During the current COVID-19 disease emergency, it is not only an ethical imperative but also a public health responsibility to keep the network of community psychiatry services operational, ...particularly for the most vulnerable subjects (those with mental illness, disability, and chronic conditions). At the same time, it is necessary to reduce the spread of the COVID-19 disease within the outpatient and inpatient services affiliated with Mental Health Departments. These instructions, first published online on 16 March 2020 in their original Italian version, provide a detailed description of actions, proposed by the Italian Society of Epidemiological Psychiatry, addressed to Italian Mental Health Departments during the current COVID-19 pandemic. The overall goal of the operational instructions is to guarantee, during the current health emergency, the provision of the best health care possible, taking into account both public health necessities and the safety of procedures. These instructions could represent a useful resource to mental health providers, and stakeholders to face the current pandemic for which most of Mental Health Departments worldwide are not prepared to. These instructions could provide guidance and offer practical tools which can enable professionals and decision makers to foresee challenges, like those already experienced in Italy, which in part can be avoided or minimised if timely planned. These strategies can be shared and adopted, with the appropriate adjustments, by Mental Health Departments in other countries.
This article briefly reports the experience of mental health services and the lessons learned during the coronavirus disease 2019 (COVID-19) crisis. In particular, this report offers opportunities to ...build on experience gained in managing the COVID-19 emergency in the Departments of Mental Health and Addiction (DMHAs) in Lombardy, the wealthiest Italian region, which has approximately 10 million inhabitants.
Italy has a National Mental Health System divided into 134 DMHAs, 27 of which are in Lombardy. In the 4 weeks after the epidemic started, important changes occurred in the management of DMHAs in Lombardy. Many challenges have occurred in the management of health services. In many hospitals, entire wards, including some psychiatric wards, have been reorganized to admit patients with COVID-19, and many physicians and nurses have been diverted to wards managing patients with COVID-19. Most day facilities for patients with psychiatric needs have been temporarily closed, whereas in residential facilities, patients who usually are free to come and go during the day have had to be confined in the facilities with very limited or no leave. These changes have produced considerable stresses on people with severe mental disorders. Many outpatient clinics have limited appointments to those with the most urgent cases, and home visits, a common practice in most DMHAs, have been drastically reduced with potentially detrimental consequences for patients' well-being. Another potential detrimental consequence of being forced to stay at home has been an increase in the hours spent face to face with families with high amounts of conflict.
Departments of Mental Health need to be equipped with appropriate e-health technologies and procedures to cope with situations such as the COVID-19 pandemic. Additionally, interventions are needed to mitigate the potentially harmful consequences of quarantine. Departments of Mental Health should be able to assume a leadership position in the psychosocial management of disasterlike situations, and this requires the acquisition of new skills, notably how to correctly inform the population about risk, train and disseminate effective preventive and management procedures for disasters, support health personnel and rescuers, and support those experiencing bereavement.
In mental healthcare, one area of major concern identified by health information systems is variability in antipsychotic prescribing. While most studies have investigated patient- and ...prescriber-related factors as possible reasons for such variability, no studies have investigated facility-level characteristics. The present study ascertained whether staffing level is associated with antipsychotic prescribing in community mental healthcare.
A cross-sectional analysis of data extracted from the Italian national mental health information system was carried out. For each Italian region, it collects data on the availability and use of mental health facilities. The rate of individuals exposed to antipsychotic drugs was tested for evidence of association with the rate of mental health staff availability by means of univariate and multivariate analyses.
In Italy there were on average nearly 60 mental health professionals per 100,000 inhabitants, with wide regional variations (range 21 to 100). The average rate of individuals prescribed antipsychotic drugs was 2.33%, with wide regional variations (1.04% to 4.01%). Univariate analysis showed that the rate of individuals prescribed antipsychotic drugs was inversely associated with the rate of mental health professionals available in Italian regions (Kendall's tau -0.438, p = 0.006), with lower rates of antipsychotic prescriptions in regions with higher rates of mental health professionals. After adjustment for possible confounders, the total availability of mental health professionals was still inversely associated with the rate of individuals exposed to antipsychotic drugs.
