China's abrupt exit from the zero-COVID policy in late 2022 led to a rapid surge in infections, overwhelming healthcare systems and exposing healthcare providers to intensified psychological pressures. This sudden shift exacerbated pandemic-related psychological issues, including fear, health anxiety, and emotional processing difficulties. This study aimed to unravel the relationships among pandemic fear, cyberchondria, and alexithymia following China's exit from the zero-COVID policy.

Remnant cholesterol (RC) has received increasing attention due to its association with a variety of diseases. However, comprehensive population-based studies elucidating the relationship between RC and major depressive disorder (MDD) are limited. The current study aimed to determine the association between RC and MDD in US adults.

Burnout harms workers physical and mental health due to induced brain changes, autonomous nervous system and hypothalamus-pituitary-adrenal axis excessive activation. Although several correlations and risk factors have been identified, the research around burnout biological correlates remains underdeveloped. The omega-3 index has been proposed in mental health as a contributor to identify high risk patients and monitor disease advancements but the evidence on its relationship with burnout is limited. This study is meant to test the hypothesis that the omega-3 index is inversely associated with burnout levels and to discuss its potential as a biological correlate of burnout.

Multiple lines of evidence indicate that altered dopamine signaling may be involved in neuropsychiatric disorders and common behavioral traits. Here we critically review evidence collected during the past 40-plus years supporting the role of dopamine dysfunction in attention deficit hyperactivity disorder (ADHD). We recapitulate the basic components of dopaminergic signaling in the central nervous system, focusing on core enzymes, transporters and receptors involved in monoaminergic functions, particularly in striatal and cortical regions. We summarize key human brain imaging and genetic studies reporting associations between dopaminergic neurotransmission and behavioral traits, with an emphasis on ADHD. We also consider ADHD in the context of animal models and single gene, metabolic, and neurological disorders with established dysfunction of the dopaminergic system. Examining the evidence in this way leads us to conclude that there is evidence for the involvement of dopamine but limited evidence for a hypo-dopaminergic state as a key component of ADHD. We propose a path forward to increase our understanding of dopamine signaling in human behavioral traits and disorders that should particularly focus on its role in clinical subgroups, during brain development and how it interacts with other neurotransmitter systems.

The inclusion of students with autism spectrum disorder (ASD) in mainstream education (primary and secondary, in the range of 4-5 to 8-10 years old) is a complex task that has long challenged both educators and health professionals. However, the correct use of digital technologies such as personalization settings and interaction with robots has clearly shown how these new technologies can benefit ASD students. However, it is essential to characterize the profile, problems, and needs of each student, since it is not possible to generalize an accessible approach for all users. The work presented shows the creation and validation, through pilot tests, of an instrument that outlines the main needs of a student with ASD, based on behavioral variables. In a later phase, instructional sequences will be designed and adapted through digital tablets and interaction with a robot to improve specific aspects identified in the initial profile. The results demonstrate the method's ability to assess and prioritize profiles satisfactorily which helps create a design adjusted to each student. The first pilot tests have been well received by ASD students, who have shown increased interest in the contents and methods used in this approach. Motivation levels and engagement have also increased, and social interactions with their peers have improved.

Safeguarding college students' mental health and well-being poses a challenge for college administrators and clinicians because of the unique circumstances students face and the limited literature on their needs. Prior to the pandemic, depression and anxiety were already on the rise among college students, but the changes associated with it may have exacerbated these issues. Our study aimed to explore factors influencing college students' mental health and identify common trends in their experiences that could assist organizations and policymakers in the future.

Pregnancy and the postnatal period represent a time of heightened risk for women to experience mental health difficulties. Some mothers may require specialist inpatient psychiatric support made available through Mother and Baby units (MBUs). Although there is evidence of the therapeutic benefits of MBUs, many studies have utilised methodologies vulnerable to interviewer and social desirability biases. The repertory grid technique (RGT), derived from personal construct theory (PCT), has been successfully used to explore how the way in which a person thinks about and defines the self (i.e., self-construal) changes following therapeutic intervention in samples of people experiencing mental health conditions. Therefore, this study aimed to explore change in maternal self-construal following MBU admission, utilising the RGT, thereby enhancing our understanding for the therapeutic role of MBU admissions in women's mental health recoveries.

Peripheral neurofilament light chain (NfL) reflect neuronal and axonal damage. Most studies have been focused on NfL cerebrospinal fluid measures since peripheral levels were difficult to detect. However, with recent advent of single molecule array (SIMOA) technology, NfL is now detectable peripherally at small concentrations (pg/ml). In neurodegenerative disorders, NfL peripheral levels have been found significantly elevated compared against psychiatric disorders. However, there is still controversy of whether NfL peripheral levels might be altered in psychiatric disorders like major depressive disorder (MDD) when compared against a normal population.

