Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
2,584
datasets available to search
ShareScore release 0.9.0
Dataset results
2,584 results for “Mentalization”
Hochfrequente Mental Health Surveillance
<p>Im Rahmen der Mental Health Surveillance (MHS) am Robert Koch-Institut (RKI) werden für eine Auswahl an Indikatoren der psychischen Gesundheit von Erwachsenen basierend auf Surveydaten Zeitreihen bestehend aus gleitenden Drei-Monats-Schätzern und Glättungskurven berechnet. Dadurch sollen Entwicklungen in der psychischen Gesundheit der erwachsenen Bevölkerung in Deutschland mit möglichst geringem Zeitverzug beobachtet und insbesondere negative Entwicklungen frühzeitig erkannt werden. Diese hochfrequente Surveillance wurde ursprünglich vor dem Hintergrund neuer Informationsbedarfe zur Entwicklung der psychischen Gesundheit der Bevölkerung in der COVID-19-Pandemie entwickelt.</p>
Data from: mPRIME Study - Interaction of Insulin Resistance with Cognition, Lifestyle, and Mental Health
<p>The presented datasets were collected within the <em>m</em>PRIME study, a prospective, observational study of the H2020 project Prevention and Remediation of Insulin Multimorbidity in Europe (PRIME) (grant No. 847879). The study investigates the interaction of insulin resistance with cognition, lifestyle, and mental health by combining traditional methods with ambulatory assessment and sensor-based data collection. Recruitment took place between March 2021 and March 2023 at the University Hospital Frankfurt, Germany.</p> <p>The eligibility criteria for the study were as follows: Age above 18 years, no intake of antidiabetic medication, insulin or glucocorticoids, no existing type 1 diabetes mellitus or gestational diabetes, no diagnoses of bipolar I disorder, schizophrenia, organically caused mental disorders and substance dependence, no severe neurological disorders, no current pregnancy or breastfeeding, no non-correctable visual impairments, no participation in medication-related studies within the last 6 months, no use of weight-reducing medications or a diet within the last 3 months, sufficient proficiency in German to complete questionnaires and neuropsychological tests.</p> <p>All participants in the <em>m</em>PRIME study provided written informed consent. The study protocol and procedures were approved by the local ethics committee.</p> <p><strong>Study Design</strong></p> <p>Individuals completed a baseline assessment and a one-week ambulatory assessment. The baseline assessment included: socio-demographic information, blood samples, anthropometric measures, neuropsychological tests, and several questionnaires. In addition, individuals were introduced to smartphone-based ecological momentary assessment (EMA), food protocols, and the use of sensors (continuous glucose monitor, accelerometer). Food protocols and EMA were conducted on three consecutive days, including two weekdays and one weekend day (Thursday to Saturday or Sunday to Tuesday). Several times a day, individuals were prompted via their smartphone to complete a working memory task and answer questions about stress, affect, and food intake. The continuous glucose monitor and accelerometer were worn continuously for 1 week.</p> <p> </p>
Dataset of The distinct influence of different maternal mental health symptom profiles on infant sleep during the first year postpartum: a cross-sectional survey
<p>The distinct influence of different, but comorbid, maternal mental health difficulties, such as postpartum depression, anxiety, or childbirth-related posttraumatic stress disorder (CB-PTSD) on infant sleep is unknown, although maternal mental health was reported to be associated with infant sleep. This paper first aimed to associations between maternal mental health symptoms and infant sleep. Second, it aimed to exploratory obtain maternal mental health symptom profiles from maternal mental health symptoms. Finally, it aimed to investigate the distinct influence of these maternal mental health symptom profiles on infant sleep, when including mediators (i.e., maternal perception of infant temperament and method to fall asleep) and moderators (maternal educational level and infant age).</p> <p>This dataset contains data on the mental health (i.e., CB-PTSD, depression, anxiety) of 410 mothers with an infant aged between 3 to 12 months old. Information on infant sleep and temperament (negative emotionality) was collected via standardised maternal-report questionnaires (City BiTS, EPDS, HADS, BISQ, and IBQ-R very short form). Sociodemographic data such as maternal age, marital status, educational level, infant age, and week of gestation are reported.</p> <p>This dataset is related to: Sandoz, V.; Lacroix, A.; Stuijfzand, S.; Bickle Graz, M.; Horsch, A. Maternal Mental Health Symptom Profiles and Infant Sleep: A Cross-Sectional Survey. <em>Diagnostics</em> <strong>2022</strong>, <em>12</em>, 1625. https://doi.org/10.3390/diagnostics12071625. </p>
