Types Of Psychiatric Disorders Research Articles

P2X7 receptor: a potential target for treating comorbid anxiety and depression.

In clinical practice, depression and anxiety frequently coexist, and they are both comorbid with somatic diseases. The P2X7R is an adenosine 5'-triphosphate (ATP)-gated non-selective cation channel that is widely expressed in immune-related cells. Under conditions of stress, chronic pain, and comorbid chronic physical illness, P2X7R activation in glial cells leads to neuroinflammation. This could contribute to the development of anxiety and depression-related emotional disturbances. Previous studies have shown that the P2X7 receptor (P2X7R) plays an important role in the pathogenesis of both anxiety and depression. Thus, the P2X7R may play a role in the comorbidity of anxiety and depression. Positron emission tomography can be used to assess the degree and location of neuroinflammation by monitoring functional and expression-related changes in P2X7R, which can facilitate clinical diagnoses and guide the treatment of patients with anxiety and depression. Moreover, single nucleotide polymorphisms (SNPs) in the P2X7R gene are associated with susceptibility to different types of psychiatric disorders. Thus, evaluating the SNPs of the P2X7R gene could enable personalized mood disorder diagnoses and treatments. If the P2X7R were set as a therapeutic target, selective P2X7R antagonists may modulate P2X7R function, thereby altering the balance of intra- and extra-cellular ATP. This could have therapeutic implications for treating anxiety and depression, as well as for pain management. According to in vitro and in vivo studies, the P2X7R plays an important role in anxiety and depression. In this review, we consider the potential of the P2X7R as a therapeutic target for comorbid anxiety and depression, and discuss the potential diagnostic and therapeutic value of this receptor.

Overall comorbidities in functional neurological disorder: A narrative review

IntroductionThe importance to assess and include the frequent comorbidities in the personalised care management plan of patients with functional neurological disorders (FND) has arisen through the years. FND patients are not only complaining from motor and/or sensory symptoms. They also report some non-specific symptoms that participate to the burden of FND. In this narrative review, we aim to better describe these comorbidities in terms of prevalence, clinical characteristics and their variability depending on the subtype of FND. MethodsThe literature was searched for on Medline and PubMed. The search was narrowed to articles between 2000 and 2022. ResultsFatigue is the most common symptom reported in relation to FND (from 47 to 93%), followed by cognitive symptoms (from 80 to 85%). Psychiatric disorders are reported in 40 to 100% FND patients, depending on the FND subtype (functional motor disorder [FMD], functional dissociative seizures [FDS]…) but also on the type of psychiatric disorder (anxiety disorders being the most frequent, followed by mood disorders and neurodevelopmental disorders). Stress factors such as childhood trauma exposure (emotional neglect and physical abuse predominantly) have also been identified in up to 75% of FND patients, along with maladaptive coping strategies. Organic disorders are commonly reported in FND, such as neurological disorders (including epilepsy in FDS [20%] and FMD in Parkinson's Disease [7%]). Somatic symptom disorders including chronic pain syndromes are frequently associated to FND (about 50%). To be noted, recent data also suggest a high comorbidity between FND and hypermobile Ehlers Danlos Syndrome (about 55%). ConclusionPut together, this narrative review highlights the high burden of FND patients, not only due to somatosensory alterations but also by considering the frequent comorbidities reported. Thus, such comorbidities must be taken into consideration when defining the FND personalised care management strategy for the patients.

Children's cognitive performance and suicide risk through middle adulthood.

