Npj mental health research最新文献

{"title":"Neurocognitive consequences of adolescent sleep disruptions and their relationship to psychosis vulnerability: a longitudinal cohort study","authors":"Julien Ouellet, Roxane Assaf, Mohammad H. Afzali, Sima Nourbakhsh, Stéphane Potvin, Patricia Conrod","doi":"10.1038/s44184-024-00058-x","DOIUrl":"10.1038/s44184-024-00058-x","url":null,"abstract":"Adolescence is a key period for neurocognitive maturation where deviation from normal developmental trajectories may be tied to adverse mental health outcomes. Cognitive disruptions have been noted in populations at risk for psychosis and are known to accompany periods of sleep deprivation. This study aims to assess the role of cognition as a mediator between sleep disruptions and psychosis risk. A cohort of 3801 high school students (51% female, mean age = 12.8, SD = 0.45 years) was recruited from 31 Montreal high schools. Measures of sleep, psychotic-like experiences, inhibition, working memory, perceptual reasoning, and delayed recall were collected from participants on a yearly basis over the five years of their high school education. A multi-level model mediation analysis was performed controlling for sex and time squared. Response inhibition was shown to be associated with, and to mediate (B = −0.005, SD = 0.003, p = 0.005*) the relationship between sleep disruptions (B = −0.011, SD = 0.004, p < 0.001*) and psychotic-like experiences (B = 0.411, SD = 0.170, p = 0.005*). Spatial working memory deficits on a given year were associated with a higher frequency of psychotic-like experiences that same year (B = −0.046, SD = 0.018, p = 0.005*) and the following year (B = −0.051, SD = 0.023, p = 0.010*), but were not associated with sleep disturbances. No significant associations were found between our variables of interest and either delayed recall or perceptual reasoning at the within person level. Findings from this large longitudinal study provide evidence that the association between sleep disruptions and psychosis risk is specifically mediated by inhibitory rather than general cognitive impairments. The association of spatial working memory, response inhibition, and sleep disruptions with psychotic-like experiences suggests that these factors may represent potential targets for preventative interventions.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00058-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140878134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence of burnout among healthcare professionals: a survey at fort portal regional referral hospital","authors":"Ian Batanda","doi":"10.1038/s44184-024-00061-2","DOIUrl":"10.1038/s44184-024-00061-2","url":null,"abstract":"The work environment in most hospitals is characterised by activities that are strenuous both physically and mentally. These can result in physical and mental exhaustion, which can lead to burnout if not adequately addressed. Burnout among healthcare professionals can negatively affect their clinical decision-making, quality of communication with patients and colleagues as well as their ability to cope with work-related pressure, and ultimately affect the quality of care and patient outcomes. The inclusion of burnout in the 11th revision of the International Classification of Diseases (ICD-11) as an occupational phenomenon indicates that it is an issue of concern in the workplace for which people may need professional attention. This descriptive cross-sectional survey aimed to determine the point prevalence of burnout among healthcare professionals at Fort Portal Regional Referral Hospital and the factors contributing to burnout. The study also evaluated the linear relationship between the age of workers, their work duration at the hospital, and their burnout score, in addition to the possible impact on patient care. Participants were selected from the hospital WhatsApp group and invitations to participate were sent to their individual accounts. Burnout was assessed using the Copenhagen Burnout Inventory. Generally, burnout scores ranged from 16% to 86%, with an overall mean burnout score of 57.4%. The notable factors contributing to burnout included imbalances in duty allocation, physically strenuous work, and resource constraints. Burnout of varying levels was found to be prevalent across all carders in the hospital, although the results indicate that most healthcare professionals experience moderate burnout. Most of the factors contributing to burnout are within the scope of hospital leadership to address. The possible impact on staff performance and patients’ clinical outcomes is speculative, and additional studies are required.