Current Psychiatry Research and Reviews - Volume 15, Issue 4, 2019

Introduction: Vaginismus includes some psychological conditions such as fear of pain and avoidance from penetration. There is little knowledge about the effects of vaginismus. Objective: The present study aims to present the bio-psychosocial consequences of vaginismus in women life. Methods: The method of the present study is a review, which is conducted on the available resources. All relevant studies were included to present effects of vaginismus on the women. Results: Women who have vaginismus have many problems with self-identity, psychological and reproductive lives. Most of the effects of vaginismus lead to another deep effect on women. Women with vaginismus mostly describe themselves negatively. This negative self-perception affects women’s self-esteem levels which cause psychiatric disorders. The psychiatric disorders have been associated with vaginismus as a reason and result. It is stated in the studies that the general anxiety and, penetration specific anxiety are related to vaginismus. This result reflects that women with vaginismus have more anxiety about penetration. Women with vaginismus encounter reproductive problems, who are more likely to encounter increased cesarean section and fertility problems, they are reluctant to seek health care services, especially due to fear of the gynaecological examination. Conclusion: Although vaginismus is a common problem, there is little information about the effects of vaginismus on women. Vaginismus causes psychiatric disorders and reproductive problems. The researchers should examine how women live with vaginismus. It is also suggested that psychotherapy techniques should include couples interventions and, researchers should examine psychological health of women deeply.

Background: The last twenty years have seen major advancements in unraveling the etiology and the identification of biological markers of Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococci (PANDAS). However, this body of evidence has not yet been translated into a clinical setting. Objective: We will review the most important studies to date on PANDAS, emphasizing those whose advances could improve the diagnosis of these disorders. We also suggest the need for updated diagnosis criteria integrating the recent findings from the hereby included studies. Methods: Consulting the PubMed database, a literature review of the last twenty-one years (between 1998 and 2019) was carried out using the terms “PANDAS” and “pediatric autoimmune neuropsychiatric disorders” in combination with “diagnosis” and “markers”. The search resulted in 175 hits from which we selected clinical cases, original investigations, and clinical reviews. Results: This review offers a compilation of the most important studies performed to date regarding the clinical presentation and potential biological markers of PANDAS. Moreover, we suggest the refinement of some aspects in the current diagnosis criteria, such as focusing on specific symptoms and the inclusion of neuroimaging and peripheral markers. Conclusion: The identification of specific biological markers in PANDAS is crucial for its diagnosis and opportune treatment. Future research will determine whether PANDAS require separated diagnostic and therapeutic measures or if it should be included in recently proposed categories such as Pediatric Acute Neuropsychiatric Syndrome (PANS) or Childhood Acute Neuropsychiatric Syndrome (CANS).

Background: Association splitting is a cognitive technique that targets obsessions in obsessive-compulsive disorder (OCD) by weakening biased semantic associations among OCDrelevant concepts. Objective: In this systematic review, we examine studies on the efficacy of association splitting for reducing OCD symptoms. Methods: Following PRISMA guidelines, six studies were included, with diversity in sample characteristics, mode of administration (i.e., self-help vs therapist-assisted), language of administration, comparator groups, etc. Results: Results indicated that association splitting, as a self-help intervention, was efficacious in reducing overall OCD symptom severity, specific OCD symptoms (i.e., sexual obsessions), subclinical unwanted intrusions, and thought suppression, with small-to-large effect sizes (e.g., across relevant studies, ds = .28-1.07). Findings were less clear when association splitting was administered on a therapist-assisted basis as an add-on to standard cognitive-behavior therapy (CBT). Nonetheless, across studies, the majority of participants reported high acceptability, ease of comprehension, and adherence to daily association splitting practice. Conclusion: Although association splitting is an efficacious and acceptable self-help intervention for OCD symptoms, future studies should include appropriate comparison groups, conduct longitudinal assessments, examine efficacy for different symptom dimensions, and assess changes in semantic networks as proof of mechanistic change. There should also be greater representation of marginalized groups in future studies to assess association splitting’s utility in circumventing barriers to face-to-face CBT. Ethical considerations are also discussed.

Background: We aimed to evaluate the effects of various antipsychotics on the in vitro production of C-reactive protein (CRP) in whole blood cell cultures from healthy volunteers. The evaluation was performed using haloperidol, quetiapine, clozapine, amisulpride, and chlorpromazine. Methods: Antipsychotic agents were added to the participants' whole blood samples, and the resulting CRP levels were measured. For each agent, three different concentrations were tested: the therapeutic concentration, one-tenth the therapeutic concentration, and ten times the therapeutic concentration. The differences in CRP concentrations before and after drug administration were investigated. Results: The Friedman test showed that haloperidol, amisulpride, and chlorpromazine significantly increased CRP levels in the blood culture samples; however, clozapine and quetiapine did not increase CRP levels. In the case of chlorpromazine, elevated CRP levels were noted at all concentrations tested. Conclusion: Our study suggests that some antipsychotics elevate CRP levels in vitro. These results agree with previous studies showing that antipsychotics have immunomodulatory effects. Future research will clarify our findings and our understanding of antipsychotic drugs and their impact on immune regulation.

