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Research data keyboard_double_arrow_right Collection 2021SAGE Journals SSHRCSSHRCAuthors: Harasymchuk, Cheryl; Walker, Deanna L.; Muise, Amy; Impett, Emily A.;Harasymchuk, Cheryl; Walker, Deanna L.; Muise, Amy; Impett, Emily A.;Spending time with a romantic partner by going on dates is important for promoting closeness in established relationships; however, not all date nights are created equally, and some people might be more adept at planning dates that promote closeness. Drawing from the self-expansion model and relationship goals literature, we predicted that people higher (vs. lower) in approach relationship goals would be more likely to plan dates that are more exciting and, in turn, experience more self-expansion from the date and increased closeness with the partner. In Study 1, people in intimate relationships planned a date to initiate with their partners and forecasted the expected level of self-expansion and closeness from engaging in the date. In Study 2, a similar design was employed, but we also followed up with participants 1 week later to ask about the experience of engaging in their planned dates (e.g., self-expansion, closeness from the date). Taken together, the results suggest that people with higher (vs. lower) approach relationship goals derive more closeness from their dates, in part, because of their greater aptitude for planning dates that are more exciting and promote self-expansion.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2023figshare CIHR, SSHRCCIHR ,SSHRCKelly, Christine; Dansereau, Lisette; Sebring, Jennifer; Aubrecht, Katie; FitzGerald, Maggie; Lee, Yeonjung; Williams, Allison; Hamilton-Hinch, Barbara;Abstract Many countries adopted comprehensive national initiatives to promote equity in higher education with the goal of transforming the culture of research. Major health research funders are supporting this work through calls for projects that focus on equity, resulting in a proliferation of theoretical frameworks including “intersectionality,” “health equity,” and variations of equity, diversity and inclusion, or EDI. This commentary is geared at individual principal investigators and health research teams who are developing research proposals and want to consider equity issues in their research, perhaps for the first time. We present histories and definitions of three commonly used frameworks: intersectionality, health equity, and EDI. In the context of health research, intersectionality is a methodology (a combination of epistemology and techniques) that can identify the relationships among individual identities and systems of oppression; however, it should also be used internally by research teams to reflect on the production of knowledge. Health equity is a societal goal that operationalizes the social determinants of health to document and address health disparities at the population level. EDI initiatives measure and track progress within organizations or teams and are best suited to inform the infrastructure and human resourcing “behind the scenes” of a project. We encourage researchers to consider these definitions and strive to tangibly move health research towards equity both in the topics we study and in the ways we do research.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2008 EnglishICPSR - Interuniversity Consortium for Political and Social Research WT, NIH | Cascades of Network Struc..., NIH | Economic Evaluation of Ad... +207 projectsWT ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| Economic Evaluation of Adolescent Alcohol Use and the Impact of Social Networks ,EC| ENGAGE ,NIH| Consortium for Neuropsychiatric Phenomics-Coordinating Center (1 of 8) ,NIH| Administrative and Research Support Core ,NIH| PATHOLOGY MONITORING--F344 RAT COLONY ,NIH| GENETICS OF ADOLESCENT ANTISOCIAL DRUG DEPENDENCE ,NIH| NYS FAMILY STUDY: PROBLEM ALCOHOL USE &PROBLEM BEHAVIOR ,NIH| Neuropharmacology of Response Inhibition in Comorbid ADHD and Nicotine Dependence ,NIH| Genome-Wide Associations Environmental Interactions in the Lung Health Study ,NIH| BIOBEHAVIORAL FACTORS IN CORONARY HEART DISEASE ,EC| DEPRIVEDHOODS ,NIH| Genome Wide Association Coordinating Center ,NIH| Health Disparities Among a Vulnerable Population: A Longitudinal Analysis ,EC| SOCIOGENOME ,NIH| ECONOMICS OF AGING TRAINING PROGRAM -- EXTENSION ,NIH| Center for Family and Demographic Research ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Computational Methods to Detect Epistasis ,NIH| OPTIMIZING BEHAVIORAL INTERVENTIONS FOR DRUG ABUSE PREVENTION &TREATMENT ,NIH| The Collaborative Genetic Study of Nicotine Dependence ,NIH| Alcohol Contextual Influences: Effects on Health Disparities and Mortality ,NIH| The University of Iowa Prevention Research Center ,NIH| Adolescent Alcohol Use: Disentangling Friend Selection &Influence ,NSF| Science Achievement and Health Behavior: High School Curriculum, Social Context, and Opportunity to Learn ,NIH| Dietary Etiologies of Heart Disease ,NIH| Birth Outcomes Among Adolescents ,NIH| Socioeconomic Disparities in Young Adult Health ,NIH| Genetic Risk to Stroke in Smokers and Nonsmokers in Two Ethnic Groups ,AKA| Impact of childhood growth patterns and latent cardiovascular risk factors on the microcirculation in adult life: Cardiovascular risk in Young Finns Study ,NIH| GWA for Gene-Environment Interaction Effects Influencing CHD ,NIH| Training in Developmental Science to Improve Child Health and Well-Being ,NIH| Statistical Methods for Network Epidemiology ,NIH| Genetics of Alcohol Dependence in African-Americans ,NIH| The Genetic Epidemiology of Nicotine Dependence ,NIH| Carolina Population Center ,NIH| Study of Addiction: Genetics and Environment ,NIH| Linkage Disequilibrium Studies of Alcohol Dependence ,NIH| Molecular Epidemiology of Alcoholism 2- Big Sibships ,NIH| Mentoring Clinical Investigators in Adolescent-onset Substance Use Disorders Research ,NIH| Social Demographic Moderation of Genome Wide Associations for Body Mass Index ,NIH| FLUORIDE AND OTHER FACTORS IN CHILDHOOD BONE DEVELOPMENT ,NIH| Genetic Epidemiology of Lung Cancer ,NIH| Role of Romantic Relationships in the Sexual Behavior of Obese and Non-Obese Girl ,NIH| A Nurse-Community Health Worker-Family Partnership Model to Increase COVID-19 Testing in Urban Underserved and Vulnerable Communities ,AKA| MSDs@LIFECOURSE CONSORTIU Subproject: Shared Risk Factors Study Group Turku University Central Hospital / Consortium: MSDs@LIFE ,ARC| Quantitative and Molecular Genetic Analysis of Cognition ,NIH| Institute for Clinical and Translational Research (UL1) ,NIH| High Density Association Analysis of Lung Cancer ,NIH| Propensity Scores and Preventive Drug Use in the Elderly ,NIH| Genetic Risk, Pathways to Adulthood, and Health Inequalities ,NIH| Washington University Institute of Clinical and Translational Sciences (UL1) ,WT| Familial and other risk factors for adolescent substance use and abuse. ,NIH| From GWAS loci to blood pressure genes, variants & mechanisms ,NIH| Genome-Wide Association for Loci Influencing CHD and Other Heart, Lung and Blood ,NIH| COSTS AND BENEFITS OF ALCOHOL SERVICES &INTERVENTIONS ,NSF| Social Inequality and Status Attainment ,NIH| Containing Bioterroist and Emerging Infectious Diseases ,NIH| UNC Interdisciplinary Obesity Training (IDOT)(RMI) ,EC| DYNANETS ,NIH| BEHAVIORAL PHARMACOGENETICS OF DRUG AND ALCOHOL ABUSE ,NIH| Variants in CHRNA5/CHRNA3/CHRNB4 and nicotine dependence ,NIH| Statistical Methods for Gene Environment Interactions In Lung Cancer ,NIH| Economic Evaluation Methods: Development and Application ,NIH| Model-Based Clustering Methods of Medical Image ,NIH| Nicotinic receptor genes &substance abuse: Functional studies of associated SNPs ,NSF| CAREER: Model Fluid-Solid Interactions, Networks REUs, and BioCalculus ,NIH| Genes, early adversity, and sensitive periods in social-emotional development ,NIH| Health Communication and Health Literacy Core ,NIH| HUMAN GENETIC VARIATION IN SMOKING AND ADDICTION RISK ,NIH| Data Core ,NIH| Genetics of Adolescent Antisocial Drug Dependence ,NIH| Cancer Center Support Grant ,NIH| NATURAL HISTORY OF ALCOHOL USE &ABUSE--GENETIC MODELS ,EC| NBHCHOICE ,NIH| The Role of Peer Networks in Youth Drug Use ,NIH| Inflammation Genes and Lung Cancer Risk ,NIH| Fine Mapping Susceptibility Loci for Nicotine Dependence ,NIH| Longitudinal Study of Trauma, HIV Risk, and Criminal Justice Involvement ,NSF| Health Lifestyles and the Reproduction of Inequality ,NIH| GENETICS OF COCAINE DEPENDENCE ,EC| TODO ,NIH| SOCIAL DEMOGRAPHY ,NIH| UIC Program for Interdisciplinary Careers in Womens Health Research ,NIH| LONGITUDINAL STUDY OF SUBSTANCE USE, INCARCERATION, AND STI IN THE US ,NIH| GENETICS OF