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16,086 results for “Intervention”
Supporting data for “Climate Intervention through Stratospheric Aerosol Injection may partially mitigate marine heatwaves"
Although climate intervention aims to lower the global average temperature, the potential impact of Stratospheric Aerosol Injection on marine heatwaves (MHW) has not been thoroughly examined. This spatial dataset provides global and regional MHW metrics—such as frequency, maximum intensity, and duration—from the Community Earth System Model, version 2 (CESM2), using the baseline scenario SSP2-4.5, referred to as a no climate intervention scenario, and the ARISE-SAI ensemble. The ARISE-SAI model uses the SSP2-4.5 scenario, introducing stratospheric aerosol injection at approximately 21 km in 2035, aiming to keep global mean surface air temperature near 1.5°C for ARISE-SAI-1.5 and near 1.0°C for ARISE-SAI-1.0 above pre-industrial levels. The dataset includes global MHW properties for the historical period (1990-2009), the current period under SSP2-4.5 emission scenario (2015-2034), and future scenarios under SSP2-4.5, ARISE-SAI-1.5, and ARISE-SAI-1.5 for 2050-2059 and 2060-2069.
COgnitive intervention to Restore attention using nature Environment (CORE) study data
<p>The COgnitive intervention to Restore attention using nature Environment (CORE) study is single-blinded, two-group randomized-controlled pilot trial among patients with heart failure. The aims to test the preliminary efficacy of the newly developed Nature-VR, a virtual reality-based cognitive intervention that is based on the restorative effects of nature. The Nature-VR intervention group viewed 3-dimensional nature pictures using a virtual reality headset for 10 minutes per day, 5 days per week for 4 weeks (a total of 200 minutes). The active comparison group, Urban-VR, viewed 3-dimensional urban pictures using a virtual reality headset to match the Nature-VR intervention in intervention dose and delivery mode, but not in content. In this study, 73 participants with heart failure completed the baseline and randomized to either Nature-VR or Urban-VR. The target outcomes were attention, self-care of heart failure, and health-related quality of life (HRQoL). After baseline data collection, 4 follow-up data were collected at 4, 8, 26, and 52 weeks.</p>
Bulk and single-cell gene expression profiling of SARS-CoV-2 infected human cell lines identifies molecular targets for therapeutic intervention
<p>Single cell RNA seq datasets used for analysis in the Bulk and single-cell gene expression profiling of SARS-CoV-2 infected human cell lines identifies molecular targets for therapeutic intervention</p>
Co-design – Part 2: Workshop with professionals, early-adopters, and late/non-adopters to design interventions for a more responsible and just future with smart home technologies
<h3>Description</h3> <p>This qualitative dataset is the <strong>second part</strong> of a PhD study on co-designing smart home technologies, and represents the data collected during a series of two <strong>in-person workshops</strong>: one with professionals developing smart technology and its early-adopters, and a second one with late/non-adopters of smart technology. The first workshop had four groups of participants and the second three groups. The data is divided by each group. The data collected during the previous and subsequent parts of the referred study are also available at Zenodo.</p> <h3> </h3> <h3>Documents from workshop with professionals and early-adopters</h3> <ul> <li><strong>P2_WSP-PA-G1-TRANSCR_R00.docx</strong> (transcription of group 1 audio recordings) <ul> <li><strong>P2_WSP-PA-G1-VIS_000 </strong>to <strong>_005</strong> (participant-generated visual data)</li> </ul> </li> </ul> <ul> <li><strong>P2_WSP-PA-G2-TRANSCR_R00.docx </strong>(transcription of group 2 audio recordings) <ul> <li><strong>P2_WSP-PA-G2-VIS_000 </strong>to<strong> _008</strong> (participant-generated visual data)</li> </ul> </li> </ul> <ul> <li><strong>P2_WSP-PA-G3-TRANSCR_R00.docx </strong>(transcription of group 3 audio recordings) <ul> <li><strong>P2_WSP-PA-G3-VIS_000 </strong>to<strong> _004</strong> (participant-generated visual data)</li> </ul> </li> </ul> <ul> <li><strong>P2_WSP-PA-G4-TRANSCR_R00.docx </strong>(transcription of group 4 audio recordings) <ul> <li><strong>P2_WSP-PA-G4-VIS_000 </strong>to<strong> _002</strong> (participant-generated visual data)</li> </ul> </li> </ul> <p> </p> <h3>Documents from workshop with late/non-adopters</h3> <ul> <li><strong>P2_WSP-LN-G1-TRANSCR_R00</strong> (transcription of group 1 audio recordings) <ul> <li><strong>P2_WSP-LN-G1-VIS_000 </strong>and<strong> _001</strong> (participant-generated visual data)</li> </ul> </li> </ul> <ul> <li><strong>P2_WSP-LN-G2-TRANSCR_R00</strong> (transcription of group 2 audio recordings) <ul> <li><strong>P2_WSP-LN-G2-VIS_000 </strong>to<strong> _003</strong> (participant-generated visual data)</li> </ul> </li> </ul> <ul> <li><strong>P2_WSP-LN-G3-TRANSCR_R00</strong> (transcription of group 3 audio recordings) <ul> <li><strong>P2_WSP-LN-G3-VIS_000 </strong>to<strong> _002</strong> (participant-generated visual data)</li> </ul> </li> </ul> <p> </p> <h3>Acknowledgements</h3> <p>This study is part of the GECKO Project (<a href="https://gecko-project.eu/">https://gecko-project.eu/</a>) and has received funding from the European Commission under the Horizon2020 MSCA-ITN-2020 Innovative Training Networks programme, Grant Agreement No 955422 (<a href="https://cordis.europa.eu/project/id/955422">https://cordis.europa.eu/project/id/955422</a>).</p>
GERONTE H2020 project - GERDAT005 - Intrinsic capacity evaluation and intervention protocol
<p><strong>The present document is a dataset generated as part of Deliverable D1.1. of the GERONTE project, which has received funding from the European Union’s Horizon 2020 Programme under Grant Agreement N°945218. It aims to provide the geriatric oncology professional community with a protocol for the evaluation of intrinsic capacity and frailty, with subsequent interventions aimed at optimizing health status and support for older patients with multimorbidity and cancer.</strong></p> <p>GERONTE is a 5-year research and innovation project (April 2021 to Mars 2026) funded by the European Union within the framework of the H2020 Research and Innovation programme, in response to the health societal challenge topic SC1-BHC-24-2020 “Healthcare interventions for the management of the elderly multimorbid patient”. The overall aim of GERONTE is to improve quality of life - defined as well-being on three levels: global health status, physical functioning and social functioning- for older multimorbid patients, while reducing overall costs of care. To this end, GERONTE will co-design, test, and prepare for deployment an innovative cost-effective patient-centred holistic health management system, hereafter referred to as the GERONTE intervention. GERONTE intervention will rely on an ICT based application for real-time collection and integration of standardised clinical and home patient-reported data. GERONTE intervention will be demonstrated in the context of care of multimorbid patients having cancer as a dominant morbidity, and be adaptable to any other combination of morbidities.</p> <p>An important component of Geronte is to take account of intrinsic capacity. Most older patients who are diagnosed with cancer also suffer from other illnesses and impairments that could affect their prognosis, priorities and ability to tolerate and benefit from treatment. For tailored oncologic decision making, it is essential to obtain a complete overview of the patient’s health status. This dataset contains the protocol for evaluation intrinsic capacity and potential interventions for impairments or vulnerabilities that were identified in this evaluation. It is going to be used in the assessment and management of older patients with multimorbidity and cancer, within the GERONTE care pathway.</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>
Not So Weak-PICO: Leveraging weak supervision for Participants, Interventions, and Outcomes recognition for systematic review automation
