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engine on the 2019-present COVID-19 / Coronavirus pandemic. The aim was to make it easier to find potentially relevant datasets for this specific topic</div></li><li><div><a href="/collections/ec0567cc-53db-451f-a02a-6e109e2cf8b6">COVID-19: Epidemiology & infectious modelling datasets</a></div><div>We selected Epidemiology & infectious modelling datasets that are indexed by the Mendeley Data Search engine on the 2019-present COVID-19 / Coronavirus pandemic. The aim was to make it easier to find potentially relevant datasets for this specific topic.</div></li><li><div><a href="/collections/f082ece9-8143-4e19-8611-31f9973a0a2d">COVID-19: Vaccine, prevention, diagnosis & treatment datasets</a></div><div>We selected Vaccine, prevention, diagnosis & treatment datasets indexed by the Mendeley Data Search engine on the 2019-present COVID-19 / Coronavirus pandemic. The aim was to make it easier to find potentially relevant datasets for this specific topic</div></li></ul></div><div class="background"></div></div></div><h2 class="mdui-h4 institution-subheader">Find research data from Elsevier BV</h2><div class="mdui-datasearch"><div class="search-bar" role="search"><div class="top-bar"><input placeholder="Search Elsevier Data Repository" type="search" aria-label="Search Elsevier Data Repository" class="mdui-text-input large datasearch-input" value=""/><button aria-label="Search" type="button" class="mdui-button primary search-button"><svg class="mdui-icon" viewBox="0 0 16 16" height="20" width="20" aria-hidden="true"><path d="M3.06 10.098A4.943 4.943 0 0 1 1.602 6.58C1.602 5.25 2.12 4 3.06 3.06a4.943 4.943 0 0 1 3.52-1.458c1.329 0 2.578.518 3.518 1.458s1.458 2.19 1.458 3.52c0 1.329-.517 2.579-1.458 3.519a4.943 4.943 0 0 1-3.519 1.458c-1.33 0-2.579-.518-3.519-1.459zM16 14.867l-4.24-4.24a6.525 6.525 0 0 0 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(1)</span></label></li></ul></div><div class="facet"><button aria-expanded="true" type="button" class="mdui-button action facet-toggle expanded">Funders<svg class="mdui-icon" viewBox="0 0 14.5 14.5" height="12" width="12" preserveAspectRatio="none" aria-hidden="true"><path transform="translate(6.250000, 7.250000) rotate(90.000000) translate(-12.000000, -12.000000) " d="M5 9.09006928 6.10264465 8 11.999844 13.8229407 17.8973553 8 19 9.09006928 11.999844 16z"></path></svg></button><div class="funding-facet"><div><div><div class="mdui-dropdown" role="combobox" aria-expanded="false" aria-haspopup="listbox"><input aria-autocomplete="list" autoComplete="off" id="downshift-74-input" class="dropdown-control" aria-label="Search for funders" value=""/></div></div></div></div></div></div><div class="datasearch-results"><div class="results-title"><span class="mdui-h5">142 results</span><label class="mdui-label sort-dropdown">Sort by<div><div><div class="mdui-dropdown" role="combobox" aria-expanded="false" aria-haspopup="listbox"><button type="button" role="button" aria-label="open menu" aria-haspopup="true" data-toggle="true" class="dropdown-control"><span>Most relevant</span><svg class="mdui-icon" viewBox="0 0 14.5 14.5" height="14" width="14" preserveAspectRatio="none" aria-hidden="true"><path transform="translate(6.250000, 7.250000) rotate(90.000000) translate(-12.000000, -12.000000) " d="M5 9.09006928 6.10264465 8 11.999844 13.8229407 17.8973553 8 19 9.09006928 11.999844 16z"></path></svg></button></div></div></div></label></div><ul class="results-list"><li class="datasearch-item"><a class="item-title mdui-h6" href="https://data.mendeley.com/datasets/6mfzj4j6vk">Deenz Psychopathy Spectrum Scale (DPSS-24) sample of 21 participants</a><div class="metadata">Dar Deen, Deen MOHD</div><div class="metadata">Published 1 November 2024 | Mendeley Data</div><div class="description">In the initial testing phase, I administered the