VULNERABILITY TO NICOTINE ADDICTION ,NIH| Community Assist of Southern Arizona ,NIH| Human Genetics of Addiction: A Study of Common and Specific Factors ,NIH| The effects of heavy alcohol use on weight gain in college freshmen: Examining an overlooked calorie source ,NSF| National Science Foundation Alan T. Waterman Award ,NIH| The Social Marginalization of Adolescents in High School ,NIH| Refining Phenotypic Measures of Nicotine Withdrawal ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Individual differences and health outcomes: A secondary data analysis in cognitiv ,NIH| Understanding memory consolidation by studying pharmacologically enhanced naps ,NIH| A Center for GEI Association Studies ,NIH| Longtudinal Relations Between Internalizing Disorders and Substance Use Problems ,NIH| JH/CIDR Genotyping for Genome-Wide Association Studies ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| MOTS: Modeling Obesity Through Simulation ,NIH| Comprehensive Mapping of a Blood Pressure QTL on Chromosome 17 ,NIH| Deciphering genes and pathways in nicotine dependence ,NIH| MECHANISMS AND PREVENTION OF ENVIRONMENTAL DISEASE ,NHMRC| Experience-dependent cellular plasticity and cognitive deficits in mouse models of schizophrenia ,NIH| FINANCIAL STATUS--RETIREMENT SAVING PROGRAMS ,NIH| Genetics of Early Onset-Stroke ,NIH| Human Development: Interdisciplinary Research Training ,SSHRC ,NIH| DIET, HORMONES AND RISK OF COLORECTAL CANCERS ,NIH| Population Research Institute ,NIH| GENETIC EPIDEMIOLOGY OF LUNG CANCER ,NIH| NICHD Population Center ,NIH| Population Research Training ,NIH| Data Mgmt &Analysis Core - 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the 27-year follow-up. ,NIH| Obesity and Metabolic Risk Disparities: Underlying Food Environment Factors ,NIH| VARIATION IN THE EFFECTS OF ALCOHOL ON LIVER FUNCTION ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN CANCER ,NIH| The University of Colorado Population Center ,NIH| Genes and Environment Initiatives in Type 2 Diabetes ,NIH| Pharmacogenetics of Nicotine Addiction Treatment ,NIH| Interracial Friendship and Romance Among Adolescents ,NIH| Phenotypic refinement of externalizing pathways to alcohol-related behaviors ,ARC| Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis ,NIH| PERSISTENCE &CHANGE IN DRINKING HABITS: TWIN STUDY ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| Exome Variants Underlying Weight Gain from Adolescence to Adulthood ,NIH| Adolescent Health and Academic Achievement ,NIH| YOUNG ADULT SUBSTANCE USE--PREDICTORS AND CONSEQUENCES ,NIH| CORE--ADIPOSE TISSUE BIOLOGY AND BASIC MECHANISMS ,NIH| MDMA and Other Hallucinogen Use: Onset and Abuse/Dependence ,NIH| Molecular Genetics and Behavior: Alcohol and Tobacco Use ,NIH| Adenocarinoma of the Lung in Women ,NIH| Do active communities support activity or support active people? ,NSF| Neighborhoods and Schools, Education, and Heritability ,NIH| Sexual Orientation and Obesity: Test of a Gendered Biopsychosocial Model ,NSF| Machine learning techniques to model the impact of relational communication on distributed team effectiveness ,NIH| DIETARY ETIOLOGIES OF HEART DISEASE AND CANCER ,NSF| The Genetic Basis of Social Networks and Civic Engagement ,NIH| Social and Demographic Context and Heritability ,NIH| High Risk Drug Use &HIV-Learning from the NYC Epidemic ,AKA| Sustainable Innovative Materials in High Tech Applications. An Interdisciplinary Approach to Design,Engineering Technology and Chemistry of Environmentally Sound Products and Production. ,AKA| Roles of inflammation, oxidation, sex hormones and genetic variation in vascular aging and the development of atherosclerosis over the life-course. ,NIH| The Pathobiology of Nephrolithiasis ,NIH| GENETIC INTERACTIONS CONTRIBUTING TO ALCOHOL AND NICOTINE DEPENDENCE ,NIH| Modeling HIV and STD in Drug User and Social Networks ,NIH| Innovations in Pediatric Pain ResearchAuthors: Harris, Kathleen Mullan; Udry, J. Richard;Harris, Kathleen Mullan; Udry, J. Richard;doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v2 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v7 , 10.3886/icpsr21600.v13
doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v2 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v7 , 10.3886/icpsr21600.v13
A Data Guide for this study is available as a web page and for download. The National Longitudinal Study of Adolescent to Adult Health (Add Health), 1994-2008 [Public Use] is a longitudinal study of a nationally representative sample of U.S. adolescents in grades 7 through 12 during the 1994-1995 school year. The Add Health cohort was followed into young adulthood with four in-home interviews, the most recent conducted in 2008 when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents' social, economic, psychological, and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships. Add Health Wave I data collection took place between September 1994 and December 1995, and included both an in-school questionnaire and in-home interview. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12, and gathered information on social and demographic characteristics of adolescent respondents, education and occupation of parents, household structure, expectations for the future, self-esteem, health status, risk behaviors, friendships, and school-year extracurricular activities. All students listed on a sample school's roster were eligible for selection into the core in-home interview sample. In-home interviews included topics such as health status, health-facility utilization, nutrition, peer networks, decision-making processes, family composition and dynamics, educational aspirations and expectations, employment experience, romantic and sexual partnerships, substance use, and criminal activities. A parent, preferably the resident mother, of each adolescent respondent interviewed in Wave I was also asked to complete an interviewer-assisted questionnaire covering topics such as inheritable health conditions, marriages and marriage-like relationships, neighborhood characteristics, involvement in volunteer, civic, and school activities, health-affecting behaviors, education and employment, household income and economic assistance, parent-adolescent communication and interaction, parent's familiarity with the adolescent's friends and friends' parents. Add Health data collection recommenced for Wave II from April to August 1996, and included almost 15,000 follow-up in-home interviews with adolescents from Wave I. Interview questions were generally similar to Wave I, but also included questions about sun exposure and more detailed nutrition questions. Respondents were asked to report their height and weight during the course of the interview, and were also weighed and measured by the interviewer. From August 2001 to April 2002, Wave III data were collected through in-home interviews with 15,170 Wave I respondents (now 18 to 26 years old), as well as interviews with their partners. Respondents were administered survey questions designed to obtain information about family, relationships, sexual experiences, childbearing, and educational histories, labor force involvement, civic participation, religion and spirituality, mental health, health insurance, illness, delinquency and violence, gambling, substance abuse, and involvement with the criminal justice system. High School Transcript Release Forms were also collected at Wave III, and these data comprise the Education Data component of the Add Health study. Wave IV in-home interviews were conducted in 2008 and 2009 when the original Wave I respondents were 24 to 32 years old. Longitudinal survey data were collected on the social, economic, psychological, and health circumstances of respondents, as well as longitudinal geographic data. Survey questions were expanded on educational transitions, economic status and financial resources and strains, sleep patterns and sleep quality, eating habits and nutrition, illnesses and medications, physical activities, emotional content and quality of current or most recent romantic/cohabiting/marriage relationships, and maltreatment during childhood by caregivers. Dates and circumstances of key life events occurring in young adulthood were also recorded, including a complete marriage and cohabitation history, full pregnancy and fertility histories from both men and women, an educational history of dates of degrees and school attendance, contact with the criminal justice system, military service, and various employment events, including the date of first and current jobs, with respective information on occupation, industry, wages, hours, and benefits. Finally, physical measurements and biospecimens were also collected at Wave IV, and included