Pictured (left to right): Jaymes Paolo Rombaoa (Research Associate), Baohua Liu (Research Assistant), Dr. Corey Abramson (Consultant), Dr. Martín Sanchez-Jankowski, Catalina Oselio (Research Assistant), Saina Salamati (Research Assistant), and Dr. Saida Heshmati (Primary Investigator)

Ethnography and Qualitative Data Analysis Training

Dr. Sanchez-Jankowski on Day 1 starting off the three-day training.

This October, our team dove into an intensive and comprehensive weekend of training sessions led by two incredible experts: Dr. Martin Sánchez-Jankowski, Professor of Sociology at UC Berkeley, and Dr. Corey M. Abramson, associate Professor of Sociology at Rice University.

Our project will focus on understanding love and well-being from culturally-informed perspectives. We will use ethnography and qualitative data collection to immerse ourselves in the culture and the real-world experiences of people.

From this workshop, we learned about three methods used in ethnography studies: (1) Field Observation, (2) Focus Groups, and (3) 1:1 In-Depth Interviewing.

Field Observation

A major portion of this study will include in-field observations. Through this training, we learned that observing human behavior is not just about how people behave but also the reasonings behind those behaviors within their cultural settings and everyday lives. The workshop included opportunities to practice observations and take notes through various exercises that taught us to look beyond the obvious and reflect on subtle cues that might go unnoticed. We were reminded that our biases can impact how we gather data, so we need to seek out information in an unbiased way and be aware that things may not always go according to our expectations. Also, we learned an important component of observation and research that was highlighted was the importance of recognizing patterns. Overall, the field observation skills we learned in this workshop will be crucial in our data collection in each of the six countries that we travel to.

Discussing key differences between Focus Group and 1:1 Interview questions.

Focus Groups

In addition to field observations, we will obtain data through the use of focus groups in order to gather subjective opinions on love. We learned that the best kind of group structure for our study is a group in which the participants share certain similarities. For example, it would be best to have homogenous groups that include participants from the same age group, gender, socioeconomic status, etc. To have a successful focus group session, it’s vital that the facilitator is prepared and remains flexible. As focus group facilitators, we learned that we need to use neutral language and emphasize that different opinions are important; additionally, to make the participants feel at ease, using active listening and probing questions are great ways to have a successful session.

Dr. Saida Heshmati and the group evaluating interview protocol and questions.

In-Depth Interviews

In this workshop we learned to develop an interview guide for our project. We learned that our core aims as researchers are to elicit narratives and create a space where the participants feel comfortable to have a conversation. We also learned about The Hourglass Structure of interviewing: beginning with general questions to build rapport with the participants, followed by more specific questions that build trust, and ending with participant reflection. In addition to interview guides, we received training on how to prepare for the interview. We learned to have a pre/post-interview checklist, what kind of technology to use, and what “on-tap” questions to prepare for the interview. These probing questions help us get richer and more detailed information.

Dr. Corey Abramson facilitating an introduction to ATLAS.ti

Computational Qualitative Data Analysis

Data doesn’t analyze itself! Dr. Corey Abramson led us through the technical side of our research by providing a thorough introduction to ATLAS.ti, a computational software for qualitative data analysis (QDA) that proves to be ideal for our mixed-methods study. Because of the intense nature of the data we will collect from observation notes, interviews, and focus groups, it is crucial that we organize our data well so that our analyses run as seamlessly as possible to yield accuracy. In our training on ATLAS.ti, we learned how to:

Upload and manage transcripts in ATLAS.ti for accessible, organized data
Create codes to capture key themes and insights from our data

Build networks of codes to visualize relationships between ideas, which helps us to see our data and its influences more clearly and in ways that may not have otherwise been obvious
Use memos to document emerging thoughts during analysis; this provides space for us as researchers to revisit patterns and determine relevance to our study
Leverage machine learning to uncover patterns in the data and links between love and well-being

Now having this hands-on training under our belts, there is further reinforcement that our team is prepared to work both systematically and collaboratively during the data collection phases in each of the countries we travel to. Using ATLAS.ti and computational qualitative data analysis will help us analyze our qualitative data efficiently and gain deeper insights into how love is experienced across an array of contexts and cultures.

Why This Training Matters for Our Project

Given that we aim to understand as it occurs in people’s cultural contexts, mastering ethnographic techniques and complex data analysis tools is essential. The utilization of these techniques will help us make rich observations, analyze our data accurately, and ensure reliable insights into the culture.

We are incredibly grateful for the time and expertise shared by Dr. Sánchez-Jankowski and Dr. Abramson. Their guidance has equipped us with tools and strategies that will be pivotal to the success of our project.

Stay tuned for updates on our progress—there’s so much more to come as we get ready to move forward!