BackgroundWith the availability of raw DNA generated from direct‐to‐consumer (DTC) testing companies, there has been a proliferation of third‐party online services that are available to interpret the raw data for both genealogy and/or health purposes. This study examines the current landscape and downstream clinical implications of consumer use of third‐party services.MethodsStudy participants were recruited online from social media platforms. A total of 321 survey respondents reported using third‐party services for raw DNA interpretation.ResultsParticipants were highly motivated to explore raw DNA for ancestral information (67%), individual health implications (62%), or both (40%). Participants primarily used one of seven companies to interpret raw DNA; 73% used more than one. Company choice was driven by the type of results offered (51%), price (45%), and online reviews (31%). Approximately 30% of participants shared results with a medical provider and 21% shared with more than one. Outcomes of sharing ranged from disinterest/discounting of the information to diagnosis of genetic conditions. Participants were highly satisfied with their decision to analyze raw DNA (M = 4.54/5), yet challenges in understanding interpretation results were reported irrespective of satisfaction ratings.ConclusionConsumers face challenges in understanding the results and may seek out clinical assistance in interpreting their raw DNA results.
Background In recent years, there has been a proliferation of third-party Web-based services available to consumers to interpret raw DNA from direct-to-consumer genetic testing companies. Little is known about who uses these services and the downstream health implications. Identifying this hard-to-reach population of consumers for research raised questions about the most effective recruitment methods to undertake. Past studies have found that Web-based social media survey distribution can be cost-effective for targeting hard-to-reach populations, yet comparative efficacy information across platforms is limited. Objective The aim of this study was to identify the most effective Web-based strategies to identify and recruit the target population of direct-to-consumer genetic testing users who also made use of third-party interpretation services to analyze their raw genetic data. Web-based survey recruitment methods varying by social media platform and advertising method were compared in terms of cost-effectiveness and demographics of survey respondents. Methods A total of 5 Web-based survey distribution conditions were examined: 4 paid advertising services and 1 unpaid service. For the paid services, a 2x2 quasi-experimental design compared social media platforms (Facebook vs Twitter) and advertising tracking metrics (by click vs by conversion). The fifth unpaid comparison method consisted of study postings on the social media platform, Reddit, without any paid advertising. Links to identical Web-based versions of the study questionnaire were posted for 10 to 14 days for each of the distribution conditions, which allowed tracking the number of respondents that entered and completed the questionnaire by distribution condition. Results In total, 438 individuals were recruited to the study through all conditions. A nearly equivalent number of participants were recruited from paid campaigns on Facebook (n=159) and Twitter (n=167), with a smaller sample recruited on Reddit (n=112). Significantly more participants were recruited through conversion-tracking (n=222) than through click-tracking campaigns (n=104; Z=6.5, P<.001). Response rates were found to be partially driven by organic sharing of recruitment materials among social media users. Conversion tracking was more cost-effective than click tracking across paid social media platforms. Significant differences in terms of gender and age distributions were noted between the platforms and between the tracking metrics. Conclusions Web-based recruitment methods were effective at recruiting participants from a hard-to-reach population in a short time frame. There were significant differences in the effectiveness of various paid advertising techniques. Recruitment through Web-based communities also appeared to perform adequately, yet it may be limited by the number of users accessible in open community groups. Future research should evaluate the impact of organic sharing of recruitment materials because this appeared to play a substantial role in the observed effectiveness of different methods.
On June 24, 2022, the United States Supreme Court overturned landmark rulings made in its 1973 verdict in Roe v. Wade. The justices by way of a majority vote in Dobbs v. Jackson Women's Health Organization, decided that abortion wasn't a constitutional right and returned the issue of abortion to the elected representatives. This decision triggered multiple protests and debates across the US, especially in the context of the midterm elections in November 2022. Given that many citizens use social media platforms to express their views and mobilize for collective action, and given that online debate provides tangible effects on public opinion, political participation, news media coverage, and the political decision-making, it is crucial to understand online discussions surrounding this topic. Toward this end, we present the first large-scale Twitter dataset collected on the abortion rights debate in the United States. We present a set of 74M tweets systematically collected over the course of one year
Institutions and cultures usually evolve in response to environmental incentives. However, sometimes institutional change occurs due to stochastic drivers beyond current fitness, including drift, path dependency, blind imitation, and complementary cooperation in fluctuating environments. Disentangling the selective and stochastic components of social system change enables us to identify the key features of long-term organizational development. Evolutionary approaches provide organizational science with abundant theories to demonstrate organizational evolution by tracking beneficial or harmful features. In this study, focusing on 20,000 Minecraft communities, we measure these drivers empirically using two of the most widely applied evolutionary models: the Price equation and the bet-hedging model. As a result, we find strong selection pressure on administrative and information rules, suggesting that their positive correlation with community fitness is the main reason for their frequency change. We also find that stochastic drivers decrease the average frequency of administrative rules. The result makes sense when viewed in the context of evolutionary bet-hedging. We show through the bet-hedging result that institutional diversity contributes to the growth and stability of rules related to information, communication, and economic behaviors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.