anthropometric measures of weight, height and waist circumference, cardiovascular measures such as systolic blood pressure, diastolic blood pressure, and pulse, metabolic measures from dried blood spots assayed for lipids, glucose, and glycosylated hemoglobin (HbA1c), measures of inflammation and immune function, including High sensitivity C-reactive protein (hsCRP) and Epstein-Barr virus (EBV). Datasets: DS0: Study-Level Files DS1: Wave I: In-Home Questionnaire, Public Use Sample DS2: Wave I: Public Use Contextual Database DS3: Wave I: Network Variables DS4: Wave I: Public Use Grand Sample Weights DS5: Wave II: In-Home Questionnaire, Public Use Sample DS6: Wave II: Public Use Contextual Database DS7: Wave II: Public Use Grand Sample Weights DS8: Wave III: In-Home Questionnaire, Public Use Sample DS9: Wave III: In-Home Questionnaire, Public Use Sample (Section 17: Relationships) DS10: Wave III: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancies) DS11: Wave III: In-Home Questionnaire, Public Use Sample (Section 19: Relationships in Detail) DS12: Wave III: In-Home Questionnaire, Public Use Sample (Section 22: Completed Pregnancies) DS13: Wave III: In-Home Questionnaire, Public Use Sample (Section 23: Current Pregnancies) DS14: Wave III: In-Home Questionnaire, Public Use Sample (Section 24: Live Births) DS15: Wave III: In-Home Questionnaire, Public Use Sample (Section 25: Children and Parenting) DS16: Wave III: Public Use Education Data DS17: Wave III: Public Use Graduation Data DS18: Wave III: Public Use Education Data Weights DS19: Wave III: Add Health School Weights DS20: Wave III: Peabody Picture Vocabulary Test (PVT), Public Use DS21: Wave III: Public In-Home Weights DS22: Wave IV: In-Home Questionnaire, Public Use Sample DS23: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16B: Relationships) DS24: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16C: Relationships) DS25: Wave IV: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancy Table) DS26: Wave IV: In-Home Questionnaire, Public Use Sample (Section 19: Live Births) DS27: Wave IV: In-Home Questionnaire, Public Use Sample (Section 20A: Children and Parenting) DS28: Wave IV: Biomarkers, Measures of Inflammation and Immune Function DS29: Wave IV: Biomarkers, Measures of Glucose Homeostasis DS30: Wave IV: Biomarkers, Lipids DS31: Wave IV: Public Use Weights Wave I: The Stage 1 in-school sample was a stratified, random sample of all high schools in the United States. A school was eligible for the sample if it included an 11th grade and had a minimum enrollment of 30 students. A feeder school -- a school that sent graduates to the high school and that included a 7th grade -- was also recruited from the community. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12. The Stage 2 in-home sample of 27,000 adolescents consisted of a core sample from each community, plus selected special over samples. Eligibility for over samples was determined by an adolescent's responses on the in-school questionnaire. Adolescents could qualify for more than one sample.; Wave II: The Wave II in-home interview surveyed almost 15,000 of the same students one year after Wave I.; Wave III: The in-home Wave III sample consists of over 15,000 Wave I respondents who could be located and re-interviewed six years later.; Wave IV: All original Wave I in-home respondents were eligible for in-home interviews at Wave IV. At Wave IV, the Add Health sample was dispersed across the nation with respondents living in all 50 states. Administrators were able to locate 92.5% of the Wave IV sample and interviewed 80.3% of eligible sample members. ; For additional information on sampling, including detailed information on special oversamples, please see the Add Health Study Design page. Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health. Waves I and II focused on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants aged into adulthood, the scientific goals of the study expanded and evolved. Wave III explored adolescent experiences and behaviors related to decisions, behavior, and health outcomes in the transition to adulthood. Wave IV expanded to examine developmental and health trajectories across the life course of adolescence into young adulthood, using an integrative study design which combined social, behavioral, and biomedical measures data collection. Response Rates: Response rates for each wave were as follows: Wave I: 79 percent; Wave II: 88.6 percent; Wave III: 77.4 percent; Wave IV: 80.3 percent; Adolescents in grades 7 through 12 during the 1994-1995 school year. Respondents were geographically located in the United States. audio computer-assisted self interview (ACASI) computer-assisted personal interview (CAPI) computer-assisted self interview (CASI) paper and pencil interview (PAPI) face-to-face interview
Inter-university Con... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu65 citations 65 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!more_vert Inter-university Con... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2022SAGE Journals SSHRCSSHRCAuthors: Dall’Olio, Filippo; Vakratsas, Demetrios;Dall’Olio, Filippo; Vakratsas, Demetrios;This study provides a comprehensive assessment of the impact of advertising creative strategy (ACS) on advertising elasticity, founded on an integrative framework that distinguishes between the function (content) and form (execution) of an advertising creative. The authors evaluate function using a three-dimensional representation of content (experience, affect, cognition), whereas the representation of form accounts for both executional elements and the use of creative templates. The distinction between function and form allows for the investigation of potential synergies between content and execution, previously unaccounted for in the literature. The ACS framework also facilitates the calculation of composite metrics that capture holistic aspects of the creative strategy, such as focus (i.e., the extent of the emphasis on a specific content dimension) and variation (i.e., changes in content and execution over time). The empirical application focuses on a dynamic linear model analysis of 2,251 television advertising creatives from 91 brands in 16 consumer packaged goods categories. The findings show that for function, experiential content has the greatest effect on elasticity, followed by cognitive and affective content. Function and form produce synergies that advertisers can leverage to increase returns. Finally, focus, variation, and the use of templates increase advertising elasticity.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2021SAGE Journals SSHRCSSHRCSaunders, Jessica F.; Zak, Michelle; Matejko, Emily; Kassan, Anusha; Mukred, Rabab; Priolo, Alissa;Many modern emerging adults undertake the task of identity development while navigating life on a post-secondary campus, where they assimilate to new social and learning environments. Emerging adult newcomers (i.e. immigrants) must navigate additional developmental challenges as they reconcile their cultural, ethnic, and personal identity development simultaneously while facing systemic barriers to post-secondary integration. We employed an arts-based engagement ethnography to investigate the post-secondary integration experiences of 10 emerging adults from a person-first perspective. Through cultural probes, individual semi-structured interviews, and focus groups, we identified four key structures to participants’ integration experience: fitting in (through assimilation and accommodation), biculturalism, managing familial expectations, and being a newcomer in the classroom. This research clarifies the key experiences shaping young newcomer identity development and highlights the profound ways in which young newcomers negotiate and reconcile their intersecting identities while integrating into new education contexts following migration.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Taylor & Francis NSERC, SSHRCNSERC ,SSHRCSchmidtke, Daniel; Gagné, Christina L.; Kuperman, Victor; Spalding, Thomas L.; Tucker, Benjamin V.;Previous research has shown that compound word recognition involves selecting a relational meaning (e.g. “box for letters” for letterbox) out of a set of competing relational meanings for the same compound. We conducted five experiments to investigate the role of competition between relational meanings across visual and auditory compound word processing. In Experiment 1 conceptual relations judgments were collected for 604 English compound words. From this database we computed an information-theoretic measure of competition between conceptual relations – entropy of conceptual relations. Experiments 2 and 3 report that greater entropy (i.e. increased competition) among a set of conceptual relations leads to longer latencies for compounds in auditory lexical decision. Experiments 4 and 5 demonstrate the same result in two visual lexical decision studies. These findings provide evidence that relational meanings are constructed and evaluated during compound recognition, regardless of whether compounds are recognised via auditory or visual input.