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Background: The clinical presentation of Eating Disorders (EDs) is often characterized by a great phenotypic variability and by a substantial instability over time of diagnostic categories. For these reasons, it has been proposed a different approach to EDs, encompassing both their dimensional and categorical descriptions, in a lifetime perspective, namely the ‘Anorexic-Bulimic Spectrum’ (ABS). Here we report a retrospective study with the interview built and validated for the assessment of ABS signs and symptoms, the ‘Structured Clinical Interview for Anorexic-Bulimic Spectrum’ (SCI-ABS), administered together with the ‘Mood Spectrum Self Report’ (MOODS-SR), a questionnaire able to assess sub-threshold mood spectrum dysregulations often comorbid with EDs signs and symptoms. The main aim of the study was twofold: to assess and better characterize clinical phenotypes of EDs; to highlight potential lifetime sub-threshold mood dysregulations that might occur comorbid with EDs, and that patients might consider relevant to their ‘subjective experience of illness’. In order to obtain these goals, we decided to utilize a machine learning analysis. Methods: two groups were recruited and compared, namely patients with EDs (n=53) and healthy controls (HC) (n=54). Both groups underwent psychological testing with MOODS-SR and SCI-ABS. Results: in discriminating and classifying EDs individuals from HC, machine learning classifiers obtained an accuracy higher than 70%. Based on all variables considered, the analysis revealed that SCI-ABS ‘Phobias’ domain (more in detail, ‘Weight Gain Phobia’ total score), the ‘Impairment and Insight’ item 5, (‘…your relationship with food was all you could think about?’) and the MOODS-SR item 154 (‘you were less sexually active than is typical for you?’) were the best psychological elements in discriminating EDs patients from HC (accuracy range: 72.90-86.92%). Given the large number of predictors, we run a supervised attributes selection procedure. The procedure yielded an accuracy of 90.65% in classifying EDs patients from HC. Conclusions: the very high overall accuracy is indicative that the selected combinations of features capture the most important determinants in the discrimination of EDs patient’s vs HC. The items selected by the machine learning analysis confirmed that an extreme polarization of ideas on weight and food control characterize the cognitive asset of EDs patients., Mediterranean Journal of Clinical Psychology, Vol 9, No 1 (2021)

BackgroundCoronavirus disease 2019 (COVID-19) seriously affected all Italy. The extreme virulence, the speed of propagation resulted in restrictions and home confinement. This change was immediately perceived by people who found themselves exposed to feelings of uncertainty, fear, anger, stress and a drastic change in the diurnal but above all nocturnal lifestyle. For these reasons, we aimed to study the quality of sleep and its connection to distress levels and evaluate how lifestyle changed in the Italian population during the lockdown.MethodsThrough an internet survey we recruited 6,519 adults during the whole COVID-19 lockdown (from 10thMarch – 1st phase - to 4th May – 2nd phase). We investigated the socio-demographic and COVID-19 related information and assessed sleep quality using the Medical Outcomes Study - sleep scale (MOS-SS) and mental health with the short form of Depression, Anxiety, and Stress Scales – 21 Items (DASS-21). Multiple logistic regression model was used to evaluate the multivariate association between the dependent variable (good sleeper vs. poor sleeper) and all the variables that were significant in the univariate analysis.Results3,562 (55.32%) participants reported poor sleep quality according to the MOS-Sleep Index II score. The multiple binary logistic regression results of poor sleepers reveal several risk factors during the outbreak restrictions: female gender, living in Central Italy, having someone close who died due to COVID-19, markedly changed sleep-wake rhythm characterized by earlier or postponed habitual bedtime, earlier habitual awakening time and reduced number of afternoon naps, extremely severe levels of stress, of anxiety, and of depression. ConclusionsThis is the first study designed to understand sleep quality and sleep habits during the whole lockdown in the Italian population that provides more than 6,000 participants in a survey developed specifically for the health emergency related to COVID-19. Our study found that more than half of the Italian population have had impaired sleep quality and sleep habits elevated psychological distress during the COVID-19 lockdown containment measures. A multidisciplinary action should be taken in order to plan appropriate responses to the current crisis caused by the COVID-19 health emergency.

Objective We reviewed literature on drugs for bipolar disorders (BD), utilized in ovarian cancer (OC). Method We adhered to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines in completion of this systematic review. Results We identified 73 papers. Thirty-two studies were finally included. BD is rarely diagnosed in OC patients. Limited finding from case reports is available. Drugs used to treat BD (mainly lithium and valproic acid) have been extensively studied in add-on to chemotherapy for treatment-resistant OC cells or in animal models, with promising results in vitro but not in vivo. Conclusions The clinical underestimation of BD in OC has leaded to the almost complete absence of evidences for a soundly based clinical guidance in this field. There is a urgent need for a systematic multi-disciplinary approach to OC.

The primary aim of the study was to determine the frequency of psychiatric disorders in Behçet's syndrome (BS) patients, both with and without neurological involvement. The secondary aims were: to investigate a possible association between disease activity/organ involvement/demographic data and psychiatric profile in BS patients, and to compare the distribution of psychiatric disorders in BS patients compared to patients with other chronic diseases.One hundred and sixteen BS patients were studied; in addition, two groups of patients affected by systemic lupus erythematosus and chronic arterial hypertension were included in the study as disease control groups. The end-point was represented by the assessment of disease activity, performed by the evaluation of: the presence/absence of manifestations, BDCAF and clinician's overall perception of disease activity. Psychiatric comorbidity was evaluated according to the DSMIV-TR criteria.The frequency of bipolar disorders resulted significantly higher in BS than in disease controls. The presence of bipolar disorders in BS patients does not seem to be related to the presence of neurological involvement in the history of the disease. Notably, a significant correlation was found between BS disease activity and mood disorders, also in the follow-up.The study demonstrated a high frequency of psychiatric disorders in BS patients, peculiarly represented by bipolar disorders. The presence of this involvement, independently from the organ involvement, and strictly related to the disease activity, seems to suggest that neuro-psycho-BS may represent an intrinsic aspect of BS.

Patients with systemic lupus erythematosus (SLE) can be affected by a multitude of neurologic and psychiatric symptoms with a wide range of prevalence and severity. Irrespectively from attribution to SLE or other causes, neuropsychiatric (NP) symptoms strongly impact short-term and long-term outcomes, thus NP evaluation during routine clinical practice in SLE should be undertaken regularly. The assessment of NP involvement in SLE patients is challenging and the available diagnostic tools fail to guarantee optimal diagnostic accuracy, sensitivity to changes as well as feasibility in routine clinical care. Standardised questionnaires (both physician-administered and self-reported) can offer valuable help to the treating physician to capture all possible NP syndromes; few SLE-specific NP questionnaire have been developed but validation in large cohort or cross-cultural adaptations are still pending. On the other hand, general instruments have been largely applied to SLE patients. Both kinds of questionnaires can address all possible NP manifestations either globally or, more frequently, focus on specific NP symptoms. These latter have been mainly used in SLE to detect and classify mild and subtle symptoms, more likely to be overlooked during routine clinical assessment such as headache, cognitive impairment and psychiatric manifestations. In conclusion, this literature review highlights a clear case for validation studies in this area and the wider implementation of questionnaires to assess NP involvement is still warranted. The broader use of such instruments could have important consequences; first of all, by standardising symptom assessment, a better definition of the prevalence of NP manifestation across different centres could be achieved. Secondly, prospective studies could allow for the evaluation of clinical significance of mild symptoms and their impact on the patient's function and quality of life.