Background: People living with HIV (PLHIV) have a longer lifespan with treatment and continue to be sexually active. To date, the extent of risky sexual behaviour among local PLHIV and its associated factors were undetermined. Objective: To examine the role of depression, anxiety and illness characteristics on risky sexual behaviour among PLHIV attending care in a Malaysian tertiary reference hospital (N= 406). Methods: It was a cross-sectional study. Subjects were recruited by systematic random sampling. Risky sexual behaviour was determined by using the modified National Youth Risk Behaviour Survey. PHQ-9 and GAD-7 were used to measure the depressive and anxiety symptoms, respectively. Chi-square test was used to examine the association between the variables. Multiple logistic regression was used to examine the predictors of the study. A p value of less than 0.05 was considered significant and odds ratio was used as the measure of risk association. Results: Our study showed that 29.3% had risky sexual behaviour. Meanwhile, 21.9% and 26.4% had depressive and anxiety symptoms, respectively. Risky sexual behaviour was significantly associated with age, religion, education level, duration of HIV diagnosis, depressive and anxiety symptoms. From multivariate logistic regression, duration of HIV diagnosis and anxiety symptoms significantly predicted risky sexual behaviour. Conclusion: This study highlights that a substantial number of PLHIV had risky sexual behaviour and psychological symptoms. It is important for psychological interventions that reduce risky sexual behaviour among PLHIV who attend treatment, especially during the early phase.

Background: A marked sexual dimorphism exists in psychiatric diagnoses. Culture derived gender bias in diagnostic criteria is one explanation. Adverse childhood events, including sexual and physical abuse, are more reliable and consistent predictors of later psychiatric diagnoses, including depression and post-traumatic stress disorder. Some interesting interactions between genes and experience have been uncovered, but the primary effect appears to be epigenetic with life experience altering gene expression and being transmitted to subsequent generations. Objectives: To determine if reconceptualizing depression as encompassing both internalizing and externalizing strategies would eliminate gender differences in the diagnosis of depression Methods: We reviewed 74 life stories of patients, collected during a study of the effect of physicians’ knowing patients’ life stories on the quality of the doctor-patient relationship. Looking at diagnoses, the prevalence of women to men was 2.9 to 1. We redefined depression as a response to being in a seemingly hopeless situation accompanied by despair, either externalizing ((more often diagnosed as substance use disorders, impulse control disorders, antisocial personality disorder, or bipolar disorder) or internalizing (the more standard diagnosis of depression). Then we reviewed these life stories from that perspective to determine how many would be diagnosed as depressed. Results: With this reconceptualization of depression, the sex ratio changed to 1.2 to 1. Conclusions: From this perspective, men and women are equally likely to respond to hopelessness, though men are more socialized to externalize and women to internalize. Considering depression in this way may help to better identify men at risk for suicide.

Background: Post-traumatic stress disorder (PTSD) is prevalent in approximately 12% of patients with cardiovascular disease (CVD) and such patients are at risk of further CVD morbidity and mortality. It is unknown whether CVD patients with cardiac and non-cardiac traumatic events leading to PTSD differ in medical comorbidities and psychiatric vulnerabilities. Our objective was to compare heart failure (HF) patients with cardiac and non-cardiac PTSD. Methods: A population of HF patients from 3 hospitals underwent a two-step depression and anxiety screening process to identify potential mental health treatment needs. The post-traumatic stress disorder module of the Structured Clinical Interview for DSM-IV Axis-I disorders was used to classify trauma(s) exposure, and other disorders. The patients with PTSD were sub-divided by cardiac related traumas (e.g. myocardial infarction, sudden cardiac arrest) and non-cardiac related traumas (e.g. sexual abuse, interpersonal violence). Results: 10 patients met criteria for non-cardiac trauma and 18 patients met criteria for cardiacinduced trauma. There were no significant differences in HF aetiology or severity nor cardiac comorbidities. Time since PTSD, onset was significantly longer for those with non-cardiac PTSD. Among psychiatric comorbidities, alcohol and substance abuse disorders, as well as depression were more prevalent in patients with non-cardiac PTSD. Conclusion: Cardiac related PTSD was associated with less alcohol and substance abuse disorders, and depression by comparison to their non-cardiac induced PTSD counterparts. Ongoing research is required to establish if cardiac-induced PTSD truly reflects a unique subtype of PTSD, and whether there are different treatment needs and therapeutic approaches for this subtype.

Background: Autistic Spectrum Disorder (ASD) is a disorder associated with genetic and neurological components leading to difficulties in social interaction and communication. According to statistics of WHO, the number of patients diagnosed with ASD is gradually increasing. Most of the current studies focus on clinical diagnosis, data collection and brain images analysis, but do not focus on the diagnosis of ASD based on machine learning. Objective: This study aims to classify ASD data to provide a quick, accessible and easy way to support early diagnosis of ASD. Methods: Three ASD datasets are used for children, adolescences and adults. To classify the ASD data, we used the k-Nearest Neighbours method (kNN), the Support Vector Machine method (SVM) and the Random Forests method (RF). In our experiments, the data was randomly split into training and test sets. The parts of the data were randomly selected 100 times to test the classification methods. Results: The final results were assessed by the average values. It is shown that SVM and RF are effective methods for ASD classification. In particular, the RF method classified the data with an accuracy of 100% for all above datasets. Conclusion: The early diagnosis of ASD is critical. If the number of data samples is large enough, we can achieve a high accuracy for machine learning-based ASD diagnosis. Among three classification methods, RF achieves the best performance for ASD data classification.