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.5868177.v1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2017Figshare SSHRCSSHRCMcIntyre, Laureen; Laurie-Ann Hellsten; Bidonde, Julia; Boden, Catherine; Doi, Carolyn;Abstract Background The majority of a child’s language development occurs in the first 5 years of life when brain development is most rapid. There are significant long-term benefits to supporting all children’s language and literacy development such as maximizing their developmental potential (i.e., cognitive, linguistic, social-emotional), when children are experiencing a critical period of development (i.e., early childhood to 9 years of age). A variety of people play a significant role in supporting children’s language development, including parents, guardians, family members, educators, and/or speech-language pathologists. Speech-language pathologists and educators are the professionals who predominantly support children’s language development in order for them to become effective communicators and lay the foundation for later developing literacy skills (i.e., reading and writing skills). Therefore, these professionals need formal and informal assessments that provide them information on a child’s understanding and/or use of the increasingly complex aspects of language in order to identify and support the receptive and expressive language learning needs of diverse children during their early learning experiences (i.e., aged 1.5 to 9 years). However, evidence on what methods and tools are being used is lacking. Methods The authors will carry out a scoping review of the literature to identify studies and map the receptive and expressive English language assessment methods and tools that have been published and used since 1980. Arksey and O’Malley’s (2005) six-stage approach to conducting a scoping review was drawn upon to design the protocol for this investigation: (1) identifying the research question; (2) identifying relevant studies; (3) study selection; (4) charting the data; (5) collating, summarizing, and reporting the results; and (6) consultation. Discussion This information will help these professionals identify and select appropriate assessment methods or tools that can be used to support development and/or identify areas of delay or difficulty and plan, implement, and monitor the progress of interventions supporting the development of receptive and expressive language skills in individuals with diverse language needs (e.g., typically developing children, children with language delays and disorders, children learning English as a second or additional language, Indigenous children who may be speaking dialects of English). Researchers plan to evaluate the effectiveness of the assessment methods or tools identified in the scoping review as an extension of this study.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022The Royal Society EC | NICH, NSERC, SSHRCEC| NICH ,NSERC ,SSHRCAuthors: Alexander, Jake M.; Atwater, Daniel Z.; Colautti, Robert I.; Hargreaves, Anna L.;Alexander, Jake M.; Atwater, Daniel Z.; Colautti, Robert I.; Hargreaves, Anna L.;This file contains code to model adaptive trade-offs across a species' range, and to produce Figs. 2 and 3.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2020SAGE Journals SSHRCSSHRCHamm, Jeremy M.; Perry, Raymond P.; Chipperfield, Judith G.; Hladkyj, Steve; Parker, Patti C.; Weiner, Bernard;Despite increased emphasis on educating students in science, technology, engineering, and mathematics (STEM) disciplines, nearly half of U.S. college students who enroll in these programs fail to graduate with STEM degrees. Using archival data from the Motivation and Academic Achievement Database, we tested whether a motivation intervention to reframe causal attributions for academic setbacks improved graduation rates for college students in STEM disciplines (N = 496). Results showed that the intervention increased the odds of 8-year graduation for students who were at risk of college dropout. Findings highlight the potential of theory-informed psychological interventions to increase persistence to graduation for at-risk students in STEM fields.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2018Figshare SSHRC, EC | INQMINDSSSHRC ,EC| INQMINDSAuthors: Völter, Christoph J.; Tinklenberg, Brandon; Call, Josep; Seed, Amanda M.;Völter, Christoph J.; Tinklenberg, Brandon; Call, Josep; Seed, Amanda M.;Cognitive abilities cannot be measured directly. What we can measure is individual variation in task performance. In this paper, we first make the case for why we should be interested in mapping individual differences in task performance on to particular cognitive abilities: we suggest that it is crucial for examining the causes and consequences of variation both within and between species. As a case study, we examine whether multiple measures of inhibitory control for non-human animals do indeed produce correlated task performance; however, no clear pattern emerges that would support the notion of a common cognitive ability underpinning individual differences in performance. We advocate a psychometric approach involving a three-step programme to make theoretical and empirical progress: first, we need tasks that reveal signature limits in performance. Second, we need to assess the reliability of individual differences in task performance. Third, multi-trait multi-method test batteries will be instrumental in validating cognitive abilities. Together, these steps will help us to establish what varies between individuals that could impact their fitness and ultimately shape the course of the evolution of animal minds. Finally, we propose executive functions, including working memory, inhibitory control and attentional shifting, as a sensible starting point for this endeavour.This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive ability’.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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Research data keyboard_double_arrow_right Collection 2021SAGE Journals SSHRCSSHRCAuthors: Harasymchuk, Cheryl; Walker, Deanna L.; Muise, Amy; Impett, Emily A.;Harasymchuk, Cheryl; Walker, Deanna L.; Muise, Amy; Impett, Emily A.;Spending time with a romantic partner by going on dates is important for promoting closeness in established relationships; however, not all date nights are created equally, and some people might be more adept at planning dates that promote closeness. Drawing from the self-expansion model and relationship goals literature, we predicted that people higher (vs. lower) in approach relationship goals would be more likely to plan dates that are more exciting and, in turn, experience more self-expansion from the date and increased closeness with the partner. In Study 1, people in intimate relationships planned a date to initiate with their partners and forecasted the expected level of self-expansion and closeness from engaging in the date. In Study 2, a similar design was employed, but we also followed up with participants 1 week later to ask about the experience of engaging in their planned dates (e.g., self-expansion, closeness from the date). Taken together, the results suggest that people with higher (vs. lower) approach relationship goals derive more closeness from their dates, in part, because of their greater aptitude for planning dates that are more exciting and promote self-expansion.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2023figshare CIHR, SSHRCCIHR ,SSHRCKelly, Christine; Dansereau, Lisette; Sebring, Jennifer; Aubrecht, Katie; FitzGerald, Maggie; Lee, Yeonjung; Williams, Allison; Hamilton-Hinch, Barbara;Abstract Many countries adopted comprehensive national initiatives to promote equity in higher education with the goal of transforming the culture of research. Major health research funders are supporting this work through calls for projects that focus on equity, resulting in a proliferation of theoretical frameworks including “intersectionality,” “health equity,” and variations of equity, diversity and inclusion, or EDI. This commentary is geared at individual principal investigators and health research teams who are developing research proposals and want to consider equity issues in their research, perhaps for the first time. We present histories and definitions of three commonly used frameworks: intersectionality, health equity, and EDI. In the context of health research, intersectionality is a methodology (a combination of epistemology and techniques) that can identify the relationships among individual identities and systems of oppression; however, it should also be used internally by research teams to reflect on the production of knowledge. Health equity is a societal goal that operationalizes the social determinants of health to document and address health disparities at the population level. EDI initiatives measure and track progress within organizations or teams and are best suited to inform the infrastructure and human resourcing “behind the scenes” of a project. We encourage researchers to consider these definitions and strive to tangibly move health research towards equity both in the topics we study and in the ways we do research.