DPSS-24 to a sample of 21 participants to evaluate its reliability, validity, and practical application. This small yet insightful sample provided preliminary data, highlighting response patterns that helped refine the scale’s structure and effectiveness. I analyzed each participant’s responses, comparing them with established psychopathy measures to ensure that the DPSS-24 could offer a nuanced, comprehensive assessment. My goal with the DPSS-24 is to provide a reliable tool for both research and clinical settings, contributing to a deeper understanding of psychopathy and supporting psychological evaluation and intervention strategies. The dataset contains sample responses for the Deenz Psychopathy Spectrum Scale (DPSS-24), collected from 21 participants. Each participant responded to 24 items on a Likert scale ranging from 1 to 5, where 1 indicates low agreement and 5 indicates high agreement with psychopathy-related traits (such as impulsivity, emotional detachment, and interpersonal challenges). Each item reflects a specific aspect of psychopathy, and responses are aggregated to provide an overall psychopathy score for each participant. This dataset serves as a preliminary evaluation tool to assess the scale’s consistency, reliability, and initial descriptive patterns. Overall Psychopathy Score: For each participant, scores across the 24 items were summed, resulting in a total psychopathy score. Higher scores suggest a greater presence of psychopathy traits. Score Range: The psychopathy scores in this sample of 21 participants range from approximately 24 (minimal psychopathy traits) to 120 (maximum psychopathy traits). Mean Score: The average psychopathy score for this sample was calculated to provide a central measure. Standard Deviation: This was used to observe the variability in psychopathy scores among participants. Item-level Analysis: Responses for each of the 24 items were analyzed individually to detect any trends in specific traits that appeared more consistently across participants. Initial Reliability Check: Cronbach’s alpha was calculated to assess internal consistency across items, which is a preliminary indicator of the scale’s reliability. A Cronbach’s alpha value close to or above 0.7 is generally considered acceptable in psychometric research. Interpretation: The sample data suggests that the DPSS-24 can differentiate between varying levels of psychopathy traits.</div><div class="data-types"><ul><li><span class="mdui-pill mdui-text-small">Dataset</span></li></ul></div><div class="datasearch-citations">Export:<a class="mdui-button action" href="/api/citations/text/x-bibliography/10.17632/6mfzj4j6vk.1?style=apa" download="Deenz Psychopathy Spectrum Scale (DPSS-24) sample of 21 participants.txt">APA</a><a class="mdui-button action" href="/api/citations/application/x-bibtex/10.17632/6mfzj4j6vk.1" download="Deenz Psychopathy Spectrum Scale (DPSS-24) sample of 21 participants.bib">BibTeX</a><a class="mdui-button action" href="/api/citations/application/vnd.datacite.datacite+xml/10.17632/6mfzj4j6vk.1" download="Deenz Psychopathy Spectrum Scale (DPSS-24) sample of 21 participants.xml">DataCite</a><a class="mdui-button action" href="/api/citations/application/x-research-info-systems/10.17632/6mfzj4j6vk.1" download="Deenz Psychopathy Spectrum Scale (DPSS-24) sample of 21 participants.ris">RIS</a></div></li><li class="datasearch-item"><a class="item-title mdui-h6" href="https://elsevier.digitalcommonsdata.com/datasets/jmy6pt5zhj">Researcher mobility - customizable research tool</a><div class="metadata">Ding, Alvin , Dobre, Silvia</div><div class="metadata">Published 25 July 2024 | Elsevier BV</div><div class="description">A set of four nested PySpark notebooks on Elsevier’s cloud-based computational platform powered by Databricks that constitute a customisable research tool for studying researcher mobility.