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Abstract

The methodological purpose of this article is to generate practical guidance for researchers studying complex phenomena through an adaptive case study-mixed methods (CS-MM) design. We describe CS-MM design adjustments made in response to our rapidly changeable research conditions that make complex phenomena challenging to study. We leverage Guetterman & Fetters’ (2018) CS-MM design recommendations while discussing specific adaptive design practice areas and advancing new insights gleaned from an expanded 21-month timeline when compared with a previous 4-month CS-MM study. We draw upon Mike Fetters’ extensive scholarly contributions while striving to continue his legacy for a better world and embodying Mike’s “kind mentoring” approach in our team-based study of the complex phenomena involving the response to a public health emergency.

Keywords

COVID-19 case study-mixed methods research design complex adaptive system integration public health

Recognizing the inherent complexities of our research settings and adapting the requisite integration of qualitative and quantitative perspectives requires new ways of designing case studies-mixed methods (CS-MM) research. Adaptive design practices represent a departure from implementing predetermined integration procedures because CS-MM researchers assume, from the onset, that their initial plans will adapt to arising conditions. In this work, we draw upon Guetterman and Fetters’ (2018) essential design distinction of CS-MM as case studies nested within mixed methods designs and follow their recommendation to clearly document integration details in our illustrative adaptive practice area descriptions. This documentation is vital to maximize the value of the novel insights derived from the integration within CS-MM research designs. The methodological purpose of this article is to generate practical guidance for researchers navigating and documenting the study of complex phenomena through an adaptive CS-MM research design.

Complex phenomena are perplexing to study because they defy simplistic analyses of cause and effect and involve numerous interrelated and often unknown complex adaptive systems (CASs). That CASs interact with one another in unpredictable and nonlinear ways is well documented as a paradoxical challenge and opportunity (e.g., Lewin, 1993; Weaver, 1948). A growing body of literature elucidates the need for adaptations and re-emphases agility in mixed methods designs (e.g., Creswell & Plano Clark, 2023; Maxwell & Loomis, 2003; Plano & Ivankova, 2016; Poth, 2018). Yet, illustrative guidance for successfully managing the required integration where the whole is greater than the sum of its parts remains a pressing need (Sancartier, 2020).

Key to the novel contribution of this article is the use of the collection of theories known as complexity science for informing the study of complex phenomena using CS-MM designs. Complexity science is increasingly recognized as helpful for mixed methods researchers’ thinking integratively with complexity and research design innovations (e.g., Kallemeyn et al., 2020; Poth, 2018). Focusing on attending to three key concepts of CASs—emergence, interdependence, and adaptation—helps CS-MM researchers navigate the rapidly changeable conditions surrounding complex phenomena. In our discussions of six specific adaptive CS-MM design practice areas, we leverage Guetterman and Fetters' (2018) CS-MM design recommendations (see Table 1) and examine new insights gleaned from comparing an expanded 21-month timeline of the study of the public health response to COVID-19 in Alberta with a previous 4-month CS-MM study (for full description; see Poth et al., 2021). We recognize Mike Fetters’ extensive scholarly contributions (Creswell & Johnson, 2023), strive to continue his legacy for a better world and embody Mike’s “kind mentoring” approach in our team-based study of the complex phenomena involving the response to a public health emergency.

Table 1.

Adaptive Case Study-Mixed Methods (CS-MM) Research Practice Areas Mapped Onto Design Recommendations.

Adaptive CS-MM Research Practice Areas	Four Design Recommendations for CS-MM Research (Guetterman & Fetters, 2018, p. 915)
Case conditions for integration	—
Case purposes for integration	Determine a rationale for selecting the case or multiple cases
Case boundaries for integration	Describe the case and the boundaries—what is and what is not included
Case expertise for integration	—
Case procedures for integration	Carefully consider your approach to mixed methods integration
Case evidence for integration	Clearly report integrated mixed methods results

Leveraging Case Study-Mixed Methods Design Recommendations for Studies of Complex Adaptive Systems

Guetterman and Fetterss’ (2018) review and discussion of mixed methods case studies published between 2011 and 2016 yielded significant contributions, culminating in their advancement of eight design recommendations. Their description of four illustrative examples adeptly highlighted the design options available to researchers that can “help investigators better harness the value added from mixed methods case studies” (p. 912). Key among the design options involved distinguishing two approaches to the requisite integration of qualitative and quantitative research within a case study design. Guetterman and Fetters (2018) then drew attention to the “general paucity of mixed methods features” (p. 913) revealed by their review and pointed to recent mixed methods research practices such as the necessity of a detailed systematic integration focus within the mixed methods research design and the use of joint displays to provide evidence of integrated outcomes. Of particular note for our current discussion focused on adaptive mixed methods case study practices, Guetterman and Fetters (2018) discussed the need for adaptations of case study or mixed methods approaches as a key consideration and specified conventional practices relating to levels of analysis, sampling, and multiple data sources. In our current work, we found four of Guetterman and Fetters’ (2018) recommendations for designing mixed methods case studies (i.e., rationales, boundaries, approaches, and reporting) helpful for discussing our adaptive CS-MM research practice areas.

