Keating-Memorial-research

Documentation of the CBPPlab research on personal science regarding the Open Humans Keating Memorial project

View the Project on GitHub PeerProducedResearch/Keating-Memorial-research

PROTOCOL OF RESEARCH: The impact of peer-support on self-research and citizen science projects

Table of Contents

Copy of document submitted for CRI institutional review board (IRB) - Sent on 12/10/2020; accepted on 22/10/2020.

Image

Organisation responsible for the research Name and contact information of the researcher conducting the study
The Center for Research and Interdisciplinarity (CRI)
8bis Rue Charles V, 75004 Paris, France
Tel: 01 44 41 25 27
Responsible for research: Bastian Greshake Tzovaras
Function(or Position): CRI Research fellow (INSERM U1284)
Work address: 8bis Rue Charles V, 75004 Paris, The centre for Research and Interdisciplinarity(CRI), 2nd floor, office 2.16
Tel: +33 766752149
Email: bastian.greshake-tzovaras@cri-paris.org

Typology of research

Required fields Project characteristics
(1) Prospective / retrospective The study is prospective. The study will take place upon IRB approval until the end of 2022
(2) Nature of the research Group study
(3) Genetic study No
(4) Specific sampling for research Semi-structured interviews with participants, participant-observation
(5) Constitution of a biological collection No
(6) Use of an already assembled collection of biological samples No
(7) Not applicable
(8) CCTIRS / CNIL Our DPO point of contact at CRI is Lionel Deveaux lionel.deveaux@cri-paris.org
(9) Products of human origin No

Abstract

“Citizen science” describes the practice of scientific research that is conducted in part or completely by amateurs or non-professional researchers, often in groups or communities. A highly related practice and subdomain of citizen science is that of “personal science”, which describes research fully conducted by an individual to understand a phenomenon, commonly an aspect of their own lives - e.g. their health, habits or behavior. Personal science, as a form participant-lead research, constitutes a growing movement around the exploration of personal health questions using self-collected data, in which individuals develop their own research projects mainly to learn about themselves. Despite its growing popularity, there are little support frameworks to enable individuals to successfully perform their self-research, nor evidence on how it can relate or contribute to other paradigms of open collaboration. We aim to create a better understanding of the interactions, principles and motivations that drive participant-led research within the space of citizen and personal science, to lay the groundwork for potential future improvements of such support frameworks.

In particular we are interested in the following questions that we want to answer: (1) What are the current barriers and opportunities for enabling personal science processes through open communities of practice? (2) What is the role of peer-to-peer support among self-researchers to generate relevant insights from their research projects? (3) What are the types of individual and community learning processes that take place? (4) What are intrinsic and extrinsic motivations for participating in the different stages of personal research among peers?

To explore these questions we will work with citizen scientists and people performing personal science within the framework of the Open Humans system and the Quantified Self community. These communities have thousands of members and provide citizen scientists and self-researchers with a digital infrastructure (e.g. online forums) as well as facilitated interactions among them (e.g. weekly virtual meeting space), providing an ideal community to answer our research questions. To collect relevant data in this early exploratory phase we will use the qualitative methods of semi-structured interviews with community members alongside participant observation techniques at the virtual meeting spaces to gain insights on how personal science is being performed and the community dynamics present. This will allow us to develop a wider comprehensive analytical approach that describes and reflects motivations, as well as the different interaction dynamics that are taking place in relation to shared processes and principles.

Introduction

Citizen science is currently a broad and diverse research practice where members of the public and non-professional scientists collaborate with professional scientists to conduct scientific research, usually aided by Information and Communication Technologies (ICT) and other digital tools (Bonney et al., 2019). As a still emergent and evolving phenomena, citizen science projects to date respond to different typologies and classifications, depending on the type of interaction they articulate: from those in which citizen researchers are trained only for basic data collection tasks, to other participatory models in which amateur researchers can also collaborate in problem definition, data collection and analysis (Haklay, 2013). This later perspective emphasizes the potential of citizens to deal actively with questions that are relevant to their lives (Irwin, 2015), and also connects to key issues of engagement, learning and knowledge creation processes (Jennett et al., 2016).

Personal science (or personal research) is a specific type of participatory citizen science (Heyen, 2016), which can be defined as the practice of using empirical methods to explore personal questions (Wolf & De Groot, 2020). It covers activities and practices for science-based production of knowledge initiated or operated by citizens or laypeople, usually in relation to their own personal health (Heyen & Dickel, 2019). Personal science has its origins in the long tradition of self-experimentation, especially in the medical sciences (Neuringer, 1981), as well as in connection with new approaches to participant-led research (Vayena et al., 2016). Personal science is characterised by individuals performing self-tracking activities, usually aided by digital tools, for the permanent gathering and evaluation of self-related data in their daily life (Heyen, 2020). Usually coordinated and articulating peer support through specific online communities of practice, like Open Humans (Greshake Tzovaras et al., 2019) or Quantified Self (Lupton, 2016), self-tracking data is generated via wearables and other methods and analyzed regularly (Grant & Wolf, 2019). Often data is uploaded and shared via these web platforms, open for reuse and for group discussions regarding the possible consequences for the person’s own health or daily behavior (Pantzar & Ruckenstein, 2017). Some recent research on Open Humans has focused on the motivations and ethical oversight of personal data sharing (Fadda et al., 2018), but not on the personal science practices.

