Category: Nevin Manimala

Psychiatr Danub. 2025 Sep;37(Suppl 1):300-304.

ABSTRACT

BACKGROUND: Adolescents and young adults present elevated suicide risk, which remains a major public health concern. This study aims to characterize the clinical and psychosocial features of adolescents and young adults referred for psychiatric consultation after a suicide attempt.

SUBJECTS AND METHODS: We conducted a retrospective observational study at the University Hospital of Perugia, Italy, analyzing 72 patients aged 14-35 who received their first psychiatric evaluation during medical hospitalization. Patients were divided into two groups: those referred after a suicide attempt (SA group, n=36) and those referred for other psychiatric concerns (non-SA group, n=36). Data were extracted from structured consultation reports and included sociodemographic, clinical, and psychopathological variables. Bivariate analyses compared the two groups using appropriate statistical tests.

RESULTS: Compared to the non-SA group, the SA group had significantly higher rates of unemployment, positive psychiatric family history, previous suicide attempts, insomnia prior to admission, anxiety symptoms with both psychic and somatic features, personality disorders, and mood stabilizer use. SA patients also showed lower cooperativeness during interviews and were more likely to be assessed with suicidal ideation. More than one third of SA patients were assessed as euthymic post-attempt.

CONCLUSIONS: Key clinical markers of suicide risk in youths may include unemployment, family psychiatric history, insomnia, anxiety with somatic and psychic features, and personality disorders. The clinical profile of suicide attempters suggests a possible contribution of bipolar spectrum diathesis and affective dysregulation. Early, multidimensional risk assessment and integrated intervention strategies in liaison psychiatry are essential to improve detection and prevention of suicidality in youth.

PMID:40982928

Psychiatr Danub. 2025 Sep;37(Suppl 1):284-287.

ABSTRACT

BACKGROUND: Schizophrenia spectrum disorders (SSD) are linked to a higher risk of suicidality, especially among young adults. Despite progress in psychiatric treatments, suicidality remains a leading cause of early death in this group. Symptoms like depression and anxiety are increasingly seen as major contributors to this risk. This study aims to explore clinical risk factors for suicidality in young males inpatients diagnosed with SSD, focusing on the roles of depression, anxiety, and previous suicidal behavior.

METHODS: This cross-sectional study was conducted at the Psychiatric Hospital no. 1 named after N.A. Alexeev of the Department of Health of Moscow, involving 40 male inpatients aged 18-35 years. Participants were divided into two groups: those with suicidal behavior (n=20) and those without (n=20). Psychometric assessments included the Columbia Suicide Severity Rating Scale (C-SSRS), Calgary Depression Scale for Schizophrenia (CDSS), Positive and Negative Syndrome Scale (PANSS), and Personal and Social Performance scale (PSP). Descriptive statistics, correlation analysis, regression analysis, and Student’s t-tests were used.

RESULTS: The group with suicidal behavior had significantly higher scores on the C-SSRS and CDSS, as well as on the PANSS anxiety/depression subscale, compared to the control group. Regression analysis indicated that depression and anxiety accounted for 74% of the variance in suicidality scores. No significant differences in social functioning (PSP) were found between the groups. A history of suicide attempts was not a significant predictor in this sample.

CONCLUSION: Depression and anxiety are significant predictors of suicidality in young males with SSD. Historical suicide attempts showed no significant effect in this sample. The findings underscore the importance of regular screening and timely intervention to lower suicide risk in young adults with SSD.

PMID:40982925

Psychiatr Danub. 2025 Sep;37(Suppl 1):278-283.

ABSTRACT

BACKGROUND: The degree of cognitive impairment and verbal fluency are more important predictors of a patient’s social rehabilitation than the severity of negative or positive symptoms. At the same time, researchers have confirmed and rejected linkages between linguistic functioning and certain cognitive functions in various studies. In several cases these correlations were observed, but did not reach any statistical significance. The aim of this study was to investigate and understand the effects of cognitive decline and impaired fluency on the social functioning of patients with schizophrenia, using a set of experimental psychological techniques on a homogeneous group of patients.

METHODS: The study involved 30 patients with paranoid schizophrenia. The average age of the patients was around 22 years. All patients received cariprazine in doses of 1.5, 3.0, and 4.5 mg per day. Assessment was performed at baseline and after 8 months using a battery of neurocognitive tests, verbal fluency tests, social functioning scales, PANSS scale and adverse effect scales.