</div><div class="data-types"><ul><li><span class="mdui-pill mdui-text-small">Dataset</span></li></ul></div><div class="datasearch-citations">Export:<a class="mdui-button action" href="/api/citations/text/x-bibliography/10.17632/jmy6pt5zhj.1?style=apa" download="Researcher mobility - customizable research tool.txt">APA</a><a class="mdui-button action" href="/api/citations/application/x-bibtex/10.17632/jmy6pt5zhj.1" download="Researcher mobility - customizable research tool.bib">BibTeX</a><a class="mdui-button action" href="/api/citations/application/vnd.datacite.datacite+xml/10.17632/jmy6pt5zhj.1" download="Researcher mobility - customizable research tool.xml">DataCite</a><a class="mdui-button action" href="/api/citations/application/x-research-info-systems/10.17632/jmy6pt5zhj.1" download="Researcher mobility - customizable research tool.ris">RIS</a></div></li><li class="datasearch-item"><a class="item-title mdui-h6" href="https://elsevier.digitalcommonsdata.com/datasets/bb5jb7t2zv">Gender Equality in Research & Innovation – 2024 Review</a><div class="metadata">van der Linden, Nicolien, Roberge, Guillaume, Malkov, Dmitry</div><div class="metadata">Published 20 June 2024 | Elsevier BV</div><div class="description">Elsevier's 2024 Gender Report tracks and analyzes data across 18 countries and 2 regions (EU 27 and the world) examining women’s performance in research and innovation across disciplines and career stages. Our Report provides new insights into interdisciplinarity, multidisciplinarity, grant recipients, patent applications, open access, UN Sustainable Development Goals (SDG) research areas, as well as alternative metrics including policy and media citations. More information at https://www.elsevier.com/en-au/insights/gender-and-diversity-in-research</div><div class="data-types"><ul><li><span class="mdui-pill mdui-text-small">Dataset</span></li></ul></div><div class="datasearch-citations">Export:<a class="mdui-button action" href="/api/citations/text/x-bibliography/10.17632/bb5jb7t2zv.2?style=apa" download="Gender Equality in Research & Innovation – 2024 Review.txt">APA</a><a class="mdui-button action" href="/api/citations/application/x-bibtex/10.17632/bb5jb7t2zv.2" download="Gender Equality in Research & Innovation – 2024 Review.bib">BibTeX</a><a class="mdui-button action" href="/api/citations/application/vnd.datacite.datacite+xml/10.17632/bb5jb7t2zv.2" download="Gender Equality in Research & Innovation – 2024 Review.xml">DataCite</a><a class="mdui-button action" href="/api/citations/application/x-research-info-systems/10.17632/bb5jb7t2zv.2" download="Gender Equality in Research & Innovation – 2024 Review.ris">RIS</a></div></li><li class="datasearch-item"><a class="item-title mdui-h6" href="https://data.mendeley.com/datasets/s2xymfm9w8">STUDENT WELL-BEING DURING THE COVID-19 PANDEMIC IN GREECE.RESULTS FROM THE C19 ISWS SURVEY.</a><div class="metadata">Stathopoulou, Theoni, Mouriki, Aliki, Papaliou, Olga</div><div class="metadata">Published 17 June 2024 | Mendeley Data</div><div class="description">The current report presents the first results of the International survey “Covid-19 Student Well-Being Study” carried out by EKKE (National Centre for Social Research) between 13 May-12 June 2020 with the participation of students enrolled in Greece’s higher education institutions. The survey was designed by the University of Antwerp in collaboration with the University of Ghent in Belgium. A total of 27 European and North American countries, as well South-Africa participated in the study.