Altered Heart Rate Variability During Gameplay in Internet Gaming Disorder: The Impact of Situations During the Game

Internet gaming disorder (IGD) is characterized by a loss of control over gaming and a decline in psychosocial functioning derived from excessive gameplay. We hypothesized that individuals with IGD would show different autonomic nervous system (ANS) responses to the games than those without IGD. In this study, heart rate variability (HRV) was assessed in 21 young males with IGD and 27 healthy controls while playing their favorite Internet game. The subjects could examine the game logs to identify the most and least concentrated periods of the game. The changes in HRV during specific 5-min periods of the game (first, last, and high- and low-attention) were compared between groups via a repeated measures analysis of variance. Significant predictors of HRV patterns during gameplay were determined from stepwise multiple linear regression analyses. Subjects with IGD showed a significant difference from controls in the patterns of vagally mediated HRV, such that they showed significant reductions in high-frequency HRV, particularly during the periods of high attention and the last 5 min, compared with baseline values. A regression analysis showed that the IGD symptom scale score was a significant predictor of this reduction. These results suggest that an altered HRV response to specific gaming situations is related to addictive patterns of gaming and may reflect the diminished executive control of individuals with IGD while playing Internet games

Greater Impairment in Negative Emotion Evaluation Ability in Patients with Paranoid Schizophrenia

To explore whether or not patients with schizophrenia display a more profound impairment of negative emotion processing, we assessed the implicit evaluation of positive and negative emotional stimuli. Twenty patients with schizophrenia (9 paranoid, 11 non-paranoid) and 22 normal controls were instructed to classify emotional pictures according to the intrinsic valence if the pictures were black and white. If the stimuli were color-filtered, participants were instructed to press the positive/negative response key according to the extrinsic valence (assigned valence of color). The error rates of the color-filtered stimuli were used as dependent measures. Normal controls made more errors on trials of the positive pictures when the correct response was the negative response key than when the correct response was the positive response key. The reverse was true on trials of the negative pictures. Patients with schizophrenia, especially paranoid schizophrenia, committed more errors in trials of the positive pictures when the correct response key was the negative response key. However, the reverse was not true on trials of the negative pictures. These findings suggest that patients with paranoid schizophrenia might suffer from an impaired ability to evaluate negative emotions and have a loosening of association within their negative emotional networks

Correction: Population-based dementia prediction model using Korean public health examination data: A cohort study.

[This corrects the article DOI: 10.1371/journal.pone.0211957.]

Population-based dementia prediction model using Korean public health examination data: A cohort study.

The early identification and prevention of dementia is important for reducing its worldwide burden and increasing individuals' quality of life. Although several dementia prediction models have been developed, there remains a need for a practical and precise model targeted to middle-aged and Asian populations. Here, we used national Korean health examination data from adults (331,126 individuals, 40-69 years of age, mean age: 52 years) from 2002-2003 to predict the incidence of dementia after 10 years. We divided the dataset into two cohorts to develop and validate of our prediction model. Cox proportional hazards models were used to construct dementia prediction models for the total group and sex-specific subgroups. Receiver operating characteristics curves, C-statistics, calibration plots, and cumulative hazards were used to validate model performance. Discriminative accuracy as measured by C-statistics was 0.81 in the total group (95% confidence interval (CI) = 0.81 to 0.82), 0.81 in the male subgroup (CI = 0.80 to 0.82), and 0.81 in the female subgroup (CI = 0.80 to 0.82). Significant risk factors for dementia in the total group were age; female sex; underweight; current hypertension; comorbid psychiatric or neurological disorder; past medical history of cardiovascular disease, diabetes mellitus, or hypertension; current smoking; and no exercise. All identified risk factors were statistically significant in the sex-specific subgroups except for low body weight and current hypertension in the female subgroup. These results suggest that public health examination data can be effectively used to predict dementia and facilitate the early identification of dementia within a middle-aged Asian population