Npj mental health research最新文献

Mental health service use among individuals experiencing suicidality and self-harm is highly variable, with many individuals not seeking professional help. Using large-scale data from the UK Biobank, this study examined factors predictive of distinct service use phenotypes across varying levels of suicidality and self-harm. Male sex, the absence of psychological distress, and lower severity of suicide risk were the factors most strongly associated with reduced engagement with professional care. Additionally, although use of informal support predicted greater odds of service engagement, the type of support varied depending on suicidality severity: informal therapeutic strategies (e.g. yoga) were linked to service use among lower-risk individuals, whereas use of helplines was most strongly associated with service use among higher-risk individuals (e.g. those with a history of suicide attempts). These findings suggest that tailoring interventions to the unique needs and contexts of different subgroups may improve service engagement among individuals experiencing suicidality and/or self-harm.

University students remain vulnerable to the experience of loneliness and comorbid psychiatric difficulties, as evidenced in countries worldwide. In the present study, we examined the prevalence of loneliness among UK university students whilst assessing the association between multiple psychiatric risk factors. Here, N = 1408 students completed eight validated measures: Generalized Anxiety Disorder Scale; Patient Health Questionnaire; The Mood Disorder Questionnaire; The Sleep Condition Indicator; The Perceived Stress Scale; Suicidal Behaviours Questionnaire-Revised; The Prodromal Questionnaire 16; and the University of California Loneliness Scale. Moderate to severe levels of loneliness was reported by approximately two thirds of students (78.98%). Loneliness was significantly associated with each psychiatric symptom. After accounting for shared variance between symptoms, linear regression analyses determined loneliness to be significantly related to perceived stress, depression, psychotic like experiences and suicidal ideation. We demonstrate the exceedingly high prevalence of loneliness amongst large sample of UK university students, whilst highlighting the prominent role of depression, psychotic experiences, perceived stress, and suicidal ideation. Whilst highlighting the primacy of tailored interventions for lonely students, future work should explore contextual factors faced by UK university students.

In response to stress, the body attempts to maintain protein homeostasis through intron retention (IR). By identifying the genes that undergo IR in response to stress, possibly we can identify what type of stress the body is experiencing. Using this principle, we reanalyzed RNA sequencing data of patients with treatment-resistant depression and examined IR genes to investigate their characteristics to ketamine. The ketamine nonresponders were characterized by a state of elevated viral infection. Several IR genes related to viral infection were restored to a healthy state by ketamine, regardless of whether the individual was a nonresponder or a responder. Accordingly, it was more reasonable to describe nonresponders not as individuals for whom ketamine is ineffective but rather as individuals for whom ketamine is insufficient to overcome the extremely elevated inflammatory state of these individuals. This study is pioneering in its exploration of the molecular underpinnings that differentiate between nonresponders and responders.

The use of generative large language models (LLMs) in mental health applications is gaining traction, with some proposals even suggesting LLM-based automated therapists. In this study, we assess the impact of fine-tuning therapist LLMs to improve the quality of therapy sessions, addressing a critical question in LLM-based mental health research. Specifically, we demonstrate that fine-tuning with datasets focused on specific therapeutic techniques significantly enhances the performance of LLM therapists. To facilitate this assessment, we introduce a novel evaluation system based on digital patients, powered by LLMs, which engage in text-based therapy sessions and provide session evaluations through questionnaires designed for human patients. This method addresses the inadequacies of traditional text-similarity metrics, which are insufficient for assessing the quality of therapeutic interactions. This study centers on motivational interviewing (MI), a structured and goal-oriented therapeutic approach. However, our digital therapists and patients can be adapted to work in other forms of therapy. We believe that our digital therapists offer a standardized method for assessing automated therapists and showcasing the potential of LLMs in mental health care.

Loneliness is a growing global health issue, yet real-time assessments of its objective risk and protective factors are limited. This study identifies momentary and daily predictors using digital phenotyping and temporal analysis. Analyzing 12788 momentary observations from social mobile sensing and actigraphy, we examined how they impact loneliness on average (between-person) and in daily fluctuations (within-person). Instant messenger app usage was associated with increased loneliness, both momentarily (B = 2.95, p = 0.017) and daily (B = 2.83, p = 0.018), within and between subjects. Social media usage was associated with higher within-person momentary loneliness (B = 0.53, p = 0.001). An exploratory network analysis suggested that physical activity is associated with in-person social interaction, which is negatively associated with loneliness, while social media may replace social interactions. Thus, objective risk factors include increased use of social media and instant messaging, whereas greater physical activity may serve as a protective factor.

