“OCCIDENTALES”
3.1.3. LA EDUCACIÓN AUDIOVISUAL EN EL ESTADO ESPAÑOL
3.1.3.3. EL PROYECTO MERCURIO
Eijnden et al.’s (2008) studies. Respondents rate each item on a 4-point scale (1: never, 2:
rarely, 3: sometimes, 4: often). The Cronbach’s alpha coefficient for the current sample was
Questionnaires assessing co-morbidity of psychopathology
A 9-item self-report questionnaire assessed the presence of emotional and psychiatric problems. Specific questions were asked such as: Have you ever had 1) depression, 2) attempted suicide /deliberate self-harm, 3) manic episode/manic depression/bipolar, 4) anxiety/panic/phobia, 5) obsessive compulsive disorder, 6) psychotic episode/schizophrenia, 7) eating disorders, 8) drug and alcohol problem, 9) other psychopathology? A score of either 0 (absent) or 1 (present) was assigned. In order to obtain an index of the co-morbidity, I summed the scores obtained from each of the psychopathologies (scores ranging from 0 to 9) were summed.
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2.3.4 Procedure
The participants were invited to complete an online questionnaire assessing levels of internet use (IAT and PIUQ) on an online data collection website (the Bristol Online Survey).
In this phase, the participants were given information about the study and offered the opportunity to ask any further questions. Based on the IAT and PIUQ scores, a convenient sample was contacted via email and asked to participate in the second phase of the experiment. In the second phase, an effort was made to recruit participants whose internet use ranged from low to high. Those invited for the second phase were asked to attend the Psychology Lab at the University of Bath where they were given information explaining the procedure for the experiment and a consent form, which they had to sign once they agreed to take part in the study. Subsequently, they were asked to fill in an online questionnaire assessing different aspects of psychopathology (BSI-53), personality dimension of impulsivity (BIS-11), questions related to online activities and finally questions assessing the co-morbidity of psychopathological disorders (depression, substance misuse etc.). Then they proceeded to the computerized task (IGT). Completing prescreen assessments such as those detailing psychopathological and demographic information has been reported in prior studies using the IGT and there is no indication that this order has an effect over performance (Miu et al., 2008; Briggs et al., 2015). The task was performed in a sound proof room in order to control for any noise which might have interfered with the physiological recordings (SCRs).
In order to record the SCRs, before participants started the IGT two electrodes were attached to the middle and index fingers in the distal phalanx area of the non-dominant hand by applying an electrolyte gel and waiting for about 5 minutes. It has been suggested that this area of the hand provides the best responsivity to SCRs (Bouscein et al., 2012). These fingers were selected so that participants could use the dominant hand to give responses while performing the IGT and the waiting time is considered sufficient for the electrolyte gel to be absorbed and thus enable better contact between the skin and the electrodes. At this stage participants were asked to rest their hand, to which the electrodes had been attached in a comfortable position and not to move it throughout the experiment. Also, they were asked to try to not to move and stay still during the experiment as any movement would have an impact on data acquisition. Once it was assured that there was good connectivity of the
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electrodes by asking participants to take a deep breath and checking for an appropriate SCR response, they started the IGT. Participants read the following instructions on the computer screen:
On the screen in front of you there are four decks of cards: A, B, C, and D. I want you to select one card at a time, by pressing on A, B, C and D keys on the keyboard. Each time you select a card from a deck, the colour of the card will turn red or black, and the computer will tell you that you have won some money. Every time you win, the green bar gets longer.
However, every so often when you click on a card the computer will tell you that you have won some money but also it will tell you that you have lost some money. Every time you lose, the red bar gets longer. You are absolutely free to switch from one deck to another at any time you wish. The goal of the game is to win as much money as possible. All I can say is that you may find yourself losing money on all of the decks, but some decks will make you lose more than others. If you have any questions please ask now.
Press the SPACE bar to begin.
The total participation time was 30 minutes. Participants received a payment of £10 for their time and they were verbally debriefed at the end of the experiment.
2.3.5 Psychophysiological Responses
Skin Conductance Responses (SCRs)
Electrodermal responses are the index of the changes in electrical activity in a person’s skin (Bach, Flandin, Friston, & Dolan, 2009). SCRs have been widely used to measure levels of arousal associated with emotional and cognitive processes (Bach et al., 2009). In the present study SCRs were acquired using a Biopac system (MP150) in combination with the modules for skin conductance (GSR100C). AcqKnowledge software was used in order to set up: acquisition parameters, real time monitoring, and the recording and analysis of the measurements for the SCRs data. In this study, the Biopac amplification was linked up to no
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hardware high-pass filters. That is, the switches were set to DC-which meant that the current flows and the two electrodes were polarized in opposite directions. This method provides an exosomatic measure of SCRs by applying a direct current (0.5V). The sampling rate was set to 1000Hz. Reusable electrodes Ag/AgCl, were used, filled with electrolyte gel (NaCl isotonic-a solution that has the same salt concentration as the normal cells of the body and the blood), which is specially formulated with 0.5% saline in a neutral base and these were cleaned after each use. SCRs were measured in MicroSiemens (S) and the threshold value for analysing SCRs was set at 0.02 S and the rejection rate was set to 0% (all SCRs were included in the analysis). The rejection rate has been used in order to control for contextual information which might affect the SCR amplitude. For example, a rejection rate of 10%
suggests that detected SCRs with an amplitude smaller of the 10% of the maximum SCR amplitude in this segment are excluded. However, due to the nature of this experiment, there is a possibility that the maximum SCR amplitude might reflect the initial activation when the secure contact of the electrodes was checked. This might then mask any SCR amplitudes associated with the task so it was decided to include all SCR responses.