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00061-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140842591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying autism spectrum disorder from multi-modal data with privacy-preserving","authors":"Haishuai Wang, Hezi Jing, Jianjun Yang, Chao Liu, Liwei Hu, Guangyu Tao, Ziping Zhao, Ning Shen","doi":"10.1038/s44184-023-00050-x","DOIUrl":"10.1038/s44184-023-00050-x","url":null,"abstract":"The application of deep learning models to precision medical diagnosis often requires the aggregation of large amounts of medical data to effectively train high-quality models. However, data privacy protection mechanisms make it difficult to perform medical data collection from different medical institutions. In autism spectrum disorder (ASD) diagnosis, automatic diagnosis using multimodal information from heterogeneous data has not yet achieved satisfactory performance. To address the privacy preservation issue as well as to improve ASD diagnosis, we propose a deep learning framework using multimodal feature fusion and hypergraph neural networks for disease prediction in federated learning (FedHNN). By introducing the federated learning strategy, each local model is trained and computed independently in a distributed manner without data sharing, allowing rapid scaling of medical datasets to achieve robust and scalable deep learning predictive models. To further improve the performance with privacy preservation, we improve the hypergraph model for multimodal fusion to make it suitable for autism spectrum disorder (ASD) diagnosis tasks by capturing the complementarity and correlation between modalities through a hypergraph fusion strategy. The results demonstrate that our proposed federated learning-based prediction model is superior to all local models and outperforms other deep learning models. Overall, our proposed FedHNN has good results in the work of using multi-site data to improve the performance of ASD identification.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-023-00050-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140819081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measuring algorithmic bias to analyze the reliability of AI tools that predict depression risk using smartphone sensed-behavioral data","authors":"Daniel A. Adler, Caitlin A. Stamatis, Jonah Meyerhoff, David C. Mohr, Fei Wang, Gabriel J. Aranovich, Srijan Sen, Tanzeem Choudhury","doi":"10.1038/s44184-024-00057-y","DOIUrl":"10.1038/s44184-024-00057-y","url":null,"abstract":"AI tools intend to transform mental healthcare by providing remote estimates of depression risk using behavioral data collected by sensors embedded in smartphones. While these tools accurately predict elevated depression symptoms in small, homogenous populations, recent studies show that these tools are less accurate in larger, more diverse populations. In this work, we show that accuracy is reduced because sensed-behaviors are unreliable predictors of depression across individuals: sensed-behaviors that predict depression risk are inconsistent across demographic and socioeconomic subgroups. We first identified subgroups where a developed AI tool underperformed by measuring algorithmic bias, where subgroups with depression were incorrectly predicted to be at lower risk than healthier subgroups. We then found inconsistencies between sensed-behaviors predictive of depression across these subgroups. Our findings suggest that researchers developing AI tools predicting mental health from sensed-behaviors should think critically about the generalizability of these tools, and consider tailored solutions for targeted populations.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00057-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140632091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of temporal discounting with transdiagnostic symptom dimensions","authors":"Kristof Keidel, Xiaping Lu, Shinsuke Suzuki, Carsten Murawski, Ulrich Ettinger","doi":"10.1038/s44184-024-00060-3","DOIUrl":"10.1038/s44184-024-00060-3","url":null,"abstract":"Temporal discounting (TD), the tendency to devalue future rewards as a function of delay until receipt, is aberrant in many mental disorders. Identifying symptom patterns and transdiagnostic dimensions associated with TD could elucidate mechanisms responsible for clinically impaired decision-making and facilitate identifying intervention targets. Here, we tested in a general population sample (N = 731) the extent to which TD was related to different symptom patterns and whether effects of time framing (dates/delay units) and monetary magnitude (large/small) had particularly strong effects in people scoring higher on specific symptom patterns. Analyses revealed that TD was related to symptom patterns loading on anxious-depression and inattention-impulsivity-overactivity dimensions. Moreover, TD was lower in the date than the delay version and with higher magnitudes, especially in people scoring higher on the inattention-impulsivity-overactivity dimension. Overall, this study provides evidence for TD as a transdiagnostic process across affective and impulsivity-related dimensions. Future studies should test framing interventions in clinical populations characterized by impulsivity. Preregistration: This research was preregistered at https://osf.io/fg9sc .","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00060-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140556426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations