The Survey of Health, Ageing and Retirement in Europe (SHARE) is a research infrastructure for studying the effects of health, social, economic and environmental policies over the life-course of European citizens and beyond. From 2004 until today, 530,000 in-depth interviews with 140,000 people aged 50 or older from 28 European countries and Israel have been conducted. Thus, SHARE is the largest pan-European social science panel study providing internationally comparable longitudinal micro data which allow insights in the fields of public health and socio-economic living conditions of European individuals.

The SHARE Mental Health (SHARE-MH) cohort was established to address the paucity of clinical and genetic data available for mental health research. The cohort brings together detailed mental health questionnaire responses, routinely-collected electronic health data and genetic data to provide researchers with an unprecedented linkable dataset. This data represents the mental health survey that was sent to participants of the SHARE research register, and which forms the basis for the SHARE-MH cohort. It provides research-grade individual-level data on mental health and the experiences of those interacting with healthcare services.

ObjectivesA survey of a population-based sample of U.S adults was conducted to measure their attitudes about, and inform the design of the Precision Medicine Initiative’s planned national cohort study.MethodsAn online survey was conducted by GfK between May and June of 2015. The influence of different consent models on willingness to share data was examined by randomizing participants to one of eight consent scenarios.ResultsOf 4,777 people invited to take the survey, 2,706 responded and 2,601 (54% response rate) provided valid responses. Most respondents (79%) supported the proposed study, and 54% said they would definitely or probably participate if asked. Support for and willingness to participate in the study varied little among demographic groups; younger respondents, LGBT respondents, and those with more years of education were significantly more likely to take part if asked. The most important study incentive that the survey asked about was learning about one’s own health information. Willingness to share data and samples under broad, study-by-study, menu and dynamic consent models was similar when a statement about transparency was included in the consent scenarios. Respondents were generally interested in taking part in several governance functions of the cohort study.ConclusionsA large majority of the U.S. adults who responded to the survey supported a large national cohort study. Levels of support for the study and willingness to participate were both consistent across most demographic groups. The opportunity to learn health information about one’s self from the study appears to be a strong motivation to participate.

Various concerns have been documented in the literature over the sharing of data, including the lack of incentives for sharing. To address this, several systems for recognition have been proposed (e.g. Data Authorship, CRediT, data citation…). This study was set up to discuss the past experiences with data sharing with persons involved with data sharing platforms to better understand the potential barriers and solutions. In total, 17 cohort holders and developers associated with three different data sharing platforms were recruited for a semi-structured interview. The goal of this study was to (1) document the views and opinions on different incentives for data sharing; (2) to explore experiences on data sharing and credit mechanisms within consortia; (3) to record views on the roles of different actors within academia to change the existing incentive structure for Open/FAIR Data; and (4) to investigate the interaction between data sharing practices and novel technologies.

Interactions on social media have the potential to help us to understand human behaviour, including the development of both good and poor mental health. However, to do the best science we need to know as much as possible about the people who are participating in our research. The CLOSER group of UK longitudinal cohorts include people who have contributed their data to research since birth. By inviting participants in these cohorts to also allow us to derive information from their social media feeds, we will be able to relate this information to gold-standard measures of the behaviours we are trying to understand and to world-class data on other aspects of life. To work out the best way to do this, our project will engage with participants in the Children of the '90s cohort to find out what is acceptable to them in terms of collecting and using their interactions on social media. We will use what we have learnt to develop software that collects and codes social media data in a way that protects the anonymity of participants by scoring Tweets without making the text available to researchers. We will share this software with other CLOSER cohorts to make it easy for them to invite participants to contribute their Twitter data in a safe and secure way. The high-resolution data collected in this way will help us to understand human behaviour and how mental health changes over time. Collecting these data in well known groups of people will also give scientists the information they need to improve the quality of all research using social media.Interactions on social media have the potential to help us to understand human behaviour, including the development of both good and poor mental health. However, to do the best science we need to know as much as possible about the people who are participating in our research. The CLOSER group of UK longitudinal cohorts include people who have contributed their data to research since birth. By inviting participants in these cohorts to also allow us to derive information from their social media feeds, we will be able to relate this information to gold-standard measures of the behaviours we are trying to understand and to world-class data on other aspects of life. To work out the best way to do this, our project will engage with participants in the Children of the '90s cohort to find out what is acceptable to them in terms of collecting and using their interactions on social media. We will use what we have learnt to develop software that collects and codes social media data in a way that protects the anonymity of participants by scoring Tweets without making the text available to researchers. We will share this software with other CLOSER cohorts to make it easy for them to invite participants to contribute their Twitter data in a safe and secure way. The high-resolution data collected in this way will help us to understand human behaviour and how mental health changes over time. Collecting these data in well known groups of people will also give scientists the information they need to improve the quality of all research using social media. We are demonstrating collection, anonymisation and analysis of social media data from consenting participants in the Avon Longitudinal Study of Parents and Children. Initially we are studying Twitter use, and gathering data through the platforms API. Our software gathers social media posts and interactions from participants every few days, with datasets being stored under security ISO 27001 certification. Derived, depersonalised datasets can be made available to approved researchers, and we aim to provide a means to evaluate sentiment analysis methods against ground truth data.