Longitudinal studies show that lower cognitive performance in adolescence and early adulthood is associated with higher risk of suicide death throughout adulthood. However, it is unclear whether this cognitive vulnerability originates earlier in childhood since studies conducted in children are scarce and have inconsistent results. Vital status of 49,853 individuals born between 1959 and 1966 to participants in the Collaborative Perinatal Project cohort was determined by a probabilistic linkage to the National Death Index, covering all US deaths occurring from 1979 through 2016. Cox proportional hazard models were used to examine associations of general, verbal, and non-verbal intelligence at ages 4 and 7, and academic skills at age 7 with suicide death coded according to ICD-9/10 criteria, while accounting for sociodemographic and pregnancy factors previously associated with suicide in this sample. By the end of 2016, 288 cohort members had died by suicide. Cognitive performance at 7 years on tests with verbal components was associated with suicide risk (average vs. high verbal intelligence, HR = 1.97, 95% CI 1.05-3.71; low vs. high spelling skills, HR = 2.02, 95% CI 1.16-3.51; low vs. high reading skills, HR = 2.01, 95% CI 1.27-3.17). Associations were still evident, especially for verbal intelligence and reading skills, but hazard ratios were attenuated after adjusting for prenatal and sociodemographic factors at birth (verbal intelligence, HR = 1.97, 95% CI 1.03-3.78; spelling, HR = 1.61, 95% CI 0.90-2.88; reading, HR = 1.67, 95% CI 1.02-2.72). Childhood neurocognitive performance is associated with vulnerability to suicide mortality through middle-adulthood, suggesting that there might be a cognitive diathesis for suicide originating in early childhood. Future studies should examine how multiple domains of childhood cognitive performance contribute to vulnerability to suicide risk, including by increasing risk for social and environmental factors that are associated not only with suicide but also with many types of psychiatric disorders.

Effectiveness of Structured Teaching Programme on Knowledge Regarding Cigarette Smoking and Its Selected Comorbid Psychiatric Disorders among College Students

Substance dependence is also a type of psychiatric disorder, characterized by compulsive substance use and appearance of withdrawal symptoms when the substance is no longer used. Cigarette Smoking which contains tobacco or cannabis, is the most common substance dependence seen in the population today. There is neurobiological link between tobacco use and many psychiatric disorders. The finding revealed that the post test mean score was 33.28 with a standard deviation of 16.40 which was significantly higher than the mean pre test score 18.20 with a standard deviation of 17.49. The computed paired ‘t’ value was 36.12 which was higher than table value 3.5004, which shows that the structured teaching programme on cigarette smoking and its selected comorbid psychiatric disorders was effective and statistically significant at P< 0.001 level. Chi square value shows significant (P ≤ 0.05) association with socio-demographic variables.

Sistem Pakar Diagnosa Penyakit Skizofrenia Dengan Menerapkan Kombinasi Metode Constraint Satisfaction Problem (CSP) Dan Metode Certainty Factor

Psychiatric illness is a change in mental function that causes disturbances in ways of thinking, will, emotions, actions and social relations that can cause obstacles in carrying out social roles. One type of psychiatric disorder that is very often known by the public is schizophrenia. If schizophrenia is not followed up, it will have a lot of impact on Indonesian society. For this reason, we need a system that is designed to mimic the expertise of an expert in answering questions and solving a problem in accordance with the knowledge of an expert that is entered into a computer system. The development of artificial intelligence technology that has occurred has enabled expert systems to be applied in detecting diseases using programming languages. One of them is in providing information about various problems, especially psychiatric disorders or often called schizophrenia. The expert system method used is a combination of the Constraint Satisfaction Problem (CSP) and Certainty Factor (CF) methods, which is one of the solutions that can display the final results of several diagnoses of schizophrenia. With the facilities provided to users, it is possible to use this system according to their individual needs. Users are given the convenience of finding information about the symptoms of Schizophrenia and its prevention. This expert system was created using the Microsoft Visual Basic 2010 application.

The frequency of psychiatric disorder co-morbidities in patients with fibromyalgia: A cross-sectional study in Iran.

This study aimed to investigate psychiatric disorders in Iranian female patients with fibromyalgia (FM). Female patients, newly diagnosed with FM, were interviewed by a psychiatrist for psychiatric assessments during a 2-year period. The diagnosis of the psychiatric disorders was based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), and sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). In total, 159 patients with the mean age of 42.15 ± 9.89 were recruited in this study. Over 92% of the cases were also diagnosed with at least one type of psychiatric disorder. Sleep disorders (SDs, 90.57%), mood disorders (MDs, 52.83%), personality disorders (PDs, 40.25%) and anxiety disorders (ADs, 16.98%) were the most prevalent diagnoses among these patients. The logistic regression results correspondingly showed that suffering from Cluster-B PDs was associated with a higher prevalence rate of somatic symptom disorders (SSDs), with a p-value of 0.019 and an odds ratio (OR) of 2.7.