RESULTS: Assessment of higher cognitive functions through verbal fluency may provide a new approach to assessing social functioning. Since social engagement and social involvement usually require considerable effort, the ability of verbal fluency tests may help assess social functioning in a time-constrained clinical setting by both psychologists and psychiatrists, without additional training in clinical psychology. Subsequently, the impact of both antipsychotic treatment and neurocognitive training in improving social outcomes in patients with schizophrenia may be assessed. Comparisons of different antipsychotic medications and combination treatments and a longer-term assessment after 2-3 years of treatment are also needed.

CONCLUSIONS: Verbal fluency deficits can serve as early indicators of cognitive decline and indicators of the success of psychosocial interventions, characterizing the clinical condition of patients and their social functioning.

PMID:40982924

Psychiatr Danub. 2025 Sep;37(Suppl 1):260-266.

ABSTRACT

BACKGROUND: This study investigates impairments in real-life functioning domains among patients with affective disorders (depression and mania), addressing gaps in understanding the relationship between symptom severity and functional outcomes. The research aims to assess real-life functioning domains in clinical populations exhibiting varying degrees of affective disorder severity.

SUBJECTS AND METHODS: A cross-sectional study was conducted with 23 outpatients (16 with depression, 7 with mania) and 44 healthy controls. Participants were assessed using the Hamilton Depression Rating Scale (HDRS), Young Mania Rating Scale (YMRS), and Specific Levels of Functioning Scale (SLOF). Statistical analyses included Chi-square tests for functional impairments and Pearson’s correlations to examine associations between symptom severity and functioning.

RESULTS: Key findings demonstrate significant functional deficits in depressive patients across all measured domains (physical functioning, personal care, interpersonal relationships, social acceptability, activities, and work skills), with particularly pronounced impairments in physical functioning (χ²=12.25, p<0.001) and personal care skills (universally low scores). Manic patients exhibited comparable domain-specific impairments, though with less pronounced severity differentiation. Notably, symptom severity (measured via HDRS/YMRS scales) showed minimal correlation with functional outcomes, with the exception of an inverse relationship between depression severity and social acceptability (r=-0.56, p<0.03). Limitations include modest sample sizes and cross-sectional design, warranting future longitudinal research with larger cohorts.

CONCLUSIONS: Affective disorders broadly impair real-life functioning irrespective of symptom severity, except for depression’s inverse relationship with social acceptability. This finding suggests that functional impairments in affective disorders may represent independent disease dimensions rather than simple byproducts of symptom intensity, emphasizing the need for targeted psychosocial interventions alongside symptom management.

PMID:40982921

Psychiatr Danub. 2025 Sep;37(Suppl 1):237-S259.

ABSTRACT

BACKGROUND: Modern post-industrial society is facing a complex of challenges, such as including epidemiological threats, high demands from employers, aggressive forms of corporations’ management, stress at the work place, as well as geopolitical and economic instability worldwide. These factors bring a significant impact on mental health of the general population, contributing to an increased prevalence of mental disorders, particularly, affective states. The aim of this study was to develop a sensitive screening tool based on a self-questionnaire approach for accurate differentiation of affective spectrum state, from preclinical / at-risk to severe clinical conditions. To achieve this goal, we focused on identifying key affective symptoms’ domains and application of machine learning (ML) methods to perform a comprehensive data analysis on classifying the respondents into preclinical and clinical subgroups.

SUBJECTS AND METHODS: The study consisted of two stages. At the first stage, we developed and conducted an online survey among the experimental population consisting of university staff and students. This survey version included 19 questions. The study was interrupted to make adjustments. At the second stage, the survey was finalized based on data analysis (descriptive and inferential) and classification tasks. The revised survey was redistributed with additional criteria for inclusion and exclusion of the respondents applied to the study design. The final version contained 34 questions, excluding unreliable questions characterized by p > .05. 381 individuals (269 employees and 112 students) were interviewed, of whom 99 showed signs of depression, normal sadness or emotional burnout. We conducted correlation, descriptive, and inferential analyses and classification of respondents using ML-based methods.

RESULTS: The results confirmed the presence of significant differences (p < .001) between the groups with euthymia, normal sadness, emotional burnout and depression. However, there were no statistically significant differences for respondents with a pre-known emotional state and for respondents whose condition has been classified using machine learning technologies. The final distribution by category was as follows: euthymia – 38.8%, normal sadness – 27.3%, emotional burnout – 25.2%, depression – 8.7%. Our developed self-report tool has demonstrated statistical benefit, but requires further clinical research to clarify sensitive symptoms’ domains for updating its items content.

