Personality testing in dogs has become a controversial topic in the dog community in the last few years. These assessments have been used among owners, shelters, working dog trainers, breeders, and researchers to identify patterns of behavior that may lead to insight about a dog’s personality. Due to inconsistencies in terminology and validity testing, these personality tests have lost a notable amount of credibility. Focusing on questionnaire and behavioral based testing, this literature review aims to evaluate the significance of personality testing within the dog community. Each assessment will be analyzed for measurements and validity, as well as potential drawbacks and benefits. Four prominent personality assessments will be discussed in depth. These assessments include C-BARQ, DPQ, SAFER, and VIDOPET. I advocate for a mixed assessment model approach and highlight the benefits of expanding personality testing into genetic research.

A dynamical approach is used to avoid isolating systems and instead view systems as interacting together. The current study applied a dynamical approach to heart rate variability and personality. There were two main research questions that this study sought to answer with a dynamical analysis of heart rate variability and personality: “Can we listen to a heartbeat and draw connections to behavior and personality?” and “Is dynamical analysis more effective than traditional analysis at finding correlations between heart rate variability and personality?” To answer these questions a dynamical analysis of heart rate variability was conducted (detrended fluctuation analysis; DFA) along with traditional analysis (standard deviations of NN intervals, SDNN, and root mean squared of successive deviations, RMSSD) and then correlations between heart rate variability measures and personality traits from the Big Five Inventory, Positive and Negative Affect schedule, and State-Trait Anxiety Inventory were examined. Data for this study came from the Rapid Automatic & Adaptive Model for Performance Prediction (RAAMP2) Dataset that was part of The Multimodal Objective Sensing to Assess Individuals with Context (MOSAIC) project. There were no statistically significant correlations between heart rate variability and personality. However, there were notable correlations between extraversion and SDNN and RMSSD and between positive affect and SDNN and RMSSD. We found that SDNN and RMSSD were more closely correlated to each other compared to DFA to either measure. This suggests that DFA can provide information that SDNN and RMSSD do not. Future research can explore dynamic analysis of heart rate variability and other nested systems.

With the emergence of programs that focus on socio-emotional regulation through online intervention, our focus is to move beyond the current literature to look at how personality might help to identify those in need of such an intervention, while also assessing if personality may moderate the overall efficacy of the treatment in middle-aged adults. In particular, our focus is on the established improvements that similar programs have shown to have on positive affect (PA), negative affect (NA), and emotional reactivity (ER). Through a randomized controlled trial, this research examines whether an online social intelligence training (SIT) program improves socio-emotional regulation compared to an attention-control (AC) condition. During the pre- and post-test phases of the study, participants (N = 230) completed a questionnaire, along with online surveys for 14-days that included measures of social connectedness, emotional awareness, and perspective-taking. Our analysis, while lacking significant findings in the way of PA and NA, shed light on how SIT programs can improve ER, while personality can simultaneously predict baseline levels of ER and moderate the efficacy of the program.