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BACKGROUND: Burnout is a pervasive issue among medical students, exhibiting a high prevalence that jeopardizes their academic success and may also predispose them to more severe affective disorders such as depression. This study aims to explore the complex relationships between psychological capital (PsyCap), general social support, educational satisfaction, and burnout, and how these factors collectively influence dropout intentions. METHODS: A non-probabilistic convenience sample was collected through an online survey from first- and second-year medical students at a Faculty of Medicine in Portugal. The survey employed psychometric instruments to measure burnout (BAT-12), social support (F-SozU K-6), PsyCap (CPC-12R), satisfaction with education, and dropout intentions (Screening Instrument for Students At-Risk of Dropping Out). Structural equation modeling was applied to analyze the data from 351 participants. RESULTS: The model demonstrated a significant positive association between burnout and dropout intentions (ßÌ = 0.37; p < 0.001), underscoring burnout as a direct correlate of dropout intentions alongside educational satisfaction (ßÌ = -0.25; p = 0.003) and PsyCap (ßÌ = -0.22; p = 0.005). Higher social support is associated with reduced burnout (ßÌ = -0.28; p < 0.001) and increased educational satisfaction (ßÌ = 0.22; p = 0.002). LIMITATIONS: The non-probabilistic sampling method prevents the generalization of the findings. The cross-sectional data do not permit the inference of temporal relationships between the studied variables. CONCLUSIONS: These findings emphasize the importance that burnout may have on dropout intentions, and contribute to the understanding of affective syndromes such as burnout in educational settings.
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The cerebellar cognitive affective syndrome is a neuropsychiatric syndrome composed of affective (anxiety, depression, euphoria, and emotional lability) and cognitive symptoms (executive, attentional, and visuospatial deficits) that was described in the 1990s. We present the case of a 49-year-old woman with a history of an acute neurological episode at the age of 28, after which she reported a change in personality, brief and alternating periods of depression, hypomania, and mixed episodes, and cognitive impairment that had a major impact on her personal and occupational level of functioning. She was initially diagnosed with bipolar disorder, but a clinical, neuropsychological, and imaging re-evaluation prompted a diagnostic reconsideration in favor of a cerebellar cognitive affective syndrome. This enabled therapeutical and prognostic refinement. Here, we discuss the diagnostic challenges of this syndrome and the implications that an accurate diagnosis has for patients.
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INTRODUCTION: The use of social media is an extremely popular activity, with an average time spent of two and a half hours daily. The number of users continues to rise, with 4.65 billion around the world in 2022, approximately 58.7% of the world population. A rising number of studies show that a minority of these persons will develop a behavioral addiction on social media. The aim of this study was to understand if the use of a specific social media platform predicts increased addictive potential. MATERIAL AND METHODS: A cross-sectional sample of 300 persons (aged 18 years-old or older, 60.33% female), completed an online survey including sociodemographic questions, data regarding the use of social media and the Bergen Social Media Addiction Scale (BSMAS). Linear and logistic regression models were performed to determine the risk for each media platform. RESULTS: Instagram® use was a significant predictor of higher scores on the BSMAS (B 2.51; p < 0.0001; CI 1.33 - 3.69). The use of other platforms including Facebook® (B -0.31), Twitter® (B 1.38) and Pinterest® (B -0.15) was not found to predict a higher risk of social media addiction. CONCLUSION: Instagram® scored a higher grade in BSMAS scale, with statistical significance, which could suggest a higher addictive potential. More research is needed to establish the direction of this relationship, since the cross-sectional study design does not allow inferences about directionality.