Hospitalization Associated With Comorbid Psychiatric and Substance Use Disorders Among Adults With COVID-19 Treated in US Emergency Departments From April 2020 to August 2021

During the COVID-19 pandemic, US emergency department (ED) visits for psychiatric disorders (PDs) and drug overdoses increased. Psychiatric disorders and substance use disorders (SUDs) independently increased the risk of COVID-19 hospitalization, yet their effect together is unknown. To assess how comorbid PD and SUD are associated with the probability of hospitalization among ED patients with COVID-19. This retrospective cross-sectional study analyzed discharge data for adults (age ≥18 years) with a COVID-19 diagnosis treated in 970 EDs and inpatient hospitals in the United States from April 2020 to August 2021. Any past diagnosis of (1) SUD from opioids, stimulants, alcohol, cannabis, cocaine, sedatives, or other substances and/or (2) PD, including attention-deficit/hyperactivity disorder (ADHD), anxiety, bipolar disorder, major depression, other mood disorder, posttraumatic stress disorder (PTSD), or schizophrenia. The main outcome was any hospitalization. Differences in probability of hospitalization were calculated to assess its association with both PD and SUD compared with PD alone, SUD alone, or neither condition. Of 1 274 219 ED patients with COVID-19 (mean [SD] age, 54.6 [19.1] years; 667 638 women [52.4%]), 18.6% had a PD (mean age, 59.0 years; 37.7% men), 4.6% had a SUD (mean age, 50.1 years; 61.7% men), and 2.3% had both (mean age, 50.4 years; 53.1% men). The most common PDs were anxiety (12.9%), major depression (9.8%), poly (≥2) PDs (6.4%), and schizophrenia (1.4%). The most common SUDs involved alcohol (2.1%), cannabis (1.3%), opioids (1.0%), and poly (≥2) SUDs (0.9%). Prevalence of SUD among patients with PTSD, schizophrenia, other mood disorder, or ADHD each exceeded 21%. Based on significant specific PD-SUD pairs (Q < .05), probability of hospitalization of those with both PD and SUD was higher than those with (1) neither condition by a weighted mean of 20 percentage points (range, 6 to 36; IQR, 16 to 25); (2) PD alone by 12 percentage points (range, -4 to 31; IQR, 8 to 16); and (3) SUD alone by 4 percentage points (range, -7 to 15; IQR, -2 to 7). Associations varied by types of PD and SUD. Substance use disorder was a stronger predictor of hospitalization than PD. This study found that patients with both PD and SUD had a greater probability of hospitalization, compared with those with either disorder alone or neither disorder. Substance use disorders appear to have a greater association than PDs with the probability of hospitalization. Overlooking possible coexisting PD and SUD in ED patients with COVID-19 can underestimate the likelihood of hospitalization. Screening and assessment of both conditions are needed.

Psychiatric Disorder Incidence among Adolescents and Young Adults Aged 15-39 with Cancer: Population-Based Cohort.

Adolescent and young adult (AYA) cancer survivors face physical and psychological sequelae related to having cancer decades after treatment completion. It is unclear if AYA cancer survivors are at increased risk for late psychiatric disorders. We used the Alberta AYA Cancer Survivor Study that includes five-year survivors of cancer diagnosed at 15-39 years of age during 1991 to 2013. The primary outcome was incidence of psychiatric disorder (composite outcome) including anxiety, depressive, trauma- and stressor-related, psychotic, and substance use disorders that were identified using coding algorithms for administrative health databases. A validated coding algorithm identified people who experienced a suicide attempt or event of self-harm. Secondary outcomes were incidences of diagnoses by type of psychiatric disorder. Among 12,116 five-year AYA cancer survivors (n = 4,634 [38%] males; n = 7,482 [62%] females), 7,426 (61%; n = 2,406 [32%] males; n = 5,020 [68%] females) were diagnosed with at least one of five psychiatric disorders occurring at least three years after cancer diagnosis. Survivors of all cancer types were most often diagnosed with anxiety (males, 39.0%, 95% confidence interval [CI] 37.6-40.4); females, 54.5%, 95%CI 53.3-55.6), depressive (males, 32.7%, 95%CI 31.3-34.0; females, 47.0%, 95%CI 45.8-48.1), and trauma- and stressor-related disorders (males, 13.5%, 95%CI 12.5-14.5; females, 22.5%, 95%CI 21.6-23.5). diagnosis. Anxiety, depressive, and trauma- and stressor-related disorders are common amongst five-year survivors of AYA cancer. Primary, secondary, or tertiary preventive strategies for AYAs diagnosed with cancer, particularly at an early age, are needed to mitigate risk of potentially severe outcomes due to psychiatric disorders.