Recently various topics related to personal science have been studied in diverse depth, such as questions of project governance (Grant & Wolf, 2019), the management of self-generated data (Hall, 2014) or new conceptual models to understand the phenomenon (Wolf & De Groot, 2020). However, there is still little literature and systematic studies about other key factors that characterize this type of participant-lead research, especially in connection with advances in open online collaboration and citizen science. For this, it is necessary to explore in greater depth key factors of participation and collaboration related to the motivations and expectations of self-researchers, the learning dynamics and knowledge sharing processes they generate, their group dynamics and the facilitation processes and infrastructure technology in which they participate.

Details of the project

This study aims to create a better understanding of how both individual personal science projects, as well as group citizen science projects that come out of personal science ideas, are performed by individuals, with the goal to understand the interactions, principles and motivations that drive participant-led research within the space of citizen science and personal research.

We focus on three aspects of personal/citizen science: (1) the individual and their motivations and learning processes, (2) the interactions between individuals and group dynamics, (3) the role of technological infrastructure.

Aim 1: Understanding individual processes when doing personal/citizen science

Research Question: We want to get a basic understanding of what individuals learn when participating in personal science and citizen science and what their motivations are for engaging in these activities.

Aim 2: Understanding interactions between self-researchers and group dynamics

Research Question: As part of their engagement with personal science individuals frequently interact with other community members. We want to understand how those interactions are experienced by people engaged in personal science and how these group dynamics shape personal science done by individuals.

Aim 3: Understanding the role of technology and technological infrastructure

Research Question: As part of their engagement with personal science individuals frequently interact with other community members. We want to understand how community interactions are experienced through technology by people engaged in personal science and how these group dynamics shape personal science done by individuals.

Evaluation criteria

We will collect via semi-structured interviewing specific questions and topics related to self-researchers activity, motivations, learnings and digital interactions. Although the interviewer will have some discretion about the order in which questions will be asked, these will be standardized and probes would be provided to ensure that the interviews cover the correct issues. The majority of questions will be descriptive, providing a narrative based on how self-researchers describe things, additionally providing insights or suggesting new areas for query that we might not have previously considered (according to repeated phrases, concrete examples, personal research experiences and specific language questions).

Transcribed interviews as primary data will be coded for text analysis based on specific categories about self-researcher’s own practices, beliefs and opinions. Codification will be done by two researchers: one who will conduct the interviews and another one who will not participate in the interviews. Afterwards each category will be tested for reliability to check the level of agreement between the two codifiers. The overall reliability should be higher than the 0.80 (alpha) index recommended by Krippendorff (2018), which enables solid and fundamental conclusions to be drawn beyond mere speculation.

Methodology

This is an interdisciplinary, observational, descriptive and analytic cohort study. A semi-structured interview protocol will be used to address a series of questions regarding participation and collaboration in personal science. A special emphasis will be put on motivations and learning processes as a measure of how collaboration takes place and relates to knowledge generation in specific projects and communities of practice related to Open Humans and Quantified Self. Finally, this experimental study will be complemented with participant observation through open community calls and discussion forums, to uncover relations between concepts that relate to self-researchers perceptions, roles and attitudes. We expect this methodology to provide a qualitative basis and a useful approach to understand good practices for personal research projects as participatory citizen science. Additionally, analysis from interview results and online participant observation will also inform future research in the same field for additional methods we are considering, like community surveys and action research interventions (separate IRB review will be requested if additional methods are sought to be used in a later study).

Total duration of the study: The research will take place during the autumn of 2020, beginning as soon as possible after IRB approval and no longer than the end of 2021.

Data Storage and Handling: All information and data will be stored using secure data management systems owned by the Center for Research and Interdisciplinarity (CRI). No unauthorized access to data will be given to non-anonymized data. Only the study research staff will have access to identifiable information.

Anonymization and data sharing: Individual information and data will be stored privately and will only be accessible to the study staff. Information and data about participants shared outside the study staff will be de-identified by default. This includes not sharing specific details such that an individual’s identity may be inferred.

Individual participants may be provided an opportunity to opt in to being identified. If the research project plans to disseminate information and data about identified individuals, these individuals will be given a copy of the identified material that will be shared prior to any dissemination outside the study staff and may request its anonymization.

De-identified data will be made available to the scientific community, and will be distributed with any publications that arise from this study.

Compensation: Participants will not be monetarily compensated for their participation in this study. We will provide a report on the study to all participants at the end of the study and make it also publicly available.