CONCLUSIONS: ML-based analysis of the self-report screening tool-related data demonstrated its sensitivity to classify affective states spectrum onto the separate states of depression, emotional burnout, normal sadness and euthymia (i.e. affective or emotional profiles of the respondents) with 100% accuracy at the final iteration. The problem of assessing mental health lies in the difficulty of obtaining fast, accurate, and emotionally neutral determination of the affective state in individual respondents and across populations. Development of a sensitive self-questionnaire / screening benefits from the the integration of clinical assessments along with the modern ML-based algorithms, as well as targeting the approach that helps to reduce costs and increase the diagnostic accuracy of existing psychometric tools.

PMID:40982919

Psychiatr Danub. 2025 Sep;37(Suppl 1):213-223.

ABSTRACT

BACKGROUND: Early recognition of autoaggressive tendencies in young people is essential for diagnostic screening and reducing suicidality risks. This can be achieved through psycholinguistic approaches such as corpus analysis and eye-tracking studies. Corpus research helps to develop generalized speech patterns of those at risk of suicide, while oculographic methods examine perceptual cues linked to suicidal tendencies.

METHODS: We formulated an algorithmic framework for constructing verbal, visual, and multimodal material to identify autoaggressive tendencies among youth. The stimuli material was created following the idiolect paradigm of forensic authorship attribution. The first stage involved analyzing corpus data including materials from social networks and social media, the Rusentiment database, and a text collection from the Privolzhsky Research Medical University. Python’s NLTK and SpaCy libraries for automated text processing were used to extract corpus statistics, n-grams, keywords, and collocations for identifying linguistic markers of autoaggression. Keywords were statistically ranked using Log-likelihood, T-score, and mutual information, while collocations were derived via T-score analysis. Sentiment analysis for the Dostoevsky Python library and stylistic indices (lexical diversity, readability) were also applied. The total analyzed material comprised more than 100 million tokens. We next integrated, stimulus and filler materials into an eye-tracking application (developed by LLC Lad IT Group) using standard laptop video cameras. Oculographic data quantified gaze delay differences via a percentage excess formula to pinpoint the most diagnostically relevant stimuli. In two iterations of the pilot experiment, 66 youths from the control group and 29 from the target group participated in the oculographic experiments.

RESULTS: In multimodal texts, most stimuli derived from corpus statistics were relevant, and all individuals in the target group showed a prolonged gaze delay; visual stimuli (pseudo-self-portraits, anime/game characters) elicited 26-36% longer gaze delay in the target group. Verbal stimuli analysis revealed prolonged gaze fixations on self-referential pronouns (12-25%) and metaphorical death expressions, although direct terms, like “suicide” showed the gaze avoidance (-11.9 to -129% deviation). We then developed a system of weighted coefficients for an automated diagnostic model. The algorithm showed 72 % accuracy in identifying autoaggression, presenting a promising tool for early diagnostic screening of this phenomenon.

CONCLUSIONS: The present methodology focuses on creating and employing a novel selective dataset consisting of visual, linguistic, and multimodal text stimuli integrated into the oculographic examination protocol. The oculographic detection of eye movement perceptual cues in response to exposure to the stimuli dataset may identify objective markers for evidence-based diagnostics of mental disorders (e.g., depression) and fundamental psychopathological phenomena (e.g., suicidality), including at-risk states (e.g., autoaggression). Furthermore, this approach may contribute to the enhancement of suicide prevention programs, particularly targeted interventions for the vulnerable population of young people who experience autoaggressive tendencies (i.e., self-aggression).

PMID:40982917

Psychiatr Danub. 2025 Sep;37(Suppl 1):207-212.

ABSTRACT

The explosion of the use of artificial intelligence (AI) in medical practice has shaken the foundations of clinical assessment and management. In our study, we conducted structured interviews with 43 patients (23 female, 15 male) affected by MMD (DSM-5-TR criteria). We sent the recorded and transcribed semi-structured interviews to the analysis of appropriately trained AI programs. We evaluated the predictive weight of symptoms described by patients beyond those present among the DSM-5-TR diagnostic criteria. We also analyzed the relationship with forgiveness, hopelessness, and diminished drive. The results revealed a positive predictive factor in patients with higher levels of somatization and physical oppression, ambivalent and blocked anhedonia, distress and agitated restlessness, mixed states, and subthreshold symptomatic oscillations.

