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889 results for “Suicides”
Dataset Multifaceted intervention for patients admitted to an emergency unit for suicide attempt: an exploratory study
<p>This dataset is related to "Multifaceted intervention for patients admitted to an emergency unit for suicide attempt: an exploratory study" (Brovelli S., Dorogi Y., Feiner A.-S., Golay P., Stiefel F., Bonsack C. & Michaud L.)</p>
Weekly county-level pollution data for China from Zhang, Carleton, Lin, and Zhou (accepted, Nature Sustainability), "Estimating the role of air quality improvements in the decline of suicide rates in China"
<p>This dataset contains weekly, county-level air pollution data for 2,839 counties from 2013 to early 2018. These data are used and described in Zhang, Carleton, Lin, and Zhou (accepted, <em>Nature Sustainability</em>), "Estimating the role of air quality improvements in the decline of suicide rates in China". When the paper is published a link to the manuscript will be added here. </p> <p>The manuscript Methods section details data construction. In summary, these county-level observations are obtained from monitoring stations maintained by the China National Environmental Monitoring Center (CNEMC), which is affiliated with the Ministry of Ecology and Environment of China. CNEMC began publishing hourly air pollution data in 2013, including the Air Quality Index, PM2.5, PM10, ozone, sulfur dioxide, nitrogen dioxide, and carbon monoxide. We average hourly data to the station-day level and use inverse-distance weighting with a radius of 200km to convert data from station to the county level. We average across days to generate county-level weekly values. Any missing station-hour observations in the raw data are omitted in this spatial and temporal aggregation. Our main analysis relies on PM2.5, but all pollutants are released here.</p>
Obesity, Suicides and Unemployment by Country
<p>This dataset contains data about obesity, suicides and unemployment segregated by Country. The sources of data are wikipedia tables as updated on 11/04/2022. More information can be found in project's github: <a href="https://github.com/martinsanc/wikipedia_scraper"><strong>https://github.com/martinsanc/wikipedia_scraper</strong></a></p> <p> </p> <ul> <li> <p><strong>Países (<a href="https://en.wikipedia.org/wiki/List_of_countries_by_population_(United_Nations)">List of countries by population (United Nations) - Wikipedia</a>)</strong></p> <ul> <li> <p><strong>Country</strong></p> </li> <li> <p><strong>UN continental region</strong></p> </li> <li> <p><strong>UN statistical subregion</strong></p> </li> <li> <p><strong>Population 1 July 2018</strong></p> </li> <li> <p><strong>Population 1 July 2019</strong></p> </li> <li> <p><strong>Change</strong></p> </li> </ul> </li> <li> <p><strong>Desempleo (<a href="https://en.wikipedia.org/wiki/List_of_countries_by_unemployment_rate">List of countries by unemployment rate - Wikipedia</a>)</strong></p> <ul> <li> <p><strong>Unemployment Rate</strong></p> </li> <li> <p><strong>Sourcedate of information</strong></p> </li> </ul> </li> <li> <p><strong>Suicidios (<a href="https://en.wikipedia.org/wiki/List_of_countries_by_suicide_rate">List of countries by suicide rate - Wikipedia</a>)</strong></p> <ul> <li> <p><strong>All</strong></p> </li> <li> <p><strong>Male</strong></p> </li> <li> <p><strong>Female</strong></p> </li> </ul> </li> <li> <p><strong>Tasa de obesidad por país (<a href="https://en.wikipedia.org/wiki/List_of_countries_by_suicide_rate">List of countries by suicide rate - Wikipedia</a>)</strong></p> <ul> <li> <p><strong>Rank</strong></p> </li> <li> <p><strong>Obesity rate</strong></p> </li> </ul> </li> </ul>
APC modeling datasets of suicide in Brazil
<p>Datasets of Age-Period-Cohort analysis of suicides in Brazil, part of the PhD thesis of Pauliana Valéria Machado Galvão, supervised by Dr. Cosme Marcelo Furtado Passos da Silva</p>
Global suicide mortality rates (2000-2019) and bibliographic data