In Table 1, we demonstrate our mapping of those four design recommendations (Guetterman & Fetters, 2018) onto four adaptive practices initially advanced by Poth (2018) and adapted for our current purposes. Note that an additional two adaptive practice areas (i.e., conditions and expertise) were not highlighted by Guetterman and Fetters’ (2018) review and, thus, beyond the scope of the design recommendations and not discussed. This article examines the extent to which Guetterman and Fetters’ (2018) recommendations are applicable for mixed methods-case studies of complex phenomena, a topic that has not been previously discussed.

Case Conditions for Integration

We begin with the question: What study conditions indicate a complex phenomenon that benefits from a CS-MM design? Our initial conceptualization of the study phenomenon, the public health response to the COVID-19 pandemic as a CAS, provided a first step towards recognizing and capturing its inherent complexity. In the four-month onset CS-MM study (March – June 2020), we used the three key concepts of a CAS to describe our emerging understandings of the public health response to the global COVID-19 pandemic as an unprecedented and unpredictable disruption to the ways people around the world lived their daily lives and interacted with one another, including in the Canadian province of Alberta (for full description, see Poth et al., 2021). During the 21-month extended timeline CS-MM study (March 2020 – December 2021), we generated a more complex representation of how the public health response (a) evolved as an emergent property in response to new understandings about the virus characteristics, for example, transmission rates and variants, (b) influenced and was influenced by various interdependent components, for example, informing and regulating, and (c) adapted to reflect up-to-date information, for example, public health measures and community behavior (see Figure 1). In the sections that follow, we describe how the case conditions met what Poth (2018) describes as the five necessary research conditions for high complexity that, in turn, required adaptive mixed methods research practices across five integration-focused areas of purposes, boundaries, expertise, procedures, and evidence.

Figure 1.

Interdependent components of public health communication in response to the COVID-19 Pandemic (December 2021).

Case Purpose for Integration

We ask the question: What purpose for innovation might be suitable for studying complex phenomena as a case study nested within a mixed methods design? Our focus on communications during an unprecedented public health crisis represents a research problem requiring an innovative approach to understanding the many social and public health factors that interact and have yet to be studied. We were uncertain about how to begin, yet we were informed by the well-established importance of effective health communication at the onset of public health crises because people seek credible sources of information to understand health risks and ways to cope with them (Austin et al., 2021). Specific to the COVID-19 global pandemic, we recognized a vital component of the early public health response involved the use of regular publicly accessible communications led by regional, national, and international health authorities and government bodies (e.g., Gardner et al., 2021; Wang et al., 2020). Over time, emerging evidence pointed to the benefit of trustworthy sources of information in promoting COVID-19 prevention behaviors and improving vaccine uptake (e.g., Latkin et al., 2020; Malecki et al., 2021). The growing prevalence of the infodemic, where false information and non-rigorous recommendations were spreading through social media, intensified the need for the credibility of data and the trustworthiness of messaging (Mheidly & Fares, 2020).

While we now recognize the usefulness of CS-MM designs as suitable for studying the COVID-19 pandemic era (Cook & Kamalodeen, 2023), it took time to articulate the specific onset study purpose. In Table 2, we demonstrate how our purpose for integration statements shifted in focus from examining how to build credibility and trust through public health briefings during the onset study to focusing on how they were maintained in the extended timeline study. A similar shift, which will be discussed as part of case boundaries, can be seen in the focus of our guiding onset CS-MM research questions on key periods of fluctuation to waves in the study extended timeline study. Shifts in purposes for integration and clarification of rationales for selecting the case or multiple cases are to be expected in CS-MM research that studies complex phenomena.

Table 2.

Shifts Across the Purposes for Integration and Research Questions of the Two Onset and Extended Timeline Studies.

