Christopher S. Y. Benwell, Greta Mohr, Jana Wallberg, Aya Kouadio, Robin A. A. Ince
{"title":"Psychiatrically relevant signatures of domain-general decision-making and metacognition in the general population","authors":"Christopher S. Y. Benwell, Greta Mohr, Jana Wallberg, Aya Kouadio, Robin A. A. Ince","doi":"10.1038/s44184-022-00009-4","DOIUrl":"10.1038/s44184-022-00009-4","url":null,"abstract":"Human behaviours are guided by how confident we feel in our abilities. When confidence does not reflect objective performance, this can impact critical adaptive functions and impair life quality. Distorted decision-making and confidence have been associated with mental health problems. Here, utilising advances in computational and transdiagnostic psychiatry, we sought to map relationships between psychopathology and both decision-making and confidence in the general population across two online studies (N’s = 344 and 473, respectively). The results revealed dissociable decision-making and confidence signatures related to distinct symptom dimensions. A dimension characterised by compulsivity and intrusive thoughts was found to be associated with reduced objective accuracy but, paradoxically, increased absolute confidence, whereas a dimension characterized by anxiety and depression was associated with systematically low confidence in the absence of impairments in objective accuracy. These relationships replicated across both studies and distinct cognitive domains (perception and general knowledge), suggesting that they are reliable and domain general. Additionally, whereas Big-5 personality traits also predicted objective task performance, only symptom dimensions related to subjective confidence. Domain-general signatures of decision-making and metacognition characterise distinct psychological dispositions and psychopathology in the general population and implicate confidence as a central component of mental health.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-17"},"PeriodicalIF":0.0,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-022-00009-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47972286","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}
Eric Jutkowitz, Christopher Halladay, Jack Tsai, Dina Hooshyar, Portia Y. Cornell, James L. Rudolph
{"title":"Association of statewide stay-at-home orders with utilization of case management and supportive services for veterans experiencing housing insecurity","authors":"Eric Jutkowitz, Christopher Halladay, Jack Tsai, Dina Hooshyar, Portia Y. Cornell, James L. Rudolph","doi":"10.1038/s44184-022-00010-x","DOIUrl":"10.1038/s44184-022-00010-x","url":null,"abstract":"The US Department of Housing and Urban Development-Department of Veterans Affairs (VA) Supportive Housing (HUD-VASH) program provides Veterans with a subsidy for rent and case management. In response to the Coronavirus 2019 pandemic, many states enacted stay-at-home orders that may have limited access to case managers. Therefore, we examined the association between statewide stay-at-home orders and utilization of HUD-VASH case management. We linked data on whether a state implemented a statewide stay-at-home order between March 1, 2020 and April 30, 2020 with VA medical records. Analysis time was centered on the date of a state’s stay-at-home order (exposed states). For Veterans in states without a stay-at home-order (unexposed states), we used the average date exposed states implemented an order (March 27, 2020). We used a difference-in-difference design and adjusted linear regression models to compare total, in-person, telephone, and video case management encounters per Veteran in the 60 days after a stay-at-home order relative to the prior year. There was no significant difference in utilization of case management between Veterans who lived in states that did and did not issue a stay-at-home order. Across all states and in the 60 days after the index date relative to the prior year, Veterans had more total, telephone and video, and fewer in-person encounters. Statewide stay-at-home orders did not differentially affect utilization of case management. Virtual case management in HUD-VASH can increase program reach; however, the effect of virtual case management on outcomes such as quality of life and Veteran satisfaction is unknown.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9412792/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9910555","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}
Ofir Shany, Guy Gurevitch, Gadi Gilam, Netta Dunsky, Shira Reznik Balter, Ayam Greental, Noa Nutkevitch, Eran Eldar, Talma Hendler
{"title":"A corticostriatal pathway mediating self-efficacy enhancement","authors":"Ofir Shany, Guy Gurevitch, Gadi Gilam, Netta Dunsky, Shira Reznik Balter, Ayam Greental, Noa Nutkevitch, Eran Eldar, Talma Hendler","doi":"10.1038/s44184-022-00006-7","DOIUrl":"10.1038/s44184-022-00006-7","url":null,"abstract":"Forming positive beliefs about one’s ability to perform challenging tasks, often termed self-efficacy, is fundamental to motivation and emotional well-being. Self-efficacy crucially depends on positive social feedback, yet people differ in the degree to which they integrate such feedback into self-beliefs (i.e., positive bias). While diminished positive bias of this sort is linked to mood and anxiety, the neural processes by which positive feedback on public performance enhances self-efficacy remain unclear. To address this, we conducted a behavioral and fMRI study wherein participants delivered a public speech and received fictitious positive and neutral feedback on their performance in the MRI scanner. Before and after receiving feedback, participants evaluated their actual and expected performance. We found that reduced positive bias in updating self-efficacy based on positive social feedback associated with a psychopathological dimension reflecting symptoms of anxiety, depression, and low self-esteem. Analysis of brain encoding of social feedback showed that a positive self-efficacy update bias associated with a stronger reward-related response in the ventral striatum (VS) and stronger coupling of the VS with a temporoparietal region involved in self-processing. Together, our findings demarcate a corticostriatal circuit that promotes positive bias in self-efficacy updating based on social feedback, and highlight the centrality of such bias to emotional well-being.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-022-00006-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46981950","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}
Katie Seaborn, Kailyn Henderson, Jacek Gwizdka, Mark Chignell
