The purpose of this study is to determine the prevalence of behavioral addictions in undergraduate psychology students and create a risk profile for behavioral addictions based on these variables. A total of 329 (251 females and 78 males) psychology students from two different public universities were included in the study. Participants completed a socio-demographic data form, Exercise Dependence Scale-21, Internet Addiction Test, Compulsive Buying Scale, South Oaks Gambling Screen Test, Yale Food Addiction Scale, and the Symptom Checklist-90-Revised (SCL-90-R). The prevalence of food addiction was 21%, exercise addiction 5.5%, gambling addiction 3.3%, internet addiction 10.3%, and compulsive buying 10.3%. Behavioral addictions varied by demographics: compulsive buying and food addiction were more common in females, while exercise and gambling addictions were higher in males. Internet addiction showed no gender differences. Higher income was linked to increased compulsive buying. Furthermore, phobic anxiety was a predictor for internet addiction and food addiction; depression was a predictor for internet addiction; and paranoid ideation was a predictor for compulsive buying and internet addiction. The results of the current study have enhanced the understanding of the prevalence of behavioral addictions in undergraduate psychology students, as well as the underlying shared and distinct etiological factors for each of the behavioral addictions. These findings underscore the importance of early identification and intervention strategies for at-risk students in clinical settings, informing practitioners about the multifaceted nature of behavioral addictions and their psychological implications.

Objective Methamphetamine use disorder (MUD) is a global health condition that impairs a person’s health which may result in morbidity and mortality. Inflammation is a crucial process playing a vital role in MUD. For this reason, it is necessary to examine biochemical parameters for follow-up and treatment alternatives.Methods We aimed to reveal the relationship between inflammatory response and MUD by evaluating peripheral hemogram parameters, leukocyte count, subtypes, and their ratios to each other, systemic immune inflammation index (SII), monocyte/high-density lipoprotein (HDL) ratio, and human C-reactive protein (CRP) in adult men with MUD. We included 76 adult male participants in the patient group and 70 adult male participants in the control group. We calculated the neutrophil/lymphocyte rate (NLR), monocyte/lymphocyte rate (MLR), platelet/lymphocyte rate (PLR), and basophil/lymphocyte rate (BLR). In addition, we obtained the SII and the monocyte/HDL rate.Results The patients’ leukocyte (p<0.001), platelet (p<0.001), plateletcrit (PCT) (p=0.002), neutrophil (p<0.001), monocyte (p=0.002), CRP (p<0.001), NLR (p=0.001), PLR (p=0.004), MLR (p=0.009), SII (p<0.001) and monocyte/HDL ratio (p<0.001) were higher than the control group. We observed a significant and positive relationship between the daily methamphetamine intake, and methamphetamine use duration (p=0.002), PCT (p=0.044), neutrophil (p=0.021), NLR (p=0.001), PLR (p=0.004), MLR (p=0.029), and SII (p<0.001). Daily methamphetamine intake had a significant and positive effect on SII. A one-unit increase in daily methamphetamine intake elevated SII by 165.53 units.Conclusion The results confirm the presence of peripheral subclinical inflammation and systemic immune inflammation in adult men with MUD.

Objective: Alcohol Use Disorder (AUD) is a significant public health issue associated with serious health risks. This study aims to reveal the relationship between AUD and inflammatory, immunonutritive, and cardiovascular risk markers by evaluating hemogram and biochemistry parameters together in AUD. Method: The data of 54 male patients with AUD and 45 male controls were included in the study. Sociodemographic-clinical data of the participants and Alcohol Use Disorders Identification Test (AUDIT) results were obtained from medical records. Systemic immune inflammation index (SII) was obtained with the platelet x neutrophil/lymphocyte formula; systemic immune response index (SIRI) was obtained with the monocyte x neutrophil/lymphocyte formula, plasma atherogenicity index (AIP) was obtained with the ratio of triglyceride to High-density Lipoprotein (HDL) cholesterol. C-Reactive Protein (CRP) albumin-lymphocyte (CALLY) index was obtained with the albumin x lymphocyte/CRP x 104 formula. Results: Aspartate aminotransferase (AST), Gamma Glutamyl Transferase (GGT) activities, neutrophil, CRP, ferritin, SII, and SIRI levels were significantly higher in those with AUD compared to controls. Laboratory results of those with AUD were consistent with atherogenic dyslipidemia; higher triglyceride and total cholesterol levels and AIP values were found compared to controls. The amount of alcohol consumed was a predictor for high SII, SIRI, and AIP levels. The CALLY index, which evaluates immune function, inflammation, and nutritional status together, was significantly lower in patients compared to controls. The amount of alcohol use and the total AUDIT score were predictors for a low CALLY index. Conclusion: The results of this study support that AUD is a chronic inflammatory psychiatric disorder. We suggest that new inflammatory, immunonutritive, and cardiovascular biomarkers SII, SIRI, AIP, and CALLY index could be promising clinical tools to evaluate the severity, potential complications, and treatment response of AUD.