Supporting Material for "Enhancing Mental Health and Cognitive Function in Older Adults: A Swiss Perspective on Public Health Interventions and Stigma Mitigation Strategies Informed by a Desk Review"
<p>This dataset contains all supporting material for the paper "Enhancing Mental Health and Cognitive Function in Older Adults: A Swiss Perspective on Public Health Interventions and Stigma Mitigation Strategies Informed by a Desk Review", published in the journal Swiss Psychology Open:</p> <p><em>Mack, M., Scarampi, C., Joly-Burra, E., Zuber, S., de Freitas, C., Teixeira, R. and Kliegel, M. (2025) ‘Enhancing Mental Health and Cognitive Function in Older Adults: A Swiss Perspective on Public Health Interventions and Stigma Mitigation Strategies Informed by a Desk Review’, Swiss Psychology Open, 5(1), p. 2. Available at: <a href="https://doi.org/10.5334/spo.81.">https://doi.org/10.5334/spo.81</a>.</em></p> <p>It includes the following documents and files:</p> <p><strong>S1. Protocol:</strong> ADVANCE Protocol for desk reviews</p> <p><strong>S2. Search strategy</strong></p> <p><strong>S3. Guidelines for title and abstract screening:</strong> Guidelines for the selection of articles included in the desk review</p> <p><strong>S4. Guidelines full-text screening:</strong> Guidelines for the selection of articles included in the desk review</p> <p><strong>S5. Guidelines data extraction:</strong> ADVANCE Guidelines/codebook data extraction</p> <p><strong>data extraction_desk review_switzerland.xlsx</strong></p> <p>This desk review was conducted as part of the ADVANCE project, which aims to enhance our understanding of mental health promotion and prevention. This desk review evaluates the current state of interventions for mental health and cognitive functioning among older adults in Switzerland focusing on the features of these interventions as well as on Swiss-specific contextual factors that contribute to vulnerability and stigma. This results of the desk review has been submitted for publication to 'LIVES Working Papers' and 'Swiss Psychology Open' . The two versions of the desk review differ slightly. The version for LIVES Working Papers, included the results of the Delphi survey and the resulting intervention scenarios. The version for Swiss Psychology Open, did not include the Delphi survey results and the resulting intervention scenarios, but included a more detailed discussion of the review results.</p>
Data for manuscript Marmet, Studer, Lemoine, Grazioli, Bertholet & Gmel (2019). Reconsidering the associations between self-reported alcohol use disorder and mental health problems in the light of co-occurring addictions in young Swiss men. Plos One. DOI: 10.1371/journal.pone.0222806.
<p>Dataset for the manuscript Marmet, Studer, Lemoine, Grazioli, Bertholet & Gmel (2019). Reconsidering the associations between self-reported alcohol use disorder and mental health problems in the light of co-occurring addictions in young Swiss men. Plos One. DOI: 10.1371/journal.pone.0222806.</p> <p>The dataset contains all data needed to reproduce the results in the above cited manuscript. Variable description and labels can be found in the codebook. For further information on the instruments used please refer to the manuscript.</p> <p>The data was collected between April 2016 and March 2018 in Switzerland by the C-SURF study (<a href="http://www.c-surf.ch">www.c-surf.ch</a>). Participants were on average 25 years old when they answered the questionnaires. The final sample size used in the manuscript is 5516. Please note that the dataset contains 25 datasets created with multiple imputation, therefore there are no missing values in the dataset.</p> <p>The research protocol for this study was approved by the Human Research Ethics Committee of the Canton Vaud (Protocol No. 15/07). Data collection was funded by the Swiss National Science Foundation (FN 33CSC0-122679, FN 33CS30_139467, FN 33CS30_148493)</p>
DATA to support Dyrk1a function in glutamatergic neurons in mouse models of Mental Retardation Disease 7 (MRD7) and Down syndrome (or trisomy 21)
<p>Four datasets are provided here to support the function of Dyrk1a in glutamatergic neurons in mouse models of Mental Retardation Disease 7 (MRD7) and Down syndrome (or trisomy 21):</p> <p>- RNAseq data to compare hippocampal expressed genes at postnatal day 30, in the complete inactivation of Dyrk1a in glutamatergic neurons using a Dyrk1a floxed-allele and the Camk2:Cre transgene</p> <p>- data from all the figures</p> <p>-data from all the supplementary figures </p> <p>-data from the quantitative proteomic analysis made from hippocampal extract of wt, Dyrk1a heterozygote, Dp(16)1Yey and Dp(16)1Yey with only two functional copies of Dyrk1a</p> <p>Detailed information are available in the article by Brault et al 2021, deposited in Biorachiv https://doi.org/10.1101/2021.05.01.442242 </p>
NDVI Raster maps of Scotland for 2013-2016 used to analyse correlations between greenness, mortality and mental health.
