Motivations of participants in the citizen science of microbiomics: data from the British Gut Project

Savio, Lorenzo Del; Prainsack, Barbara; Buyx, Alena

doi:10.1038/gim.2016.208

Cited by 18 publications

(16 citation statements)

References 17 publications

(6 reference statements)

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“…Our participant’s strongest motivations for taking part in the study were personal interest and a desire to contribute. Previous studies have also found these two reasons to be important to participants but, contrary to our study, tend to find that the desire to contribute is most common and personal interest is second [16–18]. This may be because other studies have had a clearer link between participation and a specific research outcome such as finding a cure for a medical condition.…”

Section: Discussioncontrasting

confidence: 98%

The feasibility of using citizens to segment anatomy from medical images: Accuracy and motivation

et al. 2019

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The development of automatic methods for segmenting anatomy from medical images is an important goal for many medical and healthcare research areas. Datasets that can be used to train and test computer algorithms, however, are often small due to the difficulties in obtaining experts to segment enough examples. Citizen science provides a potential solution to this problem but the feasibility of using the public to identify and segment anatomy in a medical image has not been investigated. Our study therefore aimed to explore the feasibility, in terms of performance and motivation, of using citizens for such purposes. Public involvement was woven into the study design and evaluation. Twenty-nine citizens were recruited and, after brief training, asked to segment the spine from a dataset of 150 magnetic resonance images. Participants segmented as many images as they could within three one-hour sessions. Their accuracy was evaluated by comparing them, as individuals and as a combined consensus, to the segmentations of three experts. Questionnaires and a focus group were used to determine the citizens’ motivation for taking part and their experience of the study. Citizen segmentation accuracy, in terms of agreement with the expert consensus segmentation, varied considerably between individual citizens. The citizen consensus, however, was close to the expert consensus, indicating that when pooled, citizens may be able to replace or supplement experts for generating large image datasets. Personal interest and a desire to help were the two most common reasons for taking part in the study.

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Section: Discussioncontrasting

confidence: 98%

The feasibility of using citizens to segment anatomy from medical images: Accuracy and motivation

et al. 2019

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“…Different diver types have similar preferences and motivations to participate in CS, but there are important differences in their profile that could affect their participation in CS projects. For example, the differences in education level could influence their decision to participate, since a low level of education has been reported as a barrier to CS projects (Savio et al, 2017) and can affect data quality (Delaney et al, 2008). Our findings show that artisanal fishermen, despite their comparatively basic science literacy, have a high level of diving experience.…”

Section: The Diversity Of Divers and Designing Cs Projectsmentioning

confidence: 83%

How Does the Diversity of Divers Affect the Design of Citizen Science Projects?

et al. 2019

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Divers have widely participated in citizen science (CS) projects and are one of the main groups of marine citizen scientists. However, there is little knowledge about profiles of, and incentives for potential divers to join CS projects. To date, most studies have focused on the SCUBA diving industry; nevertheless, there is a diversity of divers, not all using SCUBA, who engage in different activities during their dives. Differences in diver profiles could affect their willingness and ability to contribute to CS. In this study, we compare the diving profile, interests, preferences and motivations to participate in CS of five diver types (artisanal fishermen, recreational divers, instructors, scientific divers, and others). All divers have strong interests in participating in CS projects, with no major differences among diver types. In general, they are interested in a wide variety of themes related to CS but they prefer simple sampling protocols. Divers are motivated to participate in CS to learn about the sea and contribute to science. Some important differences among diver types were found, with artisanal fishermen having significantly more dive experience than other diver types, but less free time during their dives and limited access to some communication channels and technologies. These characteristics make them ideal partners to contribute their local ecological knowledge (LEK) to local CS projects. In contrast, recreational divers have the least experience but most free time during their dives and good access to cameras and communications channels, making them suitable partners for large-scale CS projects that do not require a high level of species knowledge. Instructors and scientific divers are well-placed to coordinate and supervise CS activities. The results confirm that divers are not all alike and specific considerations have to be taken into account to improve the contribution of each diver type to CS. The findings provide essential information for the design of different types of CS projects. By considering the relevant incentives and opportunities for diverse diver groups, marine CS projects will make efficient gains in volunteer recruitment, retention, and collaborative generation of knowledge about the marine environment.

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“…Following suit, multiple nationwide and cohort-specific studies were conducted to understand the impact of the gut microbiome. 21 , 22 . These studies led to an exponential rise in available gut microbiome datasets across multiple cohorts.…”

Section: Background and Summarymentioning

confidence: 99%

LogMPIE, pan-India profiling of the human gut microbiome using 16S rRNA sequencing

Dubey

Uppadhyaya

Nilawe³

et al. 2018

Sci Data

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The “Landscape Of Gut Microbiome - Pan-India Exploration”, or LogMPIE study, is the first large-scale, nationwide record of the Indian gut microbiome. The primary objective of the study was to identify and map the Indian gut microbiome baseline. This observational study was conducted across 14 geographical locations in India. Enrolled subjects were uniformly distributed across geographies (north, east, west and south) and body mass index (obese and non-obese). Furthermore, factors influencing the microbiome, such as age and physical activity, were also considered in the study design. The LogMPIE study recorded data from 1004 eligible subjects and reported 993 unique microorganisms across the Indian microbiome diaspora. The data not only map the Indian gut microbiome baseline but also function as a useful resource to study, analyse and identify signatures characterizing the physiological dispositions of the subjects. Furthermore, they provide insight into the unique features describing the Indian microbiome. The data are open and may be accessed from the European Nucleotide Archive (ENA) portal of the European Bioinformatics Institute (https://www.ebi.ac.uk/ena/data/view/PRJEB25642).

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Motivations of participants in the citizen science of microbiomics: data from the British Gut Project

Cited by 18 publications

References 17 publications

The feasibility of using citizens to segment anatomy from medical images: Accuracy and motivation

The feasibility of using citizens to segment anatomy from medical images: Accuracy and motivation

How Does the Diversity of Divers Affect the Design of Citizen Science Projects?

LogMPIE, pan-India profiling of the human gut microbiome using 16S rRNA sequencing

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