Qualitative and Quantitative Method Integration in Diabetes Communication Research: Applications and Contributions

Abstract

This article is a systematic methodological literature review with the goal of understanding how and why health communication researchers are using mixed methods research (MMR) to better understand interpersonal communication between diabetes patients, their loved ones, and health care professionals. First, we provide a brief overview of MMR, followed by a discussion of the appropriateness of using MMR in health research. We then explain our search procedures for identifying MMR studies about interpersonal diabetes communication and describe our analysis of the identified studies. We then offer a brief, quantitative summary of our findings and provide details of exemplar studies to illustrate the unique value added by using MMR. We conclude the article with a discussion of implications and recommendations for the use of MMR in diabetes communication research.

Keywords

health communication mixed methods research diabetes diabetes communication methodological review qualitative North America Asia

About 1.5 million Americans are diagnosed with diabetes every year, and it is the seventh leading cause of death in America (American Diabetes Association, 2017). The ramifications of the condition are immense: Diabetes reduces life expectancy by up to 13 years (Livingstone et al., 2015), and average medical expenses of diabetes patients are 2.3 times higher than for those without the diagnosis (American Diabetes Association, 2013). Successful diabetes treatment requires long-term navigation of a complex web of numerical data (glucose level monitoring, blood pressure checks, etc.) and emotional issues (lifestyle changes, confusion, vigilance, etc.), making effective communication between patients, caregivers, and health care providers essential. However, diabetes management—and diabetes-related communication—can be hampered by factors such as stigma-based social isolation (Schabert, Browne, Mosely, & Speight, 2013) and poor functional health literacy (Schillinger, Bindman, Wang, Stewart, & Piette, 2004), so it is important to fully understand the unique communication preferences, needs, and challenges of diabetes patients.

Increasingly, researchers are conducting mixed methods research (MMR)—that is, employing both qualitative and quantitative methods in the same study in an intentional and integrated way—which has led to important discoveries about how communication affects the health and well-being of patients with diabetes. Using MMR to study communication about diabetes is particularly appropriate, as the diabetes experience is different for people of various ages, socioeconomic statuses, and cultures, and these complexities call for equally complex research methods, such as MMR, to more fully capture the nuances of myriad divergent experiences.

The purpose of this methodological review is to understand how and why researchers use MMR to better understand communication between patients with diabetes, their loved ones, and their health care professionals. First, we offer a brief discussion of the appropriateness for using MMR in the study of interpersonal diabetes communication. We then describe our analysis of 20 MMR studies we identified in this field and provide a quantitative summary of results. We describe four exemplar studies to illustrate key features of MMR studies and highlight the unique value added by using MMR. We conclude by proposing recommendations for the use of MMR in the field of diabetes communication in particular, but note the recommendations may be relevant to health communication research in general.

Overview of MMR

Since the study of MMR gained traction in the 1980s, scholars have supported various approaches in an attempt to standardize and promote the practice. Plano Clark and Ivankova (2016) state that MMR is still experiencing “a development process complete with growing pains and many advances” (p. 13), and there is ongoing debate about what parameters to place on MMR studies. Generally, the minimum criterion for MMR is the collection, analysis, and purposeful integration of both qualitative and quantitative data. To ensure an MMR study is taking full advantage of both methods, several specific study rationales, designs, and data integration processes have been proposed and widely adopted, as summarized in Mixed Methods Research: A Guide to the Field (Plano Clark & Ivankova, 2016).