A RETROSPECTIVE STUDY OF THE PREVALENCE OF DEPRESSION DUE TO LOW HAEMOGLOBIN COUNT

Objective: It has been shown that low haemoglobin count is associated with psychological consequences and psychiatric morbidity. The association between low haemoglobin count and psychological depression has not been properly interpreted with standard values. Hence the purpose of this pilot study is to know whether there is a relation between the haemoglobin levels and the risk of developing psychiatric disorders and morbidities.&#x0D; To find out if there is any relationship between low haemoglobin count and depression in a rural healthcare setup.&#x0D; Methods: Patients from the Psychiatry Department in Saveetha Medical College and Hospital were taken. Adults over the age of 18 were included. The period between the months September 2020 and July 2021. The primary outcome was the diagnosis of psychiatric depression and their associated blood haemoglobin values.&#x0D; Results: Among the other types of psychiatric disorders, the female patients with low haemoglobin count were associated with a significantly higher incidence of anxiety disorders, depression and adjustment disorders. Furthermore, patients with normal haemoglobin levels were associated with a significantly lower risk of psychiatric morbidities.&#x0D; Conclusion: The undergone study indicates that patients with psychiatric disorders such as depression, adjustment disorders and anxiety are related with significantly low haemoglobin counts in women and not in men.

Psychiatric Outcomes in ICU Patients With Family Visitation: A Population-Based Retrospective Cohort Study

Lack of family visitation in the ICU can have long-term consequences on patients in the ICU after discharge. The effect of family visitation on the incidence of patient psychiatric disorders is unknown. What is the association between family visitation in the ICU and incidence of psychiatric outcomes in patients in the ICU 1 year after hospital discharge? This study assessed a population-based retrospective cohort of adult patients admitted to the ICU from January 1, 2014, through May 30, 2017, surviving to hospital discharge with ICU length of stay of≥ 3days. To be eligible, patients needed to have minimum of 5 years of administrative data before ICU admission and a minimum of 1 year of follow-up data after hospital discharge. An internally validated algorithm that interpreted natural language in health records determined patients with or without in-person family (ie, relatives, friends) visitation during ICU stay. The primary outcome was risk of an incidence of psychiatric disorder (composite outcome), including anxiety, depressive, trauma- and stressor-related, psychotic, and substance use disorders, identified using coding algorithms for administrative databases. Propensity scores were used in inverse probability weighted logistic regression models, and average treatment effects were converted to risk ratios (RRs) with 95%CIs. Secondary outcomes were incidences of diagnoses by type of psychiatric disorder. We included 14,344 patients with (96%[n= 13,771]) and without (4.0%[n= 573]) in-person family visitation who survived hospital discharge. More than one-third of patients received a diagnosis of any psychiatric disorder within 1 year after discharge (34.9%; 95%CI, 34.1%-35.6%). Patients most often received diagnoses of anxiety disorders (17.5%; 95%CI, 16.9%-18.1%) and depressive disorders (17.2%; 95%CI, 16.6%-17.9%). After inverse probability weighting of 13,731 patients, in-person family visitation was associated with a lower risk of received a diagnosis of any incident psychiatric disorder within 1 year after discharge (RR, 0.79; 95%CI, 0.68-0.92). ICU family visitation is associated with a decreased risk of psychiatric disorders in critically ill patients up to 1 year after hospital discharge.

Exploring dysconnectivity of the large-scale neurocognitive network across psychiatric disorders using spatiotemporal constrained nonnegative matrix factorization method.

Psychiatric disorders usually have similar clinical and neurobiological features. Nevertheless, previous research on functional dysconnectivity has mainly focused on a single disorder and the transdiagnostic alterations in brain networks remain poorly understood. Hence, this study proposed a spatiotemporal constrained nonnegative matrix factorization (STCNMF) method based on real reference signals to extract large-scale brain networks to identify transdiagnostic changes in neurocognitive networks associated with multiple diseases. Available temporal prior information and spatial prior information were first mined from the functional magnetic resonance imaging (fMRI) data of group participants, and then these prior constraints were incorporated into the nonnegative matrix factorization objective functions to improve their efficiency. The algorithm successfully obtained 10 resting-state functional brain networks in fMRI data of schizophrenia, bipolar disorder, attention deficit/hyperactivity disorder, and healthy controls, and further found transdiagnostic changes in these large-scale networks, including enhanced connectivity between right frontoparietal network and default mode network, reduced connectivity between medial visual network and default mode network, and the presence of a few hyper-integrated network nodes. Besides, each type of psychiatric disorder had its specific connectivity characteristics. These findings provide new insights into transdiagnostic and diagnosis-specific neurobiological mechanisms for understanding multiple psychiatric disorders from the perspective of brain networks.

