Background/Objectives: Alcohol consumption in young persons is a growing phenomenon, with significant implications for physical and mental health. This behavior exposes adolescents and young adults to multiple risks, such as affecting cognitive functions, the development of emotional disorders, and social integration difficulties. The present study sets out to investigate the way alcohol consumption influences emotionality in young people, focusing on the emotional changes (anxiety and irritability), cognitive changes (attention deficit and memory disorder), and behavioral changes (impulsivity and aggressiveness). Methods: The methodology involved collecting quantitative data from a sample of young people who consume and do not consume alcohol, using standardized questionnaires and advanced statistical software (processed in MATLAB version 9.11_R2021b). We analyzed variables such as consumption frequency and intensity, affective scores, and demographic factors to highlight the correlations between consumption level and the intensity of affective modifications. Results: The results revealed a significant association between alcohol consumption and the rise in anxiety and depression symptoms or a tendency toward impulsive behaviors. Additionally, we observed that psychosocial factors, including group pressure, family climate, and stressful contexts, can exacerbate emotional vulnerability. Conclusions: This study suggests the need for early psychological interventions and prevention programs to approach emotional and cognitive dimensions and the social influences associated with consumption. Implementing support and counseling strategies, as well as education and awareness campaigns, can contribute to reducing risky behavior and promoting young people’s harmonious development.

Artificial Intelligence (AI) has increasingly contributed to advancements in pharmaceutical practice, particularly by enhancing the pharmacist–patient relationship and improving medication adherence. This quantitative, descriptive, cross-sectional study investigated Eastern Romanian pharmacists’ perception of AI-based applications as effective optimization tools, correlating it with disruptive communication factors. An anonymous and online questionnaire was distributed to community pharmacists, examining sociodemographic characteristics, awareness of disruptive factors, and the perceived usefulness of AI. The sample included 437 respondents: pharmacists (55.6%), mostly female (83.8%), and aged between 25 and 44 (52.6%). Data analysis involved descriptive statistics and independent t-tests. The statistical analysis revealed a significantly positive perception (p < 0.001) of AI on pharmacist–patient communication. Respondents viewed AI as a valuable tool for reducing medication errors and optimizing counseling time, though they maintain a strong emphasis on genuine human interaction. Significant correlations were found between disruptive factors—such as noise and high patient volume—and the quality of communication. Participants also expressed an increased interest in applications like automatic prescription scheduling and the use of chatbots. The study concludes that a balanced implementation of AI technologies is necessary, one that runs parallel with the continuous development of pharmacists’ communication skills. Future research should focus on validating AI’s impact on clinical outcomes and establishing clear ethical guidelines regarding the use of patient data.

Background and Objectives: This study investigated whether the interaction between heavy alcohol use and depression amplifies the risk of hyperglycemia in psychiatric patients. Materials and Methods: We conducted a cross-sectional study on 172 patients (aged 18–65) hospitalized at the “Elisabeta Doamna” Clinical Psychiatric Hospital, Romania. The data included fasting blood glucose, gamma-glutamyl transferase (GGT), Beck Depression Inventory (BDI), and Alcohol Use Disorders Identification Test (AUDIT) scores. Results: Moderate positive correlations were observed between depression scores and blood glucose (r = 0.44) and between alcohol consumption and blood glucose (r = 0.43). The interaction term (BDI × AUDIT) was statistically significant in multiple regression (β = 0.012, p = 0.001), and the model explained 39.1% of glucose variability. Logistic regression analysis revealed that neither high alcohol consumption (OR = 1.38, p = 0.441) nor severe depression alone (OR = 1.30, p = 0.582) were significantly associated with hyperglycemia. However, their interaction demonstrated a strong and statistically significant effect (OR = 19.3, 95% CI: 3.22–115.81, p = 0.001). The prevalence of hyperglycemia reached 95.8% in patients with both risk factors. Conclusions: The combined presence of high alcohol consumption and severe depression significantly increases the risk of hyperglycemia. These findings highlight the importance of integrated screening and interventions in psychiatric settings.

Background/Objectives: Cognitive deficiency associated with chronic alcohol consumption in older people remains an under-investigated public health issue in Romania, particularly concerning rural–urban disparities and the impact of reversible hepatic dysfunction on cognitive performance. To evaluate cognitive function at hospital admission and discharge using the Mini-Mental State Examination (MMSE); to identify rural–urban disparities; and to analyze the relationship between hepatic markers and MMSE scores in older people with chronic alcohol consumption. Methods: This retrospective, single-center observational study was conducted on 152 patients aged ≥55 years, hospitalized between January 2021 and December 2023 at the “Elisabeta Doamna” Psychiatric Hospital, Galați. Demographic variables, MMSE scores (at admission and discharge), and hepatic parameters (AST, ALT, GGT, total bilirubin, and ammonia) were collected. Statistical analysis included descriptive statistics, chi-square tests for categorical variables, paired t-tests or ANOVA for MMSE scores, and Pearson correlations between MMSE and hepatic markers (α = 0.05). Results: At admission, 94% of patients had an MMSE score < 24. The mean MMSE score increased from 23.4 ± 4.1 to 25.0 ± 3.7 at discharge (Δ = +1.6; p < 0.001). Patients from rural areas (63.8% of the sample) had significantly lower MMSE scores at admission compared to urban patients (22.6 ± 3.9 vs. 24.8 ± 4.2; p = 0.02). However, no statistically significant difference was observed between rural and urban patients regarding cognitive improvement during hospitalization (p = 0.88), indicating that the initial gap persisted at discharge. GGT levels were inversely correlated with MMSE scores (r = −0.41; p < 0.001), suggesting a contribution of hepatic dysfunction to cognitive decline. Conclusions: Alcohol-related cognitive impairment is highly prevalent among older patients hospitalized for withdrawal, with partial reversibility observed through inpatient management. The observed rural disparities and the association between hepatic dysfunction and cognitive performance highlight the need of concurrent MMSE and hepatic screening, with prioritized interventions in rural settings. Prospective, multicenter studies are warranted to validate these findings and to identify additional prognostic biomarkers.