Introdução: A utilização de redes sociais é uma atividade bastante popular nos dias de hoje, com um tempo médio de utilização diária de duas horas e meia. O número de utilizadores continua a aumentar, perfazendo 4,65 mil milhões em 2022, aproximadamente 58,7% da população mundial. Um número crescente de estudos mostra que uma minoria destes utilizadores irá desenvolver uma adicção comportamental às redes sociais. O objetivo deste estudo é compreender se o uso de uma plataforma de rede social específica é um preditor de maior potencial adictivo. Material e Métodos: Uma amostra de 300 pessoas (idade igual ou superior a 18 anos, 60,33% sexo feminino), completou um questionário online, com fatores sociodemográficos, dados acerca do uso de redes sociais e a Bergen Social Media Addiction Scale (BSMAS). Foram feitas análises de regressão linear e logística para determinar o potencial de adicção de cada plataforma. Resultados: A utilização do Instagram® foi um preditor significativo para pontuações mais altas na BSMAS (B 2,51; p < 0,0001; CI 1,33 - 3,69). O uso de outras plataformas, incluindo o Facebook® (B -0,31), o Twitter® (B 1,38) e o Pinterest® (B -0,15) não pareceu ser um preditor de maior risco adictivo Conclusão: O Instagram® atingiu uma maior classificação na BSMAS, com significância estatística, o que pode sugerir um maior potencial adictivo. É necessária mais investigação para estabelecer a direção desta relação, visto que o desenho transversal não permite inferências sobre a direccionalidade.
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Behavior, Addictive , Social Media , Humans , Female , Adolescent , Male , Cross-Sectional Studies , Portugal , Behavior, Addictive/epidemiology , Surveys and QuestionnairesABSTRACT
Present time nosology has its roots in Kraepelin's demarcation of schizophrenia and bipolar disorder. However, accumulating evidence has shed light on several commonalities between the two disorders, and some authors have advocated for the consideration of a disease continuum. Here, we review previous genetic, biological and pharmacological findings that provide the basis for this conceptualization. There is a cross-disease heritability, and they share single-nucleotide polymorphisms in some common genes. EEG and imaging patterns have a number of similarities, namely reduced white matter integrity and abnormal connectivity. Dopamine, serotonin, GABA and glutamate systems have dysfunctional features, some of which are identical among the disorders. Finally, cellular calcium regulation and mitochondrial function are, also, impaired in the two.
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Bipolar Disorder , Schizophrenia , Humans , Bipolar Disorder/drug therapy , Bipolar Disorder/genetics , Schizophrenia/drug therapy , Schizophrenia/geneticsSubject(s)
COVID-19 , Psychiatry , Humans , SARS-CoV-2 , Cross-Sectional Studies , Prevalence , COVID-19/epidemiologyABSTRACT
BACKGROUND: While shared clinical decision-making (SDM) is the preferred approach to decision-making in mental health care, its implementation in everyday clinical practice is still insufficient. The European Psychiatric Association undertook a study aiming to gather data on the clinical decision-making style preferences of psychiatrists working in Europe. METHODS: We conducted a cross-sectional online survey involving a sample of 751 psychiatrists and psychiatry specialist trainees from 38 European countries in 2021, using the Clinical Decision-Making Style - Staff questionnaire and a set of questions regarding clinicians' expertise, training, and practice. RESULTS: SDM was the preferred decision-making style across all European regions ([central and eastern Europe, CEE], northern and western Europe [NWE], and southern Europe [SE]), with an average of 73% of clinical decisions being rated as SDM. However, we found significant differences in non-SDM decision-making styles: participants working in NWE countries more often prefer shared and active decision-making styles rather than passive styles when compared to other European regions, especially to the CEE. Additionally, psychiatry specialist trainees (compared to psychiatrists), those working mainly with outpatients (compared to those working mainly with inpatients) and those working in community mental health services/public services (compared to mixed and private settings) have a significantly lower preference for passive decision-making style. CONCLUSIONS: The preferences for SDM styles among European psychiatrists are generally similar. However, the identified differences in the preferences for non-SDM styles across the regions call for more dialogue and educational efforts to harmonize practice across Europe.