Free Papers Compiled

BACKGROUND:Tuberculosis (TB) is an infectious disease caused by Mycobacterium Tuberculosis and is one of the leading cause of mortality worldwide. Presence of various psychiatric co-morbidities can have impact on treatment of tuberculosis and Identifying and treating them can increase cure rates of tuberculosis.AIM AND OBJECTIVES-The aim of the study is to assess the psychiatric co-morbidities and their relationship with socio-demographic variables in patients of pulmonary tuberculosis.MATERIAL AND METHODS-A total of 120 patients diagnosed with pulmonary tuberculosis from the department of respiratory medicine were assessed for the presence of psychiatric co-morbidity using Mini International Neuropsychiatry Inventory (MINI).RESULT-Overall psychiatric co-morbidities were found in 54 (45%) patients out of 120. The frequency of co-occurrence of different types of psychiatric disorders was as following: depression 22.5%, social phobia 9.2%, panic disorder 7.5%, obsessive compulsive disorder 5.8%, generalized anxiety disorder 4.2%, alcohol dependence 2.5%, suicidality 1.7%. Among socio-demographic parameters, marital status and educational level were associated with psychiatric co-morbidities in pulmonary tuberculosis patients. psychiatric co-morbidities were found to be more in singles and patients with lower educational level.CONCLUSION-Psychiatric comorbidities were found to be a common problem with pulmonary tuberculosis. The Results of this study are in line with many different research works both in India and abroad. A proper address of this issue is important for the management, better outcome and policy making in patients with pulmonary tuberculosis.

Depression, Anxiety and Stress on Caregivers of Persons with Dementia (CGPWD) in Hong Kong amid COVID-19 Pandemic.

Background: Coronavirus disease 2019 (COVID-19) contributed to increasing prevalence of depressive symptoms and other psychological repercussions, particularly in the disease population in Hong Kong. Nonetheless, the caregiver burden of caregivers of persons with dementia (CGPWD), has been under-investigated. Aims: This study examined the psychological impact and its correlates on the CGPWD in Hong Kong amid the COVID-19 outbreak. Methods: CGPWD referred from rehabilitation clinics and online seminar were used to recruit participants to complete an online questionnaire by the end of the second-wave of the COVID-19 outbreak (June 2021). To be eligible, either full-time or part-time CGPWD, aged 18 or above, can understand Cantonese, currently reside in Hong Kong and offering care to PWD for at least one year, were recruited. Those CGPWD diagnosed with any type of psychiatric disorder were excluded from this study. The Chinese Center for Epidemiologic Studies Depression Scale (CES-D), Perceived Stress Scale (PSS-10), Generalized Anxiety Disorder (GAD-7), Zarit Burden Interview (ZBI-22), and Nonattachment Scale (NAS-7) were used to measure participants’ depression, perceived stress, anxiety symptoms, caregiver burden and wisdom in subjective feelings of internal stress. The modified Medical Outcomes Study Social Support Survey (mMOS-SS) and the SARS Appraisal Inventory (SAI) were also administered to measure participants’ perceived support and coping efficacy. Follow-up responses were gathered by the end of third-wave outbreak (October 2021). Results: A total of 51 CGPWD participated, of which, 33 (64.7%) suffered from probable depression (CES-D score ≥ 16). Participants also showed a significant increase in depression symptom scores at the three-month follow-up period (t = 2.25, p = 0.03). CGPWD with probable depression had less non-attachment awareness and higher scores in anxiety, stress, caregiving burden, and coronavirus impact (all p < 0.05) than those without. Conclusions: High prevalence of depressive symptoms was noted among our CGPWD sample and these symptoms seemed to worsen substantially. Contingent online mental health support should be prioritized to those CGPWD to reduce psychiatric morbidity and the global disease burden.

