Combining Mini-Mental State Examination and Montreal Cognitive Assessment for assessing the clinical efficacy of cholinesterase inhibitors in mild Alzheimer's disease: a pilot study.

Current drugs for Alzheimer's Disease (AD), such as cholinesterase inhibitors (ChEIs), exert only symptomatic activity. Different psychometric tools are needed to assess cognitive and non-cognitive dimensions during pharmacological treatment. In this pilot study, we monitored 33 mild-AD patients treated with ChEIs. Specifically, we evaluated the effects of 6 months (Group 1 = 17 patients) and 9 months (Group 2 = 16 patients) of ChEIs administration on cognition with the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Frontal Assessment Battery (FAB), while depressive symptoms were measured with the Hamilton Depression Rating Scale (HDRS). After 6 months (Group 1), a significant decrease in MoCA performance was detected. After 9 months (Group 2), a significant decrease in MMSE, MoCA, and FAB performance was observed. ChEIs did not modify depressive symptoms. Overall, our data suggest MoCA is a potentially useful tool for evaluating the effectiveness of ChEIs.

Impact of Stress during COVID-19 Pandemic in Italy: A Study on Dispositional and Behavioral Dimensions for Supporting Evidence-Based Targeted Strategies.

The COVID-19 pandemic caused critical mental health issues and lifestyle disruptions. The aim of this study was to explore, during the lockdown of second-wave contagions in Italy, how stress was affected by dispositional (personality factors and intolerance to uncertainty) and behavioral (coping strategies) dimensions, how these variables differed among sex, age, educational, professional, and health groups, and how the various changes in work and daily routine intervened in the psychological impact of the emergency. Our results highlight that women, the youngs, students/trainees, those with chronic diseases, those who stopped their jobs due to restrictions, and those who left home less than twice a week were more stressed, while health professionals showed lower levels of the same construct. Those with higher levels of stress used more coping strategies based on avoidance, which positively correlated with age, agreeableness, conscientiousness, and intolerance to uncertainty, and negatively with openness. Stress levels also positively correlated with agreeableness, conscientiousness, intolerance to uncertainty, and seeking of social support, and negatively with openness, a positive attitude, and a transcendent orientation. Finally, stress was predicted mainly by behavioral dimensions. Our results are discussed and framed within the literature, as important insights for targeted intervention strategies to promote health even in emergencies.

A narrative review on insomnia and hypersomnolence within Major Depressive Disorder and bipolar disorder: A proposal for a novel psychometric protocol.

Sleep disorders have become increasingly prevalent, with many adults worldwide reporting sleep dissatisfaction. Major Depressive Disorder (MDD) and Bipolar Disorder (BD) are common conditions associated with disrupted sleep patterns such as insomnia and hypersomnolence. These sleep disorders significantly affect the progression, severity, treatment, and outcome of unipolar and bipolar depression. While there is evidence of a connection between sleep disorders and depression, it remains unclear if sleep features differ between MDD and BD. In light of this, this narrative review aims to: (1) summarize findings on common sleep disorders like insomnia and hypersomnolence, strongly linked to MDD and BD; (2) propose a novel psychometric approach to assess sleep in individuals with depressive disorders. Despite insomnia seems to be more influent in unipolar depression, while hypersomnolence in bipolar one, there is no common agreement. So, it is essential adopting a comprehensive psychometric protocol for try to fill this gap. Understanding the relationship between sleep and MDD and BD disorders are crucial for effective management and better quality of life for those affected.

A network study to differentiate suicide attempt risk profiles in male and female patients with major depressive disorder.

Suicide attempts are a possible consequence of Major Depressive Disorder (MDD), although their prevalence varies across different epidemiological studies. Suicide attempt is a significant predictor of death by suicide, highlighting its importance in understanding and preventing tragic outcomes. Researchers are increasingly recognizing the need to study the differences between males and females, as several distinctions emerge in terms of the characteristics, types and motivations of suicide attempts. These differences emphasize the importance of considering gender-specific factors in the study of suicide attempts and developing tailored prevention strategies. We conducted a network analysis to represent and investigate which among multiple neurocognitive, psychosocial, demographic and affective variables may prove to be a reliable predictor for identifying the 'suicide attempt risk' (SAR) in a sample of 81 adults who met DSM-5 criteria for MDD. Network analysis resulted in differences between males and females regarding the variables that were going to interact and predict the SAR; in particular, for males, there is a stronger link toward psychosocial aspects, while for females, the neurocognitive domain is more relevant in its mnestic subcomponents. Network analysis allowed us to describe otherwise less obvious differences in the risk profiles of males and females that attempted to take their own lives. Different neurocognitive and psychosocial variables and different interactions between them predict the probability of suicide attempt unique to male and female patients.