between symptoms of attention-deficit hyperactivity disorder, socioeconomic status and asthma in children","authors":"Makiko Omura, Samuele Cortese, Marion Bailhache, Marie C. Navarro, Maria Melchior, Judith van der Waerden, Barbara Heude, Blandine de Lauzon-Guillain, Cédric Galera","doi":"10.1038/s44184-024-00064-z","DOIUrl":"10.1038/s44184-024-00064-z","url":null,"abstract":"Socioeconomic status (SES) influences the risk of both physical diseases, such as asthma, and neurodevelopmental conditions, including attention-deficit/hyperactivity disorder (ADHD). Using Causal Mediation Analysis on French birth-cohort data, we found a causal pathway from SES to ADHD symptoms, in part mediated by asthma. An increase in family income at age 3 by one unit resulted in lower ADHD symptoms at age 5, by −0.37 [95% CI: −0.50, −0.24] SDQ-score-points, with additional −0.04 [95% CI: −0.08, −0.01] points reduction indirectly via asthma at age 3, both with statistical significance. Importantly, family income at age 3 exerted both direct and indirect (via asthma) negative effects on later ADHD symptoms with much higher magnitudes for the direct effect. Our findings underscore the importance of apprehending ADHD symptoms in the broader context of socioeconomic disparities, along with their comorbidities with asthma, potentially influencing public health interventions and clinical practice in managing ADHD.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00064-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140556429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Are there distinct levels of language comprehension in autistic individuals – cluster analysis","authors":"Andrey Vyshedskiy, Rohan Venkatesh, Edward Khokhlovich","doi":"10.1038/s44184-024-00062-1","DOIUrl":"10.1038/s44184-024-00062-1","url":null,"abstract":"Autism is a neurodevelopmental condition characterized by deficits in social communication. We assessed 14-language comprehension abilities in 31,845 autistic individuals 4 to 21 years of age using parent-generated reports. Data-driven cluster analysis identified three distinct levels of language comprehension: (1) individuals in the command-language-phenotype were limited to comprehension of simple commands; (2) individuals in the modifier-language-phenotype showed additional comprehension of color, size, and number modifiers; 3) individuals in the most-advanced syntactic-language-phenotype added comprehension of spatial prepositions, verb tenses, flexible syntax, possessive pronouns, and complex narratives. The observation of three distinct language levels was consistent across different age groups. Autistic individuals’ communication level is currently commonly characterized as nonverbal, minimally-verbal, or verbal. This one-dimensional description is not ideal for characterizing an individual’s communication ability. In fact, a nonverbal individual with syntactic-language-phenotype may have normal ability to communicate albeit nonverbally, while a verbal person with command-language-phenotype does not have a normal ability to communicate by any means. Identification of the three distinct language-comprehension-phenotypes provides an opportunity to enhance characterization of individuals’ communication level. A composite description in terms of both, verbal abilities and a language-comprehension-level, will not only be more precise, but can improve language therapy by focusing it on both aspects of language development.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00062-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140544590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Post-traumatic stress disorder during the Covid-19 pandemic: a national, population-representative, longitudinal study of U.S. adults","authors":"Salma M. Abdalla, Catherine K. Ettman, Samuel B. Rosenberg, Ruochen Wang, Gregory H. Cohen, Sandro Galea","doi":"10.1038/s44184-024-00059-w","DOIUrl":"10.1038/s44184-024-00059-w","url":null,"abstract":"Substantial literature documents the impact of mass traumatic events on post-traumatic stress disorder (PTSD) in populations. However, the trajectory of PTSD in the US population during the pandemic and the association between assets, Covid-19 related stressors, and PTSD over time remains unclear. The Covid-19 and Life Stressors Impact on Mental Health and Well-Being (CLIMB) is a nationally representative, longitudinal panel of US adults in Spring 2020 (N = 1270), 2021 (N = 1182), and 2022 (N = 1091). Using the four-item PC-PTSD-4, we assessed the prevalence of probable PTSD in the US population over three years. Using generalized estimating equations (GEE) and logistic regression at each wave, we estimated associations of demographics, assets, and stressors with probable PTSD. Here we report that the overall prevalence of PTSD decreases from 22.2% in 2020 to 16.8% in 2022 (p = 0.02). Persons with household incomes below $20,000 report higher prevalence of probable PTSD compared to other income groups. The GEE model shows higher odds of probable PTSD among persons with household incomes below $20,000 (OR = 2.17 (95%CI: 1.35,3.50)) relative to $75,000 or more; and high stressor scores (OR = 2.33 (95%CI: 1.72,3.15)) compared to low stressor scores. High stressor scores are associated with higher odds of probable PTSD in 2020 (OR = 2.69 (95%CI: 1.56,4.66)), 2021 (OR = 4.58 (95%CI: 2.52,8.30)), and 2022 (OR = 3.89 (95%CI: 2.05,7.38)) compared to low stressor scores. This analysis highlights the pandemic’s prolonged influence on population mental health, particularly among persons with fewer economic assets and those experiencing more pandemic-related stressors. Reducing mental health disparities requires interventions to address inequities.