Objectives: This study aimed to assess serum Galectin-3 (Gal-3) and IL-6 levels, along with other inflammatory markers, in type-1 bipolar disorder (BD) patients and explore their relationship with clinical features, metabolic parameters, and symptom severity. Background: The study included 38 manic, 35 euthymic BD patients, and 40 healthy controls. Sociodemographic data, such as age, gender, alcohol and smoking habits, and body mass index (BMI), were recorded. Methods: The Young Mania Rating Scale (YMRS) and Hamilton Depression Rating Scale (HAM-D) were administered to patients. Biochemical measurements included Gal-3, IL-6, CRP, neutrophil, lymphocyte, platelet counts, and inflammatory indices like NLR, PLR, SII, and SIRI. Results: Gal-3 levels significantly differed among the groups (F = 52.251, p < 0.001), with the highest levels in euthymic patients. IL-6 levels were elevated in both manic and euthymic patients compared to controls (F = 7.379, p = 0.001). Manic patients had significantly higher levels of neutrophils, monocytes, CRP, NLR, PLR, SII, and SIRI. A positive correlation was found between Gal-3 levels, the total number of episodes, and YMRS scores in manic patients. In euthymic patients, Gal-3 levels correlated positively with disease duration and episode count. Conclusions: Elevated Gal-3 levels, particularly in the euthymic phase, may serve as a biomarker for BD and indicate ongoing inflammation. These findings suggest Gal-3 could help identify BD and differentiate the euthymic phase.

Objective: This study aimed to evaluate the differences between Alzheimer's disease (AD) patients and controls in biochemistry and peripheral hemogram parameters neutrophil, lymphocyte, monocyte, platelet, and C-reactive protein (CRP) levels, lipid profile, inflammatory burden index (IBI), and hemoglobin, albumin, lymphocyte, and platelet (HALP) score and the relationship between inflammatory and immunonutritive biomarkers and cognitive impairment in patients. Method: Data from 79 patients with AD and 42 controls were included in the study. Medical data of the participants were obtained from hospital records. IBI was obtained by using the following formula: CRP × neutrophil/lymphocyte. HALP score was calculated as (hemoglobin (g/L) × albumin (g/L) × lymphocytes (/L))/platelets (/L). Results: Neutrophil count (p=0.003, effect size=0.60), CRP level (p<0.001, effect size=0.87), and IBI (p<0.001, effect size=0.93) were significantly higher in AD patients compared to the control group; hemoglobin (p<0.001, effect size=1.03), lymphocyte count (p<0.001, effect size=0.78), albumin level (p<0.001, effect size=1.31), and HALP score (p<0.001, effect size=0.85) were lower. According to the Standardized Mini Mental Test (SMMT) score, neutrophil count (p=0.001), CRP (p<0.001), and IBI (p<0.001) were significantly higher and lymphocyte count (p=0.001) and HALP score (p<0.001) were lower in the group with severe cognitive impairment. Albumin levels were highest in the group with mild cognitive impairment. In the patient group, there was a moderately significant negative relationship between SMMT score and age (p<0.001, r=-0.437), neutrophil count (p=0.033, r=-0.240), CRP (p<0.001, r=-0.451), and IBI (p<0.001, r=-0.538). Lymphocyte count (p<0.001, r=0.412), high-density lipoprotein (HDL) (p=0.049, r=0.223), albumin levels (p=0.001, r=0.357), and HALP score (p<0.001, r=0.486) were moderately positively associated with SMMT score. Age (β=-0.437, p<0.001), HALP score (β=0.403, p<0.001), and IBI (β=-0.322, p=0.004) were found to be predictors for the severity of cognitive impairment. Conclusion: Our results revealed that inflammation and immunonutritive status play an important role in the pathogenesis of AD. Novel inflammatory and immunonutritive biomarkers, and IBI and HALP score may be promising clinical tools that may pave the way for more personalized treatment strategies and interventions for patients.