Case Study-Mixed Methods (CS-MM) Statements	The Onset Study (Poth et al., 2021)	The Current Extended Timeline Study
Purpose for integration	Examine how public health briefings built the necessary credibility and trust for effective public health communications during the first four months of rapidly changing onset conditions of the COVID-19 pandemic in Alberta.	Examine the extent to which and how credibility and trust for effective public health communications were maintained across 21 months of rapidly changing conditions of the COVID-19 pandemic in Alberta.
CS-MM research questions	How do the changes in public health messaging help us identify the key periods of fluctuation in response to the onset of the COVID-19 pandemic in Alberta, Canada?	How does examining the interdependencies among public health communications, provincial case statistics, and media coverage of the province’s efforts to mitigate the virus effects help us understand the communication shifts within each wave of the COVID-19 pandemic in Alberta, Canada?
CS-MM research questions	What novel insights can a cross-analysis of integrated findings of six key periods of fluctuation reveal about building credibility and trust through public health briefings during the onset of the COVID-19 pandemic in Alberta, Canada?	What novel insights can a cross-wave analysis of integrated findings reveal about the extent to which and how credibility and trust for effective public health communications were maintained across 21 months of rapidly changing conditions of COVID-19 pandemic in Alberta?

Case Boundaries for Integration

We consider: What boundaries might be suitable for what is currently known about the nested systems of the complex phenomena? During the onset study, we recognized the nested systems of our case as the province of Alberta within the country of Canada. In so doing our case boundaries became focused on the Alberta population, representing approximately 11% of Canada’s total population, with a smaller than average proportion of residents over age 65 (13% compared with 17.5% nationally; Statistics Canada, 2019) and the provincial health system overseen by the Government of Alberta (Ministry of Health) with a Chief Medical Officer of Health (CMOH) serving as the primary spokesperson. Since 1962, all essential basic health care needs have been delivered through the ten provincial and three territorial systems, which are nested within Canada’s publicly funded health care system and governed by the Canada Health Act adopted in 1984 (Statistics Canada, 2020). While each province holds jurisdiction for public health communications, the federal and provincial public health structures create unique opportunities for coordination; the Public Health Agency of Canada was established in 2004 to provide oversight and communications at the national level and is led by the Chief Public Health Officer of Canada (2020).

How we went about generating insights through a cross-analysis approach changed in response to the arising case conditions and emerging understandings of boundaries. In the onset study, we used text mining to identify six key fluctuations in sentiment messaging and word counts and describe how trust was built in public health communications during the first four months (for full description, see Poth et al., 2021). Then, we provided evidence of attending to the emergence, interdependence, and adaptation of topic areas and message contents related to key areas of effective public health communications and risk assessments. In comparison, our unit of analysis shifted from key fluctuations to waves in the current extended timeline study. We defined the wave duration, as represented in Figure 2, by looking at case statistics using downloaded datasets shared by the Government of Alberta via its interactive COVID-19 data app (Government of Alberta, 2021) to identify peaks and areas of stability and confirmed our date intervals by looking for alignment with news reports of the provincial response. As previously discussed, our research questions (see Table 2) demonstrate the shift from using key fluctuations to examine how public health briefings build credibility and trust in the onset study to the focus on maintenance during the subsequent three waves. The assumption that understandings of suitable boundaries emerge is to be expected in CS-MM research that studies complex phenomena. The need for differing expertise to emerge and for teams to form over time in response is to be expected in CS-MM research that studies complex phenomena.

Figure 2.

Wave definitions for the current expanded case study-mixed methods Study of the COVID-19 pandemic in Alberta, Canada based on case count data. Note. The Y-axis represents case counts and the X-axis the date. Case count data from the Government of Alberta via its interactive COVID-19 data app (Government of Alberta, 2021).

Case Expertise for Integration

We look to the differing iterations of our interdisciplinary CS-MM research team that leverage our expertise to generate novel insights by integrating open datasets. Open datasets, freely available for download from the Internet, are recognized for their ease of timely access to information germane to the study of the COVID-19 pandemic (Alamo et al., 2020; Almeida, 2021). In Table 3, we summarize the expertise and backgrounds of each team member and their contributions across the two studies. Of note is both the depth of expertise and the uniqueness of expertise across each of the team members, which means neither of the studies could have been completed by any of the members alone. While the team membership across both studies was four, each study blended expertise in new ways in response to changing expertise needs; Aquilina contributed to the qualitative analysis in the onset study, and Wongvorachan practiced his data mining and mixed methods integration skills in the expanded study. Considering the ongoing scarcity of discussions regarding the specialized expertise needed for mixed method research, it came as no surprise to us that Guetterman and Fetters’ (2018) review and discussion of mixed methods case studies and their design recommendations did not address expertise (see Table 1).

