship on the pathological use of Internet games,” Community Mental Health Journal, volume 47, number 1, pp. 113–121.
doi:, accessed 25 June 2014.

Chun Bun Lam and Darius K.–S. Chan, 2007. “The use of cyberpornography by young men in Hong Kong: Some psychosocial correlates,” Archives of Sexual Behavior, volume 36, number 4, pp. 588–598.
doi:, accessed 25 June 2014.

Robert LaRose, 2011. “Uses and gratifications of Internet addiction,” In: Kimberly S. Young and Cristiano Nabuco de Abreu (editors). Internet addiction: A handbook and guide to evaluation and treatment. Hoboken, N.J.: Wiley, pp. 55–72.
doi:, accessed 25 June 2014.

Li Lei and Yana Wu, 2007. “Adolescents’ paternal attachment and Internet use,” CyberPsychology & Behavior, volume 10, number 5, pp. 633–639.
doi:, accessed 25 June 2014.

Amanda Lenhart, Paul Hitlin and Mary Madden, 2005. “Teens and technology” (27 July), Pew Research Internet Project, at, accessed 25 June 2014.

Chien–Huang Lin and Shu–Fen Yu, 2008. “Adolescent Internet usage in Taiwan: Exploring gender differences,” Adolescence, volume 43, number 170, pp. 317–331.

Chia–Yi Liu and Feng–Yang Kuo, 2007. “A study of Internet addiction through the lens of the interpersonal theory,” CyberPsychology & Behavior, volume 10, number 6, pp. 799–804.
doi:, accessed 25 June 2014.

Malaysia. Department of Statistics, 2009. “Population,” updated 31 July, at, accessed 15 October 2009.

Malaysia. Economic Planning Unit, 2012. “The Malaysian economy in figures 2012,” at, accessed 25 June 2014.

Gert–Jan Meerkerk, Regina J.J.M. van den Eijnden and Henk F.L. Garretsen, 2006. “Predicting compulsive Internet use: It’s all about sex!” CyberPsychology & Behavior, volume 9, number 1, pp. 95–103.
doi:, accessed 25 June 2014.

Gustavo S. Mesch, 2005. “Youth pornographic consumption: How similar and different are from other Internet users,” paper presented at the CyberSafety conference: Safety and security in a networked world: Balancing cyber–rights and responsibilities (Oxford); version at, accessed 25 June 2014.

Olivia Metcalf and Kristen Pammer, 2011. “Attentional bias in excessive massively multiplayer online role–playing gamers using a modified Stroop task,” Computers in Human Behavior, volume 27, number 5, pp. 1,942–1,947.
doi:, accessed 25 June 2014.

J. Morahan–Martin and P. Schumacher, 2000. “Incidence and correlates of pathological Internet use among college students,” Computers in Human Behavior, volume 16, number 1, pp. 13–29.
doi:, accessed 25 June 2014.

Amy I. Nathanson, 2001. “Parents versus peers: Exploring the significance of peer mediation of antisocial television,” Communication Research, volume 28, number 3, pp. 251–274.
doi:, accessed 25 June 2014.

John E. Newhagen and Sheizaf Rafaeli, 1996. “Why communication researchers should study the Internet: A dialogue,” Journal of Communication, volume 46, number 1, pp. 4–13.
doi:, accessed 25 June 2014.

Zizi Papacharissi and Alan M. Rubin, 2000. “Predictors of Internet use,” Journal of Broadcasting and Electronic Media, volume 44, number 2, pp. 175–196.
doi:, accessed 25 June 2014.

Jochen Peter, Patti M. Valkenburg and Alexander P. Schouten, 2005. “Developing a model of adolescent friendship formation on the Internet,” CyberPsychology & Behavior, volume 8, number 5, pp. 423–430.
doi:, accessed 25 June 2014.

Helen Phillips, 2006. “Just can’t get enough,” New Scientist, volume 191, number 2566 (26 August), pp. 30–35.

Stephen P. Robbins and Timothy A. Judge, 2011. Organizational behavior. Fourteenth edition. Upper Saddle River, N.J.: Prentice Hall.

Keith Roe, 1995. “Adolescents’ use of socially disvalued media: Towards a theory of media delinquency,” Journal of Youth and Adolescence, volume 24, number 5, pp. 617–631.
doi:, accessed 25 June 2014.

Alan M. Rubin and Elizabeth M. Perse, 1987. “Audience activity and soap opera involvement: A uses and effects investigation,” Human Communication Research, volume 14, number 2, pp. 246–268.
doi:, accessed 25 June 2014.

