The Interplay of Sleep Quality, Mental Health, and Sociodemographic and Clinical Factors among Italian College Freshmen.

Background/Objectives: Sleep and mental health are closely linked, with sleep deprivation increasing the risk of mental health problems in college students. This study aimed to analyze the role of sleep in the mental health status of a sample of Italian freshmen, considering various mental health outcomes and potential interactions between sleep and other relevant factors, such as sociodemographic characteristics, academic experiences, and mental health history. Methods: All freshmen from a medium-sized Italian university were invited to participate in a multidimensional online survey (n = 3756). Sleep quality was assessed through questions on average hours of sleep per night and on satisfaction of perceived sleep quality. Mental health outcomes included psychophysical well-being, psychological distress, substance use, and problematic internet use. Statistical analysis involved multivariate analysis of variance, followed by pairwise comparisons. Results: The sample (n = 721) exhibited low levels of well-being and a high prevalence of psychological distress (52.1%). Approximately one-third of students (n = 258) were dissatisfied with their sleep quality, and one-fourth (n = 186) reported inadequate sleep (less than 7 h per night). More specifically, 24.4% of students slept on average six hours per night, and 1.4% slept five hours or less. Satisfaction with perceived sleep quality significantly influenced well-being, psychological distress, and cannabis use (ηp2 = 0.02). Interaction effects were observed between satisfaction with sleep quality and drop-out intentions (ηp2 = 0.01), as well as between satisfaction with sleep quality and history of mental health diagnosis (ηp2 = 0.02), both of which were significant for psychological distress and cannabis use. Conclusions: This study highlights the influence of perceived sleep quality on academic distress among college freshmen, particularly those with higher intentions of leaving university and with a history of mental health diagnosis.

Potential suicide risk among the college student population: machine learning approaches for identifying predictors and different students' risk profiles.

BACKGROUND: Suicide is one of the leading causes of death among young people and university students. Research has identified numerous socio-demographic, relational, and clinical factors as potential predictors of suicide risk, and machine learning techniques have emerged as promising ways to improve risk assessment. OBJECTIVE: This cross-sectional observational study aimed at identifying predictors and college student profiles associated with suicide risk through a machine learning approach. METHODS: A total of 3102 students were surveyed regarding potential suicide risk, socio-demographic characteristics, academic career, and physical/mental health and well-being. The classification tree technique and the multiple correspondence analysis were applied to define students' profiles in terms of suicide risk and to detect the main predictors of such a risk. RESULTS: Among the participating students, 7% showed high potential suicide risk and 3.8% had a history of suicide attempts. Psychological distress and use of alcohol/substance were prominent predictors of suicide risk contributing to define the profile of high risk of suicide: students with significant psychological distress, and with medium/high-risk use of alcohol and psychoactive substances. Conversely, low psychological distress and low-risk use of alcohol and substances, together with religious practice, represented the profile of students with low risk of suicide. CONCLUSIONS: Machine learning techniques could hold promise for assessing suicide risk in college students, potentially leading to the development of more effective prevention programs. These programs should address both risk and protective factors and be tailored to students' needs and to the different categories of risk.

Impact of COVID-19 Pandemic on Well-Being, Social Relationships and Academic Performance in a Sample of University Freshmen: A Propensity Score Match Evaluation Pre- and Post-Pandemic.

The COVID-19 pandemic has impacted freshmen, compromising their mental health, lifestyles, and academic performance. There are few studies that have investigated changes in the health status and lifestyles of freshmen before and after the pandemic. The aims of this study were: (1) to carry out a pre-post-COVID-19 pandemic comparison between two freshmen samples, in order to detect differences in their socio-demographic characteristics and in some clinical variables; (2) to assess the effect of the COVID-19 pandemic on the social and academic lives of the second sample of freshmen. The samples recruited in 2019 and 2022, matched by propensity score procedure (N = 553), were mostly female (57.3% vs. 55.3%); the mean age was 22.9 and 20.9 years, respectively. The freshmen recruited after the pandemic had less psychological distress and substance use than freshmen recruited before the pandemic. Seventy-eight percent of the freshmen stated that the pandemic had an impact on their social relationships. This effect was greater for females and Italian students. Forty-seven percent reported that the pandemic has worsened their academic performance, while 60% stated that pandemic has improved their grades. The results of this study can provide valuable insights into the impact of the pandemic on freshmen, in order to implement interventions to mitigate the consequences of the pandemic in some subgroups of this target population.

