Developing the Foundations of Collaborative Self-Reflection
For my doctoral dissertation, I am investigating the role of collaboration in self-reflection. Through a variety of studies, I unpack the process and characteristics of collaborative self-reflection and discuss how technology can facilitate this process.
Project Overview
Self-reflection is a crucial mental health tool, often used in therapies like CBT to increase self-awareness and reduce symptoms of depression and anxiety. Traditionally, it's viewed as an individual activity, like journaling or meditation. However, collaborations (like talking to a friend!) often help people self-reflect. To better understand collaborative self-reflection, I conducted a multi-phase project to explore how people interact with each other during the self-reflection. This knowledge will help us design self-reflection technologies.
My Role
I spearheaded this project, from planning and study design to disseminating the findings. My responsibilities included:
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Reviewing the literature
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Writing and submitting the IRB
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Developing the study protocol and interview guides
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Recruiting and scheduling participants
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Interviewing participants (remote and in-person)
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Coding and analyzing the data
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Generating insights from data
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Effectively sharing research results
Tools Used: Qualtrics, Microsoft Excel, Miro, Mendeley
The Team
This dissertation work is advised by:
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Madhu Reddy, Ph.D., University of California, Irvine
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Maia Jacobs, Ph.D., Northwestern University
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Darren Gergle, Ph.D., Northwestern University
Research Process and Approach
To understand the collaborative aspects of self-reflection, I planned and executed three different studies:
Review of Studies on Self-Reflection
I started this project with a formal review of the literature. This allowed me to understand what research has already been done and identify gaps in the literature that my future studies could address. My review of the literature involved a database search that was carefully designed to be comprehensive, a screening process that was thorough and nuanced, and data analysis that was carefully executed to uncover meaningful themes and patterns.
Database Search: Casting a Wide Net
I began by conducting a comprehensive search across two prominent databases. The search terms were carefully chosen to capture studies related to self-reflection and mental health.
Screening: Narrowing Down the Focus
I then screened the articles to determine their relevance to the research questions. I developed clear inclusion and exclusion criteria.
Papers were included if they met two primary criteria:
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Evaluation of a self-reflection tool (e.g., user studies)
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The purpose of reflection was to improve mental health (e.g., clinical symptoms or mood/emotions)
This step resulted in a final corpus of 16 papers and 18 studies (some papers included multiple studies).
Data Extraction and Analysis: Uncovering the Themes
After finalizing the set of studies, I extracted relevant data and conducted a thorough analysis to qualitatively characterize the nature of the studies. Data was extracted from each article across various fields such as mental health context, research setting, metrics, and type of technology and features. I created a spreadsheet to extract the data, classify the information, and identify trends.
Self-Reflection within a Structured Collaborative Setting
The next phase of this project involved an interview study with participants of from a youth-led storytelling program called Mental Health Advocacy Through Storytelling (MHATS). In the program, youth work together to craft stories about personal experiences that have shaped their mental well-being. This is a structured setting that encourages collaborative activities and provides a rich context for understanding how collaboration shapes self-reflection.
Forming a Partnership with the Program
I reached out to the program and expressed interest in partnering with them to understand their program and and learn from what they have implemented. I met with the advisory board and described my goals. I actively listened to their concerns and we brainstormed ways to address the concerns they had with the research plans. We agreed upon a research plan that would answer my research questions as well as questions that the advisory board had for their participants. I met biweekly with the advisory board during data collection to share recruitment updates and preliminary findings.
Planning and Executing Interviews
I developed the interview protocol by identifying the core questions that will answer my research questions. I then develop probing and follow up questions that will help clarify answers and dive deeper into the intended topic. I carefully phrased the questions so that they are clear and non-leading. I pilot-tested the interview guide to ensure that the questions efficiently extract relevant information.
The interviews began with "icebreaker" background questions. The conversation then transitioned to the storytelling process, prompting participants to describe their experiences. The interviews concluded with broader reflections on the program and potential role of technology.
I interviewed 10 participants. The interviews were conducted remotely over Zoom and lasted between 40-60 minutes. The interviews were audio-recorded and transcribed to capture the richness of the conversations and ensure accurate data analysis.
