A Comprehensive Guide for PhD Researchers: Real-World Applications of Mixed Methods Research

A Comprehensive Guide for PhD Researchers: Real-World Applications of Mixed Methods Research

Introduction

In the current research environment, complex social, behavioural, and scientific phenomena typically require more than a single methodological strategy. Mixed Methods Research (MMR), the use of qualitative and quantitative methodology together, represents a robust approach to engage in thorough insights beyond either approach on its own.

For PhD researchers, the capacity to develop MMR is a methodological confidence and also a strategy that adds legitimacy, rigour and depth to their work, as well as impact. MMR methodology merges the statistical certainty of quantitative analysis with the descriptive richness of qualitative inquiry to provide nuanced and holistic perspectives on complex questions that affect the social, healthcare, education, business, and scientific domains.

This guide considers real-world applications of mixed methods research examples, informed by scholarly examples, and practical considerations that demonstrate how PhD researchers can apply MMR to develop rigorous research studies that reinforce their findings and contribute meaningfully to both academic and professional practice.

The Role of Mixed Methods Research in Case Studies

Mixed methods inquiry is critical in case study design, which must represent measurable outcomes with depth of context. Onghena, Maes, and Heyvaert (2019) note that having both qualitative narratives and quantitative information increases the potential to understand complex realities that cannot be seen through a single lens. This mixed-methods inquiry creates balance and provides generalizable breadth and in-depth understanding.

In practice, mixed methods inquiry encourages researchers to explore phenomena from multiple perspectives, which advances knowledge of the “story behind the numbers.” Mixed methods inquiry also supports triangulation, which can support the credibility and dependability of data. For PhD researchers, that may mean designing a stronger, more defensible research approach to complex stated research questions.

Example: Single Case Study in Healthcare

MMR in healthcare research is well exemplified by Onghena et al. (2019). Suppose you are examining a healthcare study of an entirely new treatment protocol for a chronic condition. The quantitative data you may collect, such as survival rates, symptom scores, and biomarkers, may yield measurable indications of treatment effectiveness. However, using these statistics in isolation fails to showcase the humanity behind those numbers.

Researchers can also collect qualitative data through patient interviews, focus groups, or diaries, and in doing so, they may begin to draw out how patients experience treatment effectiveness, respond to side effects, and experience other emotional or psychological impacts throughout the process. This synthesis leads to a patient-centred understanding of healthcare interventions that can help inform practice and policy decisions within healthcare. This is one example of mixed methods research paper approaches that PhD students can learn from.

Tip for researchers

PhD researchers in medical and health sciences may find that taking a dual approach lends itself to developing evidence-informed, empathetic solutions that can positively contribute toward clinical challenges in the real world.

Table 1 Mixed Methods Research study

Component

Details

 

 

 

Qualitative Methods

Techniques: Interviews, Focus Groups, Observation

Purpose: Explore experiences, perceptions, and context; Understand “why” and “how” phenomena occur

Example Applications: Patient interviews (Healthcare), Teacher insights (Education), Employee narratives (Organizations)

 

 

 

Quantitative Methods

Techniques: Experiments, Surveys, Statistical Analysis

Purpose: Measure variables; Test hypotheses; Identify patterns and correlations

Example Applications: Survival rates (Healthcare), Standardized test scores (Education), Employee satisfaction surveys (Organizations)

Integration

Combines strengths of both approaches; Provides a holistic understanding of complex research problems

Mixed Methods in Movement Sciences

Mixed methods have also been embraced within movement sciences such as sports, physical education, and dance. For example, Camerino, Castañer, and Anguera (2012) show how the integration of qualitative observational approaches and quantitative measurement methods can deepen understanding of physical performance and human movement.

Qualitative methods, such as structured interviews, field notes, or video-based observations, allow researchers to explore behavioural patterns, motivation, and interpersonal dynamics, while quantitative tools provide objective data such as heart rate, velocity, or reaction time. The synergy between these approaches offers a deeper look into both the mechanics and psychology of performance.

Example: Sports Performance Research

In the area of sports performance, a PhD researcher could also explore how the intensity of training affects athlete wellness. For instance, a quantitative measure could informally assess the endurance, agility, or speed of the participant using wearables or controlled settings. Qualitative inquiry could support the researcher by interviewing athletes and examining components of emotional fatigue, levels of confidence and motivation, and general coping and coping skills.

