Improving Participation in Data Donation Studies: A Systematic Review of Factors Driving Participation and Evidence-Informed Best Practices

Data donation makes it possible to invite participants to request and share their data from digital platforms for research purposes. While it is a user-centric approach to digital trace data collection, little is known about how participants experience and understand the data donation process. This study therefore asked twenty participants to verbalize their thoughts and actions as they went through data donation (from Google, YouTube, Facebook, X, Instagram, TikTok, LinkedIn), and interviewed them about their experiences. Using a workflow that visualized participants’ own data and enabled them to inspect and delete data prior to donation, we not only identified strengths and obstacles within the data donation process from a user perspective, but also gained insight into how participants make sense of data donation. Overall, we find that while participants enjoyed gaining insight into their own media behavior, their understanding of data donation was problematic. Most participants misunderstood or overlooked the option to search through and delete their data, raising questions about meaningful informed consent. Another key finding was that participants interpreted data visualizations as objective representations of their media use, even when these data were incomplete or contradicted their own ideas about their platform use. Privacy considerations were at play during platform selection, but less during the actual donation process.

The purpose of this comment is to examine the experimental design and empirical results presented by Johannesson, M., Liljas, B. and Peterson, G. (Applied Economics Letters, 4, 1997). Their paper attempts to confirm the Neill, H. R., Cummings, R. G., Ganderton, P., Harrison, G. W. and McGuckin, T. (Land Economics, 70, 1994) results. Their results are noteworthy since they find no statistical difference between real and hypothetical willingness–to–pay responses between groups. Their results also differ from earlier studies where hypothetical willingness to pay exceeds actual willingness to pay. This comment will examine important differences between the two studies. These differences make any substantive comparison of results difficult, if not impossible.

To compare hypothetical and actual willingness to enroll in a preventive HIV vaccine trial and identify factors affecting enrollment. Participants previously enrolled in an HIV vaccine preparedness study (VPS) in 8 US cities were invited to be screened for a phase 2 HIV vaccine trial. Demographic and risk characteristics of those enrolling, ineligible, and refusing enrollment were compared using the chi2 or Fisher exact test. Multivariable logistic models were used to identify independent predictors of refusal. Of 2531 high-risk HIV-uninfected former VPS participants contacted for the vaccine trial, 13% enrolled, 34% were ineligible, and 53% refused enrollment. Only 20% of those stating hypothetical willingness during the VPS actually enrolled in this vaccine trial. In multivariate analysis, refusal was higher among African Americans and lower in persons >40 years of age, those attending college, and those with > or =5 partners in the prior 6 months. All racial ethnic groups cited concerns about vaccine-induced seropositivity; African Americans also cited mistrust of government and safety concerns as barriers to enrollment. Steps can be taken to minimize potential social harms and to mobilize diverse communities to enroll in trials. Statements of hypothetical willingness to participate in future trials may overestimate true enrollment.

Hypothetical questionnaires may overestimate willingness to participate in HIV cure research: Comparison of a cross-sectional survey to actual willingness to participate in an HIV cure study in the Netherlands

As we navigate physical (e.g., supermarket) and digital (e.g., social media) systems, we generate personal data about our behavior. Researchers and designers increasingly rely on this data and appeal to several approaches to collect it. One of these is data donation, which encourages people to voluntarily transfer their (personal) data collected by external parties to a specific cause. One of the central pillars of data donation is informed consent, meaning people should be adequately informed about what and how their data will be used. However, can we be adequately informed when it comes to donating our data when many times we don’t even know it is being collected and, even more so, what exactly is being collected? In this paper, we investigate how to foster (personal) data literacy and increase donors’ understanding of their data. We introduce a Research through Design approach where we define a data donation journey in the context of speech records, data collected by Google Assistant. Based on the data donation experiences of 22 donors, we propose a data donation framework that understands and approaches data donation as an encompassing process with mutual benefit for donors and researchers. Our framework supports a donation process that dynamically and iteratively engages donors in exploring and understanding their data and invites them to (re)evaluate and (re)assess their participation. Through this process, donors increase their data literacy and are empowered to give meaningfully informed consent.

