LA METODOLOGÍA EN LA INTEGRACIÓN CURRICULAR DE LOS MAV-MCM 159

2000ms

Until response

Figure 3.4: Example of an experimental trial in the Visual Dot-Probe Task.

3.3.4 Pleasantness Rating task

The Pleasantness Rating task was generated with E-prime 2.0 Professional software (Psychology Software Tools, Pittsburgh, PA). The main requirement of this task was to rate the pleasantness of each of the 40 images (15 internet and 25 control images) which were presented in the Dot-Probe task, with the exception of the neutral images which were used for the practice and filler trials. Following the presentation of each image (2000ms) participants rated on a 7-point scale how pleasant each image appeared to them (ranging from 1 “not pleasant” to 7 “very pleasant”) by pressing one of the seven corresponding keys on the keyboard (numbers 1 to 7). The size of the pictures was 15.5cm wide and 11cm high and there was a 2000ms inter trial interval.

3.3.5 Eye tracking

A head-free Eye Tracking System, Desktop 6 (D6) Optics ASL (Applied Science Laboratories, Bedford, MA) tracked and recorded eye movements. Some of the advantages of this type of eye tracker are: 1) it does not require any equipment to be attached to the participant; 2) it allows for free movement of the head; 3) it records the gaze’s horizontal

+

.

129

and vertical location at a sample rate of 60Hz with an accuracy of 0.5^o of visual angle; and, 4) it uses a facial recognition program to find the participant’s eye and thus the calibration procedure is carried out very quickly. Eye-tracking equipment was calibrated by presenting the numbers 1 to 9 on the screen in a 3x3 array (with number 1 at the top left of the screen and 9 at the bottom right). Participants were instructed to look at each number in turn, whilst their gaze position was recorded for each number. The direction of gaze was measured in degrees, and sampled once every 17ms. If eye movements were stable within 1^o degree of the visual angle for 100ms or more, this was classified as a fixation on that position, the duration of which was recorded. The eye tracker was placed below the computer monitor display at a distance of 70cm away from the participant’s chair. Eye movements were recorded for each trial from the offset of the fixation cross until participants made a response to the probe. Data were analysed with ASL Results⁺ GM data analysis software (Applied Science Laboratories, Bedford, MA).

3.3.6 Self-report measures - Questionnaires

Addiction-Engagement Questionnaire (AEQ)

The AEQ is a 24-item self-report assessment of the severity of problematic internet use and consists of positive and negative statements. Respondents rate each item on a 7-point scale (1 “completely agree” to 7 “completely disagree”). The AEQ consists of two factors:

addiction and engagement with scores ranging from 12 to a maximum 84 for each factor.

The addiction factor consists of 12 items, seven of which relate to what have been termed to be the “core” criteria of addiction (behavioural salience-2 items, conflict-3 items, relapse and reinstatement-1 item, and withdrawal symptoms-1 item) and similarly, the engagement factor consists of 12 items, two of which relate to what have been termed “peripheral” criteria of addiction (cognitive salience-1 item, euphoria-1 item). The presence or absence of core and peripheral criteria are indicative for the categorization of problematic and non-problematic users.

The AEQ was initially developed to distinguish between problematic and high

130

engagement in association with computer and online gaming use based on Brown’s (1991, 1993) proposed criteria for behavioural addictions (Charlton, 2002; Charlton and Danforth, 2007, 2010). Carlton (2002) argued that different sets of the proposed criteria associated with problematic (core criteria of addiction) and high engagement (peripheral criteria of addiction) respectively. Charlton’s argument developed through the observation that for some individuals even though they spent a lot of time on computer activities, their lives did not suffer negative consequences. He suggested that the negative consequences were a hallmark for distinguishing between high engagement and problematic behaviour.

In this present study the latest version of the scale which previously had been used to assess behavioural patterns of a specific type of Massively Multiplayer Online Role-Playing Game: Asheron’s Call, was adapted and each item reworded with a reference to the internet (see Appendix III for details). For example, a statement such as “Arguments have sometimes arisen at home because of the time I spend on Asheron’s Call” was reworded to “Arguments have sometimes arisen at home because of the time I spend on the internet”. Moreover, the severity of problematic internet use in relation to specific online applications such as social networking sites (SNS) and online gaming was assessed. Thus, two more versions of the AEQ were included and adapted accordingly. For example, all the items of the questionnaire were reworded with reference to SNS and online gaming. Therefore a statement such as

“Arguments have sometimes arisen at home because of the time I spend on the internet” was reworded to “Arguments have sometimes arisen at home because of the time I spend on SNS” and “Arguments have sometimes arisen at home because of the time I spend on online gaming”.

In order to classify participants based on their responses in relation to core and peripheral criteria on the AEQ, a polythetic approach and classification system was adapted similar to Charlton and Danforth (2007, 2010) and Metcalf and Pammer’s (2011) methodology.

