TABLE.

Combining Core Epidemiologic Concepts and Mixed Methods

Epidemiologic Concept	Qualitative Component	Quantitative Component	Mixed-Method Study Design	Examples
Association	Identify potential new causes of disease	Measure and test exposure and outcome in a quantitative phase	Exploratory Sequential	High rates of asthma are observed in students attending schools within the southeast region of a large US city, and the rates cannot be explained by existing risk factors. An epidemiologist’s study begins with qualitative data collection using interviews with various key informants including city epidemiologists, clinicians, school principals, parents, and participant observation with students during the school day. There is a lot of mention about a new food factory that was recently built in that district and a viral social media video has many students consuming the new crunchy snack made by the factory. It seems that the added pollution and a possible food allergen in the snack may be triggering the high rates of asthma. The epidemiologist then tests this hypothesis in a quantitative phase in city schools.
Confounding	Identify confounders or connections between variables	Control for confounders in statistical model	Exploratory Sequential	An epidemiologist is interested in opioid use as pain management in those with fibroids, a very painful disease that is often undiagnosed. She designs a study beginning with in-depth interviews with women diagnosed with fibroids. When coding the interviews for themes, she generates a list of variables that may be related to either the exposure, outcome, or both. These variables, such as social support, previous sexual health education, body positivity, maternal history of menstrual pain may be potential confounders or they may also help describe how confounders in the causal diagram are related to each other. The epidemiologist then builds a directed acyclic graph and decides which variables remain, and then tests it using quantitative methods.
Mediation and Effect modification
	Identify possible mediators or effect modifiers	Examine association between exposure, mediator, modifier, and outcome	Exploratory Sequential	An epidemiologist is interested in knowing why an area of Miami has higher rates of cervical cancer. The exploratory sequential design begins with participant observation and in-depth interviews with Haitian women who predominantly live in that area, which reveals that twalet deba, a culturally mediated feminine hygiene practice, is widespread and many local shops sell products, both natural and synthetic, for twalet deba.34 In collaboration with community partners the epidemiologist begins to think that certain products used in twalet deba may increase the risk of cervical cancer. They then use quantitative methods to test whether any of the intravaginal agents used in twalet deba are effect modifiers for high risk HPV, a precursor for cervical cancer risk.33
	Gain an in-depth perspective of the mediators, or effect modifiers, causal partners	Examine association between exposure, mediator, modifier, and outcome	Explanatory Sequential	An epidemiologist is interested in the high rate of tuberculosis on indigenous population of Colombia.47 He uses quantitative methods to identify gaps in the tuberculosis care cascade and then uses interviews to explore why the gaps in the cascade are there.
	Identify possible mediators, or effect modifiers, causal partners of the main effect	Examine association between exposure, mediator, modifier, and outcome	Convergent	An epidemiologist is interested if a higher socioeconomic status (SES) and body mass index (BMI) are positively associated in a new context and want to explore socio-behavioral variables associated with BMI.48 She quantitatively measures SES, BMI, and other variables such as marital status, number of food market visits using structured questionnaires. She uses multivariate linear regression to confirm that SES is positively associated with BMI. Her collaborator collects qualitative data through participant observation and spends several weeks living and interacting with community members. In addition, he conducts in-depth interviews on food shopping, preparation, presentation, and nutrition perspectives. Families from higher SES tended to live closer to the market, which in turn seemed to lead to a higher number of market visits with an increased consumption of ultra-processed foods. In this community with a high prevalence of undernutrition during childhood, participants showed a preoccupation with hunger, rather than obesity. The qualitative component not only aligns with the quantitative finding that a higher SES is associated with higher BMI, but also provides details on how the exposure and outcome are linked in this particular setting.