An important first step in conducting an MMR study is clarifying the reason for using MMR. Several MMR rationale typologies exist, though most include these five common rationales: off-setting weaknesses, complementarity, development, triangulation, and social justice (Plano Clark & Ivankova, 2016). Beyond rationales, scholars have also proposed that both qualitative and quantitative data should be collected in an intentional, planned order that best answers the overall research question. To that end, many recent publications have endorsed three basic MMR study designs: convergent, sequential exploratory, and sequential explanatory (Creswell & Plano Clark, 2018; Plano Clark & Ivankova, 2016). Although not always explicitly stated by researchers, the emphasis, or priority, in an MMR study may be placed on the quantitative strand, qualitative strand, or shared equally across both methods; the priority is often driven by the research purpose and can emerge throughout the study implementation to accommodate new information or evolving research questions (Creswell & Plano Clark, 2018). Beyond intentional designs that collect both qualitative and quantitative data, true MMR integrates results from both strands in a meaningful way (Teddlie & Tashakkori, 2006), rather than merely allowing the data sets to cohabitate within a single publication or quantifying qualitative results (Sale, Lohfeld, & Brazil, 2002). Four common integration approaches include merging, building, connecting, and embedding (Fetters, Curry, & Creswell, 2013). The final hallmark of MMR is that it must contribute to inferences that would have been impossible in a single-method study (Johnson & Onwuegbuzie, 2004). Due to the thoughtful, dynamic process of MMR studies, inferences arising from such studies are often more nuanced and deeper than those emerging from single-method studies.

One critique of MMR is that by blending qualitative (i.e., inductive) and quantitative (i.e., deductive) methods, researchers inappropriately combine research paradigms that should not be mixed—an opinion referred to as the “incompatibility thesis” (K. R. Howe, 1988). However, MMR scholars have rejected the idea that paradigms are mutually exclusive: K. R. Howe (1988) asserts that the methodological differences of these paradigms are “often blown out of proportion,” and that “having more than one set of tools is useful” (p. 15), whereas Kristine Florczak (2014), RN and PhD, says that MMR is appropriate for researchers who believe that “dogmatic paradigms impede progress. . . and that all types of knowledge should be brought to bear in the goal of understanding a phenomenon” (p. 281).

The Current Investigation

Scholars have advocated for more—and more systematic—MMR in health research. In 1998, Morgan observed that “Given all the factors that affect virtually every aspect of health and illness, it is easy to appreciate the different strengths that different methods have to offer” (p. 362), and nearly two decades later, he again called for more mixed methods studies within health research (Morgan, 2015). In this spirit, we conducted a systematic methodological literature review of MMR around interpersonal diabetes communication. Our two specific goals were to first understand how and why researchers are using MMR to better understand communication between diabetes patients, their loved ones, and their health care professionals. Second, we aimed to highlight exemplary MMR studies, which will inform and inspire health researchers within all disciplines and paradigms. Our review focused on answering one overarching research question:

Research Question 1: How is MMR being used to study interpersonal diabetes-related communication?

The following two subquestions framed our coding and analysis approach:

What rationales, designs, forms of data integration, and types of data collection are used in MMR studies of interpersonal diabetes communication, and are they clearly labeled?

What are the unique contributions of MMR to the study of interpersonal diabetes communication?

Method

Data Collection

We conducted a systematic methodological search for MMR on interpersonal, diabetes-related communication, that is, communication between patients and their health care professionals, fellow patients, or friends and family. See Figure 1 in the Supplemental Material for details on our article search procedures. We searched nine online research databases, as well as consulted Google Scholar, using the search terms “communication,” “diabetes,” and “mixed method*” or “qualitative + quantitative.” After eliminating duplicate articles, studies incorrectly designated as mixed methods, and those regarding communication between providers or the creation of diabetes management tools, we were left with 20 articles that explicitly employed MMR to study interpersonal patient communication about diabetes (see Table 1 in the Supplemental Material).

Data Analysis

Once the search was complete, we conducted a summative content analysis, which involved counting certain factors within the articles, coding for particular ideas and themes, and then comparing the findings to interpret the underlying context (Hsieh & Shannon, 2005). In particular, we coded for the MMR rationale (Plano Clark & Ivankova, 2016), MMR design (Creswell & Plano Clark, 2018), and data integration (Fetters et al., 2013), discussing and coming to agreement over any aspects of articles that were not clearly described or labeled. To capture the value-added inferences derived specifically from the usage of MMR, we made notes about each study’s findings and how mixed methods contributed to those particular insights.

