Understanding Users Information Needs and Collaborative Sensemaking of Microbiome Data

This blog summarizes the research paper “Understanding Users Information Needs and Collaborative Sensemaking of Microbiome Data” by Jennifer Otiono, Monsurat Olaosebikan, Orit Shaer, Mad Ball, and Oded Nov. This paper will be presented at the ACM Conference on Computer-Supported Cooperative Work and Social Computing.

Have you ever thought about your microbiome, the genetic material of all microbes that live on and inside your body, and how it influences your health and wellbeing?

In our paper, we investigated the motivations and information needs of people who discuss microbial information on Reddit. As a social news aggregator and discussion website, Reddit is one of the top most visited websites in the US. We focused on Reddit’s r/HumanMicrobiome — the largest Reddit forum to engage users in discussions related to their microbiome and its health implications.

The goal of our investigation is to inform the design of future interactive tools that will help non-experts to explore and make sense of their microbiome information.

Methodology

In order to gain insight into the information needs and collaborative sense-making practices of r/HumanMicrobiome users, we extracted r/HumanMicrobiome messages and posts from a public database that stores 1.7 billion Reddit posts and comments on Google’s BigQuery service.

We obtained 393 posts and 3,991 comments from r/HumanMicrobiome dated between the inception of the subreddit in June 2017 to November 2018.

We analyzed the posts and comments using a thematic analysis method, which consists of iterative reading and coding of qualitative data, in order to identify themes.

Figure 1: Overview of r/HumanMicrobiome on Reddit

Findings

This is what we found:

Q: Why do people discuss their microbiome on r/HumanMicrobiome?

A: Analyzing comments and posts, we identified three goals for non-experts engaging with microbiome data: 1) Monitoring how a particular health condition affects their microbiome, 2) Improving their microbiome with hopes of alleviating symptoms, and 3) Learning more about the relationship between health and the microbiome. These goals are often not mutually exclusive.

In the words of one user:

“I have MS and want to see if my gut microbiome has been affected. I have found that there are a few direct-to-consumer Gut Microbiome tests, but I’m not convinced they’re useful. Are they?”

Q:What are users’ information needs?

A: Based on the themes emerging in our analysis, we identified seven information needs of non-experts engaging with their microbiome data:

Figure 2: Information needs of non-experts exploring and engaging with their microbiome data.

Q: How do users in this community interact with each other to collaboratively make sense of human microbiome data?

A: We observed three primary modes of collaborative engagement between r/HumanMicrobiome participants:

1) Learning and knowledge sharing — the rapidly evolving scientific knowledge on the microbiome and lack of trust in the knowledge of health care providers further motivates community members to learn from each other by sharing knowledge. In the words of one user: “We are on the edge of science in this sub, because no-one else could help us. We must help each other here.”

2) Exchanging recommendations and advice — users make posts and comments providing recommendations or seeking advice for an individual’s medical conditions or data. For example, “Here’s some more screen-shots, I have

no idea what it all means. It seems like I have more of a lot of different bacteria than most people… am I supposed to lower that somehow?”

3) Sharing symptoms and experiences — users openly share their data, symptoms, and experiences relating to their microbiome and health. For example, “I’d love to chat with you and compare symptoms, I’ve found very few people who suffer from these exact symptoms.”

Our conclusion:

People’s exposure to direct to consumer microbiome data is a new phenomenon, and there are no established best practices for the design of interactive tools for microbiome data exploration and communication. Our findings inform the design of such future tools by advancing our understanding of users’ needs within this personal and often sensitive data context. By analyzing users’ discussion of experiences related to personal microbiome data, we identified information and interaction needs which highlighted how users apply collaborative sense-making of data. We also point to other design implications, including tools for better communication with healthcare providers and symptom-centered sharing and discussion features. Developing tools that enhance the ability of the user to detect and interpret inputs of microbiome information is a challenge we seek to address, and which will expand the knowledge in this area for the HCI and personal informatics communities.