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- Author or Editor: Feng Jing x
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Abstract
Background and aims
The Pavlovian-to-instrumental transfer (PIT) effect is a phenomenon that Pavlovian conditioned cues that could influence one's instrumental behavior. In several substance and behavioral addictions, such as tobacco use disorder and gambling disorder, addiction-related cues could promote independently trained instrumental drug-seeking/drug-taking behaviors, indicating a specific PIT effect. However, it is unclear whether Internet gaming disorder (IGD) would show a similar change in PIT effects as other addictions. The study aimed to explore the specific PIT effects in IGD.
Methods
We administrated a PIT task to individuals with IGD (n = 40) and matched health controls (HCs, n = 50), and compared the magnitude of specific PIT effects between the two groups. The severity of the IGD symptoms was assessed by the Chinese version 9-item Internet Gaming Disorder Scale (IGDS) and the Internet Addiction Test (IAT).
Results
We found that: (1) related to the HCs group, the IGD group showed enhanced specific PITgame effects, where gaming-related cues lead to an increased choice rate of gaming-related responses; (2) in the IGD group, the magnitude of specific PITgame effects were positively correlated with IAT scores (rho = 0.39, p = 0.014).
Discussion and Conclusions
Individuals with IGD showed enhanced specific PIT effects related to HCs, which were associated with the severity of addictive symptoms. Our results highlighted the incentive salience of gaming-related cues in IGD.
Abstract
Background and aims
Problematic online social networking use is prevalent among adolescents, but consensus about the instruments and their optimal cut-off points is lacking. This study derived an optimal cut-off point for the validated Online Social Networking Addiction (OSNA) scale to identify probable OSNA cases among Chinese adolescents.
Methods
A survey recruited 4,951 adolescent online social networking users. Latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses were applied to the validated 8-item OSNA scale to determine its optimal cut-off point.
Results
The 3-class model was selected by multiple criteria, and validated in a randomly split-half subsample. Accordingly, participants were categorized into the low risk (36.4%), average risk (50.4%), and high risk (13.2%) groups. The highest risk group was regarded as “cases” and the rest as “non-cases”, serving as the reference standard in ROC analysis, which identified an optimal cut-off point of 23 (sensitivity: 97.2%, specificity: 95.2%). The cut-off point was used to classify participants into positive (probable case: 17:0%) and negative groups according to their OSNA scores. The positive group (probable cases) reported significantly longer duration and higher intensity of online social networking use, and higher prevalence of Internet addiction than the negative group.
Conclusions
The classification strategy and results are potentially useful for future research that measure problematic online social networking use and its impact on health among adolescents. The approach can facilitate research that requires cut-off points of screening tools but gold standards are unavailable.
