Objective We aimed to find the optimal cut-off scores for screening of odor detection threshold, odor discrimination, and odor identification tests for detection of mild cognitive impairment (MCI) and dementia in Korean elderly.Methods A total of 195 elderly people were divided into three groups: the normal cognition (NC), MCI, and dementia groups. All participants underwent neurocognitive and olfactory function tests. We used k-means cluster analysis and receiver operating characteristic (ROC) analysis to identify the most appropriate cut-off value.Results To distinguish the MCI from NC groups, odor identification [area under the curve (AUC)=0.670, p<0.007] with a cut-off point of 7 showed greater validity for screening (sensitivity/specificity=0.462/0.837) than did other olfactory function tests. To distinguish the MCI and dementia from NC as well, odor identification (AUC=0.817, p=0.002) with a cut-off point of 7 showed the highest validity for screening (0.785/0.654). To distinguish MCI from AD, an odor detection threshold (AUC=0.722, p=0.001) with a cut-off point of 2 showed the highest validity for screening (0.785/0.654).Conclusion Olfactory function tests may be a useful screening tool for cognitive decline before clinical symptoms of dementia have completely developed. This tool can be used as a supplementary tool to enhance the sensitivity of traditional cognitive tests to screen for dementia.

Introduction: Previous studies on internet gaming disorder (IGD) have reported an association between personality traits and impulsive or problematic use of the internet or internet games, but the results obtained were inconsistent. Our study’s hypothesis was that personality traits are associated with the individual’s choice to play internet games, and psychological status of the individual is associated with seeking treatment for addictive behavior at a hospital. Method: In the current study, individuals who reported excessive internet gaming and visited the hospital for treatment were enrolled and defined as the problematic internet gaming group; through advertisement, additional 138 individuals who were frequent gamers and 139 who were infrequent gamers were recruited. In a multiple logistic regression analysis of all participants’ data, a discrete set of hierarchical variables, with gaming preference (frequent gamers + problematic gamers) or problematic internet gaming as the dependent variable, was added to the demographic factors for model 1, personality traits for model 2, and psychological state for model 3. Results: Temperament was a potential factor associated with internet gaming preference. Additionally, model 2, which comprised both demographic factors and personality traits, was a significant factor to enhance the predictability of internet gaming preference with maximum accuracy of 96.7%. Of the three models in the current study, model 2 and model 3 with combined model 2 and patient’s psychological status were associated with problematic internet gaming. Discussion: The current study indicated that personality traits were potential factors associated with the individual’s preference for gaming. In addition, abnormal psychological status, especially, depressive mood and attention deficit, may lead individuals with problematic internet gaming to seek treatment at the hospital.