The public sharing of primary research datasets potentially benefits the research community but is not yet common practice. In this pilot study, we analyzed whether data sharing frequency was associated with funder and publisher requirements, journal impact factor, or investigator experience and impact. Across 397 recent biomedical microarray studies, we found investigators were more likely to publicly share their raw dataset when their study was published in a high-impact journal and when the first or last authors had high levels of career experience and impact. We estimate the USA's National Institutes of Health (NIH) data sharing policy applied to 19% of the studies in our cohort; being subject to the NIH data sharing plan requirement was not found to correlate with increased data sharing behavior in multivariate logistic regression analysis. Studies published in journals that required a database submission accession number as a condition of publication were more likely to share their data, but this trend was not statistically significant. These early results will inform our ongoing larger analysis, and hopefully contribute to the development of more effective data sharing initiatives. Earlier version presented at ASIS&T and ISSI Pre-Conference: Symposium on Informetrics and Scientometrics 2009

The Covid-19 pandemic required many clinical trials to adopt a decentralized framework to continue research activities during lock down restrictions. The STOPCoV study was designed to assess the safety and efficacy of Covid-19 vaccines in those aged 70 and above compared to those aged 30–50 years of age. In this sub-study we aimed to determine participant satisfaction for the decentralized processes, accessing the study website and collecting and submitting study specimens. The satisfaction survey was based on a Likert scale developed by a team of three investigators. Overall, there were 42 questions for respondents to answer. The invitation to participate with a link to the survey was emailed to 1253 active participants near the mid-way point of the main STOPCoV trial (April 2022). The results were collated and answers were compared between the two age cohorts. Overall, 70% (83% older, 54% younger cohort, no difference by sex) responded to the survey. The overall feedback was positive with over 90% of respondents answering that the website was easy to use. Despite the age gap, both the older cohort and younger cohort reported ease of performing study activities through a personal electronic device. Only 30% of the participants had previously participated in a clinical trial, however over 90% agreed that they would be willing to participate in future clinical research. Some difficulties were noted in refreshing the browser whenever updates to the website were made. The feedback attained will be used to improve current processes and procedures of the STOPCoV trial as well as share learning experiences to inform future fully decentralized research studies.

The Covid-19 pandemic required many clinical trials to adopt a decentralized framework to continue research activities during lock down restrictions. The STOPCoV study was designed to assess the safety and efficacy of Covid-19 vaccines in those aged 70 and above compared to those aged 30–50 years of age. In this sub-study we aimed to determine participant satisfaction for the decentralized processes, accessing the study website and collecting and submitting study specimens. The satisfaction survey was based on a Likert scale developed by a team of three investigators. Overall, there were 42 questions for respondents to answer. The invitation to participate with a link to the survey was emailed to 1253 active participants near the mid-way point of the main STOPCoV trial (April 2022). The results were collated and answers were compared between the two age cohorts. Overall, 70% (83% older, 54% younger cohort, no difference by sex) responded to the survey. The overall feedback was positive with over 90% of respondents answering that the website was easy to use. Despite the age gap, both the older cohort and younger cohort reported ease of performing study activities through a personal electronic device. Only 30% of the participants had previously participated in a clinical trial, however over 90% agreed that they would be willing to participate in future clinical research. Some difficulties were noted in refreshing the browser whenever updates to the website were made. The feedback attained will be used to improve current processes and procedures of the STOPCoV trial as well as share learning experiences to inform future fully decentralized research studies.

