Examining the Relationship between Emotion Perception and Bullying: A Proposal

Bullying and aggressive behaviors have adverse effects on many children. Violent behavior among children occurs most commonly in the school setting and may lead to negative emotional outcomes later in life (Kub & Feldman, 2015). According to a study conducted by Baroncelli et al. (2014), boys who have been found to be high in aggression have a difficult time perceiving relevant social cues such as fear and anger. However, boys were prone to frequently identify happiness and fear in faces when a different emotion was expressed. For girls, Baroncelli and colleagues did not find any significant relationships. The purpose of this paper was to conceptually replicate the research of Baroncelli et al. (2014), which was originally done in Italy. For my study, I plan on using children in the United States to determine if the ability to perceive emotion predicts aggression. Participants will be recruited from Hyde Park Middle School in Las Vegas, Nevada and will consist of approximately 1,100 male and female students. The Aggression Scale (Orpinas & Frankowski, 2001) and the Diagnostic Analysis of Nonverbal Accuracy –2 (DANVA2; Nowicki, 2013; Nowicki & Duke, 1994) will be completed online and will take approximately 30 minutes to complete. In order to determine if there is a relationship between aggression and emotion perception, I will calculate the correlation between the DANVA and the Aggression Scale

Which Data Checking Method is More Accurate?

Researchers use multiple methods for data checking. Each method can help identify and fix errors that were introduced during the data entry process. Fixing the errors that were introduced during the data entry process increases the accuracy of the research results. Accuracy is impor­tant because if a researcher publishes inaccurate results other researchers would not be able to replicate those results and draw the same conclusions. The purpose of this study is to compare the accuracy of four different data checking methods: double entry with one person, double en­try with two people, visual checking, and solo read aloud. So far, previous research has shown that double entry is more accurate than visual checking (Barchard & Pace, 2011) and partner read aloud (Kawado, Hinotsu, Matsuyama, Yamaguchi, Hashimoto, & Ohashi, 2003). Although there has not been many studies done on the comparison of these four methods and only one study has used solo read aloud, double entry has been shown to produce the highest quality data. I therefore hypothesize that the two double entry methods will have the highest accuracy

Relationship between perceived and actual quality of data checking

Data quality is critical to reaching correct research conclusions. Researchers attempt to ensure that they have accurate data by checking the data after it has been entered. Previous research has demonstrated that some methods of data checking are better than others, but not all researchers use the best methods. Perhaps researchers continue to use less optimal data checking methods because they mistakenly believe that they are highly accurate. The purpose of this study was to examine the relationship between perceived data quality and actual data quality. A total of 29 participants completed this study. Participants checked that letters and numbers had been entered correctly into the computer using one of three randomly assigned data checking methods. Afterwards, they rated the quality of their data checking method. The sample correlations between perceived and actual data quality were small to moderate and confidence intervals for the population correlations did not include high values. We conclude that the relationship between actual and perceived data quality is not high

Emotional Resilience Emerges as Novel Aspect of Meta-Mood Experience: A Confirmatory Factor Analysis Accounting for Data Censoring

Meta-mood experience refers to the thoughts and feelings that serve to monitor, evaluate, and at times change mood. The Trait Meta-Mood Scale (TMMS) was designed to gauge meta-mood experience along three factors: Attention, Clarity, and Repair. Previous factor analyses have verified this three-factor structure. However, one study by Palmer and colleagues found strong support for a four-factor structure. In light of this discrepancy, the present study aimed to replicate Palmer and colleagues’ study in a new sample, comparing the models they used to determine which is best-fitting. We also aimed to correct the effect of data point censoring when estimating the factor models. Data point censoring occurs when researchers have only partial information about the value of a variable. Because no previous research has explored the TMMS while accounting for potential censoring, we aimed to test this idea in the current sample. A total of 202 undergraduates completed the TMMS during an online study. To compare the models, we relied on Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC). Results revealed that the four-factor model fit the data better than the three- and one-factor models tested. In the four-factor model, the first three factors corresponded to the previous Attention, Clarity, and Repair factors. We named the fourth factor Emotional Resilience because the items loading on this factor suggested resistance to negative emotional experiences. We suggest TMMS users calculate scale scores based on all four of these factors to provide a more detailed description of meta-mood experience