Results

The earliest article in our sample was published in 2007 (see Figure 2 in the Supplemental Material). The majority of studies (n = 15, 75%) were published in the past 8 years, with 2017 being the most common publication year (n = 5, 25%). This upward trajectory mirrors other methodological reviews that found similar MMR publication and funding trends (e.g., Coyle et al., 2016; McKim, 2017).

Based on the coding and analysis of the 20 MMR interpersonal diabetes communication articles in our pool, we present the results relative to each research subquestion in turn.

MMR Rationales

Of the studies in our pool, the two most common rationales were complementarity and triangulation (see Figure 3 in the Supplemental Material). Complementarity, or developing a more complete picture, was noted in 40% (n = 8) of studies, though only two of them explicitly indicated the rationale. Another 40% (n = 8) of studies in the current review used triangulation as their rationale, indicating their intent to directly compare and contrast results from the qualitative and quantitative strands, and in six of those studies, the triangulation rationale was explicitly labeled. Though not clearly labeled by the authors, three studies (15%) used the rationale of off-setting weaknesses. The final study (n = 1, 5%) used development as a rationale, with in-depth interview data used to create a structured questionnaire regarding psychosocial care during routine nurse consultations (van Dijk-de Vries et al., 2016). Note that some authors provided more than one rationale for their study.

MMR Designs

We coded each study for the basic MMR design used and whether it was clearly labeled (see Figure 4 in the Supplemental Material). Overall, only 35% of the studies explicitly stated an MMR design. Most of the studies in our review (n = 16, 80%) used a convergent design; of those, only four were clearly labeled. In convergent studies, also sometimes called concurrent or triangulation studies, qualitative and quantitative data are collected independently of each other (i.e., the analysis of one type of data does not dictate or influence collection of the other type of data), sometimes simultaneously, and then interpreted together during the project’s overall data analysis phase (Creswell & Plano Clark, 2018). Three studies (15%) used a sequential explanatory design, with two clearly labeled. Explanatory designs begin with a quantitative strand and then use a qualitative strand to explain or refine the quantitative results. One study (5%) employed a sequential exploratory design, which was explicitly labeled. Exploratory designs with an initial qualitative strand that is often used to create or inform a quantitative strand—this method is best used when researchers have research questions but not hypotheses and are not entirely sure what direction the study will ultimately take.

Integration

Consistent with common parameters of MMR designs, the 16 convergent studies used a merging approach to integration, in that they brought the qualitative and quantitative strands together during their analysis or interpretation. The three explanatory studies used three different integration approaches. Lee et al. (2015) integrated by building from their initial quantitative strand to their follow-up qualitative strand. C. J. Howe, Cipher, LeFlore, and Lipman (2015) employed a connecting integration strategy, using the results from the initial quantitative strand to guide their sampling decisions for the follow-up qualitative strand. Shawe, Smith, and Stephenson (2011) also used a connecting strategy, but because they also merged the qualitative and quantitative strands, their approach is characterized as embedding, which reflects the multiple types of integration. The sole sequential exploratory study in our pool used a building strategy to integrate their initial qualitative strand with their follow-up quantitative strand (van Dijk-de Vries et al., 2016).

Data Collection Methods

We coded each study for the type of qualitative and quantitative data collection methods. Several studies used more than one data collection method per strand; hence, the percentages of our analyses of data collection sum to more than 100%. In terms of qualitative data collection, the majority of studies (n = 13, 65%) used interviews. Four studies (20%) used audio recordings of patient–provider interactions, four (20%) employed focus groups, and two (10%) used questionnaires with open-ended survey questions. For quantitative data collection, most studies (n = 16, 80%) used questionnaires/surveys, though four (20%) used biomedical data from patient charts, and one (5%) used interviews with closed-ended questions.

Exemplars

To illustrate the power that MMR has to meaningfully contribute to the field of health research in general, and diabetes-related health communication in particular, we selected four exemplar articles to highlight in detail. The authors of each of these articles have explicitly labeled both the MMR design and rationale, mentioned how qualitative and quantitative data were integrated, and presented unique inferences that only MMR could have helped them achieve. Organized chronologically, these examples highlight the unique value created by carefully integrating qualitative and quantitative methods.