</div><div class="data-types"><ul><li><span class="mdui-pill mdui-text-small">Dataset</span></li></ul></div><div class="datasearch-citations">Export:<a class="mdui-button action" href="/api/citations/text/x-bibliography/10.17632/s2xymfm9w8.1?style=apa" download="STUDENT WELL-BEING DURING THE COVID-19 PANDEMIC IN GREECE.RESULTS FROM THE C19 ISWS SURVEY..txt">APA</a><a class="mdui-button action" href="/api/citations/application/x-bibtex/10.17632/s2xymfm9w8.1" download="STUDENT WELL-BEING DURING THE COVID-19 PANDEMIC IN GREECE.RESULTS FROM THE C19 ISWS SURVEY..bib">BibTeX</a><a class="mdui-button action" href="/api/citations/application/vnd.datacite.datacite+xml/10.17632/s2xymfm9w8.1" download="STUDENT WELL-BEING DURING THE COVID-19 PANDEMIC IN GREECE.RESULTS FROM THE C19 ISWS SURVEY..xml">DataCite</a><a class="mdui-button action" href="/api/citations/application/x-research-info-systems/10.17632/s2xymfm9w8.1" download="STUDENT WELL-BEING DURING THE COVID-19 PANDEMIC IN GREECE.RESULTS FROM THE C19 ISWS SURVEY..ris">RIS</a></div></li><li class="datasearch-item"><a class="item-title mdui-h6" href="https://data.mendeley.com/datasets/t7zjt8zn5j">HW_NoVPN_NMLSC_02Sep2020(DT1.1)</a><div class="metadata">Natra, NatSciLive</div><div class="metadata">Published 17 June 2024 | Mendeley Data</div><div class="description">HW_NoVPN_NMLSC_02Sep2020(DT1.1)</div><div class="data-types"><ul><li><span class="mdui-pill mdui-text-small">Dataset</span></li></ul></div><div class="datasearch-citations">Export:<a class="mdui-button action" href="/api/citations/text/x-bibliography/10.17632/t7zjt8zn5j.1?style=apa" download="HW_NoVPN_NMLSC_02Sep2020(DT1.1).txt">APA</a><a class="mdui-button action" href="/api/citations/application/x-bibtex/10.17632/t7zjt8zn5j.1" download="HW_NoVPN_NMLSC_02Sep2020(DT1.1).bib">BibTeX</a><a class="mdui-button action" href="/api/citations/application/vnd.datacite.datacite+xml/10.17632/t7zjt8zn5j.1" download="HW_NoVPN_NMLSC_02Sep2020(DT1.1).xml">DataCite</a><a class="mdui-button action" href="/api/citations/application/x-research-info-systems/10.17632/t7zjt8zn5j.1" download="HW_NoVPN_NMLSC_02Sep2020(DT1.1).ris">RIS</a></div></li><li class="datasearch-item"><a class="item-title mdui-h6" href="https://data.mendeley.com/datasets/55rgck5ckj">Validación - Instrumento de competencias</a><div class="metadata">García Arango, David Alberto</div><div class="metadata">Published 17 June 2024 | Mendeley Data</div><div class="description">Archivos en Excel de aplicación a expertos para validación de instrumento de evaluación. Uno de los instrumentos es aplicado para validez aparente (VALIDACIÓN-UNIMINUTO SECCIONAL ANTIOQUIA-CHOCÓ) y otro instrumento es de validez de constructo (VALIDACIÓN-UNIMINUTO SECCIONAL ANTIOQUIA-CHOCÓ - Segunda Parte).</div><div class="data-types"><ul><li><span class="mdui-pill mdui-text-small">Dataset</span></li></ul></div><div class="datasearch-citations">Export:<a class="mdui-button action" href="/api/citations/text/x-bibliography/10.17632/55rgck5ckj.1?style=apa" download="Validación - Instrumento de competencias.txt">APA</a><a class="mdui-button action" href="/api/citations/application/x-bibtex/10.17632/55rgck5ckj.1" download="Validación - Instrumento de competencias.bib">BibTeX</a><a class="mdui-button action" href="/api/citations/application/vnd.datacite.datacite+xml/10.17632/55rgck5ckj.1" download="Validación - Instrumento de competencias.xml">DataCite</a><a class="mdui-button action" href="/api/citations/application/x-research-info-systems/10.17632/55rgck5ckj.1" download="Validación - Instrumento de competencias.ris">RIS</a></div></li><li class="datasearch-item"><a class="item-title mdui-h6" href="https://elsevier.digitalcommonsdata.com/datasets/s3prjwms9r">Webinar on the report "Progress Toward Gender Equality in Research & Innovation - 2024 Review"</a><div class="metadata">van der Linden, Nicolien, Browning, Elisabeth, Roberge, Guillaume</div><div class="metadata">Published 17 June 2024 | Elsevier BV</div><div class="description">The global research community is making progress, albeit slowly, towards the full and equal participation of women. This webinar recording presents highlights from a major new