For this study, three types of SCR were measured; punishment SCRs, which were generated after turning a card for which there was a reward immediately followed by a penalty; reward SCRs, which were generated after turning a card for which there was a reward, and anticipatory SCRs, which were generated prior to turning a card from any given deck. Event-related analysis was used to analyse the SCRs in this study. The time window for the reward and punishment SCRs was set from the 2nd second after participants made a response, until the 5th second. This time window was long enough to capture SCRs related to the stimulus for it has been suggested that the electrodermal response begins between 1 and 4 seconds after stimulus presentation (Dawson, Schell, & Courtney, 2011). Moreover, it is short enough to avoid noise in terms of electrodermal activity related to non-specific changes in autonomic arousal. Additionally, those SCRs generated during the end of the reward/punishment window and before the next click of a card were considered as anticipatory SCRs. The time window varied from trial to trial as there was a set-up period of 6 seconds where participants could not make a response, and after this time interval on average participants made a response within two to three seconds after the end of these 6 seconds. Thus, the time window for the anticipatory SCRs was set from the end of the 6th
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second (where the four decks of cards appeared on the screen and another choice could be made) for a duration of 3 seconds. This measure differs from Bechara et al.’s (2002) time window of 5 seconds that participants took to respond. In our sample participants made quicker choices, within 3 seconds and thus the time window chosen was the best possible fit of the data, in order to control for overlapping activity between trials and events. For each participant two dependent variables for reward, punishment and anticipatory SCRs were obtained respectively, for both advantageous and disadvantageous decks.
SCRs activity was recorded continuously while performing the IGT and their choice of cards was recorded as a ‘’mark’’ on the polygram. Thus, it was possible to associate SCRs activity with choices from a specific deck of cards each time. The room temperature conditions were the same for all the participants and averaged between 20 and 22 degrees Celsius.
2.3.6 Statistical Analysis
All statistical analyses of the data presented below were conducted using the software SPSS 20. The Pearson correlation coefficients assessed whether performance on the IGT degraded as the severity of problematic internet use increased. Performance was analysed for the total number of trials (100 trials) and for each of the five blocks (20 trials each).
Additionally, biserial correlations assessed the association between the severity of problematic internet use and psychopathological co-morbidity. Moreover, due to the higher number of females in our sample, gender was initially introduced in the analysis as a covariate but it had no effect on performance and therefore it was excluded from further analysis. Although problematic internet use was viewed along a continuum, in order to assess the distribution of the scores within the samples two groups were created based on the median split scores on the IAT (median =50.5, thus individuals with lower/no levels of problematic internet use scored lower than 50.5 and individuals with higher levels of problematic internet use scored higher than 50.5) as well as on the PIUQ (median = 46.5, thus individuals with lower/no levels of problematic internet use scored lower than 46.5 and individuals with higher levels of problematic internet use scored higher than 46.5). The
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median value for PIUQ of our sample was similar to the cut off mean value of 46.7 which, according to Demetrovics et al. (2008), is a cut off that reliably distinguishes problematic from non-problematic internet users. Thus, performance on the IGT for the two groups (conducted separately, either based on the IAT or PIUQ median split) was assessed with a 2 (groups) x 5 (blocks) mixed way ANOVA, followed up with post-hoc tests to identify differences in performance between the blocks in the IGT.
Due to technical difficulties seven participants had no SCR data and thus were excluded from further analysis. Furthermore, data were excluded from the analysis when they were deviating more than three times the interquartile range from the 25th or 75th percentile (2.8%
of the data) in order to control for movement artefacts and when there was a missing value for that particular event (9.7% of data). A Spearman correlation was used to correlate SCRs with the IAT and PIUQ scores because the SCR data violated parametric assumptions, i.e.
highly skewed with high levels of kurtosis. Finally, Mann-Whitney and Wilcoxon tests assessed between and within group differences on SCRs data respectively. SCRs data were averaged for each type of deck in relation to the whole task performance in a similar way to Goudriaan et al. (2006), Miu et al. (2008) and Bechara et al.’s (1999) methodologies.
Additionally, Pearson correlation coefficients assessed the association between various psychopathological constructs and impulsivity with the severity of problematic internet use, as well as the association between various online applications with the severity of problematic internet use. Finally, multiple regressions assessed the predictability of various online applications in association to the severity of problematic internet use.