<p>The dataset contains World Bank Suicide mortality rate WDI (world development indicator) (2000-2019) world-wide data in original and processed form. In addition to the statistical data this dataset also contains bibliographic records of articles published on the topic of suicide in relation to individual countries during (2000-2019) in original and processed form. </p> <p>The data consists of six archives:</p> <ol> <li>World development indicator suicide mortality rate SH.STA.SUIC.P5. This archive contains suicide mortality rate of 159 countries during the period of 2000-2019 per 100,000 population including males and females as of November, 2023.</li> <li>Web of science records country and suicide. This archive contains bibliographic records organized by country on the topic of suicide related to that country published during 2000-2019 as of November, 2023.</li> <li>Suicide mortality rate statistics and keywords. This archive contains processed data of 1 and 2 archives in three files. The 'Countries suicide rates and WOS records' contains organized temporal suicide mortality rate data for each country and each year for males and females including counts of articles on suicide related in that country. The 'words and countries matrix' file contains information about how many times author and paper keywords from suicide related publications were seen in articles associated with each country. This data is organized as matrix in which rows are keywords, columns are countries and cells are counts of the keyword. The 'words and countries pairs' file contains same information only organized as keyword country pairs.</li> <li>Suicide mortality rate clusters countries keywords titles. This archive contains bibliographic data organized by country clusters. These clusters group countries with similar suicide mortality rate dynamics in males and females shown in two included figures. Each folder of the cluster contains a section with bibliographic records; a section with keywords associated with each country; and a section in which each publication associated with the country has a separate filecontaining its title and keywords.</li> <li>Suicide keywords embedding data. This archive contains word embedding vectors and metadata learned by recurrent neural network trained to classify countries from suicide related keywords of articles associated with those countries. Folder 'trained with keywords' contains embeddings learned in classifying countries in which training samples are keyword strings of publications. Folder 'trained with titles' contains embeddings learned in classifying countries in which training samples are strings containing titles of publication plus keywords.</li> <li>Suicide keywords association rule mining. This archive contains files of subsets of keywords frequently mentioned together in suicide related publications. Folder 'Mining in clusters' has frequent keyword itemsets in country clusters. Folder 'Mining in individual countries' has frequent keyword itemsets in countries. Examples of keyword networks connecting clusters and networks connecting countries in individual clusters are included which helps to identify specific and shared keywords by country clusters and by countries in the individual clusters. </li> </ol> <p>These datasets support a data availability statements for upcoming articles.</p>
Relationship between Australia suicide and Catalonia GDP
<p>Experiment that uses open data from 2000 to 2014.</p> <p><br> Datasets used:</p> <ul> <li>Suicide people in AUS:<br> https://data.oecd.org/healthstat/suicide-rates.htm</li> <li>Catalonia GDP by demand components (2000-2016):<br> https://www.kaggle.com/xavier14/catalonia-gdp-by-demand-components-20002016</li> </ul> <p>This Experiment compares these two datasets and make a chart for comparison.</p>
The relationship between linguistic expression and symptoms of depression, anxiety, and suicidal thoughts: A longitudinal study of blog content