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2008 EnglishICPSR - Interuniversity Consortium for Political and Social Research WT, NIH | Cascades of Network Struc..., NIH | Economic Evaluation of Ad... +207 projectsWT ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| Economic Evaluation of Adolescent Alcohol Use and the Impact of Social Networks ,EC| ENGAGE ,NIH| Consortium for Neuropsychiatric Phenomics-Coordinating Center (1 of 8) ,NIH| Administrative and Research Support Core ,NIH| PATHOLOGY MONITORING--F344 RAT COLONY ,NIH| GENETICS OF ADOLESCENT ANTISOCIAL DRUG DEPENDENCE ,NIH| NYS FAMILY STUDY: PROBLEM ALCOHOL USE &PROBLEM BEHAVIOR ,NIH| Neuropharmacology of Response Inhibition in Comorbid ADHD and Nicotine Dependence ,NIH| Genome-Wide Associations Environmental Interactions in the Lung Health Study ,NIH| BIOBEHAVIORAL FACTORS IN CORONARY HEART DISEASE ,EC| DEPRIVEDHOODS ,NIH| Genome Wide Association Coordinating Center ,NIH| Health Disparities Among a Vulnerable Population: A Longitudinal Analysis ,EC| SOCIOGENOME ,NIH| ECONOMICS OF AGING TRAINING PROGRAM -- EXTENSION ,NIH| Center for Family and Demographic Research ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Computational Methods to Detect Epistasis ,NIH| OPTIMIZING BEHAVIORAL INTERVENTIONS FOR DRUG ABUSE PREVENTION &TREATMENT ,NIH| The Collaborative Genetic Study of Nicotine Dependence ,NIH| Alcohol Contextual Influences: Effects on Health Disparities and Mortality ,NIH| The University of Iowa Prevention Research Center ,NIH| Adolescent Alcohol Use: Disentangling Friend Selection &Influence ,NSF| Science Achievement and Health Behavior: High School Curriculum, Social Context, and Opportunity to Learn ,NIH| Dietary Etiologies of Heart Disease ,NIH| Birth Outcomes Among Adolescents ,NIH| Socioeconomic Disparities in Young Adult Health ,NIH| Genetic Risk to Stroke in Smokers and Nonsmokers in Two Ethnic Groups ,AKA| Impact of childhood growth patterns and latent cardiovascular risk factors on the microcirculation in adult life: Cardiovascular risk in Young Finns Study ,NIH| GWA for Gene-Environment Interaction Effects Influencing CHD ,NIH| Training in Developmental Science to Improve Child Health and Well-Being ,NIH| Statistical Methods for Network Epidemiology ,NIH| Genetics of Alcohol Dependence in African-Americans ,NIH| The Genetic Epidemiology of Nicotine Dependence ,NIH| Carolina Population Center ,NIH| Study of Addiction: Genetics and Environment ,NIH| Linkage Disequilibrium Studies of Alcohol Dependence ,NIH| Molecular Epidemiology of Alcoholism 2- Big Sibships ,NIH| Mentoring Clinical Investigators in Adolescent-onset Substance Use Disorders Research ,NIH| Social Demographic Moderation of Genome Wide Associations for Body Mass Index ,NIH| FLUORIDE AND OTHER FACTORS IN CHILDHOOD BONE DEVELOPMENT ,NIH| Genetic Epidemiology of Lung Cancer ,NIH| Role of Romantic Relationships in the Sexual Behavior of Obese and Non-Obese Girl ,NIH| A Nurse-Community Health Worker-Family Partnership Model to Increase COVID-19 Testing in Urban Underserved and Vulnerable Communities ,AKA| MSDs@LIFECOURSE CONSORTIU Subproject: Shared Risk Factors Study Group Turku University Central Hospital / Consortium: MSDs@LIFE ,ARC| Quantitative and Molecular Genetic Analysis of Cognition ,NIH| Institute for Clinical and Translational Research (UL1) ,NIH| High Density Association Analysis of Lung Cancer ,NIH| Propensity Scores and Preventive Drug Use in the Elderly ,NIH| Genetic Risk, Pathways to Adulthood, and Health Inequalities ,NIH| Washington University Institute of Clinical and Translational Sciences (UL1) ,WT| Familial and other risk factors for adolescent substance use and abuse. ,NIH| From GWAS loci to blood pressure genes, variants & mechanisms ,NIH| Genome-Wide Association for Loci Influencing CHD and Other Heart, Lung and Blood ,NIH| COSTS AND BENEFITS OF ALCOHOL SERVICES &INTERVENTIONS ,NSF| Social Inequality and Status Attainment ,NIH| Containing Bioterroist and Emerging Infectious Diseases ,NIH| UNC Interdisciplinary Obesity Training (IDOT)(RMI) ,EC| DYNANETS ,NIH| BEHAVIORAL PHARMACOGENETICS OF DRUG AND ALCOHOL ABUSE ,NIH| Variants in CHRNA5/CHRNA3/CHRNB4 and nicotine dependence ,NIH| Statistical Methods for Gene Environment Interactions In Lung Cancer ,NIH| Economic Evaluation Methods: Development and Application ,NIH| Model-Based Clustering Methods of Medical Image ,NIH| Nicotinic receptor genes &substance abuse: Functional studies of associated SNPs ,NSF| CAREER: Model Fluid-Solid Interactions, Networks REUs, and BioCalculus ,NIH| Genes, early adversity, and sensitive periods in social-emotional development ,NIH| Health Communication and Health Literacy Core ,NIH| HUMAN GENETIC VARIATION IN SMOKING AND ADDICTION RISK ,NIH| Data Core ,NIH| Genetics of Adolescent Antisocial Drug Dependence ,NIH| Cancer Center Support Grant ,NIH| NATURAL HISTORY OF ALCOHOL USE &ABUSE--GENETIC MODELS ,EC| NBHCHOICE ,NIH| The Role of Peer Networks in Youth Drug Use ,NIH| Inflammation Genes and Lung Cancer Risk ,NIH| Fine Mapping Susceptibility Loci for Nicotine Dependence ,NIH| Longitudinal Study of Trauma, HIV Risk, and Criminal Justice Involvement ,NSF| Health Lifestyles and the Reproduction of Inequality ,NIH| GENETICS OF COCAINE DEPENDENCE ,EC| TODO ,NIH| SOCIAL DEMOGRAPHY ,NIH| UIC Program for Interdisciplinary Careers in Womens Health Research ,NIH| LONGITUDINAL STUDY OF SUBSTANCE USE, INCARCERATION, AND STI IN THE US ,NIH| GENETICS OF VULNERABILITY TO NICOTINE ADDICTION ,NIH| Community Assist of Southern Arizona ,NIH| Human Genetics of Addiction: A Study of Common and Specific Factors ,NIH| The effects of heavy alcohol use on weight gain in college freshmen: Examining an overlooked calorie source ,NSF| National Science Foundation Alan T. Waterman Award ,NIH| The Social Marginalization of Adolescents in High School ,NIH| Refining Phenotypic Measures of Nicotine Withdrawal ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Individual differences and health outcomes: A secondary data analysis in cognitiv ,NIH| Understanding memory consolidation by studying pharmacologically enhanced naps ,NIH| A Center for GEI Association Studies ,NIH| Longtudinal Relations Between Internalizing Disorders and Substance Use Problems ,NIH| JH/CIDR Genotyping for Genome-Wide Association Studies ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| MOTS: Modeling Obesity Through Simulation ,NIH| Comprehensive Mapping of a Blood Pressure QTL on Chromosome 17 ,NIH| Deciphering genes and pathways in nicotine dependence ,NIH| MECHANISMS AND PREVENTION OF ENVIRONMENTAL DISEASE ,NHMRC| Experience-dependent cellular plasticity and cognitive deficits in mouse models of schizophrenia ,NIH| FINANCIAL STATUS--RETIREMENT SAVING PROGRAMS ,NIH| Genetics of Early Onset-Stroke ,NIH| Human Development: Interdisciplinary Research Training ,SSHRC ,NIH| DIET, HORMONES AND RISK OF COLORECTAL CANCERS ,NIH| Population Research Institute ,NIH| GENETIC EPIDEMIOLOGY OF LUNG CANCER ,NIH| NICHD Population Center ,NIH| Population Research Training ,NIH| Data Mgmt &Analysis Core - The NINDS International Stroke Genetics Consortium St ,NIH| Obesity and the Environment: The Transition to Adulthood ,EC| ADDICTION ,NIH| Age at First Sex, Genes, Religion, and Other Social and Demographic Context ,NIH| Novel Use of Gwas for Improved Understanding of Nicotine Dependence ,NIH| Racial disparities in cancer outcomes: quantifying modifiable mechanisms ,NIH| Response Inhibition and Dopamine Neurotransmission (RI) (4 of 8) ,ARC| Locating genes for elementary and complex cognitive abilities using genetic linkage and association analysis ,NIH| Synthetic Information Systems for Better Informing Public Health Policymakers ,NSF| GSE/RES Gender Differences in Science and Math: Diversity and the Role of Social Context ,NIH| University of Minnesota Clinical and