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84 results for “personality traits”
Data from: Personality trait structures across three species of Macaca, using survey ratings of responses to conspecifics and humans
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Sex differences in fearful personality traits are explained by facultative calibration to physical strength
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Impacts of life satisfaction, job satisfaction and Big Five personality traits on satisfaction with the indoor environment in Singapore
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Measuring personality traits in Eurasian red squirrels: a critical comparison of different methods
<p>Data and R code used for the analysis of Eurasian red squirrels (<em>Sciurus vulgaris</em>) personality traits derived from open field test (activity, shyness, exploration) and capture-mark-recapture data (trappability/trap-diversity).</p>
Consistent variations in personality traits and their potential for genetic improvement in the biocontrol agent Trichogramma evanescens - Data table and code for data analysis
<p>We provide data and code needed to re-do the analyses and figures presented in our preprint <em>Consistent variations in personality traits and their potential for genetic improvement in the biocontrol agent </em>Trichogramma evanescens (DOI : 10.1101/2020.08.21.257881 ):</p> <p>- data table : <em>data_repetition01.xls</em>, with informations about each column in the file <em>data_repetition_info.pdf</em></p> <p>- data table : <em>data_individual01.xls</em>, with informations about each column in the file <em>data_indivdual_info.pdf</em></p> <p><em>- </em>The R code used to do the analyses : <em>Rscript-Consistent variations in personality traits and their potential for genetic improvement in the biocontrol agent Trichogramma evanescens.R</em></p> <p><br> </p> <p> </p> <p> </p> <p> </p>
Data from: Data for: Variation in animal personality traits across a metal pollution gradient in a free-living songbird
Anthropogenic contaminants could alter traits central to animal behavioral types, or personalities, including aggressiveness, boldness and activity level. Lead and other toxic metals are persistent inorganic pollutants that affect organisms worldwide. Metal exposure can alter behavior by affecting neurology, endocrinology, and health. However, the direction and magnitude of the behavioral effects of metal exposure remain equivocal. Moreover, the degree to which metal exposure simultaneously affects suites of correlated behavioral traits (behavioral syndromes) that are controlled by common mechanisms remains unclear, with most studies focusing on single behaviors. Using a model species for personality variation, the great tit (Parus major), we explored differences in multiple behavioral traits across a pollution gradient where levels of metals, especially lead and cadmium, are elevated close to a smelter. We employed the novel environment exploration test, a proxy for variation in personality type, and also measured territorial aggressiveness and nest defense behavior. At polluted sites birds of both sexes displayed slower exploration behavior, which could reflect impaired neurological or physiological function. Territorial aggression and nest defense behavior were individually consistent, but did not vary with proximity to the smelter, suggesting that metal exposure does not concurrently affect exploration and aggression. Rather, exploration behavior appears more sensitive to metal pollution. Effects of metal pollution on exploration behavior, a key animal personality trait, could have critical effects on fitness.
Finding Relationships between Socio-technical Aspects and Personality Traits by Mining Developer E-mails - Dataset
<p>Building on the work done by Gonzalez-Barahona et al. [1] we used the data of the Eclipse project available at [2], with information from the following repositories: source code management (git), issue tracking (Bugzilla), mailing lists (archived<br /> in mbox format), and code review (Gerrit). From the dumps that are provided by Metrics Grimoire, the databases were restored and the datasets used in the experimental stage were built.<br /> Since we are interested in identifying relationships between social and technical aspects in the evolution of FLOSS projects, the source code repository and the mailing lists are the most relevant data for the purpose of this work. Specifically, we used the data of the Eclipse Platform subproject, which in turn is divided into the following components: Ant - Eclipse/Ant integration, Workspace (Team, CVS,<br /> Compare, Resources) - Platform resource management, Debug - Generic execution debug framework, Releng - Release Engineering, Search - Integrated search facility, SWT - Standard Widget Toolkit, Text - Text editor framework and UI - Platform user interface, runtime and help components.</p>