Examining the construct validity of the metaphors test

Emotional Intelligence is a multi-faceted construct. Existing tests do a good job of measuring some aspects of Emotional Intelligence. The Metaphors Test (Barchard, 2004) was designed to measure the ability to decipher the emotional content of ambiguous sentences. This test may measure a new facet of Emotional Intelligence. The purpose of this research was to examine the construct validity of the Metaphors Test as a measure of Emotional Intelligence. Using a sample of 281 undergraduates, the Metaphors Test was correlated with the four branches of the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT; Mayer, Salovey, & Caruso, 2004): Perceiving Emotions, Using Emotions to Facilitate Thought, Understanding Emotions, and Managing Emotions. The four correlations were all moderate, positive, and statistically significant. These results provide promising evidence of construct validity. Future research should select the items with the highest correlations with the MSCEIT. This will enable researchers to create a revised, shorter version of the Metaphors Test with higher construct validity

Climate-Friendly Purchasing: An Exploratory Factor Analysis

Climate change includes long-term shifts in global temperatures, shrinking ice caps, and rising sea levels. Human activities are the main cause of such changes (Lynas et al., 2021) Individuals can mitigate the effects of climate change through their purchasing choices (Jakučionytė-Skodienė et al., 2022). To understand the strategies people use, we examined the factor structure of the Climate-Friendly Purchasing Choices domain from the Climate Change Action Inventory (CCAI; Barchard et al., 2022)

Personal Actions: The Correlation Between Water and Energy Conservation

Water and energy conservation are growing concerns around the world. Energy conservation policies create both energy and water savings (Gu et al., 2016). Conversely, water conservation impacts energy usage (Sokolow et al., 2016). Heating water in the home accounts for 20% of the home’s energy use (Chini et al., 2016). Our study examines the relationship between water conservation and energy conservation

Initial examination of the mental health disorders: screening instrument for athletes

IntroductionThere is a need to psychometrically develop assessment instruments capable of screening mental health disorders in athlete populations. The current study was conducted to determine reliability, validity and clinical utility of the Mental Health Disorders Screening Instrument for Athletes (MHDSIA).Methods and results:259 collegiate athletes completed the MHDSIA. Factor analysis determined a single factor with good internal consistency, and this factor was positively correlated with an established measure of psychiatric symptomology (Symptom Checklist 90-R), demonstrating its concurrent validity. An optimum clinical cutoff score (i.e., 32) was determined using Receiver Operating Characteristic (ROC) analyses to assist appropriate mental health referrals.DiscussionResults suggest the MHSIA is a reliable, valid, and relatively quick and easy to interpret screen for the broad spectrum of mental health disorders in collegiate athletes. As expected, NCAA athletes reported lower MHDSIA scores than club and intramural athletes, while males reported similar severity scores as females

The Climate Change Hope Scale: Does the Three-Factor Model Fit an Adult Sample?

The Climate Change Hope Scale (CCHS; Li & Monroe, 2017) adapted Synder et al.\u27s (1991) Hope Scale to focus specifically on climate change. In an adolescent sample, the CCHS has three factors: Personal-sphere willpower and waypower, Collective-sphere willpower and waypower, and Lack of willpower and waypower. Our research tests if Li and Monroe\u27s (2017) three-factor model fits the data from an adult sample

Measuring the Perceived Social Intelligence of Robots

Robotic social intelligence is increasingly important. However, measures of human social intelligence omit basic skills, and robot-specific scales do not focus on social intelligence. We combined human robot interaction concepts of beliefs, desires, and intentions with psychology concepts of behaviors, cognitions, and emotions to create 20 Perceived Social Intelligence (PSI) Scales to comprehensively measure perceptions of robots with a wide range of embodiments and behaviors. Participants rated humanoid and non-humanoid robots interacting with people in five videos. Each scale had one factor and high internal consistency, indicating each measures a coherent construct. Scales capturing perceived social information processing skills (appearing to recognize, adapt to, and predict behaviors, cognitions, and emotions) and scales capturing perceived skills for identifying people (appearing to identify humans, individuals, and groups) correlated strongly with social competence and constituted the Mind and Behavior factors. Social presentation scales (appearing friendly, caring, helpful, trustworthy, and not rude, conceited, or hostile) relate more to Social Response to Robots Scales and Godspeed Indices, form a separate factor, and predict positive feelings about robots and wanting social interaction with them. For a comprehensive measure, researchers can use all PSI 20 scales for free. Alternatively, they can select the most relevant scales for their projects