In 2022, the International Classification of Diseases (ICD-11) and an update of the Diagnostic Statistical Manual of Mental Disorders (DSM 5 TR) were released for implementation worldwide and now include the new Prolonged Grief Disorder (PGD). The newest definition of PGD is based on robust clinical research from the Global North yet until now has not been tested for global applicability. The current study assesses the new PGD ICD-11 criteria in a large international sample of 1393 bereaved adults. The majority of the sample was included from the USΑ. Additionally, we conduct a sub-sample analysis to evaluate the psychometric properties, probable caseness of PGD, and differences in network structure across three regions of residency (USA, Greece-Cyprus, Turkey-Iran). The psychometric validity and reliability of the 33-item International Prolonged Grief Disorder Scale (IPGDS) were confirmed across the whole sample and for each regional group. Using the strict diagnostic algorithm, the probable caseness for PGD for the whole sample was 3.6 %. Probable caseness was highest for the Greece-Cyprus group (6.9 %) followed by Turkey-Iran (3.2 %) and the USA (2.8 %). Finally, the network structure of the IPGDS standard items and cultural supplement items (total of 33 items) confirmed the strong connection between central items of PGD, and revealed unique network connections within the regional groups. Future research is encouraged to include larger sample sizes and a more systematic assessment of culture. Overall, our findings confirm the global applicability of the new ICD-11 PGD disorder definition as evaluated through the newly developed IPGDS. This scale includes culturally sensitive grief symptoms that may improve clinical precision and decision-making.

Background: Health science and technology today is a rapidly growing field. Health is a multifaceted concept influenced by several factors, and health literacy is essential to deal properly with the current situation. In this study, the association between health literacy and sexual function and sexual satisfaction were investigated in 2016. Materials and Methods: This descriptive and correlational study was conducted on 193 couples in the Royan Institute, Tehran. Data collection instruments were three standard questionnaires which included the Test of Functional Health Literacy, the Female Sexual Function Index (FSFI) and the International Index of Erectile Function, and the Iranian version of the Sexual Satisfaction Scale. The data were analyzed using SPSS-v23 software at a significance level of 0.05. Results: Marginal health literacy, 49.7% among men and 44.1% among women, was more common than adequate or inadequate health literacy. Erectile function for the majority of men was appropriate (53.3%), compared to 16.6% who had perfect function and 30.1% for whom function was less than appropriate. The majority of women (57.0%) had sexual dysfunction. One hundred and three (53.3%) men had appropriate sexual function and 57% of women had normal sexual function. The greater proportion of men (50.8%) and women (46.1%) had good, rather than very good or less than good, sexual satisfaction. The results of chi-square tests indicated that greater health literacy was associated with higher levels of sexual function and sexual satisfaction among men and women. However, application of the Cramer's V test indicates that the strength of these associations is moderate to weak. Conclusion: Health literacy was marginal among most couples and its adverse impacts on sexual function and sexual satisfaction were confirmed. Accordingly, it is recommended that plans be developed to promote health literacy among infertile couples.

Chronic pain is a widespread condition that profoundly affects the daily functioning of many people worldwide, characterized by persistent sensory and emotional discomfort associated with real or perceived tissue injury. This study aims to predict chronic pain based on post-traumatic stress disorder (PTSD), alexithymia, anxiety, pain catastrophizing, stress, depression, and demographic variables as correlates. The analysis included data from 234 males and 307 females experiencing chronic pain in Tehran province between 2022 and 2023. The classification results suggested that PTSD and alexithymia were the most significant predictors, followed by anxiety, depression, and pain catastrophizing. Six different machine learning (ML) classification techniques: Naive Bayes, Decision Tree, Gradient Boosting, Light Gradient Boosting Machine, Support Vector Machine, and Stochastic Gradient Boosting (SGB) were applied to examine a dataset detailing various dimensions associated with chronic pain. The findings in the study classified pain severity into three levels, low, medium, and high, based on quantiles and used six ML models to predict these classes. The SGB model outperformed the others, showing higher accuracy and F1 scores, particularly in predicting the medium pain class. SHAP analysis revealed that psychological factors such as alexithymia, anxiety, PTSD, depression, and stress were significant predictors of pain severity, while age and gender had less impact.

