Aims.: To evaluate treatment decision-making capacity (DMC) to consent to psychiatric treatment in involuntarily committed patients and to further investigate possible associations with clinical and socio-demographic characteristics of patients.Methods.: 131 involuntarily hospitalised patients were recruited in three university hospitals. Mental capacity to consent to treatment was measured with the MacArthur Competence Assessment Tool for Treatment (MacCAT-T); psychiatric symptoms severity (Brief Psychiatric Rating Scale, BPRS-E) and cognitive functioning (Mini Mental State Examination, MMSE) were also assessed.Results.: Mental capacity ratings for the 131 involuntarily hospitalised patients showed that patients affected by bipolar disorders (BD) scored generally better than those affected by schizophrenia spectrum disorders (SSD) in MacCAT-T appreciation (p< 0.05) and reasoning (p< 0.01). Positive symptoms were associated with poorer capacity to appreciate (r= −0.24;p< 0.01) and reason (r= −0.27;p< 0.01) about one's own treatment. Negative symptoms were associated with poorer understanding of treatment (r= −0.23;p< 0.01). Poorer cognitive functioning, as measured by MMSE, negatively affected MacCAT-T understanding in patients affected by SSD, but not in those affected by BD (SSDr= 0.37;p< 0.01; BDr= −0.01;p= 0.9). Poorer MacCAT-T reasoning was associated with more manic symptoms in the BD group of patients but not in the SSD group (BDr= −0.32;p< 0.05; SSDr= 0.03;p= 0.8). Twenty-two per cent (n= 29) of the 131 recruited patients showed high treatment DMC as defined by having scored higher than 75% ofunderstanding, appreciating and reasoningMacCAT-T subscales maximum sores and 2 atexpressing a choice. The remaining involuntarily hospitalised patients where considered to have low treatment DMC. Chi-squared disclosed that 32% of BD patients had high treatment DMC compared with 9% of SSD patients (p< 0.001).Conclusions.: Treatment DMC can be routinely assessed in non-consensual psychiatric settings by the MacCAT-T, as is the case of other clinical variables. Such approach can lead to the identification of patients with high treatment DMC, thus drawing attention to possible dichotomy between legal and clinical status.

Objective – The aim of this study was to investigate the prevalence of alexithymia in a sample of patients with multiple sclerosis (MS) and to further evaluate the association between alexithymia and the occurrence of common disabling MS-related symptoms such as fatigue and depression. Methods – Fifty-eight relapsing–remitting MS patients treated with interferon (IFN)-beta-1a underwent a complete neurological evaluation, including Expanded Disability Status Scale score assessment. Alexithymia, depressive symptoms and fatigue were assessed using the 20-item Toronto Alexithymia Scale, Beck Depression Inventory and Fatigue Severity Scale. Results – Prevalence of alexithymia was 13.8%, with 27.6% of patients presenting borderline alexithymia. Sixty-seven per cent of the patients complained of fatigue while 29.3% of them were depressed. Higher levels of fatigue and depression were found in alexithymic patients when compared with non-alexithymic patients. Results from logistic regressions showed that alexithymia significantly contributes to the severity of fatigue and depression. Conclusions – Alexithymia was associated with increased severity of fatigue and depression.

Objectives: To perform a meta-analysis of clinical studies on the differences in treatment or research decision-making capacity among patients with Mild Cognitive Impairment (MCI), Alzheimer’s disease (AD), and healthy comparisons (HCs). Design: A systematic search was conducted on Medline/Pubmed, CINAHL, PsycINFO, Web of Science, and Scopus. Standardized mean differences and random-effects model were used in all cases. Setting: The United States, France, Japan, and China. Participants: Four hundred and ten patients with MCI, 149 with AD, and 368 HCs were included. Measurements: The studies we included in the analysis assessed decisional capacity to consent by the MacArthur Competence Assessment Tool for Treatment (MAcCAT-T), MacArthur Competence Assessment Tool for Clinical Research (MacCAT-CR), Capacity to Consent to Treatment Instrument (CCTI), and University of California Brief Assessment of Capacity to Consent (UBACC). Results: We identified 109 potentially eligible studies from 1672 records, and 7 papers were included in the meta-analysis. The meta-analysis showed that there was significant impairment in a decision-making capacity in MCI patients compared to the HCs group in terms of Understanding (SMD = −1.04, 95% CI: −1.31 to −0.77, P < 0.001; I2 = 52%, P = 0.07), Appreciation (SMD = −0.51, 95% CI: −0.66 to −0.36, P < 0.001; I2 = 0%, P = 0.97), and Reasoning (SMD = −0.62, 95% CI: −0.77, −0.47, P < 0.001; I2=0%, P =0.46). MCI patients scored significantly higher in Understanding (SMD = 1.50, 95% CI: 0.91, 2.09, P = 0.01, I2 = 78%, P = 0.00001) compared to patients affected by AD. Conclusions: Patients affected by MCI are at higher risk of impaired capacity to consent to treatment and research compared to HCs, despite being at lower risk compared to patients affected by AD. Clinicians and researchers need to carefully evaluate decisional capacity in MCI patients providing informed consent.

Background: In the age of digitalization and big data, personal health information is a key resource for health care and clinical research. This study aimed to analyze the determinants and describe the measurement of the willingness to disclose personal health information.Methods: The study conducted a systematic review of articles assessing willingness to share personal health information as a primary or secondary outcome. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis protocol. English and Italian peer-reviewed research articles were included with no restrictions for publication years. Findings were narratively synthesized.Results: The search strategy found 1,087 papers, 89 of which passed the screening for title and abstract and the full-text assessment.Conclusion: No validated measurement tool has been developed for willingness to share personal health information. The reviewed papers measured it through surveys, interviews, and questionnaires, which were mutually incomparable. The secondary use of data was the most important determinant of willingness to share, whereas clinical and socioeconomic variables had a slight effect. The main concern discouraging data sharing was privacy, although good data anonymization and the high perceived benefits of sharing may overcome this issue.