data-driven analysis of gender diversity in research. Building on prior work by Elsevier, this analysis draws on Scopus data stretching back more than two decades to assess the representation of women in research and changes over time, in a global context and for 18 countries. Beyond examining men’s and women’s research participation and research footprint, new insights will be presented on gender participation across career stages, in areas such as interdisciplinarity and multidisciplinarity, open access publication, SDGs, mentorship contribution, and alternative metrics, to paint a fuller picture of the state of gender equity in the global research ecosystem and inform evidence-based policy and interventions. You will learn about: The benefits of adopting a longer time frame for academic evaluation and assessments; The impact of hiring and retaining senior women researchers; The importance of including societal impact metrics in evaluations or career assessments, and more. The webinar can be visioned at : https://researcheracademy.elsevier.com/communicating-research/inclusion-diversity-researchers/progress-toward-gender-equality-research</div><div class="data-types"><ul><li><span class="mdui-pill mdui-text-small">Dataset</span></li></ul></div><div class="datasearch-citations">Export:<a class="mdui-button action" href="/api/citations/text/x-bibliography/10.17632/s3prjwms9r.1?style=apa" download="Webinar on the report "Progress Toward Gender Equality in Research & Innovation - 2024 Review".txt">APA</a><a class="mdui-button action" href="/api/citations/application/x-bibtex/10.17632/s3prjwms9r.1" download="Webinar on the report "Progress Toward Gender Equality in Research & Innovation - 2024 Review".bib">BibTeX</a><a class="mdui-button action" href="/api/citations/application/vnd.datacite.datacite+xml/10.17632/s3prjwms9r.1" download="Webinar on the report "Progress Toward Gender Equality in Research & Innovation - 2024 Review".xml">DataCite</a><a class="mdui-button action" href="/api/citations/application/x-research-info-systems/10.17632/s3prjwms9r.1" download="Webinar on the report "Progress Toward Gender Equality in Research & Innovation - 2024 Review".ris">RIS</a></div></li><li class="datasearch-item"><a class="item-title mdui-h6" href="https://elsevier.digitalcommonsdata.com/datasets/kmyvjk3xmd">Evolving patterns of extreme publishing behavior across science</a><div class="metadata">Collins, Thomas, Ioannidis, John, Baas, Jeroen</div><div class="metadata">Published 3 June 2024 | Elsevier BV</div><div class="description">Author information for: Hyperprolific physics authors by year 2000-2022 inclusive. Author needs to have 73 or more publications in a year to qualify and their main field from 2000 to 2022 is Physics & Astronomy Hyperprolific non-physics authors by year 2000-2022 inclusive. Author needs to have 73 or more publications in a year to qualify and their main field from 2000 to 2022 must not be Physics & Astronomy Almost Hyperprolific physics authors by year 2000-2022 inclusive. Author needs to have between 61 and 72 publications in a year to qualify and their main field from 2000 to 2022 is Physics & Astronomy Almost Hyperprolific non-physics authors by year 2000-2022 inclusive. Author needs to have between 61 and 72 publications in a year to qualify and their main field from 2000 to 2022 must not be Physics & Astronomy Data: year - The year of publication of the articles, reviews, and conference proceedings analyzed in this study author_field - The primary field assigned to the author based upon publications and share of publications in the field field - The ScienceMetrix field classification of the journal the publication appears in Pubs_in_field_year - Total number of publications by the author in the given year in the given field Pubs_year_total - Total number of publications by the author in