This result further supports a parallel between individuals with problematic, excessive SNS use, and individuals with substance use and behavioral addictive disorders.

Our results demonstrate that more severe, excessive SNS use is associated with more deficient value-based decision making. In particular, our results indicate that excessive SNS users may make more risky decisions during the IGT task.

We found a negative correlation between BFAS score and performance in the IGT across participants, specifically over the last block of 20 trials. There were no correlations between BFAS score and IGT performance in earlier blocks of trials.

We administered the Bergen Facebook Addiction Scale (BFAS) to 71 participants to assess their maladaptive use of the Facebook SNS. We next had them perform 100 trials of the IGT to assess their value-based decision making.

Online social networking sites (SNSs) like Facebook provide users with myriad social rewards. These social rewards bring users back to SNSs repeatedly, with some users displaying maladaptive, excessive SNS use. Symptoms of this excessive SNS use are similar to symptoms of substance use and behavioral addictive disorders. Importantly, individuals with substance use and behavioral addictive disorders have difficulty making value-based decisions, as demonstrated with paradigms like the Iowa Gambling Task (IGT); however, it is currently unknown if excessive SNS users display the same decision-making deficits. Therefore, in this study, we aimed to investigate the relationship between excessive SNS use and IGT performance.

Methods Participants Seventy-one participants (44 females) between 18 and 35 years of age [(mean = 23.7, standard deviation (SD) = 3.8 years] took part in this study, which was conducted at a large German university. Individuals were recruited through posted flyers. To note, all participants were proficient in the English language, and English was used for the recruitment flyers, e-mail correspondence, face-to-face interactions, and the below-described experimental measures. All participants self-reported having no history of psychiatric disorders, including substance use disorder or other behavioral disorders (e.g., gambling disorder). After completion of the experiment, all individuals were provided 10€ for their participation. Measures We collected measures of excessive SNS use, value-based decision making, and depression: Excessive Facebook use We used the BFAS (Andreassen et al., 2012) to assess excessive Facebook use. The BFAS consists of six items rated on a 5-point Likert scale (1 = very rarely; 5 = very often). Therefore, when participants’ responses are summed, final scores can range from 6 to 30 points. Each BFAS item assesses a commonly accepted core aspect of addiction: salience (preoccupation), mood modification, tolerance, conflict, withdrawal, and relapse (Griffiths et al., 2014). Reliability and validity of the BFAS have been established (Andreassen et al., 2012), and the internal consistency with our sample was good (Cronbach’s α = .87). BFAS scores were normally distributed and no participant’s score was more than three SDs from the mean. Decision making All participants performed 100 trials of a computerized version of the IGT (Dancy & Ritter, 2017) to assess value-based decision making (Bechara et al., 1994). In this task, participants see four decks of cards displayed on the screen in front of them (A, B, C, and D). On each trial, participants choose a card and receive a specified amount of play money reward for this choice. Interspersed among these rewards are punishments, consisting of play money losses of different amounts. Importantly, two of the decks (A and B) produce high immediate gains ($100) for each choice, but they also provide sizeable punishments – in the long run, these decks take more money than they give. We term these decks, disadvantageous. Two other decks (C and D) produce low immediate gains ($50) for each choice, and they also provide smaller punishments compared to the other decks – in the long run, these decks give more money than they take. We term these decks, advantageous. Before performing the task, participants are told that the goal is to make as much money as possible and to avoid losing as much money as possible. They are also told that they can pick cards from any deck, and switch whenever they want. Participants are also informed that some decks are better than others and that if they want to do well, they should avoid the bad decks and choose cards from the good decks. To note, different versions of the IGT have been used in the literature, with some researchers providing the above hint to stay away from the bad decks and other researchers not providing the hint. Furthermore, some researchers have used play money, whereas others have used real money. We chose to provide the hint and to use play money, as previous research has demonstrated more advantageous card choices in healthy individuals with these conditions (Fernie & Tunney, 2006). As we hypothesized impaired decision making in the IGT by excessive SNS users, this experimental set up would yield the highest likelihood of finding our hypothesized effect. For analysis, we divided the 100-trial experiment into five blocks of 20 trials each and calculated scores for the task (IGT score) in each block by subtracting the total number of cards chosen from the disadvantageous decks (A and B), from the total number of cards chosen from the advantageous decks (C and D). Higher IGT Scores indicate that the participant performed better on the task. Total IGT scores (mean = 15.1, SD = 19.0) were normally distributed and no participant’s score was more than three SDs from the mean. Depression We also assessed participants’ level of depression with the Beck Depression Inventory II (BDI; Beck, Steer, Ball, & Ranieri, 1996). The BDI is one of the most commonly used instruments to assess depression and consists of 21 items rated on a 4-point Likert scale. We administered the BDI because several previous studies reported a positive correlation between depressive symptoms and online social networking, although several other studies have either failed to replicate this finding, or revealed a negative correlation (for review, see Baker & Algorta, 2016). Nevertheless, we assessed depressive symptoms in our sample with the BDI to control for it in our analyses. The reliability of the BDI with our sample was good (Cronbach’s α = .86); however, BDI data were not normally distributed. They were positively skewed (skewness = 1.64, SE = 0.29) and displayed kurtosis (kurtosis = 4.73, SE = 0.56), with two participants more than three SDs away from the mean (mean = 12.4, median = 12.0, SD = 8.8). To address this, we winsorized the two highest and lowest values to equal the third highest and lowest value, respectively (94% winsorization). This resulted in normally distributed data with no outliers (mean = 11.89, median = 12.00, SD = 7.11, skewness = 0.43, SE = 0.29, kurtosis = −0.47, SE = 0.56). This winsorized data set was used for all reported BDI analyses. Procedure After responding to our recruitment flyer, participants were sent an electronic survey to assess their age, gender, and BFAS score. Participants were then invited into our behavioral testing lab. In a closed room with no distractions, participants were provided instructions for the IGT and then performed the task on a computer. After completion of the task, participants filled out the BDI, and were then paid and debriefed. Statistical analyses All analyses were performed using SPSS software (IBM Inc., version 25, Armonk, NY, USA). First, as a manipulation check, we conducted a repeated-measures analysis of variance (ANOVA) with block IGT scores to determine if participants learned to choose the advantageous decks during the 100-trial experiment. Next, we addressed our hypothesized negative correlation between excessive use of Facebook, as measured by BFAS score and performance on the IGT. To do this, we conducted one-tailed, first-order partial correlations between BFAS scores and IGT scores for all 20-trial blocks, while controlling for depression (BDI). We also conducted two-tailed, zero-order correlation analyses between all collected survey measures: BFAS, BDI, age, and gender. All correlations were conducted with continuous variables, except correlations with gender (which is a dichotomous variable), so these correlations were point biserial. All reported significant results survived Bonferroni correction for multiple comparisons. Ethics Study procedures were carried out in accordance with the Declaration of Helsinki and approved by the ethics review committee of a large European university. All participants were informed about the study and all provided informed consent for participation.