Recently, we found adults who received digital bibliotherapy featuring lived-experience narratives related to suicidal thoughts and behaviors reported lower suicidal thoughts, mediated by increased social connectedness and optimism. This study aimed to identify characteristics of narratives associated with decreased suicidal thinking and increased social connectedness and optimism. 1532 users of a social media platform responded to surveys before and after reading narratives. Mixed-methods content analysis and clustered multidimensional scaling tested whether clusters that shared narrative characteristics were related to suicidal thoughts, social connectedness and optimism. We identified three narrative clusters: Cluster 1: "Encouraging Readers to Live," Cluster 2: "Sharing Personal Stories," and Cluster 3: "Detailed Accounts." Clusters 2 and 3 were associated with greatest reduction in suicidal thoughts, Cluster 2 with the greatest increase in social connectedness, and Cluster 3 with the greatest increase in optimism. Results suggest the optimal narratives for reducing suicidal thoughts are personal, detailed accounts.

Learning involves reducing the uncertainty of incoming information-does it reflect meaningful change (volatility) or random noise? Normative accounts of learning capture the interconnectedness of this uncertainty: learning increases when changes are perceived as meaningful (volatility) and reduces when changes are seen as noise. Misestimating uncertainty-especially volatility-may contribute to psychotic symptoms, yet studies often overlook the interdependence of noise. We developed a block-design task that manipulated both noise and volatility using inputs from ground-truth distributions, with incentivised trial-wise estimates. Across three general population samples (online Ns = 580/147; in-person N = 19), participants showed normative learning overall. However, psychometric schizotypy and delusional ideation were linked to non-normative patterns. Paranoia was associated with poorer performance and reduced insight. All traits showed inflexible adaptation to changing uncertainty. Computational modelling suggested that non-normative learning may reflect difficulties inferring noise. This could lead one to misinterpret randomness as meaningful. Capturing joint uncertainty estimation offers insights into psychosis and supports clinically relevant computational phenotyping.

The pandemic has exacerbated mental health issues across the world. The limited availability of mental health professionals is preventing many from seeking help, which highlights the need for easily available mental health care routines like yoga, breathing, and meditation. A breath-based meditation technique known as Sudarshan Kriya Yoga (SKY) harnesses the power of breath to induce deep relaxation and makes meditation easier for beginners and has proven beneficial across multiple conditions, including depression, anxiety, and hypertension. The exact EEG dynamics happening during the practice are not well understood. We collected EEG data from 43 subjects undergoing SKY and analyzed their brain rhythms before, after, and during various stages of the technique, and found that rhythmic breathing accentuates theta rhythms (d = 0.63) which allows for an easier transition to a relaxed meditative state predominant with delta-theta rhythms, reduced alpha power (d = 1.70) and aperiodic signals (d = 2.04).

We examined real-world evidence on whether Lumosity, a remote digital health technology designed to deliver cognitive training to healthy adults, can improve cognition and reduce inattention in adults who reported having received a prior (lifetime) diagnosis of ADHD. Over the course of Lumosity training, this cohort of commercial users was assessed repeatedly online with a neuropsychological test battery (NCPT) and a scale of attention and mood in real-world contexts (BAMS-7). More Lumosity training between successive assessments led to greater improvements on the NCPT composite measure and the attentional subscale of the BAMS-7. This positive dose-response relation was found for six of eight NCPT subtests and three of four BAMS-7 attentional items. Additional findings support the participants' clinical status and sensitivity of the assessments to ADHD symptoms. These findings provide evidence of cognitive and attentional benefits in a real-world cohort of adults reporting a lifetime diagnosis of ADHD from training with Lumosity under real-world conditions.

The aim was to assess the effectiveness of an intervention comprising a teacher-training program and the implementation of a ten-session mindfulness-based intervention (MBI) in regular classroom teaching for 16- to 24-year-old students in Denmark. In a cluster-randomized trial (2019-2021), upper secondary schools and vocational schools for social and health care were randomly assigned 1:1 to receive the intervention (21 schools, 35 teachers, 438 students) or teaching-as-usual (22 schools, 38 teachers, 551 students). Eighteen self-report measures of mental health were collected at baseline, three, and six months, with the Warwick-Edinburgh Mental Well-Being Scale (SWEMWBS) as the primary outcome. Intention-to-treat analyses were conducted using mixed-effects linear regression and bootstrapping. Fourteen intervention schools (n = 277) and 17 teaching-as-usual schools (n = 419) provided follow-up data. No statistically significant effect on the primary outcome (SWEMWBS) was found in the total population. However, a small positive effect on SWEMWBS was observed among females in upper secondary schools at three months, but not sustained at six months. Trial Registration: ClinicalTrials.gov Identifier: NCT04610333, registered October 26, 2020, https://clinicaltrials.gov/ct2/results?cond=&term=NCT04610333&cntry=&state=&city=&dist= .