<p>These files were used in the analysis for "Greenness, mortality and mental health prescription rates in urban Scotland - a population level, observational study" Hyam. Submitted to RIO 2020.</p> <p><strong>Extract on construction of data</strong></p> <p>NDVI data was downloaded from the United States Geological Survey (USGS) Land Satellites Data System (LSDS) Science Research and Development (LSRD) (United States Geological Survey 2018). Which produces Level 2 and Level 3 data products from the Level 1 data of instruments aboard Landsat Satellites. For this study Surface Reflectance data generated by the Landsat Surface Reflectance Code (LaSRC) from the Operational Land Imager (OLI) instrument aboard the Landsat 8 satellite was used (United States Geological Survey 2018). The Surface Reflectance NDVI (sr_ndvi) product and Level-2 Pixel Quality Assessment band (pixel_qa) were downloaded for Landsat scenes 204/21, 205/21, 206/21, 204/20, 205/20, 206/20 WRS-2 (NASA 2018) for the calendar years 2013 to 2016. These scenes cover most of Scotland and include all the major urban areas. A full list of the 333 products is given in supplemental material. Suppl. material 2</p> <p>All of Scotland is over 54° North and so for many satellite images the sun is at too low an angle to give reliable surface reflectance data especially in the winter months. Scotland also has an oceanic climate so the ground is often obscured by cloud or mist. To build a detailed, contiguous NDVI map of the whole country therefore requires combining images taken on many satellite passes especially if points are to be sampled multiple times to overcome measurement errors. The images downloaded from USGS were therefore combined. A cloud free version of each NDVI image was created by setting the pixels that corresponded to cloud, snow or water in the Quality Assurance Assessment band to NA. These cloud free images were then combined into a single, mosaic stack of images to cover all of the study area and then averaged down to a single layer as a tiff image. This was done for two seasonal periods, Winter (October, November, December of 2013, 2014, 2015 and 2016 combined with January, February, March of 2014, 2015, 2016) and summer (April, May, June, July, August, September of 2014, 2015, and 2016). The resulting two images covering most of Scotland for winters and summers between 2013 and 2016 and formed the basis of subsequent analysis.</p> <p>These two files are included here along with a list of the Landsat products used to produce them.</p>
Implications of Socio-Economic Conditions on Common Mental Disorders: A Case-study of Salt Pan Workers in Marakkanam Block of Tamil Nadu
<p>Socio-economic indicators of Saltpan workers in Marakaanam, Tamil Nadu, India and their SRQ-20 scoring.</p><p>Data regarding; Consumption, Wages, Debt, Social Group, Gender, Age, Ration Card, Education, Distance from work(saltpan), ownership of house and the SRQ-20 Questionanaire used for Screening of CMDs and Distress levels </p>
CONFLUÊNCIAS POÉTICAS: UM DOCUMENTÁRIO SOBRE FORMAÇÃO E CUIDADO EM SAÚDE MENTAL
<p>Trata-se de um documentário feito pela Liga Acadêmica de Saúde Mental da Faculdade de Enfermagem da Universidade do Estado do Rio de Janeiro (LIASME/UERJ). O documentário registou o trabalho com rodas de poesia do Centro de Atenção Psicossocial da UERJ em que docentes, alunos de graduação em enfermagem e residentes multiprofisisonais aprendem sobre o cuidado vivo a pessoas em sofrimento psiquico grave. </p>
Mapa Mental: Protección del trabajador desde la normatividad legal vigente en SST
<p>Mapa mental donde se visualiza tres normas en materia de Seguridad y Salud en el Trabajo que le aportan a la Protección del trabajador, y estas son: Ley 1562 de 2012, Decreto 1072 de 2015 y Resolución 0312 de 2019.</p>
Effects of sleep restriction and light intensity on mental effort during cognitive challenge Study 2
<p>This repository contains the data of Study 2 of the manuscript "Effects of sleep restriction and light intenisty on mental effort during cognitive challenge" by Larissa Wüst and Ruta Lasauskaite.</p>
Quantitative account of social interactions in a mental health care ecosystem: cooperation, trust and collective action