Protecting the Safety of Participants
The study was designed with several ethical safeguards in place to protect participant well-being, given the sensitive nature of the topic. These measures included:
Informed Consent: I informed the participants about the study's purpose and procedures, and their consent was obtained prior to the interviews. I emphasized that participation was voluntary and wouldn't affect their relationship with the program.
Mental Health Training: I completed a training to recognize signs of suicidal ideation and had plans in place to contact professionals if any concerning signs came up during the interview.
Data Anonymization: I took steps to protect participant identities, including removing identifying information from transcripts and avoiding the disclosure of demographic data.
These ethical safeguards were important for protecting the participants and ensuring they felt safe and comfortable.
Analyzing Data and Generating Insights
Through my analysis, I meticulously examined transcripts, identified patterns, and uncovered meaningful conclusions. This process required careful attention to detail, critical thinking, and a deep understanding of the participants' behaviors and need.
I began the analysis by familiarizing myself with the transcripts and highlighting key quotes.
Next, I identified recurring patterns and created a detailed coding scheme, assigning codes to relevant text sections. I continuously refined the coding as I analyzed more data and discussed emerging themes with the research team. I coded the data in Microsoft Excel.
After all transcripts were coded, I reviewed the codes, looked for patterns or trends, and considered differences between participants. I generated insights by explaining the themes and patterns. I also considered the findings with respect to prior knowledge of self-reflection and contemplated how these findings build up previous work. Finally, I consider the practical implications of these findings and how the findings can provide insight into ways in which we build and design technology.
Collaborative Self-Reflection in Daily Life
The final phase of this project involved an interview study with undergraduate students to explore how collaboration impacts their self-reflection in their daily life. To complement my previous study which explored self-reflection in a structured collaborative setting, I wanted to explore how collaborative self-reflection occurred during daily life.
Recruitment: Contacting and Scheduling Participants
I recruited participants through email and flyers. I reached out to leaders of undergraduate programs and asked them to pass along the call for participation. The email and flyer directed participants to complete a screening questionnaire and a short form that I had created to capture demographic information. I then contacted participants who completed the screening questionnaire and met the eligibility criteria to set up a time for the interview.
Planning and Executing Interviews
I developed an interview guide following the same strategy as the previous study (identifying the core questions, developing probing questions, carefully phrasing the questions so that they are clear and non-leading, and pilot-testing the questions). The interview questions focused on understanding when and how participants interact with others while engaging in self-reflection.
Analyzing Data and Generating Insights
I analyzed the interview data following the same steps described above (reviewing transcripts, looking for patterns, developing a coding scheme, iterating and refining the coding scheme with the research team).
I also created journey maps for each participant to understand the nuances of their unique process. I mapped out their interaction points and the channels used for each interaction. I defined the stages of the journey, which helps me understand their emotions, thoughts, and needs during each stage of the self-reflection process.
After creating journey maps for each participant, I generated self-reflection archetypes. While looking at the different journey maps, I noticed that there were several distinct patterns I was seeing. I grouped the participants with similar processes to create archetypes. This allows me to understand the different self-reflection processes and how technology could support each archetype and process.
Insights
My key findings provide insight into how the process of collaborative self-reflection occurs and what the characteristics of this process are.
Four Types of Interactions Support Self-Reflection
My findings show that there are several types of interactions that supported the self-reflector:
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Probing questions (“What did you do after?”)
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Feedback on their interpretation (“Why do you think that?”)
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Advice or an alternative perspective (“Maybe you could try...”)
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Emotional validation (“I would also feel that way.”)
The people collaborating with the self-reflector would phrase their responses and interactions so that they were specific and intentionally helpful.
The Role of Information Work
I uncovered three types of information work that people conduct when self-reflecting:
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Collecting information (e.g. considering additional context)
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Sorting information (e.g. reorganizing thoughts to identify themes)
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Interpreting information (e.g. uncovering true feelings)
The interactions and resulting information work are an iterative process.
More Details Coming Soon!
(this work is in progress and under review)