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00059-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140544626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large language models could change the future of behavioral healthcare: a proposal for responsible development and evaluation","authors":"Elizabeth C. Stade, Shannon Wiltsey Stirman, Lyle H. Ungar, Cody L. Boland, H. Andrew Schwartz, David B. Yaden, João Sedoc, Robert J. DeRubeis, Robb Willer, Johannes C. Eichstaedt","doi":"10.1038/s44184-024-00056-z","DOIUrl":"10.1038/s44184-024-00056-z","url":null,"abstract":"Large language models (LLMs) such as Open AI’s GPT-4 (which power ChatGPT) and Google’s Gemini, built on artificial intelligence, hold immense potential to support, augment, or even eventually automate psychotherapy. Enthusiasm about such applications is mounting in the field as well as industry. These developments promise to address insufficient mental healthcare system capacity and scale individual access to personalized treatments. However, clinical psychology is an uncommonly high stakes application domain for AI systems, as responsible and evidence-based therapy requires nuanced expertise. This paper provides a roadmap for the ambitious yet responsible application of clinical LLMs in psychotherapy. First, a technical overview of clinical LLMs is presented. Second, the stages of integration of LLMs into psychotherapy are discussed while highlighting parallels to the development of autonomous vehicle technology. Third, potential applications of LLMs in clinical care, training, and research are discussed, highlighting areas of risk given the complex nature of psychotherapy. Fourth, recommendations for the responsible development and evaluation of clinical LLMs are provided, which include centering clinical science, involving robust interdisciplinary collaboration, and attending to issues like assessment, risk detection, transparency, and bias. Lastly, a vision is outlined for how LLMs might enable a new generation of studies of evidence-based interventions at scale, and how these studies may challenge assumptions about psychotherapy.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00056-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140340520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of mindfulness apps on psychological processes of change: a systematic review","authors":"Natalia Macrynikola, Zareen Mir, Tishmattie Gopal, Erica Rodriguez, Sunnie Li, Milann Cox, Gloria Yeh, John Torous","doi":"10.1038/s44184-023-00048-5","DOIUrl":"10.1038/s44184-023-00048-5","url":null,"abstract":"Mindfulness-based interventions (MBIs) have demonstrated therapeutic efficacy for various psychological conditions, and smartphone apps that facilitate mindfulness practice can enhance the reach and impact of MBIs. The goal of this review was to summarize the published evidence on the impact of mindfulness apps on the psychological processes known to mediate transdiagnostic symptom reduction after mindfulness practice. A literature search from January 1, 1993, to August 7, 2023 was conducted on three databases, and 28 randomized controlled trials involving 5963 adults were included. Across these 28 studies, 67 outcome comparisons were made between a mindfulness app group and a control group. Between-group effects tended to favor the mindfulness app group over the control group in three psychological process domains: repetitive negative thinking, attention regulation, and decentering/defusion. Findings were mixed in other domains (i.e., awareness, nonreactivity, non-judgment, positive affect, and acceptance). The range of populations examined, methodological concerns across studies, and problems with sustained app engagement likely contributed to mixed findings. However, effect sizes tended to be moderate to large when effects were found, and gains tended to persist at follow-up assessments two to six months later. More research is needed to better understand the impact of these apps on psychological processes of change. Clinicians interested in integrating apps into care should consider app-related factors beyond evidence of a clinical foundation and use app databases to identify suitable apps for their patients, as highlighted at the end of this review.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-023-00048-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140145881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}