Methodology I: Participant observation in community forums

Participants will be observed in the following contexts:

Number of subjects: We estimate 20-100 individuals will have interactions that are analyzed by this research, but may analyze data from more individuals (500 or more) via public online forums.

Inclusion criteria and main exclusion criteria: Inclusion criteria: Participation in one or more of these community contexts Exclusion criteria: None

Consent process: The researchers have been ongoing community members in these contexts, and will provide these communities with information about this research project. As this research poses minimal risk and involves no procedures for which consent is normally required outside research, we seek a waiver of individual informed consent.

Methodology II: Semi-structured interviews

Prospective participants will be invited to participate in semi-structured interviews to collect information related to the research questions. These interviews are expected to occur via videochat software and will be recorded with the assent of the participant.

Number of subjects or samples needed In order to draw conclusions from our semi structured interviews we expect to need a minimum number of 6-12 participants that consent to be interviewed, but we are prepared to interview up to 25 people. Given that the Open Humans and Quantified Self communities have thousands of members, we expect to easily hit this target.

Inclusion criteria and main exclusion criteria Inclusion criteria (any): Has conducted or attempted to conduct a personal science project / Has participated in public forums, community videochats, and/or online chatrooms about personal science projects Main exclusion criteria: None

Consent Process: Prospective participants in interviews will be provided with an information form explaining the details of the study and their role in it, providing information that participation in the interview provides consent. Participants will be informed that they can withdraw from the study at any point, and may request for all information they provided to be deleted, without penalty. Participants will be encouraged to ask any questions they may have prior to participating in interviews.

Funding

This project is funded by the Center for Research and Interdisciplinarity (CRI) as part of the CRI long term research fellowships: https://projects.cri-paris.org/projects/K92ifSPw/summary

References

  1. Bonney, R., Cooper, C. B., Dickinson, J., Kelling, S., Phillips, T., Rosenberg, K. V., & Shirk, J. (2009). Citizen science: a developing tool for expanding science knowledge and scientific literacy. BioScience, 59(11), 977-984.
  2. Fadda, M., Jobin, A., Blasimme, A., Tzovaras, B. G., Ball, M. P., & Vayena, E. (2018). User Perspectives of a Web-Based Data-Sharing Platform (Open Humans) on Ethical Oversight in Participant-Led Research: Protocol for a Quantitative Study. JMIR research protocols, 7(11), e10939.
  3. Grant, A., & Wolf, G. (2019) White Paper: Design and Implementation of Participant-Led Research in the Quantified Self Community. Retrieved from https://quantifiedself.com/white-paper-design-and-implementation-of-participant-led-research/
  4. Greshake Tzovaras B., Angrist M., Arvai K., Dulaney M., Estrada-Galiñanes V., Gunderson B, Head T., Lewis D., Nov O., Shaer O., Tzovara A., Bobe J., Price Ball M. (2019). Open Humans: A platform for participant-centered research and personal data exploration, GigaScience, 8(6),giz076
  5. Hall, T. S. (2014). The quantified self movement: Legal challenges and benefits of personal biometric data tracking. Akron Intell. Prop. J., 7, 27.
  6. Haklay, M. (2013). Citizen science and volunteered geographic information: Overview and typology of participation. In Crowdsourcing geographic knowledge (pp. 105-122). Springer, Dordrecht.
  7. Heyen, N. B. (2016). Self-tracking as knowledge production: Quantified self between prosumption and citizen science. In Lifelogging (pp. 283-301). Springer VS, Wiesbaden.
  8. Heyen, N. B. (2020). From self-tracking to self-expertise: The production of self-related knowledge by doing personal science. Public Understanding of Science, 29(2), 124-138.
  9. Heyen, N. B., & Dickel, S. (2019). Was ist Personal Health Science?. In Personal Health Science (pp. 1-19). Springer VS, Wiesbaden.
  10. Irwin, A. (2015). Citizen science and scientific citizenship: Same words, different meanings. Science communication today, 2015, 29-38.
  11. Jennett, C., Kloetzer, L., Schneider, D., Iacovides, I., Cox, A., Gold, M., … & Talsi, Y. (2016). Motivations, learning and creativity in online citizen science. Journal of Science Communication, 15(3).
  12. Krippendorff, K. (2018). Content analysis: An introduction to its methodology. Sage publications.
  13. Lupton, D. (2016). The quantified self. John Wiley & Sons.
  14. Neuringer, A. (1981). Self-experimentation: A call for change. Behaviorism, 9(1), 79-94.
  15. Pantzar, M., & Ruckenstein, M. (2017). Living the metrics: Self-tracking and situated objectivity. Digital health, 3, 2055207617712590.
  16. Vayena, E., Brownsword, R., Edwards, S. J., Greshake, B., Kahn, J. P., Ladher, N., … & Rid, A. (2016). Research led by participants: a new social contract for a new kind of research. Journal of Medical Ethics, 42(4), 216-219.
  17. Wolf, G., & De Groot, M. (2020). A Conceptual Framework for Personal Science. Front. Comput. Sci. 2:21.