We report on MRi-Share, a multi-modal brain MRI database acquired in a unique sample of 1,870 young healthy adults, aged 18 to 35 years, while undergoing university-level education. MRi-Share contains structural (T1 and FLAIR), diffusion (multispectral), susceptibility weighted (SWI), and resting-state functional imaging modalities. Here, we described the contents of these different neuroimaging datasets and the processing pipelines used to derive brain phenotypes, as well as how quality control was assessed. In addition, we present preliminary results on associations of some of these brain image-derived phenotypes at the whole brain level with both age and sex, in the subsample of 1,722 individuals aged less than 26 years. We demonstrate that the post-adolescence period is characterized by changes in both structural and microstructural brain phenotypes. Grey matter cortical thickness, surface area and volume were found to decrease with age, while white matter volume shows increase. Diffusivity, either radial or axial, was found to robustly decrease with age whereas fractional anisotropy only slightly increased. As for the neurite orientation dispersion and densities, both were found to increase with age. The isotropic volume fraction also showed a slight increase with age. These preliminary findings emphasize the complexity of changes in brain structure and function occurring in this critical period at the interface of late maturation and early aging. Methods The dataset is based on magnetic resonance imaging (MRI) data collected as part of MRiShare database. The anatomical and diffusion-weighted imaging data from 1,832 healthy subjects were processed as described in the associated publication. The dataset contains global imaging-derived phenotypes (IDPs) described in the paper.

(n = 2,601).

In 2023, **** percent of the cohort that started schooling in 2009 were admitted to publicly-funded degree courses in Singapore. The share of the cohort admitted to such degree courses had been increasing since 2018.

In 2023, over *** percent of Aboriginal and Torres Strait Islander children in the year before formal school age cohort were enrolled in a preschool program in Australia, representing an increase from 2022. The number is over 100 percent as the data underestimates the number of Aboriginal and Torres Strait Islander people in the years after the 2016 Census.

The Covid-19 pandemic required many clinical trials to adopt a decentralized framework to continue research activities during lock down restrictions. The STOPCoV study was designed to assess the safety and efficacy of Covid-19 vaccines in those aged 70 and above compared to those aged 30–50 years of age. In this sub-study we aimed to determine participant satisfaction for the decentralized processes, accessing the study website and collecting and submitting study specimens. The satisfaction survey was based on a Likert scale developed by a team of three investigators. Overall, there were 42 questions for respondents to answer. The invitation to participate with a link to the survey was emailed to 1253 active participants near the mid-way point of the main STOPCoV trial (April 2022). The results were collated and answers were compared between the two age cohorts. Overall, 70% (83% older, 54% younger cohort, no difference by sex) responded to the survey. The overall feedback was positive with over 90% of respondents answering that the website was easy to use. Despite the age gap, both the older cohort and younger cohort reported ease of performing study activities through a personal electronic device. Only 30% of the participants had previously participated in a clinical trial, however over 90% agreed that they would be willing to participate in future clinical research. Some difficulties were noted in refreshing the browser whenever updates to the website were made. The feedback attained will be used to improve current processes and procedures of the STOPCoV trial as well as share learning experiences to inform future fully decentralized research studies.

In 2023, millennials were the most likely to engage in grocery e-commerce in the U.S., with ** percent reporting that they shopped for groceries on the internet. Gen Z was next, with ** percent making online grocery purchases.

This dataset contains anonymized transcripts of interviews performed during a qualitative interview study with members of 16 research funding agencies. Sample: Funding agencies were located mainly, but not exclusively, in Europe. Funding agencies were selected using a purposive sampling strategy that aimed to acquire sufficient representation of (a) national and international agencies; (b) public and philanthropic agencies; and (c) agencies in continental European and the anglophone world. Suitable funding agencies were selected through various means, such as a list of health research funding organizations according to their annual expenditure on health research (https://www.healthresearchfunders.org/health-research-funding-organizations/) and Science Europe Working Groups. Background: Open science policy documents have emphasized the need to install more incentives for data sharing. These incentives are often understood as being reputational or financial. Additionally, there are other policy measures that could be taken, such as data sharing mandates. Aim: To document views of funding agencies on (1) potential alterations to recognition systems in academia; (2) incentives to enhance the sharing of cohort data; (3) data sharing policies in terms of the governance of cohort data; (4) other potential interactions between science policy and data sharing platforms for cohorts. Our study focused on the sharing of patient- and population-based cohorts through data infrastructures.