<p>Mental disorders have an enormous impact in our society, both in personal terms and in the economic costs associated with their treatment. In order to scale up services and bring down costs, administrations are starting to promote social interactions as key to care provision. We analyze quantitatively the importance of communities for effective mental health care, considering all community members involved. By means of citizen science practices, we have designed a suite of games that allow to probe into different behavioral traits of the role groups of the ecosystem. The evidence reinforces the idea of community social capital, with caregivers and professionals playing a leading role. Yet, the cost of collective action is mainly supported by individuals with a mental condition - which unveils their vulnerability. The results are in general agreement with previous findings but, since we broaden the perspective of previous studies, we are also able to find marked differences in the social behavior of certain groups of mental disorders. We finally point to the conditions under which cooperation among members of the ecosystem is better sustained, suggesting how virtuous cycles of inclusion and participation can be promoted in a ’care in the community’ framework.</p>
MHMisinfo - Video-based Mental Health Misinformation Dataset
<p>MHMisinfo-Gold and MHMisinfo-Large datasets, as described in the paper "Supporters and Skeptics: LLM-based Analysis of Engagement with Mental Health (Mis)Information Content on Video-sharing Platforms" (forthcoming at ICWSM 2025). Videos and comments for each dataset are seperately stored in different .csv files</p> <p><strong>Dataset schema, videos</strong></p> <table> <tbody> <tr> <th><strong>Column Name</strong></th> <th><strong>Description</strong></th> </tr> <tr> <td><strong>video_id</strong></td> <td>ID of the Video, as assigned by their respective platforms</td> </tr> <tr> <td><strong>video_title</strong></td> <td>The title of the video</td> </tr> <tr> <td><strong>video_description</strong></td> <td>The description of the video, given by the video creators</td> </tr> <tr> <td><strong>audio_transcript</strong></td> <td>Text transcription of the video's audio track, as generated by Whisper speech-to-text model</td> </tr> <tr> <td><strong>video_view_count</strong></td> <td>View count of the video, at the time of data collection</td> </tr> <tr> <td><strong>video_like_count</strong></td> <td>Like count of the video, at the time of data collection</td> </tr> <tr> <td><strong>video_comment_count</strong></td> <td>Comment count of the video, at the time of data collection</td> </tr> <tr> <td><strong>label_ioi</strong></td> <td>"Information of Interventions" label of video, annotated by experts. 1 = High-quality information on interventions, -1 = Low-quality information on interventions</td> </tr> <tr> <td><strong>label_ebt</strong></td> <td>"Evidence-based Treatment" label of video, annotated by experts. 1 = Encourages evidence-based treatment, -1 = Discourages evidence-based treatment</td> </tr> <tr> <td><strong>label_aoc</strong></td> <td>"Alignment of Consensus" label of video, annotated by experts, 1 = High Alignment with Consensus, -1 = Low Alignment with Consensus</td> </tr> <tr> <td><strong>label</strong></td> <td>Overall mental health misinformation label of the video. 0 = non-MHMisinfo videos, and -1 = MHMisinfo videos</td> </tr> <tr> <td><strong>platform</strong></td> <td>Platform of the video</td> </tr> </tbody> </table> <p><strong>Dataset schema, comments</strong></p> <table> <tbody> <tr> <th><strong>Column Name</strong></th> <th><strong>Description</strong></th> </tr> <tr> <td><strong>text</strong></td> <td>The raw text of the comment</td> </tr> <tr> <td> <p><strong>commenter_channel_display_name</strong></p> </td> <td>The display name of the user who posted the comment.</td> </tr> <tr> <td> <p><strong>comment_publish_date</strong></p> </td> <td>The time when the comment was orignally published, .</td> </tr> <tr> <td> <p><strong>video_id</strong></p> </td> <td>ID of the Video associated by the platform, as assigned by their respective platforms</td> </tr> <tr> <td> <p><strong>platform</strong></p> </td> <td>Platform of the video associated with the comment</td> </tr> <tr> <td> <p><strong>label</strong></p> </td> <td>Overall mental health misinformation label of the video associated with the comment. 0 = non-MHMisinfo videos, and -1 = MHMisinfo videos</td> </tr> </tbody> </table> <p> </p>
Shopping in Immersive Virtual Reality: Effects of Visual, Auditory, and Cognitive Demands on Mental Workload
<p>The dataset - of the journal article "Shopping in Immersive Virtual Reality: Effects of Diminishing Visual, Auditory, and Cognitive Demands on Workload" - consists of heart rate and eye-tracking data per participant and experimental condition. It also contains the figures inserted in the manuscript, the MATLAB scripts, the Unity project of an immersive virtual supermarket, and a demo video of a participant performing a grocery task across the experimental conditions in the virtual supermarket.</p>