Measurement
	Identify constructs and ways to inquiry about them to develop a survey	Use survey results to measure variables	Exploratory Sequential	An epidemiologist wants to measure depression in older adults in a future epidemiologic study. First, to better measure depression, she wants to understand the definition of depression in older adults in contrast to clinical definitions.27 So her collaborators conducts semistructured interviews and asks participants to describe “a person who is depressed.” The qualitative results suggest that traditional measures of depression do not capture loneliness, but it was one of the most salient terms of the definition from older adults. For the subsequent quantitative phase, they develop a survey that measures depression that includes loneliness.
	Explore a variable to complement, expand, contrast how it is measured quantitatively	Measure a variable to complement, expand, contrast how it is measured quantitatively	Convergent	An epidemiologist designs a study to examine the association between discrimination and cardiovascular risk in Black men. He uses an existing questionnaire on discrimination to survey participants. At the same time he knows that the survey may not capture discrimination accurately so he also conducts focus groups with participants.
Selection Bias
	Observe population for characteristics	Measure study sample characteristics	Exploratory Sequential	An epidemiologist is conducting a study of pregnancy associated breast cancer. Her co- investigator observes moms in parks and attends mom groups/activities for moms and babies in the same catchment area for the study. She notices at first there is a good representation of moms in terms of where they were born, but that after 2 weeks, most of the migrant women are no longer attending activities. The study team realizes many of the migrant moms have returned to work and this may affect their ability to keep breastfeeding. She makes sure to recruit moms from different types of work into the study to avoid selecting only moms with jobs that support breastfeeding. She decides to measure work-based policies for family leave and breastfeeding support at baseline to determine if she has selected women with different work-based lactation support. This approach helps identify covariates to measure to assess selection bias.
	Capture diverse perspectives on a variable/topic of study and use these perspectives to classify survey respondents from the QUANT component	Measure variables and compare their distribution by perspectives determined using QUAL methods	Convergent	An epidemiologist is interested in conducting a study of suicide among soldiers. He conducts a case-control study of suicide deaths using military clinical chart review. He also administers survey and focus groups interviews with soldiers and healthcare providers to provide context for associations between identified risk factors.30 To assess selection bias in the survey, the research team could also interview soldiers about substance abuse and identify codes (reasons for substance abuse) and sub codes (chronic pain, mental health, etc). The interviewees also complete the quantitative survey. Then, the epidemiologist classifies interviewees by sub codes and compares the distribution of substance use between these groups and the survey study sample. If the distribution differs between the quantitative sample and any of the qualitative subgroups, there may be selection bias based on what defines that particular subgroup.
Attrition/Lost to Follow-up
	Understand the Wdynamics of the research study, including the study rationale, design, recruitment, retention and role of study personnel, participants, and advocates.	Examine association of exposure and outcome using a cohort design	Convergent/Embedded	An epidemiologist conducts a cohort study looking at the association of socioeconomic status (SES) and early-onset breast cancer risk (<40 years) in Mexican migrants to the United States. She assesses SES using a survey at baseline and follow women for 10 years for breast cancer outcomes. Over those same 10 years an ethnographer follows the study, its participants, and the epidemiologist. In year 7, the ethnographer picks up on a political issue that may affect retention. The university and a prominent local politician are in conflict about gentrification and the politician is dissuading residents from engaging with the university. The epidemiologist and ethnographer hold a town hall to hear the community’s concerns. They also incorporate zip code to account for loss to follow-up in the statistical analysis.
	Interview participants about the characteristics that differed between those lost to follow-up and who stayed on study	Compare baseline characteristics of those lost to follow with those with complete follow-up	Explanatory Sequential	Using the same example as above, an epidemiologist assesses socioeconomic status using a survey at baseline and follow women for 10 years for breast cancer outcomes. When she is creating Table 1 of study participants, she notices those lost to follow-up were more likely to live in a particular zip code. She decides to interview participants who completed follow-up living in that same zip code and come to learn that a local politician urged residents to stop participating in the University’s studies. The interviews help the epidemiologist decide whether those lost to follow-up differ from the overall sample regarding socioeconomic status and how to account for this in the statistical analysis.