Translational Science Institute (UMN CTSI) ,NIH| Molecular Epidemiology of Alcoholism 3 - EDAC Families ,NIH| Identifying essential network properties for disease spread ,NIH| Health Disparities in Obesity: Partner Violence and its Psychosocial Pathways ,NIH| Childhood Family Instability, Adult Stress Reactivity, and Consequences for Health ,NIH| Outreach Core ,NIH| Social Support as a Facilitator of Adherence to HIV Pre-Exposure Prophylaxis Among Young MSM of Color ,CIHR ,NIH| GENETICS OF NICOTINE AND OTHER ABUSED SUBSTANCES ,NIH| Substance Abuse & Treatment Gaps in Asians, Pacific Islanders & Multiple-race Ind ,NIH| Colorado Adoption/Twin Study of Lifespan behavioral development & cognitive aging (CATSLife) ,NIH| The Genetics of Vulnerability to Nicotine Addictions ,NIH| PROSTATE, LUNG, COLORECTAL &OVARIAN CANCER ,NIH| HEALTHY YOUTH DEVELOPMENT PREVENTION RESEARCH AND TRAINING CENTER ,NIH| GENETICS AND CONSEQUENCES OF NICOTINE ADDICTION ,NIH| PROSTATE, LUNG, COLORECTAL, AND OVARIAN (PLCO) CANCER ,NIH| Population Research Center ,NIH| Mid Southern Primary Care Networks Node ,NIH| University of Washington Reproductive, Perinatal and Pediatric Epidemiology ,NIH| Carolina Population Center ,NIH| Mapping Genes for comorbidity of SUDs and Depression ,NIH| Genetic &environmental pathways to drug use, abuse &dependence ,NIH| Epidemiology of Venous Thrombosis &Pulmonary Embolism ,AKA| Role of early life risk factors in associations between work, cardiovascular disease and depression: A life course approach based on two prospective cohorts. / Consortium: ELRFWCDD ,ARC| Elucidating the genetics of attention deficit hyperactivity disorder by integrating pathway and prediction analyses ,NIH| Administrative Core ,NIH| TRAINING GRANT IN CANCER EPIDEMIOLOGY ,NIH| Physical Environment Dynamics, Inequality and Obesity ,NIH| Transitions to Adulthood and Health Risk Among U.S. Young Adults ,NIH| CUPC Admin Core ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Translational studies of nicotinic receptor genes: alcohol and nicotine behaviors ,NIH| Sexual Behavior Trajectories from Adolescence to Adulthood ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| Washington University Institute of Clinical and Translational Sciences (KL2) ,NIH| PROSPECTIVE LONGITUDINAL STUDY OF ADOLESCENT HEALTH ,NIH| Identifying Mediated Pathways of Risk for Substance Use in Sexual Minority Girls ,EC| GMI ,NIH| Intergenerational Research on Obesity Prevention: From Correlates to Intervention ,NIH| Smoking/Nicotine Dependence in Attention Deficit Hyperactivity Disorder (ADHD) ,NIH| University of Colorado Population Center ,NIH| The Washington University Center for Diabetes Translation Research ,NIH| Genes, Environments & Interventions: Understanding and Addressing Alcohol Misuse ,NIH| Center on Antisocial Drug Dependence: The Genetics of HIV Risk Behaviors ,AKA| Public Health Genomics to Practice in Cardiovascular Diseases / Consortium: PUBGENSENS ,NIH| SUBSTANCE USE AND DISORDERED WEIGHT BEHAVIORS IN SEXUAL MINORITY YOUTH CONTEXTS ,NIH| BEYOND RACE--EXPLAINING INEQUALITY MANIFESTED AS OBESITY ,NIH| Research Training Program in the Behavioral and Biomedical Sciences ,NIH| Genetics of Opioid Dependence ,NIH| HIV in Young Adulthood: Pathways and Prevention ,NIH| Research and Mentoring on Integrating Psychiatric Genetics and Neuroscience ,NIH| Vitamin D metabolism related genetic variations and developmental origins of card ,NIH| Systematic Error and Confounding: Meta-Analyses of Alcohol and Disease ,AKA| The Cardiovascular Risk in Young Finns Study - the 27-year follow-up. ,NIH| Obesity and Metabolic Risk Disparities: Underlying Food Environment Factors ,NIH| VARIATION IN THE EFFECTS OF ALCOHOL ON LIVER FUNCTION ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN CANCER ,NIH| The University of Colorado Population Center ,NIH| Genes and Environment Initiatives in Type 2 Diabetes ,NIH| Pharmacogenetics of Nicotine Addiction Treatment ,NIH| Interracial Friendship and Romance Among Adolescents ,NIH| Phenotypic refinement of externalizing pathways to alcohol-related behaviors ,ARC| Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis ,NIH| PERSISTENCE &CHANGE IN DRINKING HABITS: TWIN STUDY ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| Exome Variants Underlying Weight Gain from Adolescence to Adulthood ,NIH| Adolescent Health and Academic Achievement ,NIH| YOUNG ADULT SUBSTANCE USE--PREDICTORS AND CONSEQUENCES ,NIH| CORE--ADIPOSE TISSUE BIOLOGY AND BASIC MECHANISMS ,NIH| MDMA and Other Hallucinogen Use: Onset and Abuse/Dependence ,NIH| Molecular Genetics and Behavior: Alcohol and Tobacco Use ,NIH| Adenocarinoma of the Lung in Women ,NIH| Do active communities support activity or support active people? ,NSF| Neighborhoods and Schools, Education, and Heritability ,NIH| Sexual Orientation and Obesity: Test of a Gendered Biopsychosocial Model ,NSF| Machine learning techniques to model the impact of relational communication on distributed team effectiveness ,NIH| DIETARY ETIOLOGIES OF HEART DISEASE AND CANCER ,NSF| The Genetic Basis of Social Networks and Civic Engagement ,NIH| Social and Demographic Context and Heritability ,NIH| High Risk Drug Use &HIV-Learning from the NYC Epidemic ,AKA| Sustainable Innovative Materials in High Tech Applications. An Interdisciplinary Approach to Design,Engineering Technology and Chemistry of Environmentally Sound Products and Production. ,AKA| Roles of inflammation, oxidation, sex hormones and genetic variation in vascular aging and the development of atherosclerosis over the life-course. ,NIH| The Pathobiology of Nephrolithiasis ,NIH| GENETIC INTERACTIONS CONTRIBUTING TO ALCOHOL AND NICOTINE DEPENDENCE ,NIH| Modeling HIV and STD in Drug User and Social Networks ,NIH| Innovations in Pediatric Pain ResearchAuthors: Harris, Kathleen Mullan; Udry, J. Richard;Harris, Kathleen Mullan; Udry, J. Richard;doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v2 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v7 , 10.3886/icpsr21600.v13
doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v2 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v7 , 10.3886/icpsr21600.v13
A Data Guide for this study is available as a web page and for download. The National Longitudinal Study of Adolescent to Adult Health (Add Health), 1994-2008 [Public Use] is a longitudinal study of a nationally representative sample of U.S. adolescents in grades 7 through 12 during the 1994-1995 school year. The Add Health cohort was followed into young adulthood with four in-home interviews, the most recent conducted in 2008 when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents' social, economic, psychological, and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships. Add Health Wave I data collection took place between September 1994 and December 1995, and included both an in-school questionnaire and in-home interview. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12, and gathered information on social and demographic characteristics of adolescent respondents, education and occupation of parents, household structure, expectations for the future, self-esteem, health status, risk behaviors, friendships, and school-year extracurricular activities. All students listed on a sample school's roster were eligible for selection into the core in-home interview sample. In-home interviews included topics such as health status, health-facility utilization, nutrition, peer networks, decision-making processes, family composition and dynamics, educational aspirations and expectations, employment experience, romantic and sexual partnerships, substance use, and criminal activities. A parent, preferably the resident mother, of each adolescent respondent interviewed in Wave I was also asked to complete an interviewer-assisted questionnaire covering topics such as inheritable health conditions, marriages and marriage-like relationships, neighborhood characteristics, involvement in volunteer, civic, and school activities, health-affecting behaviors, education and employment, household income and economic assistance, parent-adolescent communication and interaction, parent's familiarity with the adolescent's friends and friends' parents. Add Health data collection recommenced for Wave II from April to August 1996, and included almost 15,000 follow-up in-home interviews with adolescents from Wave I. Interview questions were generally similar to Wave I, but also included questions about sun exposure and more detailed nutrition questions. Respondents were asked to report their height and weight during the course of the interview, and were also weighed and measured by the interviewer. From August 2001 to April 2002, Wave III data were collected through in-home