the given year Pubs_in_field_2000_2022 - Total number of publications by the author in the period 2000 to 2022 in the given field, Pubs_2000_2022_total - Total number of publications by the author in the period 2000 to 2022 rank - The author's rank, within their SM subfield, based on citation count rank (ns) - The author's rank, within their SM subfield, based on citation count with self citations excluded sm-subfield-1 - The author's SM subfield rank sm-subfield-1 - The author's rank, within their SM subfield, based upon their citation score rank sm-subfield-1 (ns) - The author's rank, within their SM subfield, based upon their citation score excluding self citations sm-subfield-1 count - The number of authors in the SM subfield Subfield_Percentile - 100 * rank/count Subfield_Percentile_ns - 100 * rank (ns)/count author_name - Author's name from their Scopus Author Profile hidx - The author's career H-Index affil_name - The name of the author's most recent affiliation cntry - The country of the author's most recent affiliation Total_Pubs - The number of articles, reviews, and conference proceedings from the affiliation in the period Pubs_with_more_than_100_authors - The number of articles, reviews, and conference proceedings from the affiliation in the period with more than 100 authors Pubs_with_more_than_500_authors - The number of articles, reviews, and conference proceedings from the affiliation in the period with more than 500 authors Pubs_with_more_than_1000_authors - The number of articles, reviews, and conference proceedings from the affiliation in the period with more than 1000 authors</div><button aria-expanded="false" type="button" class="mdui-button action preview-button"><svg class="mdui-icon" viewBox="0 0 14.5 14.5" height="12" width="12" preserveAspectRatio="none" aria-hidden="true"><path transform="translate(6.250000, 7.250000) rotate(90.000000) translate(-12.000000, -12.000000) " d="M5 9.09006928 6.10264465 8 11.999844 13.8229407 17.8973553 8 19 9.09006928 11.999844 16z"></path></svg>Preview</button><div class="data-types"><ul><li><span class="mdui-pill mdui-text-small">Dataset</span></li></ul></div><div class="datasearch-citations">Export:<a class="mdui-button action" href="/api/citations/text/x-bibliography/10.17632/kmyvjk3xmd.2?style=apa" download="Evolving patterns of extreme publishing behavior across science.txt">APA</a><a class="mdui-button action" href="/api/citations/application/x-bibtex/10.17632/kmyvjk3xmd.2" download="Evolving patterns of extreme publishing behavior across science.bib">BibTeX</a><a class="mdui-button action" href="/api/citations/application/vnd.datacite.datacite+xml/10.17632/kmyvjk3xmd.2" download="Evolving patterns of extreme publishing behavior across science.xml">DataCite</a><a class="mdui-button action" href="/api/citations/application/x-research-info-systems/10.17632/kmyvjk3xmd.2" download="Evolving patterns of extreme publishing behavior across science.ris">RIS</a></div></li><li class="datasearch-item"><a class="item-title mdui-h6" href="https://elsevier.digitalcommonsdata.com/datasets/hjkjp2fff4">Newton's Third Law of Motion</a><div class="metadata">Abria, Jan Lady Ann</div><div class="metadata">Published 28 May 2024 | Elsevier BV</div><div class="description">This data describes Newton's third law of motion which states that "in every action there is an opposite or equal reaction".