Communication Workshop for Nurses

In our first exemplar, Latter et al. (2010) examined the effectiveness of a new, patient-centered communication workshop for nurses who are qualified to prescribe medication and regularly do so for diabetes patients in the United Kingdom. The authors explicitly labeled the design as mixed methods concurrent triangulation, which, as mentioned previously, is a synonym for a convergent design. Participants (n = 14) were interviewed twice—1 month and 6 months after the workshops—which provided the qualitative data for the study. Quantitative data came from coding audio-recorded patient consultations before and after the workshop, which were then analyzed statistically using the MEDICODE analysis tool. Quantitative results showed an increase in nurse–patient conversation about medication concerns and patient-initiated questions about medications—both of which imply that the intervention encouraged a change in dynamic for nurse–patient interactions. The qualitative findings revealed a prominent theme of nurses paying more attention to patients’ beliefs about diabetes and medications, and employing more patient-centered communication, post-workshop. Based on these findings, the authors suggested that the intervention should be modified to promote nurses’ confidence and self-efficacy, and encouraged clinics to create more supportive contexts for nurse–patient interactions (such as allowing more time for patient discussions or encouraging more colleague support for patient-based care).

Diabetes and Contraception Choices

Our second exemplar presents the results from Phases 2 and 3 of a three-phase, mixed methods study. Phase 1 of the study was a quantitative, retrospective study of patient data regarding hormonal contraception use for women with type 1 or type 2 diabetes (Shawe, Mulnier, Nicholls, & Lawrenson, 2008). In Phases 2 and 3, Shawe et al. (2011) used and explicitly labeled a sequential explanatory design in their study of contraception-related knowledge and behavior of women with diabetes. First, researchers collected questionnaires from 107 women with diabetes, asking about demographics, existing medical conditions, main method of contraception, and where they sought contraception advice. The researchers used results from the quantitative survey to guide their sampling decisions for the follow-up qualitative strand. By reviewing respondents’ age, obstetric history, ethnicity, and use and method of contraception, the researchers purposively sampled 16 survey respondents for semi-structured interviews that followed up on their attitudes, knowledge, and use of contraception, as well as pregnancy and preconception care. In addition to connecting the quantitative strand to the qualitative strand through participant selection, this study integrated qualitative and quantitative strands by directly comparing their findings (labeled as triangulation) to understand this topic from different angles. For example, six women interviewed had reported on the survey that they used natural family planning for contraception, but none of the 16 interviewees had ever received training on natural family planning methods. Furthermore, separate interviews with diabetes specialists indicated that many do not feel comfortable providing contraceptive information and instead assume patients speak with general practitioners about it. However, one-third of patient survey respondents said they had not received contraceptive advice in the past year from any health professional. By triangulating the mixed methods data in this way, the researchers identified a “worrying communication gap” (p. 357) and made several specific recommendations, including that health professionals and patients should update their understanding of hormone-based contraception and its safety for women with diabetes, and that diabetes specialists should be trained to educate women about their contraceptive options, rather than relying solely on general practitioners to broach the subject.

Parents’ Health Literacy and Patient Satisfaction

Our third exemplar also used a sequential explanatory design. C. J. Howe et al. (2015) studied how the health literacy of parents of children with juvenile diabetes influences communication during their child’s medical encounters. These authors specifically labeled their study as mixed methods, saying that they intended “the quantitative and qualitative data sets would be complementary to more fully explain the communication processes” in question (p. 52). Researchers collected 162 surveys from parents exploring the potential relationship between the quality of communication during medical visits and their health literacy. A subsample of participants with adequate-to-low health literacy (n = 24) were purposively selected to complete semi-structured interviews to further understand upon that population’s communication needs and preferences expressed through the survey. The quantitative data indicated that health literacy did not significantly affect parents’ satisfaction with provider communication, but the qualitative data—somewhat counterintuitively—showed that parents with low health literacy were more likely to report satisfying provider communication around explanations of diabetes condition and care. The authors note that one possible explanation for these seemingly contradictory results could be that parents with medium health literacy had higher expectations of diabetes educators and are more critical of patient–provider communication, whereas those with low health literacy may feel shame or stigma during clinical interactions, leading them to blame themselves for poor patient–provider communication. Ultimately, by analyzing both qualitative and quantitative data together, these researchers determined that parents with low health literacy may benefit more from a learner-driven diabetes curriculum that adapts to their pace.