Data from: Plasticity and the structural characteristics of personality traits in captive-reared Japanese quail during ontogeny
<p>This dataset contains the measurements of different personality traits in a study on Japanese quail.</p>
Micro-personality traits and their implications for behavioural and movement ecology research
<ol> <li>Many animal personality traits have implicit movement‐based definitions, and can directly or indirectly influence ecological and evolutionary processes. It has therefore been proposed that animal movement studies could benefit from acknowledging and studying consistent inter-individual differences (personality), and, conversely, animal personality studies could adopt a more quantitative representation of movement patterns.</li> <li>Using high-resolution tracking data of three-spined stickleback fish (<i>Gasterosteus</i> <i>aculeatus</i>)<i>, </i>we examined the repeatability of four movement parameters commonly used in the analysis of discrete time-series movement data (time stationary, step-length, turning angle, burst frequency), and four behavioural parameters commonly used in animal personality studies (distance travelled, space use, time in free water, time near objects).</li> <li>Fish showed repeatable inter-individual differences in both movement and behavioural parameters when observed in a simple environment with two, three, or five shelters present. Moreover, individuals that spend less time stationary, take more direct paths and less commonly burst travel (movement parameters), were found to travel farther, explored more of the tank, and spent more time in open water (behavioural parameters).</li> <li>Our case-study indicates that the two approaches – quantifying movement and behavioural parameters – are broadly equivalent, and we suggest that movement parameters can be viewed as "micro-personality" traits that give rise to broad-scale consistent inter-individual differences in behaviour. This finding has implications for both personality and movement ecology research areas. For example, the study of movement parameters may <span>provide a robust way to analyse</span><span> individual </span><span>personalities in species that are difficult or impossible to study using standardised behavioural assays.</span> </li> </ol>
Links between personality traits and problem-solving performance in zebra finches (Taeniopygia guttata)
<p><span>Consistent individual differences in behaviour across time or contexts (i.e., personality types) have been found in many species and have implications for fitness. Likewise, individual variation in cognitive abilities has been shown to impact fitness. Cognition and personality are complex, multidimensional traits. However, p</span><span>revious work has generally examined the connection between a single personality trait and a single cognitive ability, yielding equivocal results. Links between personality and cognitive ability suggest that behavioural traits coevolved and highlight their nuanced connections. Here we examined individuals' performance on multiple personality tests and repeated problem-solving tests (each measuring innovative performance). </span>We assessed behavioural traits (dominance, boldness, activity, risk-taking, aggressiveness, and obstinacy) in 41 captive zebra finches. Birds' scores for boldness and obstinacy were consistent over two years. We also examined whether personality correlated with problem-solving performance on repeated tests. Our results indicate that neophobia, dominance, and obstinacy were related to successful solving, and less dominant, more obstinate birds solved the tasks quicker on average. Our results indicate the importance of examining multiple measures over a long period. <span>Future work that identifies links between personality and innovation in non-model organisms may elucidate the coevolution of these two forms of individual differences.</span></p>
SPSS data file and output file for study "Relationship Between Big Five Personality Traits and Attitudes Towards Artificial Intelligence".
<p>The SPSS data file and output file for the study "Relationship Between Big Five Personality Traits and Attitudes Towards Artificial Intelligence".</p>
Expanded dynamic methylome and quantitative trait detection by long-read epigenome profiling of personal DNA
<p>Scripts and methylation frequencies for "Expanded dynamic methylome and quantitative trait detection by long-read epigenome profiling of personal DNA" manuscript.</p>
Persistence of Learning Style, Learning Strategy, and Personality Traits