</div><div class="data-types"><ul><li><span class="mdui-pill mdui-text-small">Dataset</span></li></ul></div><div class="datasearch-citations">Export:<a class="mdui-button action" href="/api/citations/text/x-bibliography/10.17632/hjkjp2fff4.1?style=apa" download="Newton's Third Law of Motion.txt">APA</a><a class="mdui-button action" href="/api/citations/application/x-bibtex/10.17632/hjkjp2fff4.1" download="Newton's Third Law of Motion.bib">BibTeX</a><a class="mdui-button action" href="/api/citations/application/vnd.datacite.datacite+xml/10.17632/hjkjp2fff4.1" download="Newton's Third Law of Motion.xml">DataCite</a><a class="mdui-button action" href="/api/citations/application/x-research-info-systems/10.17632/hjkjp2fff4.1" download="Newton's Third Law of Motion.ris">RIS</a></div></li><li class="datasearch-item"><a class="item-title mdui-h6" href="https://elsevier.digitalcommonsdata.com/datasets/xhh4thgrt4">Elsevier Author Aid Human Disease Collection, part 4 (Cancers)</a><div class="metadata">Nesterova, Anastasia, Sozin, Sergey, Klimov, Eugene, Golovatenko-Abramov, Pavel , Linsley, Peter</div><div class="metadata">Published 28 May 2024 | Elsevier BV</div><div class="description">-----> Human Disease Author Aid Collection combines information about human diseases in standardized, easy-to-navigate overview templates and tables. It includes clinical, molecular, and pharmacological data from several Elsevier's and public sources. Tables are planned to be updated quarterly. -----> Author Aid Templates can be a helpful guide for authors, researchers, clinicians, and students, especially those interested in rare diseases, because it highlights updates and findings from several sources on one page. -----> Each disease template overview includes 6 sections: Terminology; Epidemiology/Demographics; Clinical presentation/Diagnosis; Etiology/Pathology (genetics, biomarkers, pathways); Treatment/Follow-Up; Case studies. Each subset of data is linked to a list of publications with relevant citations. -----> Cancers (Human Disease Author Aid Collection, Part 4) In the current part, selected Gynecological and Brain cancers were chosen based on their prevalence, and data availability. Part 3 includes A) Templates for: Endometrial cancer Ovarian Cancer Сervical cancer Gestational trophoblastic disease Сhoriocarcinoma B) Automatically collected information about 8 Brain Cancers. ----> PLEASE download files to read them and open the links!</div><div class="data-types"><ul><li><span class="mdui-pill mdui-text-small">Dataset</span></li></ul></div><div class="datasearch-citations">Export:<a class="mdui-button action" href="/api/citations/text/x-bibliography/10.17632/xhh4thgrt4.1?style=apa" download="Elsevier Author Aid Human Disease Collection, part 4 (Cancers).txt">APA</a><a class="mdui-button action" href="/api/citations/application/x-bibtex/10.17632/xhh4thgrt4.1" download="Elsevier Author Aid Human Disease Collection, part 4 (Cancers).bib">BibTeX</a><a class="mdui-button action" href="/api/citations/application/vnd.datacite.datacite+xml/10.17632/xhh4thgrt4.1" download="Elsevier Author Aid Human Disease Collection, part 4 (Cancers).xml">DataCite</a><a class="mdui-button action" href="/api/citations/application/x-research-info-systems/10.17632/xhh4thgrt4.1" download="Elsevier Author Aid Human Disease Collection, part 4 (Cancers).ris">RIS</a></div></li></ul></div></div><div class="datasearch-pagination"><span class="current" aria-label="Current page: 0">1</span><button type="button" class="mdui-button action">2</button><button type="button" class="mdui-button action">3</button><button type="button" class="mdui-button action">4</button><button type="button" class="mdui-button action">5</button><button type="button" class="mdui-button action">6</button><button type="button" class="mdui-button action">7</button><button type="button" class="mdui-button action">8</button><button type="button" class="mdui-button action">9</button><button type="button" class="mdui-button action next">Next<svg class="mdui-icon" viewBox="0 0 14.5 14.5" height="16" width="16" preserveAspectRatio="none" aria-hidden="true"><path transform="translate(6.250000, 7.250000) 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This small yet insightful sample provided preliminary data, highlighting response patterns that helped refine the