<p>To investigate the associations between linguistic features and symptoms of depression, generalised anxiety, and suicidal ideation, we extracted linguistic features from individuals’ blog content and correlated it with validated mental health data in a longitudinal study (n=38). Depressive symptoms were assessed using the self-report Patient Health Questionnaire (PHQ-9), anxiety symptoms using the self-report Generalised Anxiety Disorder Scale (GAD-7), and social media data was analysed using the Linguistic Inquiry and Word Count (LIWC) tool for linguistic features. Bivariate and multivariate analyses were performed to investigate the correlations between the linguistic features and mental health scores between subjects. We then used the multivariate regression model to predict longitudinal changes in mood within subjects.</p>
Dataset of suicidal ideation texts in Brazilian Portuguese - Boamente System
<p>We obtained non-clinical texts from tweets (user posts of the online social network Twitter). To find suicide-related tweets, we used the Twitter API to download tweets in a personalized way based on search terms associated with suicide. After different experiments to retrieve relevant texts, 5699 tweets were collected in May 2021. Each downloaded tweet had user-specific information (for example, user ID, timestamp, language, location, number of likes, etc.). Still, we kept only the post content (suicide-related texts) and discarded the additional data. Therefore, all texts were anonymized. </p><p>After data collection, three psychologists were invited to perform the data annotation, in which they individually labeled each tweet. To avoid bias in the annotation process, we selected psychologists with different psychological approaches, namely cognitive behavioral theory, psychoanalytic theory, and humanistic theory. Professionals had to classify each tweet as negative for suicidal ideation (annotated as 0), or positive for suicidal ideation (annotated as 1). </p><p>All tweets with at least one divergence between psychologists (n = 1513) were excluded, resulting in a dataset with 4186 instances. 398 duplicate tweets were excluded. The final dataset consists of 2691 instances labeled negative and 1097 labeled positive.</p><p> </p>
BRAIN Journal-Suicide: Neurochemical Approaches-Figure 3. Representative gel electrophoreses showing the mRNA levels of BDNF, Trk B, NGF and Trk A
<p>Our present study, provides the evidence for the first time that two major neurotrophins<br> BDNF and NGF along with their cognitive TrkB and TrkA receptors are not only less expressed in<br> their protein levels but also their transcription levels are also compromised in postmortem brains of<br> suicide subjects as evident from the mRNA studies of the present experiment.</p>
BRAIN Journal-Suicide: Neurochemical Approaches-Figure 1. Representative bands of Western Blot showing the Protein levels of BDNF, Trk B, NGF and Trk A
<p>The molecular weights of BDNF, TrkB, NGF, TrkA and β-actin were 14 kDa, 145 kDa,<br> 13.5 kDa, 140 kDa and 46 kDa, respectively. The expression levels of BDNF, NGF, TrkB, and<br> TrkA proteins were normalized against the β-actin protein level, which was used as an internal<br> control. The results showed that the expression of BDNF, NGF, TrkB and TrkA in the hippocampus<br> decreased significantly in the suicide subjects when compared to the control subjects (P<0.05,<br> Figure 1).</p>
BRAIN Journal-Suicide: Neurochemical Approaches-Figure 2. Hippocampal BDNF and NGF levels of suicide subjects and normal controls
<p>Among the suicidal victims BDNF and NGF levels were significantly reduced in the<br> hippocampus compared to normal control subjects (tBDNF =5.43; df=18; p<0.001; tNGF =6.13; df=18;<br> p<0.001 Figure 2). Such observations clearly indicate the relation of chronic mental depression and<br> hippocampal neurotrophin levels.</p>
Functional and molecular characterization of suicidality factors using phenotypic and genome-wide data
<p>GWAS summary statistics for Functional and molecular characterization of suicidality factors using phenotypic and genome-wide data published in Molecular Psychiatry by Quintero Reis A, Newton BA, Kessler R, Polimanti R, and Wendt FR.</p>
Lithium for Suicidal Behavior in Mood Disorders
ClinicalTrials.gov study NCT01928446. IPD Sharing: YES. Countries: 1. Publications: 1.
Effect of Perimenstrual Ovarian Steroid Supplementation on Perimenstrual Suicidality
ClinicalTrials.gov study NCT03720847. IPD Sharing: YES. Countries: 1. Publications: 3.