The dynamic interaction between symptoms and pharmacological treatment in patients with major depressive disorder: the role of network intervention analysis.

INTRODUCTION: The Major Depressive Disorder (MDD) is a mental health disorder that affects millions of people worldwide. It is characterized by persistent feelings of sadness, hopelessness, and a loss of interest in activities that were once enjoyable. MDD is a major public health concern and is the leading cause of disability, morbidity, institutionalization, and excess mortality, conferring high suicide risk. Pharmacological treatment with Selective Serotonin Reuptake Inhibitors (SSRIs) and Serotonin Noradrenaline Reuptake Inhibitors (SNRIs) is often the first choice for their efficacy and tolerability profile. However, a significant percentage of depressive individuals do not achieve remission even after an adequate trial of pharmacotherapy, a condition known as treatment-resistant depression (TRD). METHODS: To better understand the complexity of clinical phenotypes in MDD we propose Network Intervention Analysis (NIA) that can help health psychology in the detection of risky behaviors, in the primary and/or secondary prevention, as well as to monitor the treatment and verify its effectiveness. The paper aims to identify the interaction and changes in network nodes and connections of 14 continuous variables with nodes identified as "Treatment" in a cohort of MDD patients recruited for their recent history of partial response to antidepressant drugs. The study analyzed the network of MDD patients at baseline and after 12 weeks of drug treatment. RESULTS: At baseline, the network showed separate dimensions for cognitive and psychosocial-affective symptoms, with cognitive symptoms strongly affecting psychosocial functioning. The MoCA tool was identified as a potential psychometric tool for evaluating cognitive deficits and monitoring treatment response. After drug treatment, the network showed less interconnection between nodes, indicating greater stability, with antidepressants taking a central role in driving the network. Affective symptoms improved at follow-up, with the highest predictability for HDRS and BDI-II nodes being connected to the Antidepressants node. CONCLUSION: NIA allows us to understand not only what symptoms enhance after pharmacological treatment, but especially the role it plays within the network and with which nodes it has stronger connections.

Physical Activity, Sun Exposure, Vitamin D Intake and Perceived Stress in Italian Adults.

The last decades of global development have, due to rapid urbanization, pressuring entire populations to changes in lifestyle and dietary habits, led to an increase in the prevalence of mental disorders, including stress. This study explored how lifestyle and dietary factors, such as physical activity, sun exposure, and vitamin D intake are related to perceived stress in a Mediterranean-based population. Physical activity level was evaluated using the international physical activity questionnaires (IPAQ), sun exposure was evaluated using the sunlight exposure measurement questionnaire (SEM-Q), and validated food frequency questionnaires (FFQs) were used to assess dietary intakes. The perceived stress of the study participants was evaluated using the perceived stress scale (PSS). Multivariate logistic regression models were used to test for potential associations. In the most adjusted model, an inverse association between physical activity level, sunlight exposure, vitamin D intake, and high perceived stress was found (OR = 0.72, 95% CI: 0.51, 1.00, OR = 0.72, 95% CI: 0.52, 0.99, OR = 0.69, 95% CI: 0.53, 0.89, respectively). However, when stratifying the population by level of physical activity, the retrieved associations with sunlight exposure and dietary vitamin D intake were significant only among those individuals reporting being moderately to highly physically active (OR = 0.16, 95% CI: 0.08, 0.33 and OR = 0.46, 95% CI: 0.28, 0.76, respectively), while results on low physically active participants were null. In conclusion, this study demonstrated that higher dietary intake of vitamin D and sunlight exposure are associated with a lower likelihood of having high perceived stress among physically active individuals.

Predictors of functional outcome in patients with major depression and bipolar disorder: A dynamic network approach to identify distinct patterns of interacting symptoms.