Psychiatric care in prisons

Prisoners with all types of psychiatric disorders are numerous in prisons. As a result, access to care is a priority in order to detect, orient and treat these patients. Thepsychiatric care system in prisons is based on a triptych composed of local care teams, regional medical- psychological services and inter-regional structures, such as specially equipped hospital units. Although policies have now worked to develop access to psychiatric care in prisons, there are still constraints, linked to security, demographics and institutional requirements.

Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study

The placebo effect across psychiatric disorders is still not well understood. In the present study, we conducted meta-analyses including meta-regression, and machine learning analyses to investigate whether the power of placebo effect depends on the types of psychiatric disorders. We included 108 clinical trials (32,035 participants) investigating pharmacological intervention effects on major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SCZ). We developed measures based on clinical rating scales and Clinical Global Impression scores to compare placebo effects across these disorders. We performed meta-analysis including meta-regression using sample-size weighted bootstrapping techniques, and machine learning analysis to identify the disorder type included in a trial based on the placebo response. Consistently through multiple measures and analyses, we found differential placebo effects across the three disorders, and found lower placebo effect in SCZ compared to mood disorders. The differential placebo effects could also distinguish the condition involved in each trial between SCZ and mood disorders with machine learning. Our study indicates differential placebo effect across MDD, BD, and SCZ, which is important for future neurobiological studies of placebo effects across psychiatric disorders and may lead to potential therapeutic applications of placebo on disorders more responsive to placebo compared to other conditions.

Psychiatric comorbidity and treatment outcomes in patients with opioid use disorder: Results from a multisite trial of buprenorphine-naloxone and methadone

BackgroundIndividuals treated for opioid use disorder (OUD) have high rates of psychiatric disorders potentially diminishing treatment outcomes. We examined long-term treatment experiences and outcomes by type of psychiatric disorder among participants who participated in the Starting Treatment with Agonist Replacement Therapies (START) study and its follow-up study. MethodsWe categorized the 593 participants who completed the Mini-International Neuropsychiatric Interview (MINI) during the START follow-up study into four mutually exclusive groups to indicate current psychiatric diagnosis: 1) bipolar disorder (BPD; n = 51), 2) major depressive disorder (MDD; n = 85), 3) anxiety disorder (AXD; n = 121), and 4) no comorbid mental disorder (NMD; n = 336). We compared participants’ baseline characteristics and treatment outcomes. ResultsGroups with mental disorders had worse substance use outcomes and poorer psychosocial functioning than the NMD group. Participants with BPD had significantly more self-reported days using opioids (Mean: 8.6 for BPD vs. 3.4 days for NMD, p < 0.01) and heroin (Mean: 6.4 for BPD vs. 2.0 for MDD, 3.1 days for NMD, p < 0.05) in the 30 days prior to the final interview. Compared to patients without mental disorders, patients with MDD spent more time engaged with OUD pharmacotherapy during the ∼16-month period between MINI and final interview (mean: 71.6 % vs. 50.6 %; p < 0.001). ConclusionsOur results show that treatment outcomes in individuals with OUD vary by psychiatric comorbidity groups, which supports the need for mental health assessment and treatment for psychiatric conditions in the context of pharmacotherapy for patients with OUD.

Immunological and hormonal mechanisms in Alzheimer's disease.

Alzheimer’s disease (AD) is a disorder which is today treated and approached at the crossroad of two medical specialties – psychiatry and neurology. The insidious onset which can often mimic depressive disorders or other type of psychiatric disorders, the behavioral changes, the paranoid thoughts usually send people to the psychiatrist, while the brain changes observed on magnetic resonance imaging (MRI) scans and other imaging techniques may indicate the need for neurological monitoring also. The complex symptomatology and progression of this dementia requires a multidisciplinary approach and recent studies focused on adding a third perspective: a metabolic one. The common findings regarding type 2 diabetes and AD made some researchers to informally name it “the third type diabetes”. This mini review aims to highlight the mechanisms through which brain insulin resistance can lead to cognitive impairment and to make a short overview of the current findings which demonstrate why insulin may be a promising adjunctive treatment of Alzheimer’s dementia, for certain patients.

The relationship between working alliance with peer mentors and eating psychopathology in a digital 6-week guided self-help intervention for anorexia nervosa.