Alan M. Rubin, Paul M. Haridakis, Gwen A. Hullman, Shaojing Sun, Pamela M. Chikombero and Vikanda Pornsakulvanich, 2003. “Television exposure not predictive of terrorism fear,” Newspaper Research Journal, volume 24, number 1, pp. 128–145.

Thomas E. Ruggiero, 2000. “Uses and gratifications theory in the 21st century,” Mass Communication and Society, volume 3, number 1, pp. 3–37.
doi:, accessed 25 June 2014.

Wilbur Schramm, Jack Lyle and Edwin B. Parker, 1961. Television in the lives of our children. Stanford, Calif.: Stanford University Press.

Andreas Schindler, Rainer Thomasius, Peter–Michael Sack, Brigitte Gemeinhardt and Udo Küstner, 2007. “Insecure family bases and adolescent drug abuse: A new approach to family patterns of attachment,” Attachment and Human Development, volume 9, number 2, pp. 111–126.
doi:, accessed 25 June 2014.

Soonhwa Seok and Boaventura DaCosta, 2012. “The world’s most intense gaming culture: Addiction and high–engagement prevalence rates among South Korean adolescents and young adults,” Computers in Human Behavior, volume 28, number 6, pp. 2,143–2,151.
doi:, accessed 25 June 2014.

Patrick C.–H. Soh, Yap Liang Yan, Tze San Ong, Boon Heng Teh, 2012. “Digital divide amongst urban youths in Malaysia — Myth or reality?” Asian Social Science, volume 8, number 15, pp. 75–85, and at, accessed 25 June 2014.

Frantisek Sudzina and Liana Razmerita, 2012. “Escapist motives for on–line gaming and strengthening of weak ties,” paper presented at the itAIS 2012: IX Conference of the Italian Chapter of Association for Information Systems, at, accessed 25 June 2014.

Laurence Steinberg, 2001. “We know some things: Parent–adolescent relationships in retrospect and prospect,” Journal of Research on Adolescence, volume 11, number 1, pp. 1–19.
doi:, accessed 25 June 2014.

Artemis Tsitsika, Elena Critselis, Georgios Kormas, Anastasia Filippopoulou, Despoina Tounissidou, Aliki Freskou, Theodora Spiliopoulou, Amalia Louizou, Eleftheria Konstantoulaki and Dimitrios Kafetzis, 2008. “Internet use and misuse: A multivariate regression analysis of the predictive factors of Internet use among Greek adolescents,” European Journal of Pediatrics, volume 168, number 6, pp. 655–665.
doi:, accessed 25 June 2014.

Emmanuelle Vignoli and Pascal Mallet, 2004. “Validation of a brief measure of adolescents’ parent attachment based on Armsden and Greenberg’s three–dimension model,” Revue Européene de Psychologie Appliquée, volume 54, number 4, pp. 251–260.
doi:, accessed 25 June 2014.

Patricia M. Wallace, 1999. The psychology of the Internet. Cambridge: Cambridge University Press.

Thomas A. Widiger and Douglas B. Samuel, 2005. “Diagnostic categories or dimensions? A question for the Diagnostic and Statistical Manual of Mental Disorders — fifth edition,” Journal of Abnormal Psychology, volume 114, number 4, pp. 494–504.
doi:, accessed 25 June 2014.

Vincent Yoder, Thomas B. Virden and Kiran Amin, 2005. “Internet pornography and loneliness: An association?” Sexual Addiction & Compulsivity, volume 12, number 1, pp. 19–44.
doi:, accessed 25 June 2014.

Kimberly S. Young, 1998. Caught in the net: How to recognise the signs of Internet addiction — and a winning strategy for recovery. New York: John Wiley.

Kimberly S. Young, Xiao Dong Yue and Li Ying, 2011. “Prevalence estimates and etiologic models of Internet addiction,” In: Kimberly S. Young and Cristiano Nabuco de Abreu (editors). Internet addiction: A handbook and guide to evaluation and treatment. Hoboken, N.J.: Wiley, pp. 3–17.
doi:, accessed 25 June 2014.

James Youniss, 1980. Parents and peers in social development: A Sullivan–Piaget perspective. Chicago: University of Chicago Press.


Editorial history

Received 21 January 2014; revised 26 May 2014; accepted 19 June 2014.

Creative Commons License
This paper is in the public domain.

The influence of parental and peer attachment on Internet usage motives and addiction
by Patrick Chin–Hooi Soh, John P. Charlton, and Kok–Wai Chew.
First Monday, Volume 19, Number 7 - 7 July 2014

A Great Cities Initiative of the University of Illinois at Chicago University Library.

© First Monday, 1995-2017. ISSN 1396-0466.