Predictors of problematic smartphone use among university students.

Predictors of problematic smartphone use have been found mainly in studies on elementary and high school students. Few studies have focused on predictors related to social network and messaging apps or smartphone model. Thus, the objective of our study was to identify predictors of problematic smartphone use related to demographic characteristics, loneliness, social app use, and smartphone model among university students. This cross-sectional study involved 257 Brazilian university students who answered a smartphone addiction scale, a questionnaire about smartphone usage patterns, and the Brazilian version of the UCLA-R loneliness scale. Women, iPhone owners, and users of Instagram and Snapchat had significantly higher smartphone addiction scores. We found correlations between scores for the Brazilian version of smartphone addiction scale and the importance attributed to WhatsApp, Facebook, Instagram, and Snapchat, and the Brazilian version of the UCLA-R loneliness scale. Our hierarchical regression model predicted 32.2% of the scores of the Brazilian version of the smartphone addiction scale, with the greatest increase in predictive capability by the step that added smartphone social app importance, followed by the step that added loneliness. Adding the smartphone model produced the smallest increase in predictive capability. The theoretical and practical implications of these results are discussed.

Predictors of problematic smartphone use among university students

Abstract Predictors of problematic smartphone use have been found mainly in studies on elementary and high school students. Few studies have focused on predictors related to social network and messaging apps or smartphone model. Thus, the objective of our study was to identify predictors of problematic smartphone use related to demographic characteristics, loneliness, social app use, and smartphone model among university students. This cross-sectional study involved 257 Brazilian university students who answered a smartphone addiction scale, a questionnaire about smartphone usage patterns, and the Brazilian version of the UCLA-R loneliness scale. Women, iPhone owners, and users of Instagram and Snapchat had significantly higher smartphone addiction scores. We found correlations between scores for the Brazilian version of smartphone addiction scale and the importance attributed to WhatsApp, Facebook, Instagram, and Snapchat, and the Brazilian version of the UCLA-R loneliness scale. Our hierarchical regression model predicted 32.2% of the scores of the Brazilian version of the smartphone addiction scale, with the greatest increase in predictive capability by the step that added smartphone social app importance, followed by the step that added loneliness. Adding the smartphone model produced the smallest increase in predictive capability. The theoretical and practical implications of these results are discussed.

Hemiface Differences in Visual Exploration Patterns When Judging the Authenticity of Facial Expressions.

Past studies have found asymmetry biases in human emotion recognition. The left side bias refers to preferential looking at the left-hemiface when actively exploring face images. However, these studies have been mainly conducted with static and frontally oriented stimuli, whereas real-life emotion recognition takes place on dynamic faces viewed from different angles. The aim of this study was to assess the judgment of genuine vs. masked expressions in dynamic movie clips of faces rotated to the right or left side. Forty-eight participants judged the expressions on faces displaying genuine or masked happy, sad, and fearful emotions. The head of the actor was either rotated to the left by a 45° angle, thus showing the left side of the face (standard orientation), or inverted, with the same face shown from the right side perspective. The eye movements were registered by the eye tracker and the data were analyzed for the inverse efficiency score (IES), the number of fixations, gaze time on the whole face and in the regions of interest. Results showed shorter IESs and gaze times for happy compared to sad and fearful emotions, but no difference was found for these variables between sad and fearful emotions. The left side preference was evident from comparisons of the number of fixations. Standard stimuli received a higher number of fixations than inverted ones. However, gaze time was long on inverted compared to standard faces. Number of fixations on exposed hemiface interacted with the emotions decreasing from happy to sad and fearful. An opposite pattern was found for the occluded hemiface. These results suggest a change in fixation patterns in the rotated faces that may be beneficial for the judgments of expressions. Furthermore, this study replicated the effects of the judgment of genuine and masked emotions using dynamic faces.