Effects of strict COVID-19 lockdown on patients with obsessive-compulsive disorder compared to a clinical and a nonclinical sample.

BACKGROUND: Symptoms of obsessive-compulsive disorder (OCD) have been reported to increase during the COVID-19 lockdowns because of the hygiene requirements related to the pandemic. Patients with adjustment disorder (AD) may, in turn, represent a vulnerable population for identifiable stressors. In this study, we aimed at assessing potential symptoms changes in OCD patients during the lockdown in comparison with AD patients as well as versus healthy controls (HC). METHODS: During the COVID-related lockdown, we enrolled 65 patients and 29 HC. Participants were tested with four clinical rating scales (Yale-Brown obsessive-compulsive scale and Brown Assessment of Beliefs Scale for OCD patients; Beck Depression Inventory-II and State-Trait Anxiety Inventory-Y for each group) that had been also administered just before the Italian lockdown. RESULTS: Our results showed that during the lockdown: (i) the symptoms of depression and anxiety increased in all groups, but this increase was most pronounced in HC (p < 0.001); (ii) OCD symptoms severity did not increase, but the insight worsened (p = 0.028); (iii) the proportion of OCD patients showing hygiene-related symptoms increased (p = 0.031 for obsessions of contamination), whereas that of patients with checking-related symptoms decreased. CONCLUSIONS: The lockdown-induced psychological distress apparently changed the characteristics and the pattern of OCD symptoms expression but not their overall severity. This evidence confirms the heterogeneity and changing nature of OCD symptoms, strongly depending on the environmental circumstances.

Depression and Anxiety Symptoms "Among the Waves" of the COVID-19 Pandemic in Obsessive Compulsive Disorder and Adjustment Disorder Patients.

The COVID-19 pandemic and the associated restrictions caused great psychological suffering to the general population and psychiatric patients. We aimed to explore the course of depression and anxiety symptoms in obsessive compulsive disorder (OCD) patients, adjustment disorder (AD) patients, and participants without psychiatric disorders (control group, CG) across the different phases of the pandemic: the first lockdown, a temporary interruption of restrictions, and the second lockdown. Out of the 158 patients screened, we enrolled 46 OCD and 19 AD patients as well as 29 CG participants. The Beck Depression Inventory-II and the State-Trait Anxiety Inventory-Y were administered to all participants at each time point. The results showed different symptom severities among the groups throughout the whole study, with OCD patients always scoring higher than AD patients and the CG, and the AD patients always scoring higher than the CG. The symptom course within each group was different. OCD patients' symptoms sharply worsened during the first lockdown and then remained stable irrespective of the subsequent pandemic phases. In the AD and CG groups, symptoms waxed and waned following the fluctuations of the restriction provisions, with a complete return to the baseline when the restrictions were stopped only in the CG. These findings suggest that the influence of the pandemic and of the associated restrictions on depression and anxiety manifestations may vary depending on the particular pre-existing mental health status.

The effects of sustained COVID-19 emergency and restrictions on the mental health of subjects with serious mental illness: A prospective study.

Few longitudinal studies have so far investigated the impact of sustained COVID-19 among people with pre-existing psychiatric disorders. We conducted a prospective study involving people with serious mental illness (n = 114) and healthy controls (n = 41) to assess changes in the Perceived Stress Scale, Generalized Anxiety Disorder Scale, Patient Health Questionnaire, and Specific Psychotic Experiences Questionnaire scores 18 months after the COVID-19 pandemic outset. Subjects underwent interviews with a mental health professional in April 2020 and at the end of the local third wave (October 2021). A significant increase in perceived stress was found in healthy controls, especially females. Psychiatric patients showed a significant worsening of anxiety symptoms compared to baseline records (t = -2.3, p = 0.036). Patients who rejected vaccination had significantly higher paranoia scores compared to those willing to get vaccinated (U = 649.5, z = -2.02, p = 0.04). These findings indicate that COVID-19's sustained emergency may cause enduring consequences on mental health, soliciting further investigations.

Predicting the Severity of Lockdown-Induced Psychiatric Symptoms with Machine Learning.

During the COVID-19 pandemic, an increase in the incidence of psychiatric disorders in the general population and an increase in the severity of symptoms in psychiatric patients have been reported. Anxiety and depression symptoms are the most commonly observed during large-scale dramatic events such as pandemics and wars, especially when these implicate an extended lockdown. The early detection of higher risk clinical and non-clinical individuals would help prevent the new onset and/or deterioration of these symptoms. This in turn would lead to the implementation of public policies aimed at protecting vulnerable populations during these dramatic contingencies, therefore optimising the effectiveness of interventions and saving the resources of national healthcare systems. We used a supervised machine learning method to identify the predictors of the severity of psychiatric symptoms during the Italian lockdown due to the COVID-19 pandemic. Via a case study, we applied this methodology to a small sample of healthy individuals, obsessive-compulsive disorder patients, and adjustment disorder patients. Our preliminary results show that our models were able to predict depression, anxiety, and obsessive-compulsive symptoms during the lockdown with up to 92% accuracy based on demographic and clinical characteristics collected before the pandemic. The presented methodology may be used to predict the psychiatric prognosis of individuals under a large-scale lockdown and thus supporting the related clinical decisions.