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Patient Participation , Psychiatry , Humans , Decision Making , Cross-Sectional Studies , Clinical Decision-Making , Surveys and QuestionnairesABSTRACT
Communication skills are paramount in all areas of medicine but particularly in psychiatry due to the challenges posed by mental health patients and the essential role of communication from diagnosis to treatment. Despite the prevalence of psychiatric disorders in different medical specialties, particularly in primary care settings, communication skills in psychiatry and their training are not well studied and are often not included in the undergraduate medical curriculum. Our paper explores the relevance of teaching communication competencies in psychiatry for undergraduate medical students. Our work focused on reviewing the methods for teaching communication skills to undergraduate students in Psychiatry. Eleven studies were selected to be included in this review. We found considerable heterogeneity among methods for teaching communication skills but also some common elements such as the use of simulated patients and providing feedback. This review has identified two models: the Calgary-Cambridge interview model and the Kolb cycle-based model. However, most studies still lack a theoretical background model. We believe that the inclusion of communication skills training in medical curricula is fundamental to teaching medical students general communication skills but also specific training on establishing adequate communication with psychiatric patients. However, more research is needed to determine the best method for training but also regarding its translation to patient care and cost-effectiveness.
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Objective: The coronavirus disease 2019 (COVID-19) pandemic has had a major impact globally. While sleep problems have increased during the pandemic, their impact on specific populations is less well known. The objective of this study was to measure the impact of the COVID-19 pandemic on sleep and how it correlates with the feeling of isolation in individuals aged ≥ 50 years.Methods: A cross-sectional study was conducted using data from the Survey of Health, Aging, and Retirement conducted between June and August 2020. A multivariate logistic regression model was performed to analyze the outcome "more or less trouble sleeping since the outbreak" and its main predictors.Results: The mean ± SD age of the participants was 71 ± 9 years. Since the outbreak, 29% reported a deterioration of their quality of sleep. Being male and older were found to be significant predictors of more sleep complaints (OR = 1.13; P = .004; CI, 1.04-1.23 and OR = 1.02; P = .000; CI, 1.02-1.03, respectively). Moreover, those who claimed that they often felt alone or more loneliness since the beginning of the outbreak also had more trouble sleeping (OR = 1.21; P = .002; CI, 1.07-1.37 and OR = 4.06; P = .000; CI, 2.75-5.99, respectively).Conclusions: Male sex, older age, and loneliness are associated with more sleeping difficulties since the beginning of the COVID-19 pandemic. These findings can aid health authorities to address sleep issues in this vulnerable population more directly.
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COVID-19 , Sleep Wake Disorders , Aged , Cross-Sectional Studies , Female , Humans , Male , Pandemics , SARS-CoV-2 , Sleep , Sleep Wake Disorders/epidemiologyABSTRACT
INTRODUCTION: About one-third of patients with epilepsy have a refractory form which is associated with important economic and psychosocial burden. Most of these patients also suffer from comorbidities. One of the most frequent is cognitive impairment. Resective surgery or neuromodulation techniques may improve seizure control. Several factors have been proposed as potential predictors of the success of surgery regarding seizure frequency. We aimed to study preoperative cognitive performance as a predictor of the epilepsy surgery outcome. METHODS: In this ambispective study we studied total intelligence quotients (IQ) measured before surgery with the Wechsler Adult Intelligence Scale (WAIS) as a potential predictor of Engel Class at 1â¯year after surgery. Then we included IQ in a multivariate model and tested its performance. RESULTS: Preoperative IQ was a significant and independent predictor of the Engel Class at 1â¯year after surgery (OR 0.94; CI 0.90-0.98; pâ¯=â¯0.007). The multivariate model including the age at epilepsy onset, education level, sex, and the type of surgery (resective versus palliative surgery) showed an area under the ROC curve of 0.85. CONCLUSIONS: A low intelligence level may constitute a marker of worse prognosis after epilepsy surgery. However, other predictors should also be considered when evaluating surgical candidates.