In the year 2022, this research conducted an in-person study involving 780 single or widowed women, aged between 20 and 70, falling within the bottom three economic deciles and possessing varying levels of education. All participants held educational qualifications below a high school diploma and were beneficiaries of charitable financial support in Khorasan province, Iran. The study aimed to investigate the predictive factors of social dysfunction in this specific demographic. Data collection spanned a 12-month period throughout 2022, with participants completing the GHQ-28 questionnaire during their visits to the charity office. Clinical in-person interviews were also conducted to gather comprehensive data. Data analysis was carried out using IBM SPSS version 27. The research employed a Multilayer Perceptron (MLP) neural network model, considering an extensive set of input factors and covariates. These factors included cognitive functioning, anxiety, depression, age, and education levels. The MLP model exhibited robust performance, achieving high overall accuracy and sensitivity in identifying cases of high social dysfunction. The findings emphasized the significance of cognitive functioning, anxiety, and depression as pivotal predictors of social dysfunction within this specific demographic, while education and age displayed relatively lower importance. The normalized importance scores provided a relative measure of each covariate’s impact on the model’s predictions. These results furnish valuable insights for the development of targeted interventions and evidence-based policies aimed at addressing social dysfunction and promoting societal well-being among economically disadvantaged, single or widowed women. Notably, the research underscores the potential of MLP modeling in social science research and suggests avenues for further research and refinement to enhance the model’s predictive accuracy, particularly for cases of low social dysfunction.

Iranian Journal of Psychiatry and Behavioral Sciences

Objective: Traumatic experiences are a significant risk factor for psychological disturbances, including disorders such as complex posttraumatic stress disorder, emotion-processing problems, and trauma-related dissociative experiences. The present investigation examined the coexistence of these symptoms using a network analysis model.Method: This study included a sample of 406 people referred to comprehensive health centers in Tehran from September to December 2023 with psychopathological syndromes. Variables were assessed using The International Trauma Questionnaire, International Measurement of Exposure to Traumatic Event checklist, Baker Emotional Processing Questionnaire, and Dissociative Experiences. A regularized partial correlation network and Glasso algorithm, in combination with Extended Bayesian information criteria, were applied to estimate the network structure.Results: Signs of unprocessed emotions and disturbance in self-organization symptoms were the most important symptoms in the symptom network, forming strong connections with other nodes. Thereby, these two symptoms can be regarded as the most important clinical manifestations in the symptom network following traumatic experiences. Three distinct symptom communities were identified: the community of traumatic experiences (childhood, adolescence, adulthood), the community of dissociative experiences (amnesia, depersonalization/derealization, and absorption), and the community of emotional processing (suppression, unpleasant emotional experience, Signs of unprocessed emotions, avoidance, and emotional control, posttraumatic stress disorder symptoms and disturbance in self-organization symptoms). The strongest edges observed were between childhood trauma-adolescence trauma (0.473) in the community of traumatic experiences, between amnesia and depersonalization/derealization (0.644) in the community of dissociative experiences, and between disturbance in self-organization symptoms and unprocessed emotions (0.324) in the community of emotional processing, indicating the recurrent occurrence of these symptoms.Conclusion: In this study, disturbance in self-organization symptoms was identified as the central psychopathologic symptom in individuals experiencing traumas at different developmental stages. It seems that adolescent trauma and not childhood trauma plays a more decisive role in the symptoms that a person manifests after traumatic experiences. Also, posttraumatic stress disorder symptoms and disturbance in self-organization symptoms were recognized in the cluster of emotional processing symptoms and can have substantial roles in prioritizing therapeutic measures.