<p>This dataset contains the result of the survey to learning styles, learning strategies, and personality traits.</p> <p>The survey was executed in winter term 2023/24 and summer term 2023 in a German university (OTH Regensburg) during the course "Software Engineering".</p> <p>Examined questionnaires are ILS (learning styles), LIST-K (learning strategies), and BFI-10 (personality traits).</p> <p> </p> <p>The same three questionnaires were asked at two different survey periods three to four months apart while each survey period lasts one to two weeks. Pretest data were examined at the start of the term, while posttest data at the end.</p> <p> </p> <p>Files:</p> <ul> <li>answer_comparison.xlsx</li> <li>persistence.xlsx</li> <li>value_comparison.xlsx</li> </ul> <table> <tbody> <tr> <td>Abbreviation LIST-K</td> <td>Full name</td> </tr> <tr> <td>CS</td> <td>Cognitive strategies</td> </tr> <tr> <td>MCS</td> <td>Metacognitive strategies</td> </tr> <tr> <td>MIR</td> <td>Strategies for managing internal resources</td> </tr> <tr> <td>MER</td> <td>Strategies for managing external resources</td> </tr> <tr> <td>CSORG</td> <td>Cognitive strategies - organizing</td> </tr> <tr> <td>CSELA</td> <td>Cognitive strategies - elaborating</td> </tr> <tr> <td>CSCCH</td> <td>Cognitive strategies - critical checking</td> </tr> <tr> <td>CSREP</td> <td>Cognitive strategies - repeating</td> </tr> <tr> <td>MCSGOP</td> <td>Metacognitive strategies - goals & plans</td> </tr> <tr> <td>MCSMON</td> <td>Metacognitive strategies - monitoring</td> </tr> <tr> <td>MCSREG</td> <td>Metacognitive strategies - regulating</td> </tr> <tr> <td>MIRATT</td> <td>Strategies for managing internal resources - attention</td> </tr> <tr> <td>MIREFF</td> <td>Strategies for managing internal resources - effort</td> </tr> <tr> <td>MIRTIM</td> <td>Strategies for managing internal resources - time</td> </tr> <tr> <td>MERLEE</td> <td>Strategies for managing external resources - learning environment</td> </tr> <tr> <td>MERLIT</td> <td>Strategies for managing external resources - literature research</td> </tr> <tr> <td>MERLWP</td> <td>Strategies for managing external resources - learning with peers</td> </tr> </tbody> </table> <p> </p> <table> <tbody> <tr> <td>Abbreviation ILS</td> <td>Full name</td> </tr> <tr> <td>VV</td> <td>Visual Verbal</td> </tr> <tr> <td>SG</td> <td>Sequential Global</td> </tr> <tr> <td>AR</td> <td>Active Reflective</td> </tr> <tr> <td>SI</td> <td>Sensing Intuitive</td> </tr> </tbody> </table> <p> </p> <table> <tbody> <tr> <td>Abbreviation BFI-10</td> <td>Full name</td> </tr> <tr> <td>A</td> <td>Agreeableness</td> </tr> <tr> <td>C</td> <td>Conscientiousness</td> </tr> <tr> <td>E</td> <td>Extraversion</td> </tr> <tr> <td>N</td> <td>Neuroticism</td> </tr> <tr> <td>O</td> <td>Openness</td> </tr> </tbody> </table> <p> </p> <p> </p> <p>The presented work is supported by the ‘German Federal Ministry of Research, Technology and Space’ (BMFTR) through the granting of the funding project HASKI (FKZ: 16DHBKI035).</p>
Data from: Environmental heterogeneity and population differences in blue tits personality traits
Environmental heterogeneity can result in spatial variation in selection pressures that can produce local adaptations. The pace-of-life syndrome hypothesis predicts that habitat-specific selective pressures will favor the coevolution of personality, physiological, and life-history phenotypes. Few studies so far have compared these traits simultaneously across different ecological conditions. In this study, we compared 3 personality traits (handling aggression, exploration speed in a novel environment, and nest defense behavior) and 1 physiological trait (heart rate during manual restraint) across 3 Corsican blue tit (Cyanistes caeruleus) populations. These populations are located in contrasting habitats (evergreen vs. deciduous) and are situated in 2 different valleys 25 km apart. Birds from these populations are known to differ in life-history characteristics, with birds from the evergreen habitat displaying a slow pace-of-life, and birds from the deciduous habitat a comparatively faster pace-of-life. We expected personality to differ across populations, in line with the differences in pace-of-life documented for life-history traits. As expected, we found behavioral differences among populations. Despite considerable temporal variation, birds exhibited lower handling aggression in the evergreen populations. Exploration speed and male heart rate also differed across populations, although our results for exploration speed were more consistent with a phenotypic difference between the 2 valleys than between habitats. There were no clear differences in nest defense intensity among populations. Our study emphasizes the role of environmental heterogeneity in shaping population divergence in personality traits at a small spatial scale.