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Epilepsy , Adult , Epilepsy/diagnosis , Epilepsy/psychology , Epilepsy/surgery , Humans , Intelligence , Intelligence Tests , Seizures/surgery , Treatment OutcomeABSTRACT
Translational psychiatry has been a hot topic in Neurosciences research. The authors present a commentary on the relevant findings from a transdiagnostic study applicable to clinic practice. Additional discussion on conceptual and clinical insight into this current broad line of research is explored in the integration of multi-level paradigm in Psychiatry research.
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BACKGROUND: The therapeutic options for neurobehavioral disorders are still limited, and in many cases, they lack a satisfactory balance between efficacy and side effects. OBJECTIVES: This work aims to review current evidence regarding the potential contribution of psychedelics and hallucinogens to the discovery of new drugs for treating different psychiatric disorders. DISCUSSION: Ayahuasca/N,N-dimethyltryptamine (DMT), lysergic acid diethylamide (LSD), and psilocybin have evidence supporting their use in depression, and psilocybin and ayahuasca have also shown good results in treatment-resistant depression. In randomized controlled trials (RCTs) conducted with anxious patients, there were symptomatic improvements with psilocybin and LSD. Psilocybin diminished Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores in a small obsessive- compulsive disorder (OCD) sample. The evidence is less robust regarding substance use disorders, but it suggests a possible role for LSD and psilocybin in alcohol use disorders and for psilocybin in tobacco addiction. In a clinical setting, these substances seem to be safe and well-tolerated. Their mechanisms of action are not fully elucidated, but there seems to be a preponderant role of 5-hydroxytryptamine (5HT) 2A agonism, as well as connectivity changes within the default mode network (DMN) and amygdala and some other molecular modifications. CONCLUSION: The studies underlying the conclusions have small samples and are heterogeneous in their methods. However, the results suggest that the use of psychedelics and hallucinogens could be considered in some disorders. More studies are needed to reinforce their evidence as potential new drugs.
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Hallucinogens , Psychiatry , Substance-Related Disorders , Hallucinogens/adverse effects , Humans , Lysergic Acid Diethylamide/pharmacology , Lysergic Acid Diethylamide/therapeutic use , Psilocybin/pharmacology , Psilocybin/therapeutic use , Substance-Related Disorders/drug therapyABSTRACT
OBJECTIVES: The present work reviews current evidence regarding the contribution of machine learning to the discovery of new drug targets. METHODS: Scientific articles from PubMed, SCOPUS, EMBASE, and Web of Science Core Collection published until May 2021 were included in this review. RESULTS: The most significant areas of research are schizophrenia, depression and anxiety, Alzheimer´s disease, and substance use disorders. ML techniques have pinpointed target gene candidates and pathways, new molecular substances, and several biomarkers regarding psychiatric disorders. Drug repositioning studies using ML have identified multiple drug candidates as promising therapeutic agents. CONCLUSION: Next-generation ML techniques and subsequent deep learning may power new findings regarding the discovery of new pharmacological agents by bridging the gap between biological data and chemical drug information.
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Alzheimer Disease , Psychiatry , Schizophrenia , Alzheimer Disease/drug therapy , Drug Repositioning/methods , Humans , Machine Learning , Psychiatry/methodsABSTRACT
BACKGROUND: There is increasing evidence regarding the influence of the intestinal microbiota on the disease processes of various organs and systems. Dysbiosis, that is, alteration of the composition and function of the microbiota may constitute an important risk factor for the development of mental disorders, namely, schizophrenia. OBJECTIVE: This works aims to review current evidence regarding the pathological mechanisms leading from dysbiosis to schizophrenia and in particular the deficit syndrome in schizophrenia. METHODS: Scientific articles from PubMed, SCOPUS, EMBASE, and Web of Science Core Collection published between September 2017 and December 2020 were included in this review. RESULTS: The commensal intestinal flora plays an important role in neurodevelopment. In the presence of dysbiosis, this maturation gets disturbed, resulting in the modification of brain structures and inflammatory responses at the intestinal, systemic, and Central Nervous System (CNS) levels. These disturbances may be linked to the development of symptoms of the disease. The microbiota exerts its influence on the CNS through several pathways, however, in this paper we focused on the membrane hypothesis and the inflammatory hypothesis. We explored the evidence concerning the use of probiotics, prebiotics, and fecal transplants. CONCLUSION: Although there is no consensus regarding the alterations that could constitute a risk factor for schizophrenia, some of the species appear to be more frequently altered, and their relationship with the host is dysregulated in patients at risk and with established schizophrenia, particularly in deficit schizophrenia.