Qualitative Data on Effects of Early and Prolonged Parent-Child Separation: Understanding Mental Health of Separated-Reunited Chinese American Children
<div> <div> <div> <div>Early and prolonged parent-child separation due to parental migration or immigration may result in attachment disruption that can threaten the long-term mental health and functioning of affected children, and these risks can persist following reunification and through adulthood. Although sending infants back to the home country for rearing is often practiced among <em>Chinese</em> immigrants, especially low-income families, research has been sparse in understanding the long-term impact of early and prolonged parent-child separation and reunification on disparities in mental health and functioning among separated-reunited children and the mechanism through which such relationships may operate.</div> <div>Funded by National Institute on Minority Health and Health Disparities (NIMH), we collected semi-structured interview data from 24 parent-child dyads who have experienced separation. The data included interview scrpits with primary coding to understand the mental health impacts, risk/protective factors, and service needs among separated-reunited <em>Chinese</em> American children.</div> </div> </div> </div> <div> </div>
An EEG dataset for cross-session mental workload estimation: Passive BCI competition of the Neuroergonomics Conference 2021
<p>The dataset is part of a new open EEG database designed to answer a need for more publicly available EEG-based dataset to design and benchmark passive brain-computer interface pipelines (as detailed in [Hinss2021]). This database is currently being created and will be fully released before the end of the year. It will include data acquired over 30 participant, 4 tasks and 3 sessions. For this competition, hosted by the Neuroergonomics Conference 2021, only one task and half the participants will be analyzed. Hence, this competition focuses on a renowned task that elicits various levels of mental/cognitive workload: the Multi-Atribute Task Battery-II (MATB-II) developed by NASA (https://matb.larc.nasa.gov/). It is composed of 4 sub-tasks: system monitoring, tracking, resource management and communications. By varying the number and complexity of the sub-tasks, 3 levels of workload were elicited (verified through statistical analyzes of both subjective and objective -behavioral and cardiac- data). Each difficulty level was performed by 15 subjects (6 female; 9 average 25 y.o.) during 5 minutes per session, in a pseudo-randomized order. Each session was separated by 7 days. We used a 62 actiChamp EEG channels device (BrainProducts; electrode placement 10-20 system).</p> <p> </p> <p><strong>For the competition, your goal is to predict the mental workload for a given subject (intra-subject estimation) using the EEG data from another session (inter-session adaptation). More information on the conference website and in the documentation file.</strong></p>
Datasets for testing the computational thinking of children with mental disabilities by cCT-test
<p>This study aims to evaluate the impact of web technologies on the development of computational thinking of students with mental disabilities. The experiment involved 14 students aged 8-12. For 8 weeks children were trained in computational thinking and computer science. Assessment of computational thinking was performed with cCT-test by El-Hamamsi et al. before and after the experiment (El-Hamamsy, L., Zapata-Cáceres, M., Barroso, E. M., Mondada, F., Zufferey, J. D., & Bruno, B. (2022). The competent Computational Thinking Test: Development and Validation of an Unplugged Computational Thinking Test for Upper Primary School. Journal of Educational Computing Research, 07356331221081753 <a href="https://doi.org/10.1177/07356331221081753">https://doi.org/10.1177/07356331221081753</a>).</p> <p>After conducting computer science lessons using web technologies the respondents showed a higher level of computational thinking (M=15,7, SD=3,69), compared to the results of preliminary testing (M=5,93, SD=2,3). Web technologies can significantly increase the effectiveness of inclusive pedagogy, which establishes the importance of integrating web technologies into the teaching system in inclusive classes of general education schools.</p> <p>Examples of tasks are located at the link <a href="https://miro.com/app/board/uXjVPz8p6LE=/?share_link_id=864046044746">https://miro.com/app/board/uXjVPz8p6LE=/?share_link_id=864046044746</a> </p> <p>https://wordwall.net/resource/48631685</p> <p>https://wordwall.net/resource/48650842</p> <p>https://wordwall.net/resource/48655774</p> <p>https://wordwall.net/resource/48661305</p> <p> </p>