Tip for researchers

Taking all of this together, the researcher has a much better understanding of the performance dynamic, as they can demonstrate how the training interacts and affects not only physical capacities, but mental and emotional capacities, and how they interact with performance. This multi-faceted type of understanding supports evidence-informed recommendations for development an athlete’s physical and psychological capacities.

Combining Stories and Numbers in Public Health

In the field of public health, it is critically important to have an incorporate of statistics and human experience to address health issues in a community. According to Pluye and Hong (2014), mixed methods allow researchers to link the strength of numbers with the substance of human experience. For example, quantitative findings might highlight trends, while qualitative findings help explain why those trends exist.

Although having an integrated approach is impactful in numerous fields of research, it is increasingly valuable within health promotion, epidemiology, and community-based research, whereby sociocultural and behavioural factors are determinants of health outcomes.

Example: Public Health Research on Vaccination Rates

Picture a research project that looks at vaccination uptake in a particular community. Surveys generating quantitative data may show a troubling decline in vaccination rates but we do not know why without qualitative inquiry. A researcher might conduct interviews or focus groups and learn that barriers like misinformation, distrust in the healthcare system, or deep-rooted cultural beliefs exist.

Tip for researchers

Mixed-methods design provides a layered understanding by integrating evidence with thick, contextual interpretation. This is particularly beneficial for a PhD researcher seeking to address public health, as it supports their ability to identify solutions that would address the situation holistically through culturally relevant interventions.

Mixed Methods in Case Study Designs

Envision a study investigating vaccination uptake in a specific community. The surveys that generate quantitative data may be showing a concerning decrease in vaccination rates, but we do not know why to conduct a qualitative inquiry. The researcher may conduct qualitative interviews or focus groups, which help to describe barriers to vaccination as misinformation, trust in the healthcare system, or deeply held cultural beliefs, to name a few. 

Mixed-methods design provides a rich understanding when we combine evidence with thick, contextual interpretation. This is especially important for a PhD researcher in public health, because to address any public health priority holistically, you must be able to identify culturally relevant interventions to address the problem.

Example: Organisational Behaviour Research

In organisational research, taking a mixed methods approach offers strong potential for studying employee experiences, leadership, and workplace culture. For example, when examining employee engagement, a researcher might begin with quantitative surveys assessing job satisfaction and productivity, then follow up with qualitative interviews or focus groups to explore the underlying drivers of those metrics—such as leadership communication, group dynamics, teamwork, and individual values.

Organisational phenomena are multi-level, complicated, and continuously changing (Chan, 1998; Humphrey & LeBreton, 2019; Kozlowski & Klein, 2000). Despite being widely recognised across management and organisation studies (Hitt et al., 2007; Mathieu & Chen, 2011; Molloy et al, 2011), research continues to seperate perspectives of macro-, meso-, and micro-level framing under the assumption that theory and analysis can exist comfortably within an isolated level (Hernaus et al., 2020). Consider organisational culture, which has been defined as “a pattern of shared basic assumptions… taught to new members as the correct way to perceive, think, and feel” (Schein, 2010, p. 18). Often conceived as a macro-level construct, culture develops from the enactments from a team or department (meso), but is frequently conceptualised, measured, and examined through individual perceptions (micro), creating a misalignment between theory, measurement, and analysis frame (Molina-Azorín et al., 2020).

The multilevel nature of workplace phenomena has been recognised for some time in disciplines such as organisational psychology, behaviour, and human resource management with the development of multilevel statistical analysis of the workplace (Aguinis et al., 2011; Aguinis & Molina-Azorín, 2015; Preacher et al., 2010). Similarly, macro disciplines such as strategic management and organisation theory have also adopted multilevel designs. Yet many areas in the organisational sciences (despite recent methodological and theoretical advances in disciplines such as psychology, behaviour management, and organisation science review, e.g., Humphrey & LeBreton, 2019; O’Connell et al., 2022 related to multilevel designs) still does not contain rigorous quantitative, qualitative, or mixed methods research that recognises the complexity and interdependent nature of workplace life.