scale’s structure and effectiveness. I analyzed each participant’s responses, comparing them with established psychopathy measures to ensure that the DPSS-24 could offer a nuanced, comprehensive assessment. My goal with the DPSS-24 is to provide a reliable tool for both research and clinical settings, contributing to a deeper understanding of psychopathy and supporting psychological evaluation and intervention strategies. The dataset contains sample responses for the Deenz Psychopathy Spectrum Scale (DPSS-24), collected from 21 participants. Each participant responded to 24 items on a Likert scale ranging from 1 to 5, where 1 indicates low agreement and 5 indicates high agreement with psychopathy-related traits (such as impulsivity, emotional detachment, and interpersonal challenges). Each item reflects a specific aspect of psychopathy, and responses are aggregated to provide an overall psychopathy score for each participant. This dataset serves as a preliminary evaluation tool to assess the scale’s consistency, reliability, and initial descriptive patterns. Overall Psychopathy Score: For each participant, scores across the 24 items were summed, resulting in a total psychopathy score. Higher scores suggest a greater presence of psychopathy traits. Score Range: The psychopathy scores in this sample of 21 participants range from approximately 24 (minimal psychopathy traits) to 120 (maximum psychopathy traits). Mean Score: The average psychopathy score for this sample was calculated to provide a central measure. Standard Deviation: This was used to observe the variability in psychopathy scores among participants. Item-level Analysis: Responses for each of the 24 items were analyzed individually to detect any trends in specific traits that appeared more consistently across participants. Initial Reliability Check: Cronbach’s alpha was calculated to assess internal consistency across items, which is a preliminary indicator of the scale’s reliability. A Cronbach’s alpha value close to or above 0.7 is generally considered acceptable in psychometric research. Interpretation: The sample data suggests that the DPSS-24 can differentiate between varying levels of psychopathy traits."}],"dates":[{"dateStr":"2024-11-01T00:00:00.000Z","typeName":"Created"},{"dateStr":"2024-11-01T07:42:10.07Z","typeName":"Issued"}],"rights":[{"title":"Creative Commons Attribution 4.0 International","uri":"http://creativecommons.org/licenses/by/4.0","identifier":{"id":"01d9c749-3c4d-4431-9df3-620b2dcfe144","idType":"PID"}}],"subjects":[{"title":"Psychometric Assessment","uri":"data.elsevier.com/vocabulary/OmniScience/Concept-253477780"},{"title":"Psychology","uri":"data.elsevier.com/vocabulary/OmniScience/Concept-170589342"}],"source":{"id":"MENDELEY_DATA","label":"Mendeley Data","providerName":"Digital Commons Data"},"institutions":[{"name":"Elsevier India","identifiers":[{"id":"0c55f2fe-9083-5d3c-8676-8f297b5a2d81","idType":"MENDELEY_PROFILE"}]}],"authors":[{"name":"Dar Deen, Deen MOHD","role":"Creator","givenName":"Deen MOHD","familyName":"Dar Deen","identifiers":[{"id":"71250b57-618a-4a4e-96cf-7435db18608b","idType":"MENDELEY_PROFILE"}]}],"id":"107118054106052106122102109054:MENDELEY_DATA","externalId":"6mfzj4j6vk"},{"repoType":"NON_ARTICLE_BASED_REPOSITORY","version":"1","url":"https://elsevier.digitalcommonsdata.com/datasets/jmy6pt5zhj","importedDate":"2024-07-27T01:08:11Z","updatedDate":"2024-11-20T10:43:29.380Z","externalUpdatedDate":"2024-07-25","publicationYear":2024,"dataTypes":["DATASET"],"keywords":["Bibliometrics"],"assetTypes":[],"externalIdentifiers":[{"id":"10.17632/jmy6pt5zhj.1","idType":"DOI"},{"id":"jmy6pt5zhj","idType":"PID"}],"alternateIdentifiers":[{"id":"jmy6pt5zhj","idType":"PID"},{"id":"10.17632/jmy6pt5zhj.1","idType":"DOI"}],"titles":[{"text":"Researcher mobility - 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