Informed consent (IC) is key to generating and maintaining research participants' trust and upholding the ethical principle of respect for persons. Broad consent for future use, wherein researchers ask participants for their permission to share participant-level data and samples collected within the study for purposes loosely related to the study objectives, is central to enabling data and sample reuse. Ensuring that participants understand broad consent-related language is key to maintaining their trust in the study itself and in public health research more generally. To ensure research projects' adherence to core ethical principles, many research centres, ethics review committees (ERCs), and journals ask that studies use templates for informed consent and have different levels of comfort with investigators' deviation from the template language.

The principal aim of the Swiss Household Panel (SHP) is to observe social change, in particular the dynamics of changing living conditions and representations in the population of Switzerland. Covering a broad range of topics and approaches in the social sciences, SHP is a yearly panel with rotating modules following three random samples of private households in Switzerland over time, interviewing all household members, mainly by telephone. The LIVES FORS Cohort Survey can be essentially seen as an SHP additional sample. The waves of SHP and the LIVES FORS Cohort Survey run in parallel and share most of the questions and modules. That said the LIVES FORS Cohort Survey is distinguished from SHP by a specific reference population and sampling procedure. In addition, only the targeted member of the household has to respond to the individual questionnaire (and not all members as in SHP).

This statistic displays the findings of a survey on the the share of individuals who interacted with a physical store on their path to purchase in the United Kingdom (UK) in 2017, by demographic cohort. In 2017, it was found that ** percent of responding Millennials reported that they interacted with a physical store.

Background and Objectives: Few studies have investigated the bidirectional relationship between disability and multimorbidity, which are common conditions among the older population. Based on the data from the China Health and Retirement Longitudinal Study (CHARLS) and the Survey of Health, Ageing and Retirement in Europe (SHARE), we aimed to investigate the bidirectional relationship between disability and multimorbidity. Methods: The activities of daily living (ADLs) and the instrumental activities of daily living (IADLs) scales were used to measure disability. In stage I, we used multinomial logistic regression to assess the longitudinal association between ADL/IADL disability and follow-up multimorbidity. In stage II, binary logistic regression was used to evaluate the multimorbidity effect on future disability. Results: Compared with those free of disability, people with disability possessed ascending risks for developing an increasing number of diseases. For ADL disability, the odds ratio (OR) (95% confidence interval [CI]) values of developing ≥4 diseases were 4.10 (2.58, 6.51) and 6.59 (4.54, 9.56) in CHARLS and SHARE; for IADL disability, the OR (95% CI) values were 2.55 (1.69, 3.84) and 4.85 (3.51, 6.70) in CHARLS and SHARE. Meanwhile, the number of diseases at baseline was associated, in a dose-response manner, with future disability. Compared with those without chronic diseases, participants carrying ≥4 diseases had OR (95% CI) values of 4.82 (3.73, 6.21)/4.66 (3.65, 5.95) in CHARLS and 3.19 (2.59, 3.94)/3.28 (2.71, 3.98) in SHARE for developing ADL/IADL disability. Conclusion: The consistent findings across 2 national longitudinal studies supported a strong bidirectional association between disability and multimorbidity among middle-aged and elderly adults. Thus, tailored interventions should be taken to prevent the mutual development of disability and multimorbidity.

According to data findings from the United Kingdom (UK) in 2020, the baby boomer cohort claimed to have visited less make up and skincare retail stores amid the pandemic compared to normal by ** percent compared with Gen Z and Millennials at ** percent. When it came to visiting at the same frequency, the younger cohort took the lead with ** percent over baby boomers at ** percent. A similar result was observed when Gen Z and Millennials stated to have visited stores more at * percent over * percent of baby boomers.