To facilitate this, analytic advances from health services research can be paired with mixed methods, or qualitative methods, as in conducting observations at different levels of an organisation (Hall et al., 2018). This is important because it could provide additional insights into how interventions operate and develop within organisational contexts. Aguinis and Molina-Azorín (2015) note that there is significant promise for mixed-methods multilevel research to enhance the integration of theory and empirical evidence into multilevel designs. Mixed-methods designs are models that integrate both qualitative and quantitative approaches to develop rich insights into the complex nature of organisational phenomena (Headley & Plano Clark, 2020).

Tip for researchers

This mixed-method design can support PhD researchers in offering evidence-based contributions to decision-makers/practitioners that inform management practices, motivation, and support a better working environment. The use of mixed methods (qualitative and quantitative) can also address some of the potential divides in management; for example, between research and practice, bridging data to decision, and rendering research as relevant as it is academically rigorous.

The Future of Mixed Methods Research

The future of mixed methods research papers is characterised by both technological advances and collaborative work across disciplinary fronts, with a renewed emphasis on data integration and visualisation techniques.  Schoonenboom and Johnson (2017) identified the next frontier to be the production of designs that effectively integrate qualitative and quantitative data, using advanced analytics, AI coding, and visual mapping tools.

For early career researchers, this shift offers fresh possibilities for undertaking possibly more agile, scalable, interactive studies, utilising multiple data forms and sources. The flexibility of MMR would support and predictably enable it to endure in addressing our complex social problems – whether in the domain of digital education, environmental sustainability, or social equity.

Example: Advancing Educational Research

In educational research, creating a sample of mixed methods research thesis can involve combining numerical data—such as test scores, attendance rates, or assessment outcomes—with qualitative insights from teacher and student interviews offers a multidimensional perspective on learning (Schoonenboom and Johnson et al.,2017).

Tip for researchers

This integration helps researchers understand not only what students achieve but also how and why certain pedagogical strategies succeed or fail. For PhD researchers, this dual analysis supports evidence-informed educational reform, driving improvements in curriculum design, teaching methodology, and student support systems.

Conclusion

Mixed Methods Research study provides a powerful framework for PhD researchers seeking to explore the depth and breadth of complex academic questions. By harmonising quantitative precision with qualitative depth, MMR facilitates a level of insight that neither approach can achieve independently.

Evidence exists to support that combining these two approaches allows researchers to develop original, based on evidence, and context-based knowledge, as illustrated in Onghena et al. (2019), Camerino et al. (2012), Pluye & Hong (2014), Guetterman & Fetters (2018), and Schoonenboom & Johnson (2017).

PhD students beginning the research process consume a lot of time and energy starting their programs. Using mixed methods can provide students with a much clearer path to becoming excellent scholars and contributing to their field; it turns data into discovery, insights into innovation, and research into concrete, real-world change.

References

  1. Aramo-Immonen, H. (2011). Mixed methods research design. In M. D. Lytras, P. O. de Pablos, A. Ziderman, A. Roulstone, H. Maurer, & J. B. Imber (Eds.), Proceedings of the World Summit on Knowledge Society (pp. 32–43). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-35879-1_4
  2. Camerino, O., Castañer, M., & Anguera, M. T. (2012). Mixed methods research in the movement sciences: Case studies in sport, physical education, and dance. Routledge.
  3. Guetterman, T. C., & Fetters, M. D. (2018). Two methodological approaches to the integration of mixed methods and case study designs: A systematic review. American Behavioural Scientist, 62(7), 900–918. https://doi.org/10.1177/0002764218772641
  4. Onghena, P., Maes, B., & Heyvaert, M. (2019). Mixed methods single case research: State of the art and future directions. Journal of Mixed Methods Research, 13(4), 461–480. https://doi.org/10.1177/1558689818773715
  5. Pluye, P., & Hong, Q. N. (2014). Combining the power of stories and the power of numbers: Mixed methods research and mixed studies reviews. Annual Review of Public Health, 35(1), 29–45. https://doi.org/10.1146/annurev-publhealth-032013-182440
  6. Schoonenboom, J., & Johnson, R. B. (2017). How to construct a mixed methods research design. Kölner Zeitschrift für Soziologie und Sozialpsychologie, 69(S2), 107–131. https://doi.org/10.1007/s11577-017-0454-1