Perceived fairness and perceived transparency of AI systems according to system's characteristics, personality traits and demographic characteristics
<p>We collected data of 3197 users' fairness perception regarding various configurations of a AI-based system in the recruitment domain, as well as, the demographic and personally characteristics of the participants.</p> <p>The dataset includes the following columns:</p> <p><strong>:System characteristics</strong></p> <p> :Certification</p> <p>Uncertificated system (U)</p> <p>Certificated system (C)</p> <p>:Input data</p> <p>High quality input data (H)</p> <p>Low quality input data (L)</p> <p>:Output</p> <p>Positive outcome (P)</p> <p>Borderline outcome (B)</p> <p>Negative outcome (N)</p> <p>:Explanation style</p> <p>Control- no explanation (CON)</p> <p>Case-based (CAS)</p> <p>Certification-based (CER)</p> <p>Demographic-based (DEM)</p> <p>Input influence-based (INP)</p> <p>Sensitivity-based (SEN)</p> <p><strong>:Demographic characteristics</strong></p> <p>:Gender</p> <p>Female</p> <p>Male</p> <p>:Age</p> <p>18-34</p> <p>35-50</p> <p>50+</p> <p>:Residence</p> <p>Unites states of America</p> <p>India</p> <p>Other</p> <p>:Education level</p> <p>High school degree or less</p> <p>Bachelor's degree</p> <p>Master's or doctoral degree</p> <p>:Employment status</p> <p>Not employed</p> <p>Employed</p> <p>:Income level</p> <p>Above average</p> <p>Average</p> <p>Below average</p> <p><strong>:Personality characteristics</strong></p> <p>(TIPI questionnaire)</p> <p>Extraverted, enthusiastic</p> <p>1-7 (1= disagree strongly up to 7= agree strongly)</p> <p>Critical, quarrelsome</p> <p>1-7 (1= disagree strongly up to 7= agree strongly)</p> <p>Dependable, self-disciplined</p> <p>1-7 (1= disagree strongly up to 7= agree strongly)</p> <p>Anxious, easily upset</p> <p>1-7 (1= disagree strongly up to 7= agree strongly)</p> <p>Open to new experiences, complex</p> <p>1-7 (1= disagree strongly up to 7= agree strongly)</p> <p>Reserved, quiet</p> <p>1-7 (1= disagree strongly up to 7= agree strongly)</p> <p>Sympathetic, warm</p> <p>1-7 (1= disagree strongly up to 7= agree strongly)</p> <p>Disorganized, careless</p> <p>1-7 (1= disagree strongly up to 7= agree strongly)</p> <p>Calm, emotionally stable</p> <p>1-7 (1= disagree strongly up to 7= agree strongly)</p> <p>Conventional, uncreative</p> <p>1-7 (1= disagree strongly up to 7= agree strongly)</p> <p><strong>:Participants responses</strong></p> <p>:Fairness evaluation</p> <p>The participants were requested to report their level of perceived fairness (their view about the fairness of the system - at what level they consider the system as a fair system) on a 6-point Likert scale, from "Extremely fair" (represented as 3) to "Extremely unfair" (represented as -3). The option of "neither fair or unfair" (represented as 0) was excluded from the scale.</p> <p>:Transparency evaluation</p> <p>the participants were requested to report their level of perceived transparency (their understanding why the system produced the specific output - at what level they understand why this output was given) on a 6-point Likert scale, from " Thoroughly understand" (represented as 3) to " Thoroughly don't understand" (represented as -3). The option of "neither understand or don't understand" (represented as 0) was excluded from the scale.</p> <p>:Output Expectation</p> <p>The participants were requested to report their expectation for the specific output based on the input they received according to the system's scale, 5-point Likert scale from "Strongly recommended" (represented as 2) to "Strongly not recommended" (represented as -2).</p> <p> </p>
Choking Susceptibility and the Big Five Personality Traits
<p>Dataset for a study examining the differences between the Big Five personality traits on choking susceptible and choking non-susceptible individuals from a Canadian University using a cross-sectional design. </p>
Quality of Life and Personality Traits in Patients With Type 1 Diabetes
ClinicalTrials.gov study NCT03481218. IPD Sharing: Not stated. Countries: 1. Publications: 16.
Difficult Colonoscopy and Personality Traits
ClinicalTrials.gov study NCT06531226. IPD Sharing: NO. Countries: 1. Publications: 6.
Mindfulness-Based Stress Reduction (MBSR) for People High on the Personality Trait Sensory Processing Sensitivity: A Mixed Methods Study
ClinicalTrials.gov study NCT06390020. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Relationship Between Personality Traits and Perioperative Anesthetic Drug Consumption
ClinicalTrials.gov study NCT06093789. IPD Sharing: Not stated. Countries: 1. Publications: 3.
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.