Pakistani Patients’ Satisfaction With Physician Interactions

Our final exemplar, by Jalil, Zakar, Zakar, and Fischer (2017), sought to understand the connection between the satisfaction of Pakistani diabetes patients and their physicians’ technical expertise, interpersonal aspects, communication, time devoted to consultations, and access/availability. The study also explored the impact of various social demographics (gender, education level, etc.) on patient satisfaction. Using an explicitly labeled convergent design, the research team conducted structured, face-to-face interviews with patients from a large outpatient diabetes clinic in Pakistan. Participants were asked 37 closed-ended questions with scaled answers to measure their perception of each of the five physician factors and overall patient satisfaction and were prompted to provide qualitative comments about their interactions with their physician. Nearly 1,100 patients completed the questionnaire portion of the interview, with 186 also providing qualitative comments. Quantitative data showed that less educated and unemployed patients were more likely to be highly satisfied with their physicians than well-educated, employed patients. Paradoxically, the open-ended portion of the interview (for which the majority of participants, 120, were illiterate) yielded comments about long wait time and disrespectful physician behavior, such as doctors taking phone calls during the appointment. Data triangulation revealed that less educated patients admitted during the open-ended portion of the interview that their satisfaction is mostly related to the physician’s ability to successfully treat them, not on the physician’s behavior; illiterate patients felt vulnerable during clinic visits because of a lack of respect from doctors, a lack of alternative clinics, and a sense of discrimination. Therefore, researchers determined that these patients’ satisfaction was influenced by “the absence of alternative source of consultation, tolerance of disrespect, and affordability” (Jalil et al., 2017, p. 11). Using MMR for this study allowed researchers to better understand patients’ complex perceptions of medical visits and make several specific recommendations for improvements, such as tolerance training for physicians dealing with illiterate or poor patients and educating patients of their rights to privacy and respect.

Discussion and Recommendations

The number of MMR studies published related to interpersonal diabetes communication has increased consistently since 2007—growth that is consistent with other health and social science disciplines (Plano Clark, 2010). The extant literature we reviewed demonstrates the unique value that MMR can bring to this particular topic, by creating inferences beyond what would have been contributed by mono-method studies and by focusing on populations with unique needs that may not have been easily addressed with traditional mono-methods. For example, this review included the following articles: (a) a study that used audio recordings of patient–provider visits, along with quantitative questionnaire data, to determine a connection between African American patients’ health literacy and the perceived balance of power between patient and providers (Arthur et al., 2009); (b) a research team who used interviews and questionnaires to advocate for clearer communication with, and more support for, foreign-born diabetes patients, to alleviate the increased social isolation that often results from a diabetes diagnosis (Berterö & Hjelm, 2010); and (c) a study in which analysis of focus group transcripts alongside glucose monitor data indicated the need for better education for Muslims with diabetes who fast during Ramadan (Lee et al., 2015). See Table 2 in the Supplemental Material for the unique inferences in interpersonal diabetes communication created by using MMR across all studies in our pool. Based on the findings in this review, we propose several recommendations for conducting MMR in the field of health communication research.

Recommendation 1: Be Clear How We Define “MMR”

According to Creswell, Fetters, and Ivankova (2004), MMR requires more than simply collecting both qualitative and quantitative data; the real hallmark of MMR is that the data are “integrated, related, or mixed at some stage of the research process” (p. 7). There is an ample body of work in which researchers conduct a two-phase study, collecting both qualitative and quantitative data on the same topic, but neglect to integrate them in a meaningful way. There are also examples of studies where only one form of data is collected, but is transformed into another form. Although these types of studies may be classified as MMR, they do not fulfill the comprehensive view advocated for by leading MMR scholars. We encourage health researchers to be aware of existing MMR conventions to ensure they are conducting “true” MMR that leads to inferences unavailable via other means.