<p>EBM-PICO is a widely used dataset with PICO annotations at two levels: span-level or coarse-grained and entity-level or fine-grained. Span-level annotations encompass the full information about each class. Entity-level annotations cover the more fine-grained information at the entity level, with PICO classes further divided into fine-grained subclasses. For example, the coarse-grained Participant span is further divided into participant age, gender, condition and sample size in the randomised controlled trial. This dataset comes pre-divided into a training set (n=4,933) annotated through crowd-sourcing and an expert annotated gold test set (n=191) for evaluation.</p> <p>The <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6174533/bin/NIHMS988059-supplement-Appendix.pdf">EBM-PICO annotation guidelines</a> caution about variable annotation quality. <a href="http://ceur-ws.org/Vol-2429/paper1.pdf">Abaho et al.</a> developed a framework to post-hoc correct EBM-PICO outcomes annotation inconsistencies. <a href="https://arxiv.org/pdf/1904.09557.pdf">Lee et al.</a> studied annotation span disagreements suggesting variability across the annotators. Low annotation quality in the training dataset is excusable, but the errors in the test set can lead to faulty evaluation of the downstream ML methods. We evaluate 1% of the EBM-PICO training set tokens to gauge the possible reasons for the fine-grained labelling errors and use this exercise to conduct an error-focused PICO re-annotation for the EBM-PICO gold test set. The file 'test_ebm_correctedlabels.tsv' has error corrected EBM-PICO gold test set.</p> <p> </p> <p>The upload also contains two zip files containing labelling sources mentioned in the Distant-PICO paper. </p> <ol> <li>ds_cto_dict.zip: contains the four distant supervision dictionaries (P: participant.txt, I = intervention.txt, intervetion_syn.txt, O: outcome.txt) generated from clinicaltrials.gov using the methodology described in Distant-CTO. </li> <li>handcrafted_dictionaries.zip: contains three files <ul> <li>gender_sexuality.txt: contains a list of possible genders and sexual orientations found across the web. The list is not comprehensive.</li> <li>endpoints_dict.txt: contains outcome names and the names of questionnaires used to measure outcomes assembled from PROM questionnaires and PROMs.</li> <li>comparator_dict: contains a list of idiosyncratic comparator terms like a sham, saline, placebo, etc., compiled from the literature search. The list is not comprehensive.</li> </ul> </li> </ol>
Beyond the passive–active dichotomy: aligning research with the intervention continuum framework of ecological restoration
<p>The dataset and R script file are associated with the publication, "Krishnan, A. and Osuri, A.M. (2022), Beyond the passive-active dichotomy: aligning research with the intervention continuum framework of ecological restoration. Restoration Ecology:e13828. https://doi.org/10.1111/rec.13828"</p> <p>Please refer to the readme.txt file for more information on the dataset and analyses.</p>
Information Based Behavioural Intervention Study (Bologna case)
<p>iSCAPE Dataset Reference No. = DS_PD_011, DS_MA_003, DS_PD_016</p> <p>Following datasets are acquired and generated during the implementation of behavioural intervention study in Bologna:</p> <ol> <li>Participant's detailed activity-travel diary </li> <li>Pollutant concentrations of a study area</li> <li>Introductory and Followup questionnaire responses </li> </ol>
A route to school informational intervention for air pollution exposure reduction
<p>iSCAPE Dataset Reference No. = DS_PD_020</p> <p>Following datasets are gathered during the implementation of route to school intervention study in Antwerp (Belgium)</p> <ol> <li>Introductory Questionnaire Responses</li> <li>Feedback Questionnaire Responses</li> </ol>
Information Based Behavioural Intervention Study (Hasselt case)
<p>iSCAPE Dataset Ref. No. = DS_PD_010, DS_MA_002, DS_PD_015</p> <p>Following datasets are acquired and generated during the implementation of behavioural intervention study in Hasselt:</p> <ol> <li>Participant's detailed activity-travel diary </li> <li>Pollutant concentration maps</li> <li>Introductory and Followup questionnaire responses </li> </ol> <p> </p>