Subject(s)
Brain/metabolism , Dysbiosis/complications , Gastrointestinal Microbiome/physiology , Inflammation/metabolism , Schizophrenia/etiology , Central Nervous System/growth & development , Central Nervous System/metabolism , Dysbiosis/metabolism , Fecal Microbiota Transplantation , Humans , Intestines/microbiology , Prebiotics , Probiotics/metabolismABSTRACT
OBJECTIVE: With this study, we aimed to assess the importance of including psychiatric disorders in a comprehensive prediction model for epilepsy surgery. METHODS: Ambispective observational study with a sample of adults who underwent resective surgery. Participants were evaluated, before and one year after surgery, to collect data regarding their neurological and psychiatric history. The one-year post-surgical outcome was classified according to the Engel Outcome Scale. Previously identified predictors of post-surgical Engel Class were included in a logistic regression model. Then, the accuracy of alternative predictive models, including or excluding, past and current psychiatric diagnoses, were tried. RESULTS: One hundred and forty-six people participated in this study. The inclusion of psychiatric diagnosis resulted in a model with a higher AUC curve, however, the Delong method showed no significant statistical differences between the models. SIGNIFICANCE: Despite the fact that presurgical psychiatric diagnoses have shown to contribute to the prediction of epilepsy surgery outcome they do not contribute to a significant improvement of predictive models.
Subject(s)
Epilepsy , Mental Disorders , Adult , Electroencephalography , Epilepsy/diagnosis , Epilepsy/surgery , Humans , Logistic Models , Mental Disorders/diagnosis , Mental Disorders/surgery , Postoperative Complications/psychology , Retrospective Studies , Treatment OutcomeABSTRACT
INTRODUCTION: In March 2020, the World Health Organization declared COVID-19 as a pandemic, and Portugal reported its initial cases. In this study, we aimed to determine the impact of COVID-19 on Portuguese individuals aged over 60 years old. MATERIAL AND METHODS: We performed a cross-sectional study using data from the Survey of Health, Ageing and Retirement in Europe (SHARE 8: COVID-19 Survey). We selected a sample of 1080 noninstitutional Portuguese individuals aged ≥ 60 years. RESULTS: The study sample consisted of 605 (56%) women and 475 (44%) men, with a mean age of 70 ± 9.1 years. In total, 80% of the participants experienced higher levels of anxiety, 73% felt more depressed and 30% experienced additional sleep problems comparedto the period before the pandemic. Interestingly, there were no statistically significant differences between the sexes or the two selected age groups (60 - 74 and over 75 years old) regarding the incidence of these changes. Only 23%, of those that were interviewed maintained their walking routines. In addition, only 8% of the participants continued visiting family members as frequently as before. While 8% of the participants were refused some form of medical treatment, 56% claimed that they experienced healthcare delays. However,only 15% of the participants reported that their health status worsened during the pandemic. DISCUSSION: The pandemic has had a significant impact on Portuguese individuals aged ≥ 60 years; which is in agreement with the findings of previous international studies. It changed the participants' routines and increased their anxiety and depression levels. Despite the deterioration of healthcare services, most participants did not experience worsening of their health status. CONCLUSION: In conclusion, a COVID-19 pandemic had a significant impact on the elderly population, particularly regarding their mental health.