Results Participants displayed a wide range of BFAS scores (mean = 15.1, SD = 5.8, range = 6–27). BFAS scores did not correlate with age (r = −.13, p = .14, 95% CI = −0.17/0.29) or gender (r = −.02, p = .43, 95% CI = −0.28/0.22), and age and gender were not correlated with each other (r = −.06, p > .05, 95% CI = −0.33/0.19). BFAS scores did correlate with BDI scores (r = .43, p r = −.13, p > .05, 95% CI = −0.32/0.07) and gender (r = .06, p > .05, 95% CI = 0.10/0.25) were not correlated with BDI. Group performance across the 100-trial IGT, organized into 20-trial blocks, is depicted in Figure 1 (block 1: mean = −3.7, SD = 3.4; block 2: mean = 1.5, SD = 5.9; block 3: mean = 4.5, SD = 7.4; block 4: mean = 6.1, SD = 7.6; block 5: mean = 6.7, SD = 7.8). Repeated-measures ANOVA with block IGT scores revealed that as the experiment progressed, participants choose more advantageous decks than disadvantageous decks [F (4, 280) = 31.9, p 2 = 0.31]. Post-hoc paired t-tests revealed that mean IGT scores for blocks 1 and 2 were significantly different from all other blocks (for all comparisons: t’s > 3.0, p’s p’s > .05). Our significant repeated measures finding with a large effect size demonstrates that, as a group, participants were performing the task as instructed and able to learn from the rewards and punishments they received as a result of their deck choices. Figure 1. Download Figure

Download figure as PowerPoint slide IGT scores [(Decks C + D) – (Decks A + B)] for each block of 20 trials across the 100-trial experiment. As the experiment progressed, participants choose more advantageous decks than disadvantageous decks. Error bars = ±1 SEM Citation: Journal of Behavioral Addictions J Behav Addict 8, 1; 10.1556/2006.7.2018.138 We analyzed the relationship between excessive social media use and IGT performance. This revealed a significant negative, first-order partial correlation between BFAS and IGT score for block 5 (trials 81–100), when controlling for BDI (r = −.31, p 2). A post-hoc power analysis revealed power of 0.85, demonstrating that this study was well-powered to detect the reported medium effect size. The partial correlation between BFAS and IGT score was not significant in any other block: block 1 (trials 1–20; r = −.01, p > .05, 95% CI = −0.24/0.25), block 2 (trials 21–40; r = .23, p > .05, 95% CI = −0.04/0.48), block 3 (trials 41–60; r = .01, p > .05, 95% CI = −0.26/0.24), or block 4 (trials 61–80; r = .03, p > .05, 95% CI = −0.22/0.31). Figure 2. Download Figure

Download figure as PowerPoint slide IGT score for block 5 of the task negatively correlates with BFAS score across participants Citation: Journal of Behavioral Addictions J Behav Addict 8, 1; 10.1556/2006.7.2018.138 To note, there were no significant correlations between BDI and IGT scores across blocks (block 1: r = .21, p > .05, 95% CI = −0.13/0.40; block 2: r = .09, p > .05, 95% CI = −0.12/0.30; block 3: r = −.01, p > .05, 95% CI = −0.17/0.19; block 4: r = .07, p > .05, 95% CI = −0.13/0.25; block 5: r = −.15, p > .05, 95% CI = −0.33/0.05).