Recommendation 2: Clearly Label MMR Rationales and Designs

The desire for researchers to explicitly label MMR rationales and designs is not a novel one: more than a decade ago, Miller and Fredericks (2006) lamented the use of “vague rationales” (p. 569) in their review of MMR in educational evaluation research. As noted in Table 1 in the Supplemental Material, only about half of the studies included in the current review explicitly labeled their MMR rationales or designs. Not only is this challenging for those who are unfamiliar with MMR, it complicates analysis of the content within these studies, and it does not facilitate the continued use of MMR. When researchers clearly explain when and how they collected, analyzed, and integrated qualitative and quantitative data within the same study—and why they made those decisions—their results will be easier for everyone to understand, evaluate, and replicate. Furthermore, explicitly labeling an MMR rationale or design implies that researchers understand and intentionally chose MMR for their study, which relates to Recommendation 1, above.

Recommendation 3: Undertake More Sequential Studies

The clear majority (n = 16, 80%) of studies in our review used a convergent design, wherein qualitative and quantitative data were collected concurrently. Although this approach is valid and useful in certain situations (particularly those in which the target audience and research problem are clearly envisioned before the study begins), the vast topic of “health” begs for more sequential MMR studies, particularly more exploratory designs, as there is still so much we do not understand about wellness, treatment, illness prevention, and effective health communication. Just as the development of medical treatments and cures requires a pioneering spirit of trial and error, creating more effective interventions necessitates that scholars admit that sometimes, we are not entirely sure what we are looking for when we begin the search.

Recommendation 4: Continue Interdisciplinary Partnerships in MMR

Because appropriate collection and analysis of qualitative and quantitative data is vital to MMR, collaborative teams of researchers from various disciplines, and with different research strengths, can produce stronger studies. We found evidence of such interdisciplinary collaboration in several of the MMR studies included in our review, which is promising. In addition, researchers should make a point to collaborate specifically with communication scholars, because effective and appropriate communication is a key ingredient for success of public health campaigns, health literacy programs, patient satisfaction initiatives, and tailored health interventions. As Parrott (2004) notes, health communication scholars offer expertise in areas such as privacy, disclosure, and stigma—all factors that are incredibly important to consider when attempting to help a patient manage a chronic illness.

If health researchers follow these recommendations, future scholars and care providers will have more thorough inferences on which to base their care decisions, and therefore, the quality of research studies—and patients’ well-being—will ultimately improve. There is plenty of room for more MMR in the field of health research, and there is potential for such studies to contribute important knowledge to our shared understanding of a topic that affects millions of patients, their loved ones, and their health care providers.

Supplemental Material

Voorhees_and_Howell_Smith_-_Interpersonal_Communication_About_Diabetes_MMR_-_Supplemental_Material_v2 – Supplemental material for Qualitative and Quantitative Method Integration in Diabetes Communication Research: Applications and Contributions

Supplemental material, Voorhees_and_Howell_Smith_-_Interpersonal_Communication_About_Diabetes_MMR_-_Supplemental_Material_v2 for Qualitative and Quantitative Method Integration in Diabetes Communication Research: Applications and Contributions by Heather L. Voorhees and Michelle C. Howell Smith in Qualitative Health Research

Footnotes

Authors’ Note

Heather L. Voorhees is also affiliated with University of Texas at Austin, Austin, Texas, USA.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Heather L. Voorhees

Supplemental Material

Supplemental Material for this article is available online at . Please enter the article’s DOI, located at the top right-hand corner of this article in the search bar, and click on the file folder icon to view.

Author Biographies

Heather L. Voorhees University of Nebraska-Lincoln is a post-doctoral fellow at the Center for Health Communication at the University of Texas at Austin.

Michelle Howell Smith is a research assistant professor and lecturer for mixed methods research at the University of Nebraska-Lincoln, Nebraska, US.

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Supplementary Material

Please find the following supplemental material available below.

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