The role of psychological distress, stigma and coping strategies on help-seeking intentions in a sample of Italian college students.

BACKGROUND: Mental health issues are common among university students, but the latter are unlikely to seek professional help even when mental health services are available. Coping strategies, stigma and psychological distress are often considered as factors that can affect help-seeking intentions in university students. METHODS: This study aimed to determine the role of coping strategies, stigma and psychological distress on the intentions to seek professional help for psychological problems. All students (N = 13,886) from an Italian medium-sized university were asked to participate in a multidimensional online survey and 3754 (27.1%) agreed to participate. A Structural Equation Modelling approach was applied to explore the simultaneous direct and indirect effects of distress, stigma and coping strategies on professional help-seeking intentions. RESULTS: Results showed that students were not very likely to seek professional help and, through the Structural Equation Model, psychological distress was found to be positively correlated with coping strategies, which in turn was negatively associated with the stigma of seeking help. The latter was negatively associated with professional help-seeking intentions. These effects suggest that students with significant psychological distress use coping strategies to face the stigma of seeking help: the lower the stigma of seeking help, the higher the chance of developing intentions to seek professional help. CONCLUSIONS: This study suggests the importance of implementing programs to encourage college students to seek help, including measures that foster a stigma-free environment, reduce psychological distress and promote the use of adaptive coping strategies. Interventions should be focused firstly on self-stigma and secondly on perceived stigma, taking into consideration the level of psychological distress and social stereotypes associated with mental disorders and help seeking behaviours. Programs about coping are also essential and should focus on promoting emotion-focused strategies and problem-focused strategies.

Risk and protective factors associated with mental health status in an Italian sample of students during the fourth wave of COVID-19 pandemic.

BACKGROUND: It is well known that the COVID-19 pandemic has caused a global health crisis, especially for young people. However, most studies were conducted during the first waves of the pandemic. Few Italian studies specifically attempted to broadly assess young people's mental health status during the fourth wave of the pandemic. METHODS: This study aimed at evaluating the mental health status among a group of Italian adolescents and young adults during the fourth wave of the COVID-19 pandemic. 11,839 high school students and 15,000 university students (age range 14-25) were asked to complete a multidimensional online survey, of which 7,146 (26,6%) agreed to participate. The survey also included standardized measures for depression, anxiety, anger, somatic symptoms, resilience, loneliness and post-traumatic growth. Two separate clusters were identified through cluster analysis. Random forest, classification tree and logistic regressions analyses were applied to identify factors associated to a good or a poor level of mental health and, thus, to define students' mental health profiles. RESULTS: Overall, the students in our sample showed high levels of psychopathology. The clustering methods performed identified two separate clusters reflecting groups of students with different psychological features, that we further defined as "poor mental health" and "good mental health". The random forest and the logistic regressions found that the most discriminating variables among those two groups were: UCLA Loneliness Scale score, self-harm behaviors, Connor-Davidson Resilience Scale-10 score, satisfaction with family relationships, Fear of COVID-19 Scale score, gender and binge eating behaviors. The classification tree analysis identified students' profiles, showing that, globally, poor mental health was defined by higher scores of loneliness and self-harm, followed by being of female gender, presenting binge eating behaviors and, finally, having unsatisfying family relationships. CONCLUSIONS: The results of this study confirmed the major psychological distress caused by the COVID-19 pandemic in a large sample of Italian students, and provided further insights regarding those factors associated with a good or poor mental health status. Our findings suggest the importance of implementing programs targeting aspects that have been found to be associated to a good mental health.

Machine learning approaches to identify profiles and predictors of psychosocial discomfort among Italian college students / Enfoques de machine learning para identificar perfiles y predictores de malestar psicosocial entre estudiantes universitarios italianos