Moreover, responses to items associated with the core and peripheral criteria of addiction were dichotomised and mid-range responses were discarded. For the classification of problematic internet use, participants had to respond positively in at least 4 out of the 7 core criteria related to the addiction factor. Also, for the classification of high engagement,

131

participants had to respond positively to 1 or 2 of the peripheral criteria related to the engagement factor and to 3 or less of the core criteria related to the addiction factor. The non-problematic internet users had to have negative responses in all of the 7 core and the 2 peripheral criteria. Moreover, from the initial phase where patterns of internet use were assessed, a high proportion of individuals who did not satisfy any of the criteria of the aforementioned groups were identified. Previous research (Charlton and Danforth, 2007, 2010; Metcalf & Pammer, 2011) has not made any reference to individuals that belong to this newly identified group. The participants belonging to this group either responded positively to 3 or less of the core criteria of addiction and negatively in the peripheral criteria or positively in 1 of the peripheral criteria and negatively to all core criteria. This group was termed the moderate internet users and they were included in the second phase of the experiment in order to assess whether they had similar characteristics to the non-problematic group. The Cronbach’s alpha coefficient for the addiction factor was and for the high engagement factor 0.83 for the general internet use, 0.92 and 0.92 for the online gaming and 0.92 and 0.91 for social networking sites respectively.

Internet Addiction Test (IAT)

The Cronbach’s alpha coefficient was 0 for the whole scale and 0.89 (withdrawal and social problems), 0.85 (time management and performance) and 0.70 (reality substitute).

Problematic Internet Use Questionnaire (PIUQ)

The Cronbach’s alpha coefficient sample was 0 for the whole scale and 0.91 (obsession), 0.84 (neglect) and 0.89 (control disorder).

In order to accommodate for the discrepancies in relation to assessment criteria and diagnosis for problematic internet use, in this study problematic internet use was assessed based on three different well established and validated questionnaires (the AEQ, the IAT and the PIUQ).The goal was to assess relationships between these questionnaires with their

132

factors and thus provide; 1) a better understanding of the different components of problematic internet use, 2) relationships between the different assessment criteria and 3) validate whether or not there were qualitative differences between problematic, high engager, moderate and non-problematic internet users.

Brief Symptom Inventory (BSI-53)

The Cronbach’s alpha coefficient was 0 for the whole scale and 0.85 (somatization), 0.84 (obsession-compulsion), 0.88 (interpersonal sensitivity), 0.86 (depression), 0.87 (anxiety), 0.85 (hostility), 0.86 (phobic anxiety), 0.84 (paranoid ideation), and, 0.84 (psychoticism). All raw scores were converted to T-scores using adult non-patient norms for each gender (Derogatis, 1993).

Barratt Impulsiveness Scale version 11 (BIS)

The Cronbach’s alpha coefficient was 0 for the whole scale and 0.72 (non-planning), 0.70 (motor) and 0.71 (cognitive).

The BSI-53 and BIS-11 were used in order to assess whether there were qualitative differences between groups of problematic internet users in relation to psychopathological and personality constructs.

Questionnaire on internet use urges (QIUU)

The QIUU is a 10-item self-report questionnaire assessing severity of urges to be online.

Respondents rate each item on a 7-point scale (1 “completely disagree” to 7 “completely agree”).The QIUU was adapted from the original Questionnaire on Smoking Urges-Brief (Cox, Tiffany, & Christen, 2001; Tiffany & Drobes, 1991). In order to assess levels of urges to be online each item was reworded with a reference to online activity. For example a

133

statement such as “I have the desire for a cigarette right now” was reworded to “I have the desire to be online right now”. The Cronbach’s alpha coefficient was 0

The QIUU was used to assess whether increase urges to be online correlate with attentional bias for internet-related stimuli.

3.3.7 Procedure

On first contact, participants were given information in relation to the study’s aims and procedures and were provided with the opportunity to ask any questions that they might have had. Once they agreed to take part they completed a battery of questionnaires comprising the AEQ, IAT, PIUQ, BIS-11 and BSI-53 on an online data collection website (Bristol Online Survey). Based on the selection criteria outlined above (subsection 3.3.1), a sample of internet users were invited to participate in the second phase of the experiment which took place in the Department of Psychology Laboratories. Upon arrival, participants were given information in relation to the experimental procedures, they provided informed consent and asked any questions they had. Next the participants sat comfortably in a chair at a 70cm distance (approximately) from a computer display where they performed the two computer based tasks. At the beginning of the testing procedure eye tracker calibration was conducted.

The participants then completed the Dot-Probe task and were explicitly instructed to try to stay as still as possible throughout the experiment, to fixate on the cross at the start of each trial when it appeared on the screen and to try not to blink while they viewed the cross and the pair of pictures. Then they completed the Pleasantness Rating task and a battery of questionnaires comprising the QIUU and AEQ for specific online applications namely;

social networking sites and online gaming. After the completion of the questionnaires, participants were fully debriefed and received a payment of £10. The total participation time took approximately thirty minutes. Those participants who filled in the online questionnaires but were not selected for the second phase of the experiment had the opportunity to win a

£50 Amazon voucher in a prize draw.

134