Data and code for the analysis in "Assessing the impact of non-pharmaceutical interventions on SARS-CoV-2 transmission in Switzerland"
<p>Data and code used for the analysis in <em>Assessing the impact of non-pharmaceutical interventions on SARS-CoV-2 transmission in Switzerland</em> (Lemaitre et al., Swiss Medial Weekly 2020).</p>
Supplementary material for the publication: J.D. Nixon, K. Bhargava and E. Gaura, Energy Performance Gap in Community-Based Solar Energy Interventions: Lessons from two Rwandan Refugee Camps, 2020
<p>The dataset deposited here was prepared under the EPSRC-funded <a href="http://heed-refugee.coventry.ac.uk/">Humanitarian Engineering and Energy for Displacement</a> research project (EP/P029531/1). The project aimed to understand energy needs of displaced communities, create an evidence base on the usage of different energy interventions and provide recommendations for improved design of future energy interventions to better meet the needs of people. </p> <p>As part of the project, we deployed a Standalone Solar System for a Community Hall in Nyabiheke camp, Rwanda, and a PV-battery Microgrid in Kigeme camp, Rwanda. The microgrid supplies power to a playground and two nursery buildings. It powers a total of 20 CPE (each with 3 LEDs) and 10 sockets. The standalone system at Hall powers 7 CPE (with 3 LEDs each) and 4 sockets. The aim of the study was to (a) understand the energy consumption behaviour, light usage and other enabled uses within the set location in each camp (b) create an evidence base on the value of energy and its benefits in displaced contexts (c) identify best practice in the construction, control and operation of the respective systems as a shared energy resource.</p> <p>The system data used for the performance analysis for this study (July 2019 and March 2020) is deposited here along with the metadata. The results from analysis are presented in a paper titled '<strong>Energy Performance Gap in Community-Based Solar Energy Interventions: Lessons from two Rwandan Refugee Camps</strong>' (currently under submission). The scripts for analysis can be found at our Github account <a href="https://github.com/cogent-computing">Cogent Labs</a> under HEED-Microgrid and HEED-Hall repositories.</p>
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>
Co-design – Part 3: Focus group with professionals, early-adopters, and late/non-adopters to better detail each intervention designed, who would be involved, and how it would happen
<h3>Description</h3> <p>This qualitative dataset is the <strong>third part</strong> of a PhD study on co-designing smart home technologies, and represents the data collected during a <strong>online focus group</strong> with professionals developing smart technology, its early-adopters, and late/non-adopters. The meeting was conducted at Microsoft Teams with the support of an visual board on Miro. The data collected during the previous and subsequent parts of the referred study are also available at Zenodo.</p> <h3> </h3> <h3>Documents from focus group</h3> <ul> <li><strong>P3_FG-PAN-TRANSCR_R00.docx </strong>(transcription of focus group audio recordings)</li> </ul> <p> </p> <h3>Acknowledgements</h3> <p>This study is part of the GECKO Project (<a href="https://gecko-project.eu/">https://gecko-project.eu/</a>) and has received funding from the European Commission under the Horizon2020 MSCA-ITN-2020 Innovative Training Networks programme, Grant Agreement No 955422 (<a href="https://cordis.europa.eu/project/id/955422">https://cordis.europa.eu/project/id/955422</a>).</p>
Data associated with the article 'Intervention factors associated with efficacy, when targeting oral language comprehension of children with or at risk for (Developmental) Language Disorder: A meta-analysis'