{"title":"A meta-review of psychological resilience during COVID-19","authors":"Katie Seaborn, Kailyn Henderson, Jacek Gwizdka, Mark Chignell","doi":"10.1038/s44184-022-00005-8","DOIUrl":"10.1038/s44184-022-00005-8","url":null,"abstract":"Psychological resilience has emerged as a key factor in mental health during the global COVID-19 pandemic. However, no work to date has synthesised findings across review work or assessed the reliability of findings based on review work quality, so as to inform public health policy. We thus conducted a meta-review on all types of review work from the start of the pandemic (January 2020) until the last search date (June 2021). Of an initial 281 papers, 30 were included for review characteristic reporting and 15 were of sufficient review quality for further inclusion in strategy analyses. High-level strategies were identified at the individual, community, organisational, and governmental levels. Several specific training and/or intervention programmes were also identified. However, the quality of findings was insufficient for drawing conclusions. A major gap between measuring the psychological resilience of populations and evaluating the effectiveness of strategies for those populations was revealed. More empirical work, especially randomised controlled trials with diverse populations and rigorous analyses, is strongly recommended for future research.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2022-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9255496/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9913122","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}
Peter J. Na, Jack Tsai, Steven M. Southwick, Robert H. Pietrzak
{"title":"Provision of social support and mental health in U.S. military veterans","authors":"Peter J. Na, Jack Tsai, Steven M. Southwick, Robert H. Pietrzak","doi":"10.1038/s44184-022-00004-9","DOIUrl":"10.1038/s44184-022-00004-9","url":null,"abstract":"While social support has been linked to better health, most research has focused on the receipt of social support. In this study, we evaluated associations between provided support and mental health in a nationally representative cohort of 4069 US veterans. The majority (60–72%) of veterans reported providing support on a consistent basis. Veterans who scored higher on certain aspects of personality (i.e., agreeableness, conscientiousness, and extraversion) and received greater support were more likely to provide support. Further, each standard deviation increase in provided support was independently associated with 22–32% reduced odds of internalizing psychiatric disorders and suicidal ideation, and veterans who scored higher on both provided and received support had 3.5- to 14-fold lower odds of these outcomes relative to those with high received support but low provided support. Results suggest that interventions to promote the provision of support may help mitigate risk for adverse mental health outcomes in veterans.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-022-00004-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48470652","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":"Machine learning based suicide prediction and development of suicide vulnerability index for US counties","authors":"Vishnu Kumar, Kristin K. Sznajder, Soundar Kumara","doi":"10.1038/s44184-022-00002-x","DOIUrl":"10.1038/s44184-022-00002-x","url":null,"abstract":"Suicide is a growing public health concern in the United States. A detailed understanding and prediction of suicide patterns can significantly boost targeted suicide control and prevention efforts. In this article we look at the suicide trends and geographical distribution of suicides and then develop a machine learning based US county-level suicide prediction model, using publicly available data for the 10-year period from 2010–2019. Analysis of the trends and geographical distribution of suicides revealed that nearly 25% of the total counties experienced at least a 10% increase in suicides from 2010 to 2019, with about 12% of total counties exhibiting an increase of at least 50%. An eXtreme Gradient Boosting (XGBoost) based machine learning model was used with 17 unique features for each of the 3140 counties in the US to predict suicides with an R2 value of 0.98. Using the SHapley Additive exPlanations (SHAP) values, the importance of all the 17 features used in the prediction model training set were identified. County level features, namely Total Population, % African American Population, % White Population, Median Age and % Female Population were found to be the top 5 important features that significantly affected prediction results. The top five important features based on SHAP values were then used to create a Suicide Vulnerability Index (SVI) for US Counties. This newly developed SVI has the potential to detect US counties vulnerable to high suicide rates and can aid targeted suicide control and prevention efforts, thereby making it a valuable tool in an informed decision-making process.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-022-00002-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41295831","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":"We all have “skin in the game” in mental health research: Inaugural editorial","authors":"Jack Tsai","doi":"10.1038/s44184-022-00003-w","DOIUrl":"10.1038/s44184-022-00003-w","url":null,"abstract":"","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-1"},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-022-00003-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45958681","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}
Maria Klitgaard Christensen, John J. McGrath, Natalie C. Momen, Harvey A. Whiteford, Nanna Weye, Esben Agerbo, Carsten Bøcker Pedersen, Preben Bo Mortensen, Oleguer Plana-Ripoll, Kim Moesgaard Iburg
{"title":"The cost of mental disorders in Denmark: a register-based study","authors":"Maria Klitgaard Christensen, John J. McGrath, Natalie C. Momen, Harvey A. Whiteford, Nanna Weye, Esben Agerbo, Carsten Bøcker Pedersen, Preben Bo Mortensen, Oleguer Plana-Ripoll, Kim Moesgaard Iburg","doi":"10.1038/s44184-022-00001-y","DOIUrl":"10.1038/s44184-022-00001-y","url":null,"abstract":"The aim of the study was to undertake a detailed analysis of healthcare cost, public transfer payments, and income loss associated with a broad range of mental disorders in Denmark. Based on all persons living in Denmark, we identified those with a hospital diagnosis of one of 18 types of mental disorders and 10 age- and sex-matched controls per case. For each mental disorder, the outcomes were nationwide totals, cost per case, and cost per capita, investigated by sex, age strata, and the number of years after diagnosis. We found a substantial annual income loss of 5 billion Euros and excess healthcare cost of 1 billion Euros for persons with any mental disorder. Each mental disorder was associated with an income loss, excess healthcare cost, and excess public transfer payments compared to matched controls. An interactive data visualisation site with summary data is available at https://nbepi.com/cost .","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-022-00001-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44103094","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}