Table 3.

Team Member Contributions to Case Expertise for Integration.

Team Members & Background	Team Member Contributions
Team Members & Background	The Onset Study	The Current Extended Timeframe Study
Poth: Extensive expertise and experiences in • Application of complexity science to mixed methods research • Qualitative case research	Led the overall CS-MM study conceptualization, implementation, and dissemination	Led the overall CS-MM study conceptualization, implementation, and dissemination
	Organized team logistics, communications, and meetings	Organized team logistics, communications, and meetings
Bulut: Extensive expertise and experiences in • Quantitative and qualitative data mining and analysis • Data visualizations	Led the text mining planning, procedures, visualizations, and reporting	Contributed to validating the findings of text mining analyses and the accuracy of data visualizations to the CS-MM study
Otto: Extensive experience and experiences in • Emergency outbreak management and public health research and practice	Led the interpretation of the integrated findings and meta-inference discussion	Contextualization of the learnings from the CS-MM of this CAS for public health communication
		Positioned findings of the CS-MM in a manner to resonate with public health professionals
Aquilina: Building expertise and emerging experiences in: • Qualitative and quantitative data analysis and reporting	Contributed to qualitative data analysis and development of case description	Did not participate
Wongvorachan: Building expertise and emerging experiences in: • Data mining • Mixed methods	Did not participate	Led the text mining and data visualization process Contributed to the integration of results

Case Procedures for Integration

We explore how our shift to focus during the current extended timeline study on a cross-analysis of waves created the conditions for our use of the metaphor of braided ropes to emerge. We began, as depicted in Figure 3, with an analysis of within-wave changes in message sentiment and topics across public communications using natural language processing techniques of sentiment analysis, word clouds, and topic modeling (Bengfort et al., 2018). We used descriptive statistics to generate frequencies about the use of the two formats by the CMOH to communicate that emerged over time (i.e., Live briefings and Twitter) and explored how public health communications shifted across waves with provincial case statistics (Government of Alberta, 2021) and patient-level data was aggregated by date to calculate the total number of daily confirmed cases, deaths, hospitalizations, and intensive care admissions. To study local media coverage of key changes in public health measures and public perceptions, we created a timeline from the online news searches of provincial news sources. Our within-wave integration procedures were guided by a qualitative dominant crossover mixed analysis strategy (Hitchcock & Onwuegbuzie, 2020). The braided metaphor was essential for generating our case meta-inferences derived from our cross-analysis of four waves. Shifts in case procedures and approaches to integration are to be expected in CS-MM research that studies complex phenomena.

Figure 3.

Current expanded timeline study within-wave integration procedures and use of braided ropes metaphor. Note. CMOH = Chief Medical Officer of Health.

Case Evidence of Integration

Recent practice discussions involving researchers from around the globe (e.g., Fàbregues et al., 2021; Guetterman et al., 2022; Makabe et al., 2022) has informed our thinking about quality criteria and integration evidence. As a result we think more broadly about the types of integration evidence associated with CS-MM designs. None of our procedures reflect established strategies to generate meta-inferences. In the onset-focused study, we derived our case meta-inferences by attending to three key concepts of complex adaptive systems: emergence, interdependence, and adaptation across fluctuations within the first wave. Our detailed descriptions of emerging data trends to inform risk assessments, demonstrating care and openness in describing a range of concerns and accessible supports, and being specific about the actions of individuals affecting others was a reasonable start to providing evidence of validity for our onset CS-MM study meta-inferences (Poth et al., 2021). The current expanded timeline study provided the opportunity for generating further meta-inferences reflective of the contemporary descriptions of and expectations for effective public health communications that are more realistic of the rapidly evolving and unpredictable conditions in which a global pandemic unfolds over time across waves. Specifically, our descriptions of defining the wave durations were detailed, as were our accounts of the processes involved in collecting and analyzing evidence for the integration of each case. Among the key insights was identifying an interdependency among various information sources. These sources collectively influence each other in the complex landscape surrounding the COVID-19 pandemic, as depicted in Figure 4. The three information sources continue to exert influence and serve as integral evidence for case integration, provide insights into the characteristics of the cases, and inform the development of meta-inferences.

Figure 4.

Interdependencies among the information sources informing the study of adjustments in public health pandemic communications. Note. CMOH = Chief Medical Officer of Health. Source: Adapted from Figure 1 (Poth et al., 2021).