The evidence that staffing level was inversely associated with antipsychotic prescribing indicates that any actions aimed at decreasing variability in antipsychotic prescribing need to take into account aspects related to the organization of the mental health system.
During economic recession people with mental health problems have higher risk of losing their job. This paper analyses the issue by considering the Italian rates of unemployment amongst individuals ...with and without mental health problems in 2005 and 2013, that is prior and during the economic crisis.
We used data from the National surveys on "Health conditions and use of health services" carried out by the Italian National Institute of Statistics (ISTAT) for the years 2005 and 2013. The surveys collected information on the health status and socioeconomic conditions of the Italian population. Self-reported unemployment status was analysed amongst individuals with and without reported mental health problems. In addition, descriptive statistics were performed in order to detect possible differences in the risk of unemployment within different regional contexts characterised by different socio-economic conditions.
The recession determined increased disparities in unemployment rates between people with and without mental health problems. Regardless to the presence of mental health problems, young people were more likely to be unemployed. Among people who reported mental health problems, males were more likely to be unemployed than females. People with low education level were more likely to be unemployed, particularly during the recession and in presence of mental health problems. Changes in unemployment rates due to the crisis showed different patterns across different regions of the Country.
These analyses confirm that in periods of economic crisis people with mental health problems are at risk of experiencing exclusion from labour market. In addition, the impact is even worse within the group with low education and younger age. These findings emphasise the importance of specific interventions aimed at promoting labour market participation and reintegration for people with mental health problems.
The Experience Sampling Method (ESM) is a valid method of remotely recording activities and mood, but the predictors of adherence to ESM in patients with Schizophrenia Spectrum Disorder (SSD) are not ...known. Studies on adherence are significant as they highlight the strengths and weaknesses of ESM-based study designs and allow the development of recommendations and practical guidelines for implementing future studies or treatment plans.
The aim of this study was to compare the adherence to ESM in patients with SSD and unaffected control individuals, investigate their patterns, and report the predictors of adherence.
In total, 131 patients with SSD (74 in residential facilities and 57 outpatients) and 115 unaffected control individuals were recruited at 10 different centers in Italy as part of the DiAPAson project. Demographic information, symptom severity, disability level, and level of function were recorded for the clinical sample. Participants were evaluated for daily time use and mood through a smartphone-based ESM 8 times a day for 7 consecutive days. Adherence was measured by the response rate to ESM notifications. Results were analyzed using the chi-square test, ANOVA, Kruskal-Wallis test, and Friedman test, and a logistic regression model.
The overall adherence rate in this study was 50% for residents, 59% for outpatients, and 78% for unaffected control individuals. Indeed, patients with SSD had a lower rate of adherence to ESM than the unaffected control group (P≤.001), independent of time slot, day of monitoring, or day of the week. No differences in adherence rates between weekdays and weekends were found among the 3 groups. The adherence rate was the lowest in the late evening time slot (8 PM to 12 AM) and days 6-7 of the study for both patients with SSD and unaffected control individuals. The adherence rate among patients with SSD was not predicted by sociodemographic characteristics, cognitive function, or other clinical features. A higher adherence rate (ie, ≥70%) among patients with SSD was predicted by higher collaboration skills (odds ratio OR 2.952; P=.046) and self-esteem (OR 3.394; P=.03), and lower positive symptom severity (OR 0.835; P=.04).
Adherence to ESM prompts for both patients with SSD and unaffected control individuals decreased during late evening and after 6 days of monitoring. Higher self-esteem and collaboration skills predicted higher adherence to ESM among patients with SSD, while higher positive symptom scores predicted lower adherence rates. This study provides important information to guide protocols for future studies using ESM. Future clinical or research studies should set ESM monitoring to waking hours, limit the number of days of monitoring, select patients with more collaborative skills and avoid those with marked positive symptoms, provide intensive training sessions, and improve participants' self-confidence with technologies.