Smartphones are now ubiquitous in daily life, requiring the development of accurate methodologies to study their impact on various aspects of human experience. A promising approach to collect mobile log data is to ask participants to donate, in the context of online surveys, the data that is already available to them through features such as iOS Screen Time and Android Digital Wellbeing. This approach grants participants control over the data they share while providing researchers with valuable observational insights into their mobile and app behaviours. However, the active involvement required from participants poses challenges, leading to low compliance rates and potential biases in the final sample of donors. This study investigates whether the method used to collect data donations, and the incentives provided, have an impact on compliance rates, and the subsequent composition of the sample. Specifically, we implemented a 2 × 3 between-subject web survey experiment (N = 872) in a research-led probability-based panel in Switzerland. Participants were randomly asked to capture and share their data through screenshots, video recordings, and by manual imputation (which we call enhanced recall). Results show that, while compliance rates are very low when using screenshots and video recordings as data donation methods, almost two thirds of participants donated their data by manually imputing their log data. We also found donors to be younger and more technologically adept. Overall, our study sheds light on maximising compliance in data donation studies, offering insights for researchers studying mobile and app usage.

Use of multiple devices among U.S. adults frequently using ENDS in 2023.

This paper reports the findings of a field experiment that explores the criterion validity of the contingent valuation (CV) method. The empirical experiment examined the disparity between hypothetical and actual willingness to pay (WTP) bids for Red Kite conservation in Wales. Hypothetical WTP was elicited using an open‐ended CV instrument, while the actual WTP value was determined from actual donations to the Welsh Kite Trust—a charity set up to aid the conservation of Red Kites in Wales. The survey results indicate that hypothetical WTP was three times greater than the mean value of actual donations; this finding is consistent with a number of other criterion validity experiments. However, we also demonstrate equality of hypothetical and actual WTP among those who actually express a payment amount. Further investigations identify that an underlying cause of this disparity stems from the respondents of the CV survey overstating their intention of pay. This observation has potentially significant implication for CV design in that it suggests that the emphasis in design should be placed much more fully on initially determining whether people would actually pay at all. Le présent article présente les résultats d'une expérience sur le terrain qui a exploré la validité de critère de la méthode d'évaluation contingente (CV). L'expérience empirique a examiné l'écart entre la volonté de payer (VDP) hypothétique et réelle pour la conservation du milan royal dans le pays de Galles. La VDP hypothétique a été obtenue en utilisant un questionnaire ouvert pour effectuer l'évaluation contingente (CV), tandis que la valeur de la VDP réelle a été déterminée d'après les dons réels versés àThe Welsh Kite Trust, organisation caritative créée pour la conservation du milan royal au pays de Galles. Les résultats du sondage ont indiqué que la VDP hypothétique était trois fois supérieures à la valeur moyenne des dons réels; ce résultat rejoint ceux d'autres expériences sur la validité de critère. Cependant, nous avons aussi démontré une égalité entre la VDP hypothétique et réelle des personnes qui ont exprimé le montant du don. Des sondages ultérieurs ont montré qu'une des causes sous‐jacentes de cet écart venait du fait que les répondants avaient exagéré leur intention de payer. Cette observation a une implication potentielle importante pour la conception d'évaluation contingente puisqu'elle laisse supposer que l'accent mis sur la conception devrait plutôt être mis sur la détermination initiale de l'intention des personnes à payer ou non.

To determine the hypothetical and actual willingness of households to pay (WTP) for insecticide-treated nets (ITNs), and compare these in areas with and without previous exposure to free ITNs. The contingent valuation method was used to determine the willingness of the heads of 1908 randomly selected households from five communities in south-east Nigeria to pay for two sizes of ITNs. Two communities previously had free access to ITNs. Validity was assessed using multiple regression analyses, and by offering ITNs for sale to 200 randomly selected people drawn from the original sample. The data was collected between March and September 1998. Most respondents were willing to pay for ITNs: Mbano (93.26%), Ugwogo (97.69%), Orba (83.24%), Alor-uno (95.37%), and Ibagwa-ani (87.34%). In multivariate analyses, WTP was significantly associated with the number of people living in a household, sex of the respondent, average yearly expenditure on gifts and the type of savings scheme (P < 0.05). Some of the residences were also statistically significant in the two models used, and those with prior exposure to free ITNs were negatively related to WTP. Seventy-six percent of those who were hypothetically willing to pay actually purchased them, and the WTP technique correctly predicted the choices of 80% of the respondents. There was good evidence that stated WTP could be translated into actual WTP. However, peoples' perception of affordability of the nets and its link to their WTP needs further exploration. The WTP technique is a potentially valid tool for market research in healthcare, as it was able to predict the direction of actual WTP for the ITNs. The hypothetical WTP amounts could be used as guide to know either the optimal price to charge for the ITNs or the level of subsidy to introduce.