Introdução: Em março de 2020, a COVID-19 foi declarada pandemia pela Organização Mundial da Saúde e Portugal registou os seus primeiros casos. Este estudo visou determinar o impacto da COVID-19 na população portuguesa maior de 60 anos. Material e Métodos: Trata-se de um estudo observacional transversal que analisa várias variáveis de saúde, comportamentais, sociais e económicas. Utilizaram-se dados do projecto Survey of Health, Ageing and Retirement (SHARE 8: COVID-19 Survey), seleccionando uma amostra de 1080 portugueses não institucionalizados e maiores de 60 anos. Resultados: A amostra englobou 605 mulheres (56%) e 475 homens (44%), com idade média de 70 ± 9,1 anos. No total, 80% dos participantes notou aumento da ansiedade, 73% sentiu-se mais deprimido e 30% considerou que o seu sono piorou em relação ao período anterior à pandemia. Não houve diferenças estatisticamente significativas entre os sexos ou as duas faixas etárias analisadas (60 - 74 e ≥ 75 anos) quanto à incidência destas alterações. No respeitante a saídas de casa, apenas 23% dos entrevistados manteve os hábitos de passeio e 8% manteve as visitas a familiares no seu padrão habitual. Relativamente ao acesso a cuidados médicos, a 8% foi negado algum tratamento e 56% queixou-se do adiamento dos cuidados. Apenas 13% referiu um agravamento do seu estado de saúde durante a pandemia. Discussão: Este trabalho mostra que esta pandemia impactou a população portuguesa com mais de 60 anos, o que está em linha com o reportado noutros estudos internacionais. Os hábitos alteraram-se, e a ansiedade e depressão aumentaram. Apesar da deterioração dos cuidados de saúde, a maioria dos participantes não notou agravamento do seu estado de saúde. Conclusão: Em conclusão, a pandemia por COVID-19 teve um impacto significativo na população idosa particularmente no que concerne à sua saúde mental.
Subject(s)
COVID-19 , Aged , Aging , Anxiety , Cross-Sectional Studies , Depression , Female , Humans , Male , Middle Aged , Pandemics , Portugal/epidemiology , Retirement , SARS-CoV-2ABSTRACT
Aim: Our study aimed to test whether plasma acetylcholinesterase and butyrylcholinesterase enzyme activity were related to the presence and intensity of delirium in acute stroke patients. Methods: We carried out a matched (age and gender) case-control study, in a sample of consecutive patients with an acute infarct or intracerebral haemorrhage (≤7 days). We assessed delirium using the DSM-5 criteria and the Delirium Rating Scale, and we measured plasma acetylcholinesterase and butyrylcholinesterase enzyme activity after the patient's admission in the stroke unit and before hospital discharge. Mantel-Haenszel's chi-square was used to test bivariate associations between cases (delirious patients) and controls (non-delirious patients). Results: At admission in the stroke unit, cases and controls did not present significant differences in plasma acetylcholinesterase or butyrylcholinesterase activity. At hospital discharge (18 cases and 21 controls) patients who have had delirium at admission had higher levels of butyrylcholinesterase activity. Butyrylcholinesterase activity may secondarily increase due to the inflammatory process associated with neuronal dysfunction in delirium patients.
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The aim of this study was to determine the rate and types of lifetime psychiatric disorders, as well as their predictors, in a sample of people with refractory epilepsy. Demographic, neurological, psychiatric and neuropsychological data, from people with refractory epilepsy, were registered at the pre-surgical interview. Linear regression was used to determine predictors. One hundred and ninety-one participants were included. Forty-six percent of our sample had at least one previous psychiatric diagnosis, most frequently depressive (64%), anxiety (10%), substance use (10%) and psychotic disorders (6%). Patients with a right-side epileptogenic zone had an increased risk for these disorders (OR 2.36; CI 1.22-4.56; p = 0.01). Specific epilepsy-related factors may raise the risk of developing a psychiatric disorder. Our study adds evidence to support a bidirectional relationship between epilepsy and mental health.