RR2-10.1186/s12888-020-02588-y.
The unwillingness to share contacts is one of the least explored aspects of the COVID-19 pandemic. Here we report the factors associated with resistance to collaborate on contact tracing, based on ...the results of a nation-wide survey conducted in Italy in January-March 2021. The repeated cross-sectional on-line survey was conducted among 7,513 respondents (mean age 45.7, 50.4% women) selected to represent the Italian adult population 18-70 years old. Two groups were defined based on the direct question response expressing (1) unwillingness or (2) willingness to share the names of individuals with whom respondents had contact. We selected 70% of participants (training data set) to produce several multivariable binomial generalized linear models and estimated the proportion of variation explained by the model by McFadden R.sup.2, and the model's discriminatory ability by the index of concordance. Then, we have validated the regression models using the remaining 30% of respondents (testing data set), and identified the best performing model by removing the variables based on their impact on the Akaike information criterion and then evaluating the model predictive accuracy. We also performed a sensitivity analysis using principal component analysis. Our analysis revealed several groups that expressed unwillingness to collaborate on contact tracing. The identified patterns may play a principal role not only in the COVID-19 epidemic but also be important for possible future public health threats, and appropriate interventions for their correction should be developed and ready for the implementation.
COVID-19 pandemic had a negative impact on the mental health and well-being (WB) of citizens. This cross-sectional study included 4 waves of data collection aimed at identifying profiles of ...individuals with different levels of WB. The study included a representative stratified sample of 10,013 respondents in Italy. The WHO 5-item well-being scale (WHO-5) was used for the assessment of WB. Different supervised machine learning approaches (multinomial logistic regression, partial least-square discriminant analysis-PLS-DA-, classification tree-CT-) were applied to identify individual characteristics with different WB scores, first in waves 1-2 and, subsequently, in waves 3 and 4. Forty-one percent of participants reported "Good WB", 30% "Poor WB", and 28% "Depression". Findings carried out using multinomial logistic regression show that Resilience was the most important variable able for discriminating the WB across all waves. Through the PLS-DA, Increased Unhealthy Behaviours proved to be the more important feature in the first two waves, while Financial Situation gained most relevance in the last two. COVID-19 Perceived Risk was relevant, but less than the other variables, across all waves. Interestingly, using the CT we were able to establish a cut-off for Resilience (equal to 4.5) that discriminated good WB with a probability of 65% in wave 4. Concluding, we found that COVID-19 had negative implications for WB. Governments should support evidence-based strategies considering factors that influence WB (i.e., Resilience, Perceived Risk, Healthy Behaviours, and Financial Situation).
BackgroundThe unwillingness to share contacts is one of the least explored aspects of the COVID-19 pandemic. Here we report the factors associated with resistance to collaborate on contact tracing, ...based on the results of a nation-wide survey conducted in Italy in January-March 2021.Methods and findingsThe repeated cross-sectional on-line survey was conducted among 7,513 respondents (mean age 45.7, 50.4% women) selected to represent the Italian adult population 18-70 years old. Two groups were defined based on the direct question response expressing (1) unwillingness or (2) willingness to share the names of individuals with whom respondents had contact. We selected 70% of participants (training data set) to produce several multivariable binomial generalized linear models and estimated the proportion of variation explained by the model by McFadden R2, and the model's discriminatory ability by the index of concordance. Then, we have validated the regression models using the remaining 30% of respondents (testing data set), and identified the best performing model by removing the variables based on their impact on the Akaike information criterion and then evaluating the model predictive accuracy. We also performed a sensitivity analysis using principal component analysis. Overall, 5.5% of the respondents indicated that in case of positive SARS-CoV-2 test they would not share contacts. Of note, this percentage varied from 0.8% to 46.5% depending on the answers to other survey questions. From the 139 questions included in the multivariable analysis, the initial model proposed 20 independent factors that were reduced to the 6 factors with only modest changes in the model