PMID:40982916

Psychiatr Danub. 2025 Sep;37(Suppl 1):201-206.

ABSTRACT

This study examined individual and relational predictors of cyberbully-victim involvement among young adults, focusing on social connectedness (offline, mixed offline-online, and exclusively online), parasocial relationships (PSRs) with social media influencers (SMIs), and social media addiction. Using a generalized logistic regression model, results revealed that being female and younger significantly increased the likelihood of dual-role involvement. Offline social connectedness emerged as a significant protective factor, while offline-online and exclusively online ties were not associated with cyberbully-victim status. Notably, stronger PSRs with influencers were linked to a decreased likelihood of dual-role involvement, suggesting a possible compensatory or protective role for vulnerable individuals. Social media addiction was confirmed as a strong risk factor, more than doubling the odds of cyberbully-victim involvement. These findings underscore the complex interplay between psychosocial vulnerabilities and digital relational dynamics, highlighting the need for prevention strategies that foster offline relationships, promote digital resilience, and address problematic social media use among young adults.

PMID:40982915

J Holist Nurs. 2025 Sep 22:8980101251377481. doi: 10.1177/08980101251377481. Online ahead of print.

ABSTRACT

Purpose: Using the holistic nursing perspective as a guide, this study aimed to explore nursing students’ self-care practices in Indonesian nursing educational institutions. Design: A cross-sectional study. Methods: Nursing students enrolled in undergraduate programs across 13 institutions in Indonesia were recruited using proportionate stratified random sampling. A total of 1,071 students participated in an online survey. Data were analyzed using univariate, bivariate, and multivariate statistics. Findings: Overall, students took care of themselves. Self-care scores were highest in the emotional and spiritual dimensions, while physical self-care was lowest. Students’ self-care practices differed significantly based on their age, self-care education, self-care perception and health status. Educational background, self-care education, self-care perception and health status were all significant predictors of students’ self-care practices. Conclusion: Indonesian nursing students demonstrated satisfactory scores in the total Integrated Health and Wellness Assessment, but strategies to support students’ positive self-care practices beyond their nursing education should be established, alongside a focus on self-care dimensions that scored low. Centrally regulating nurse self-care education could ensure uniformity in curriculum integration and maximize long-term benefits for nursing students, the profession and the healthcare system in general.

PMID:40982315 | DOI:10.1177/08980101251377481

BJS Open. 2025 Sep 8;9(5):zraf091. doi: 10.1093/bjsopen/zraf091.

ABSTRACT

BACKGROUND: The aim of this meta-analysis was to elucidate the effects of prehabilitation (PR) on outcomes after surgery for upper gastrointestinal tract cancer.

METHODS: PubMed, Web of Science, Embase, and Cochrane databases were searched from inception up to 21 May 2024 for randomized clinical trials (RCTs) and cohort studies investigating PR interventions in patients with upper gastrointestinal tract cancer. Data were synthesized using standardized mean differences (SMDs) and risk ratios (RRs) with corresponding 95% confidence intervals. Sensitivity and subgroup analyses were used to examine the robustness of the results and find possible sources of heterogeneity. Statistical analyses were performed using Review Manager 5.4 and Stata 16.0.

RESULTS: Eight RCTs and eight cohort studies were included in the meta-analysis. Compared with the control group (no PR), the PR group had a significantly shorter postoperative length of hospital stay (SMD -0.27; 95% confidence interval (c.i.) -0.47 to -0.07; P = 0.008), a significant reduction in the occurrence of pneumonia after the surgery (RR 0.71; 95% c.i. 0.50 to 1.00; P = 0.005), and a greater improvement in the 6-minute walk distance (SMD 0.95; 95% c.i. 0.68 to 1.22; P < 0.00001). However, there were no significant differences between the control and PR groups in overall postoperative complications, anastomotic leakage, overall pulmonary complications, operative time, intraoperative blood loss, wound infection rate, in-hospital mortality, or recurrence rate (all P > 0.05).

CONCLUSION: For the population with upper gastrointestinal tract cancer, PR can partially lower the risk of postoperative pneumonia and promote faster postoperative recovery. Given the inherent limitations in the included studies, more large-scale RCTs are needed to verify these findings.

PMID:40982301 | DOI:10.1093/bjsopen/zraf091