The American Heart Association (AHA) recently introduced a new metric for promoting cardiovascular health (CVH) called Life's Essential 8 (LE8). However, there has been no investigation into the relationship between levels of LE8 and the risk of depression symptom. Therefore, our objective was to determine this association using a nationally representative sample of U.S adults.

This study aimed to investigate the independent or synergistic effects of evening chronotype and poor sleep quality on cognitive impairment in patients with major depressive disorder (MDD).

Methylphenidate (MPH), a central nervous system stimulant primarily prescribed for attention-deficit/hyperactivity disorder (ADHD), has seen increasing rates of misuse and abuse, particularly in patients with dual diagnosis (co-occurring psychiatric disorders and substance use disorders/SUDs). The heightened risk of dependence and adverse effects in these vulnerable populations warrants a systematic review to assess the prevalence and pattern of abuse/misuse of MPH among patients within this population and to understand potential risk factors, patterns of misuse, and outcomes, including the impact on psychiatric symptoms and overall mental health, the effects on SUD (e.g., exacerbation or mitigation of symptoms), and the incidence of adverse events and complications (e.g., cardiovascular issues, psychological effects).

People with severe mental illness experience physical health inequalities and a 15-20-year premature mortality rate. Forensic inpatients are particularly affected by restrictions on movement, long admissions, and obesogenic/sedative psychotropic medication. We aimed to establish the feasibility and acceptability of Motiv8, a multidisciplinary weight management intervention co-produced with service users for forensic inpatients.

Suicide disproportionately affects the military and veteran population, yet the task of identifying those at an increased risk of suicidal behavior remains challenging. In the face of this complex issue, novel machine learning methods have been applied to study the relationship between suicide and potential risk factors, but are often not generalizable to new and unseen samples. Herein, we examine the problem of prediction on unknown environments, commonly known as environment-wise domain adaptation, as it relates to the prediction of suicidal beliefs, measured with items from the Suicide Cognitions Scale (SCS). We adapt several recently invariance-based models trained using a sample consisting of people without any prior suicidal ideation (SI) to the prediction of suicidal beliefs of those with prior SI. In addition, we examine the possible causal relations regarding the SCS. Using a prospective sample of 2744 primary care patients with 17 risk and protective factors, we show that, to some extent, these methods are able to generalize to a new environment, namely, a sample with prior SI. Additionally, our results indicate suicidal ideation and suicidal behavior are likely to be causal children of SCS.

Digital health interventions specifically those realized as chatbots are increasingly available for mental health. They include technologies based on artificial intelligence that assess user's sentiment and emotions for the purpose of responding in an empathetic way, or for treatment purposes, e.g. for analyzing the expressed emotions and suggesting interventions.

This study aimed to investigate the prevalence of cognitive impairment among patients with major depressive disorder (MDD) hospitalized during the acute phase and to analyze the in-depth association between this cognitive impairment and clinical correlation factors.

A number of studies have demonstrated that suicidal ideation in late life is associated with early-life circumstances. However, the importance of early-life circumstances in predicting suicidal ideation is not entirely clear. This study aims to use a machine learning approach to evaluate the importance of 32 early-life circumstances from six domains in predicting suicidal ideation in old age.

Cancer can have negative effects on mental health. The aim of this study was to investigate the prevalence of anxiety symptoms/disorders in cancer patients' worldwide using meta-analysis.

With the advancement of transcranial electrical stimulation (tES) technology, an increasing number of stimulation devices and treatment protocols have emerged. However, safety and tolerability remain critical concerns before new strategies can be implemented. Particularly, the use of gel particle electrodes brings new challenges to the safety and tolerability of tES, which hinders its widespread adoption and further research.

The prevailing view is that loneliness predominantly affects older adults. However, awareness of high rates of loneliness among younger populations is growing, prompting a call for interventions. The current study aimed to listen to the voices of young people regarding how they cope with loneliness, gaining a better understanding of how to then develop tailored interventions.

Despite the increasing proportion of older-aged individuals suffering from problematic gambling, research on gambling among this specific age cohort is still in its infancy. Chasing is a pathognomonic feature of disordered gambling and is considered one of the key risk factors in the transition from recreational to disordered gambling. Despite the increased research on chasing over the past decade, no previous study has ever examined the psychological determinants of chasing behavior among old-aged gamblers. Given the importance of chasing in facilitating and maintaining problem gambling, and the paucity of research examining gambling among older individuals, the present study is the first to empirically investigate the joint role of chasing behavior, negative affectivity, and mentalizing among older-aged gamblers.

The purpose of this study was to explore the key pathways leading to low quality of life in type 2 diabetes patients by means of network analysis, so as to provide the possibility of effective interventions.