The medical profession requires continuous knowledge acquisition, effective communication skills, an appropriate level of empathy, and a personality profile that can support high-quality patient care. (1) The purpose of this study was to research whether there are associations or correlations between personality dimensions, empathy, and the attitudes of medical students regarding the learning of communication skills. (2) We conducted a pilot study with 267 first- and sixth-year medical students from the George Emil Palade University of Medicine, Pharmacy, Sciences, and Technology of Targu Mures as the subjects. The students were evaluated using the DECAS personality inventory, the Romanian communication skills ability scale, and Toronto empathy scale. (3) Our results showed that regarding the level of empathy (p = 0.09) and positive attitudes related to communication skills (p = 0.52), there were no statistically significant differences between first- and sixth-year medical students. On the other hand, in the case of negative attitudes, it was observed that there was a statistical significance (p = 0.0003). It was also observed that there was a positive association between agreeableness and empathy (OR = 6.12, p < 0.0001) and a negative association between emotional stability and empathy (OR = 0.45, p = 0.01). Correlations were also found between positive attitudes related to communication skills with patients and the personality dimensions of conscientiousness (r = 0.21, p = 0.0004) and agreeableness (r = 0.15, p = 0.01), as well as between negative attitudes related to communication skills with patients and the agreeableness dimension (r = −0.23, p = 0.0001) and emotional stability dimension (r = −0.13, p = 0.02). Furthermore, the two proposed models confirmed the influence that personality and empathy have on attitudes towards learning communication skills. (4) The findings of this study show that both the personality structure and the empathy of a student are linked to their attitudes about communication.

Background/Objectives: Emotional stability is a personality trait associated with emotion regulation and adaptation to stress. Low emotional stability has been associated with anxiety, depressive symptoms, and emotional eating, but the mechanisms underlying these relationships among medical students remain unclear. This study examined the association between emotional stability and emotional eating and explored indirect statistical associations involving anxiety and depressive symptoms using exploratory parallel and serial path analyses. Methods: A cross-sectional observational study was conducted among 291 medical students. Emotional stability was assessed using the DECAS Personality Inventory, emotional eating using the DEBQ (Dutch Eating Behavior Questionnaire), anxiety symptoms using the GAD-7 (Generalized Anxiety Disorder-7), and depressive symptoms using the PHQ-9 (Patient Health Questionnaire-9). Spearman correlations and exploratory parallel and serial path analyses were performed using the PROCESS macro for SPSS Statistical Calculator v26 with 5000 bootstrap samples. Results: Emotional stability was negatively correlated with anxiety (ρ = −0.546; p < 0.001), depressive symptoms (ρ = −0.603; p < 0.001), and emotional eating (ρ = −0.383; p < 0.001). Anxiety (ρ = 0.380; p < 0.001) and depressive symptoms (ρ = 0.454; p < 0.001) were positively correlated with emotional eating. Only depressive symptoms showed a significant indirect statistical association linking emotional stability and emotional eating (B = −0.0139; 95% bootstrap CI: −0.0223 to −0.0068). In the serial path analysis, only the model specifying anxiety as the first intermediate variable showed a significant indirect effect (B = −0.0065; 95% bootstrap CI: −0.0109 to −0.0032). Conclusions: Depressive symptoms showed the strongest indirect association linking emotional stability and emotional eating in medical students. These findings should be interpreted as being consistent with the proposed statistical model and do not establish temporal or causal relationships.

Background/Objectives: Sleep health contributes to glucose homeostasis and metabolic regulation. We explored associations between subjective sleep characteristics, glycemic control, and diabetes-related clinical factors in adults with type 1 diabetes mellitus (T1DM). Methods: This exploratory cross-sectional, pilot investigation included 30 adults with T1DM at the Emergency Clinical County Hospital of Târgu Mureș between April 2025 and March 2026. We analyzed subjective sleep parameters, 90- and 14-day continuous glucose monitoring (CGM) data, clinical and laboratory parameters, diabetes distress and depression symptom scores. Results: Mean age was 39.0 ± 12.87 years, and 56.7% were male. Mean HbA1c was 7.28 ± 1.24%, 90-day time in range (TIR) was 61.47 ± 17.90%, and the coefficient of variation (CV) was 35.91 ± 6.71%. Mean nocturnal sleep duration was 7.15 ± 0.89 h, which was negatively correlated with mean afternoon nap duration on both weekdays (Pearson’s r = −0.492, 95% CI −0.739 to −0.124, n = 30, p = 0.009) and weekends (Pearson’s r = −0.481, 95% CI −0.736 to −0.119, n = 30, p = 0.012). Moreover, weekend sleep duration (p = 0.032, r = −0.401) was negatively correlated only with TIR assessed over 90 days. Social jetlag, self-reported sleep quality, the number of self-reported nocturnal awakenings, altered sleep duration on weekdays, and daytime napping were not significantly correlated with HbA1c or CGM-derived metrics (all p > 0.05). Mean subjective sleep quality score was 3.22 ± 0.87 on a five-point Likert scale. Restful sleep was reported only on half of the monitored nights; 20% had high risk for obstructive sleep apnea (OSA). Physical activity was positively correlated with TIR assessed over both 90 days (Pearson’s r = 0.446, 95% CI 0.144 to 0.606, n = 30, p = 0.025) and 14 days (Pearson’s r = 0.464, 95% CI 0.345 to 0.704, n = 30 p = 0.037). Conclusions: Among the assessed sleep characteristics, only weekend sleep duration was significantly associated with historical 90-day TIR, whereas physical activity was positively associated with TIR over both monitoring periods. Given the exploratory nature and small sample size of this study, larger longitudinal studies are needed to clarify the relationships between sleep health and glycemic control in adults with type 1 diabetes.