interviews with 15,170 Wave I respondents (now 18 to 26 years old), as well as interviews with their partners. Respondents were administered survey questions designed to obtain information about family, relationships, sexual experiences, childbearing, and educational histories, labor force involvement, civic participation, religion and spirituality, mental health, health insurance, illness, delinquency and violence, gambling, substance abuse, and involvement with the criminal justice system. High School Transcript Release Forms were also collected at Wave III, and these data comprise the Education Data component of the Add Health study. Wave IV in-home interviews were conducted in 2008 and 2009 when the original Wave I respondents were 24 to 32 years old. Longitudinal survey data were collected on the social, economic, psychological, and health circumstances of respondents, as well as longitudinal geographic data. Survey questions were expanded on educational transitions, economic status and financial resources and strains, sleep patterns and sleep quality, eating habits and nutrition, illnesses and medications, physical activities, emotional content and quality of current or most recent romantic/cohabiting/marriage relationships, and maltreatment during childhood by caregivers. Dates and circumstances of key life events occurring in young adulthood were also recorded, including a complete marriage and cohabitation history, full pregnancy and fertility histories from both men and women, an educational history of dates of degrees and school attendance, contact with the criminal justice system, military service, and various employment events, including the date of first and current jobs, with respective information on occupation, industry, wages, hours, and benefits. Finally, physical measurements and biospecimens were also collected at Wave IV, and included anthropometric measures of weight, height and waist circumference, cardiovascular measures such as systolic blood pressure, diastolic blood pressure, and pulse, metabolic measures from dried blood spots assayed for lipids, glucose, and glycosylated hemoglobin (HbA1c), measures of inflammation and immune function, including High sensitivity C-reactive protein (hsCRP) and Epstein-Barr virus (EBV). Datasets: DS0: Study-Level Files DS1: Wave I: In-Home Questionnaire, Public Use Sample DS2: Wave I: Public Use Contextual Database DS3: Wave I: Network Variables DS4: Wave I: Public Use Grand Sample Weights DS5: Wave II: In-Home Questionnaire, Public Use Sample DS6: Wave II: Public Use Contextual Database DS7: Wave II: Public Use Grand Sample Weights DS8: Wave III: In-Home Questionnaire, Public Use Sample DS9: Wave III: In-Home Questionnaire, Public Use Sample (Section 17: Relationships) DS10: Wave III: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancies) DS11: Wave III: In-Home Questionnaire, Public Use Sample (Section 19: Relationships in Detail) DS12: Wave III: In-Home Questionnaire, Public Use Sample (Section 22: Completed Pregnancies) DS13: Wave III: In-Home Questionnaire, Public Use Sample (Section 23: Current Pregnancies) DS14: Wave III: In-Home Questionnaire, Public Use Sample (Section 24: Live Births) DS15: Wave III: In-Home Questionnaire, Public Use Sample (Section 25: Children and Parenting) DS16: Wave III: Public Use Education Data DS17: Wave III: Public Use Graduation Data DS18: Wave III: Public Use Education Data Weights DS19: Wave III: Add Health School Weights DS20: Wave III: Peabody Picture Vocabulary Test (PVT), Public Use DS21: Wave III: Public In-Home Weights DS22: Wave IV: In-Home Questionnaire, Public Use Sample DS23: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16B: Relationships) DS24: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16C: Relationships) DS25: Wave IV: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancy Table) DS26: Wave IV: In-Home Questionnaire, Public Use Sample (Section 19: Live Births) DS27: Wave IV: In-Home Questionnaire, Public Use Sample (Section 20A: Children and Parenting) DS28: Wave IV: Biomarkers, Measures of Inflammation and Immune Function DS29: Wave IV: Biomarkers, Measures of Glucose Homeostasis DS30: Wave IV: Biomarkers, Lipids DS31: Wave IV: Public Use Weights Wave I: The Stage 1 in-school sample was a stratified, random sample of all high schools in the United States. A school was eligible for the sample if it included an 11th grade and had a minimum enrollment of 30 students. A feeder school -- a school that sent graduates to the high school and that included a 7th grade -- was also recruited from the community. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12. The Stage 2 in-home sample of 27,000 adolescents consisted of a core sample from each community, plus selected special over samples. Eligibility for over samples was determined by an adolescent's responses on the in-school questionnaire. Adolescents could qualify for more than one sample.; Wave II: The Wave II in-home interview surveyed almost 15,000 of the same students one year after Wave I.; Wave III: The in-home Wave III sample consists of over 15,000 Wave I respondents who could be located and re-interviewed six years later.; Wave IV: All original Wave I in-home respondents were eligible for in-home interviews at Wave IV. At Wave IV, the Add Health sample was dispersed across the nation with respondents living in all 50 states. Administrators were able to locate 92.5% of the Wave IV sample and interviewed 80.3% of eligible sample members. ; For additional information on sampling, including detailed information on special oversamples, please see the Add Health Study Design page. Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health. Waves I and II focused on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants aged into adulthood, the scientific goals of the study expanded and evolved. Wave III explored adolescent experiences and behaviors related to decisions, behavior, and health outcomes in the transition to adulthood. Wave IV expanded to examine developmental and health trajectories across the life course of adolescence into young adulthood, using an integrative study design which combined social, behavioral, and biomedical measures data collection. Response Rates: Response rates for each wave were as follows: Wave I: 79 percent; Wave II: 88.6 percent; Wave III: 77.4 percent; Wave IV: 80.3 percent; Adolescents in grades 7 through 12 during the 1994-1995 school year. Respondents were geographically located in the United States. audio computer-assisted self interview (ACASI) computer-assisted personal interview (CAPI) computer-assisted self interview (CASI) paper and pencil interview (PAPI) face-to-face interview
Inter-university Con... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu65 citations 65 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!more_vert Inter-university Con... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2022SAGE Journals SSHRCSSHRCAuthors: Dall’Olio, Filippo; Vakratsas, Demetrios;Dall’Olio, Filippo; Vakratsas, Demetrios;This study provides a comprehensive assessment of the impact of advertising creative strategy (ACS) on advertising elasticity, founded on an integrative framework that distinguishes between the function (content) and form (execution) of an advertising creative. The authors evaluate function using a three-dimensional representation of content (experience, affect, cognition), whereas the representation of form accounts for both executional elements and the use of creative templates. The distinction between function and form allows for the investigation of potential synergies between content and execution, previously unaccounted for in the literature. The ACS framework also facilitates the calculation of composite metrics that capture holistic aspects of the creative strategy, such as focus (i.e., the extent of the emphasis on a specific content dimension) and variation (i.e., changes in content and execution over time). The empirical application focuses on a dynamic linear model analysis of 2,251 television advertising creatives from 91 brands in 16 consumer packaged goods categories. The findings show that for function, experiential content has the greatest effect on elasticity, followed by cognitive and affective content. Function and form produce synergies that advertisers can leverage to increase returns. Finally, focus, variation, and the use of templates increase advertising elasticity.