<p>The efficacy of oral language comprehension interventions varies, but the reasons for this variation have received little attention. A meta-analysis was conducted to examine intervention factors associated with the efficacy (as expressed with effect sizes) of oral language comprehension interventions in children under the age of 18 with or at risk for (Developmental) Language Disorder, (D)LD.</p> <p>The meta-analysis article together with this additional material comprise the content needed for a thorough understanding and replication of the results.</p> <p>This dataset is based on two systematic scoping reviews on oral language comprehension interventions (Tarvainen et al., 2020, 2021). Further information from the sourced articles was extracted for this study titled ‘Intervention factors associated with efficacy, when targeting oral language comprehension of children with or at risk for (Developmental) Language Disorder: A meta-analysis’. </p> <p>In the future, we hope that this data is used with a growing body of oral language comprehension interventions to conduct further and more detailed examinations of intervention factors associated with efficacy.</p> <p>References:</p> <p>Tarvainen, S., Launonen, K., & Stolt, S. (2021). Oral language comprehension interventions in school-age children and adolescents with developmental language disorder: A systematic scoping review. <em>Autism & Developmental Language Impairments</em>, <em>6</em>, 1–24. https://doi.org/10.1177/23969415211010423</p> <p>Tarvainen, S., Stolt, S., & Launonen, K. (2020). Oral language comprehension interventions in 1–8-year-old children with language disorders or difficulties: A systematic scoping review. <em>Autism & Developmental Language Impairments</em>, <em>5</em>, 1–24. https://doi.org/10.1177/2396941520946</p> <p> </p>
Figure 9 of paper: It's not only the sea: a history of human intervention in the beach-dune ecosystem of Costa da Caparica (Portugal)
<p>This if the figure 9 of paper with DOI 10.5894/rgci-n432.</p> <p>Dunes of Trafaria and Costa da Caparica. This figure was adapted by Dissanayake M. Ruwan Sampath.</p> <p>The original source can be found at Archive from Instituto para a Conservação da Natureza e Florestas (Portugal).</p> <p>Representation of the works made by the Forestry Services between 1884 and 1910. Reference to an area flooded by the ocean in 1905 [sementeira de 1905 inundada pelo mar] and areas where new sowings had to be done [resementeiras]. Notice the drainage systems [valla] and the fences [sébe] near the coastline to protect the plants.</p>
Figure 11 of paper: It's not only the sea: a history of human intervention in the beach-dune ecosystem of Costa da Caparica (Portugal)
<p>This is the figure 11 of the article with DOI 10.5894/rgci-n432.</p> <p>Forests of Trafaria and Costa da Caparica in the 1930s-1940s. This figure was adapted by Dissanayake M. Ruwan Sampath.</p> <p>Original source can be found at the Archive of Instituto para a Conservação da Natureza e Florestas.</p> <p>In green, the existing forests. In pink, the Forestry Services areas given to other institutions or services for public uses. In yellow, the dunes to be afforested.</p> <p> </p>
Inventory of Policy Interventions related to Energy and Transport Behaviours
<p>User behaviour is a complex issue, as it is influenced by a multitude of factors from economic status, age, education, political environment etc. The WHY project aims to identify the possible user reactions and their effect on the energy consumption due to external stimuli. In context of the WHY project these external stimuli are called “interventions”. In this chapter different approaches for policy driven interventions are discussed and presented. </p>
Insider trading regulation and shorting constraints. Evaluating the joint effects of two market interventions.
<p>This dataset contains the raw experimental data and the analysis script for the paper Merl, R., Stöckl, T., Palan, S., 2022. "Insider trading regulation and shorting constraints. Evaluating the joint effects of two market interventions", Journal of Banking and Finance 106490, https://doi.org/10.1016/j.jbankfin.2022.106490.</p> <p>Instructions:</p> <p>1. Unpack all files into one folder.<br> 2. Open R version 4.1.2 and set the working directory to the folder with all the files.<br> 3. Run Script.R.</p> <p>In case the SPTools package is not available from GitHub anymore, you can also find it included in this dataset so you can install it from here.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.