Abstract Introduction College students live a crucial period of transition from late adolescence to adulthood when they have to deal with important stressful tasks. Thus, university often represents a stressful environment, pushing students to cope with a high academic pressure. As a result, this period constitutes a sensitive age for the onset of mental disorders. Typically, students are not aware of the early signs of their own compromised mental health until symptoms aggravate to an overt disorder. Therefore, it is important to timely detect subthreshold symptoms mostly related to generic mental distress. Objective First, to assess psychophysical well-being and mental distress among college students in northern Italy, and to detect predictors, among socio-demographic and academic characteristics, and risky drug use of these two outcomes. Method The study involved 13,886 students who received an email explaining the purpose of the e-research. The questionnaires used were the General Health Questionnaire (GHQ-12), the University Stress Scale (USS), and a modified version of World Health Organization-ASSIST v3.0. Results 3,754 students completed the web-survey. Students showed poor well-being and mental distress. The strongest predictor of mental distress and compromised well-being was physical health, followed by sex, study field, risky drug use, and academic performance concerns. Discussion and conclusion This study shows that it is very important to promote in college students healthy behaviors in order to increase their physical exercise and reduce substance use. Moreover, it would be desirable to improve academic counselling facilities as an important front-line service to intercept mental health issues among young adults.

Resumen Introducción Los estudiantes universitarios pasan por un periodo crucial en su transición de la adolescencia tardía a la edad adulta, periodo en que tienen que lidiar con tareas estresantes. La universidad representa un entorno estresante, que empuja a los estudiantes a hacer frente a una alta presión académica. Como resultado, este periodo constituye una edad sensible para la aparición de trastornos mentales. En general, los estudiantes no cobran consciencia de los primeros signos de que su propia salud mental está en riesgo sino hasta que los síntomas se agravan y se convierten en un trastorno manifiesto. Por tanto, es importante detectar oportunamente los síntomas subumbrales relacionados ante todo con la angustia mental genérica. Objetivo Evaluar el bienestar psicofísico y la angustia mental entre estudiantes universitarios del norte de Italia, y en segundo lugar, detectar predictores entre las características sociodemográficas y académicas, y el uso de drogas de estos dos resultados. Método En el estudio participaron 13,886 estudiantes que recibieron un correo electrónico que explicaba el propósito de la investigación. Los instrumentos utilizados fueron el Cuestionario de Salud General (GHQ-12), la Escala de Estrés Universitario (USS) y una versión modificada de la Organización Mundial de la Salud-ASSIST v3.0. Resultados 3,754 estudiantes completaron la encuesta en línea. Los estudiantes mostraron bienestar y angustia mental. El predictor más fuerte de angustia mental y bienestar comprometido fue la salud física, seguido del sexo, el campo de estudio, el uso de drogas y el rendimiento académico. Discusión y conclusión Este estudio muestra que es muy importante promover entre los estudiantes universitarios comportamientos saludables para promover el ejercicio físico y reducir el consumo de sustancias. Además, sería deseable mejorar la orientación académica que es un importante servicio de primera línea para interceptar los problemas de salud mental en los estudiantes.

Meta-analysis of the Interval between the Onset and Management of Bipolar Disorder.

OBJECTIVE: To evaluate the length of the interval between the onset and the initial management of bipolar disorder (BD). METHOD: We conducted a meta-analysis using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Systematic searches located studies reporting estimates of the age of onset (AOO) and indicators of the age at initial management of BD. We calculated a pooled estimate of the interval between AOO and age at management. Factors influencing between-study heterogeneity were investigated using sensitivity analyses, meta-regression, and multiple meta-regression. RESULTS: Twenty-seven studies, reporting 51 samples and a total of 9415 patients, met the inclusion criteria. The pooled estimate for the interval between the onset of BD and its management was 5.8 years (standardized difference, .53; 95% confidence interval, .45 to .62). There was very high between-sample heterogeneity ( I2 = 92.6; Q = 672). A longer interval was found in studies that defined the onset according to the first episode (compared to onset of symptoms or illness) and defined management as age at diagnosis (rather than first treatment or first hospitalization). A longer interval was reported among more recently published studies, among studies that used a systematic method to establish the chronology of illness, among studies with a smaller proportion of bipolar I patients, and among studies with an earlier mean AOO. CONCLUSIONS: There is currently little consistency in the way researchers report the AOO and initial management of BD. However, the large interval between onset and management of BD presents an opportunity for earlier intervention.

Oxytocin to modulate emotional processing in schizophrenia: A randomized, double-blind, cross-over clinical trial.