Independent samples and paired responses of adults were used to test differences between hypothetical and actual willingness to pay (WTP) for an art print elicited using an open-ended WTP question. We attempted to overcome hypothesized reasons for divergences between cash and hypothetical WTP by asking respondents not report what they thought the market price was for the good and to act as if this was a real market. The results reject equality of hypothetical and actual WTP, but the differences are smaller than in other experiments, with hypothetical WTP being two times larger than actual WTP.

Medical data are being generated in large quantities. However, these data are rarely used beyond their primary purpose. Big data methods to medical data offer the opportunity to transform healthcare. The healthcare industry has been a lot less successful than other industries in applying these new tools. Main reasons are privacy concerns and the fact that medical data in Germany are scattered across institutions. The method of data donation can offer a solution. The first aim of the proposed Medical Data Donation Enabler (MADE) project is to investigate ethical, legal and socio-technical barriers to data donation. The second aim is to develop a concept of a medical data donation process model that addresses the barriers by providing a data donation process model. The process model concept created through MADE could be provided for this purpose.

This paper describes the methodology used to design and execute a project for donating multiple high-resolution datasets simultaneously to a number of university geoscience departments. A step-by-step process shows how an integrated, multidisciplinary team consisting of data specialists, geoscientists, attorneys, administrators and others verified that the datasets were sound, eligible for distribution and consistently delivered to recipient universities. The steps include obtaining permissions from four internal BP asset teams and four external data co-owners, and assuring ownership and distribution rights through the data acquisition contractor. Efficiencies in the data donation process were achieved by batch issuing the data to a group of universities under a single round of permissions granted by internal BP data owners and a Letter Agreement executed between BP and each of the data co-owners. The permissions and agreements put in place will cover additional qualified research and teaching institutions that may be identified in the future, allowing subsequent data donations without the need for supplementary rounds of approvals. After executing Confidentiality Agreements and distributing data to a group of 15 targeted U.S. University Geoscience Departments, additional universities have applied for, and received, the datasets, with selected universities outside the U.S. also receiving data. Originally, data were delivered on a physical disk drive however, more recently, a digital data download system has been enabled. The BP Data Donation Project met the initial goal of delivering high-resolution geophysical datasets from four BP deep-water developments in the Gulf of Mexico to multiple universities in 2011. BP have seen that these universities are using the data in teaching and research and that expertise in using these data types is developing in the recipient Geoscience Departments. Research results based on the donated datasets have enhanced our understanding of seafloor and shallow subsurface geology. The data donation effort has enabled graduate research projects and the first manuscripts based on research using the data are beginning to be published. The data donation project will eventually be shut down, with one potential trigger being a drop off in demand for the high-resolution datasets. However, alternative datasets may become eligible for donation in the future, possibly including a collection of proprietary, high-resolution 3D seismic data.

Health data are being generated in large quantities. However, these data are rarely used beyond their primary purpose in comparison to other industries. Main barriers are privacy and ethical concerns and the fact that medical data are scattered across institutions. The study investigated the availability and utilization of public use files (PUF) of primary research data as well as ethical and legal barriers limiting the donation of medical research data for secondary use in preparation for the development of a process model to foster medical data donation. First, the availability and utilization of PUFs from primary research data were investigated through a selective literature review. Secondly, ethical and legal barriers that are limiting the donation of medical research data for secondary use were investigated. A simplified process model was developed based on an initial literature review. The process model was used to identify questions that need to be addressed to facilitate data donation. Solutions to address the identified questions will be developed through another review of the literature and expert interviews. An enhanced data donation process model will be developed and refined through a second iteration. The review of PUFs has shown that the availability and utilization of research data through public use files for secondary use is limited. As a means to facilitate and foster secondary data use, the researchers advocate for a simplified data donation process for medical research data. The results of the first step of the project showed that several ethical, legal, and social-technical questions need to be addressed to implement a simplified data donation process. The project s next steps will include the development of solutions to those barriers will be developed and included in an improved concept of a data donation process model.

Data donation is a novel approach to collecting digital trace data, where users are asked to download their retrospective data from a platform and share them with the researchers. Little is known about the willingness to donate data and the potential bias that may arise from nonparticipation. We conducted a study among over 900 German Facebook users asking them to donate two data packages. While around 80% of participants were willing to donate their data, only around one-third of them successfully did so. Trust in researchers positively correlates with willingness and donation success, and trust in Facebook is negatively associated with donation success. The framing of the data donation request did not affect the outcomes. We find no difference in frequency of Facebook use between donors and non-donors.

‘Address and command’: Two-handed mid-air interactions with multiple home devices