performance. The 6-variables model demonstrated good performance in the training (c-index 0.85 and McFadden R2 criteria 0.25) and in the testing data set (93.3% accuracy, AUC 0.78, sensitivity 30.4% and specificity 97.4%). The most influential factors related to unwillingness to share contacts were the lack of intention to perform the test in case of contact with a COVID-19 positive individual (OR 5.60, 95% CI 4.14 to 7.58, in a fully adjusted multivariable analysis), disagreement that the government should be allowed to force people into self-isolation (OR 1.79, 95% CI 1.12 to 2.84), disagreement with the national vaccination schedule (OR 2.63, 95% CI 1.86 to 3.69), not following to the preventive anti-COVID measures (OR 3.23, 95% CI 1.85 to 5.59), the absence of people in the immediate social environment who have been infected with COVID-19 (1.66, 95% CI 1.24 to 2.21), as well as difficulties in finding or understanding the information about the infection or related recommendations. A limitation of this study is the under-representation of persons not participating in internet-based surveys and some vulnerable groups like homeless people, persons with disabilities or migrants.ConclusionsOur analysis revealed several groups that expressed unwillingness to collaborate on contact tracing. The identified patterns may play a principal role not only in the COVID-19 epidemic but also be important for possible future public health threats, and appropriate interventions for their correction should be developed and ready for the implementation.
Background:
Long-Term Care Facilities (LTCF) in Italy have been particularly affected by the COVID-19 pandemic, especially in terms of mortality rates of older residents. However, it is still unclear ...the actual extent of this situation. The aim of this manuscript is to assess the extent of mortality rates of older adults in LTCF during the pandemic across different regions of Italy, compared to the previous years and to older general population not resident in LTCF.
Methods:
We extracted and analyzed data collected by three Italian institutions (i.e., Italian Statistician Institute ISTAT, Italian N.I.H, Milan Health Unit) about the number of deaths among older people living in the community and among LTCF residents during the pandemic and the previous years. We also compared the observed mortality rate among LTCF residents in each Italian Region with the corresponding expected number of deaths of the general older adult population to obtain an observed/expected ratio (O/E ratio).
Results:
During the pandemic, about 8.5% (
N
= 6,797) of Italian older adults residents in LTCF died. Findings resulting from the O/E ratio suggest that LTCF residents (in particular in the Lombardy Region) show higher mortality rates when compared to expected values of mortality rates among the older general population living in the community. Furthermore, we found that the risk of death among LTCF residents increased about 4 times during the pandemic when compared to the previous years.
Conclusions:
Mortality rates in LTCF were high during the pandemic, especially in Lombardy. Possible causes of higher mortality rates in LTCF and suggestions for specific targeted interventions are discussed.
Background
Evaluating emotional experiences in the life of people with Schizophrenia Spectrum Disorder (SSD) is fundamental for developing interventions aimed at promoting well‐being in specific ...times and contexts. However, little is known about emotional variability in this population. In DiAPAson project, we evaluated between‐ and within‐person differences in emotional intensity, variability, and instability between people with SSD and healthy controls, and the association with psychiatric severity and levels of functioning.
Methods
102 individuals diagnosed with SSD (57 residential patients, 46 outpatients) and 112 healthy controls were thoroughly evaluated. Daily emotions were prospectively assessed with Experience Sampling Method eight times a day for a week. Statistical analyses included ANOVA, correlations, and generalized linear models.
Results
Participants with SSD, and especially residential patients, had a higher intensity of negative emotions when compared to controls. Moreover, all people with SSD reported a greater between‐person‐variability of both positive and negative emotions and greater intra‐variability of negative emotions than healthy controls. In addition, the emotion variability in people with SSD does not follow a linear or quadratic trend but is more “chaotic” if compared to controls.
Conclusions
Adequate assessments of positive and negative emotional experiences and their time course in people with SSD can assist mental health professionals with well‐being assessment, implementing targeted interventions through the identification of patterns, triggers, and potential predictors of emotional states.
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