Data for: Psychological distress, anxiety, suicidality, and wellbeing in New Zealand during the COVID-19 lockdown: a cross-sectional study
<p>Dataset for following paper.</p> <p>Introduction</p> <p>New Zealand's early response to the novel coronavirus pandemic included a strict lockdown which eliminated community transmission of COVID-19. However, this success was not without cost, both economic and social. In our study, we examined the psychological wellbeing of New Zealanders during the COVID-19 lockdown when restrictions reduced social contact, limited recreation opportunities, and resulted in job losses and financial insecurity.</p> <p>Methods</p> <p>We conducted an online panel survey of a demographically representative sample of 2010 adult New Zealanders. The survey contained three standardised measures – the Kessler Psychological Distress Scale (K10), the GAD-7, and the Well-Being Index (WHO-5) – as well as questions designed specifically to measure family violence, suicidal ideation, and alcohol consumption. It also included items assessing positive aspects of the lockdown.</p> <p>Results</p> <p>Thirty percent of respondents reported moderate to severe psychological distress (K10), 16% moderate to high levels of anxiety, and 39% low wellbeing; well above baseline measures. Poorer outcomes were seen among young people and those who had lost jobs or had less work, those with poor health status, and who had past diagnoses of mental illness. Suicidal ideation was reported by 6%, with 2% reporting making plans for suicide and 2% reporting suicide attempts. Suicidality was highest in those aged 18–34. Just under 10% of participants had directly experienced some form of family harm over the lockdown period. However, not all consequences of the lockdown were negative, with 64% reporting 'silver linings', which included enjoying working from home, spending more time with family, and a quieter, less polluted environment.</p> <p>Conclusions</p> <p>New Zealand's lockdown successfully eliminated COVID-19 from the community, but our results show this achievement brought a significant psychological toll. Although much of the debate about lockdown measures has focused on their economic effects, our findings emphasise the need to pay equal attention to their effects on psychological wellbeing.</p>
Differential ADAR editing landscapes in major depressive disorder and suicide.
<p>Neuropsychiatric disorders including depression and suicide are becoming an increasing public health concern. The current COVID19 pandemic by contributing to the rising rates of both depression and suicide has only hastened our need for objective and reliable diagnostic biomarkers. These can aide clinicians in not only diagnosing, but also in development of treatment plans for depression and suicide. While differential gene expression analysis has highlighted the serotonin signaling cascadeamong other critical neurotransmitter pathways to underly the pathology of depression and suicide, the biological mechanisms remain elusive. Well studied adenosine deaminase action on RNA (ADAR) editing sites such as serotonin and glutamate receptors have been examined individually one at a time. Here we propose a novel approach to better understand molecular underpinnings of neuropsychiatric disorders. We take advantage of publically available RNA-seq datasets to map ADAR editing landscapes in a more global gene-centric view. We use a unique combination of Guttman scaling and random forest classification modeling to create, describe and compare ADAR editing profiles focusing on both temporal and biological sex differences. We use a subset of experimentally confirmed ADAR editing sites located in known protein coding regions, the excitome, to map ADAR editing profiles in Major Depressive Disorder (MDD) and suicide. Using Guttman scaling, we were able to describe significant changes in editing profiles across brain regions in males and females with respect to cause of death (COD) and MDD diagnosis. The temporal distribution of editing sites may provide insight into biological mechanisms under-pinning clinical symptoms associated with MDD and suicidal behavior. Additionally, we use random forest modeling including these differential profiles among other markers of global editing patterns in order to highlight potential biomarkers providing insight into changes in synaptic plasticity. Together these models identify potential prognostic, diagnostic and therapeutic biomarkers for MDD diagnosis and/or suicide.</p>
APPETITE FOR SELF-DESTRUCTION: SUICIDAL BITING AS A NEST DEFENSE STRATEGY IN TRIGONA STINGLESS BEES