Deficits in social cognition, including emotional processing, are hallmarks of schizophrenia and antipsychotic agents seem to be ineffectual to improve these symptoms. However, oxytocin does seem to have beneficial effects on social cognition. The aim of this study was to examine the effects of four months of treatment with intranasal oxytocin, in 31 patients with schizophrenia, on distinct aspects of social cognition. This was assessed using standardized and experimental tests in a randomized, double-blind, placebo-controlled, cross-over trial. All patients underwent clinical and experimental assessment before treatment, four months after treatment and at the end of treatment. Social cognition abilities were assessed with the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and the Reading the Mind in the Eyes task (RMET). Furthermore, an Emotional Priming Paradigm (EPP) was developed to examine the effects of oxytocin on implicit perceptual sensitivity to affective information and explicit facial affect recognition. We found that oxytocin improved performance on MSCEIT compared to placebo in Branch 3-Understanding Emotion (p-value=0.004; Cohen׳s d=1.12). In the EPP task, we observed a significant reduction of reaction times for facial affect recognition (p-value=0.021; Cohen׳s d=0.88). No effects were found for implicit priming or for theory of mind abilities. Further study is required in order to highlight the potential for possible integration of oxytocin with antipsychotic agents as well as to evaluate psycho-social treatment as a multi-dimensional approach to increase explicit emotional processing abilities and compensate social cognition deficits related to schizophrenia.

Do we need oxytocin to treat schizophrenia? A randomized clinical trial.

BACKGROUND: Schizophrenia is a disabling complex mental disorder and despite all available treatment, many patients unfortunately remain partial- or non-responders. A large body of research has shown that oxytocin is an important prosocial peptide and there is initial evidence that the central oxytocin system is altered in several mental disorders. The aim of this study was to test the efficacy of oxytocin, as augmentation therapy, in a sample of patients with schizophrenia. METHODS: We conducted an 8-month randomized, double-blind, controlled trial with a crossover design. We wanted to test the hypothesis that intranasal oxytocin could reduce symptoms in 32 patients with schizophrenia aged 18-45 with short-medium illness duration (<11 years). Patients were randomly assigned to either 40 International Units oxytocin once daily or a vehicle placebo group, in addition to their pre-study antipsychotic medication regimen. We subsequently conducted a multi-dimensional assessment including psychopathological, psychosocial and neuropsychological aspects. RESULTS: Positive and Negative Syndrome Scale scores showed no significant differences in treatment effects between the experimental group and controls. Furthermore, no treatment effects were shown in any of the rating scales used in this study. However, a statistically significant period effect was shown in most outcome measurements. CONCLUSIONS: In our trial, oxytocin did not add any significant beneficial effects to anti-psychotic treatment in terms of clinical symptoms or psychosocial functioning. Further research should focus on different ways to administer oxytocin, or investigate predictors (such as past traumas, or biomarkers), which could identify subgroups of patients with different treatment responses to oxytocin. ClinicalTrials.gov Identifier: NCT01699997. ID number: RF-2010-2311148. URL: https://clinicaltrials.gov/ct2/show/NCT01699997.

Moderate efficiency of clinicians' predictions decreased for blurred clinical conditions and benefits from the use of BRASS index. A longitudinal study on geriatric patients' outcomes.

OBJECTIVES: Accurate prognosis is an essential aspect of good clinical practice and efficient health services, particularly for chronic and disabling diseases, as in geriatric populations. This study aims to examine the accuracy of clinical prognostic predictions and to devise prediction models combining clinical variables and clinicians' prognosis for a geriatric patient sample. STUDY DESIGN AND SETTING: In a sample of 329 consecutive older patients admitted to 10 geriatric units, we evaluated the accuracy of clinicians' prognosis regarding three outcomes at discharge: global functioning, length of stay (LoS) in hospital, and destination at discharge (DD). A comprehensive set of sociodemographic, clinical, and treatment-related information were also collected. RESULTS: Moderate predictive performance was found for all three outcomes: area under receiver operating characteristic curve of 0.79 and 0.78 for functioning and LoS, respectively, and moderate concordance, Cohen's K = 0.45, between predicted and observed DD. Predictive models found the Blaylock Risk Assessment Screening Score together with clinicians' judgment relevant to improve predictions for all outcomes (absolute improvement in adjusted and pseudo-R(2) up to 19%). CONCLUSION: Although the clinicians' estimates were important factors in predicting global functioning, LoS, and DD, more research is needed regarding both methodological aspects and clinical measurements, to improve prognostic clinical indices.

Frequency of trauma exposure and Post-Traumatic Stress Disorder in Italy: analysis from the World Mental Health Survey Initiative.