Data from: CoAct Citizen Science chatbot explores social support networks in mental health based on lived experiences
<p>A data set on lived experiences in the context of social support in mental health, created within a Citizen Social Science project. </p> <p><br> Societies around the world increasingly encounter wicked and complex problems, such as those related to mental health, environmental justice, and youth employment. <strong>CoAct as a EU-funded global effort</strong> addresses these problems by deploying Citizen Social Science. </p> <p> </p> <p><strong>Citizen Social Science</strong> is understood here as participatory research co-designed and directly driven by citizen groups sharing a social concern. This methodology wants to give citizen groups an equal ‘seat at the table’ through <strong>active participation in research</strong>, from the design to the interpretation of the results and their transformation into concrete actions. Citizens thus act as <strong>co-researchers</strong> and are recognised as in-the-field competent experts. </p> <p> </p> <p>In Barcelona, a group of <strong>32 co-researchers</strong> work together with the OpenSystems group, Universitat de Barcelona, the Catalan Federation of Mental Health (Federació Salut Mental Catalunya), and with the help of many others on a better understanding of informal <strong>social support networks in mental health</strong> in the project <em>CoActuem per la Salut Mental</em> (lit. “We act together for mental health”). The co-researchers, who are either persons with a personal history of mental health problems or are family members of the latter, contributed their <strong>personal experiences related to social support</strong> in the form of <strong>222 micro-stories</strong>, each shorter than 400 characters, and most accompanied by an illustration by Pau Badia.</p> <p> </p> <p>Those micro-stories form the heart of the first co-created Citizen Science chatbot, the code of which is open on <a href="https://github.com/Chaotique/CoActuem_per_la_Salut_Mental_Chatbot.git">https://github.com/Chaotique/CoActuem_per_la_Salut_Mental_Chatbot.git</a> . The <strong>Telegram chatbot</strong> sends them to participants <strong>on a daily basis over the course of a year</strong> and asks them either, whether they and/ or their close surrounding lived this experience, too (stories of type C), or, how they would or would have reacted in the presented situation (stories of type T). The answers of each participant can be contrasted with the individual participants’ answer to a 32-questions <strong>socio-demographic survey</strong>. Further, the timing of the messages is included to allow for a broader analysis. </p> <p> </p> <p>The chatbot is still running, hence this data set will still be updated. For further information on the project <strong>CoAct</strong>, see <a href="https://coactproject.eu/">https://coactproject.eu/</a>. For further details on the co-creation process and purpose of the chatbot <strong>CoActuem per la Salut Mental</strong>, take a look on <a href="https://coactuem.ub.edu/">https://coactuem.ub.edu/</a>. Please direct your questions regarding the data set to <strong>coactuem[at]ub.edu</strong>.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>The CoAct project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement number 873048. We especially thank the co-researchers for the passion and time invested.</p>
Intimate Partner Violence and Mental Health in Migrant Women Living in Spain
<p>This dataset contains data from a convenience sample in a cross-sectional study of intimate partner violence (IPV) and mental health in migrant women living in the Valencian Community of Spain. IPV was assessed using the Revised Composite Abuse Scale Short Form (CASR-SF), the Revised Scale of Economic Abuse (SEA2) and the Cyber Aggression in Relationship Scale (CARS). Mental health was assessed using the PHQ-9 for symptoms of depression and the GAD-7 for symptoms of anxiety.</p>
PsPM-CogSF: SCR, ECG and respiration measurements during mental arithmetic, attention, and rest
<p>This dataset includes skin conductance, ECG and respiration measurements for 20 healthy unmedicated participants (9 males and 11 females aged 23.68 +/- 2.94 years, gender information misprinted in Bach & Staib 2015) undergoing two 120-s periods of resting, attention, or mental arithmetic (adding numbers). Selection and order of the two periods is contained as group information. An event marker is recorded at the beginning and the end of each period.</p>
ScienceDex guides
Understand access before you commit
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.