The purpose of this study is to use a dynamic network approach as an innovative way to identify distinct patterns of interacting symptoms in patients with Major Depressive Disorder (MDD) and patients with Bipolar Type I Disorder (BD). More precisely, the hypothesis will be testing that the phenotype of patients is driven by disease specific connectivity and interdependencies among various domains of functioning even in the presence of underlying common mechanisms. In a prospective observational cohort study, hundred-forty-three patients were recruited at the Psychiatric Clinic "Villa dei Gerani" (Catania, Italy), 87 patients with MDD and 56 with BD with a depressive episode. Two nested sub-groups were treated for a twelve-week period, which allowed us to explore differences in the pattern of symptom distribution (central vs. peripheral) and their connectedness (strong vs weak) before (T0) and after (T1) treatment. All patients underwent a complete neuropsychological evaluation at baseline (T0) and at T1. A network structure was computed for MDD and BD patients at T0 and T1 from a covariance matrix of 17 items belonging to three domains-neurocognitive, psychosocial, and mood-related (affective) to identify what symptoms were driving the networks. Clinically relevant differences were observed between MDD and BD, at T0 and after 12 weeks of pharmacological treatment. At time T0, MDD patients displayed an affective domain strongly connected with the nodes of psychosocial functioning, while direct connectivity of the affective domain with the neurocognitive cluster was absent. The network of patients with BD, in contrast, revealed a cluster of highly interconnected psychosocial nodes but was guided by neurocognitive functions. The nodes related to the affective domain in MDD are less connected and placed in the periphery of the networks, whereas in BD they are more connected with psychosocial and neurocognitive nodes. Noteworthy is that, from T0 to T1 the "Betweenness" centrality measure was lower in both disorders which means that fewer "shortest paths" between nodes pass through the affective domain. Moreover, fewer edges were connected directly with the nodes in this domain. In MDD patients, pharmacological treatment primarily affected executive functions which seem to improve with treatment. In contrast, in patients with BD, treatment resulted in improvement of overall connectivity and centrality of the affective domain, which seems then to affect and direct the overall network. Though different network structures were observed for MDD and BD patients, data suggest that treatment should include tailored cognitive therapy, because improvement in this central domain appeared to be fundamental for better outcomes in other domains. In sum, the advantage of network analysis is that it helps to predict the trajectory of future phenotype related disease manifestations. In turn, this allows new insights in how to balance therapeutic interventions, involving different fields of function and combining pharmacological and non-pharmacological treatment modalities.

Professional quality of life and psychopathological symptoms among first-line healthcare workers facing COVID-19 pandemic: an exploratory study in an Italian southern hospital.

Background: The COVID-19 pandemic has significantly affected the mental health of healthcare workers, who have taken on the major problems triggered by the emergency. The mental consequences concern high levels of insomnia, anxiety, depression and burnout, which inevitably affect their professional quality of life too. Objective: The aim of this study was to analyze the relationship between psychopathological symptoms (tested with the Depression Anxiety Stress Scale, DASS-21) and professional quality of life (measured with the Professional Quality of Life Scale, ProQol) in a hospital of southern Italy. Methods: 204 healthcare workers were recruited by non-probabilistic sampling and divided by age, gender, work roles (physicians, nurses and intermediate care technicians) and clinical departments (Cardio-medicine, Infectious Diseases, Emergency Medicine, First Aid, Obstetrics and Pneumology). Results: The results showed higher levels of Secondary Traumatic Stress, Depression, Anxiety and Stress in women than in men. Physicians and nurses experienced lower levels of Compassion Satisfaction but higher Burnout than intermediate care technicians; likewise, nurses were more anxious than physicians. The Emergency Medicine had higher scores in Compassion Satisfaction than Infectious Disease, Pneumology, Obstetrics and Cardio-Medicine. Conclusion: In light of what has been said so far, it appears essential to intervene on the first mild signs of Burnout and Secondary Traumatic Stress, because they precede the onset of Depression, Stress and Anxiety in healthcare workers.

"Don't Touch Your Face!" The Contribution of Habit Reversal in the COVID-19 Pandemic.

The Habit Reversal Training (HRT) is a behavioral procedure for treating the so-called nervous habits, such as nail biting, hair pulling and thumb sucking. In addition to being an established clinical procedure, HRT is also a strategy for behavioral change that can serve the entire community. For this reason, this review aims to explore the studies proposing the use of HRT for the reduction of hand-to-face habits in the context of COVID-19 pandemic. Touching one's nose, mouth and eyes, indeed, is one of the means of virus transmission that many awareness campaigns seek to highlight. After an overview of how HRT works and of the current epidemiological situation, studies supporting Habit Reversal Training for the reduction of risky hand-to-face habits are presented. The possible strategies are then exposed and critically discussed to identify their limitations and propose a new version according to the Relational Frame Theory.