Epidemiological studies have examined the relative importance of Traumatic Events (TEs) in accounting for the societal burden of post-traumatic stress disorder (PTSD). However, most studies used the worst trauma experienced, which can lead to an overestimation of the conditional risk of PTSD. Although a number of epidemiological surveys on PTSD have been carried out in the United States, only a few studies in limited sample have been conducted in Italy. This study, carried out in the framework of the World Mental Health Survey Initiative, is a cross-sectional household survey of a representative sample of the Italian adult population. Lifetime prevalence of TEs and 12-month prevalence of PTSD were evaluated using the Composite International Diagnostic Interview (CIDI). Reports of PTSD associated with randomly selected TEs were weighted by the individual-level probabilities of TE selection to generate estimates of population-level PTSD risk associated with each TE. Network events was the most commonly reported class of TEs (29.4%). War events had the highest conditional risk of PTSD (12.2%). The TEs that contributed most to societal PTSD burden were unexpected death of a loved one (24.1%) and having seen atrocities (18.2%). Being female was related to high risk of PTSD after experiencing a TE. Exposure to network events is commonly reported among Italian adults, but two TEs are responsible for the highest burden associated with PTSD: the unexpected death of someone close and sexual assault. These results can help designing public health interventions to reduce the societal PTSD burden.

Monitoring and evaluating the Italian mental health system: the "Progetto Residenze" study and beyond.

Filling an alarming gap in evidence-based data on the post-1978 reformed Italian psychiatric system, two turn-of-millennium nationwide projects, Progetto Residenze (PROGRES) and PROGRES-Acute, provided detailed qualitative-quantitative information about care facilities. In 2000, there were 2.9 residential beds per 10,000 inhabitants, hospital care being delivered through small (15-bed) psychiatric units. Private inpatient facilities had proliferated, private inpatient beds per 10,000 inhabitants outnumbering public beds. In 2002, there were 1.7 acute inpatient beds per 10,000 inhabitants, one of Europe's lowest current ratios. The PROGRES and other subsequent projects showed marked nationwide variation in the provision of residential inpatient and outpatient care, grounds for concern about the quality of such care, and an uneven service use pattern. Although the Italian reform law produced a broad network of facilities to meet diverse mental health care needs, the present overview article confirms that further efforts are required to improve quality, balance public and private sectors, and coordinate resources and agencies.

A prospective, multidimensional follow-up study of a geriatric hospitalised population: predictors of discharge and well-being.

BACKGROUND AND AIMS: Ageing trends in populations are common amongst most European countries. One of the consequences of this trend is the increase of hospitalisation of elderly patients. To better manage the elderly population hospitalisation, it is crucial to obtain a better understanding of this population's clinical and functional conditions and their hospitalisation outcome predictors. The present prospective observational cohort study aimed at studying the variables considered predictive of the length of stay, of destination at discharge, of re-hospitalisation, and of mortality at 6 months of elderly (age >64 years, N = 329) admitted to ten geriatric units, having different missions (e.g., cognitive impairment and dementia; movement disorders; bone fractures and immobilisation syndrome; or stroke), of the St. John of God Order during a 4-month-long index period. METHODS: The patients were monitored from the first day of hospitalisation through the discharge. Researchers filled in a "Patient Schedule" based on a comprehensive set of socio-demographic and clinical variables and standardised assessment tools. We used a standardised telephone interview to re-assess patients at the 6-month follow-up. RESULTS: The BRASS score proved to be a better reliable predictor of length of stay (F = 3.9, p = 0.04) among all variables associated with higher risks of prolonged hospital stay and post-discharge problems. In addition, discharge destination was also predicted by the use of the Tinetti Scale score (OR = 0.95, 95 % CI 0.90-0.99), the Mini Mental State Examination (MMSE) score (OR = 0.1.07, 95 % CI 1.01-1.13) and by independence in daily activity as measured by the IADL scale (OR = 4.09, 95 % CI 1.46-11.44). Motor functioning resulted as a reliable predictor (OR = 2.67, 95 % CI 1.27-5.59) of re-hospitalisation in all the medical units. Lastly, female gender (OR = 0.28, 95 % CI 0.11-0.71) resulted as the only reliable variable associated with a lower mortality risk after discharge. CONCLUSION: The variables related to the clinical and functional status were reliable predictors for length of stay, for discharge destination, and for re-hospitalisation among older patients admitted to ten geriatric units in Italy. Further research is needed to establish valid and reliable predictors of mortality risk, to develop effective preventive strategies in those vulnerable populations.