ObjectiveThe quality of working alliance (WA) is associated with treatment outcomes across several types of psychiatric disorders and psychological interventions. This study examined the role of WA with peer mentors (people with lived experience of illness) and student mentors (graduated psychology students) in a 6‐week, digital, guided self‐help (GSH) intervention for anorexia nervosa.MethodNinety‐nine patients rated weekly, for 6 weeks: (a) eating psychopathology using the short version of the Eating Disorder Examination Questionnaire (EDE‐QS) and (b) WA with a student mentor (n = 14) or a peer mentor (n = 10). WA was assessed by asking patients the extent to which they felt comfortable working with their mentor and the extent to which they agreed with them on the goals for support. WA with mentors and the association with eating psychopathology change were measured on a session‐by‐session basis. The analysis involved a random intercepts cross‐lagged panel model.ResultsWA with peer mentors was slightly higher than WA with students (ES = 0.3). Peer mentors' WA in the previous session was significantly associated with eating psychopathology ratings in the next session. No significant relationship was found between the previous session's EDE‐QS scores and peer mentor alliance in the following session. In the student mentor group, there were no session‐by‐session associations between WA and eating psychopathology. However, greater WA with the student mentor across sessions was associated with less eating psychopathology.DiscussionThese findings suggest that clinical outcomes are in part associated with the characteristics of the mentor delivering guidance in an online GSH for eating disorders.

Murder she said – a review on mental health issues in intimate relationship violence

IntroductionViolence in intimate relationships is a prevalent worldwide health problem and it is underreported, underrecognized and underadressed by health care professionals.This problem affects women more commonly than men and occurs in heterosexual and same-sex relationships. Violence can include physical, emotional, sexual and financial abuse, as well as control over contraception or pregnancy and medical care and it tends to be repetitive, with an escalation in frequency and severity over time. Abused patients exhibit chronic physical and emotional symptoms and injuries resulting from physical and sexual violence.ObjectivesWe conducted a review on violence in intimate relationships and the impact on mental health of the victims.MethodsComprehensive search of literature in the medical databases MEDLINE, PsycINFO, SciELO using the keywords: women, violence, intimate relationship violence, mental health, self injury.ResultsResearch has established a relationship between violence and mental health outcomes among women and girls. Violence or inter-personal trauma render women vulnerable to a range of psychiatric symptoms - depression, post-traumatic stress disorder (PTSD), suicide, and substance use are most common. Women reporting bidirectional violence had higher rates of depression and PTSD. When examining differences in rates of psychiatric disorders by the type of violence, it was found that all types of violence were strongly associated with all types of psychiatric disorders. Severity of psychiatric symptoms increased stepwise with increasing severity of violence.ConclusionsCaring for patients in abusive relationships can be challeging - continuous supportive care improves patient outcomes. Physicians shoul be able to recognize and manage this situations in order prevent its negative outcomes.

Mapping relationships among schizophrenia, bipolar and schizoaffective disorders: A deep classification and clustering framework using fMRI time series

BackgroundPsychiatric disorders are categorized using self-report and observational information rather than biological data. There is also considerable symptomatic overlap between different types of psychiatric disorders, which makes diagnostic categorization and multi-class classification challenging. MethodsIn this work, we propose a unified framework for supervised classification and unsupervised clustering of psychotic disorders using brain imaging data. A new multi-scale recurrent neural network (MsRNN) model was developed and applied to fMRI time courses (TCs) for multi-class classification. The high-level representations of the original TCs were then submitted to a tSNE clustering model for visualizing the group differences between disorders. A leave-one-feature-out approach was used for disorder-related biomarker identification. ResultsWhen studying fMRI from schizophrenia, psychotic bipolar disorder, schizoaffective disorder, and healthy individuals, the accuracy of a 4-class classification reached 46%, significantly above chance. The hippocampus, supplementary motor area and paracentral lobule were discovered as the most contributing regional TCs in the multi-class classification. Beyond this, visualization of the tSNE clustering suggested that the disease severity can be captured and schizoaffective disorder (SAD) may be separated into two subtypes. SAD cluster1 has significantly higher Positive And Negative Syndrome Scale (PANSS) scores than SAD cluster2 in PANSS negative2 (emotional withdrawal), general2 (anxiety), general3 (guilt feelings), general4 (tension). ConclusionsThe proposed deep classification and clustering framework is not only able to identify psychiatric disorders with high accuracy, but also interpret the correlation between brain networks and specific psychiatric disorders, and reveal the relationship between them. This work provides a promising way to investigate a spectrum of similar disorders using neuroimaging-based measures.