<p>Data 1 is an excel spreadsheet containing data needed to analyse<br /> "attack duration", as this is measured at the level of the individual bee.</p> <p>Data 2 is an excel spreadsheet containing data needed to analyse<br /> "probability of attack", "latency" (time until attack) and "number of bees",<br /> as these variables are analysed at the level of each flag wave on a colony.</p> <p>Data3 is an excel spreadsheet containing data for the "suicide" bioassay.<br /> A 1 in the self.sacrifice column indicates a dead bee, a 0 indicates a surviving one.</p> <p> </p>
State by State Rape Suicide and No Religion Rates from 2014 to 2020
<table> <tbody> <tr> <td>1. No Religion Rate</td> <td>The 2014 Data have been drawn from the Pew Religious Landscape Survey of that year.<span> </span>Pew Research Center. (2015). U.S. public becoming less religious. Pew Research Center. Data for the years 2014 - 2020 are from the Public Religion Research Institute (PRRI). Public Religion Research Institute. (2015). PRRI Religion and Politics Tracking Survey. PRRI. https://ava.prri.org/media/methodology/PRRI-AVA%20Issue%20Topline%202014.pdf.<span> </span>The data download process can be viewed at this URL: https://youtu.be/pG1KMFTjMso</td> </tr> <tr> <td>2. Suicide Rate</td> <td>The analysis makes use of state-by-state suicide rates.<span> </span>This used the data extraction tool maintained by the Centers for Disease Control (CDC) covering deaths for the years 1999-2020 <span>(CDC, 2021)</span><span>.<span> </span>The causes of death used for this analysis cover all those under the heading “Intentional Self-Harm”.<span> </span>These include the range of description codes from X60 to X84 under the International Classification of Diseases 10</span><span><sup>th</sup></span><span> revision (ICD10).<span> </span>CDC. (2021). Mortality 1999-2020 on CDC WONDER Online Database. Centers for Disease Control and Prevention, National Center for Health Statistics. National Vital Statistics System.<span> </span>https://wonder.cdc.gov/ucd-icd10.html</span></td> </tr> <tr> <td>3. Clery Act Rape Rate</td> <td>The Office of Postsecondary Education’s campus security handbook defines rape as “the penetration, no matter how slight, of the vagina or anus, with any body part or object, or oral penetration by a sex organ of another person, without the consent of the victim” <span>(Department of Education, 2016, pp. 3–6)</span><span>. All campus rape rates cited below are based on this new revised definition.<span> </span>For the purposes of calculating campus rape rates the full federal data files were downloaded from the Web site of the U.S. Department of Education. https://ope.ed.gov/campussafety/#/</span></td> </tr> <tr> <td>4. UCR Rape Rate</td> <td>The FBI reports state-by-state rape rates using a revised definition of rape <span>(Federal Bureau of Education, 2013)</span><span> that is identical to the Department of Education Handbook definition cited above.<span> </span>The FBI’s legacy definition is not used in any of the analyses described below.<span> </span>Just as institutions of higher education are required to report campus crime incidents to the federal Department of Education under the Clery Act, local police agencies are required to report crime incidents to the FBI under the Uniform Crime Reports (UCR) program.<span> </span>These rape rates are the number of crime incidents divided by the state population divided by 100,000.<span> </span>Data was downloaded using the FBI's Crime Data Explorer.<span> </span>https://cde.ucr.cjis.gov/LATEST/webapp/#/pages/home</span></td> </tr> </tbody> </table>
Suicide, mental health & economic statistics
<p>The dataset contains data on world suicide rate (per 100 000 people, 2000, 2005, 20010, 2016 years), mental disorders rate (population%, 2017), share of population with substance use disorders (population%, 1990-2016), GDP per capita by PPP (current US$, 1990-2017), adjusted net national income per capita (current US$, 2016) and unemployment rate (population %, 1991-2017), which are then analysed and compared by country. </p>
Accuracy of online survey assessment of mental disorders and suicidal thoughts and behaviors in Spanish university students. Results of the WHO World Mental Health-International College Student initiative.
<p>This dataset contains clinical data about 287 university students that participated in a clinical reappraisal study with the objective of examining the accuracy of WMH-ICS online screening scales for evaluating four common mental disorders (Major Depressive Episode, Mania/Hypomania, Panic Disorder, Generalized Anxiety Disorder) and suicidal thoughts and behaviors used in a survey of Spanish university students(UNIVERSAL project).</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.