Our generation of holistic and timely cross-wave case meta-inferences would have been inaccessible by either qualitative or quantitative data sets alone, and the integrated case descriptions of individual pandemic waves benefited from the use of text mining to efficiently manage the consistent analysis of large volumes of freely accessible qualitative and quantitative datasets. The pandemic provided unprecedented access to open datasets that could profoundly impact public health responses to crises in the future and required new ways of thinking about quality criteria and evidence of integration. Our understanding of appropriate evidence of integration to emerge is to be expected in CS-MM research that studies complex phenomena.

Contributions to Mixed Methods Research

This article contributes much-needed practical guidance for CS-MM researchers navigating and documenting the study of complex phenomena through an illustrative study and discussion of six integration-focused adaptive design practice areas. To that end, we heed the calls by Guetterman and Fetters (2018) to make explicit the requisite integration in our CS-MM designs and offer novel opportunities for visualizations to juxtapose information (Tables 1, 2, and 3) and data (Figure 2), and display emerging understandings (Figures 1, 4) and integration procedures (Figure 3).

Together, our discussions of adaptive CS-MM research practice areas and the use of visualizations benefit CS-MM researchers’ study of complex phenomena by attending in new ways to the three key characteristics of CAS: emergence, interdependency, and adaptation. By identifying the case conditions for integration as involving the study of a complex phenomenon and CS-MM as a suitable design, we provide methodological guidance for a design that realistically represents and accounts for many of the multiple interacting influences within the rapidly changeable research conditions we encountered. By framing the case purpose of CS-MM for integration as emergent and not dependent on the problem being well understood, we offer researchers who study complex phenomena freedom from guiding literature and methodology. By describing what is initially known about the interrelated and nested systems and influences of the CS-MM boundaries for integration, we can promote the assimilation of emerging understandings in further boundary considerations. Conceptualizing evolving public health communications as CASs offers a lens for studying complex public health phenomena using a holistic focus on waves within a CS-MM design that departs from examining their parts in isolation to allow attending to system interdependencies and dynamic influences on and by one another. By forming the case expertise for integration in responsive, integrative, and emergent ways, we make the leveraging of existing team expertise possible in new ways. In turn, this helps foster innovations in researcher combinations and methodologies involved in CS-MM designs. By anticipating case procedures for integration as agile and implementation not required as initially planned, it can stimulate innovations in CS-MM designs such as the use of open datasets. Normalizing the need for procedural adaptations helps us reconsider stability assumptions of the research conditions across time. Assessing the quality of case insights on practical merit and not only on established expectations of methodological rigor can inspire innovations in CS-MM research evidence when assessing the validity of outcomes.

Strengths, Limitations, and Future Directions

Open datasets, freely available for download from the Internet, are recognized for their ease of timely access to valuable yet limited information for the current study of the evolving public health communications during the COVID-19 pandemic in Alberta, Canada. Our study findings should be considered in light of our geographical focus on the COVID-19 pandemic in Alberta during the specified timeframes and by the open data sources selected for inclusion. The public health communications in Alberta are likely influencing and being influenced by communication efforts in other provinces within Canada and may be vastly different from other countries. Further research would be necessary to test the veracity of these open data sources in contexts beyond the current study and to seek open data sources beyond what was included in the current study.

Footnotes

Author Contributions

We dedicate this paper to Mike Fetters in recognition of his numerous contributions as a scholar, clinician, and friend. Mike was indeed a giant in the field of mixed methods research who was generous with his time and energy, and we are all better for it. His legacy lives on in the work he completed and the people he inspired. Cheryl speaks from experience, it was his gentle nudge and words of encouragement at dinner during the 2016 MMIRA global conference in Durham, UK that helped her see through to publication her book that became Innovations in Mixed Methods Research (Poth, 2018).

Declaration of Conflicting Interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Poth serve as an associate editor for JMMR.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: We gratefully acknowledge funding for the study from the University of Alberta’s Endowment Fund for the Future - Support for the Advancement of Scholarship Program.

ORCID iDs

Cheryl N. Poth

Tarid Wongvorachan

Okan Bulut

Simon J. G. Otto

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Adaptive Case Study-Mixed Methods Design Practices for Researchers Studying Complex Phenomena

Abstract

Keywords

Leveraging Case Study-Mixed Methods Design Recommendations for Studies of Complex Adaptive Systems

Case Conditions for Integration

Case Purpose for Integration

Case Boundaries for Integration

Case Expertise for Integration

Case Procedures for Integration

Case Evidence of Integration

Contributions to Mixed Methods Research

Strengths, Limitations, and Future Directions

Footnotes

Author Contributions

Declaration of Conflicting Interests

Funding

ORCID iDs

References