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2021SAGE Journals SSHRCSSHRCSaunders, Jessica F.; Zak, Michelle; Matejko, Emily; Kassan, Anusha; Mukred, Rabab; Priolo, Alissa;Many modern emerging adults undertake the task of identity development while navigating life on a post-secondary campus, where they assimilate to new social and learning environments. Emerging adult newcomers (i.e. immigrants) must navigate additional developmental challenges as they reconcile their cultural, ethnic, and personal identity development simultaneously while facing systemic barriers to post-secondary integration. We employed an arts-based engagement ethnography to investigate the post-secondary integration experiences of 10 emerging adults from a person-first perspective. Through cultural probes, individual semi-structured interviews, and focus groups, we identified four key structures to participants’ integration experience: fitting in (through assimilation and accommodation), biculturalism, managing familial expectations, and being a newcomer in the classroom. This research clarifies the key experiences shaping young newcomer identity development and highlights the profound ways in which young newcomers negotiate and reconcile their intersecting identities while integrating into new education contexts following migration.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Taylor & Francis NSERC, SSHRCNSERC ,SSHRCSchmidtke, Daniel; Gagné, Christina L.; Kuperman, Victor; Spalding, Thomas L.; Tucker, Benjamin V.;Previous research has shown that compound word recognition involves selecting a relational meaning (e.g. “box for letters” for letterbox) out of a set of competing relational meanings for the same compound. We conducted five experiments to investigate the role of competition between relational meanings across visual and auditory compound word processing. In Experiment 1 conceptual relations judgments were collected for 604 English compound words. From this database we computed an information-theoretic measure of competition between conceptual relations – entropy of conceptual relations. Experiments 2 and 3 report that greater entropy (i.e. increased competition) among a set of conceptual relations leads to longer latencies for compounds in auditory lexical decision. Experiments 4 and 5 demonstrate the same result in two visual lexical decision studies. These findings provide evidence that relational meanings are constructed and evaluated during compound recognition, regardless of whether compounds are recognised via auditory or visual input.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2017Figshare SSHRCSSHRCMcIntyre, Laureen; Laurie-Ann Hellsten; Bidonde, Julia; Boden, Catherine; Doi, Carolyn;Abstract Background The majority of a child’s language development occurs in the first 5 years of life when brain development is most rapid. There are significant long-term benefits to supporting all children’s language and literacy development such as maximizing their developmental potential (i.e., cognitive, linguistic, social-emotional), when children are experiencing a critical period of development (i.e., early childhood to 9 years of age). A variety of people play a significant role in supporting children’s language development, including parents, guardians, family members, educators, and/or speech-language pathologists. Speech-language pathologists and educators are the professionals who predominantly support children’s language development in order for them to become effective communicators and lay the foundation for later developing literacy skills (i.e., reading and writing skills). Therefore, these professionals need formal and informal assessments that provide them information on a child’s understanding and/or use of the increasingly complex aspects of language in order to identify and support the receptive and expressive language learning needs of diverse children during their early learning experiences (i.e., aged 1.5 to 9 years). However, evidence on what methods and tools are being used is lacking. Methods The authors will carry out a scoping review of the literature to identify studies and map the receptive and expressive English language assessment methods and tools that have been published and used since 1980. Arksey and O’Malley’s (2005) six-stage approach to conducting a scoping review was drawn upon to design the protocol for this investigation: (1) identifying the research question; (2) identifying relevant studies; (3) study selection; (4) charting the data; (5) collating, summarizing, and reporting the results; and (6) consultation. Discussion This information will help these professionals identify and select appropriate assessment methods or tools that can be used to support development and/or identify areas of delay or difficulty and plan, implement, and monitor the progress of interventions supporting the development of receptive and expressive language skills in individuals with diverse language needs (e.g., typically developing children, children with language delays and disorders, children learning English as a second or additional language, Indigenous children who may be speaking dialects of English). Researchers plan to evaluate the effectiveness of the assessment methods or tools identified in the scoping review as an extension of this study.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.c.3734023&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.c.3734023&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022The Royal Society EC | NICH, NSERC, SSHRCEC| NICH ,NSERC ,SSHRCAuthors: Alexander, Jake M.; Atwater, Daniel Z.; Colautti, Robert I.; Hargreaves, Anna L.;Alexander, Jake M.; Atwater, Daniel Z.; Colautti, Robert I.; Hargreaves, Anna L.;This file contains code to model adaptive trade-offs across a species' range, and to produce Figs. 2 and 3.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.19114112&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.19114112&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2020SAGE Journals SSHRCSSHRCHamm, Jeremy M.; Perry, Raymond P.; Chipperfield, Judith G.; Hladkyj, Steve; Parker, Patti C.; Weiner, Bernard;Despite increased emphasis on educating students in science, technology, engineering, and mathematics (STEM) disciplines, nearly half of U.S. college students who enroll in these programs fail to graduate with STEM degrees. Using archival data from the Motivation and Academic Achievement Database, we tested whether a motivation intervention to reframe causal attributions for academic setbacks improved graduation rates for college students in STEM disciplines (N = 496). Results showed that the intervention increased the odds of 8-year graduation for students who were at risk of college dropout. Findings highlight the potential of theory-informed psychological interventions to increase persistence to graduation for at-risk students in STEM fields.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.25384/sage.c.4976162&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.25384/sage.c.4976162&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection 2018Figshare SSHRC, EC | INQMINDSSSHRC ,EC| INQMINDSAuthors: Völter, Christoph J.; Tinklenberg, Brandon; Call, Josep; Seed, Amanda M.;Völter, Christoph J.; Tinklenberg, Brandon; Call, Josep; Seed, Amanda M.;Cognitive abilities cannot be measured directly. What we can measure is individual variation in task performance. In this paper, we first make the case for why we should be interested in mapping individual differences in task performance on to particular cognitive abilities: we suggest that it is crucial for examining the causes and consequences of variation both within and between species. As a case study, we examine whether multiple measures of inhibitory control for non-human animals do indeed produce correlated task performance; however, no clear pattern emerges that would support the notion of a common cognitive ability underpinning individual differences in performance. We advocate a psychometric approach involving a three-step programme to make theoretical and empirical progress: first, we need tasks that reveal signature limits in performance. Second, we need to assess the reliability of individual differences in task performance. Third, multi-trait multi-method test batteries will be instrumental in validating cognitive abilities. Together, these steps will help us to establish what varies between individuals that could impact their fitness and ultimately shape the course of the evolution of animal minds. Finally, we propose executive functions, including working memory, inhibitory control and attentional shifting, as a sensible starting point for this endeavour.This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive ability’.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.c.4154450&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.c.4154450&type=result"></script>'); --> </script>
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